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1. Challenges of Francisella classification exemplified by an atypical clinical isolate

Author: Matz, LM, Kamdar, KY, Holder, ME, Metcalf, GA, Weissenberger, GM, Meng, Q, Vee, V, Han, Y, Muzny, DM, Gibbs, RA, Johnson, CL, Revell, PA, and Petrosino, JF
Published: 2018
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2. Integrated Model of De Novo and Inherited Genetic Variants Yields Greater Power to Identify Risk Genes

Author: State, Matthew, Sanders, Stephan, He, X, Sanders, SJ, Liu, L, De, S, Lim, ET, Sutcliffe, JS, Schellenberg, GD, Gibbs, RA, Daly, MJ, and Buxbaum, JD
Abstract: De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based
Published: 2013

3. Integrated genomic analyses of ovarian carcinoma

Author: Bell, D, Berchuck, A, Birrer, M, Chien, J, Cramer, DW, Dao, F, Dhir, R, DiSaia, P, Gabra, H, Glenn, P, Godwin, AK, Gross, J, Hartmann, L, Huang, M, Huntsman, DG, Iacocca, M, Imielinski, M, Kalloger, S, Karlan, BY, Levine, DA, Mills, GB, Morrison, C, Mutch, D, Olvera, N, Orsulic, S, Park, K, Petrelli, N, Rabeno, B, Rader, JS, Sikic, BI, Smith-McCune, K, Sood, AK, Bowtell, D, Penny, R, Testa, JR, Chang, K, Creighton, CJ, Dinh, HH, Drummond, JA, Fowler, G, Gunaratne, P, Hawes, AC, Kovar, CL, Lewis, LR, Morgan, MB, Newsham, IF, Santibanez, J, Reid, JG, Trevino, LR, Wu, Y-Q, Wang, M, Muzny, DM, Wheeler, DA, Gibbs, RA, Getz, G, Lawrence, MS, Cibulskis, K, Sivachenko, AY, Sougnez, C, Voet, D, Wilkinson, J, Bloom, T, Ardlie, K, Fennell, T, Baldwin, J, Nichol, R, Fisher, S, Gabriel, S, Lander, ES, Ding, L, Fulton, RS, Koboldt, DC, McLellan, MD, Wylie, T, Walker, J, O’Laughlin, M, Dooling, DJ, Fulton, L, Abbott, R, Dees, ND, Zhang, Q, Kandoth, C, Wendl, M, Schierding, W, Shen, D, Harris, CC, Schmidt, H, Kalicki, J, Delehaunty, KD, Fronick, CC, Demeter, R, Cook, L, Wallis, JW, Lin, L, Magrini, VJ, Hodges, JS, Eldred, JM, Smith, SM, Pohl, CS, and Vandin, F
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Genetics, Oncology and Carcinogenesis, Biotechnology, Rare Diseases, Human Genome, Ovarian Cancer, Cancer, Aged, Carcinoma, DNA Methylation, Female, Gene Dosage, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Genomics, Humans, MicroRNAs, Middle Aged, Mutation, Ovarian Neoplasms, RNA, Messenger, Cancer Genome Atlas Research Network, General Science & Technology
Abstract: A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying therapies that will improve patients' lives. The Cancer Genome Atlas project has analysed messenger RNA expression, microRNA expression, promoter methylation and DNA copy number in 489 high-grade serous ovarian adenocarcinomas and the DNA sequences of exons from coding genes in 316 of these tumours. Here we report that high-grade serous ovarian cancer is characterized by TP53 mutations in almost all tumours (96%); low prevalence but statistically recurrent somatic mutations in nine further genes including NF1, BRCA1, BRCA2, RB1 and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes. Analyses delineated four ovarian cancer transcriptional subtypes, three microRNA subtypes, four promoter methylation subtypes and a transcriptional signature associated with survival duration, and shed new light on the impact that tumours with BRCA1/2 (BRCA1 or BRCA2) and CCNE1 aberrations have on survival. Pathway analyses suggested that homologous recombination is defective in about half of the tumours analysed, and that NOTCH and FOXM1 signalling are involved in serous ovarian cancer pathophysiology.
Published: 2011

4. Initial sequencing and analysis of the human genome

Author: Lander, ES, Linton, LM, Birren, B, Nusbaum, C, Zody, MC, Baldwin, J, Devon, K, Dewar, K, Doyle, M, FitzHugh, W, Funke, R, Gage, D, Harris, K, Heaford, A, Howland, J, Kann, L, Lehoczky, J, LeVine, R, McEwan, P, McKernan, K, Meldrim, J, Mesirov, JP, Miranda, C, Morris, W, Naylor, J, Raymond, C, Rosetti, M, Santos, R, Sheridan, A, Sougnez, C, Stange-Thomann, N, Stojanovic, N, Subramanian, A, Wyman, D, Rogers, J, Sulston, J, Ainscough, R, Beck, S, Bentley, D, Burton, J, Clee, C, Carter, N, Coulson, A, Deadman, R, Deloukas, P, Dunham, A, Dunham, I, Durbin, R, French, L, Grafham, D, Gregory, S, Hubbard, T, Humphray, S, Hunt, A, Jones, M, Lloyd, C, McMurray, A, Matthews, L, Mercer, S, Milne, S, Mullikin, JC, Mungall, A, Plumb, R, Ross, M, Shownkeen, R, Sims, S, Waterston, RH, Wilson, RK, Hillier, LW, McPherson, JD, Marra, MA, Mardis, ER, Fulton, LA, Chinwalla, AT, Pepin, KH, Gish, WR, Chissoe, SL, Wendl, MC, Delehaunty, KD, Miner, TL, Delehaunty, A, Kramer, JB, Cook, LL, Fulton, RS, Johnson, DL, Minx, PJ, Clifton, SW, Hawkins, T, Branscomb, E, Predki, P, Richardson, P, Wenning, S, Slezak, T, Doggett, N, Cheng, JF, Olsen, A, Lucas, S, Elkin, C, Uberbacher, E, Frazier, M, Gibbs, RA, Muzny, DM, Scherer, SE, Bouck, JB, Sodergren, EJ, Worley, KC, Rives, CM, Gorrell, JH, Metzker, ML, Naylor, SL, Kucherlapati, RS, Nelson, DL, Weinstock, GM, Sakaki, Y, Fujiyama, A, Hattori, M, Yada, T, Toyoda, A, Itoh, T, Kawagoe, C, Watanabe, H, Totoki, Y, Taylor, T, Weissenbach, J, Heilig, R, Saurin, W, Artiguenave, F, Brottier, P, Bruls, T, Pelletier, E, Robert, C, Wincker, P, Smith, DR, Doucette-Stamm, L, Rubenfield, M, Weinstock, K, Lee, HM, Dubois, J, Rosenthal, A, Platzer, M, Nyakatura, G, Taudien, S, Rump, A, Yang, H, Yu, J, Wang, J, Huang, G, Gu, J, Hood, L, Rowen, L, Madan, A, Qin, S, Davis, RW, Federspiel, NA, Abola, AP, Proctor, MJ, Myers, RM, Schmutz, J, Dickson, M, Grimwood, J, Cox, DR, Olson, MV, Kaul, R, Shimizu, N, Kawasaki, K, Minoshima, S, Evans, GA, Athanasiou, M, Schultz, R, Roe, BA, Chen, F, Pan, H, Ramser, J, Lehrach, H, Reinhardt, R, McCombie, WR, de la Bastide, M, Dedhia, N, Blöcker, H, Hornischer, K, Nordsiek, G, Agarwala, R, Aravind, L, Bailey, JA, Bateman, A, Batzoglou, S, Birney, E, Bork, P, Brown, DG, Burge, CB, Cerutti, L, Chen, HC, Church, D, Clamp, M, Copley, RR, Doerks, T, Eddy, SR, Eichler, EE, Furey, TS, Galagan, J, Gilbert, JG, Harmon, C, Hayashizaki, Y, Haussler, D, Hermjakob, H, Hokamp, K, Jang, W, Johnson, LS, Jones, TA, Kasif, S, Kaspryzk, A, Kennedy, S, Kent, WJ, Kitts, P, Koonin, EV, Korf, I, Kulp, D, Lancet, D, Lowe, TM, McLysaght, A, Mikkelsen, T, Moran, JV, Mulder, N, Pollara, VJ, Ponting, CP, Schuler, G, Schultz, J, Slater, G, Smit, AF, Stupka, E, Szustakowski, J, Thierry-Mieg, D, Thierry-Mieg, J, Wagner, L, Wallis, J, Wheeler, R, Williams, A, Wolf, YI, Wolfe, KH, Yang, SP, Yeh, RF, Collins, F, Guyer, MS, Peterson, J, Felsenfeld, A, Wetterstrand, KA, Patrinos, A, Morgan, MJ, de Jong, P, Catanese, JJ, Osoegawa, K, Shizuya, H, Choi, S, Chen, YJ, and Szustakowki, J
Subjects: Genetics, Cancer genome sequencing, Chimpanzee genome project, Multidisciplinary, Cancer Genome Project, Gene density, DNA sequencing theory, Hybrid genome assembly, Computational biology, Biology, Genome, Personal genomics
Abstract: The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.
Published: 2016

5. A second generation human haplotype map of over 3.1 million SNPs

Author: Frazer, KA, Ballinger, DG, Cox, DR, Hinds, DA, Stuve, LL, Gibbs, RA, Belmont, JW, Boudreau, A, Hardenbol, P, Leal, SM, Pasternak, S, Wheeler, DA, Willis, TD, Yu, F, Yang, H, Zeng, C, Gao, Y, Hu, H, Hu, W, Li, C, Lin, W, Liu, S, Pan, H, Tang, X, Wang, J, Wang, W, Yu, J, Zhang, B, Zhang, Q, Zhao, H, Zhou, J, Gabriel, SB, Barry, R, Blumenstiel, B, Camargo, A, Defelice, M, Faggart, M, Goyette, M, Gupta, S, Moore, J, Nguyen, H, Onofrio, RC, Parkin, M, Roy, J, Stahl, E, Winchester, E, Ziaugra, L, Altshuler, D, Shen, Y, Yao, Z, Huang, W, Chu, X, He, Y, Jin, L, Liu, Y, Sun, W, Wang, H, Wang, Y, Xiong, X, Xu, L, Waye, MM, Tsui, SK, Xue, H, Wong, JT, Galver, LM, Fan, JB, Gunderson, K, Murray, SS, Oliphant, AR, Chee, MS, Montpetit, A, Chagnon, F, Ferretti, V, Leboeuf, M, Olivier, JF, Phillips, MS, Roumy, S, Sallée, C, Verner, A, Hudson, TJ, Kwok, PY, Cai, D, Koboldt, DC, Miller, RD, Pawlikowska, L, Taillon-Miller, P, Xiao, M, Tsui, LC, Mak, W, Song, YQ, Tam, PK, Nakamura, Y, Kawaguchi, T, Kitamoto, T, Morizono, T, Nagashima, A, Ohnishi, Y, Sekine, A, Tanaka, T, Tsunoda, T, Deloukas, P, Bird, CP, Delgado, M, Dermitzakis, ET, Gwilliam, R, Hunt, S, Morrison, J, Powell, D, Stranger, BE, Whittaker, P, Bentley, DR, Daly, MJ, de Bakker, PI, Barrett, J, Chretien, YR, Maller, J, McCarroll, S, Patterson, N, Pe'er, I, Price, A, Purcell, S, Richter, DJ, Sabeti, P, Saxena, R, Schaffner, SF, Sham, PC, Varilly, P, Stein, LD, Krishnan, L, Smith, AV, Tello-Ruiz, MK, Thorisson, GA, Chakravarti, A, Chen, PE, Cutler, DJ, Kashuk, CS, Lin, S, Abecasis, GR, Guan, W, Li, Y, Munro, HM, Qin, ZS, Thomas, DJ, McVean, G, Auton, A, Bottolo, L, Cardin, N, Eyheramendy, S, Freeman, C, Marchini, J, Myers, S, Spencer, C, Stephens, M, Donnelly, P, Cardon, LR, Clarke, G, Evans, DM, Morris, AP, Weir, BS, Mullikin, JC, Sherry, ST, Feolo, M, Skol, A, Zhang, H, Matsuda, I, Fukushima, Y, Macer, DR, Suda, E, Rotimi, CN, Adebamowo, CA, Ajayi, I, Aniagwu, T, Marshall, PA, Nkwodimmah, C, Royal, CD, Leppert, MF, Dixon, M, Peiffer, A, Qiu, R, Kent, A, Kato, K, Niikawa, N, Adewole, IF, Knoppers, BM, Foster, MW, Clayton, EW, Watkin, J, Muzny, D, Nazareth, L, Sodergren, E, Weinstock, GM, Yakub, I, Birren, BW, Wilson, RK, Fulton, LL, Rogers, J, Burton, J, Carter, NP, Clee, CM, Griffiths, M, Jones, MC, McLay, K, Plumb, RW, Ross, MT, Sims, SK, Willey, DL, Chen, Z, Han, H, Kang, L, Godbout, M, Wallenburg, JC, L'Archevêque, P, Bellemare, G, Saeki, K, An, D, Fu, H, Li, Q, Wang, Z, Wang, R, Holden, AL, Brooks, LD, McEwen, JE, Guyer, MS, Wang, VO, Peterson, JL, Shi, M, Spiegel, J, Sung, LM, Zacharia, LF, Collins, FS, Kennedy, K, Jamieson, R, and Stewart, J
Subjects: Male, Recombination, Genetic, Genetics, Linkage disequilibrium, education.field_of_study, Multidisciplinary, Homozygote, Racial Groups, Haplotype, Population, Single-nucleotide polymorphism, Tag SNP, Biology, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Article, Haplotypes, Humans, Female, Selection, Genetic, International HapMap Project, education, Imputation (genetics), Genetic association
Abstract: We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r 2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r 2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations. ©2007 Nature Publishing Group., link_to_OA_fulltext
Published: 2016

6. Identification of Intellectual Disability Genes in Female Patients with a Skewed X-Inactivation Pattern

Author: Fieremans N, Van Esch H, Holvoet M, Van Goethem G, Devriendt K, Rosello M, Mayo S, Martinez F, Jhangiani S, Muzny DM, Gibbs RA, Lupski JR, Vermeesch JR, Marynen P, and Froyen G
Subjects: escape genes, skewing of X-inactivation, intellectual disability, exome sequencing
Abstract: Intellectual disability (ID) is a heterogeneous disorder with an unknown molecular etiology in many cases. Previously, X-linked ID (XLID) studies focused on males because of the hemizygous state of their X chromosome. Carrier females are generally unaffected because of the presence of a second normal allele, or inactivation of the mutant X chromosome in most of their cells (skewing). However, in female ID patients, we hypothesized that the presence of skewing of X-inactivation would be an indicator for an X chromosomal ID cause. We analyzed the X-inactivation patterns of 288 females with ID, and found that 22 (7.6%) had extreme skewing (>90%), which is significantly higher than observed in the general population (3.6%; P=0.029). Whole-exome sequencing of 19 females with extreme skewing revealed causal variants in six females in the XLID genes DDX3X, NHS, WDR45, MECP2, and SMC1A. Interestingly, variants in genes escaping X-inactivation presumably cause both XLID and skewing of X-inactivation in three of these patients. Moreover, variants likely accounting for skewing only were detected in MED12, HDAC8, and TAF9B. All tested candidate causative variants were de novo events. Hence, extreme skewing is a good indicator for the presence of X-linked variants in female patients.
Published: 2016

7. Human genomic regions with exceptionally high levels of population differentiation identified from 911 whole-genome sequences

Author: Colonna, V, Ayub, Q, Chen, Y, Pagani, L, Luisi, P, Pybus, M, Garrison, E, Xue, Y, Tyler-Smith, C, Abecasis, GR, Auton, A, Brooks, LD, Depristo, MA, Durbin, RM, Handsaker, RE, Kang, HM, Marth, GT, McVean, G, Altshuler, DM, Bentley, DR, Chakravarti, A, Clark, AG, Donnelly, P, Eichler, EE, Flicek, P, Gabriel, SB, Gibbs, RA, Green, ED, Hurles, ME, Knoppers, BM, Korbel, JO, Lander, ES, Lee, C, Lehrach, H, Mardis, ER, McVean, GA, Nickerson, DA, Schmidt, JP, Sherry, ST, Wang, J, Wilson, RK, Dinh, H, Kovar, C, Lee, S, Lewis, L, Muzny, D, Reid, J, Wang, M, Fang, X, Guo, X, Jian, M, Jiang, H, Jin, X, Li, G, Li, J, Li, Y, Li, Z, Liu, X, Lu, Y, Ma, X, Su, Z, Tai, S, Tang, M, Wang, B, Wang, G, Wu, H, Wu, R, Yin, Y, Zhang, W, Zhao, J, Zhao, M, Zheng, X, Zhou, Y, Gupta, N, Clarke, L, Leinonen, R, Smith, RE, Zheng-Bradley, X, Grocock, R, Humphray, S, James, T, Kingsbury, Z, Sudbrak, R, Albrecht, MW, Amstislavskiy, VS, Borodina, TA, Lienhard, M, Mertes, F, Sultan, M, Timmermann, B, Yaspo, ML, Fulton, L, Fulton, R, Weinstock, GM, Balasubramaniam, S, Burton, J, Danecek, P, Keane, TM, Kolb-Kokocinski, A, McCarthy, S, Molecular Dynamics, Biomimetics, Urban and Regional Studies Institute, Nanomedicine & Drug Targeting, Artificial Intelligence, Micromechanics, Molecular Cell Biology, Van Swinderen Institute for Particle Physics and G, Archaeology of Northwestern Europe, Polymer Chemistry and Bioengineering, Christianity and the History of Ideas, Scientific Visualization and Computer Graphics, Chemical Technology, Macromolecular Chemistry & New Polymeric Materials, Bernoulli Institute, Surfaces and Thin Films, Hemelrijk group, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Falcao Salles lab, Synthetic Organic Chemistry, Psychometrics and Statistics, Bio-inspired systems and circuits, Advanced Production Engineering, Drug Design, The 1000 Genomes Project Consortium, Faculteit Medische Wetenschappen/UMCG, Wellcome Trust, Consiglio Nazionale delle Ricerche, EMBO, and 1000 Genomes Project Consortium
Subjects: Historia y Arqueología, lactase persistence, POSITIVE SELECTION, BALANCING SELECTION, SOFT SWEEP, Biología, standing variation, Population, Biology, Balancing selection, Genome, Polymorphism, Single Nucleotide, Genètica de poblacions humanes, Ciencias Biológicas, purl.org/becyt/ford/1 [https], selective sweep, functional annotation cluster, Genética y Herencia, HUMANIDADES, Genetic drift, Gene Frequency, INDEL Mutation, Humans, Selection, Genetic, education, purl.org/becyt/ford/1.6 [https], Selection (genetic algorithm), education.field_of_study, purl.org/becyt/ford/6 [https], Genome, Human, Research, Genetic Drift, Levenshtein distance, Selecció natural, Sequence Analysis, DNA, Human genetics, Otras Historia y Arqueología, Evolutionary biology, Human genome, purl.org/becyt/ford/6.1 [https], Selective sweep, Genètica humana -- Variació, CIENCIAS NATURALES Y EXACTAS
Abstract: It contains associated material.-- The 1000 Genomes Project Consortium, [Background] Population differentiation has proved to be effective for identifying loci under geographically localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes., [Results] We demonstrate that while sites with low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12, CALD1 and ZNF804, which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively., [Conclusions] We identify known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research. © 2014 Colonna et al., This work was supported by The Wellcome Trust (098051), an Italian National Research Council (CNR) short-term mobility fellowship from the 2013 program to VC, and an EMBO Short Term Fellowship ASTF 324–2010 to VC.
Published: 2014

