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207 results on '"Paten, B."'

1. Haplotype-aware graph indexes

Author

Sirén, J, Garrison, E, Novak, AM, Paten, B, and Durbin, R

Subjects
Information and computing sciences
Abstract

The variation graph toolkit (VG) represents genetic variation as a graph. Each path in the graph is a potential haplotype, though most paths are unlikely recombinations of true haplotypes. We augment the VG model with haplotype information to identify which paths are more likely to be correct. For this purpose, we develop a scalable implementation of the graph extension of the positional Burrows-Wheeler transform. We demonstrate the scalability of the new implementation by indexing the 1000 Genomes Project haplotypes. We also develop an algorithm for simplifying variation graphs for k-mer indexing without losing any k-mers in the haplotypes.

Published
2018

2. Inversion polymorphism in a complete human genome assembly

Author

Porubsky, D., Harvey, W.T., Rozanski, A.N., Ebler, J., Höps, W., Ashraf, H., Hasenfeld, P., Paten, B., Sanders, A.D., Marschall, T., Korbel, J.O., and Eichler, E.E.

Subjects
Cancer Research
Abstract

The telomere-to-telomere (T2T) complete human reference has significantly improved our ability to characterize genome structural variation. To understand its impact on inversion polymorphisms, we remapped data from 41 genomes against the T2T reference genome and compared it to the GRCh38 reference. We find a ~ 21% increase in sensitivity improving mapping of 63 inversions on the T2T reference. We identify 26 misorientations within GRCh38 and show that the T2T reference is three times more likely to represent the correct orientation of the major human allele. Analysis of 10 additional samples reveals novel rare inversions at chromosomes 15q25.2, 16p11.2, 16q22.1-23.1, and 22q11.21.

Published
2023

3. Gaps and complex structurally variant loci in phased genome assemblies

Author

Porubsky, D., Vollger, M.R., Harvey, W.T., Rozanski, A.N., Ebert, P., Hickey, G., Hasenfeld, P., Sanders, A.D., Stober, C., Korbel, J.O., Paten, B., Marschall, T., and Eichler, E.E.

Subjects
Cancer Research
Abstract

There has been tremendous progress in phased genome assembly production by combining long-read data with parental information or linked-read data. Nevertheless, a typical phased genome assembly generated by trio-hifiasm still generates more than 140 gaps. We perform a detailed analysis of gaps, assembly breaks, and misorientations from 182 haploid assemblies obtained from a diversity panel of 77 unique human samples. Although trio-based approaches using HiFi are the current gold standard, chromosome-wide phasing accuracy is comparable when using Strand-seq instead of parental data. Importantly, the majority of assembly gaps cluster near the largest and most identical repeats (including segmental duplications [35.4%], satellite DNA [22.3%], or regions enriched in GA/AT-rich DNA [27.4%]). Consequently, 1513 protein-coding genes overlap assembly gaps in at least one haplotype, and 231 are recurrently disrupted or missing from five or more haplotypes. Furthermore, we estimate that 6-7 Mbp of DNA are misorientated per haplotype irrespective of whether trio-free or trio-based approaches are used. Of these misorientations, 81% correspond to bona fide large inversion polymorphisms in the human species, most of which are flanked by large segmental duplications. We also identify large-scale alignment discontinuities consistent with 11.9 Mbp of deletions and 161.4 Mbp of insertions per haploid genome. Although 99% of this variation corresponds to satellite DNA, we identify 230 regions of euchromatic DNA with frequent expansions and contractions, nearly half of which overlap with 197 protein-coding genes. Such variable and incompletely assembled regions are important targets for future algorithmic development and pangenome representation.

Published
2023

4. A comparative genomics multitool for scientific discovery and conservation

Author

Massachusetts Institute of Technology. Department of Biology, Genereux, DP, Serres, A, Armstrong, J, Johnson, J, Marinescu, VD, Muren, E, Juan, D, Bejerano, G, Casewell, NR, Chemnick, LG, Damas, J, Di Palma, F, Diekhans, M, Fiddes, IT, Garber, M, Gladyshev, NV, Goodman, L, Haerty, W, Houck, ML, Hubley, R, Kivioja, T, Koepfli, KP, Kuderna, LFK, Lander, Eric Steven, Meadows, JRS, Murphy, WJ, Nash, W, Noh, HJ, Nweeia, M, Pfenning, AR, Pollard, KS, Ray, DA, Shapiro, B, Smit, AFA, Springer, MS, Steiner, CC, Swofford, R, Taipale, J, Teeling, EC, Turner-Maier, J, Alfoldi, J, Birren, B, Ryder, OA, Lewin, HA, Paten, B, Marques-Bonet, T, Lindblad-Toh, K, Karlsson, EK, Massachusetts Institute of Technology. Department of Biology, Genereux, DP, Serres, A, Armstrong, J, Johnson, J, Marinescu, VD, Muren, E, Juan, D, Bejerano, G, Casewell, NR, Chemnick, LG, Damas, J, Di Palma, F, Diekhans, M, Fiddes, IT, Garber, M, Gladyshev, NV, Goodman, L, Haerty, W, Houck, ML, Hubley, R, Kivioja, T, Koepfli, KP, Kuderna, LFK, Lander, Eric Steven, Meadows, JRS, Murphy, WJ, Nash, W, Noh, HJ, Nweeia, M, Pfenning, AR, Pollard, KS, Ray, DA, Shapiro, B, Smit, AFA, Springer, MS, Steiner, CC, Swofford, R, Taipale, J, Teeling, EC, Turner-Maier, J, Alfoldi, J, Birren, B, Ryder, OA, Lewin, HA, Paten, B, Marques-Bonet, T, Lindblad-Toh, K, and Karlsson, EK

Abstract

© 2020, The Author(s). The Zoonomia Project is investigating the genomics of shared and specialized traits in eutherian mammals. Here we provide genome assemblies for 131 species, of which all but 9 are previously uncharacterized, and describe a whole-genome alignment of 240 species of considerable phylogenetic diversity, comprising representatives from more than 80% of mammalian families. We find that regions of reduced genetic diversity are more abundant in species at a high risk of extinction, discern signals of evolutionary selection at high resolution and provide insights from individual reference genomes. By prioritizing phylogenetic diversity and making data available quickly and without restriction, the Zoonomia Project aims to support biological discovery, medical research and the conservation of biodiversity.

Published
2022

6. Semi-automated assembly of high-quality diploid human reference genomes

Author

Jarvis, E.D., Formenti, G., Rhie, A., Guarracino, A., Yang, C., Wood, J., Tracey, A., Thibaud-Nissen, F., Vollger, M.R., Porubsky, D., Cheng, H., Asri, M., Logsdon, G.A., Carnevali, P., Chaisson, M.J.P., Chin, C.S., Cody, S., Collins, J., Ebert, P., Escalona, M., Fedrigo, O., Fulton, R.S., Fulton, L.L., Garg, S., Gerton, J.L., Ghurye, J., Granat, A., Green, R.E., Harvey, W., Hasenfeld, P., Hastie, A., Haukness, M., Jaeger, E.B., Jain, M., Kirsche, M., Kolmogorov, M., Korbel, J.O., Koren, S., Korlach, J., Lee, J., Li, D., Lindsay, T., Lucas, J., Luo, F., Marschall, T., Mitchell, M.W., McDaniel, J., Nie, F., Olsen, H.E., Olson, N.D., Pesout, T., Potapova, T., Puiu, D., Regier, A., Ruan, J., Salzberg, S.L., Sanders, A.D., Schatz, M.C., Schmitt, A., Schneider, V.A., Selvaraj, S., Shafin, K., Shumate, A., Stitziel, N.O., Stober, C., Torrance, J., Wagner, J., Wang, J., Wenger, A., Xiao, C., Zimin, A.V., Zhang, G., Wang, T., Li, H., Garrison, E., Haussler, D., Hall, I., Zook, J.M., Eichler, E.E., Phillippy, A.M., Paten, B., Howe, K., and Miga, K.H.

Subjects
Cancer Research, Haplotypes, Genome, Human, Humans, Chromosome Mapping, High-Throughput Nucleotide Sequencing, Chromosomes, Human, Genetic Variation, Sequence Analysis, DNA, Genomics, Reference Standards, Diploidy
Abstract

The current human reference genome, GRCh38, represents over 20 years of effort to generate a high-quality assembly, which has benefitted societysup1,2/sup. However, it still has many gaps and errors, and does not represent a biological genome as it is a blend of multiple individualssup3,4/sup. Recently, a high-quality telomere-to-telomere reference, CHM13, was generated with the latest long-read technologies, but it was derived from a hydatidiform mole cell line with a nearly homozygous genomesup5/sup. To address these limitations, the Human Pangenome Reference Consortium formed with the goal of creating high-quality, cost-effective, diploid genome assemblies for a pangenome reference that represents human genetic diversitysup6/sup. Here, in our first scientific report, we determined which combination of current genome sequencing and assembly approaches yield the most complete and accurate diploid genome assembly with minimal manual curation. Approaches that used highly accurate long reads and parent-child data with graph-based haplotype phasing during assembly outperformed those that did not. Developing a combination of the top-performing methods, we generated our first high-quality diploid reference assembly, containing only approximately four gaps per chromosome on average, with most chromosomes within ±1% of the length of CHM13. Nearly 48% of protein-coding genes have non-synonymous amino acid changes between haplotypes, and centromeric regions showed the highest diversity. Our findings serve as a foundation for assembling near-complete diploid human genomes at scale for a pangenome reference to capture global genetic variation from single nucleotides to structural rearrangements.

Published
2021

7. A strategy for building and using a human reference pangenome [version 2; peer review: 2 approved]

Author

Llamas, B., Narzisi, G., Schneider, V., Audano, P., Biederstedt, E., Blauvelt, L., Bradbury, P., Chang, X., Chin, C., Fungtammasan, A., Clarke, W., Cleary, A., Ebler, J., Eizenga, J., Sibbesen, J., Markello, C., Garrison, E., Garg, S., Hickey, G., Lazo, G., Lin, M., Mahmoud, M., Marschall, T., Minkin, I., Monlong, J., Musunuri, R., Sagayaradj, S., Novak, A., Rautiainen, M., Regier, A., Sedlazeck, F., Siren, J., Souilmi, Y., Wagner, J., Wrightsman, T., Yokoyama, T., Zeng, Q., Zook, J., Paten, B., and Busby, B.

Subjects
Science, Medicine
Abstract

In March 2019, 45 scientists and software engineers from around the world converged at the University of California, Santa Cruz for the first pangenomics codeathon. The purpose of the meeting was to propose technical specifications and standards for a usable human pangenome as well as to build relevant tools for genome graph infrastructures. During the meeting, the group held several intense and productive discussions covering a diverse set of topics, including advantages of graph genomes over a linear reference representation, design of new methods that can leverage graph-based data structures, and novel visualization and annotation approaches for pangenomes. Additionally, the participants self-organized themselves into teams that worked intensely over a three-day period to build a set of pipelines and tools for specific pangenomic applications. A summary of the questions raised and the tools developed are reported in this manuscript.