8. An integrated map of genetic variation from 1,092 human genomes

Author: Altshuler, DM, Durbin, RM, Abecasis, GR, Bentley, DR, Chakravarti, A, Clark, AG, Donnelly, P, Eichler, EE, Flicek, P, Gabriel, SB, Gibbs, RA, Green, ED, Hurles, ME, Knoppers, BM, Korbel, JO, Lander, ES, Lee, C, Lehrach, H, Mardis, ER, Marth, GT, McVean, GA, Nickerson, DA, Schmidt, JP, Sherry, ST, Wang, J, Wilson, RK, Dinh, H, Kovar, C, Lee, S, Lewis, L, Muzny, D, Reid, J, Wang, M, Fang, X, Guo, X, Jian, M, Jiang, H, Jin, X, Li, G, Li, J, Li, Y, Li, Z, Liu, X, Lu, Y, Ma, X, Su, Z, Tai, S, Tang, M, Wang, B, Wang, G, Wu, H, Wu, R, Yin, Y, Zhang, W, Zhao, J, Zhao, M, Zheng, X, Zhou, Y, Gupta, N, Clarke, L, Leinonen, R, Smith, RE, Zheng-Bradley, X, Grocock, R, Humphray, S, James, T, Kingsbury, Z, Sudbrak, R, Albrecht, MW, Amstislavskiy, VS, Borodina, TA, Lienhard, M, Mertes, F, Sultan, M, Timmermann, B, Yaspo, M-L, Fulton, L, Fulton, R, Weinstock, GM, Balasubramaniam, S, Burton, J, Danecek, P, Keane, TM, Kolb-Kokocinski, A, McCarthy, S, Stalker, J, Quail, M, Davies, CJ, Gollub, J, Webster, T, Wong, B, Zhan, Y, Auton, A, Yu, F, Bainbridge, M, Challis, D, Evani, US, Lu, J, Nagaswamy, U, Sabo, A, Wang, Y, Yu, J, Coin, LJM, Fang, L, Li, Q, Lin, H, Liu, B, Luo, R, Qin, N, Shao, H, Xie, Y, Ye, C, Yu, C, Zhang, F, Zheng, H, Zhu, H, Garrison, EP, Kural, D, Lee, W-P, Leong, WF, Ward, AN, Wu, J, Zhang, M, Griffin, L, Hsieh, C-H, Mills, RE, Shi, X, Von Grotthuss, M, Zhang, C, Daly, MJ, DePristo, MA, Banks, E, Bhatia, G, Carneiro, MO, Del Angel, G, Genovese, G, Handsaker, RE, Hartl, C, McCarroll, SA, Nemesh, JC, Poplin, RE, Schaffner, SF, Shakir, K, Yoon, SC, Lihm, J, Makarov, V, Jin, H, Kim, W, Kim, KC, Rausch, T, Beal, K, Cunningham, F, Herrero, J, McLaren, WM, Ritchie, GRS, Gottipati, S, Keinan, A, Rodriguez-Flores, JL, Sabeti, PC, Grossman, SR, Tabrizi, S, Tariyal, R, Cooper, DN, Ball, EV, Stenson, PD, Barnes, B, Bauer, M, Cheetham, RK, Cox, T, Eberle, M, Kahn, S, Murray, L, Peden, J, Shaw, R, Ye, K, Batzer, MA, Konkel, MK, Walker, JA, MacArthur, DG, Lek, M, Herwig, R, Shriver, MD, Bustamante, CD, Byrnes, JK, De la Vega, FM, Gravel, S, Kenny, EE, Kidd, JM, Lacroute, P, Maples, BK, Moreno-Estrada, A, Zakharia, F, Halperin, E, Baran, Y, Craig, DW, Christoforides, A, Homer, N, Izatt, T, Kurdoglu, AA, Sinari, SA, Squire, K, Xiao, C, Sebat, J, Bafna, V, Burchard, EG, Hernandez, RD, Gignoux, CR, Haussler, D, Katzman, SJ, Kent, WJ, Howie, B, Ruiz-Linares, A, Dermitzakis, ET, Lappalainen, T, Devine, SE, Maroo, A, Tallon, LJ, Rosenfeld, JA, Michelson, LP, Kang, HM, Anderson, P, Angius, A, Bigham, A, Blackwell, T, Busonero, F, Cucca, F, Fuchsberger, C, Jones, C, Jun, G, Lyons, R, Maschio, A, Porcu, E, Reinier, F, Sanna, S, Schlessinger, D, Sidore, C, Tan, A, Trost, MK, Awadalla, P, Hodgkinson, A, Lunter, G, Marchini, JL, Myers, S, Churchhouse, C, Delaneau, O, Gupta-Hinch, A, Iqbal, Z, Mathieson, I, Rimmer, A, Xifara, DK, Oleksyk, TK, Fu, Y, Xiong, M, Jorde, L, Witherspoon, D, Xing, J, Browning, BL, Alkan, C, Hajirasouliha, I, Hormozdiari, F, Ko, A, Sudmant, PH, Chen, K, Chinwalla, A, Ding, L, Dooling, D, Koboldt, DC, McLellan, MD, Wallis, JW, Wendl, MC, Zhang, Q, Tyler-Smith, C, Albers, CA, Ayub, Q, Chen, Y, Coffey, AJ, Colonna, V, Huang, N, Jostins, L, Li, H, Scally, A, Walter, K, Xue, Y, Zhang, Y, Gerstein, MB, Abyzov, A, Balasubramanian, S, Chen, J, Clarke, D, Habegger, L, Harmanci, AO, Jin, M, Khurana, E, Mu, XJ, Sisu, C, Degenhardt, J, Stuetz, AM, Church, D, Michaelson, JJ, Ben, B, Lindsay, SJ, Ning, Z, Frankish, A, Harrow, J, Fowler, G, Hale, W, Kalra, D, Barker, J, Kelman, G, Kulesha, E, Radhakrishnan, R, Roa, A, Smirnov, D, Streeter, I, Toneva, I, Vaughan, B, Ananiev, V, Belaia, Z, Beloslyudtsev, D, Bouk, N, Chen, C, Cohen, R, Cook, C, Garner, J, Hefferon, T, Kimelman, M, Liu, C, Lopez, J, Meric, P, O'Sullivan, C, Ostapchuk, Y, Phan, L, Ponomarov, S, Schneider, V, Shekhtman, E, Sirotkin, K, Slotta, D, Zhang, H, Barnes, KC, Beiswanger, C, Cai, H, Cao, H, Gharani, N, Henn, B, Jones, D, Kaye, JS, Kent, A, Kerasidou, A, Mathias, R, Ossorio, PN, Parker, M, Reich, D, Rotimi, CN, Royal, CD, Sandoval, K, Su, Y, Tian, Z, Tishkoff, S, Toji, LH, Via, M, Yang, H, Yang, L, Zhu, J, Bodmer, W, Bedoya, G, Ming, CZ, Yang, G, You, CJ, Peltonen, L, Garcia-Montero, A, Orfao, A, Dutil, J, Martinez-Cruzado, JC, Brooks, LD, Felsenfeld, AL, McEwen, JE, Clemm, NC, Duncanson, A, Dunn, M, Guyer, MS, Peterson, JL, 1000 Genomes Project Consortium, Dermitzakis, Emmanouil, Universitat de Barcelona, Massachusetts Institute of Technology. Department of Biology, Altshuler, David, and Lander, Eric S.
Subjects: Natural selection, LOCI, Genome-wide association study, Evolutionary biology, Continental Population Groups/genetics, Human genetic variation, VARIANTS, Genoma humà, Binding Sites/genetics, 0302 clinical medicine, RARE, Sequence Deletion/genetics, WIDE ASSOCIATION, ddc:576.5, Copy-number variation, MUTATION, Exome sequencing, transcription factor, Conserved Sequence, Human evolution, Sequence Deletion, Genetics, RISK, 0303 health sciences, Multidisciplinary, Continental Population Groups, 1000 Genomes Project Consortium, Genetic analysis, Genomics, Polymorphism, Single Nucleotide/genetics, Research Highlight, 3. Good health, Algorithm, Multidisciplinary Sciences, Genetic Variation/genetics, Map, Science & Technology - Other Topics, Conserved Sequence/genetics, Integrated approach, General Science & Technology, Genetics, Medical, Haplotypes/genetics, Biology, Polymorphism, Single Nucleotide, Evolution, Molecular, 03 medical and health sciences, Genetic variation, Humans, Transcription Factors/metabolism, POPULATION-STRUCTURE, 1000 Genomes Project, Polymorphism, Nucleotide Motifs, Alleles, 030304 developmental biology, COPY NUMBER VARIATION, Science & Technology, Binding Sites, Human genome, Genome, Human, Racial Groups, Genetic Variation, Genetics, Population, Haplotypes, Genome, Human/genetics, untranslated RNA, 030217 neurology & neurosurgery, Transcription Factors, Genome-Wide Association Study
Abstract: By characterizing the geographic and functional spectrum of human genetic variation, the 1000 Genomes Project aims to build a resource to help to understand the genetic contribution to disease. Here we describe the genomes of 1,092 individuals from 14 populations, constructed using a combination of low-coverage whole-genome and exome sequencing. By developing methods to integrate information across several algorithms and diverse data sources, we provide a validated haplotype map of 38 million single nucleotide polymorphisms, 1.4 million short insertions and deletions, and more than 14,000 larger deletions. We show that individuals from different populations carry different profiles of rare and common variants, and that low-frequency variants show substantial geographic differentiation, which is further increased by the action of purifying selection. We show that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites. This resource, which captures up to 98% of accessible single nucleotide polymorphisms at a frequency of 1% in related populations, enables analysis of common and low-frequency variants in individuals from diverse, including admixed, populations., National Institutes of Health (U.S.) (Grant RC2HL102925), National Institutes of Health (U.S.) (Grant U54HG3067)
Published: 2012

9. Integrated genomic analyses of ovarian carcinoma

Author: Bell, D, Berchuck, A, Birrer, M, Chien, J, Cramer, DW, Dao, F, Dhir, R, DiSaia, P, Gabra, H, Glenn, P, Godwin, AK, Triche, T, Berman, BP, Van den Berg, DJ, Buckley, J, Baylin, SB, Zhang, J, Spellman, PT, Purdom, E, Iacocca, M, Shelton, T, Voet, D, Neuvial, P, Bengtsson, H, Jakkula, LR, Durinck, S, Han, J, Dorton, S, Marr, H, Zhang, H, Choi, YG, Wang, V, Wilkinson, J, Nguyen, H, Wang, NJ, Imielinski, M, Ngai, J, Conboy, JG, Parvin, B, Feiler, HS, Speed, TP, Gray, JW, Wu, CJ, Bloom, T, Levine, DA, Li, L, Socci, ND, Liang, Y, Taylor, BS, Kalloger, S, Schultz, N, Borsu, L, Lash, AE, Brennan, C, Ardlie, K, Viale, A, Shukla, S, Grimm, D, Sander, C, Ladanyi, M, Hoadley, KA, Meng, S, Du, Y, Karlan, BY, Shi, Y, Fennell, T, Cibulskis, K, Lawrence, MS, Meyerson, M, Hatfield, M, Mills, GB, Sivachenko, A, Jing, R, Park, RW, Liu, Y, Park, PJ, Ramos, AH, Noble, M, Chin, L, Carter, H, Kim, D, Morris, S, Winckler, W, Karchin, R, Morrison, C, Baldwin, J, Korkola, JE, Yena, P, Heiser, LM, Getz, G, Cho, RJ, Hu, Z, Gabriel, S, Mutch, D, Cerami, E, Rhodes, P, Olshen, A, Verhaak, RGW, Lander, ES, Reva, B, Antipin, Y, Shen, R, Olvera, N, Mankoo, P, Sheridan, R, Ciriello, G, Sherman, M, Chang, WK, Bernanke, JA, Hayes, DN, Carter, SL, Haussler, D, Orsulic, S, Benz, CC, Paulauskis, J, Stuart, JM, Zhang, N, Benz, SC, Sanborn, JZ, Vaske, CJ, Mermel, CH, Zhu, J, Szeto, C, Scott, GK, Yau, C, Rabeno, B, Ding, L, Park, K, Balu, S, Perou, CM, Saksena, G, Wilkerson, MD, Millis, S, Kahn, A, Turman, YJ, Fulton, RS, Onofrio, RC, Greene, JM, Sfeir, R, Jensen, MA, Chen, J, Whitmore, J, Alonso, S, Jordan, J, Chu, A, Rader, JS, Koboldt, DC, Zang, D, Gross, J, Barker, A, Compton, C, Eley, G, Ferguson, M, Fielding, P, Gerhard, DS, Myles, R, McLellan, MD, Schaefer, C, Helms, EB, Shaw, KRM, Sikic, BI, Vaught, J, Vockley, JB, Good, PJ, Guyer, MS, Ozenberger, B, Wylie, T, Peterson, J, Thomson, E, Smith-McCune, K, Sood, AK, Bowtell, D, Hubbard, D, Penny, R, Testa, JR, Chang, K, Walker, J, Dinh, HH, Drummond, JA, Fowler, G, Zhou, X, Gunaratne, P, Hawes, AC, Kovar, CL, Lewis, LR, Gupta, S, Morgan, MB, O'Laughlin, M, Newsham, IF, Santibanez, J, Reid, JG, Trevino, LR, Wu, J, Wu, Y-Q, Wang, M, Muzny, DM, Wheeler, DA, Gibbs, RA, Crenshaw, A, Sivachenko, AY, Topal, MD, Sougnez, C, Dooling, DJ, Fulton, L, Akbani, R, Abbott, R, Dees, ND, Zhang, Q, Kandoth, C, Wendl, M, Schierding, W, Shen, D, Harris, CC, Baggerly, KA, Schmidt, H, Wilson, RK, Kalicki, J, Delehaunty, KD, Fronick, CC, Demeter, R, Cook, L, Wallis, JW, Lin, L, Magrini, VJ, Yung, WK, Hodges, JS, Protopopov, A, Eldred, JM, Smith, SM, Pohl, CS, Vandin, F, Raphael, BJ, Weinstock, GM, Mardis, R, Kim, TM, Hartmann, L, Perna, I, Xiao, Y, Ren, G, Sathiamoorthy, N, Petrelli, N, Lee, E, Kucherlapati, R, Absher, DM, Huang, M, Waite, L, Sherlock, G, Brooks, JD, Li, JZ, Weinstein, JN, Xu, J, Myers, RM, Laird, PW, Cope, L, Herman, JG, Shen, H, Huntsman, DG, Weisenberger, DJ, Noushmehr, H, Pan, F, Massachusetts Institute of Technology. Department of Biology, Lander, Eric S., and Meyerson, Matthew L.
Subjects: endocrine system diseases, Serous carcinoma, Messenger, Gene Dosage, Cancer Genome Atlas Research Network, GYNECOLOGIC-ONCOLOGY-GROUP, GRADE SEROUS CARCINOMA, 0302 clinical medicine, Ovarian carcinoma, Aged, Carcinoma, DNA Methylation, Female, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, Humans, MicroRNAs, Middle Aged, Mutation, Ovarian Neoplasms, RNA, Messenger, Genomics, Multidisciplinary, Genetics, HYBRID SELECTION, 0303 health sciences, female genital diseases and pregnancy complications, 3. Good health, Multidisciplinary Sciences, Serous fluid, BRCA MUTATION CARRIERS, 030220 oncology & carcinogenesis, DNA methylation, PARP inhibitor, Science & Technology - Other Topics, General Science & Technology, Biology, Article, 03 medical and health sciences, CLEAR-CELL CARCINOMA, MD Multidisciplinary, microRNA, HIGH-THROUGHPUT ANNOTATION, medicine, DRIVER MUTATIONS, Gene, 030304 developmental biology, Neoplastic, Science & Technology, MUTANT-CELLS, SOMATIC MUTATIONS, medicine.disease, CANCER STATISTICS, Gene Expression Regulation, Cancer research, RNA, Ovarian cancer
Abstract: A catalogue of molecular aberrations that cause ovarian cancer is critical for developing and deploying therapies that will improve patients’ lives. The Cancer Genome Atlas project has analysed messenger RNA expression, microRNA expression, promoter methylation and DNA copy number in 489 high-grade serous ovarian adenocarcinomas and the DNA sequences of exons from coding genes in 316 of these tumours. Here we report that high-grade serous ovarian cancer is characterized by TP53 mutations in almost all tumours (96%); low prevalence but statistically recurrent somatic mutations in nine further genes including NF1, BRCA1, BRCA2, RB1 and CDK12; 113 significant focal DNA copy number aberrations; and promoter methylation events involving 168 genes. Analyses delineated four ovarian cancer transcriptional subtypes, three microRNA subtypes, four promoter methylation subtypes and a transcriptional signature associated with survival duration, and shed new light on the impact that tumours with BRCA1/2 (BRCA1 or BRCA2) and CCNE1 aberrations have on survival. Pathway analyses suggested that homologous recombination is defective in about half of the tumours analysed, and that NOTCH and FOXM1 signalling are involved in serous ovarian cancer pathophysiology., National Institutes of Health (U.S.) (Grant U54HG003067), National Institutes of Health (U.S.) (Grant U54HG003273), National Institutes of Health (U.S.) (Grant U54HG003079), National Institutes of Health (U.S.) (Grant U24CA126543), National Institutes of Health (U.S.) (Grant U24CA126544), National Institutes of Health (U.S.) (Grant U24CA126546), National Institutes of Health (U.S.) (Grant U24CA126551), National Institutes of Health (U.S.) (Grant U24CA126554), National Institutes of Health (U.S.) (Grant U24CA126561), National Institutes of Health (U.S.) (Grant U24CA126563), National Institutes of Health (U.S.) (Grant U24CA143882), National Institutes of Health (U.S.) (Grant U24CA143731), National Institutes of Health (U.S.) (Grant U24CA143835), National Institutes of Health (U.S.) (Grant U24CA143845), National Institutes of Health (U.S.) (Grant U24CA143858), National Institutes of Health (U.S.) (Grant U24CA144025), National Institutes of Health (U.S.) (Grant U24CA143866), National Institutes of Health (U.S.) (Grant U24CA143867), National Institutes of Health (U.S.) (Grant U24CA143848), National Institutes of Health (U.S.) (Grant U24CA143843), National Institutes of Health (U.S.) (Grant R21CA135877)
Published: 2010

10. Genome sequence of the pea aphid Acyrthosiphon pisum

Author: Richards, S, Gibbs, RA, Gerardo, NM, Moran, N, Nakabachi, A, Stern, D, Tagu, D, Wilson, ACC, Muzny, D, Kovar, C, Cree, A, Chacko, J, Chandrabose, MN, Dao, MD, Dinh, HH, Gabisi, RA, Hines, S, Hume, J, Jhangian, SN, Joshi, V, Lewis, LR, Liu, Y-S, Lopez, J, Morgan, MB, Nguyen, NB, Okwuonu, GO, Ruiz, SJ, Santibanez, J, Wright, RA, Fowler, GR, Hitchens, ME, Lozado, RJ, Moen, C, Steffen, D, Warren, JT, Zhang, J, Nazareth, LV, Chavez, D, Davis, C, Lee, SL, Patel, BM, Pu, L-L, Bell, SN, Johnson, AJ, Vattathil, S, Jr, WRL, Shigenobu, S, Dang, PM, Morioka, M, Fukatsu, T, Kudo, T, Miyagishima, S-Y, Jiang, H, Worley, KC, Legeai, F, Gauthier, J-P, Collin, O, Zhang, L, Chen, H-C, Ermolaeva, O, Hlavina, W, Kapustin, Y, Kiryutin, B, Kitts, P, Maglott, D, Murphy, T, Pruitt, K, Sapojnikov, V, Souvorov, A, Thibaud-Nissen, F, Camara, F, Guigo, R, Stanke, M, Solovyev, V, Kosarev, P, Gilbert, D, Gabaldon, T, Huerta-Cepas, J, Marcet-Houben, M, Pignatelli, M, Moya, A, Rispe, C, Ollivier, M, Quesneville, H, Permal, E, Llorens, C, Futami, R, Hedges, D, Robertson, HM, Alioto, T, Mariotti, M, Nikoh, N, McCutcheon, JP, Burke, G, Kamins, A, Latorre, A, Moran, NA, Ashton, P, Calevro, F, Charles, H, Colella, S, Douglas, A, Jander, G, Jones, DH, Febvay, G, Kamphuis, LG, Kushlan, PF, Macdonald, S, Ramsey, J, Schwartz, J, Seah, S, Thomas, G, Vellozo, A, Cass, B, Degnan, P, Hurwitz, B, Leonardo, T, Koga, R, Altincicek, B, Anselme, C, Atamian, H, Barribeau, SM, de Vos, M, Duncan, EJ, Evans, J, Ghanim, M, Heddi, A, Kaloshian, I, Vincent-Monegat, C, Parker, BJ, Perez-Brocal, V, Rahbe, Y, Spragg, CJ, Tamames, J, Tamarit, D, Tamborindeguy, C, Vilcinskas, A, Bickel, RD, Brisson, JA, Butts, T, Chang, C-C, Christiaens, O, Davis, GK, Duncan, E, Ferrier, D, Iga, M, Janssen, R, Lu, H-L, McGregor, A, Miura, T, Smagghe, G, Smith, J, van der Zee, M, Velarde, R, Wilson, M, Dearden, P, Edwards, OR, Gordon, K, Hilgarth, RS, Jr, RSD, Srinivasan, D, Walsh, TK, Ishikawa, A, Jaubert-Possamai, S, Fenton, B, Huang, W, Rizk, G, Lavenier, D, Nicolas, J, Smadja, C, Zhou, J-J, Vieira, FG, He, X-L, Liu, R, Rozas, J, Field, LM, Ashton, PD, Campbell, P, Carolan, JC, Douglas, AE, Fitzroy, CIJ, Reardon, KT, Reeck, GR, Singh, K, Wilkinson, TL, Huybrechts, J, Abdel-latief, M, Robichon, A, Veenstra, JA, Hauser, F, Cazzamali, G, Schneider, M, Williamson, M, Stafflinger, E, Hansen, KK, Grimmelikhuijzen, CJP, Price, DRG, Caillaud, M, van Fleet, E, Ren, Q, Gatehouse, JA, Brault, V, Monsion, B, Diaz, J, Hunnicutt, L, Ju, H-J, Pechuan, X, Aguilar, J, Cortes, T, Ortiz-Rivas, B, Martinez-Torres, D, Dombrovsky, A, Dale, RP, Davies, TGE, Williamson, MS, Jones, A, Sattelle, D, Williamson, S, Wolstenholme, A, Cottret, L, Sagot, MF, Heckel, DG, Hunter, W, Consortium, IAG, Universitat de Barcelona, Princeton University, Biologie des organismes et des populations appliquées à la protection des plantes (BIO3P), Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-AGROCAMPUS OUEST, Biologie Fonctionnelle, Insectes et Interactions (BF2I), Institut National de la Recherche Agronomique (INRA)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA), Baylor College of Medicine (BCM), Baylor University, An algorithmic view on genomes, cells, and environments (BAMBOO), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), IAGC, Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon, Eisen, Jonathan A., and Eisen, Jonathan A
Subjects: 0106 biological sciences, TANDEM REPEATS, Genome, Insect, Gene Transfer, RRES175, Sequència genòmica, Faculty of Science\Computer Science, CPG METHYLATION, 01 natural sciences, Genome, Medical and Health Sciences, International Aphid Genomics Consortium, Biologiska vetenskaper, Biology (General), GENE-EXPRESSION, 2. Zero hunger, Genetics, 0303 health sciences, Aphid, Afídids, General Neuroscience, GENOME SEQUENCE, food and beverages, DROSOPHILA CIRCADIAN CLOCK, Biological Sciences, Genetics and Genomics/Microbial Evolution and Genomics, INSECTE, Genètica microbiana, puceron, APIS-MELLIFERA, General Agricultural and Biological Sciences, Infection, symbiose, Biotechnology, Research Article, VIRUS VECTORING, 175_Genetics, SYMBIOTIC BACTERIA, Gene Transfer, Horizontal, QH301-705.5, ACYRTHOSIPHON PISUM, Biology, HOLOMETABOLOUS INSECTS, HOST-PLANT, 010603 evolutionary biology, PEA APHID, INSECT-PLANT, PHENOTYPIC PLASTICITY, RAVAGEUR DES CULTURES, SOCIAL INSECT, General Biochemistry, Genetics and Molecular Biology, Horizontal, 03 medical and health sciences, Buchnera, Gene family, Life Science, Animals, Symbiosis, Gene, 030304 developmental biology, Whole genome sequencing, General Immunology and Microbiology, Annotation, Genome sequence, Agricultural and Veterinary Sciences, 175_Entomology, Genètica animal, Bacteriocyte, génome, gène, Human Genome, Biology and Life Sciences, 15. Life on land, biochemical phenomena, metabolism, and nutrition, biology.organism_classification, REPETITIVE ELEMENTS, DNA-SEQUENCES, Acyrthosiphon pisum, Genome Sequence, Genetics and Genomics/Genome Projects, Aphids, PHEROMONE-BINDING, Insect, Developmental Biology, [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract: The genome of the pea aphid shows remarkable levels of gene duplication and equally remarkable gene absences that shed light on aspects of aphid biology, most especially its symbiosis with Buchnera., Aphids are important agricultural pests and also biological models for studies of insect-plant interactions, symbiosis, virus vectoring, and the developmental causes of extreme phenotypic plasticity. Here we present the 464 Mb draft genome assembly of the pea aphid Acyrthosiphon pisum. This first published whole genome sequence of a basal hemimetabolous insect provides an outgroup to the multiple published genomes of holometabolous insects. Pea aphids are host-plant specialists, they can reproduce both sexually and asexually, and they have coevolved with an obligate bacterial symbiont. Here we highlight findings from whole genome analysis that may be related to these unusual biological features. These findings include discovery of extensive gene duplication in more than 2000 gene families as well as loss of evolutionarily conserved genes. Gene family expansions relative to other published genomes include genes involved in chromatin modification, miRNA synthesis, and sugar transport. Gene losses include genes central to the IMD immune pathway, selenoprotein utilization, purine salvage, and the entire urea cycle. The pea aphid genome reveals that only a limited number of genes have been acquired from bacteria; thus the reduced gene count of Buchnera does not reflect gene transfer to the host genome. The inventory of metabolic genes in the pea aphid genome suggests that there is extensive metabolite exchange between the aphid and Buchnera, including sharing of amino acid biosynthesis between the aphid and Buchnera. The pea aphid genome provides a foundation for post-genomic studies of fundamental biological questions and applied agricultural problems., Author Summary Aphids are common pests of crops and ornamental plants. Facilitated by their ancient association with intracellular symbiotic bacteria that synthesize essential amino acids, aphids feed on phloem (sap). Exploitation of a diversity of long-lived woody and short-lived herbaceous hosts by many aphid species is a result of specializations that allow aphids to discover and exploit suitable host plants. Such specializations include production by a single genotype of multiple alternative phenotypes including asexual, sexual, winged, and unwinged forms. We have generated a draft genome sequence of the pea aphid, an aphid that is a model for the study of symbiosis, development, and host plant specialization. Some of the many highlights of our genome analysis include an expanded total gene set with remarkable levels of gene duplication, as well as aphid-lineage-specific gene losses. We find that the pea aphid genome contains all genes required for epigenetic regulation by methylation, that genes encoding the synthesis of a number of essential amino acids are distributed between the genomes of the pea aphid and its symbiont, Buchnera aphidicola, and that many genes encoding immune system components are absent. These genome data will form the basis for future aphid research and have already underpinned a variety of genome-wide approaches to understanding aphid biology.
Published: 2010

11. Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds

Author: Bovine HapMap Consortium, Gibbs RA, Taylor JF, Van Tassell CP, Barendse W, Eversole KA, Gill CA, Green RD, Hamernik DL, Kappes SM, Lien S, Matukumalli LK, McEwan JC, Nazareth LV, Schnabel RD, Weinstock GM, Wheeler DA, Ajmone-Marsan P, and Boettcher PJ
Abstract: The imprints of domestication and breed development on the genomes of livestock likely differ from those of companion animals. A deep draft sequence assembly of shotgun reads from a single Hereford female and comparative sequences sampled from six additional breeds were used to develop probes to interrogate 37,470 single-nucleotide polymorphisms (SNPs) in 497 cattle from 19 geographically and biologically diverse breeds. These data show that cattle have undergone a rapid recent decrease in effective population size from a very large ancestral population, possibly due to bottlenecks associated with domestication, selection, and breed formation. Domestication and artificial selection appear to have left detectable signatures of selection within the cattle genome, yet the current levels of diversity within breeds are at least as great as exists within humans.
Published: 2009

12. The genome of the model beetle and pest tribolium castaneum

Author: Richards, S, Gibbs, RA, Weinstock, GM, Brown, SJ, Denell, R, Beeman, RW, Gibbs, R, Bucher, G, Friedrich, M, Grimmelikhuijzen, CJ, Klingler, M, Lorenzen, M, Roth, S, Schröder, R, Tautz, D, Zdobnov, EM, Muzny, D, Attaway, T, Bell, S, Buhay, CJ, Chandrabose, MN, Chavez, D, Clerk-Blankenburg, KP, Cree, A, Dao, M, Davis, C, Chacko, J, Dinh, H, Dugan-Rocha, S, Fowler, G, Garner, TT, Garnes, J, Gnirke, A, Hawes, A, Hernandez, J, Hines, S, Holder, M, Hume, J, Jhangiani, SN, Joshi, V, Khan, ZM, Jackson, L, Kovar, C, Kowis, A, Lee, S, Lewis, LR, Margolis, J, Morgan, M, Nazareth, LV, Nguyen, N, Okwuonu, G, Parker, D, Ruiz, SJ, Santibanez, J, Savard, J, Scherer, SE, Schneider, B, Sodergren, E, Vattahil, S, Villasana, D, White, CS, Wright, R, Park, Y, Lord, J, Oppert, B, Brown, S, Wang, L, Weinstock, G, Liu, Y, Worley, K, Elsik, CG, Reese, JT, Elhaik, E, Landan, G, Graur, D, Arensburger, P, Atkinson, P, Beidler, J, Demuth, JP, Drury, DW, Du, YZ, Fujiwara, H, Maselli, V, Osanai, M, Robertson, HM, Tu, Z, Wang, JJ, Wang, S, Song, H, Zhang, L, Werner, D, Stanke, M, Morgenstern, B, Solovyev, V, Kosarev, P, Brown, G, Chen, HC, Ermolaeva, O, Hlavina, W, Kapustin, Y, Kiryutin, B, Kitts, P, Maglott, D, Pruitt, K, Sapojnikov, V, Souvorov, A, Mackey, AJ, Waterhouse, RM, Wyder, S, Kriventseva, EV, Kadowaki, T, Bork, P, Aranda, M, Bao, R, Beermann, A, Berns, N, Bolognesi, R, Bonneton, F, Bopp, D, Butts, T, Chaumot, A, Denell, RE, Ferrier, DE, Gordon, CM, Jindra, M, Lan, Q, Lattorff, HM, Laudet, V, von Levetsow, C, Liu, Z, Lutz, R, Lynch, JA, da Fonseca, RN, Posnien, N, Reuter, R, Schinko, JB, Schmitt, C, Schoppmeier, M, Shippy, TD, Simonnet, F, Marques-Souza, H, Tomoyasu, Y, Trauner, J, Van der Zee, M, Vervoort, M, Wittkopp, N, Wimmer, EA, Yang, X, Jones, AK, Sattelle, DB, Ebert, PR, Nelson, D, Scott, JG, Muthukrishnan, S, Kramer, KJ, Arakane, Y, Zhu, Q, Hogenkamp, D, Dixit, R, Jiang, H, Zou, Z, Marshall, J, Elpidina, E, Vinokurov, K, Oppert, C, Evans, J, Lu, Z, Zhao, P, Sumathipala, N, Altincicek, B, Vilcinskas, A, Williams, M, Hultmark, D, Hetru, C, Hauser, F, Cazzamali, G, Williamson, M, Li, B, Tanaka, Y, Predel, R, Neupert, S, Schachtner, J, Verleyen, P, Raible, F, Walden, KK, Angeli, S, Forêt, S, Schuetz, S, Maleszka, R, Miller, SC, Grossmann, D, MDC Library, and Zdobnov, Evgeny
Subjects: 0106 biological sciences, Repetitive Sequences, Nucleic Acid/genetics, Insecticides, Proteome, Genome, Insect, Cytochrome P-450 Enzyme System/genetics, Genes, Insect, Insect, Receptors, Odorant, 01 natural sciences, Genome, Receptors, G-Protein-Coupled, G-Protein-Coupled Receptors, Genome, Insect/ genetics, Oogenesis, Cytochrome P-450 Enzyme System, RNA interference, Odorant Receptors, Caenorhabditis elegans, Insect Genome, Phylogeny, media_common, Genetics, ddc:616, 0303 health sciences, Base Composition, Neurotransmitter Agents, Tribolium, Multidisciplinary, Neurotransmitter Agents/genetics, Receptors, Odorant/genetics, Vision, Ocular/genetics, Telomere, Insecticides/pharmacology, DNA Transposable Elements/genetics, Proteome/genetics, Genes, Insect/ genetics, Oogenesis/genetics, Taste, RNA Interference, Growth and Development, Drosophila melanogaster, animal structures, Nucleic Acid Repetitive Sequences, Taste/genetics, media_common.quotation_subject, 570 Life Sciences, Biology, 010603 evolutionary biology, 610 Medical Sciences, Medicine, 03 medical and health sciences, Humans, Insect Genes, Ocular Vision, Animals, Tribolium/classification/embryology/ genetics/physiology, Red flour beetle, Gene, Drosophila, Vision, Ocular, 030304 developmental biology, Repetitive Sequences, Nucleic Acid, Growth and Development/genetics, Telomere/genetics, Body Patterning, fungi, biology.organism_classification, Body Patterning/genetics, Cardiovascular and Metabolic Diseases, DNA Transposable Elements, Receptors, G-Protein-Coupled/genetics
Abstract: Tribolium castaneum is a member of the most species-rich eukaryotic order, a powerful model organism for the study of generalized insect development, and an important pest of stored agricultural products. We describe its genome sequence here. This omnivorous beetle has evolved the ability to interact with a diverse chemical environment, as shown by large expansions in odorant and gustatory receptors, as well as P450 and other detoxification enzymes. Development in Tribolium is more representative of other insects than is Drosophila, a fact reflected in gene content and function. For example, Tribolium has retained more ancestral genes involved in cell-cell communication than Drosophila, some being expressed in the growth zone crucial for axial elongation in short-germ development. Systemic RNA interference in T. castaneum functions differently from that in Caenorhabditis elegans, but nevertheless offers similar power for the elucidation of gene function and identification of targets for selective insect control.
Published: 2008

13. Genome-wide detection and characterization of positive selection in human populations

Author: Sabeti, PC, Varilly, P, Fry, B, Lohmueller, J, Hostetter, E, Cotsapas, C, Xie, X, Byrne, EH, McCarroll, SA, Gaudet, R, Schaffner, SF, Lander, ES, Frazer, KA, Ballinger, DG, Cox, DR, Hinds, DA, Stuve, LL, Gibbs, RA, Belmont, JW, Boudreau, A, Hardenbol, P, Leal, SM, Pasternak, S, Wheeler, DA, Willis, TD, Yu, F, Yang, H, Zeng, C, Gao, Y, Hu, H, Hu, W, Li, C, Lin, W, Liu, S, Pan, H, Tang, X, Wang, J, Wang, W, Yu, J, Zhang, B, Zhang, Q, Zhao, H, Zhou, J, Gabriel, SB, Barry, R, Blumenstiel, B, Camargo, A, Defelice, M, Faggart, M, Goyette, M, Gupta, S, Moore, J, Nguyen, H, Onofrio, RC, Parkin, M, Roy, J, Stahl, E, Winchester, E, Ziaugra, L, Altshuler, D, Shen, Y, Yao, Z, Huang, W, Chu, X, He, Y, Jin, L, Liu, Y, Sun, W, Wang, H, Wang, Y, Xiong, X, Xu, L, Waye, MM, Tsui, SK, Xue, H, Wong, JT, Galver, LM, Fan, JB, Gunderson, K, Murray, SS, Oliphant, AR, Chee, MS, Montpetit, A, Chagnon, F, Ferretti, V, Leboeuf, M, Olivier, JF, Phillips, MS, Roumy, S, Sallée, C, Verner, A, Hudson, TJ, Kwok, PY, Cai, D, Koboldt, DC, Miller, RD, Pawlikowska, L, Taillon-Miller, P, Xiao, M, Tsui, LC, Mak, W, Song, YQ, Tam, PK, Nakamura, Y, Kawaguchi, T, Kitamoto, T, Morizono, T, Nagashima, A, Ohnishi, Y, Sekine, A, Tanaka, T, Tsunoda, T, Deloukas, P, Bird, CP, Delgado, M, Dermitzakis, ET, Gwilliam, R, Hunt, S, Morrison, J, Powell, D, Stranger, BE, Whittaker, P, Bentley, DR, Daly, MJ, de Bakker, PI, Barrett, J, Chretien, YR, Maller, J, McCarroll, S, Patterson, N, Pe'er, I, Price, A, Purcell, S, Richter, DJ, Sabeti, P, Saxena, R, Sham, PC, Stein, LD, Krishnan, L, Smith, AV, Tello-Ruiz, MK, Thorisson, GA, Chakravarti, A, Chen, PE, Cutler, DJ, Kashuk, CS, Lin, S, Abecasis, GR, Guan, W, Li, Y, Munro, HM, Qin, ZS, Thomas, DJ, McVean, G, Auton, A, Bottolo, L, Cardin, N, Eyheramendy, S, Freeman, C, Marchini, J, Myers, S, Spencer, C, Stephens, M, Donnelly, P, Cardon, LR, Clarke, G, Evans, DM, Morris, AP, Weir, BS, Johnson, TA, Mullikin, JC, Sherry, ST, Feolo, M, Skol, A, Zhang, H, Matsuda, I, Fukushima, Y, Macer, DR, Suda, E, Rotimi, CN, Adebamowo, CA, Ajayi, I, Aniagwu, T, Marshall, PA, Nkwodimmah, C, Royal, CD, Leppert, MF, Dixon, M, Peiffer, A, Qiu, R, Kent, A, Kato, K, Niikawa, N, Adewole, IF, Knoppers, BM, Foster, MW, Clayton, EW, Watkin, J, Muzny, D, Nazareth, L, Sodergren, E, Weinstock, GM, Yakub, I, Birren, BW, Wilson, RK, Fulton, LL, Rogers, J, Burton, J, Carter, NP, Clee, CM, Griffiths, M, Jones, MC, McLay, K, Plumb, RW, Ross, MT, Sims, SK, Willey, DL, Chen, Z, Han, H, Kang, L, Godbout, M, Wallenburg, JC, L'Archevêque, P, Bellemare, G, Saeki, K, An, D, Fu, H, Li, Q, Wang, Z, Wang, R, Holden, AL, Brooks, LD, McEwen, JE, Guyer, MS, Wang, VO, Peterson, JL, Shi, M, Spiegel, J, Sung, LM, Zacharia, LF, Collins, FS, Kennedy, K, Jamieson, R, and Stewart, J
Subjects: Models, Molecular, Population, Single-nucleotide polymorphism, Human genetic variation, Biology, Polymorphism, Single Nucleotide, Article, Antiporters, Gene Frequency, Humans, International HapMap Project, Selection, Genetic, education, Selection (genetic algorithm), Genetics, education.field_of_study, Multidisciplinary, Natural selection, Geography, Edar Receptor, Genome, Human, Haplotype, Regional Index: Eurasia, Protein Structure, Tertiary, Europe, Genetics, Population, Haplotypes, Human genome
Abstract: With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2). We used 'long-range haplotype' methods, which were developed to identify alleles segregating in a population that have undergone recent selection, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population:LARGE and DMD, both related to infection by the Lassa virus, in West Africa;SLC24A5 and SLC45A2, both involved in skin pigmentation, in Europe; and EDAR and EDA2R, both involved in development of hair follicles, in Asia. ©2007 Nature Publishing Group., link_to_OA_fulltext
Published: 2007

14. MEAT AND OTHER ANIMAL-DERIVED FOODS AS SOURCES OF n-3 FATTY ACIDS

Author: Gibbs, RA, primary, Rymer, C, additional, and Givens, DI, additional
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15. Exploring the utility of whole-exome sequencing as a diagnostic tool in a child with atypical episodic muscle weakness

Author: Hanchard, NA, primary, Murdock, DR, additional, Magoulas, PL, additional, Bainbridge, M, additional, Muzny, D, additional, Wu, YQ, additional, Wang, M, additional, McGuire, AL, additional, Lupski, JR, additional, Gibbs, RA, additional, and Brown, CW, additional
Published: 2012
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16. Whole-exome sequencing points to considerable genetic heterogeneity of cerebral palsy.

Author: McMichael, G., Bainbridge, MN., Haan, E., Corbett, M., Gardner, A., Thompson, S., Bon, BWM van, Eyk, CL van, Broadbent, J., Reynolds, C., O'Callaghan, ME., Nguyen, LS., Adelson, DL., Russo, R., Jhangiani, S., Doddapaneni, H., Muzny, DM., Gibbs, RA., Gecz, J., and MacLennan, AH.
Subjects: CEREBRAL palsy, CHROMOSOME abnormalities, NUCLEIC acid isolation methods, LYMPHOBLASTOID cell lines
Abstract: Cerebral palsy (CP) is a common, clinically heterogeneous group of disorders affecting movement and posture. Its prevalence has changed little in 50 years and the causes remain largely unknown. The genetic contribution to CP causation has been predicted to be ∼ 2%. We performed whole-exome sequencing of 183 cases with CP including both parents (98 cases) or one parent (67 cases) and 18 singleton cases (no parental DNA). We identified and validated 61 de novo protein-altering variants in 43 out of 98 (44%) case-parent trios. Initial prioritization of variants for causality was by mutation type, whether they were known or predicted to be deleterious and whether they occurred in known disease genes whose clinical spectrum overlaps CP. Further, prioritization used two multidimensional frameworks-the Residual Variation Intolerance Score and the Combined Annotation-dependent Depletion score.Ten de novo mutations in three previously identified disease genes (TUBA!A (n = 2), SCN8A (n = 1) and KDM5C (n = 1)) and in six novel candidate CP genes (AGAP1, JHDM1D, MAST1, NAA35, RFX2 and WIPI2) were predicted to be potentially pathogenic for CP. In addition, we identified four predicted pathogenic, hemizygous variants on chromosome χ in two known disease genes, LI CAM and PAK3, and in two novel candidate CP genes, CD99L2 and TENM1. In total, 14% of CP cases, by strict criteria, had a potentially disease-causing gene variant. Half were in novel genes. The genetic heterogeneity highlights the complexity of the genetic contribution to CP. Function and pathway studies are required to establish the causative role of these putative pathogenic CP genes. [ABSTRACT FROM AUTHOR]
Published: 2015
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17. Exploring the utility of whole-exome sequencing as a diagnostic tool in a child with atypical episodic muscle weakness.

Author: Hanchard, NA, Murdock, DR, Magoulas, PL, Bainbridge, M, Muzny, D, Wu, YQ, Wang, M, McGuire, AL, Lupski, JR, Gibbs, RA, and Brown, CW
Subjects: MUSCLE weakness, DYSTONIA, DIFFERENTIAL diagnosis, HYPOKALEMIC periodic paralysis, CLINICAL medicine, DIAGNOSIS
Abstract: The advent of whole-exome next-generation sequencing ( WES) has been pivotal for the molecular characterization of Mendelian disease; however, the clinical applicability of WES has remained relatively unexplored. We describe our exploration of WES as a diagnostic tool in a 3½-year old female patient with a 2-year history of episodic muscle weakness and paroxysmal dystonia who presented following a previous extensive but unrevealing diagnostic work-up. WES was performed on the proband and her two parents. Parental exome data was used to filter potential de novo genomic events in the proband and suspected variants were confirmed using di-deoxy sequencing. WES revealed a de novo non-synonymous mutation in exon 21 of the calcium channel gene CACNA1S that has been previously reported in a single patient as a rare cause of atypical hypokalemic periodic paralysis. This was unexpected, as the proband's original differential diagnosis had included hypokalemic periodic paralysis, but clinical and laboratory features were equivocal, and standard clinical molecular testing for hypokalemic periodic paralysis and related disorders was negative. This report highlights the potential diagnostic utility of WES in clinical practice, with implications for the approach to similar diagnostic dilemmas in the future. [ABSTRACT FROM AUTHOR]
Published: 2013
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18. Postgraduate Symposium: Long-chain n-3 PUFA: intakes in the UK and the potential of a chicken meat prototype to increase them.

Author: Gibbs RA, Rymer C, Givens DI, Gibbs, Rachael A, Rymer, Caroline, and Givens, D Ian
Abstract: With the wide acceptance of the long-chain (LC) n-3 PUFA EPA and DHA as important nutrients playing a role in the amelioration of certain diseases, efforts to understand factors affecting intakes of these fatty acids along with potential strategies to increase them are vital. Widespread aversion to oil-rich fish, the richest natural source of EPA and DHA, highlights both the highly suboptimal current intakes in males and females across all age-groups and the critical need for an alternative supply of EPA and DHA. Poultry meat is a popular and versatile food eaten in large quantities relative to other meats and is open to increased LC n-3 PUFA content through manipulation of the chicken's diet to modify fatty acid deposition and therefore lipid composition of the edible tissues. It is therefore seen as a favourable prototype food for increasing human dietary supply of LC n-3 PUFA. Enrichment of chicken breast and leg tissue is well established using fish oil or fishmeal, but concerns about sustainability have led to recent consideration of algal biomass as an alternative source of LC n-3 PUFA. Further advances have also been made in the quality of the resulting meat, including achieving acceptable flavour and storage properties as well as understanding the impact of cooking on the retention of fatty acids. Based on these considerations it may be concluded that EPA- and DHA-enriched poultry meat has a very positive potential future in the food chain. [ABSTRACT FROM AUTHOR]
Published: 2010
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19. Single nucleotide polymorphisms in genes for 2'-5'-oligoadenylate synthetase and RNase L inpatients hospitalized with West Nile virus infection.