Published
2021

8. Dense sampling of bird diversity increases power of comparative genomics (vol 587, pg 252, 2020)

Author

Feng, S, Stiller, J, Deng, Y, Armstrong, J, Fang, Q, Reeve, AH, Xie, D, Chen, G, Guo, C, Faircloth, BC, Petersen, B, Wang, Z, Zhou, Q, Diekhans, M, Chen, W, Andreu-Sanchez, S, Margaryan, A, Howard, JT, Parent, C, Pacheco, G, Sinding, M-HS, Puetz, L, Cavill, E, Ribeiro, AM, Eckhart, L, Fjeldsa, J, Hosner, PA, Brumfield, RT, Christidis, L, Bertelsen, MF, Sicheritz-Ponten, T, Tietze, DT, Robertson, BC, Song, G, Borgia, G, Claramunt, S, Lovette, IJ, Cowen, SJ, Njoroge, P, Dumbacher, JP, Ryder, OA, Fuchs, J, Bunce, M, Burt, DW, Cracraft, J, Meng, G, Hackett, SJ, Ryan, PG, Jonsson, KA, Jamieson, IG, da Fonseca, RR, Braun, EL, Houde, P, Mirarab, S, Suh, A, Hansson, B, Ponnikas, S, Sigeman, H, Stervander, M, Frandsen, PB, van der Zwan, H, van der Sluis, R, Visser, C, Balakrishnan, CN, Clark, AG, Fitzpatrick, JW, Bowman, R, Chen, N, Cloutier, A, Sackton, TB, Edwards, SV, Foote, DJ, Shakya, SB, Sheldon, FH, Vignal, A, Soares, AER, Shapiro, B, Gonzalez-Solis, J, Ferrer-Obiol, J, Rozas, J, Riutort, M, Tigano, A, Friesen, V, Dalen, L, Urrutia, AO, Szekely, T, Liu, Y, Campana, MG, Corvelo, A, Fleischer, RC, Rutherford, KM, Gemmell, NJ, Dussex, N, Mouritsen, H, Thiele, N, Delmore, K, Liedvogel, M, Franke, A, Hoeppner, MP, Krone, O, Fudickar, AM, Mila, B, Ketterson, ED, Fidler, AE, Friis, G, Parody-Merino, AM, Battley, PF, Cox, MP, Lima, NCB, Prosdocimi, F, Parchman, TL, Schlinger, BA, Loiselle, BA, Blake, JG, Lim, HC, Day, LB, Fuxjager, MJ, Baldwin, MW, Braun, MJ, Wirthlin, M, Dikow, RB, Ryder, TB, Camenisch, G, Keller, LF, DaCosta, JM, Hauber, ME, Louder, MIM, Witt, CC, McGuire, JA, Mudge, J, Megna, LC, Carling, MD, Wang, B, Taylor, SA, Del-Rio, G, Aleixo, A, Vasconcelos, ATR, Mello, CV, Weir, JT, Haussler, D, Li, Q, Yang, H, Wang, J, Lei, F, Rahbek, C, Gilbert, MTP, Graves, GR, Jarvis, ED, Paten, B, Zhang, G, Feng, S, Stiller, J, Deng, Y, Armstrong, J, Fang, Q, Reeve, AH, Xie, D, Chen, G, Guo, C, Faircloth, BC, Petersen, B, Wang, Z, Zhou, Q, Diekhans, M, Chen, W, Andreu-Sanchez, S, Margaryan, A, Howard, JT, Parent, C, Pacheco, G, Sinding, M-HS, Puetz, L, Cavill, E, Ribeiro, AM, Eckhart, L, Fjeldsa, J, Hosner, PA, Brumfield, RT, Christidis, L, Bertelsen, MF, Sicheritz-Ponten, T, Tietze, DT, Robertson, BC, Song, G, Borgia, G, Claramunt, S, Lovette, IJ, Cowen, SJ, Njoroge, P, Dumbacher, JP, Ryder, OA, Fuchs, J, Bunce, M, Burt, DW, Cracraft, J, Meng, G, Hackett, SJ, Ryan, PG, Jonsson, KA, Jamieson, IG, da Fonseca, RR, Braun, EL, Houde, P, Mirarab, S, Suh, A, Hansson, B, Ponnikas, S, Sigeman, H, Stervander, M, Frandsen, PB, van der Zwan, H, van der Sluis, R, Visser, C, Balakrishnan, CN, Clark, AG, Fitzpatrick, JW, Bowman, R, Chen, N, Cloutier, A, Sackton, TB, Edwards, SV, Foote, DJ, Shakya, SB, Sheldon, FH, Vignal, A, Soares, AER, Shapiro, B, Gonzalez-Solis, J, Ferrer-Obiol, J, Rozas, J, Riutort, M, Tigano, A, Friesen, V, Dalen, L, Urrutia, AO, Szekely, T, Liu, Y, Campana, MG, Corvelo, A, Fleischer, RC, Rutherford, KM, Gemmell, NJ, Dussex, N, Mouritsen, H, Thiele, N, Delmore, K, Liedvogel, M, Franke, A, Hoeppner, MP, Krone, O, Fudickar, AM, Mila, B, Ketterson, ED, Fidler, AE, Friis, G, Parody-Merino, AM, Battley, PF, Cox, MP, Lima, NCB, Prosdocimi, F, Parchman, TL, Schlinger, BA, Loiselle, BA, Blake, JG, Lim, HC, Day, LB, Fuxjager, MJ, Baldwin, MW, Braun, MJ, Wirthlin, M, Dikow, RB, Ryder, TB, Camenisch, G, Keller, LF, DaCosta, JM, Hauber, ME, Louder, MIM, Witt, CC, McGuire, JA, Mudge, J, Megna, LC, Carling, MD, Wang, B, Taylor, SA, Del-Rio, G, Aleixo, A, Vasconcelos, ATR, Mello, CV, Weir, JT, Haussler, D, Li, Q, Yang, H, Wang, J, Lei, F, Rahbek, C, Gilbert, MTP, Graves, GR, Jarvis, ED, Paten, B, and Zhang, G

Abstract

A Correction to this paper has been published: https://doi.org/10.1038/s41586-021-03473-8.

Published
2021

9. Dense sampling of bird diversity increases power of comparative genomics

Author

Feng, S, Stiller, J, Deng, Y, Armstrong, J, Fang, Q, Reeve, AH, Xie, D, Chen, G, Guo, C, Faircloth, BC, Petersen, B, Wang, Z, Zhou, Q, Diekhans, M, Chen, W, Andreu-Sanchez, S, Margaryan, A, Howard, JT, Parent, C, Pacheco, G, Sinding, M-HS, Puetz, L, Cavill, E, Ribeiro, AM, Eckhart, L, Fjeldsa, J, Hosner, PA, Brumfield, RT, Christidis, L, Bertelsen, MF, Sicheritz-Ponten, T, Tietze, DT, Robertson, BC, Song, G, Borgia, G, Claramunt, S, Lovette, IJ, Cowen, SJ, Njoroge, P, Dumbacher, JP, Ryder, OA, Fuchs, J, Bunce, M, Burt, DW, Cracraft, J, Meng, G, Hackett, SJ, Ryan, PG, Jonsson, KA, Jamieson, IG, da Fonseca, RR, Braun, EL, Houde, P, Mirarab, S, Suh, A, Hansson, B, Ponnikas, S, Sigeman, H, Stervander, M, Frandsen, PB, van der Zwan, H, van der Sluis, R, Visser, C, Balakrishnan, CN, Clark, AG, Fitzpatrick, JW, Bowman, R, Chen, N, Cloutier, A, Sackton, TB, Edwards, SV, Foote, DJ, Shakya, SB, Sheldon, FH, Vignal, A, Soares, AER, Shapiro, B, Gonzalez-Solis, J, Ferrer-Obiol, J, Rozas, J, Riutort, M, Tigano, A, Friesen, V, Dalen, L, Urrutia, AO, Szekely, T, Liu, Y, Campana, MG, Corvelo, A, Fleischer, RC, Rutherford, KM, Gemmell, NJ, Dussex, N, Mouritsen, H, Thiele, N, Delmore, K, Liedvogel, M, Franke, A, Hoeppner, MP, Krone, O, Fudickar, AM, Mila, B, Ketterson, ED, Fidler, AE, Friis, G, Parody-Merino, AM, Battley, PF, Cox, MP, Lima, NCB, Prosdocimi, F, Parchman, TL, Schlinger, BA, Loiselle, BA, Blake, JG, Lim, HC, Day, LB, Fuxjager, MJ, Baldwin, MW, Braun, MJ, Wirthlin, M, Dikow, RB, Ryder, TB, Camenisch, G, Keller, LF, DaCosta, JM, Hauber, ME, Louder, MIM, Witt, CC, McGuire, JA, Mudge, J, Megna, LC, Carling, MD, Wang, B, Taylor, SA, Del-Rio, G, Aleixo, A, Vasconcelos, ATR, Mello, CV, Weir, JT, Haussler, D, Li, Q, Yang, H, Wang, J, Lei, F, Rahbek, C, Gilbert, MTP, Graves, GR, Jarvis, ED, Paten, B, Zhang, G, Feng, S, Stiller, J, Deng, Y, Armstrong, J, Fang, Q, Reeve, AH, Xie, D, Chen, G, Guo, C, Faircloth, BC, Petersen, B, Wang, Z, Zhou, Q, Diekhans, M, Chen, W, Andreu-Sanchez, S, Margaryan, A, Howard, JT, Parent, C, Pacheco, G, Sinding, M-HS, Puetz, L, Cavill, E, Ribeiro, AM, Eckhart, L, Fjeldsa, J, Hosner, PA, Brumfield, RT, Christidis, L, Bertelsen, MF, Sicheritz-Ponten, T, Tietze, DT, Robertson, BC, Song, G, Borgia, G, Claramunt, S, Lovette, IJ, Cowen, SJ, Njoroge, P, Dumbacher, JP, Ryder, OA, Fuchs, J, Bunce, M, Burt, DW, Cracraft, J, Meng, G, Hackett, SJ, Ryan, PG, Jonsson, KA, Jamieson, IG, da Fonseca, RR, Braun, EL, Houde, P, Mirarab, S, Suh, A, Hansson, B, Ponnikas, S, Sigeman, H, Stervander, M, Frandsen, PB, van der Zwan, H, van der Sluis, R, Visser, C, Balakrishnan, CN, Clark, AG, Fitzpatrick, JW, Bowman, R, Chen, N, Cloutier, A, Sackton, TB, Edwards, SV, Foote, DJ, Shakya, SB, Sheldon, FH, Vignal, A, Soares, AER, Shapiro, B, Gonzalez-Solis, J, Ferrer-Obiol, J, Rozas, J, Riutort, M, Tigano, A, Friesen, V, Dalen, L, Urrutia, AO, Szekely, T, Liu, Y, Campana, MG, Corvelo, A, Fleischer, RC, Rutherford, KM, Gemmell, NJ, Dussex, N, Mouritsen, H, Thiele, N, Delmore, K, Liedvogel, M, Franke, A, Hoeppner, MP, Krone, O, Fudickar, AM, Mila, B, Ketterson, ED, Fidler, AE, Friis, G, Parody-Merino, AM, Battley, PF, Cox, MP, Lima, NCB, Prosdocimi, F, Parchman, TL, Schlinger, BA, Loiselle, BA, Blake, JG, Lim, HC, Day, LB, Fuxjager, MJ, Baldwin, MW, Braun, MJ, Wirthlin, M, Dikow, RB, Ryder, TB, Camenisch, G, Keller, LF, DaCosta, JM, Hauber, ME, Louder, MIM, Witt, CC, McGuire, JA, Mudge, J, Megna, LC, Carling, MD, Wang, B, Taylor, SA, Del-Rio, G, Aleixo, A, Vasconcelos, ATR, Mello, CV, Weir, JT, Haussler, D, Li, Q, Yang, H, Wang, J, Lei, F, Rahbek, C, Gilbert, MTP, Graves, GR, Jarvis, ED, Paten, B, and Zhang, G

Abstract

Whole-genome sequencing projects are increasingly populating the tree of life and characterizing biodiversity1-4. Sparse taxon sampling has previously been proposed to confound phylogenetic inference5, and captures only a fraction of the genomic diversity. Here we report a substantial step towards the dense representation of avian phylogenetic and molecular diversity, by analysing 363 genomes from 92.4% of bird families-including 267 newly sequenced genomes produced for phase II of the Bird 10,000 Genomes (B10K) Project. We use this comparative genome dataset in combination with a pipeline that leverages a reference-free whole-genome alignment to identify orthologous regions in greater numbers than has previously been possible and to recognize genomic novelties in particular bird lineages. The densely sampled alignment provides a single-base-pair map of selection, has more than doubled the fraction of bases that are confidently predicted to be under conservation and reveals extensive patterns of weak selection in predominantly non-coding DNA. Our results demonstrate that increasing the diversity of genomes used in comparative studies can reveal more shared and lineage-specific variation, and improve the investigation of genomic characteristics. We anticipate that this genomic resource will offer new perspectives on evolutionary processes in cross-species comparative analyses and assist in efforts to conserve species.

Published
2020

10. A fully phased accurate assembly of an individual human genome

Author

Porubsky, D., Ebert, P., Audano, P.A., Vollger, M.R., Harvey, W.T., Munson, K.M., Sorensen, M., Sulovari, A., Haukness, M., Ghareghani, M., Lansdorp, P.M., Paten, B., Devine, S.E., Sanders, A.D., Lee, C., Chaisson, M.J.P., Korbel, J.O., Eichler, E.E., and Marschall, T.

Subjects
Cancer Research
Abstract

The prevailing genome assembly paradigm is to produce consensus sequences that "collapse" parental haplotypes into a consensus sequence. Here, we leverage the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing (Strand-seq) and combine them with high-fidelity (HiFi) long sequencing reads, in a novel reference-free workflow for diploid de novo genome assembly. Employing this strategy, we produce completely phased de novo genome assemblies separately for each haplotype of a single individual of Puerto Rican origin (HG00733) in the absence of parental data. The assemblies are accurate (QV > 40), highly contiguous (contig N50 > 25 Mbp) with low switch error rates (0.4%) providing fully phased single-nucleotide variants (SNVs), indels, and structural variants (SVs). A comparison of Oxford Nanopore and PacBio phased assemblies identifies 150 regions that are preferential sites of contig breaks irrespective of sequencing technology or phasing algorithms.

Published
2019

11. BRCA Challenge: BRCA Exchange as a global resource for variants in BRCA1 and BRCA2

Author

Cline, M.S., Liao, R.G., Parsons, M.T., Paten, B., Alquaddoomi, F., Antoniou, A., Baxter, S., Brody, L., Cook-Deegan, R., Coffin, A., Couch, F.J., Craft, B., Currie, R., Dlott, C.C., Dolman, L., Dunnen, J.T. den, Dyke, S.O.M., Domchek, S.M., Easton, D., Fischmann, Z., Foulkes, W.D., Garber, J., Goldgar, D., Goldman, M.J., Goodhand, P., Harrison, S., Haussler, D., Kato, K., Knoppers, B., Markello, C., Nussbaum, R., Offit, K., Plon, S.E., Rashbass, J., Rehm, H.L., Robson, M., Rubinstein, W.S., Stoppa-Lyonnet, D., Tavtigian, S., Thorogood, A., Zhang, C., Zimmermann, M., Burn, J., Chanock, S., Ratsch, G., Spurdle, A.B., Andreoletti, G., Baker, D., Brenner, S., Brush, M., Caputo, S., Castera, L., Cunningham, F., Hoya, M. de la, Diekhans, M., Dolinsky, J., Dwight, S., Eccles, D., Feng, B., Fiume, M., Flicek, P., Gaudet, P., Garcia, E.G., Haendel, M., Haeussler, M., Hahnen, E., Houdayer, C., Hunt, S., James, P., Lebo, M., Lee, J., Lerner-Ellis, J., Lin, M., Lincoln, S., Malheiro, A., Mesenkamp, A., Monteiro, A., Natzijl-Visser, E., Ngeow, J., North, K., Parkinson, H., Paschall, J., Patrinos, G., Phimister, B., Radice, P., Rainville, I., Rasmussen, M., Riley, G., Rouleau, E., Schmutzler, R., Shefchek, K., Sofia, H., Southey, M., Stuart, J., Thomas, J., Toland, A., Truty, R., Turn-Bull, C., Vaur, D., Vreeswijk, M.P.G., Walker, L., Walsh, M., Wappenschmidt, B., Weitzel, J., Wright, M., Zalunin, V., Zaranek, A., Zerbino, D., Zhou, A., Zhou, J., Zook, J., BRCA Challenge Authors, Eng, Charis, Liao, Rachel G [0000-0002-7830-1976], Parsons, Michael T [0000-0003-3242-8477], Alquaddoomi, Faisal [0000-0003-4297-8747], Baxter, Samantha [0000-0003-4616-9234], Coffin, Amy [0000-0003-2723-8222], Currie, Robert [0000-0003-1828-1827], Dlott, Chloe C [0000-0002-7268-7230], Dolman, Lena [0000-0002-3938-588X], Fischmann, Zachary [0000-0002-7687-0972], Foulkes, William D [0000-0001-7427-4651], Goldman, Mary J [0000-0002-9808-6388], Goodhand, Peter [0000-0002-2624-2820], Harrison, Steven [0000-0002-9614-9111], Haussler, David [0000-0003-1533-4575], Markello, Charles [0000-0002-3653-7155], Plon, Sharon E [0000-0002-9626-0936], Rehm, Heidi L [0000-0002-6025-0015], Rubinstein, Wendy S [0000-0002-8790-9959], Tavtigian, Sean [0000-0002-7543-8221], Thorogood, Adrian [0000-0001-5078-8164], Chanock, Stephen [0000-0002-2324-3393], Rätsch, Gunnar [0000-0001-5486-8532], Spurdle, Amanda B [0000-0003-1337-7897], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, Male, Cancer Research, Research Facilities, endocrine system diseases, Epidemiology, Genes, BRCA2, Genes, BRCA1, Social Sciences, Penetrance, QH426-470, Patient advocacy, Database and Informatics Methods, 0302 clinical medicine, Resource (project management), Sociology, Gene Frequency, Consortia, Risk Factors, Databases, Genetic, Medicine and Health Sciences, Aetiology, skin and connective tissue diseases, Genetics (clinical), Cancer, Ovarian Neoplasms, education.field_of_study, Cancer Risk Factors, Genomics, Genomic Databases, 3. Good health, Viewpoints, Phenotype, Oncology, 030220 oncology & carcinogenesis, Female, Research Laboratories, Population, Genetic Causes of Cancer, MEDLINE, Information Dissemination, Breast Neoplasms, Patient Advocacy, Biology, Research and Analysis Methods, Human Genomics, 03 medical and health sciences, Databases, Genetic, Breast Cancer, Genetics, Humans, Genetic Predisposition to Disease, education, Molecular Biology, Ecology, Evolution, Behavior and Systematics, Alleles, Human Genome, Biology and Life Sciences, Computational Biology, Genetic Variation, Genome Analysis, Genomic Libraries, BRCA1, Data science, BRCA2, Data sharing, Health Care, 030104 developmental biology, Biological Databases, Good Health and Well Being, Genes, Genetic Loci, Medical Risk Factors, BRCA Challenge Authors, Mutation, Leiden Open Variation Database, 2.6 Resources and infrastructure (aetiology), Government Laboratories, Developmental Biology
Abstract

The BRCA Challenge is a long-term data-sharing project initiated within the Global Alliance for Genomics and Health (GA4GH) to aggregate BRCA1 and BRCA2 data to support highly collaborative research activities. Its goal is to generate an informed and current understanding of the impact of genetic variation on cancer risk across the iconic cancer predisposition genes, BRCA1 and BRCA2. Initially, reported variants in BRCA1 and BRCA2 available from public databases were integrated into a single, newly created site, www.brcaexchange.org. The purpose of the BRCA Exchange is to provide the community with a reliable and easily accessible record of variants interpreted for a high-penetrance phenotype. More than 20,000 variants have been aggregated, three times the number found in the next-largest public database at the project’s outset, of which approximately 7,250 have expert classifications. The data set is based on shared information from existing clinical databases—Breast Cancer Information Core (BIC), ClinVar, and the Leiden Open Variation Database (LOVD)—as well as population databases, all linked to a single point of access. The BRCA Challenge has brought together the existing international Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium expert panel, along with expert clinicians, diagnosticians, researchers, and database providers, all with a common goal of advancing our understanding of BRCA1 and BRCA2 variation. Ongoing work includes direct contact with national centers with access to BRCA1 and BRCA2 diagnostic data to encourage data sharing, development of methods suitable for extraction of genetic variation at the level of individual laboratory reports, and engagement with participant communities to enable a more comprehensive understanding of the clinical significance of genetic variation in BRCA1 and BRCA2., Author summary The goal of this study and paper has been to develop an international resource to generate an informed and current understanding of the impact of genetic variation on cancer risk across the cancer predisposition genes, BRCA1 and BRCA2. Reported variants in BRCA1 and BRCA2 available from public databases were integrated into a single, newly created site, www.brcaexchange.org, to provide a reliable and easily accessible record of variants interpreted for a high-penetrance phenotype.

Published
2018

12. Computational pan-genomics: Status, promises and challenges

Author

Marschall, T. (Tanja), Marz, M. (Manja), Abeel, T. (Thomas), Dijkstra, L. (Louis), Dutilh, B.E. (Bas), Ghaffaari, A. (Ali), Kersey, P. (Paul), Kloosterman, W.P. (Wigard), Mäkinen, V. (Veli), Novak, A.M. (Adam M.), Paten, B. (Benedict), Porubsky, D. (David), Rivals, E. (Eric), Alkan, C. (Can), Baaijens, J.A. (Jasmijn A.), Bakker, P.I.W. (Paul) de, Boeva, V. (Valentina), Bonnal, R.J.P. (Raoul J.P.), Chiaromonte, F. (Francesca), Chikhi, R. (Rayan), Ciccarelli, F.D. (Francesca D.), Cijvat, R. (Robin), Datema, E. (Erwin), Duijn, C.M. (Cornelia) van, Eichler, E.E. (Evan), Ernst, C. (Corinna), Eskin, E. (E.), Garrison, E. (Erik), El-Kebir, M. (Mohammed), Klau, G.W. (Gunnar W.), Korbel, J.O. (Jan), Lameijer, E.-W. (Eric-Wubbo), Langmead, B. (Benjamin), Martin, M. (Marcel), Medvedev, P. (Paul), Mu, J.C. (John C.), Neerincx, P.B.T. (Pieter B T), Ouwens, K. (Klaasjan), Peterlongo, P. (Pierre), Pisanti, N. (Nadia), Rahmann, S. (S.), Raphael, B.J. (Benjamin J.), Reinert, K. (Knut), Ridder, D. (Dick) de, de Ridder, J. (Jeroen), Schlesner, M. (Matthias), Schulz-Trieglaff, O. (Ole), Sanders, A.D. (Ashley D.), Sheikhizadeh, S. (Siavash), Shneider, C. (Carl), Smit, S. (Sandra), Valenzuela, D. (Daniel), Wang, J. (Jiayin), Wessels, L. (Lodewyk), Zhang, Y. (Ying), Guryev, V. (Victor), Vandin, F. (Fabio), Ye, K. (Kai), Schönhuth, A. (Alexander), Marschall, T. (Tanja), Marz, M. (Manja), Abeel, T. (Thomas), Dijkstra, L. (Louis), Dutilh, B.E. (Bas), Ghaffaari, A. (Ali), Kersey, P. (Paul), Kloosterman, W.P. (Wigard), Mäkinen, V. (Veli), Novak, A.M. (Adam M.), Paten, B. (Benedict), Porubsky, D. (David), Rivals, E. (Eric), Alkan, C. (Can), Baaijens, J.A. (Jasmijn A.), Bakker, P.I.W. (Paul) de, Boeva, V. (Valentina), Bonnal, R.J.P. (Raoul J.P.), Chiaromonte, F. (Francesca), Chikhi, R. (Rayan), Ciccarelli, F.D. (Francesca D.), Cijvat, R. (Robin), Datema, E. (Erwin), Duijn, C.M. (Cornelia) van, Eichler, E.E. (Evan), Ernst, C. (Corinna), Eskin, E. (E.), Garrison, E. (Erik), El-Kebir, M. (Mohammed), Klau, G.W. (Gunnar W.), Korbel, J.O. (Jan), Lameijer, E.-W. (Eric-Wubbo), Langmead, B. (Benjamin), Martin, M. (Marcel), Medvedev, P. (Paul), Mu, J.C. (John C.), Neerincx, P.B.T. (Pieter B T), Ouwens, K. (Klaasjan), Peterlongo, P. (Pierre), Pisanti, N. (Nadia), Rahmann, S. (S.), Raphael, B.J. (Benjamin J.), Reinert, K. (Knut), Ridder, D. (Dick) de, de Ridder, J. (Jeroen), Schlesner, M. (Matthias), Schulz-Trieglaff, O. (Ole), Sanders, A.D. (Ashley D.), Sheikhizadeh, S. (Siavash), Shneider, C. (Carl), Smit, S. (Sandra), Valenzuela, D. (Daniel), Wang, J. (Jiayin), Wessels, L. (Lodewyk), Zhang, Y. (Ying), Guryev, V. (Victor), Vandin, F. (Fabio), Ye, K. (Kai), and Schönhuth, A. (Alexander)

Abstract

Many disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case of Homo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next few years. Simply scaling up established bioinformatics pipelines will not be sufficient for leveraging the full potential of such rich genomic data sets. Instead, novel, qualitatively different Computational methods and paradigms are needed.We will witness the rapid extension of Computational pan-genomics, a new sub-area of research in Computational biology. In this article, we generalize existing definitions and understand a pangenome as any collection of genomic sequences to be analyzed jointly or to be used as a reference. We examine already available approaches to construct and use pan-genomes, discuss the potential benefits of future technologies and methodologies and review open challenges from the vantage point of the above-mentioned biological disciplines. As a prominent example for a Computational paradigm shift, we particularly highlight the transition from the representation of reference genomes as strings to representations a

Published
2018
Full Text
View/download PDF

13. Computational pan-genomics: status, promises and challenges.

Author

Marschall, T., Marz, M., Abeel, T., Dijkstra, L., Dutilh, B.E., Ghaffaari, A., Kersey, P., Kloosterman, W.P., Mäkinen, V., Novak, A.M., Paten, B., Porubsky, D., Rivals, E., Alkan, C., Baaijens, J., Bakker, P.I. de, Boeva, V., Bonnal, R.J., Chiaromonte, F., Chikhi, R., Ciccarelli, F.D., Cijvat, R., Datema, E., Duijn, C.M. van, Eichler, E.E., Ernst, C., Eskin, E., Garrison, E., El-Kebir, M., Klau, G.W., Korbel, J.O., Lameijer, E.W., Langmead, B., Martin, M., Medvedev, P., Mu, J.C., Neerincx, P., Ouwens, K., Peterlongo, P., Pisanti, N., Rahmann, S., Raphael, B., Reinert, K., Ridder, D. de, Ridder, J. de, Schlesner, M., Schulz-Trieglaff, O., Sanders, A.D., Sheikhizadeh, S., Shneider, C., Smit, S., Valenzuela, D., Wang, J, Wessels, L., Zhang, Y, Guryev, V., Vandin, F., Ye, K., Schönhuth, A., Marschall, T., Marz, M., Abeel, T., Dijkstra, L., Dutilh, B.E., Ghaffaari, A., Kersey, P., Kloosterman, W.P., Mäkinen, V., Novak, A.M., Paten, B., Porubsky, D., Rivals, E., Alkan, C., Baaijens, J., Bakker, P.I. de, Boeva, V., Bonnal, R.J., Chiaromonte, F., Chikhi, R., Ciccarelli, F.D., Cijvat, R., Datema, E., Duijn, C.M. van, Eichler, E.E., Ernst, C., Eskin, E., Garrison, E., El-Kebir, M., Klau, G.W., Korbel, J.O., Lameijer, E.W., Langmead, B., Martin, M., Medvedev, P., Mu, J.C., Neerincx, P., Ouwens, K., Peterlongo, P., Pisanti, N., Rahmann, S., Raphael, B., Reinert, K., Ridder, D. de, Ridder, J. de, Schlesner, M., Schulz-Trieglaff, O., Sanders, A.D., Sheikhizadeh, S., Shneider, C., Smit, S., Valenzuela, D., Wang, J, Wessels, L., Zhang, Y, Guryev, V., Vandin, F., Ye, K., and Schönhuth, A.