Author: Yakub I, Lillibridge KM, Moran A, Gonzalez OY, Belmont J, Gibbs RA, Tweardy DJ, Yakub, Imtiaz, Lillibridge, Kristy M, Moran, Ana, Gonzalez, Omar Y, Belmont, John, Gibbs, Richard A, and Tweardy, David J
Abstract: Background: Infection with the flavivirus West Nile virus (WNV) is a growing problem across the United States, where there is a case-fatality rate of 15%-29% in individuals >70 years old and no consistently effective treatment. Susceptibility to WNV disease in inbred strains of mice was mapped to a nonsense mutation in the gene encoding the 1b isoform of 2'-5'-oligoadenylate synthetase (OAS), a member of the OAS/RNase L system of innate viral resistance. Genetic susceptibility to severe WNV disease in humans has not been determined.Methods: We sequenced each exon within all OAS and RNASEL genes in 33 individuals hospitalized with WNV infection in Houston to assess if there is a defect in this system in patients with severe WNV disease.Results: Sequencing did not reveal any insertions, deletions, or nonsense mutations in any OAS or RNASEL gene. However, comparison of the exonic sequences between case patients and control subjects identified 23 single nucleotide polymorphisms (SNPs), including a synonymous SNP in OASL exon 2 (rs3213545), in which the reference allele occurred at a higher frequency in case patients (P < .004).Conclusion: Because the reference allele contains a splice enhancer site, our finding suggests that the RNA transcripts generated from this allele may undergo increased splicing, which results in a dominant-negative OASL isozyme similar to the nonsense/truncation mutant form of Oas1b in mice. [ABSTRACT FROM AUTHOR]
Published: 2005
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20. Primary immunodeficiency diseases: Genomic approaches delineate heterogeneous Mendelian disorders

Author: Mohammad K. Eldomery, Olaug K. Rødningen, Cecilia Poli, Debra Canter, Berit Flatø, Ketil Heimdal, Nicholas L. Rider, Silje F. Jørgensen, Hasibe Artac, Hans Christian Erichsen, Francisco Javier Espinosa Rosales, Ivan K. Chinn, Alison A. Bertuch, Bo Yuan, Jordan S. Orange, Emily M. Mace, Wojciech Wiszniewski, Robert Lyle, Shalini N. Jhangiani, Tobias Gedde-Dahl, Carla M. Davis, Carl E. Allen, I. Celine Hanson, Magnus K. O. Burstedt, Thomas B. Issekutz, Mari Ann Kulseth, Yavuz Bayram, Eric A. Smith, Tram N. Cao, Stephen Jolles, Andrew C. Issekutz, Pubudu S. Samarakoon, Alice Y. Chan, Gozde Yesil, Eva Holmberg, Børre Fevang, Diana K. Bayer, John W. Belmont, Asbjørg Stray-Pedersen, Timothy J. Vece, Magdalena Walkiewicz, James R. Lupski, Ying Sheng, Trine Prescott, Liv T. N. Osnes, Cecilie F. Rustad, Nina Denisse Guerrero-Cursaru, Juan Carlos Aldave Becerra, Victor Wei Zhang, Philip M. Boone, Mohammad S. Ehlayel, Jason W. Caldwell, Tore G. Abrahamsen, José Luis Franco, Harshal Abhyankar, Henrik Hjorth-Hansen, Liliana Bezrodnik, Vegard Skogen, Nicola A.M. Wright, Lisa R. Forbes, Anne Grete Bechensteen, Christine R. Beck, Saul Oswaldo Lugo Reyes, Lee-Jun C. Wong, Shen Gu, Sarah K. Nicholas, Christina E. West, Filiz O. Seeborg, Mehmed M. Atik, Eric Boerwinkle, Luis A. Pedroza, Caterina Cancrini, Hanne Sørmo Sorte, Yaping Yang, Christine M. Eng, Richard A. Gibbs, Lenora M. Noroski, Alessandro Aiuti, Ender Karaca, Torstein Øverland, Claudia Milena Trujillo Vargas, Jordan K. Abbott, Geir E. Tjønnfjord, William T. Shearer, Javier Chinen, Ingunn Dybedal, Tomasz Gambin, Donna M. Muzny, Pål Aukrust, Ingvild Nordøy, María Soledad Caldirola, Jianhong Hu, Zeynep Coban Akdemir, YEŞİL, Gözde, Stray Pedersen, A, Sorte, H, Samarakoon, P, Gambin, T, Chinn, Ik, Coban Akdemir, Zh, Erichsen, Hc, Forbes, Lr, Gu, S, Yuan, B, Jhangiani, Sn, Muzny, Dm, Rødningen, Ok, Sheng, Y, Nicholas, Sk, Noroski, Lm, Seeborg, Fo, Davis, Cm, Canter, Dl, Mace, Em, Vece, Tj, Allen, Ce, Abhyankar, Ha, Boone, Pm, Beck, Cr, Wiszniewski, W, Fevang, B, Aukrust, P, Tjønnfjord, Ge, Gedde Dahl, T, Hjorth Hansen, H, Dybedal, I, Nordøy, I, Jørgensen, Sf, Abrahamsen, Tg, Øverland, T, Bechensteen, Ag, Skogen, V, Osnes, Lt, Kulseth, Ma, Prescott, Te, Rustad, Cf, Heimdal, Kr, Belmont, Jw, Rider, Nl, Chinen, J, Cao, Tn, Smith, Ea, Caldirola, M, Bezrodnik, L, Lugo Reyes, So, Espinosa Rosales, Fj, Guerrero Cursaru, Nd, Pedroza, La, Poli, Cm, Franco, Jl, Trujillo Vargas, Cm, Aldave Becerra, Jc, Wright, N, Issekutz, Tb, Issekutz, Ac, Abbott, J, Caldwell, Jw, Bayer, Dk, Chan, Ay, Aiuti, Alessandro, Cancrini, C, Holmberg, E, West, C, Burstedt, M, Karaca, E, Yesil, G, Artac, H, Bayram, Y, Atik, Mm, Eldomery, Mk, Ehlayel, M, Jolles, S, Flatø, B, Bertuch, Aa, Hanson, Ic, Zhang, Vw, Wong, Lj, Hu, J, Walkiewicz, M, Yang, Y, Eng, Cm, Boerwinkle, E, Gibbs, Ra, Shearer, Wt, Lyle, R, Orange, J, Lupski, J. R., and Selçuk Üniversitesi
Subjects: 0301 basic medicine, Male, Allergy, Genomic approaches delineate heterogeneous Mendelian disorders-, JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY, cilt.139, ss.232-245, 2017 [Stray-Pedersen A., Sorte H. S. , Samarakoon P., Gambin T., Chinn I. K. , Akdemir Z. H. C. , Erichsen H. C. , Forbes L. R. , Gu S., Yuan B., et al., -Primary immunodeficiency diseases], 0302 clinical medicine, OMIM : Online Mendelian Inheritance in Man, Immunology and Allergy, 2.1 Biological and endogenous factors, Copy-number variation, Primary immunodeficiency disease, whole-exome sequencing, Aetiology, Child, Exome sequencing, Genetics, screening and diagnosis, food and beverages, High-Throughput Nucleotide Sequencing, Genomics, Middle Aged, Settore MED/38, Detection, 030220 oncology & carcinogenesis, Child, Preschool, Medical genetics, Female, Adult, medicine.medical_specialty, Adolescent, DNA Copy Number Variations, Immunology, Biology, 03 medical and health sciences, Young Adult, Rare Diseases, Clinical Research, medicine, Humans, Genetic Testing, Preschool, Aged, Severe combined immunodeficiency, Genetic heterogeneity, Common variable immunodeficiency, Prevention, fungi, Human Genome, Immunologic Deficiency Syndromes, Infant, medicine.disease, 4.1 Discovery and preclinical testing of markers and technologies, 030104 developmental biology, Good Health and Well Being, Primary immunodeficiency, copy number variants
Abstract: WOS: 000393996800025, PubMed: 27577878, Background: Primary immunodeficiency diseases (PIDDs) are clinically and genetically heterogeneous disorders thus far associated with mutations in more than 300 genes. The clinical phenotypes derived from distinct genotypes can overlap. Genetic etiology can be a prognostic indicator of disease severity and can influence treatment decisions. Objective: We sought to investigate the ability of whole-exome screening methods to detect disease-causing variants in patients with PIDDs. Methods: Patients with PIDDs from 278 families from 22 countries were investigated by using whole-exome sequencing. Computational copy number variant (CNV) prediction pipelines and an exome-tiling chromosomal microarray were also applied to identify intragenic CNVs. Analytic approaches initially focused on 475 known or candidate PIDD genes but were nonexclusive and further tailored based on clinical data, family history, and immunophenotyping. Results: A likely molecular diagnosis was achieved in 110 (40%) unrelated probands. Clinical diagnosis was revised in about half (60/ 110) and management was directly altered in nearly a quarter (26/ 110) of families based on molecular findings. Twelve PIDD-causing CNVs were detected, including 7 smaller than 30 Kb that would not have been detected with conventional diagnostic CNV arrays. Conclusion: This high-throughput genomic approach enabled detection of disease-related variants in unexpected genes; permitted detection of low-grade constitutional, somatic, and revertant mosaicism; and provided evidence of a mutational burden in mixed PIDD immunophenotypes., South-Eastern Norway Health Authority; American Women's club of Oslo; National Human Genome Research InstituteUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Human Genome Research Institute (NHGRI); National Heart, Lung, and BloodUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI) [U54HG006542]; Jeffrey Modell Foundation; NIHUnited States Department of Health & Human ServicesNational Institutes of Health (NIH) - USA [AI-120989], Funding for the work performed in Oslo was provided by the South-Eastern Norway Health Authority, and A. S.-P. received research scholarship from the American Women's club of Oslo. The BHCMG is supported by the National Human Genome Research Institute and the National Heart, Lung, and Blood (U54HG006542). Funding was also provided by the Jeffrey Modell Foundation and NIH AI-120989 (to J.S.O.).
Published: 2017

21. Next-generation sequencing for disorders of low and high bone mineral density

Author: Sandesh C.S. Nagamani, E. Lemire, L.-J. Wong, Victor Wei Zhang, Brendan Lee, Carlos A. Bacino, Hong Cui, Philippe M. Campeau, Monica Grover, James T. Lu, Vernon R. Sutton, Richard A. Gibbs, Daniel H. Cohn, Nicola Brunetti-Pierri, Gautam Sule, Brian Dawson, Sule, G, Campeau, Pm, Zhang, Vw, Nagamani, Sc, Dawson, Bc, Grover, M, Bacino, Ca, Sutton, Vr, BRUNETTI PIERRI, Nicola, Lu, Jt, Lemire, E, Gibbs, Ra, Cohn, Dh, Cui, H, Wong, Lj, and Lee, Bh
Subjects: Adult, Male, Pathology, medicine.medical_specialty, Bone density, Sequence analysis, Endocrinology, Diabetes and Metabolism, Computational biology, DNA sequencing, Article, symbols.namesake, Bone Density, medicine, Humans, Genetic Predisposition to Disease, Genetic Testing, Genetic testing, Gene Library, Sanger sequencing, Bone Diseases, Developmental, medicine.diagnostic_test, business.industry, High-Throughput Nucleotide Sequencing, Osteopetrosis, Sequence Analysis, DNA, Osteogenesis Imperfecta, medicine.disease, Ehlers–Danlos syndrome, Osteogenesis imperfecta, Mutation, symbols, Ehlers-Danlos Syndrome, business
Abstract: To achieve an efficient molecular diagnosis of osteogenesis imperfecta (OI), Ehlers–Danlos syndrome (EDS), and osteopetrosis (OPT), we designed a next-generation sequencing (NGS) platform to sequence 34 genes. We validated this platform on known cases and have successfully identified the causative mutation in most patients without a prior molecular diagnosis. Osteogenesis imperfecta, Ehlers–Danlos syndrome, and osteopetrosis are collectively common inherited skeletal diseases. Evaluation of subjects with these conditions often includes molecular testing which has important counseling and therapeutic and sometimes legal implications. Since several different genes have been implicated in these conditions, Sanger sequencing of each gene can be a prohibitively expensive and time-consuming way to reach a molecular diagnosis. In order to circumvent these problems, we have designed and tested a NGS platform that would allow simultaneous sequencing on a single diagnostic platform of different genes implicated in OI, OPT, EDS, and other inherited conditions, leading to low or high bone mineral density. We used a liquid-phase probe library that captures 602 exons (~100 kb) of 34 selected genes and have applied it to test clinical samples from patients with bone disorders. NGS of the captured exons by Illumina HiSeq 2000 resulted in an average coverage of over 900X. The platform was successfully validated by identifying mutations in six patients with known mutations. Moreover, in four patients with OI or OPT without a prior molecular diagnosis, the assay was able to detect the causative mutations. In conclusion, our NGS panel provides a fast and accurate method to arrive at a molecular diagnosis in most patients with inherited high or low bone mineral density disorders.
Published: 2012

22. Somatic mutations affect key pathways in lung adenocarcinoma

Author: Aldi T. Kraja, Brian H. Dunford-Shore, Tittu Mathew, Otis Hall, Barbara A. Weir, Timothy Fennell, William Pao, Jack A. Roth, Alicia Hawes, Heidi Greulich, Steven E. Scherer, Xiaoqi Shi, Giovanni Tonon, Manuel L. Gonzalez-Garay, Yuzhu Tang, Mark B. Orringer, Qunyuan Zhang, Bruce E. Johnson, Li Ding, David G. Beer, Amit Dutt, Margaret R. Spitz, Carrie A. Haipek, Michael A. Province, Yiming Zhu, Liuda Ziaugra, Lucian R. Chirieac, Ken Chen, Rachel Abbott, William D. Travis, George M. Weinstock, Harold E. Varmus, Lucinda Fulton, Daniel C. Koboldt, Kristian Cibulskis, Carrie Sougnez, Christopher S. Sawyer, Richard A. Gibbs, Bradley A. Ozenberger, Thomas J. Giordano, Heather Schmidt, Ling Lin, Jennifer Baldwin, Elaine R. Mardis, Rick Meyer, Tracie L. Miner, David E. Larson, Ignacio I. Wistuba, Jiqiang Yao, Margaret Morgan, Andrew C. Chang, Akihiko Yoshizawa, Shalini N. Jhangiani, Xiaojun Zhao, David A. Wheeler, Stephen R. Broderick, Jody S. Robinson, Kerstin Clerc, Eric S. Lander, Richard K. Wilson, Ginger A. Fewell, Hua Shen, David J. Dooling, Robert S. Fulton, Aleksandar Milosavljevic, John R. Osborne, Gad Getz, Donna M. Muzny, Yanru Ren, Wendy Winckler, Roman K. Thomas, Mark A. Watson, Peter J. Good, Sacha N. Sander, Megan Hanna, Michael D. McLellan, Ginger A. Metcalf, Brian Ng, Michael C. Wendl, Lora Lewis, Seth D. Crosby, Michael C. Zody, Matthew Meyerson, Robert C. Onofrio, Michael S. Lawrence, Marc Ladanyi, Aniko Sabo, Craig Pohl, Stacey Gabriel, Tammi L. Vickery, Ding, L, Getz, G, Wheeler, Da, Mardis, Ea, Mclellan, Md, Cibulskis, K, Sougnez, C, Greulich, H, Muzny, Dm, Morgan, Mb, Fulton, L, Fulton, R, Zhang, Q, Wendl, Mc, Lawrence, M, Larson, De, Chen, K, Dooling, Dj, Sabo, A, Hawes, Ac, Shen, H, Jhangiani, Sh, Lewis, Lr, Hall, O, Zhu, Y, Mathew, T, Ren, Y, Yao, J, Scherer, Se, Clerc, K, Metcalf, Ga, Ng, B, Milosavljevic, A, Gonzalez-Garay, Ml, Osborne, Jr, Meyer, R, Shi, X, Tang, Y, Koboldt, Dc, Lin, L, Abbott, R, Miner, Tl, Pohl, C, Fewell, G, Haipek, C, Schmidt, H, Dunford-Shore, Bh, Kraja, A, Crosby, Sd, Sawyer, C, Vickery, T, Sander, S, Robinson, J, Winckler, W, Baldwin, J, Chirieac, Lr, Dutt, A, Fennell, T, Hanna, M, Johnson, Be, Onofrio, Rc, Thomas, Rk, Tonon, G, Weir, Ba, Zhao, X, Ziaugra, L, Zody, Mc, Giordano, T, Orringer, Mb, Roth, Ja, Spitz, Mr, Wistuba, Ii, Ozenberger, B, Good, Pj, Chang, Ac, Beer, Dg, Watson, Ma, Ladanyi, M, Broderick, S, Yoshizawa, A, Travis, Wd, Pao, W, Province, Ma, Weinstock, Gm, Varmus, He, Gabriel, Sb, Lander, E, Gibbs, Ra, Meyerson, M, and Wilson, Rk.
Subjects: Male, Genetics, Mutation, Lung Neoplasms, Multidisciplinary, Tumor suppressor gene, DNA repair, Gene Dosage, Adenocarcinoma, Bronchiolo-Alveolar, Biology, medicine.disease, medicine.disease_cause, Article, Gene Expression Regulation, Neoplastic, Germline mutation, Proto-Oncogenes, medicine, Humans, Adenocarcinoma, Female, Genes, Tumor Suppressor, Carcinogenesis, Lung cancer, Gene
Abstract: Determining the genetic basis of cancer requires comprehensive analyses of large collections of histopathologically well-classified primary tumours. Here we report the results of a collaborative study to discover somatic mutations in 188 human lung adenocarcinomas. DNA sequencing of 623 genes with known or potential relationships to cancer revealed more than 1,000 somatic mutations across the samples. Our analysis identified 26 genes that are mutated at significantly high frequencies and thus are probably involved in carcinogenesis. The frequently mutated genes include tyrosine kinases, among them the EGFR homologue ERBB4; multiple ephrin receptor genes, notably EPHA3; vascular endothelial growth factor receptor KDR; and NTRK genes. These data provide evidence of somatic mutations in primary lung adenocarcinoma for several tumour suppressor genes involved in other cancers--including NF1, APC, RB1 and ATM--and for sequence changes in PTPRD as well as the frequently deleted gene LRP1B. The observed mutational profiles correlate with clinical features, smoking status and DNA repair defects. These results are reinforced by data integration including single nucleotide polymorphism array and gene expression array. Our findings shed further light on several important signalling pathways involved in lung adenocarcinoma, and suggest new molecular targets for treatment.
Published: 2008