Abstract

Contains fulltext : 190288.pdf (publisher's version ) (Open Access)

Published
2018

14. Computational pan-genomics: status, promises and challenges

Author

The Computational Pan-Genomics Consortium, Marschall, T. (Tobias), Marz, M. (Manja), Abeel, T. (Thomas), Dijkstra, L.J. (Louis), Dutilh, B.E. (Bas), Ghaffaari, A. (Ali), Kersey, P. (Paul), Kloosterman, W.P. (Wigard), Mäkinen, V. (Veli), Novak, A.M. (Adam), Paten, B. (Benedict), Porubsky, D. (David), Rivals, E. (Eric), Alkan, C. (Can), Baaijens, J.A. (Jasmijn), Bakker, P.I.W. (Paul) de, Boeva, V. (Valentina), Bonnal, R.J.P. (Raoul), Chiaromonte, F. (Francesca), Chikhi, R. (Rayan), Ciccarelli, F.D. (Francesca), Cijvat, C.P. (Robin), Datema, E. (Erwin), Duijn, C.M. (Cornelia) van, Eichler, E.E. (Evan), Ernst, C. (Corinna), Eskin, E. (Eleazar), Garrison, E. (Erik), El-Kebir, M. (Mohammed), Klau, G.W. (Gunnar), Korbel, J.O. (Jan), Lameijer, E.-W. (Eric-Wubbo), Langmead, B. (Benjamin), Martin, M. (Marcel), Medvedev, P. (Paul), Mu, J.C. (John), Neerincx, P.B.T. (Pieter), Ouwens, K. (Klaasjan), Peterlongo, P. (Pierre), Pisanti, N. (Nadia), Rahmann, S. (Sven), Raphael, B.J. (Benjamin), Reinert, K. (Knut), Ridder, D. (Dick) de, Ridder, J. (Jeroen) de, Schlesner, M. (Matthias), Schulz-Trieglaff, O. (Ole), Sanders, A.D. (Ashley), Sheikhizadeh, S. (Siavash), Shneider, C. (Carl), Smit, S. (Sandra), Valenzuela, D. (Daniel), Wang, J. (Jiayin), Wessels, L.F.A. (Lodewyk), Zhang, Y. (Ying), Guryev, V. (Victor), Vandin, F. (Fabio), Ye, K. (Kai), Schönhuth, A. (Alexander), The Computational Pan-Genomics Consortium, Marschall, T. (Tobias), Marz, M. (Manja), Abeel, T. (Thomas), Dijkstra, L.J. (Louis), Dutilh, B.E. (Bas), Ghaffaari, A. (Ali), Kersey, P. (Paul), Kloosterman, W.P. (Wigard), Mäkinen, V. (Veli), Novak, A.M. (Adam), Paten, B. (Benedict), Porubsky, D. (David), Rivals, E. (Eric), Alkan, C. (Can), Baaijens, J.A. (Jasmijn), Bakker, P.I.W. (Paul) de, Boeva, V. (Valentina), Bonnal, R.J.P. (Raoul), Chiaromonte, F. (Francesca), Chikhi, R. (Rayan), Ciccarelli, F.D. (Francesca), Cijvat, C.P. (Robin), Datema, E. (Erwin), Duijn, C.M. (Cornelia) van, Eichler, E.E. (Evan), Ernst, C. (Corinna), Eskin, E. (Eleazar), Garrison, E. (Erik), El-Kebir, M. (Mohammed), Klau, G.W. (Gunnar), Korbel, J.O. (Jan), Lameijer, E.-W. (Eric-Wubbo), Langmead, B. (Benjamin), Martin, M. (Marcel), Medvedev, P. (Paul), Mu, J.C. (John), Neerincx, P.B.T. (Pieter), Ouwens, K. (Klaasjan), Peterlongo, P. (Pierre), Pisanti, N. (Nadia), Rahmann, S. (Sven), Raphael, B.J. (Benjamin), Reinert, K. (Knut), Ridder, D. (Dick) de, Ridder, J. (Jeroen) de, Schlesner, M. (Matthias), Schulz-Trieglaff, O. (Ole), Sanders, A.D. (Ashley), Sheikhizadeh, S. (Siavash), Shneider, C. (Carl), Smit, S. (Sandra), Valenzuela, D. (Daniel), Wang, J. (Jiayin), Wessels, L.F.A. (Lodewyk), Zhang, Y. (Ying), Guryev, V. (Victor), Vandin, F. (Fabio), Ye, K. (Kai), and Schönhuth, A. (Alexander)

Abstract

Many disciplines, from human genetics and oncology to plant breeding, microbiology and virology, commonly face the challenge of analyzing rapidly increasing numbers of genomes. In case of Homo sapiens, the number of sequenced genomes will approach hundreds of thousands in the next few years. Simply scaling up established bioinformatics pipelines will not be sufficient for leveraging the full potential of such rich genomic data sets. Instead, novel, qualitatively different computational methods and paradigms are needed. We will witness the rapid extension of computational pan-genomics, a new sub-area of research in computational biology. In this article, we generalize existing definitions and understand a pan-genome as any collection of genomic sequences to be analyzed jointly or to be used as a reference. We examine already available approaches to construct and use pan-genomes, discuss the potential benefits of future technologies and methodologies and review open challenges from the vantage point of the above-mentioned biological disciplines. As a prominent example for a computational paradigm shift, we particularly highlight the transition from the representation of reference genomes as strings to representations as graphs. We outline how this and other challenges from different application domains translate into common computational problems, point out relevant bioinformatics techniques and identify open problems in computer science. With this review, we aim to increase awareness that a joint approach to computational pan-genomics can help address many of the problems currently faced in various domains.

Published
2018
Full Text
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15. TrawlerWeb: an online de novo motif discovery tool for next-generation sequencing datasets

Author

Dang, LT, Tondl, M, Chiu, MHH, Revote, J, Paten, B, Tano, V, Tokolyi, A, Besse, F, Quaife-Ryan, G, Cumming, H, Drvodelic, MJ, Eichenlaub, MP, Hallab, JC, Stolper, JS, Rossello, FJ, Bogoyevitch, MA, Jans, DA, Nim, HT, Porrello, ER, Hudson, JE, Ramialison, M, Dang, LT, Tondl, M, Chiu, MHH, Revote, J, Paten, B, Tano, V, Tokolyi, A, Besse, F, Quaife-Ryan, G, Cumming, H, Drvodelic, MJ, Eichenlaub, MP, Hallab, JC, Stolper, JS, Rossello, FJ, Bogoyevitch, MA, Jans, DA, Nim, HT, Porrello, ER, Hudson, JE, and Ramialison, M

Abstract

BACKGROUND: A strong focus of the post-genomic era is mining of the non-coding regulatory genome in order to unravel the function of regulatory elements that coordinate gene expression (Nat 489:57-74, 2012; Nat 507:462-70, 2014; Nat 507:455-61, 2014; Nat 518:317-30, 2015). Whole-genome approaches based on next-generation sequencing (NGS) have provided insight into the genomic location of regulatory elements throughout different cell types, organs and organisms. These technologies are now widespread and commonly used in laboratories from various fields of research. This highlights the need for fast and user-friendly software tools dedicated to extracting cis-regulatory information contained in these regulatory regions; for instance transcription factor binding site (TFBS) composition. Ideally, such tools should not require prior programming knowledge to ensure they are accessible for all users. RESULTS: We present TrawlerWeb, a web-based version of the Trawler_standalone tool (Nat Methods 4:563-5, 2007; Nat Protoc 5:323-34, 2010), to allow for the identification of enriched motifs in DNA sequences obtained from next-generation sequencing experiments in order to predict their TFBS composition. TrawlerWeb is designed for online queries with standard options common to web-based motif discovery tools. In addition, TrawlerWeb provides three unique new features: 1) TrawlerWeb allows the input of BED files directly generated from NGS experiments, 2) it automatically generates an input-matched biologically relevant background, and 3) it displays resulting conservation scores for each instance of the motif found in the input sequences, which assists the researcher in prioritising the motifs to validate experimentally. Finally, to date, this web-based version of Trawler_standalone remains the fastest online de novo motif discovery tool compared to other popular web-based software, while generating predictions with high accuracy. CONCLUSIONS: TrawlerWeb provides users with a fa

Published
2018

16. Computational pan-genomics: status, promises and challenges

Author

Marschall, T, Marz, M, Abeel, T, Dijkstra, L, Dutilh, BE, Ghaffaari, A, Kersey, P, Kloosterman, WP, Makinen, V, Novak, AM, Paten, B, Porubsky, D, Rivals, E, Alkan, C, Baaijens, J A, de Bakker, PIW, Boeva, V, Bonnal, RJP, Chiaromonte, F, Chikhi, R, Ciccarelli, FD, Cijvat, R, Datema, E, Duijn, Cornelia, Eichler, EE, Ernst, C, Eskin, E, Garrison, E, El-Kebir, M, Klau, GW, Korbel, JO, Lameijer, EW, Langmead, B, Martin, M, Medvedev, P, Mu, JC, Neerincx, P, Ouwens, K, Peterlongo, P, Pisanti, N, Rahmann, S, Raphael, B, Reinert, K, Ridder, D, Ridder, J (Jannemarie), Schlesner, M, Schulz-Trieglaff, O, Sanders, AD, Sheikhizadeh, S, Shneider, C, Smit, S, Valenzuela, D, Wang, JY, Wessels, L, Zhang, Y, Guryev, V, Vandin, F, Ye, K, Schonhuth, A, Marschall, T, Marz, M, Abeel, T, Dijkstra, L, Dutilh, BE, Ghaffaari, A, Kersey, P, Kloosterman, WP, Makinen, V, Novak, AM, Paten, B, Porubsky, D, Rivals, E, Alkan, C, Baaijens, J A, de Bakker, PIW, Boeva, V, Bonnal, RJP, Chiaromonte, F, Chikhi, R, Ciccarelli, FD, Cijvat, R, Datema, E, Duijn, Cornelia, Eichler, EE, Ernst, C, Eskin, E, Garrison, E, El-Kebir, M, Klau, GW, Korbel, JO, Lameijer, EW, Langmead, B, Martin, M, Medvedev, P, Mu, JC, Neerincx, P, Ouwens, K, Peterlongo, P, Pisanti, N, Rahmann, S, Raphael, B, Reinert, K, Ridder, D, Ridder, J (Jannemarie), Schlesner, M, Schulz-Trieglaff, O, Sanders, AD, Sheikhizadeh, S, Shneider, C, Smit, S, Valenzuela, D, Wang, JY, Wessels, L, Zhang, Y, Guryev, V, Vandin, F, Ye, K, and Schonhuth, A

Published
2018

17. Nanopore sequencing and assembly of a human genome with ultra-long reads

Author

Jain, Miten, primary, Koren, S, additional, Quick, J, additional, Rand, AC, additional, Sasani, TA, additional, Tyson, JR, additional, Beggs, AD, additional, Dilthey, AT, additional, Fiddes, IT, additional, Malla, S, additional, Marriott, H, additional, Miga, KH, additional, Nieto, T, additional, O’Grady, J, additional, Olsen, HE, additional, Pedersen, BS, additional, Rhie, A, additional, Richardson, H, additional, Quinlan, AR, additional, Snutch, TP, additional, Tee, L, additional, Paten, B, additional, Phillippy, AM, additional, Simpson, JT, additional, Loman, NJ, additional, and Loose, M, additional

Published
2017
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18. Guilt by multiple association

Author

Etwiller, L. and Paten, B.

Subjects
Homology (Biology) -- Research, Nucleotide sequence -- Research, Computational biology -- Research, Biological sciences
Abstract

New approaches in computational comparative genomics make use of the additional information in evolutionary associations to infer co-dependencies between genes, which may imply that they interact functionally. This type of reasoning makes use of genomic sequence data, and are applied to nonhomologous gene that share an evolutionary association.