23. The Genome of the Sea Urchin Strongylocentrotus purpuratus

Author: Amro Hamdoun, Virginia Brockton, Huyen Dinh, Qiang Tu, Richard O. Hynes, Maria Ina Arnone, Wratko Hlavina, L. Courtney Smith, Mariano A. Loza, David R. Burgess, Matthew P. Hoffman, Florian Raible, Qiu Autumn Yuan, Geoffrey Okwuonu, Mark Y. Tong, Jennifer Hume, Donna Maglott, Manisha Goel, Olivier Fedrigo, Manuel L. Gonzalez-Garay, Celina E. Juliano, Judith Hernandez, Gary M. Wessel, William F. Marzluff, Audrey J. Majeske, Christian Gache, Louise Duloquin, Xingzhi Song, François Lapraz, Fowler J, Alexandre Souvorov, Jared V. Goldstone, Georgia Panopoulou, Sandra Hines, Kyle M. Judkins, Clay Davis, Christine G. Elsik, Paul Kitts, Mariano Loza-Coll, Greg Wray, Taku Hibino, Eric Röttinger, Allison M. Churcher, Annamaria Locascio, Arcady Mushegian, Masashi Kinukawa, Anna Reade, Katherine M. Buckley, I. R. Gibbons, Bert Gold, Aleksandar Milosavljevic, David Epel, Victor D. Vacquier, Ling Ling Pu, Vincenzo Cavalieri, Erin L. Allgood, Lan Zhang, Lynne V. Nazareth, Constantin N. Flytzanis, Ian Bosdet, Yi-Hsien Su, Zeev Pancer, Matthew L. Rowe, Robert C. Angerer, David R. McClay, William H. Klein, Rachel F. Gray, Julian L. Wong, Shunsuke Yaguchi, Robert Bellé, Aaron J. Mackey, Herath Jayantha Gunaratne, Karl Frederik Bergeron, Bruce P. Brandhorst, Greg Murray, Avis H. Cohen, Stephanie Bell, Kristin Tessmar-Raible, Ian K. Townley, Bertrand Cosson, Thomas D. Glenn, Jongmin Nam, Cynthia A. Bradham, Michael Dean, Joseph Chacko, Anthony J. Robertson, Margherita Branno, Valeria Matranga, K. James Durbin, Esther Miranda, Lili Chen, Eran Elhaik, Robert D. Burke, Rita A. Wright, Paola Oliveri, Sandra L. Lee, Gary W. Moy, Alexander E Primus, Shawn S. McCafferty, Cristina Calestani, David A. Garfield, Erica Sodergren, Karen Wilson, Joel Smith, Marco A. Marra, Cynthia Messier, Julia Morales, Kim D. Pruitt, Rachel Thorn, Rachel Gill, John S. Taylor, Mark E. Hahn, Victor Sapojnikov, Meredith Howard-Ashby, Lynne M. Angerer, Maurice R. Elphick, Kathy R. Foltz, Anne Marie Genevière, Justin T. Reese, Blanca E. Galindo, Kim C. Worley, Andrew Leone, Glen Humphrey, Kevin Berney, Olga Ermolaeva, George Miner, David P. Terwilliger, Elly Suk Hen Chow, Lora Lewis, Dan Graur, C. Titus Brown, Gerard Manning, Kevin J. Peterson, Angela Jolivet, Michele K. Anderson, Francesca Rizzo, Ekaterina Voronina, Thierry Lepage, Giorgio Matassi, Antonio Fernandez-Guerra, Mamoru Nomura, Charles A. Whittaker, James R.R. Whittle, James A. Coffman, George M. Weinstock, Mohammed M. Idris, Ashlan M. Musante, Sebastian D. Fugmann, Katherine D. Walton, Sorin Istrail, Shu-Yu Wu, Cerrissa Hamilton, Jonah Cool, Jacqueline E. Schein, Stacey M. Curry, Athula Wikramanayke, Seth Carbonneau, Blair J. Rossetti, Christopher E. Killian, Melissa J. Landrum, Amanda P. Rawson, Jenifer C. Croce, Ryan C. Range, Rahul Satija, John J. Stegeman, Yufeng Shen, Cavit Agca, Terry Gaasterland, Rocky Cheung, Takae Kiyama, Nikki Adams, Jonathan P. Rast, Robert Piotr Olinski, Andrew Cree, Mark Scally, Shuguang Liang, David A. Parker, Rebecca Thomason, Gretchen E. Hofmann, Michelle M. Roux, Ronghui Xu, Robert A. Obar, Enrique Arboleda, Odile Mulner-Lorillon, Shannon Dugan-Rocha, David J. Bottjer, Gabriele Amore, Manoj P. Samanta, Waraporn Tongprasit, Véronique Duboc, La Ronda Jackson, Fred H. Wilt, Viktor Stolc, Anna T. Neill, Michael Raisch, Pei Yun Lee, Jia L. Song, Margaret Morgan, Brian T. Livingston, Sofia Hussain, Zheng Wei, Bryan J. Cole, Tonya F. Severson, Victor V. Solovyev, Finn Hallböök, Donna M. Muzny, Christine A. Byrum, Albert J. Poustka, Xiuqian Mu, Andrew R. Jackson, Shin Heesun, Euan R. Brown, Nansheng Chen, Patrick Cormier, Ralph Haygood, Pedro Martinez, R. Andrew Cameron, D. Wang, Wendy S. Beane, Eric H. Davidson, Christie Kovar, Hemant Kelkar, Charles A. Ettensohn, Sham V. Nair, Robert L. Morris, Stefan C. Materna, Michael C. Thorndyke, Richard A. Gibbs, Dan O Mellott, Department of Physiology and Biophysics, Stony Brook University [The State University of New York] ( SBU ), Astronomy Unit ( AU ), Queen Mary University of London ( QMUL ), Urban and Industrial Air Quality Group, CSIRO Energy Technology, Commonwealth Scientific and Industrial Research Organisation Energy Technology ( CSIRO Energy Technology ), Commonwealth Scientific and Industrial Research Organisation, Center for Polymer Studies ( CPS ), Boston University [Boston] ( BU ), Physics Department [Boston] ( BU-Physics ), Max Planck Institute for Psycholinguistics, Max-Planck-Institut, Department of Biology [Norton], Wheaton College [Norton], Mathematical Institute [Oxford] ( MI ), University of Oxford [Oxford], Centre for the Analysis of Time Series ( CATS ), London School of Economics and Political Science ( LSE ), Thomas Jefferson National Accelerator Facility ( Jefferson Lab ), Thomas Jefferson National Accelerator Facility, Laboratoire d'Energétique et de Mécanique Théorique Appliquée ( LEMTA ), Université de Lorraine ( UL ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire Evolution, Génomes et Spéciation ( LEGS ), Centre National de la Recherche Scientifique ( CNRS ), Department of Geology, University of Illinois at Urbana-Champaign [Urbana], Department of Electrical and Computer Engineering [Portland] ( ECE ), Portland State University [Portland] ( PSU ), Saint-Gobain Crystals [USA], SAINT-GOBAIN, Institute for Animal Health ( IAH ), Biotechnology and Biological Sciences Research Council, Center for Agricultural Resources Research, Chinese Academy of Sciences [Changchun Branch] ( CAS ), Ipsen Inc. [Milford] ( Ipsen ), IPSEN, Department of Physics [Berkeley], University of California [Berkeley], Institute for Climate and Atmospheric Science [Leeds] ( ICAS ), University of Leeds, Chung-Ang University ( CAU ), Chung-Ang University [Seoul], Antarctic Climate and Ecosystems Cooperative Research Center ( ACE-CRC ), Institute of Aerodynamics and Fluid Mechanics ( AER ), Technische Universität München [München] ( TUM ), Mer et santé ( MS ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Centre National de la Recherche Scientifique ( CNRS ), Imperial College London, Radio and Atmospheric Sciences Division, National Physical Laboratory [Teddington] ( NPL ), International Research Institute for Climate and Society ( IRI ), Earth Institute at Columbia University, Columbia University [New York]-Columbia University [New York], Soils Group, The Macaulay Institute, Department of Haematology, University of Cambridge [UK] ( CAM ), School of Biology and Biochemistry, Queen's University, Leslie Hill Institute for Plant Conservation ( PCU ), University of Cape Town, Institute for Microelectronics and Microsystems/ Istituto per la Microelettronica e Microsistemi ( IMM ), Consiglio Nazionale delle Ricerche ( CNR ), Laboratoire d'acoustique de l'université du Mans ( LAUM ), Le Mans Université ( UM ) -Centre National de la Recherche Scientifique ( CNRS ), Interactive Systems Labs ( ISL ), Carnegie Mellon University [Pittsburgh] ( CMU ), Dalian Institute of Chemical Physics ( DICP ), Architectures, Languages and Compilers to Harness the End of Moore Years ( ALCHEMY ), Laboratoire de Recherche en Informatique ( LRI ), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -CentraleSupélec-Centre National de la Recherche Scientifique ( CNRS ) -Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique ( Inria ), Clean Air Task Force ( CATF ), Clean Air Task Force, Space Physics Laboratory, Indian Space Research Organisation ( ISRO ), Centre d'études et de recherches appliquées à la gestion ( CERAG ), Université Pierre Mendès France - Grenoble 2 ( UPMF ) -Centre National de la Recherche Scientifique ( CNRS ), Department of Microbiology and Immunology, College of Medicine and Health Sciences-Sultan Qaboos University, European Molecular Biology Laboratory [Heidelberg] ( EMBL ), Department of Biostatistics, University of Michigan [Ann Arbor], Department of Radiation Oncology [Michigan] ( Radonc ), Department of Physics and Astronomy [Leicester], University of Leicester, Informatique, Biologie Intégrative et Systèmes Complexes ( IBISC ), Université d'Évry-Val-d'Essonne ( UEVE ) -Centre National de la Recherche Scientifique ( CNRS ), Institut für Meteorologie und Klimaforschung ( IMK ), Karlsruher Institut für Technologie ( KIT ), Physics Department [UNB], University of New Brunswick ( UNB ), Laboratoire Parole et Langage ( LPL ), Centre National de la Recherche Scientifique ( CNRS ) -Aix Marseille Université ( AMU ), Institut des Sciences Chimiques de Rennes ( ISCR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Ecole Nationale Supérieure de Chimie de Rennes-Institut National des Sciences Appliquées ( INSA ) -Centre National de la Recherche Scientifique ( CNRS ), Biogéosciences [Dijon] ( BGS ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Bioprojet, Laboratoire de Matériaux à Porosité Contrôlée ( LMPC ), Université de Haute-Alsace (UHA) Mulhouse - Colmar ( Université de Haute-Alsace (UHA) ) -Ecole Nationale Supérieure de Chimie de Mulhouse-Centre National de la Recherche Scientifique ( CNRS ), School of Information Engineering [USTB] ( SIE ), University of Science and Technology Beijing [Beijing] ( USTB ), Laboratory for Atmospheric and Space Physics [Boulder] ( LASP ), University of Colorado Boulder [Boulder], Department of Applied Mathematics [Sheffield], University of Sheffield [Sheffield], School of Mathematics and Statistics [Sheffield] ( SoMaS ), Laboratoire de Mécanique de Lille - FRE 3723 ( LML ), Université de Lille, Sciences et Technologies-Ecole Centrale de Lille-Centre National de la Recherche Scientifique ( CNRS ), Computer Science Department [UCLA] ( CSD ), University of California at Los Angeles [Los Angeles] ( UCLA ), Développement et évolution ( DE ), Université Paris-Sud - Paris 11 ( UP11 ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de Biologie du Développement de Villefranche sur mer ( LBDV ), Laboratoire Pierre Aigrain ( LPA ), Fédération de recherche du Département de physique de l'Ecole Normale Supérieure - ENS Paris ( FRDPENS ), Centre National de la Recherche Scientifique ( CNRS ) -École normale supérieure - Paris ( ENS Paris ) -Centre National de la Recherche Scientifique ( CNRS ) -École normale supérieure - Paris ( ENS Paris ) -Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), Department of Mathematics and Statistics [Mac Gill], McGill University, Departamento de Botánica [Comahue], Universidad nacional del Comahue, Bioénergétique Cellulaire et Pathologique ( BECP ), Université Joseph Fourier - Grenoble 1 ( UJF ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ), Environnements et Paléoenvironnements OCéaniques ( EPOC ), Observatoire aquitain des sciences de l'univers ( OASU ), Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers ( INSU - CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -École pratique des hautes études ( EPHE ) -Centre National de la Recherche Scientifique ( CNRS ), Institut Jacques Monod ( IJM ), Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratori Nazionali del Sud ( LNS ), National Institute for Nuclear Physics ( INFN ), Departament de Matemàtiques [Barcelona], Universitat Autònoma de Barcelona [Barcelona] ( UAB ), Max-Planck-Institut für Kohlenforschung (coal research), Institute of Oceanology [CAS] ( IOCAS ), National Chiao Tung University ( NCTU ), Department of Hydrology and Water Resources ( HWR ), University of Arizona, Centre for Educational Technology, Environment Department [York], University of York [York, UK], State Key Laboratory of Nuclear Physics and Technology ( SKL-NPT ), Peking University [Beijing], Department of Physics and Astronomy [Iowa City], University of Iowa [Iowa], NASA Ames Research Center ( ARC ), Department of Materials, Digital Language & Knowledge Contents Research Association ( DICORA ), Hankuk University of Foreign Studies, Department of Physics [Coventry], University of Warwick [Coventry], Space Science and Technology Department [Didcot] ( RAL Space ), STFC Rutherford Appleton Laboratory ( RAL ), Science and Technology Facilities Council ( STFC ) -Science and Technology Facilities Council ( STFC ), Institut de biologie et chimie des protéines [Lyon] ( IBCP ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ), H M Nautical Almanac Office [RAL] ( HMNAO ), Rutherford Appleton Laboratory, United Kingdom Met Office [Exeter], University College of London [London] ( UCL ), Department of Pathology and Laboratory Medicine [UCLA], University of California at Los Angeles [Los Angeles] ( UCLA ) -School of Medicine, School of Earth and Environmental Sciences [Seoul] ( SEES ), Seoul National University [Seoul], Department of Chemistry, Seoul Women's University, MicroMachines Centre ( MMC ), Nanyang Technological University [Singapour], Regroupement Québécois sur les Matériaux de Pointe ( RQMP ), École Polytechnique de Montréal ( EPM ) -Université de Sherbrooke [Sherbrooke]-McGill University-Université de Montréal-Fonds Québécois de Recherche sur la Nature et les Technologies ( FQRNT ), Département de Physique [Montréal], Université de Montréal, School of Earth and Environment [Leeds] ( SEE ), Centre for Ecology and Hydrology ( CEH ), Natural Environment Research Council ( NERC ), Norwegian Institute for Water Research ( NIVA ), Norwegian Institute for Water Research, Stony Brook University [SUNY] (SBU), State University of New York (SUNY)-State University of New York (SUNY), Astronomy Unit [London] (AU), Queen Mary University of London (QMUL), Commonwealth Scientific and Industrial Research Organisation Energy Technology (CSIRO Energy Technology), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Department of Biochemistry and Molecular Biology [Houston], The University of Texas Medical School at Houston, Mathematical Institute [Oxford] (MI), University of Oxford, Centre for the Analysis of Time Series (CATS), London School of Economics and Political Science (LSE), Thomas Jefferson National Accelerator Facility (Jefferson Lab), Laboratoire Énergies et Mécanique Théorique et Appliquée (LEMTA ), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Evolution, Génomes et Spéciation (LEGS), Centre National de la Recherche Scientifique (CNRS), University of Illinois System-University of Illinois System, Department of Electrical and Computer Engineering [Portland] (ECE), Portland State University [Portland] (PSU), Saint-Gobain, Institute for Animal Health (IAH), Biotechnology and Biological Sciences Research Council (BBSRC), Chinese Academy of Sciences [Changchun Branch] (CAS), Ipsen Inc. [Milford] (Ipsen), University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC), Institute for Climate and Atmospheric Science [Leeds] (ICAS), School of Earth and Environment [Leeds] (SEE), University of Leeds-University of Leeds, Chung-Ang University (CAU), Antarctic Climate and Ecosystems Cooperative Research Centre (ACE-CRC), Institute of Aerodynamics and Fluid Mechanics (AER), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Mer et santé (MS), Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), National Physical Laboratory [Teddington] (NPL), International Research Institute for Climate and Society (IRI), Macaulay Institute, University of Cambridge [UK] (CAM), Queen's University [Kingston, Canada], Leslie Hill Institute for Plant Conservation (PCU), Istituto per la Microelettronica e Microsistemi [Catania] (IMM), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Laboratoire d'Acoustique de l'Université du Mans (LAUM), Le Mans Université (UM)-Centre National de la Recherche Scientifique (CNRS), Interactive Systems Labs (ISL), Carnegie Mellon University [Pittsburgh] (CMU), Dalian Institute of Chemical Physics (DICP), Architectures, Languages and Compilers to Harness the End of Moore Years (ALCHEMY), Laboratoire de Recherche en Informatique (LRI), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Clean Air Task Force (CATF), Indian Space Research Organisation (ISRO), Centre d'études et de recherches appliquées à la gestion (CERAG), Université Pierre Mendès France - Grenoble 2 (UPMF)-Centre National de la Recherche Scientifique (CNRS), Sultan Qaboos University (SQU)-College of Medicine and Health Sciences [Baylor], Baylor University-Baylor University, European Molecular Biology Laboratory [Heidelberg] (EMBL), University of Michigan System-University of Michigan System, Department of Radiation Oncology [Michigan] (Radonc), Informatique, Biologie Intégrative et Systèmes Complexes (IBISC), Université d'Évry-Val-d'Essonne (UEVE)-Centre National de la Recherche Scientifique (CNRS), Institute for Meteorology and Climate Research (IMK), Karlsruhe Institute of Technology (KIT), University of New Brunswick (UNB), Laboratoire Parole et Langage (LPL), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Institut des Sciences Chimiques de Rennes (ISCR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Biogéosciences [UMR 6282] (BGS), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Matériaux à Porosité Contrôlée (LMPC), Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS), School of Information Engineering [USTB] (SIE), University of Science and Technology Beijing [Beijing] (USTB), Laboratory for Atmospheric and Space Physics [Boulder] (LASP), University of Colorado [Boulder], School of Mathematics and Statistics [Sheffield] (SoMaS), Laboratoire de Mécanique de Lille - FRE 3723 (LML), Université de Lille, Sciences et Technologies-Centrale Lille-Centre National de la Recherche Scientifique (CNRS), Computer Science Department [UCLA] (CSD), University of California [Los Angeles] (UCLA), Développement et évolution (DE), Université Paris-Sud - Paris 11 (UP11)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Biologie du Développement de Villefranche sur mer (LBDV), Observatoire océanologique de Villefranche-sur-mer (OOVM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Pierre Aigrain (LPA), Fédération de recherche du Département de physique de l'Ecole Normale Supérieure - ENS Paris (FRDPENS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Department of Mathematics and Statistics [Montréal], McGill University = Université McGill [Montréal, Canada], Departamento de Botánica [Bariloche], Centro Regional Universitario Bariloche [Bariloche] (CRUB), Universidad Nacional del Comahue [Neuquén] (UNCOMA)-Universidad Nacional del Comahue [Neuquén] (UNCOMA), Bioénergétique Cellulaire et Pathologique (BECP), Université Joseph Fourier - Grenoble 1 (UJF)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Environnements et Paléoenvironnements OCéaniques (EPOC), Observatoire aquitain des sciences de l'univers (OASU), Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1 (UB)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Institut Jacques Monod (IJM (UMR_7592)), Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Laboratori Nazionali del Sud (LNS), Istituto Nazionale di Fisica Nucleare (INFN), Departament de Matemàtiques [Barcelona] (UAB), Universitat Autònoma de Barcelona (UAB), Max-Planck-Institut für Kohlenforschung (Coal Research), Max-Planck-Gesellschaft, CAS Institute of Oceanology (IOCAS), Chinese Academy of Sciences [Beijing] (CAS), National Chiao Tung University (NCTU), Department of Hydrology and Water Resources (HWR), State Key Laboratory of Nuclear Physics and Technology (SKL-NPT), University of Iowa [Iowa City], NASA Ames Research Center (ARC), Digital Language & Knowledge Contents Research Association (DICORA), Space Science and Technology Department [Didcot] (RAL Space), STFC Rutherford Appleton Laboratory (RAL), Science and Technology Facilities Council (STFC)-Science and Technology Facilities Council (STFC), Institut de biologie et chimie des protéines [Lyon] (IBCP), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), H M Nautical Almanac Office [RAL] (HMNAO), University College of London [London] (UCL), University of California (UC)-University of California (UC)-School of Medicine, School of Earth and Environmental Sciences [Seoul] (SEES), Seoul National University [Seoul] (SNU), MicroMachines Centre (MMC), Regroupement Québécois sur les Matériaux de Pointe (RQMP), École Polytechnique de Montréal (EPM)-Université de Sherbrooke (UdeS)-McGill University = Université McGill [Montréal, Canada]-Université de Montréal (UdeM)-Fonds Québécois de Recherche sur la Nature et les Technologies (FQRNT), Université de Montréal (UdeM), Centre for Ecology and Hydrology (CEH), Natural Environment Research Council (NERC), Norwegian Institute for Water Research (NIVA), SEA URCHIN GENOME SEQUENCING CONSORTIUM, SODERGREN E, WEINSTOCK GM, DAVIDSON EH, CAMERON RA, GIBBS RA, ANGERER RC, ANGERER LM, ARNONE MI, BURGESS DR, BURKE RD, COFFMAN JA, DEAN M, ELPHICK MR, ETTENSOHN CA, FOLTZ KR, HAMDOUN A, HYNES RO, KLEIN WH, MARZLUFF W, MCCLAY DR, MORRIS RL, MUSHEGIAN A, RAST JP, SMITH LC, THORNDYKE MC, VACQUIER VD, WESSEL GM, WRAY G, ZHANG L, ELSIK CG, ERMOLAEVA O, HLAVINA W, HOFMANN G, KITTS P, LANDRUM MJ, MACKEY AJ, MAGLOTT D, PANOPOULOU G, POUSTKA AJ, PRUITT K, SAPOJNIKOV V, SONG X, SOUVOROV A, SOLOVYEV V, WEI Z, WHITTAKER CA, WORLEY K, DURBIN KJ, SHEN Y, FEDRIGO O, GARFIELD D, HAYGOOD R, PRIMUS A, SATIJA R, SEVERSON T, GONZALEZ-GARAY ML, JACKSON AR, MILOSAVLJEVIC A, TONG M, KILLIAN CE, LIVINGSTON BT, WILT FH, ADAMS N, BELLE R, CARBONNEAU S, CHEUNG R, CORMIER P, COSSON B, CROCE J, FERNANDEZ-GUERRA A, GENEVIERE AM, GOEL M, KELKAR H, MORALES J, MULNER-LORILLON O, ROBERTSON AJ, GOLDSTONE JV, COLE B, EPEL D, GOLD B, HAHN ME, HOWARD-ASHBY M, SCALLY M, STEGEMAN JJ, ALLGOOD EL, COOL J, JUDKINS KM, MCCAFFERTY SS, MUSANTE AM, OBAR RA, RAWSON AP, ROSSETTI BJ, GIBBONS IR, HOFFMAN MP, LEONE A, ISTRAIL S, MATERNA SC, SAMANTA MP, STOLC V, TONGPRASIT W, TU Q, BERGERON KF, BRANDHORST BP, WHITTLE J, BERNEY K, BOTTJER DJ, CALESTANI C, PETERSON K, CHOW E, YUAN QA, ELHAIK E, GRAUR D, REESE JT, BOSDET I, HEESUN S, MARRA MA, SCHEIN J, ANDERSON MK, BROCKTON V, BUCKLEY KM, COHEN AH, FUGMANN SD, HIBINO T, LOZA-COLL M, MAJESKE AJ, MESSIER C, NAIR SV, PANCER Z, TERWILLIGER DP, AGCA C, ARBOLEDA E, CHEN N, CHURCHER AM, HALLBOOK F, HUMPHREY GW, IDRIS MM, KIYAMA T, LIANG S, MELLOTT D, MU X, MURRAY G, OLINSKI RP, RAIBLE F, ROWE M, TAYLOR JS, TESSMAR-RAIBLE K, WANG D, WILSON KH, YAGUCHI S, GAASTERLAND T, GALINDO BE, GUNARATNE HJ, JULIANO C, KINUKAWA M, MOY GW, NEILL AT, NOMURA M, RAISCH M, READE A, ROUX MM, SONG JL, SU YH, TOWNLEY IK, VORONINA E, WONG JL, AMORE G, BRANNO M, BROWN ER, CAVALIERI, V, DUBOC V, DULOQUIN L, FLYTZANIS C, GACHE C, LAPRAZ F, LEPAGE T, LOCASCIO A, MART, University of California-University of California, Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Consiglio Nazionale delle Ricerche (CNR), Centre National de la Recherche Scientifique (CNRS)-Le Mans Université (UM), Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Biogéosciences [UMR 6282] [Dijon] (BGS), Centre National de la Recherche Scientifique (CNRS)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Ecole Nationale Supérieure de Chimie de Mulhouse-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Fédération de recherche du Département de physique de l'Ecole Normale Supérieure - ENS Paris (FRDPENS), Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE), University of California-University of California-School of Medicine, Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Ecole Nationale Supérieure de Chimie de Rennes (ENSCR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS), Université de Lille, Sciences et Technologies-Centre National de la Recherche Scientifique (CNRS)-Centrale Lille, Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Joseph Fourier - Grenoble 1 (UJF), University of Manchester Institute of Science and Technology (UMIST), Condensed Matter Physics and Materials Science Department, Brookhaven National Laboratory, Brookhaven National Laboratory [Upton, NY] (BNL), UT-Battelle, LLC-Stony Brook University [SUNY] (SBU), State University of New York (SUNY)-State University of New York (SUNY)-U.S. Department of Energy [Washington] (DOE)-UT-Battelle, LLC-Stony Brook University [SUNY] (SBU), State University of New York (SUNY)-State University of New York (SUNY)-U.S. Department of Energy [Washington] (DOE), Baylor College of Medicine (BCM), Baylor University, Laboratoire de Traitement de l'Information Medicale (LaTIM), Université européenne de Bretagne - European University of Brittany (UEB)-Université de Brest (UBO)-Télécom Bretagne-Institut Mines-Télécom [Paris] (IMT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Laboratoire de Modélisation et Simulation Multi Echelle (MSME), Université Paris-Est Marne-la-Vallée (UPEM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS), Duke University [Durham], Instituto Andaluz de Geofísica y Prevención de Desastres Sísmicos [Granada] (IAGPDS), Universidad de Granada (UGR), Laboratoire d'Ingénierie des Matériaux de Bretagne (LIMATB), Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université de Brest (UBO), University of New South Wales [Sydney] (UNSW), Celera Genomics (CRA), Celera Genomics, Paléobiodiversité et paléoenvironnements, Muséum national d'Histoire naturelle (MNHN)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Università degli Studi di Roma Tor Vergata [Roma], Unité de recherches forestières (BORDX PIERR UR ), Institut National de la Recherche Agronomique (INRA), Deptartment of Neuroscience, Uppsala University, State Key Laboratory of Palaeobiology and Stratigraphy, Nanjing Institute of Geology and Palaeontology (NIGPAS-CAS), Chinese Academy of Sciences [Nanjing Branch]-Chinese Academy of Sciences [Nanjing Branch], Institut Méditerranéen d'Ecologie et de Paléoécologie (IMEP), Université Paul Cézanne - Aix-Marseille 3-Université de Provence - Aix-Marseille 1-Avignon Université (AU)-Centre National de la Recherche Scientifique (CNRS), Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China, Université Paris Diderot - Paris 7 (UPD7), Department of Physical and Environmental Sciences [Toronto], University of Toronto at Scarborough, inconnu temporaire UPEMLV, Inconnu, Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Department of Atmospheric Sciences [Seattle], University of Washington [Seattle], National Institute of Advanced Industrial Science and Technology (AIST), Department of Pharmacy, Università degli studi di Genova = University of Genoa (UniGe), Interdisciplinary Arts and Sciences Department, St. Vincent's Hospital, Sydney, Laboratoire des Sciences de l'Environnement Marin (LEMAR) (LEMAR), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Department of Electrical Engineering (DEE-POSTECH), Pohang University of Science and Technology (POSTECH), Centre Suisse d'Electronique et de Microtechnique SA [Neuchatel] (CSEM), Centre Suisse d'Electronique et Microtechnique SA (CSEM), Human Genome Sequencing Center [Houston] (HGSC), Brookhaven National Laboratory, Meteorological Service of Canada, 4905 Dufferin Street, Université européenne de Bretagne - European University of Brittany (UEB)-Télécom Bretagne-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Mines-Télécom [Paris] (IMT), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Paris-Est Marne-la-Vallée (UPEM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Unité de Recherches Forestières, Department of Physical and Environmental Sciences, University of Toronto [Scarborough, Canada], National Institute for Nuclear Physics (INFN), University of Genoa (UNIGE), Institut de Recherche pour le Développement (IRD)-Institut Universitaire Européen de la Mer (IUEM), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université de Brest (UBO)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Universidad de Granada = University of Granada (UGR), Laboratoire d'Energétique et de Mécanique Théorique Appliquée (LEMTA ), Technische Universität München [München] (TUM), Queen's University [Kingston], Centre National de la Recherche Scientifique (CNRS)-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Grenoble Alpes (UGA), Institut für Meteorologie und Klimaforschung (IMK), Karlsruher Institut für Technologie (KIT), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Ecole Nationale Supérieure de Chimie de Rennes-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES), Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Ecole Centrale de Lille-Université de Lille, Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Sciences et Technologies - Bordeaux 1-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE)-Centre National de la Recherche Scientifique (CNRS), Universitat Autònoma de Barcelona [Barcelona] (UAB), École Polytechnique de Montréal (EPM)-Université de Sherbrooke [Sherbrooke]-Université de Montréal [Montréal]-McGill University-Fonds Québécois de Recherche sur la Nature et les Technologies (FQRNT), Université de Montréal [Montréal], U.S. Department of Energy [Washington] (DOE)-UT-Battelle, LLC-Stony Brook University [SUNY] (SBU), Université de Bretagne Sud (UBS)-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université de Brest (UBO)-Université de Brest (UBO), Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC), Université Paul Cézanne - Aix-Marseille 3-Centre National de la Recherche Scientifique (CNRS)-Avignon Université (AU)-Université de Provence - Aix-Marseille 1, Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Centre National de la Recherche Scientifique (CNRS)-Université de Brest (UBO), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Lille, Sciences et Technologies-Ecole Centrale de Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Male, MESH: Signal Transduction, MESH: Sequence Analysis, DNA, MESH : Transcription Factors, MESH : Calcification, Physiologic, Genome, MESH : Proteins, 0302 clinical medicine, MESH : Embryonic Development, MESH: Gene Expression Regulation, Developmental, Innate, MESH: Embryonic Development, Developmental, Nervous System Physiological Phenomena, MESH: Animals, MESH: Proteins, [SDV.BDD]Life Sciences [q-bio]/Development Biology, Complement Activation, ComputingMilieux_MISCELLANEOUS, MESH: Evolution, Molecular, MESH : Strongylocentrotus purpuratus, Genetics, 0303 health sciences, MESH: Nervous System Physiological Phenomena, Multidisciplinary, biology, Medicine (all), MESH: Immunologic Factors, Gene Expression Regulation, Developmental, Genome project, MESH: Transcription Factors, MESH : Immunity, Innate, MESH : Complement Activation, MESH: Genes, Bacterial artificial chromosome (BAC)DeuterostomesStrongylocentrotus purpuratusVertebrate innovations, Echinoderm, MESH : Nervous System Physiological Phenomena, embryonic structures, MESH: Cell Adhesion Molecules, MESH : Genes, MESH: Immunity, Innate, Sequence Analysis, Signal Transduction, MESH: Computational Biology, Genome evolution, MESH: Complement Activation, Sequence analysis, Evolution, MESH: Strongylocentrotus purpuratus, MESH : Male, Embryonic Development, MESH : Immunologic Factors, Article, MESH: Calcification, Physiologic, Calcification, MESH : Cell Adhesion Molecules, Evolution, Molecular, 03 medical and health sciences, Calcification, Physiologic, Animals, Immunologic Factors, MESH: Genome, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, MESH : Evolution, Molecular, Physiologic, Gene, Strongylocentrotus purpuratus, [ SDV.BBM ] Life Sciences [q-bio]/Biochemistry, Molecular Biology, 030304 developmental biology, MESH : Signal Transduction, Bacterial artificial chromosome, Immunity, Molecular, Computational Biology, Proteins, Cell Adhesion Molecules, Genes, Immunity, Innate, Transcription Factors, Sequence Analysis, DNA, DNA, biology.organism_classification, MESH: Male, Gene Expression Regulation, MESH : Animals, MESH : Gene Expression Regulation, Developmental, MESH : Genome, 030217 neurology & neurosurgery, MESH : Computational Biology, MESH : Sequence Analysis, DNA
Abstract: We report the sequence and analysis of the 814-megabase genome of the sea urchin Strongylocentrotus purpuratus , a model for developmental and systems biology. The sequencing strategy combined whole-genome shotgun and bacterial artificial chromosome (BAC) sequences. This use of BAC clones, aided by a pooling strategy, overcame difficulties associated with high heterozygosity of the genome. The genome encodes about 23,300 genes, including many previously thought to be vertebrate innovations or known only outside the deuterostomes. This echinoderm genome provides an evolutionary outgroup for the chordates and yields insights into the evolution of deuterostomes.
Published: 2006