Published
2004

19. Phylogenetic automata, pruning, and multiple alignment

Author

Westesson, O, Lunter, G, Paten, B, and Holmes, I

Subjects
Genomics (q-bio.GN), FOS: Biological sciences, Populations and Evolution (q-bio.PE), Quantitative Biology - Genomics, Quantitative Biology - Populations and Evolution, Quantitative Biology - Quantitative Methods, Quantitative Methods (q-bio.QM)
Abstract

We present an extension of Felsenstein's algorithm to indel models defined on entire sequences, without the need to condition on one multiple alignment. The algorithm makes use of a generalization from probabilistic substitution matrices to weighted finite-state transducers. Our approach may equivalently be viewed as a probabilistic formulation of progressive multiple sequence alignment, using partial-order graphs to represent ensemble profiles of ancestral sequences. We present a hierarchical stochastic approximation technique which makes this algorithm tractable for alignment analyses of reasonable size., 96 pages: background, informal tutorial, and formal definitions

Published
2014

20. Long-read sequence assembly of the gorilla genome

Author

Gordon, D., primary, Huddleston, J., additional, Chaisson, M. J. P., additional, Hill, C. M., additional, Kronenberg, Z. N., additional, Munson, K. M., additional, Malig, M., additional, Raja, A., additional, Fiddes, I., additional, Hillier, L. W., additional, Dunn, C., additional, Baker, C., additional, Armstrong, J., additional, Diekhans, M., additional, Paten, B., additional, Shendure, J., additional, Wilson, R. K., additional, Haussler, D., additional, Chin, C.-S., additional, and Eichler, E. E., additional

Published
2016
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21. The Matchmaker Exchange: a platform for rare disease gene discovery

Author

Philippakis, A.A., Azzariti, D.R., Beltran, S., Brookes, A.J., Brownstein, C.A., Brudno, M., Brunner, H.G., Buske, O.J., Carey, K., Doll, C., Dumitriu, S., Dyke, S.O.M., Dunnen, J.T. den, Firth, H.V., Gibbs, R.A., Girdea, M., Gonzalez, M., Haendel, M.A., Hamosh, A., Holm, I.A., Huang, L., Hurles, M.E., Hutton, B., Krier, J.B., Misyura, A., Mungall, C.J., Paschall, J., Paten, B., Robinson, P.N., Schiettecatte, F., Sobreira, N.L., Swaminathan, G.J., Taschner, P.E.M., Terry, S.F., Washington, N.L., Zuchner, S., Boycott, K.M., Rehm, H.L., Philippakis, A.A., Azzariti, D.R., Beltran, S., Brookes, A.J., Brownstein, C.A., Brudno, M., Brunner, H.G., Buske, O.J., Carey, K., Doll, C., Dumitriu, S., Dyke, S.O.M., Dunnen, J.T. den, Firth, H.V., Gibbs, R.A., Girdea, M., Gonzalez, M., Haendel, M.A., Hamosh, A., Holm, I.A., Huang, L., Hurles, M.E., Hutton, B., Krier, J.B., Misyura, A., Mungall, C.J., Paschall, J., Paten, B., Robinson, P.N., Schiettecatte, F., Sobreira, N.L., Swaminathan, G.J., Taschner, P.E.M., Terry, S.F., Washington, N.L., Zuchner, S., Boycott, K.M., and Rehm, H.L.

Abstract

Item does not contain fulltext, There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.

Published
2015

22. Ancestral patterns of evolution among archosaurs

Author

Green, RE, Green, RE, Braun, EL, Armstrong, J, Earl, D, Nguyen, N, Hickey, G, Vandewege, MW, St John, JA, Capella-Gutiérrez, S, Castoe, TA, Kern, C, Fujita, MK, Opazo, JC, Jurka, J, Kojima, KK, Caballero, J, Hubley, RM, Smit, AF, Platt, RN, Lavoie, CA, Ramakodi, MP, Finger, JW, Suh, A, Isberg, SR, Miles, L, Chong, AY, Jaratlerdsiri, W, Gongora, J, Moran, C, Iriarte, A, McCormack, J, Burgess, SC, Edwards, SV, Lyons, E, Williams, C, Breen, M, Howard, JT, Gresham, CR, Peterson, DG, Schmitz, J, Pollock, DD, Haussler, D, Triplett, EW, Zhang, G, Irie, N, Jarvis, ED, Brochu, CA, Schmidt, CJ, McCarthy, FM, Faircloth, BC, Hoffmann, FG, Glenn, TC, Gabaldón, T, Paten, B, Ray, DA, Green, RE, Green, RE, Braun, EL, Armstrong, J, Earl, D, Nguyen, N, Hickey, G, Vandewege, MW, St John, JA, Capella-Gutiérrez, S, Castoe, TA, Kern, C, Fujita, MK, Opazo, JC, Jurka, J, Kojima, KK, Caballero, J, Hubley, RM, Smit, AF, Platt, RN, Lavoie, CA, Ramakodi, MP, Finger, JW, Suh, A, Isberg, SR, Miles, L, Chong, AY, Jaratlerdsiri, W, Gongora, J, Moran, C, Iriarte, A, McCormack, J, Burgess, SC, Edwards, SV, Lyons, E, Williams, C, Breen, M, Howard, JT, Gresham, CR, Peterson, DG, Schmitz, J, Pollock, DD, Haussler, D, Triplett, EW, Zhang, G, Irie, N, Jarvis, ED, Brochu, CA, Schmidt, CJ, McCarthy, FM, Faircloth, BC, Hoffmann, FG, Glenn, TC, Gabaldón, T, Paten, B, and Ray, DA

Abstract

To provide context for the diversification of archosaurs-the group that includes crocodilians, dinosaurs, and birds-we generated draft genomes of three crocodilians: Alligator mississippiensis (the American alligator), Crocodylus porosus (the saltwater crocodile), and Gavialis gangeticus (the Indian gharial). We observed an exceptionally slow rate of genome evolution within crocodilians at all levels, including nucleotide substitutions, indels, transposable element content and movement, gene family evolution, and chromosomal synteny. When placed within the context of related taxa including birds and turtles, this suggests that the common ancestor of all of these taxa also exhibited slow genome evolution and that the comparatively rapid evolution is derived in birds. The data also provided the opportunity to analyze heterozygosity in crocodilians, which indicates a likely reduction in population size for all three taxa through the Pleistocene. Finally, these data combined with newly published bird genomes allowed us to reconstruct the partial genome of the common ancestor of archosaurs, thereby providing a tool to investigate the genetic starting material of crocodilians, birds, and dinosaurs.

Published
2014

23. Alignathon: A competitive assessment of whole-genome alignment methods

Author

Earl, D, Nguyen, N, Hickey, G, Harris, RS, Fitzgerald, S, Beal, K, Seledtsov, I, Molodtsov, V, Raney, BJ, Clawson, H, Kim, J, Kemena, C, Chang, JM, Erb, I, Poliakov, A, Hou, M, Herrero, J, Kent, WJ, Solovyev, V, Darling, AE, Ma, J, Notredame, C, Brudno, M, Dubchak, I, Haussler, D, Paten, B, Earl, D, Nguyen, N, Hickey, G, Harris, RS, Fitzgerald, S, Beal, K, Seledtsov, I, Molodtsov, V, Raney, BJ, Clawson, H, Kim, J, Kemena, C, Chang, JM, Erb, I, Poliakov, A, Hou, M, Herrero, J, Kent, WJ, Solovyev, V, Darling, AE, Ma, J, Notredame, C, Brudno, M, Dubchak, I, Haussler, D, and Paten, B

Abstract

© 2014 Earl et al. Multiple sequence alignments (MSAs) are a prerequisite for a wide variety of evolutionary analyses. Published assessments and benchmark data sets for protein and, to a lesser extent, global nucleotide MSAs are available, but less effort has been made to establish benchmarks in the more general problem of whole-genome alignment (WGA). Using the same model as the successful Assemblathon competitions, we organized a competitive evaluation in which teams submitted their alignments and then assessments were performed collectively after all the submissions were received. Three data sets were used: Two were simulated and based on primate and mammalian phylogenies, and one was comprised of 20 real fly genomes. In total, 35 submissions were assessed, submitted by 10 teams using 12 different alignment pipelines. We found agreement between independent simulation-based and statistical assessments, indicating that there are substantial accuracy differences between contemporary alignment tools. We saw considerable differences in the alignment quality of differently annotated regions and found that few tools aligned the duplications analyzed. We found that many tools worked well at shorter evolutionary distances, but fewer performed competitively at longer distances. We provide all data sets, submissions, and assessment programs for further study and provide, as a resource for future benchmarking, a convenient repository of code and data for reproducing the simulation assessments.

Published
2014

24. Assemblathon 2 : Evaluating de novo methods of genome assembly in three vertebrate species

Author

Bradnam, K. R., Fass, J. N., Alexandrov, A., Baranay, P., Bechner, M., Birol, I., Boisvert, S., Chapman, J. A., Chapuis, G., Chikhi, R., Chitsaz, H., Chou, W. -C, Corbeil, J., Fabbro, C. D., Docking, T. R., Durbin, R., Earl, D., Emrich, S., Fedotov, P., Fonseca, N. A., Ganapathy, G., Gibbs, R. A., Gnerre, S., Godzaridis, E., Goldstein, S., Haimel, M., Hall, G., Haussler, D., Hiatt, J. B., Ho, I. Y., Howard, J., Hunt, M., Jackman, S. D., Jaffe, D. B., Jarvis, E. D., Jiang, H., Kazakov, S., Kersey, P. J., Kitzman, J. O., Knight, J. R., Koren, S., Lam, T. -W, Lavenier, D., Laviolette, F., Li, Y., Li, Z., Liu, B., Liu, Y., Luo, R., MacCallum, I., MacManes, M. D., Maillet, N., Melnikov, S., Naquin, D., Ning, Z., Otto, T. D., Paten, B., Paulo, O. S., Phillippy, A. M., Pina-Martins, F., Place, M., Przybylski, D., Qin, X., Qu, C., Ribeiro, F. J., Richards, S., Rokhsar, D. S., Ruby, J. G., Scalabrin, S., Schatz, M. C., Schwartz, D. C., Sergushichev, A., Sharpe, T., Shaw, T. I., Shendure, J., Shi, Y., Simpson, J. T., Song, H., Tsarev, F., Vezzi, F., Vicedomini, R., Vieira, B. M., Wang, J., Worley, K. C., Yin, S., Yiu, S. -M, Yuan, J., Zhang, G., Zhang, H., Zhou, S., Korf, I. F., Bradnam, K. R., Fass, J. N., Alexandrov, A., Baranay, P., Bechner, M., Birol, I., Boisvert, S., Chapman, J. A., Chapuis, G., Chikhi, R., Chitsaz, H., Chou, W. -C, Corbeil, J., Fabbro, C. D., Docking, T. R., Durbin, R., Earl, D., Emrich, S., Fedotov, P., Fonseca, N. A., Ganapathy, G., Gibbs, R. A., Gnerre, S., Godzaridis, E., Goldstein, S., Haimel, M., Hall, G., Haussler, D., Hiatt, J. B., Ho, I. Y., Howard, J., Hunt, M., Jackman, S. D., Jaffe, D. B., Jarvis, E. D., Jiang, H., Kazakov, S., Kersey, P. J., Kitzman, J. O., Knight, J. R., Koren, S., Lam, T. -W, Lavenier, D., Laviolette, F., Li, Y., Li, Z., Liu, B., Liu, Y., Luo, R., MacCallum, I., MacManes, M. D., Maillet, N., Melnikov, S., Naquin, D., Ning, Z., Otto, T. D., Paten, B., Paulo, O. S., Phillippy, A. M., Pina-Martins, F., Place, M., Przybylski, D., Qin, X., Qu, C., Ribeiro, F. J., Richards, S., Rokhsar, D. S., Ruby, J. G., Scalabrin, S., Schatz, M. C., Schwartz, D. C., Sergushichev, A., Sharpe, T., Shaw, T. I., Shendure, J., Shi, Y., Simpson, J. T., Song, H., Tsarev, F., Vezzi, F., Vicedomini, R., Vieira, B. M., Wang, J., Worley, K. C., Yin, S., Yiu, S. -M, Yuan, J., Zhang, G., Zhang, H., Zhou, S., and Korf, I. F.

Abstract

Background: The process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly. Results: In Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies. Conclusions: Many current genome assemblers produced useful assemblies, containing a significant representation of their genes and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another., QC 20170307

Published
2013
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25. Assemblathon 1: A competitive assessment of de novo short read assembly methods

Author

Earl, D, Bradnam, K, St. John, J, Darling, A, Lin, D, Fass, J, Yu, HOK, Buffalo, V, Zerbino, DR, Diekhans, M, Nguyen, N, Ariyaratne, PN, Sung, WK, Ning, Z, Haimel, M, Simpson, JT, Fonseca, NA, Birol, I, Docking, TR, Ho, IY, Rokhsar, DS, Chikhi, R, Lavenier, D, Chapuis, G, Naquin, D, Maillet, N, Schatz, MC, Kelley, DR, Phillippy, AM, Koren, S, Yang, SP, Wu, W, Chou, WC, Srivastava, A, Shaw, TI, Ruby, JG, Skewes-Cox, P, Betegon, M, Dimon, MT, Solovyev, V, Seledtsov, I, Kosarev, P, Vorobyev, D, Ramirez-Gonzalez, R, Leggett, R, MacLean, D, Xia, F, Luo, R, Li, Z, Xie, Y, Liu, B, Gnerre, S, MacCallum, I, Przybylski, D, Ribeiro, FJ, Sharpe, T, Hall, G, Kersey, PJ, Durbin, R, Jackman, SD, Chapman, JA, Huang, X, DeRisi, JL, Caccamo, M, Li, Y, Jaffe, DB, Green, RE, Haussler, D, Korf, I, Paten, B, Earl, D, Bradnam, K, St. John, J, Darling, A, Lin, D, Fass, J, Yu, HOK, Buffalo, V, Zerbino, DR, Diekhans, M, Nguyen, N, Ariyaratne, PN, Sung, WK, Ning, Z, Haimel, M, Simpson, JT, Fonseca, NA, Birol, I, Docking, TR, Ho, IY, Rokhsar, DS, Chikhi, R, Lavenier, D, Chapuis, G, Naquin, D, Maillet, N, Schatz, MC, Kelley, DR, Phillippy, AM, Koren, S, Yang, SP, Wu, W, Chou, WC, Srivastava, A, Shaw, TI, Ruby, JG, Skewes-Cox, P, Betegon, M, Dimon, MT, Solovyev, V, Seledtsov, I, Kosarev, P, Vorobyev, D, Ramirez-Gonzalez, R, Leggett, R, MacLean, D, Xia, F, Luo, R, Li, Z, Xie, Y, Liu, B, Gnerre, S, MacCallum, I, Przybylski, D, Ribeiro, FJ, Sharpe, T, Hall, G, Kersey, PJ, Durbin, R, Jackman, SD, Chapman, JA, Huang, X, DeRisi, JL, Caccamo, M, Li, Y, Jaffe, DB, Green, RE, Haussler, D, Korf, I, and Paten, B

Abstract

Low-cost short read sequencing technology has revolutionized genomics, though it is only just becoming practical for the high-quality de novo assembly of a novel large genome. We describe the Assemblathon 1 competition, which aimed to comprehensively assess the state of the art in de novo assembly methods when applied to current sequencing technologies. In a collaborative effort, teams were asked to assemble a simulated Illumina HiSeq data set of an unknown, simulated diploid genome. A total of 41 assemblies from 17 different groups were received. Novel haplotype aware assessments of coverage, contiguity, structure, base calling, and copy number were made. We establish that within this benchmark: (1) It is possible to assemble the genome to a high level of coverage and accuracy, and that (2) large differences exist between the assemblies, suggesting room for further improvements in current methods. The simulated benchmark, including the correct answer, the assemblies, and the code that was used to evaluate the assemblies is now public and freely available from http://www.assemblathon.org/. © 2011 by Cold Spring Harbor Laboratory Press.

Published
2011

27. Nanopore sequencing and assembly of a human genome with ultra-long reads

Author

Jain, M., Koren, S., Miga, K.H., Quick, J., Rand, A.C., Sasani, T.A., Tyson, J.R., Beggs, A.D., Dilthey, A.T., Fiddes, I.T., Malla, S., Marriott, H., Nieto, T., O'Grady, J., Olsen, H.E., Pedersen, B.S., Rhie, A., Richardson, H., Quinlan, A.R., Snutch, T.P., Tee, L., Paten, B., Phillippy, A.M., Simpson, J.T., Loman, N.J., Loose, M., Jain, M., Koren, S., Miga, K.H., Quick, J., Rand, A.C., Sasani, T.A., Tyson, J.R., Beggs, A.D., Dilthey, A.T., Fiddes, I.T., Malla, S., Marriott, H., Nieto, T., O'Grady, J., Olsen, H.E., Pedersen, B.S., Rhie, A., Richardson, H., Quinlan, A.R., Snutch, T.P., Tee, L., Paten, B., Phillippy, A.M., Simpson, J.T., Loman, N.J., and Loose, M.

Abstract

We report the sequencing and assembly of a reference genome for the human GM12878 Utah/Ceph cell line using the MinION (Oxford Nanopore Technologies) nanopore sequencer. 91.2 Gb of sequence data, representing ~30× theoretical coverage, were produced. Reference-based alignment enabled detection of large structural variants and epigenetic modifications. De novo assembly of nanopore reads alone yielded a contiguous assembly (NG50 ~3 Mb). Next, we developed a protocol to generate ultra-long reads (N50 > 100kb, up to 882 kb). Incorporating an additional 5×-coverage of these data more than doubled the assembly contiguity (NG50 ~6.4 Mb). The final assembled genome was 2,867 million bases in size, covering 85.8% of the reference. Assembly accuracy, after incorporating complementary short-read sequencing data, exceeded 99.8%. Ultra-long reads enabled assembly and phasing of the 4 Mb major histocompatibility complex (MHC) locus in its entirety, measurement of telomere repeat length and closure of gaps in the reference human genome assembly GRCh38.

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28. Nanopore sequencing and assembly of a human genome with ultra-long reads

Author

Jain, M., Koren, S., Miga, K.H., Quick, J., Rand, A.C., Sasani, T.A., Tyson, J.R., Beggs, A.D., Dilthey, A.T., Fiddes, I.T., Malla, S., Marriott, H., Nieto, T., O'Grady, J., Olsen, H.E., Pedersen, B.S., Rhie, A., Richardson, H., Quinlan, A.R., Snutch, T.P., Tee, L., Paten, B., Phillippy, A.M., Simpson, J.T., Loman, N.J., Loose, M., Jain, M., Koren, S., Miga, K.H., Quick, J., Rand, A.C., Sasani, T.A., Tyson, J.R., Beggs, A.D., Dilthey, A.T., Fiddes, I.T., Malla, S., Marriott, H., Nieto, T., O'Grady, J., Olsen, H.E., Pedersen, B.S., Rhie, A., Richardson, H., Quinlan, A.R., Snutch, T.P., Tee, L., Paten, B., Phillippy, A.M., Simpson, J.T., Loman, N.J., and Loose, M.

Abstract

We report the sequencing and assembly of a reference genome for the human GM12878 Utah/Ceph cell line using the MinION (Oxford Nanopore Technologies) nanopore sequencer. 91.2 Gb of sequence data, representing ~30× theoretical coverage, were produced. Reference-based alignment enabled detection of large structural variants and epigenetic modifications. De novo assembly of nanopore reads alone yielded a contiguous assembly (NG50 ~3 Mb). Next, we developed a protocol to generate ultra-long reads (N50 > 100kb, up to 882 kb). Incorporating an additional 5×-coverage of these data more than doubled the assembly contiguity (NG50 ~6.4 Mb). The final assembled genome was 2,867 million bases in size, covering 85.8% of the reference. Assembly accuracy, after incorporating complementary short-read sequencing data, exceeded 99.8%. Ultra-long reads enabled assembly and phasing of the 4 Mb major histocompatibility complex (MHC) locus in its entirety, measurement of telomere repeat length and closure of gaps in the reference human genome assembly GRCh38.

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29. Nanopore sequencing and assembly of a human genome with ultra-long reads

Author

Jain, M., Koren, S., Miga, K.H., Quick, J., Rand, A.C., Sasani, T.A., Tyson, J.R., Beggs, A.D., Dilthey, A.T., Fiddes, I.T., Malla, S., Marriott, H., Nieto, T., O'Grady, J., Olsen, H.E., Pedersen, B.S., Rhie, A., Richardson, H., Quinlan, A.R., Snutch, T.P., Tee, L., Paten, B., Phillippy, A.M., Simpson, J.T., Loman, N.J., Loose, M., Jain, M., Koren, S., Miga, K.H., Quick, J., Rand, A.C., Sasani, T.A., Tyson, J.R., Beggs, A.D., Dilthey, A.T., Fiddes, I.T., Malla, S., Marriott, H., Nieto, T., O'Grady, J., Olsen, H.E., Pedersen, B.S., Rhie, A., Richardson, H., Quinlan, A.R., Snutch, T.P., Tee, L., Paten, B., Phillippy, A.M., Simpson, J.T., Loman, N.J., and Loose, M.

Abstract

We report the sequencing and assembly of a reference genome for the human GM12878 Utah/Ceph cell line using the MinION (Oxford Nanopore Technologies) nanopore sequencer. 91.2 Gb of sequence data, representing ~30× theoretical coverage, were produced. Reference-based alignment enabled detection of large structural variants and epigenetic modifications. De novo assembly of nanopore reads alone yielded a contiguous assembly (NG50 ~3 Mb). Next, we developed a protocol to generate ultra-long reads (N50 > 100kb, up to 882 kb). Incorporating an additional 5×-coverage of these data more than doubled the assembly contiguity (NG50 ~6.4 Mb). The final assembled genome was 2,867 million bases in size, covering 85.8% of the reference. Assembly accuracy, after incorporating complementary short-read sequencing data, exceeded 99.8%. Ultra-long reads enabled assembly and phasing of the 4 Mb major histocompatibility complex (MHC) locus in its entirety, measurement of telomere repeat length and closure of gaps in the reference human genome assembly GRCh38.

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30. Nanopore sequencing and assembly of a human genome with ultra-long reads

Author

Jain, M., Koren, S., Miga, K.H., Quick, J., Rand, A.C., Sasani, T.A., Tyson, J.R., Beggs, A.D., Dilthey, A.T., Fiddes, I.T., Malla, S., Marriott, H., Nieto, T., O'Grady, J., Olsen, H.E., Pedersen, B.S., Rhie, A., Richardson, H., Quinlan, A.R., Snutch, T.P., Tee, L., Paten, B., Phillippy, A.M., Simpson, J.T., Loman, N.J., Loose, M., Jain, M., Koren, S., Miga, K.H., Quick, J., Rand, A.C., Sasani, T.A., Tyson, J.R., Beggs, A.D., Dilthey, A.T., Fiddes, I.T., Malla, S., Marriott, H., Nieto, T., O'Grady, J., Olsen, H.E., Pedersen, B.S., Rhie, A., Richardson, H., Quinlan, A.R., Snutch, T.P., Tee, L., Paten, B., Phillippy, A.M., Simpson, J.T., Loman, N.J., and Loose, M.

Abstract

We report the sequencing and assembly of a reference genome for the human GM12878 Utah/Ceph cell line using the MinION (Oxford Nanopore Technologies) nanopore sequencer. 91.2 Gb of sequence data, representing ~30× theoretical coverage, were produced. Reference-based alignment enabled detection of large structural variants and epigenetic modifications. De novo assembly of nanopore reads alone yielded a contiguous assembly (NG50 ~3 Mb). Next, we developed a protocol to generate ultra-long reads (N50 > 100kb, up to 882 kb). Incorporating an additional 5×-coverage of these data more than doubled the assembly contiguity (NG50 ~6.4 Mb). The final assembled genome was 2,867 million bases in size, covering 85.8% of the reference. Assembly accuracy, after incorporating complementary short-read sequencing data, exceeded 99.8%. Ultra-long reads enabled assembly and phasing of the 4 Mb major histocompatibility complex (MHC) locus in its entirety, measurement of telomere repeat length and closure of gaps in the reference human genome assembly GRCh38.