24. Correction: Multilocus pathogenic variants contribute to intrafamilial clinical heterogeneity: a retrospective study of sibling pairs with neurodevelopmental disorders.

Author: Bozkurt-Yozgatli T, Pehlivan D, Gibbs RA, Sezerman U, Posey JE, Lupski JR, and Coban-Akdemir Z
Published: 2024
Full Text: View/download PDF

25. Whole genome sequencing based analysis of inflammation biomarkers in the Trans-Omics for Precision Medicine (TOPMed) consortium.

Author: Jiang MZ, Gaynor SM, Li X, Van Buren E, Stilp A, Buth E, Wang FF, Manansala R, Gogarten SM, Li Z, Polfus LM, Salimi S, Bis JC, Pankratz N, Yanek LR, Durda P, Tracy RP, Rich SS, Rotter JI, Mitchell BD, Lewis JP, Psaty BM, Pratte KA, Silverman EK, Kaplan RC, Avery C, North KE, Mathias RA, Faraday N, Lin H, Wang B, Carson AP, Norwood AF, Gibbs RA, Kooperberg C, Lundin J, Peters U, Dupuis J, Hou L, Fornage M, Benjamin EJ, Reiner AP, Bowler RP, Lin X, Auer PL, and Raffield LM
Subjects: Humans, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genetic Predisposition to Disease, Female, Interleukin-6 genetics, Precision Medicine methods, Biomarkers, Inflammation genetics, Genome-Wide Association Study methods, Whole Genome Sequencing methods
Abstract: Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38 465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program (with varying sample size by trait, where the minimum sample size was n = 737 for MMP-1). We identified 22 distinct single-variant associations across 6 traits-E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin-that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
Published: 2024
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26. Inverted triplications formed by iterative template switches generate structural variant diversity at genomic disorder loci.

Author: Grochowski CM, Bengtsson JD, Du H, Gandhi M, Lun MY, Mehaffey MG, Park K, Höps W, Benito E, Hasenfeld P, Korbel JO, Mahmoud M, Paulin LF, Jhangiani SN, Hwang JP, Bhamidipati SV, Muzny DM, Fatih JM, Gibbs RA, Pendleton M, Harrington E, Juul S, Lindstrand A, Sedlazeck FJ, Pehlivan D, Lupski JR, and Carvalho CMB
Subjects: Humans, Comparative Genomic Hybridization, Genomic Structural Variation genetics, Genome, Human genetics, Gene Duplication genetics, Haplotypes genetics
Abstract: The duplication-triplication/inverted-duplication (DUP-TRP/INV-DUP) structure is a complex genomic rearrangement (CGR). Although it has been identified as an important pathogenic DNA mutation signature in genomic disorders and cancer genomes, its architecture remains unresolved. Here, we studied the genomic architecture of DUP-TRP/INV-DUP by investigating the DNA of 24 patients identified by array comparative genomic hybridization (aCGH) on whom we found evidence for the existence of 4 out of 4 predicted structural variant (SV) haplotypes. Using a combination of short-read genome sequencing (GS), long-read GS, optical genome mapping, and single-cell DNA template strand sequencing (strand-seq), the haplotype structure was resolved in 18 samples. The point of template switching in 4 samples was shown to be a segment of ∼2.2-5.5 kb of 100% nucleotide similarity within inverted repeat pairs. These data provide experimental evidence that inverted low-copy repeats act as recombinant substrates. This type of CGR can result in multiple conformers generating diverse SV haplotypes in susceptible dosage-sensitive loci., Competing Interests: Declaration of interests Baylor College of Medicine and Miraca Holdings have formed a joint venture with shared ownership and governance of BG, which performs clinical microarray analysis, clinical ES, and clinical biochemical studies. J.R.L. serves on the scientific advisory board of the BG. J.R.L. has stock ownership in 23andMe, is a paid consultant for Genomics International, and is a co-inventor on multiple US and European patents related to molecular diagnostics for inherited neuropathies, eye diseases, genomic disorders, and bacterial genomic fingerprinting. E.H. and S.J. are employees of ONT and shareholders and/or share option holders of ONT. D.P. provides consulting services for Ionis Pharmaceuticals. F.J.S. receives research support from Genetech, Illumina, Pacbio, and ONT., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
Published: 2024
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27. Frequency of pharmacogenomic variation and medication exposures among All of Us Participants.

Author: Haddad A, Radhakrishnan A, McGee S, Smith JD, Karnes JH, Venner E, Wheeler MM, Patterson K, Walker K, Kalra D, Kalla SE, Wang Q, Gibbs RA, Jarvik GP, Sanchez J, Musick A, Ramirez AH, Denny JC, and Empey PE
Abstract: Pharmacogenomics promises improved outcomes through individualized prescribing. However, the lack of diversity in studies impedes clinical translation and equitable application of precision medicine. We evaluated the frequencies of PGx variants, predicted phenotypes, and medication exposures using whole genome sequencing and EHR data from nearly 100k diverse All of Us Research Program participants. We report 100% of participants carried at least one pharmacogenomics variant and nearly all (99.13%) had a predicted phenotype with prescribing recommendations. Clinical impact was high with over 20% having both an actionable phenotype and a prior exposure to an impacted medication with pharmacogenomic prescribing guidance. Importantly, we also report hundreds of alleles and predicted phenotypes that deviate from known frequencies and/or were previously unreported, including within admixed American and African ancestry groups.
Published: 2024
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28. Author Correction: The frequency of pathogenic variation in the All of Us cohort reveals ancestry-driven disparities.

Author: Venner E, Patterson K, Kalra D, Wheeler MM, Chen YJ, Kalla SE, Yuan B, Karnes JH, Walker K, Smith JD, McGee S, Radhakrishnan A, Haddad A, Empey PE, Wang Q, Lichtenstein L, Toledo D, Jarvik G, Musick A, and Gibbs RA
Published: 2024
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29. Empowering personalized pharmacogenomics with generative AI solutions.

Author: Murugan M, Yuan B, Venner E, Ballantyne CM, Robinson KM, Coons JC, Wang L, Empey PE, and Gibbs RA
Subjects: Humans, Artificial Intelligence, Knowledge Bases, Information Storage and Retrieval methods, Pharmacogenomic Testing, Precision Medicine, Pharmacogenetics
Abstract: Objective: This study evaluates an AI assistant developed using OpenAI's GPT-4 for interpreting pharmacogenomic (PGx) testing results, aiming to improve decision-making and knowledge sharing in clinical genetics and to enhance patient care with equitable access., Materials and Methods: The AI assistant employs retrieval-augmented generation (RAG), which combines retrieval and generative techniques, by harnessing a knowledge base (KB) that comprises data from the Clinical Pharmacogenetics Implementation Consortium (CPIC). It uses context-aware GPT-4 to generate tailored responses to user queries from this KB, further refined through prompt engineering and guardrails., Results: Evaluated against a specialized PGx question catalog, the AI assistant showed high efficacy in addressing user queries. Compared with OpenAI's ChatGPT 3.5, it demonstrated better performance, especially in provider-specific queries requiring specialized data and citations. Key areas for improvement include enhancing accuracy, relevancy, and representative language in responses., Discussion: The integration of context-aware GPT-4 with RAG significantly enhanced the AI assistant's utility. RAG's ability to incorporate domain-specific CPIC data, including recent literature, proved beneficial. Challenges persist, such as the need for specialized genetic/PGx models to improve accuracy and relevancy and addressing ethical, regulatory, and safety concerns., Conclusion: This study underscores generative AI's potential for transforming healthcare provider support and patient accessibility to complex pharmacogenomic information. While careful implementation of large language models like GPT-4 is necessary, it is clear that they can substantially improve understanding of pharmacogenomic data. With further development, these tools could augment healthcare expertise, provider productivity, and the delivery of equitable, patient-centered healthcare services., (© The Author(s) 2024. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
Published: 2024
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30. Validation of Single-Nucleotide Mosaic Variants Through Droplet Digital PCR.

Author: Grochowski CM, Gibbs RA, and Doddapaneni H
Subjects: Humans, Mosaicism, Fluorescent Dyes chemistry, High-Throughput Nucleotide Sequencing methods, Polymorphism, Single Nucleotide genetics, Polymerase Chain Reaction methods
Abstract: The detection, validation, and subsequent interpretation of potentially mosaic single-nucleotide variants (SNV) within next-generation sequencing data remains a challenge in both research and clinical laboratory settings. The ability to identify mosaic variants in high genome coverage sequencing data at levels of ≤1% underscores the necessity for developing guidelines and best practices to verify these variants orthogonally. Droplet digital PCR (ddPCR) has proven to be a powerful and precise method that allows for the determination of low-level variant fractions within a given sample. Herein we describe two precise ddPCR methods using either a fluorescent TaqMan hydrolysis probe approach or an EvaGreen fluorescent dye protocol. The TaqMan approach relies on two different fluorescent probes (FAM and HEX/VIC), each designed to amplify selectively only in the presence of a single nucleotide change denoting the variant or reference position. The fractional abundance is then calculated to determine the relative quantities of both alleles in the final sample. The EvaGreen protocol relies on two independent reactions with oligonucleotide primers designed with the single nucleotide change denoting the variant at the penultimate position of the primer. The relative amplification efficiency of both primer sets (reference and variant) can be compared to determine the mosaic level of a given variant. As the cost of high-coverage sequencing continues to decrease, the identification of potentially mosaic variants will also increase. The approaches outlined will allow clinicians and researchers a more precise determination of the true mosaic level of a given variant allowing them to better assess not only its potential pathogenicity but also its possible recurrence risk when offering genetic counseling to families. © 2024 Wiley Periodicals LLC. Basic Protocol: Droplet digital PCR (ddPCR) with TaqMan hydrolysis probes Alternate Protocol: EvaGreen oligonucleotide-specific ddPCR., (© 2024 Wiley Periodicals LLC.)
Published: 2024
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31. The Cancer Genome Atlas Comprehensive Molecular Characterization of Renal Cell Carcinoma.

Author: Ricketts CJ, De Cubas AA, Fan H, Smith CC, Lang M, Reznik E, Bowlby R, Gibb EA, Akbani R, Beroukhim R, Bottaro DP, Choueiri TK, Gibbs RA, Godwin AK, Haake S, Hakimi AA, Henske EP, Hsieh JJ, Ho TH, Kanchi RS, Krishnan B, Kwiatkowski DJ, Liu W, Merino MJ, Mills GB, Myers J, Nickerson ML, Reuter VE, Schmidt LS, Shelley CS, Shen H, Shuch B, Signoretti S, Srinivasan R, Tamboli P, Thomas G, Vincent BG, Vocke CD, Wheeler DA, Yang L, Kim WY, Robertson AG, Spellman PT, Rathmell WK, and Linehan WM
Published: 2024
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32. Somatic mutations of esophageal adenocarcinoma: a comparison between Black and White patients.

Author: Lim H, Gingras MC, Zhao J, Byun J, Castro PD, Tsavachidis S, Hu J, Doddapaneni H, Han Y, Muzny DM, Gibbs RA, Amos CI, and Thrift AP
Subjects: Female, Humans, Male, Mutation, Black or African American, White, Exome Sequencing, Adenocarcinoma genetics, Adenocarcinoma pathology, Esophageal Neoplasms genetics, Esophageal Neoplasms pathology
Abstract: Esophageal adenocarcinoma is the most common histological subtype of esophageal cancer in Western countries and shows poor prognosis with rapid growth. EAC is characterized by a strong male predominance and racial disparity. EAC is up to fivefold more common among Whites than Blacks, yet Black patients with EAC have poorer survival rates. The racial disparity remains largely unknown, and there is limited knowledge of mutations in EAC regarding racial disparities. We used whole-exome sequencing to show somatic mutation profiles derived from tumor samples from 18 EAC male patients. We identified three molecular subgroups based on the pre-defined esophageal cancer-specific mutational signatures. Group 1 is associated with age and NTHL1 deficiency-related signatures. Group 2 occurs primarily in Black patients and is associated with signatures related to DNA damage from oxidative stress and NTHL1 deficiency-related signatures. Group 3 is associated with defective homologous recombination-based DNA often caused by BRCA mutation in White patients. We observed significantly mutated race related genes (LCE2B in Black, SDR39U1 in White) were (q-value < 0.1). Our findings underscore the possibility of distinct molecular mutation patterns in EAC among different races. Further studies are needed to validate our findings, which could contribute to precision medicine in EAC., (© 2024. The Author(s).)
Published: 2024
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33. Multilocus pathogenic variants contribute to intrafamilial clinical heterogeneity: a retrospective study of sibling pairs with neurodevelopmental disorders.

Author: Bozkurt-Yozgatli T, Pehlivan D, Gibbs RA, Sezerman U, Posey JE, Lupski JR, and Coban-Akdemir Z
Subjects: Humans, Retrospective Studies, Homozygote, Polymorphism, Single Nucleotide, Biological Variation, Population, Genotype, Siblings, Genome, Human
Abstract: Background: Multilocus pathogenic variants (MPVs) are genetic changes that affect multiple gene loci or regions of the genome, collectively leading to multiple molecular diagnoses. MPVs may also contribute to intrafamilial phenotypic variability between affected individuals within a nuclear family. In this study, we aim to gain further insights into the influence of MPVs on a disease manifestation in individual research subjects and explore the complexities of the human genome within a familial context., Methods: We conducted a systematic reanalysis of exome sequencing data and runs of homozygosity (ROH) regions of 47 sibling pairs previously diagnosed with various neurodevelopmental disorders (NDD)., Results: We found siblings with MPVs driven by long ROH regions in 8.5% of families (4/47). The patients with MPVs exhibited significantly higher F ROH values (p-value = 1.4e-2) and larger total ROH length (p-value = 1.8e-2). Long ROH regions mainly contribute to this pattern; the siblings with MPVs have a larger total size of long ROH regions than their siblings in all families (p-value = 6.9e-3). Whereas the short ROH regions in the siblings with MPVs are lower in total size compared to their sibling pairs with single locus pathogenic variants (p-value = 0.029), and there are no statistically significant differences in medium ROH regions between sibling pairs (p-value = 0.52)., Conclusion: This study sheds light on the significance of considering MPVs in families with affected sibling pairs and the role of ROH as an adjuvant tool in explaining clinical variability within families. Identifying individuals carrying MPVs may have implications for disease management, identification of possible disease risks to different family members, genetic counseling and exploring personalized treatment approaches., (© 2024. The Author(s).)
Published: 2024
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34. Defining and Reducing Variant Classification Disparities.

Author: Dawood M, Fayer S, Pendyala S, Post M, Kalra D, Patterson K, Venner E, Muffley LA, Fowler DM, Rubin AF, Posey JE, Plon SE, Lupski JR, Gibbs RA, Starita LM, Robles-Espinoza CD, Coyote-Maestas W, and Gallego Romero I
Abstract: Background: Multiplexed Assays of Variant Effects (MAVEs) can test all possible single variants in a gene of interest. The resulting saturation-style data may help resolve variant classification disparities between populations, especially for variants of uncertain significance (VUS)., Methods: We analyzed clinical significance classifications in 213,663 individuals of European-like genetic ancestry versus 206,975 individuals of non-European-like genetic ancestry from All of Us and the Genome Aggregation Database. Then, we incorporated clinically calibrated MAVE data into the Clinical Genome Resource's Variant Curation Expert Panel rules to automate VUS reclassification for BRCA1, TP53, and PTEN ., Results: Using two orthogonal statistical approaches, we show a higher prevalence ( p ≤5.95e-06) of VUS in individuals of non-European-like genetic ancestry across all medical specialties assessed in all three databases. Further, in the non-European-like genetic ancestry group, higher rates of Benign or Likely Benign and variants with no clinical designation ( p ≤2.5e-05) were found across many medical specialties, whereas Pathogenic or Likely Pathogenic assignments were higher in individuals of European-like genetic ancestry ( p ≤2.5e-05). Using MAVE data, we reclassified VUS in individuals of non-European-like genetic ancestry at a significantly higher rate in comparison to reclassified VUS from European-like genetic ancestry ( p =9.1e-03) effectively compensating for the VUS disparity. Further, essential code analysis showed equitable impact of MAVE evidence codes but inequitable impact of allele frequency ( p =7.47e-06) and computational predictor ( p =6.92e-05) evidence codes for individuals of non-European-like genetic ancestry., Conclusions: Generation of saturation-style MAVE data should be a priority to reduce VUS disparities and produce equitable training data for future computational predictors.
Published: 2024
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35. NODAL variants are associated with a continuum of laterality defects from simple D-transposition of the great arteries to heterotaxy.

Author: Dardas Z, Fatih JM, Jolly A, Dawood M, Du H, Grochowski CM, Jones EG, Jhangiani SN, Wehrens XHT, Liu P, Bi W, Boerwinkle E, Posey JE, Muzny DM, Gibbs RA, Lupski JR, Coban-Akdemir Z, and Morris SA
Subjects: Animals, Humans, Arteries, Comparative Genomic Hybridization, Phenotype, Heart Defects, Congenital genetics, Heterotaxy Syndrome genetics, Transposition of Great Vessels
Abstract: Background: NODAL signaling plays a critical role in embryonic patterning and heart development in vertebrates. Genetic variants resulting in perturbations of the TGF-β/NODAL signaling pathway have reproducibly been shown to cause laterality defects in humans. To further explore this association and improve genetic diagnosis, the study aims to identify and characterize a broader range of NODAL variants in a large number of individuals with laterality defects., Methods: We re-analyzed a cohort of 321 proband-only exomes of individuals with clinically diagnosed laterality congenital heart disease (CHD) using family-based, rare variant genomic analyses. To this cohort we added 12 affected subjects with known NODAL variants and CHD from institutional research and clinical cohorts to investigate an allelic series. For those with candidate contributory variants, variant allele confirmation and segregation analysis were studied by Sanger sequencing in available family members. Array comparative genomic hybridization and droplet digital PCR were utilized for copy number variants (CNV) validation and characterization. We performed Human Phenotype Ontology (HPO)-based quantitative phenotypic analyses to dissect allele-specific phenotypic differences., Results: Missense, nonsense, splice site, indels, and/or structural variants of NODAL were identified as potential causes of heterotaxy and other laterality defects in 33 CHD cases. We describe a recurrent complex indel variant for which the nucleic acid secondary structure predictions implicate secondary structure mutagenesis as a possible mechanism for formation. We identified two CNV deletion alleles spanning NODAL in two unrelated CHD cases. Furthermore, 17 CHD individuals were found (16/17 with known Hispanic ancestry) to have the c.778G > A:p.G260R NODAL missense variant which we propose reclassification from variant of uncertain significance (VUS) to likely pathogenic. Quantitative HPO-based analyses of the observed clinical phenotype for all cases with p.G260R variation, including heterozygous, homozygous, and compound heterozygous cases, reveal clustering of individuals with biallelic variation. This finding provides evidence for a genotypic-phenotypic correlation and an allele-specific gene dosage model., Conclusion: Our data further support a role for rare deleterious variants in NODAL as a cause for sporadic human laterality defects, expand the repertoire of observed anatomical complexity of potential cardiovascular anomalies, and implicate an allele specific gene dosage model., (© 2024. The Author(s).)
Published: 2024
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36. Closing the gap: Solving complex medically relevant genes at scale.

Author: Mahmoud M, Harting J, Corbitt H, Chen X, Jhangiani SN, Doddapaneni H, Meng Q, Han T, Lambert C, Zhang S, Baybayan P, Henno G, Shen H, Hu J, Han Y, Riegler C, Metcalf G, Henno G, Chinn IK, Eberle MA, Kingan S, Farinholt T, Carvalho CMB, Gibbs RA, Kronenberg Z, Muzny D, and Sedlazeck FJ
Abstract: Comprehending the mechanism behind human diseases with an established heritable component represents the forefront of personalized medicine. Nevertheless, numerous medically important genes are inaccurately represented in short-read sequencing data analysis due to their complexity and repetitiveness or the so-called 'dark regions' of the human genome. The advent of PacBio as a long-read platform has provided new insights, yet HiFi whole-genome sequencing (WGS) cost remains frequently prohibitive. We introduce a targeted sequencing and analysis framework, Twist Alliance Dark Genes Panel (TADGP), designed to offer phased variants across 389 medically important yet complex autosomal genes. We highlight TADGP accuracy across eleven control samples and compare it to WGS. This demonstrates that TADGP achieves variant calling accuracy comparable to HiFi-WGS data, but at a fraction of the cost. Thus, enabling scalability and broad applicability for studying rare diseases or complementing previously sequenced samples to gain insights into these complex genes. TADGP revealed several candidate variants across all cases and provided insight into LPA diversity when tested on samples from rare disease and cardiovascular disease cohorts. In both cohorts, we identified novel variants affecting individual disease-associated genes (e.g., IKZF1, KCNE1 ). Nevertheless, the annotation of the variants across these 389 medically important genes remains challenging due to their underrepresentation in ClinVar and gnomAD. Consequently, we also offer an annotation resource to enhance the evaluation and prioritization of these variants. Overall, we can demonstrate that TADGP offers a cost-efficient and scalable approach to routinely assess the dark regions of the human genome with clinical relevance., Competing Interests: FS received support from Illumina, Genentech, PacBio, and Oxford Nanopore Technologies. JH, XC, CL, SZ, PB, ME, SK, GH, and ZK are PacBio employees and shareholders. HC, TH, CR, and TF are employees of Twist.
Published: 2024
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37. β-Actin G342D as a Cause of NK Cell Deficiency Impairing Lytic Synapse Termination.

Author: Reed AE, Peraza J, van den Haak F, Hernandez ER, Gibbs RA, Chinn IK, Lupski JR, Marchi E, Reshef R, Alobeid B, Mace EM, and Orange JS
Subjects: Humans, Killer Cells, Natural, Cell Line, Blood Platelets metabolism, Actins metabolism, Immunologic Deficiency Syndromes metabolism
Abstract: NK cell deficiency (NKD) occurs when an individual's major clinical immunodeficiency derives from abnormal NK cells and is associated with several genetic etiologies. Three categories of β-actin-related diseases with over 60 ACTB (β-actin) variants have previously been identified, none with a distinct NK cell phenotype. An individual with mild developmental delay, macrothrombocytopenia, and susceptibility to infections, molluscum contagiosum virus, and EBV-associated lymphoma had functional NKD for over a decade. A de novo ACTB variant encoding G342D β-actin was identified and was consistent with the individual's developmental and platelet phenotype. This novel variant also was found to have direct impact in NK cells because its expression in the human NK cell line YTS (YTS-NKD) caused increased cell spreading in lytic immune synapses created on activating surfaces. YTS-NKD cells were able to degranulate and perform cytotoxicity, but they demonstrated defective serial killing because of prolonged conjugation to the killed target cell and thus were effectively unable to terminate lytic synapses. G342D β-actin results in a novel, to our knowledge, mechanism of functional NKD via increased synaptic spreading and defective lytic synapse termination with resulting impaired serial killing, leading to overall reductions in NK cell cytotoxicity., (Copyright © 2024 by The American Association of Immunologists, Inc.)
Published: 2024
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38. Germline Genetic Testing and Survival Outcomes Among Children With Rhabdomyosarcoma: A Report From the Children's Oncology Group.

Author: Martin-Giacalone BA, Li H, Scheurer ME, Casey DL, Dugan-Perez S, Marquez-Do DA, Muzny D, Gibbs RA, Barkauskas DA, Hall D, Stewart DR, Schiffman JD, McEvoy MT, Khan J, Malkin D, Linardic CM, Crompton BD, Shern JF, Skapek SX, Venkatramani R, Hawkins DS, Sabo A, Plon SE, and Lupo PJ
Subjects: Child, Humans, Female, Male, Cohort Studies, Prospective Studies, Genetic Testing, Germ Cells, Rhabdomyosarcoma genetics, Rhabdomyosarcoma therapy, Neoplasms, Second Primary
Abstract: Importance: Determining the impact of germline cancer-predisposition variants (CPVs) on outcomes could inform novel approaches to testing and treating children with rhabdomyosarcoma., Objective: To assess whether CPVs are associated with outcome among children with rhabdomyosarcoma., Design, Setting, and Participants: In this cohort study, data were obtained for individuals, aged 0.01-23.23 years, newly diagnosed with rhabdomyosarcoma who were treated across 171 Children's Oncology Group sites from March 15, 1999, to December 8, 2017. Data analysis was performed from June 16, 2021, to May 15, 2023., Exposure: The presence of a CPV in 24 rhabdomyosarcoma-associated cancer-predisposition genes (CPGs) or an expanded set of 63 autosomal-dominant CPGs., Main Outcomes and Measures: Overall survival (OS) and event-free survival (EFS) were the main outcomes, using the Kaplan-Meier estimator to assess survival probabilities and the Cox proportional hazards regression model to adjust for clinical covariates. Analyses were stratified by tumor histology and the fusion status of PAX3 or PAX7 to the FOXO1 gene., Results: In this study of 580 individuals with rhabdomyosarcoma, the median patient age was 5.9 years (range, 0.01-23.23 years), and the male-to-female ratio was 1.5 to 1 (351 [60.5%] male). For patients with CPVs in rhabdomyosarcoma-associated CPGs, EFS was 48.4% compared with 57.8% for patients without a CPV (P = .10), and OS was 53.7% compared with 65.3% for patients without a CPV (P = .06). After adjustment, patients with CPVs had significantly worse OS (adjusted hazard ratio [AHR], 2.49 [95% CI, 1.39-4.45]; P = .002), and the outcomes were not better among patients with embryonal histology (EFS: AHR, 2.25 [95% CI, 1.25-4.06]; P = .007]; OS: AHR, 2.83 [95% CI, 1.47-5.43]; P = .002]). These associations were not due to the development of a second malignant neoplasm, and importantly, patients with fusion-negative rhabdomyosarcoma who harbored a CPV had similarly inferior outcomes as patients with fusion-positive rhabdomyosarcoma without CPVs (EFS: AHR, 1.35 [95% CI, 0.71-2.59]; P = .37; OS: AHR, 1.71 [95% CI, 0.84-3.47]; P = .14). There were no significant differences in outcome by CPV status of the 63 CPG set., Conclusions and Relevance: This cohort study identified a group of patients with embryonal rhabdomyosarcoma who had a particularly poor outcome. Other important clinical findings included that individuals with TP53 had poor outcomes independent of second malignant neoplasms and that patients with fusion-negative rhabdomyosarcoma who harbored a CPV had outcomes comparable to patients with fusion-positive rhabdomyosarcoma. These findings suggest that germline CPV testing may aid in clinical prognosis and should be considered in prospective risk-based clinical trials.
Published: 2024
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39. Genetic sex validation for sample tracking in next-generation sequencing clinical testing.

Author: Hu J, Korchina V, Zouk H, Harden MV, Murdock D, Macbeth A, Harrison SM, Lennon N, Kovar C, Balasubramanian A, Zhang L, Chandanavelli G, Pasham D, Rowley R, Wiley K, Smith ME, Gordon A, Jarvik GP, Sleiman P, Kelly MA, Bland HT, Murugan M, Venner E, Boerwinkle E, Prows C, Mahanta L, Rehm HL, Gibbs RA, and Muzny DM
Subjects: Humans, Bone Marrow Transplantation, Genotype, Laboratories, High-Throughput Nucleotide Sequencing, Clinical Laboratory Services
Abstract: Objective: Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups., Results: Precise SNP tracking showed no sample swap errors within the clinical testing laboratories. In contrast, when comparing predicted sex-by-genotype to the provided sex on the test requisition, we identified 110 inconsistencies from 25,015 clinical samples (0.44%), that had occurred during sample collection or accessioning. The genetic sex predictions were confirmed using additional SNP sites in the sequencing data or high-density genotyping arrays. It was determined that discrepancies resulted from clerical errors (49.09%), samples from transgender participants (3.64%) and stem cell or bone marrow transplant patients (7.27%) along with undetermined sample mix-ups (40%) for which sample swaps occurred prior to arrival at genome centers, however the exact cause of the events at the sampling sites resulting in the mix-ups were not able to be determined., (© 2024. The Author(s).)
Published: 2024
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40. Endocrine-Sensitive Disease Rate in Postmenopausal Patients With Estrogen Receptor-Rich/ERBB2-Negative Breast Cancer Receiving Neoadjuvant Anastrozole, Fulvestrant, or Their Combination: A Phase 3 Randomized Clinical Trial.

Author: Ma CX, Suman VJ, Sanati S, Vij K, Anurag M, Leitch AM, Unzeitig GW, Hoog J, Fernandez-Martinez A, Fan C, Gibbs RA, Watson MA, Dockter TJ, Hahn O, Guenther JM, Caudle A, Crouch E, Tiersten A, Mita M, Razaq W, Hieken TJ, Wang Y, Rimawi MF, Weiss A, Winer EP, Hunt KK, Perou CM, Ellis MJ, Partridge AH, and Carey LA
Subjects: Aged, Female, Humans, Anastrozole therapeutic use, Antineoplastic Combined Chemotherapy Protocols adverse effects, Fulvestrant, Ki-67 Antigen, Neoadjuvant Therapy, Nitriles adverse effects, Postmenopause, Receptor, ErbB-2, Receptors, Estrogen, Triazoles adverse effects, Middle Aged, Breast Neoplasms pathology, Triple Negative Breast Neoplasms drug therapy
Abstract: Importance: Adding fulvestrant to anastrozole (A+F) improved survival in postmenopausal women with advanced estrogen receptor (ER)-positive/ERBB2 (formerly HER2)-negative breast cancer. However, the combination has not been tested in early-stage disease., Objective: To determine whether neoadjuvant fulvestrant or A+F increases the rate of pathologic complete response or ypT1-2N0/N1mic/Ki67 2.7% or less residual disease (referred to as endocrine-sensitive disease) over anastrozole alone., Design, Setting, and Participants: A phase 3 randomized clinical trial assessing differences in clinical and correlative outcomes between each of the fulvestrant-containing arms and the anastrozole arm. Postmenopausal women with clinical stage II to III, ER-rich (Allred score 6-8 or >66%)/ERBB2-negative breast cancer were included. All analyses were based on data frozen on March 2, 2023., Interventions: Patients received anastrozole, fulvestrant, or a combination for 6 months preoperatively. Tumor Ki67 was assessed at week 4 and optionally at week 12, and if greater than 10% at either time point, the patient switched to neoadjuvant chemotherapy or immediate surgery., Main Outcomes and Measures: The primary outcome was the endocrine-sensitive disease rate (ESDR). A secondary outcome was the percentage change in Ki67 after 4 weeks of neoadjuvant endocrine therapy (NET) (week 4 Ki67 suppression)., Results: Between February 2014 and November 2018, 1362 female patients (mean [SD] age, 65.0 [8.2] years) were enrolled. Among the 1298 evaluable patients, ESDRs were 18.7% (95% CI, 15.1%-22.7%), 22.8% (95% CI, 18.9%-27.1%), and 20.5% (95% CI, 16.8%-24.6%) with anastrozole, fulvestrant, and A+F, respectively. Compared to anastrozole, neither fulvestrant-containing regimen significantly improved ESDR or week 4 Ki67 suppression. The rate of week 4 or week 12 Ki67 greater than 10% was 25.1%, 24.2%, and 15.7% with anastrozole, fulvestrant, and A+F, respectively. Pathologic complete response/residual cancer burden class I occurred in 8 of 167 patients and 17 of 167 patients, respectively (15.0%; 95% CI, 9.9%-21.3%), after switching to neoadjuvant chemotherapy due to week 4 or week 12 Ki67 greater than 10%. PAM50 subtyping derived from RNA sequencing of baseline biopsies available for 753 patients (58%) identified 394 luminal A, 304 luminal B, and 55 nonluminal tumors. A+F led to a greater week 4 Ki67 suppression than anastrozole alone in luminal B tumors (median [IQR], -90.4% [-95.2 to -81.9%] vs -76.7% [-89.0 to -55.6%]; P < .001), but not luminal A tumors. Thirty-six nonluminal tumors (65.5%) had a week 4 or week 12 Ki67 greater than 10%., Conclusions and Relevance: In this randomized clinical trial, neither fulvestrant nor A+F significantly improved the 6-month ESDR over anastrozole in ER-rich/ERBB2-negative breast cancer. Aromatase inhibition remains the standard-of-care NET. Differential NET response by PAM50 subtype in exploratory analyses warrants further investigation., Trial Registration: ClinicalTrials.gov Identifier: NCT01953588.
Published: 2024
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41. The frequency of pathogenic variation in the All of Us cohort reveals ancestry-driven disparities.

Author: Venner E, Patterson K, Kalra D, Wheeler MM, Chen YJ, Kalla SE, Yuan B, Karnes JH, Walker K, Smith JD, McGee S, Radhakrishnan A, Haddad A, Empey PE, Wang Q, Lichtenstein L, Toledo D, Jarvik G, Musick A, and Gibbs RA
Subjects: Humans, Black People, Genomics, Hispanic or Latino genetics, United States epidemiology, European People, African People, Black or African American, Genetic Predisposition to Disease, Population Health
Abstract: Disparities in data underlying clinical genomic interpretation is an acknowledged problem, but there is a paucity of data demonstrating it. The All of Us Research Program is collecting data including whole-genome sequences, health records, and surveys for at least a million participants with diverse ancestry and access to healthcare, representing one of the largest biomedical research repositories of its kind. Here, we examine pathogenic and likely pathogenic variants that were identified in the All of Us cohort. The European ancestry subgroup showed the highest overall rate of pathogenic variation, with 2.26% of participants having a pathogenic variant. Other ancestry groups had lower rates of pathogenic variation, including 1.62% for the African ancestry group and 1.32% in the Latino/Admixed American ancestry group. Pathogenic variants were most frequently observed in genes related to Breast/Ovarian Cancer or Hypercholesterolemia. Variant frequencies in many genes were consistent with the data from the public gnomAD database, with some notable exceptions resolved using gnomAD subsets. Differences in pathogenic variant frequency observed between ancestral groups generally indicate biases of ascertainment of knowledge about those variants, but some deviations may be indicative of differences in disease prevalence. This work will allow targeted precision medicine efforts at revealed disparities., (© 2024. The Author(s).)
Published: 2024
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42. Biallelic variation in the choline and ethanolamine transporter FLVCR1 underlies a pleiotropic disease spectrum from adult neurodegeneration to severe developmental disorders.

Author: Calame DG, Wong JH, Panda P, Nguyen DT, Leong NCP, Sangermano R, Patankar SG, Abdel-Hamid M, AlAbdi L, Safwat S, Flannery KP, Dardas Z, Fatih JM, Murali C, Kannan V, Lotze TE, Herman I, Ammouri F, Rezich B, Efthymiou S, Alavi S, Murphy D, Firoozfar Z, Nasab ME, Bahreini A, Ghasemi M, Haridy NA, Goldouzi HR, Eghbal F, Karimiani EG, Srinivasan VM, Gowda VK, Du H, Jhangiani SN, Coban-Akdemir Z, Marafi D, Rodan L, Isikay S, Rosenfeld JA, Ramanathan S, Staton M, Kerby C Oberg, Clark RD, Wenman C, Loughlin S, Saad R, Ashraf T, Male A, Tadros S, Boostani R, Abdel-Salam GMH, Zaki M, Abdalla E, Manzini MC, Pehlivan D, Posey JE, Gibbs RA, Houlden H, Alkuraya FS, Bujakowska K, Maroofian R, Lupski JR, and Nguyen LN
Abstract: FLVCR1 encodes Feline leukemia virus subgroup C receptor 1 (FLVCR1), a solute carrier (SLC) transporter within the Major Facilitator Superfamily. FLVCR1 is a widely expressed transmembrane protein with plasma membrane and mitochondrial isoforms implicated in heme, choline, and ethanolamine transport. While Flvcr1 knockout mice die in utero with skeletal malformations and defective erythropoiesis reminiscent of Diamond-Blackfan anemia, rare biallelic pathogenic FLVCR1 variants are linked to childhood or adult-onset neurodegeneration of the retina, spinal cord, and peripheral nervous system. We ascertained from research and clinical exome sequencing 27 individuals from 20 unrelated families with biallelic ultra-rare missense and predicted loss-of-function (pLoF) FLVCR1 variant alleles. We characterize an expansive FLVCR1 phenotypic spectrum ranging from adult-onset retinitis pigmentosa to severe developmental disorders with microcephaly, reduced brain volume, epilepsy, spasticity, and premature death. The most severely affected individuals, including three individuals with homozygous pLoF variants, share traits with Flvcr1 knockout mice and Diamond-Blackfan anemia including macrocytic anemia and congenital skeletal malformations. Pathogenic FLVCR1 missense variants primarily lie within transmembrane domains and reduce choline and ethanolamine transport activity compared with wild-type FLVCR1 with minimal impact on FLVCR1 stability or subcellular localization. Several variants disrupt splicing in a mini-gene assay which may contribute to genotype-phenotype correlations. Taken together, these data support an allele-specific gene dosage model in which phenotypic severity reflects residual FLVCR1 activity. This study expands our understanding of Mendelian disorders of choline and ethanolamine transport and demonstrates the importance of choline and ethanolamine in neurodevelopment and neuronal homeostasis., Competing Interests: Potential Conflict of Interest J.R.L. has stock ownership in 23andMe, is a paid consultant for Genome International, and is a co-inventor on multiple United States and European patents related to molecular diagnostics for inherited neuropathies, eye diseases, genomic disorders, and bacterial genomic fingerprinting. The Department of Molecular and Human Genetics at Baylor College of Medicine receives revenue from clinical genetic testing conducted at Baylor Genetics (BG) Laboratories. Other authors have no potential conflicts to disclose.
Published: 2024
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43. Inter and intra-host diversity of RSV in hematopoietic stem cell transplant adults with normal and delayed viral clearance.