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32. A User's Guide to the Encyclopedia of DNA Elements (ENCODE)

Author

Zhi Lu, Giltae Song, Troy W. Whitfield, Vishwanath R. Iyer, Teresa Vales, Angelika Merkel, Max Libbrecht, David Haussler, Ting Wang, Kristen Lee, Lingyun Song, Richard M. Myers, Alfonso Valencia, Rachel A. Harte, Xiaoqin Xu, Lucas D. Ward, Hazuki Takahashi, Nathan C. Sheffield, Thomas Derrien, Georgi K. Marinov, Eric D. Nguyen, Bernard B. Suh, Brian J. Raney, Richard Sandstrom, Thomas D. Tullius, Benoit Miotto, Alexander Dobin, Youhan Xu, Lukas Habegger, Ian Dunham, Brian A. Risk, Paul G. Giresi, Morgan C. Giddings, Hualin Xi, Anshul Kundaje, Robert S. Harris, Devin Absher, Peter J. Bickel, Yanbao Yu, Browen Aken, Colin Kingswood, Bryan R. Lajoie, Peter J. Good, Katrina Learned, Laura Elnitski, Shirley Pepke, Brandon King, Piero Carninci, Xinqiong Yang, Ghia Euskirchen, Kathryn Beal, Christelle Borel, Michael Muratet, Robert L. Grossman, David G. Knowles, Zarmik Moqtaderi, Veronika Boychenko, Steven P. Wilder, Michael L. Tress, Florencia Pauli, Alan P. Boyle, Andrea Tanzer, Philipp Kapranov, Serafim Batzoglou, Audra K. Johnson, Jun Neri, Nitin Bhardwaj, Elise A. Feingold, Venkat S. Malladi, Michael M. Hoffman, William Stafford Noble, Andrea Sboner, Mark Gerstein, Stephanie L. Parker, Jacqueline Dumais, Felix Schlesinger, Deborah R. Winter, Randall H. Brown, Thanh Truong, Rebecca F. Lowdon, Paolo Ribeca, Brooke Rhead, Peggy J. Farnham, Krista Thibeault, Terrence S. Furey, Donna Karolchik, Alec Victorsen, Xiaoan Ruan, Rehab F. Abdelhamid, Amy S. Nesmith, Jing Wang, Nicholas M. Luscombe, Alina R. Cao, Diane Trout, Teri Slifer, Peter E. Newburger, Cricket A. Sloan, Dimitra Lotakis, Stephen M. J. Searle, Ali Mortazavi, Alexandra Bignell, Alex Reynolds, Orion J. Buske, Chris Zaleski, Theresa K. Canfield, Ian Bell, Jin Lian, Vanessa K. Swing, Katalin Toth Fejes, Catherine Ucla, Robert E. Thurman, Jacqueline Chrast, Wei Lin, Tim Hubbard, Gary Saunders, Minyi Shi, Vihra Sotirova, Sherman M. Weissman, Jason D. Lieb, Richard Humbert, Kevin M. Bowling, Assaf Gordon, Tarjei S. Mikkelsen, Jing Leng, Thomas R. Gingeras, Fabian Grubert, Nader Jameel, Jost Vielmetter, Hannah Monahan, Preti Jain, Lindsay L. Waite, Tony Shafer, Joel Rozowsky, Michael Coyne, Brian Reed, M. Kay, Harsha P. Gunawardena, Ross C. Hardison, Gavin Sherlock, Alexandra Charos, Joseph D. Fleming, Ann S. Zweig, Jason Gertz, Rajinder Kaul, Xianjun Dong, Alexandre Reymond, Carrie A. Davis, Haiyan Huang, Chao Cheng, Marco Mariotti, Phil Lacroute, Jason A. Dilocker, Kenneth McCue, R. Robilotto, Stylianos E. Antonarakis, Sridar V. Chittur, Justin Jee, Barbara J. Wold, Sudipto K. Chakrabortty, Erica Dumais, Amartya Sanyal, Nathan Boley, Tianyuan Wang, Julien Lagarde, Anthony Kirilusha, Jonathan B. Preall, Kevin Roberts, Erika Giste, Hugo Y. K. Lam, Alvis Brazma, Gregory J. Hannon, Eric Rynes, Philippe Batut, Kevin Struhl, Margus Lukk, Manching Ku, Suganthi Balasubramanian, Sonali Jha, Jorg Drenkow, W. James Kent, Michael Snyder, Jie Wang, Anna Battenhouse, Charles B. Epstein, Rami Rauch, Christopher Shestak, John A. Stamatoyannopoulos, Gaurab Mukherjee, Cédric Howald, Tanya Kutyavin, Huaien Wang, Scott A. Tenenbaum, Wan Ting Poh, Kate R. Rosenbloom, Manolis Kellis, Pauline A. Fujita, Linfeng Wu, Anita Bansal, Molly Weaver, Linda L. Grasfeder, Peter J. Sabo, Qiang Li, Melissa S. Cline, Robert M. Kuhn, Darin London, Seth Frietze, Atif Shahab, Shane Neph, Damian Keefe, James B. Brown, Mark Diekhans, Webb Miller, Katherine Aylor Fisher, Jiang Du, Hadar H. Sheffer, Sarah Djebali, Frank Doyle, Nathan Lamarre-Vincent, Chia-Lin Wei, Laura A.L. Dillon, Jennifer Harrow, Robert C. Altshuler, Tyler Alioto, Raymond K. Auerbach, Adam Frankish, Rebekka O. Sprouse, Patrick J. Collins, E. Christopher Partridge, Zheng Liu, Yoichiro Shibata, Elliott H. Margulies, Abigail K. Ebersol, Kimberly A. Showers, Eric D. Green, Krishna M. Roskin, Job Dekker, Barbara N. Pusey, Ekta Khurana, Gilberto DeSalvo, Yijun Ruan, Hao Wang, Jainab Khatun, Henriette O'Geen, Alexej Abyzov, Brian Williams, Ryan M. McDaniell, Maya Kasowski, Manoj Hariharan, Felix Kokocinski, Gloria Despacio-Reyes, Zhancheng Zhang, Subhradip Karmakar, Ewan Birney, Koon-Kiu Yan, Xian Chen, Shinny Vong, Daniel Sobral, Nick Bild, Seul K.C. Kim, Timo Lassmann, Li Wang, Minerva E. Sanchez, Vaughan Roach, Theodore Gibson, Stephen C. J. Parker, Michael F. Lin, Patrick A. Navas, Laurence R. Meyer, Luiz O. F. Penalva, Bradley E. Bernstein, Kevin P. White, Emilie Aït Yahya Graison, Juan M. Vaquerizas, Sushma Iyengar, Kimberly M. Newberry, Akshay Bhinge, Xiaolan Zhang, Kim Bell, Yoshihide Hayashizaki, Lucas Lochovsky, Noam Shoresh, Hagen Tilgner, Philip Cayting, Dorrelyn Patacsil, Timothy E. Reddy, Eric Haugen, Katherine E. Varley, M. van Baren, Nathan D. Trinklein, Bum Kyu Lee, Tristan Frum, Marianne Lindahl-Allen, Timothy Durham, Roderic Guigó, Christopher W. Maier, Micha Sammeth, Debasish Raha, Timothy R. Dreszer, Benedict Paten, Robbyn Issner, Michael R. Brent, Kevin Y. Yip, Kim Blahnik, Jason Ernst, Zhiping Weng, Henry Amrhein, Arend Sidow, Javier Herrero, Hui Gao, Stephen G. Landt, Pouya Kheradpour, Galt P. Barber, Gregory E. Crawford, Toby Hunt, HudsonAlpha Institute for Biotechnology [Huntsville, AL], ENCODE Project Consortium : Myers RM, Stamatoyannopoulos J, Snyder M, Dunham I, Hardison RC, Bernstein BE, Gingeras TR, Kent WJ, Birney E, Wold B, Crawford GE, Bernstein BE, Epstein CB, Shoresh N, Ernst J, Mikkelsen TS, Kheradpour P, Zhang X, Wang L, Issner R, Coyne MJ, Durham T, Ku M, Truong T, Ward LD, Altshuler RC, Lin MF, Kellis M, Gingeras TR, Davis CA, Kapranov P, Dobin A, Zaleski C, Schlesinger F, Batut P, Chakrabortty S, Jha S, Lin W, Drenkow J, Wang H, Bell K, Gao H, Bell I, Dumais E, Dumais J, Antonarakis SE, Ucla C, Borel C, Guigo R, Djebali S, Lagarde J, Kingswood C, Ribeca P, Sammeth M, Alioto T, Merkel A, Tilgner H, Carninci P, Hayashizaki Y, Lassmann T, Takahashi H, Abdelhamid RF, Hannon G, Fejes-Toth K, Preall J, Gordon A, Sotirova V, Reymond A, Howald C, Graison E, Chrast J, Ruan Y, Ruan X, Shahab A, Ting Poh W, Wei CL, Crawford GE, Furey TS, Boyle AP, Sheffield NC, Song L, Shibata Y, Vales T, Winter D, Zhang Z, London D, Wang T, Birney E, Keefe D, Iyer VR, Lee BK, McDaniell RM, Liu Z, Battenhouse A, Bhinge AA, Lieb JD, Grasfeder LL, Showers KA, Giresi PG, Kim SK, Shestak C, Myers RM, Pauli F, Reddy TE, Gertz J, Partridge EC, Jain P, Sprouse RO, Bansal A, Pusey B, Muratet MA, Varley KE, Bowling KM, Newberry KM, Nesmith AS, Dilocker JA, Parker SL, Waite LL, Thibeault K, Roberts K, Absher DM, Wold B, Mortazavi A, Williams B, Marinov G, Trout D, Pepke S, King B, McCue K, Kirilusha A, DeSalvo G, Fisher-Aylor K, Amrhein H, Vielmetter J, Sherlock G, Sidow A, Batzoglou S, Rauch R, Kundaje A, Libbrecht M, Margulies EH, Parker SC, Elnitski L, Green ED, Hubbard T, Harrow J, Searle S, Kokocinski F, Aken B, Frankish A, Hunt T, Despacio-Reyes G, Kay M, Mukherjee G, Bignell A, Saunders G, Boychenko V, Van Baren M, Brown RH, Khurana E, Balasubramanian S, Zhang Z, Lam H, Cayting P, Robilotto R, Lu Z, Guigo R, Derrien T, Tanzer A, Knowles DG, Mariotti M, James Kent W, Haussler D, Harte R, Diekhans M, Kellis M, Lin M, Kheradpour P, Ernst J, Reymond A, Howald C, Graison EA, Chrast J, Tress M, Rodriguez JM, Snyder M, Landt SG, Raha D, Shi M, Euskirchen G, Grubert F, Kasowski M, Lian J, Cayting P, Lacroute P, Xu Y, Monahan H, Patacsil D, Slifer T, Yang X, Charos A, Reed B, Wu L, Auerbach RK, Habegger L, Hariharan M, Rozowsky J, Abyzov A, Weissman SM, Gerstein M, Struhl K, Lamarre-Vincent N, Lindahl-Allen M, Miotto B, Moqtaderi Z, Fleming JD, Newburger P, Farnham PJ, Frietze S, O'Geen H, Xu X, Blahnik KR, Cao AR, Iyengar S, Stamatoyannopoulos JA, Kaul R, Thurman RE, Wang H, Navas PA, Sandstrom R, Sabo PJ, Weaver M, Canfield T, Lee K, Neph S, Roach V, Reynolds A, Johnson A, Rynes E, Giste E, Vong S, Neri J, Frum T, Johnson EM, Nguyen ED, Ebersol AK, Sanchez ME, Sheffer HH, Lotakis D, Haugen E, Humbert R, Kutyavin T, Shafer T, Dekker J, Lajoie BR, Sanyal A, James Kent W, Rosenbloom KR, Dreszer TR, Raney BJ, Barber GP, Meyer LR, Sloan CA, Malladi VS, Cline MS, Learned K, Swing VK, Zweig AS, Rhead B, Fujita PA, Roskin K, Karolchik D, Kuhn RM, Haussler D, Birney E, Dunham I, Wilder SP, Keefe D, Sobral D, Herrero J, Beal K, Lukk M, Brazma A, Vaquerizas JM, Luscombe NM, Bickel PJ, Boley N, Brown JB, Li Q, Huang H, Gerstein M, Habegger L, Sboner A, Rozowsky J, Auerbach RK, Yip KY, Cheng C, Yan KK, Bhardwaj N, Wang J, Lochovsky L, Jee J, Gibson T, Leng J, Du J, Hardison RC, Harris RS, Song G, Miller W, Haussler D, Roskin K, Suh B, Wang T, Paten B, Noble WS, Hoffman MM, Buske OJ, Weng Z, Dong X, Wang J, Xi H, Tenenbaum SA, Doyle F, Penalva LO, Chittur S, Tullius TD, Parker SC, White KP, Karmakar S, Victorsen A, Jameel N, Bild N, Grossman RL, Snyder M, Landt SG, Yang X, Patacsil D, Slifer T, Dekker J, Lajoie BR, Sanyal A, Weng Z, Whitfield TW, Wang J, Collins PJ, Trinklein ND, Partridge EC, Myers RM, Giddings MC, Chen X, Khatun J, Maier C, Yu Y, Gunawardena H, Risk B, Feingold EA, Lowdon RF, Dillon LA, Good PJ, Harrow J, Searle S., Becker, Peter B, Broad Institute of MIT and Harvard, Lincoln Laboratory, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology. Department of Physics, Kellis, Manolis, Epstein, Charles B., Bernstein, Bradley E., Shoresh, Noam, Ernst, Jason, Mikkelsen, Tarjei Sigurd, Kheradpour, Pouya, Zhang, Xiaolan, Wang, Li, Issner, Robbyn, Coyne, Michael J., Durham, Timothy, Ku, Manching, Truong, Thanh, Ward, Lucas D., Altshuler, Robert Charles, Lin, Michael F., ENCODE Project Consortium, Antonarakis, Stylianos, and Miotto, Benoit