Author: Avadhanula V, Agustinho DP, Menon VK, Chemaly RF, Shah DP, Qin X, Surathu A, Doddapaneni H, Muzny DM, Metcalf GA, Cregeen SJ, Gibbs RA, Petrosino JF, Sedlazeck FJ, and Piedra PA
Abstract: Respiratory syncytial virus (RSV) infection in immunocompromised individuals often leads to prolonged illness, progression to severe lower respiratory tract infection, and even death. How the host immune environment of the hematopoietic stem cell transplant (HCT) adults can affect viral genetic variation during an acute infection is not understood well. In the present study, we performed whole genome sequencing of RSV/A or RSV/B from samples collected longitudinally from HCT adults with normal (<14 days) and delayed (≥14 days) RSV clearance who were enrolled in a ribavirin trial. We determined the inter-host and intra-host genetic variation of RSV and the effect of mutations on putative glycosylation sites. The inter-host variation of RSV is centered in the attachment (G) and fusion (F) glycoprotein genes followed by polymerase (L) and matrix (M) genes. Interestingly, the overall genetic variation was constant between normal and delayed clearance groups for both RSV/A and RSV/B. Intra-host variation primarily occurred in the G gene followed by non-structural protein (NS1) and L genes; however, gain or loss of stop codons and frameshift mutations appeared only in the G gene and only in the delayed viral clearance group. Potential gain or loss of O-linked glycosylation sites in the G gene occurred both in RSV/A and RSV/B isolates. For RSV F gene, loss of N-linked glycosylation site occurred in three RSV/B isolates within an antigenic epitope. Both oral and aerosolized ribavirin did not cause any mutations in the L gene. In summary, prolonged viral shedding and immune deficiency resulted in RSV variation, especially in structural mutations in the G gene, possibly associated with immune evasion. Therefore, sequencing and monitoring of RSV isolates from immunocompromised patients are crucial as they can create escape mutants that can impact the effectiveness of upcoming vaccines and treatments., Competing Interests: F.J.S. has research funding from Illumina, Pacbio, Genentech and Oxford Nanopore. The remaining authors declare no competing interests, (© The Author(s) 2024. Published by Oxford University Press.)
Published: 2023
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44. Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification.

Author: de Vries PS, Conomos MP, Singh K, Nicholson CJ, Jain D, Hasbani NR, Jiang W, Lee S, Lino Cardenas CL, Lutz SM, Wong D, Guo X, Yao J, Young EP, Tcheandjieu C, Hilliard AT, Bis JC, Bielak LF, Brown MR, Musharoff S, Clarke SL, Terry JG, Palmer ND, Yanek LR, Xu H, Heard-Costa N, Wessel J, Selvaraj MS, Li RH, Sun X, Turner AW, Stilp AM, Khan A, Newman AB, Rasheed A, Freedman BI, Kral BG, McHugh CP, Hodonsky C, Saleheen D, Herrington DM, Jacobs DR Jr, Nickerson DA, Boerwinkle E, Wang FF, Heiss G, Jun G, Kinney GL, Sigurslid HH, Doddapaneni H, Hall IM, Bensenor IM, Broome J, Crapo JD, Wilson JG, Smith JA, Blangero J, Vargas JD, Mosquera JV, Smith JD, Viaud-Martinez KA, Ryan KA, Young KA, Taylor KD, Lange LA, Emery LS, Bittencourt MS, Budoff MJ, Montasser ME, Yu M, Mahaney MC, Mahamdeh MS, Fornage M, Franceschini N, Lotufo PA, Natarajan P, Wong Q, Mathias RA, Gibbs RA, Do R, Mehran R, Tracy RP, Kim RW, Nelson SC, Damrauer SM, Kardia SLR, Rich SS, Fuster V, Napolioni V, Zhao W, Tian W, Yin X, Min YI, Manning AK, Peloso G, Kelly TN, O'Donnell CJ, Morrison AC, Curran JE, Zapol WM, Bowden DW, Becker LC, Correa A, Mitchell BD, Psaty BM, Carr JJ, Pereira AC, Assimes TL, Stitziel NO, Hokanson JE, Laurie CA, Rotter JI, Vasan RS, Post WS, Peyser PA, Miller CL, and Malhotra R
Abstract: Coronary artery calcification (CAC) is a measure of atherosclerosis and a well-established predictor of coronary artery disease (CAD) events. Here we describe a genome-wide association study (GWAS) of CAC in 22,400 participants from multiple ancestral groups. We confirmed associations with four known loci and identified two additional loci associated with CAC ( ARSE and MMP16 ), with evidence of significant associations in replication analyses for both novel loci. Functional assays of ARSE and MMP16 in human vascular smooth muscle cells (VSMCs) demonstrate that ARSE is a promoter of VSMC calcification and VSMC phenotype switching from a contractile to a calcifying or osteogenic phenotype. Furthermore, we show that the association of variants near ARSE with reduced CAC is likely explained by reduced ARSE expression with the G allele of enhancer variant rs5982944. Our study highlights ARSE as an important contributor to atherosclerotic vascular calcification, and a potential drug target for vascular calcific disease., Competing Interests: Bruce M. Psaty serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Leslie S. Emery is now an employee of Celgene/Bristol Myers Squibb. Celgene/Bristol Myers Squibb had no role in the funding, design, conduct, or interpretation of this study. Nathan O. Stitziel has received research funding from Regeneron Pharmaceuticals, unrelated to this work. Karine A. Viaud-Martinez is an employee at Illumina Inc. Ryan W. Kim is an employee at Psomagen Inc. Roxona Mehran reports institutional research grants from Abbott Laboratories, Abiomed, Applied Therapeutics, AstraZeneca, Bayer, Beth Israel Deaconess, Bristol-Myers Squibb, CERC, Chiesi, Concept Medical, CSL Behring, DSI, Medtronic, Novartis Pharmaceuticals, OrbusNeich; consultant fees from Abbott Laboratories, Boston Scientific, CardiaWave, Chiesi, Janssen Scientific Affairs, Medscape/WebMD, Medtelligence (Janssen Scientific Affairs), Roivant Sciences, Sanofi, Siemens Medical Solutions; consultant fees paid to the institution from Abbott Laboratories, Bristol-Myers Squibb; advisory board, funding paid to the institution from Spectranetics/Philips/Volcano Corp; consultant (spouse) from Abiomed, The Medicines Company, Merck; Equity <1% from Claret Medical, Elixir Medical; DSMB Membership fees paid to the institution from Watermark Research Partners; consulting (no fee) from Idorsia Pharmaceuticals Ltd., Regeneron Pharmaceuticals; Associate Editor for ACC, AMA. Rajeev Malhotra is a consultant for MyoKardia (now owned by BMS), Epizon Pharma, Renovacor, and Third Pole, a co-founder of Patch and Angea Biotherapeutics, and has received research funding from Angea Biotherapeutics, Bayer Pharmaceuticals, and Amgen. Adrienne M. Stilp receives funding from Seven Bridges Genomics to develop tools for the NHLBI BioData Catalyst consortium. Pradeep Natarajan reports grants from Amgen, Apple, Boston Scientific, AstraZeneca, Allelica, Novartis, and Genentech, consulting income from GV, Blackstone Life Sciences, Foresite Labs, Apple, AstraZeneca, Allelica, Novartis, HeartFlow, and Genentech, is a scientific advisor to Esperion Therapeutics, Preciseli, and TenSixteen Bio, is a scientific co-founder of TenSixteen Bio, and spousal employment at Vertex, all unrelated to the present work. Clint L. Miller received a research grant from AstraZeneca for an unrelated project. The remaining authors declare no competing interests.
Published: 2023
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45. Type 2 Diabetes Modifies the Association of CAD Genomic Risk Variants With Subclinical Atherosclerosis.

Author: Hasbani NR, Westerman KE, Kwak SH, Chen H, Li X, Di Corpo D, Wessel J, Bis JC, Sarnowski C, Wu P, Bielak LF, Guo X, Heard-Costa N, Kinney GL, Mahaney MC, Montasser ME, Palmer ND, Raffield LM, Terry JG, Yanek LR, Bon J, Bowden DW, Brody JA, Duggirala R, Jacobs DR, Kalyani RR, Lange LA, Mitchell BD, Smith JA, Taylor KD, Carson AP, Curran JE, Fornage M, Freedman BI, Gabriel S, Gibbs RA, Gupta N, Kardia SLR, Kral BG, Momin Z, Newman AB, Post WS, Viaud-Martinez KA, Young KA, Becker LC, Bertoni AG, Blangero J, Carr JJ, Pratte K, Psaty BM, Rich SS, Wu JC, Malhotra R, Peyser PA, Morrison AC, Vasan RS, Lin X, Rotter JI, Meigs JB, Manning AK, and de Vries PS
Subjects: Humans, Carotid Intima-Media Thickness, Risk Factors, Genomics, Coronary Artery Disease genetics, Diabetes Mellitus, Type 2 complications, Diabetes Mellitus, Type 2 genetics, Atherosclerosis genetics, Plaque, Atherosclerotic
Abstract: Background: Individuals with type 2 diabetes (T2D) have an increased risk of coronary artery disease (CAD), but questions remain about the underlying pathology. Identifying which CAD loci are modified by T2D in the development of subclinical atherosclerosis (coronary artery calcification [CAC], carotid intima-media thickness, or carotid plaque) may improve our understanding of the mechanisms leading to the increased CAD in T2D., Methods: We compared the common and rare variant associations of known CAD loci from the literature on CAC, carotid intima-media thickness, and carotid plaque in up to 29 670 participants, including up to 24 157 normoglycemic controls and 5513 T2D cases leveraging whole-genome sequencing data from the Trans-Omics for Precision Medicine program. We included first-order T2D interaction terms in each model to determine whether CAD loci were modified by T2D. The genetic main and interaction effects were assessed using a joint test to determine whether a CAD variant, or gene-based rare variant set, was associated with the respective subclinical atherosclerosis measures and then further determined whether these loci had a significant interaction test., Results: Using a Bonferroni-corrected significance threshold of P <1.6×10 -4 , we identified 3 genes ( ATP1B1 , ARVCF , and LIPG ) associated with CAC and 2 genes ( ABCG8 and EIF2B2 ) associated with carotid intima-media thickness and carotid plaque, respectively, through gene-based rare variant set analysis. Both ATP1B1 and ARVCF also had significantly different associations for CAC in T2D cases versus controls. No significant interaction tests were identified through the candidate single-variant analysis., Conclusions: These results highlight T2D as an important modifier of rare variant associations in CAD loci with CAC., Competing Interests: Disclosures Dr Psaty serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. Dr Raffield is a consultant for the Trans-Omics for Precision Medicine (TOPMed) Administrative Coordinating Center (through WeStat). Dr Malhotra receives research funding from Aeglea BioTherapeutics and Amgen and serves as a consultant for Myokardia/Bristol Myers Squibb, Renovacor, Epizon Pharma, and Third Pole. The other authors report no conflicts.
Published: 2023
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46. Dominant negative variants in KIF5B cause osteogenesis imperfecta via down regulation of mTOR signaling.

Author: Marom R, Zhang B, Washington ME, Song IW, Burrage LC, Rossi VC, Berrier AS, Lindsey A, Lesinski J, Nonet ML, Chen J, Baldridge D, Silverman GA, Sutton VR, Rosenfeld JA, Tran AA, Hicks MJ, Murdock DR, Dai H, Weis M, Jhangiani SN, Muzny DM, Gibbs RA, Caswell R, Pottinger C, Cilliers D, Stals K, Eyre D, Krakow D, Schedl T, Pak SC, and Lee BH
Subjects: Animals, Humans, Mice, Caenorhabditis elegans genetics, Caenorhabditis elegans metabolism, Carrier Proteins genetics, Down-Regulation, NIH 3T3 Cells, Proteomics, Signal Transduction genetics, TOR Serine-Threonine Kinases genetics, TOR Serine-Threonine Kinases metabolism, Kinesins genetics, Kinesins metabolism, Osteogenesis Imperfecta
Abstract: Background: Kinesin motor proteins transport intracellular cargo, including mRNA, proteins, and organelles. Pathogenic variants in kinesin-related genes have been implicated in neurodevelopmental disorders and skeletal dysplasias. We identified de novo, heterozygous variants in KIF5B, encoding a kinesin-1 subunit, in four individuals with osteogenesis imperfecta. The variants cluster within the highly conserved kinesin motor domain and are predicted to interfere with nucleotide binding, although the mechanistic consequences on cell signaling and function are unknown., Methods: To understand the in vivo genetic mechanism of KIF5B variants, we modeled the p.Thr87Ile variant that was found in two patients in the C. elegans ortholog, unc-116, at the corresponding position (Thr90Ile) by CRISPR/Cas9 editing and performed functional analysis. Next, we studied the cellular and molecular consequences of the recurrent p.Thr87Ile variant by microscopy, RNA and protein analysis in NIH3T3 cells, primary human fibroblasts and bone biopsy., Results: C. elegans heterozygous for the unc-116 Thr90Ile variant displayed abnormal body length and motility phenotypes that were suppressed by additional copies of the wild type allele, consistent with a dominant negative mechanism. Time-lapse imaging of GFP-tagged mitochondria showed defective mitochondria transport in unc-116 Thr90Ile neurons providing strong evidence for disrupted kinesin motor function. Microscopy studies in human cells showed dilated endoplasmic reticulum, multiple intracellular vacuoles, and abnormal distribution of the Golgi complex, supporting an intracellular trafficking defect. RNA sequencing, proteomic analysis, and bone immunohistochemistry demonstrated down regulation of the mTOR signaling pathway that was partially rescued with leucine supplementation in patient cells., Conclusion: We report dominant negative variants in the KIF5B kinesin motor domain in individuals with osteogenesis imperfecta. This study expands the spectrum of kinesin-related disorders and identifies dysregulated signaling targets for KIF5B in skeletal development., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Marom et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Published: 2023
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47. Biallelic missense variants in COG3 cause a congenital disorder of glycosylation with impairment of retrograde vesicular trafficking.

Author: Duan R, Marafi D, Xia ZJ, Ng BG, Maroofian R, Sumya FT, Saad AK, Du H, Fatih JM, Hunter JV, Elbendary HM, Baig SM, Abdullah U, Ali Z, Efthymiou S, Murphy D, Mitani T, Withers MA, Jhangiani SN, Coban-Akdemir Z, Calame DG, Pehlivan D, Gibbs RA, Posey JE, Houlden H, Lupashin VV, Zaki MS, Freeze HH, and Lupski JR
Subjects: Humans, Glycosylation, Fibroblasts metabolism, Phenotype, Adaptor Proteins, Vesicular Transport genetics, Congenital Disorders of Glycosylation genetics
Abstract: Biallelic variants in genes for seven out of eight subunits of the conserved oligomeric Golgi complex (COG) are known to cause recessive congenital disorders of glycosylation (CDG) with variable clinical manifestations. COG3 encodes a constituent subunit of the COG complex that has not been associated with disease traits in humans. Herein, we report two COG3 homozygous missense variants in four individuals from two unrelated consanguineous families that co-segregated with COG3-CDG presentations. Clinical phenotypes of affected individuals include global developmental delay, severe intellectual disability, microcephaly, epilepsy, facial dysmorphism, and variable neurological findings. Biochemical analysis of serum transferrin from one family showed the loss of a single sialic acid. Western blotting on patient-derived fibroblasts revealed reduced COG3 and COG4. Further experiments showed delayed retrograde vesicular recycling in patient cells. This report adds to the knowledge of the COG-CDG network by providing collective evidence for a COG3-CDG rare disease trait and implicating a likely pathology of the disorder as the perturbation of Golgi trafficking., (© 2023 SSIEM.)
Published: 2023
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48. Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study.

Author: Wang Y, Selvaraj MS, Li X, Li Z, Holdcraft JA, Arnett DK, Bis JC, Blangero J, Boerwinkle E, Bowden DW, Cade BE, Carlson JC, Carson AP, Chen YI, Curran JE, de Vries PS, Dutcher SK, Ellinor PT, Floyd JS, Fornage M, Freedman BI, Gabriel S, Germer S, Gibbs RA, Guo X, He J, Heard-Costa N, Hildalgo B, Hou L, Irvin MR, Joehanes R, Kaplan RC, Kardia SL, Kelly TN, Kim R, Kooperberg C, Kral BG, Levy D, Li C, Liu C, Lloyd-Jone D, Loos RJ, Mahaney MC, Martin LW, Mathias RA, Minster RL, Mitchell BD, Montasser ME, Morrison AC, Murabito JM, Naseri T, O'Connell JR, Palmer ND, Preuss MH, Psaty BM, Raffield LM, Rao DC, Redline S, Reiner AP, Rich SS, Ruepena MS, Sheu WH, Smith JA, Smith A, Tiwari HK, Tsai MY, Viaud-Martinez KA, Wang Z, Yanek LR, Zhao W, Rotter JI, Lin X, Natarajan P, and Peloso GM
Subjects: Humans, Genome-Wide Association Study, Precision Medicine, Whole Genome Sequencing methods, Lipids genetics, Polymorphism, Single Nucleotide genetics, RNA, Long Noncoding genetics
Abstract: Long non-coding RNAs (lncRNAs) are known to perform important regulatory functions in lipid metabolism. Large-scale whole-genome sequencing (WGS) studies and new statistical methods for variant set tests now provide an opportunity to assess more associations between rare variants in lncRNA genes and complex traits across the genome. In this study, we used high-coverage WGS from 66,329 participants of diverse ancestries with measurement of blood lipids and lipoproteins (LDL-C, HDL-C, TC, and TG) in the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program to investigate the role of lncRNAs in lipid variability. We aggregated rare variants for 165,375 lncRNA genes based on their genomic locations and conducted rare-variant aggregate association tests using the STAAR (variant-set test for association using annotation information) framework. We performed STAAR conditional analysis adjusting for common variants in known lipid GWAS loci and rare-coding variants in nearby protein-coding genes. Our analyses revealed 83 rare lncRNA variant sets significantly associated with blood lipid levels, all of which were located in known lipid GWAS loci (in a ±500-kb window of a Global Lipids Genetics Consortium index variant). Notably, 61 out of 83 signals (73%) were conditionally independent of common regulatory variation and rare protein-coding variation at the same loci. We replicated 34 out of 61 (56%) conditionally independent associations using the independent UK Biobank WGS data. Our results expand the genetic architecture of blood lipids to rare variants in lncRNAs., Competing Interests: Declaration of interests P.N. reports research grants from Allelica, Apple, Amgen, Boston Scientific, Genentech/Roche, and Novartis; personal fees from Allelica, Apple, AstraZeneca, Blackstone Life Sciences, Eli Lilly & Co, Foresite Labs, Genentech/Roche, GV, HeartFlow, Magnet Biomedicine, and Novartis; scientific advisory board membership of Esperion Therapeutics, Preciseli, and TenSixteen Bio; scientific co-founder of TenSixteen Bio; equity in MyOme, Preciseli, and TenSixteen Bio; and spousal employment at Vertex Pharmaceuticals, all unrelated to the present work. B.M.P. serves on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. L.M.R., S.S.R., and R.M. are consultants for the TOPMed Administrative Coordinating Center (through Westat). M.E.M. receives funding from Regeneron Pharmaceutical Inc. unrelated to this work. X. Lin is a consultant of AbbVie Pharmaceuticals and Verily Life Sciences. P.T.E. receives sponsored research support from Bayer AG, IBM Research, Bristol Myers Squibb, Pfizer, and Novo Nordisk; he has also served on advisory boards or consulted for Bayer AG, MyoKardia, and Novartis. A.P.C. previously received investigator-initiated grant support from Amgen, Inc. unrelated to the present work., (Copyright © 2023 American Society of Human Genetics. All rights reserved.)
Published: 2023
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49. Break-induced replication underlies formation of inverted triplications and generates unexpected diversity in haplotype structures.

Author: Grochowski CM, Bengtsson JD, Du H, Gandhi M, Lun MY, Mehaffey MG, Park K, Höps W, Benito-Garagorri E, Hasenfeld P, Korbel JO, Mahmoud M, Paulin LF, Jhangiani SN, Muzny DM, Fatih JM, Gibbs RA, Pendleton M, Harrington E, Juul S, Lindstrand A, Sedlazeck FJ, Pehlivan D, Lupski JR, and Carvalho CMB
Abstract: Background: The duplication-triplication/inverted-duplication (DUP-TRP/INV-DUP) structure is a type of complex genomic rearrangement (CGR) hypothesized to result from replicative repair of DNA due to replication fork collapse. It is often mediated by a pair of inverted low-copy repeats (LCR) followed by iterative template switches resulting in at least two breakpoint junctions in cis . Although it has been identified as an important mutation signature of pathogenicity for genomic disorders and cancer genomes, its architecture remains unresolved and is predicted to display at least four structural variation (SV) haplotypes., Results: Here we studied the genomic architecture of DUP-TRP/INV-DUP by investigating the genomic DNA of 24 patients with neurodevelopmental disorders identified by array comparative genomic hybridization (aCGH) on whom we found evidence for the existence of 4 out of 4 predicted SV haplotypes. Using a combination of short-read genome sequencing (GS), long- read GS, optical genome mapping and StrandSeq the haplotype structure was resolved in 18 samples. This approach refined the point of template switching between inverted LCRs in 4 samples revealing a DNA segment of ∼2.2-5.5 kb of 100% nucleotide similarity. A prediction model was developed to infer the LCR used to mediate the non-allelic homology repair., Conclusions: These data provide experimental evidence supporting the hypothesis that inverted LCRs act as a recombinant substrate in replication-based repair mechanisms. Such inverted repeats are particularly relevant for formation of copy-number associated inversions, including the DUP-TRP/INV-DUP structures. Moreover, this type of CGR can result in multiple conformers which contributes to generate diverse SV haplotypes in susceptible loci .
Published: 2023
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50. Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium.

Author: Jiang MZ, Gaynor SM, Li X, Van Buren E, Stilp A, Buth E, Wang FF, Manansala R, Gogarten SM, Li Z, Polfus LM, Salimi S, Bis JC, Pankratz N, Yanek LR, Durda P, Tracy RP, Rich SS, Rotter JI, Mitchell BD, Lewis JP, Psaty BM, Pratte KA, Silverman EK, Kaplan RC, Avery C, North K, Mathias RA, Faraday N, Lin H, Wang B, Carson AP, Norwood AF, Gibbs RA, Kooperberg C, Lundin J, Peters U, Dupuis J, Hou L, Fornage M, Benjamin EJ, Reiner AP, Bowler RP, Lin X, Auer PL, and Raffield LM
Abstract: Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.
Published: 2023
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