Subjects
RNA, Messenger/genetics, [SDV]Life Sciences [q-bio], Messenger, Genoma humà, Genome, Medical and Health Sciences, 0302 clinical medicine, Models, ddc:576.5, Biology (General), Conserved Sequence, Genetics, 0303 health sciences, General Neuroscience, RNA-Binding Proteins, Genomics, Biological Sciences, Chromatin, 3. Good health, [SDV] Life Sciences [q-bio], DNA-Binding Proteins, Gene Components, 030220 oncology & carcinogenesis, DNA methylation, Encyclopedia, HIV/AIDS, Proteïnes de la sang -- Aspectes genètics, General Agricultural and Biological Sciences, Databases, Nucleic Acid, Human, Research Article, Quality Control, Process (engineering), QH301-705.5, 1.1 Normal biological development and functioning, Computational biology, Biology, ENCODE, General Biochemistry, Genetics and Molecular Biology, Chromatin/metabolism, Vaccine Related, 03 medical and health sciences, Databases, Genetic, Underpinning research, Humans, RNA, Messenger, RNA-Binding Proteins/genetics/metabolism, Vaccine Related (AIDS), Gene, 030304 developmental biology, Internet, General Immunology and Microbiology, Nucleic Acid, Agricultural and Veterinary Sciences, Base Sequence, Models, Genetic, Genome, Human, Prevention, Human Genome, Computational Biology, DNA Methylation, ENCODE Project Consortium, Gene Expression Regulation, DNA-Binding Proteins/genetics/metabolism, RNA, Human genome, Immunization, Generic health relevance, Developmental Biology
Abstract

The mission of the Encyclopedia of DNA Elements (ENCODE) Project is to enable the scientific and medical communities to interpret the human genome sequence and apply it to understand human biology and improve health. The ENCODE Consortium is integrating multiple technologies and approaches in a collective effort to discover and define the functional elements encoded in the human genome, including genes, transcripts, and transcriptional regulatory regions, together with their attendant chromatin states and DNA methylation patterns. In the process, standards to ensure high-quality data have been implemented, and novel algorithms have been developed to facilitate analysis. Data and derived results are made available through a freely accessible database. Here we provide an overview of the project and the resources it is generating and illustrate the application of ENCODE data to interpret the human genome., National Human Genome Research Institute (U.S.), National Institutes of Health (U.S.)

Published
2011

33. A phenome-wide association study of methylated GC-rich repeats identifies a GCC repeat expansion in AFF3 associated with intellectual disability.

Author

Jadhav B, Garg P, van Vugt JJFA, Ibanez K, Gagliardi D, Lee W, Shadrina M, Mokveld T, Dolzhenko E, Martin-Trujillo A, Gies SJ, Altman G, Rocca C, Barbosa M, Jain M, Lahiri N, Lachlan K, Houlden H, Paten B, Veldink J, Tucci A, and Sharp AJ

Subjects
Humans, Male, Female, Phenotype, DNA Repeat Expansion genetics, GC Rich Sequence, Promoter Regions, Genetic genetics, Tandem Repeat Sequences genetics, DNA Methylation, Intellectual Disability genetics, Genome-Wide Association Study
Abstract

GC-rich tandem repeat expansions (TREs) are often associated with DNA methylation, gene silencing and folate-sensitive fragile sites, and underlie several congenital and late-onset disorders. Through a combination of DNA-methylation profiling and tandem repeat genotyping, we identified 24 methylated TREs and investigated their effects on human traits using phenome-wide association studies in 168,641 individuals from the UK Biobank, identifying 156 significant TRE-trait associations involving 17 different TREs. Of these, a GCC expansion in the promoter of AFF3 was associated with a 2.4-fold reduced probability of completing secondary education, an effect size comparable to several recurrent pathogenic microdeletions. In a cohort of 6,371 probands with neurodevelopmental problems of suspected genetic etiology, we observed a significant enrichment of AFF3 expansions compared with controls. With a population prevalence that is at least fivefold higher than the TRE that causes fragile X syndrome, AFF3 expansions represent a major cause of neurodevelopmental delay., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2024
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34. Personalized pangenome references.

Author

Sirén J, Eskandar P, Ungaro MT, Hickey G, Eizenga JM, Novak AM, Chang X, Chang PC, Kolmogorov M, Carroll A, Monlong J, and Paten B

Subjects
Humans, Genetic Variation, Genomics methods, Haplotypes, Gene Frequency, Algorithms, High-Throughput Nucleotide Sequencing methods, Genome, Human, Software
Abstract

Pangenomes reduce reference bias by representing genetic diversity better than a single reference sequence. Yet when comparing a sample to a pangenome, variants in the pangenome that are not part of the sample can be misleading, for example, causing false read mappings. These irrelevant variants are generally rarer in terms of allele frequency, and have previously been dealt with by filtering rare variants. However, this blunt heuristic both fails to remove some irrelevant variants and removes many relevant variants. We propose a new approach that imputes a personalized pangenome subgraph by sampling local haplotypes according to k-mer counts in the reads. We implement the approach in the vg toolkit ( https://github.com/vgteam/vg ) for the Giraffe short-read aligner and compare its accuracy to state-of-the-art methods using human pangenome graphs from the Human Pangenome Reference Consortium. This reduces small variant genotyping errors by four times relative to the Genome Analysis Toolkit and makes short-read structural variant genotyping of known variants competitive with long-read variant discovery methods., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2024
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35. Development and extensive sequencing of a broadly-consented Genome in a Bottle matched tumor-normal pair.

Author

McDaniel JH, Patel V, Olson ND, He HJ, He Z, Cole KD, Schmitt A, Sikkink K, Sedlazeck FJ, Doddapaneni H, Jhangiani SN, Muzny DM, Gingras MC, Mehta H, Paulin LF, Hastie AR, Yu HC, Weigman V, Rojas A, Kennedy K, Remington J, Gonzalez I, Sudkamp M, Wiseman K, Lajoie BR, Levy S, Jain M, Akeson S, Narzisi G, Steinsnyder Z, Reeves C, Shelton J, Kingan SB, Lambert C, Bayabyan P, Wenger AM, McLaughlin IJ, Adamson A, Kingsley C, Wescott M, Kim Y, Paten B, Park J, Violich I, Miga KH, Gardner J, McNulty B, Rosen G, McCoy R, Brundu F, Sayyari E, Scheffler K, Truong S, Catreux S, Hannah LC, Lipson D, Benjamin H, Iremadze N, Soifer I, Eacker S, Wood M, Cross E, Husar G, Gross S, Vernich M, Kolmogorov M, Ahmad T, Keskus A, Bryant A, Thibaud-Nissen F, Trow J, Proszynski J, Hirschberg JW, Ryon K, Mason CE, Wagner J, Xiao C, Liss AS, and Zook JM

Abstract

The Genome in a Bottle Consortium (GIAB), hosted by the National Institute of Standards and Technology (NIST), is developing new matched tumor-normal samples, the first to be explicitly consented for public dissemination of genomic data and cell lines. Here, we describe a comprehensive genomic dataset from the first individual, HG008, including DNA from an adherent, epithelial-like pancreatic ductal adenocarcinoma (PDAC) tumor cell line and matched normal cells from duodenal and pancreatic tissues. Data for the tumor-normal matched samples comes from thirteen distinct state-of-the-art whole genome measurement technologies, including high depth short and long-read bulk whole genome sequencing (WGS), single cell WGS, and Hi-C, and karyotyping. These data will be used by the GIAB Consortium to develop matched tumor-normal benchmarks for somatic variant detection. We expect these data to facilitate innovation for whole genome measurement technologies, de novo assembly of tumor and normal genomes, and bioinformatic tools to identify small and structural somatic mutations. This first-of-its-kind broadly consented open-access resource will facilitate further understanding of sequencing methods used for cancer biology., Competing Interests: Competing interests A.S. and K.S. are employees of Arima Genomics. L.F.P. from BCM, was sponsored by Genentech Inc until September 2023. F.J.S from BCM, received research support from Illumina, ONT and Pacbio. A.R.H and H-C.Y. are employees of Bionano Genomics and own stock shares and options of Bionano Genomics, Inc. V.W., K.K., J.R., and I.G. are employees of BioSkryb Genomics. M.S., K.B., B.R.L. and S.L. are employees of Element Biosciences. S.B.K., C.L., P.B., A.M.W., I.J.M., A.A., C.K., M.W., and Y.K. are employees and shareholders of PacBio, Inc. D.L., H.B., N.I., and I.S. are employees and shareholders of Ultima Genomics. S.E. and M.W. are employees of Phase Genomics. E.C., G.H., S.G., and M.V. are employees of KromaTiD, Inc, E.C. is also a shareholder. F.B., E.S., K.S., S.T. and S.C. are employees of Illumina, Inc. All other authors have no competing interests.

Published
2024
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36. Efficient indexing and querying of annotations in a pangenome graph.

Author

Novak AM, Chung D, Hickey G, Djebali S, Yokoyama TT, Garrison E, Narzisi G, Paten B, and Monlong J

Abstract

The current reference genome is the backbone of diverse and rich annotations. Simple text formats, like VCF or BED, have been widely adopted and helped the critical exchange of genomic information. There is a dire need for tools and formats enabling pangenomic annotation to facilitate such enrichment of pangenomic references. The Graph Alignment Format (GAF) is a text format, tab-delimited like BED/VCF files, which was proposed to represent alignments. GAF could also be used to store paths representing annotations in a pangenome graph, but there are no tools to index and query them efficiently. Here, we present extensions to vg and HTSlib that provide efficient sorting, indexing, and querying for GAF files. With this approach, annotations overlapping a subgraph can be extracted quickly. Paths are sorted based on the IDs of traversed nodes, compressed with BGZIP, and indexed with HTSlib/tabix via our extensions for the GAF format. Compared to the binary GAM format, GAF files are easier to edit or inspect because they are plain text, and we show that they are twice as fast to sort and half as large on disk. In addition, we updated vg annotate, which takes BED or GFF3 annotation files relative to linear sequences and projects them into the pangenome. It can now produce GAF files representing these annotations' paths through the pangenome. We showcase these new tools on several applications. We projected annotations for all Human Pangenome Reference Consortium Year 1 haplotypes, including genes, segmental duplications, tandem repeats and repeats annotations, into the Minigraph-Cactus pangenome (GRCh38-based v1.1). We also projected known variants from the GWAS Catalog and expression QTLs from the GTEx project into the pangenome. Finally, we reanalyzed ATAC-seq data from ENCODE to demonstrate what a coverage track could look like in a pangenome graph. These rich annotations can be quickly queried with vg and visualized using existing tools like the Sequence Tube Map or Bandage.

Published
2024
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37. Complete sequencing of ape genomes.

Author

Yoo D, Rhie A, Hebbar P, Antonacci F, Logsdon GA, Solar SJ, Antipov D, Pickett BD, Safonova Y, Montinaro F, Luo Y, Malukiewicz J, Storer JM, Lin J, Sequeira AN, Mangan RJ, Hickey G, Anez GM, Balachandran P, Bankevich A, Beck CR, Biddanda A, Borchers M, Bouffard GG, Brannan E, Brooks SY, Carbone L, Carrel L, Chan AP, Crawford J, Diekhans M, Engelbrecht E, Feschotte C, Formenti G, Garcia GH, de Gennaro L, Gilbert D, Green RE, Guarracino A, Gupta I, Haddad D, Han J, Harris RS, Hartley GA, Harvey WT, Hiller M, Hoekzema K, Houck ML, Jeong H, Kamali K, Kellis M, Kille B, Lee C, Lee Y, Lees W, Lewis AP, Li Q, Loftus M, Loh YHE, Loucks H, Ma J, Mao Y, Martinez JFI, Masterson P, McCoy RC, McGrath B, McKinney S, Meyer BS, Miga KH, Mohanty SK, Munson KM, Pal K, Pennell M, Pevzner PA, Porubsky D, Potapova T, Ringeling FR, Roha JL, Ryder OA, Sacco S, Saha S, Sasaki T, Schatz MC, Schork NJ, Shanks C, Smeds L, Son DR, Steiner C, Sweeten AP, Tassia MG, Thibaud-Nissen F, Torres-González E, Trivedi M, Wei W, Wertz J, Yang M, Zhang P, Zhang S, Zhang Y, Zhang Z, Zhao SA, Zhu Y, Jarvis ED, Gerton JL, Rivas-González I, Paten B, Szpiech ZA, Huber CD, Lenz TL, Konkel MK, Yi SV, Canzar S, Watson CT, Sudmant PH, Molloy E, Garrison E, Lowe CB, Ventura M, O'Neill RJ, Koren S, Makova KD, Phillippy AM, and Eichler EE

Abstract

We present haplotype-resolved reference genomes and comparative analyses of six ape species, namely: chimpanzee, bonobo, gorilla, Bornean orangutan, Sumatran orangutan, and siamang. We achieve chromosome-level contiguity with unparalleled sequence accuracy (<1 error in 500,000 base pairs), completely sequencing 215 gapless chromosomes telomere-to-telomere. We resolve challenging regions, such as the major histocompatibility complex and immunoglobulin loci, providing more in-depth evolutionary insights. Comparative analyses, including human, allow us to investigate the evolution and diversity of regions previously uncharacterized or incompletely studied without bias from mapping to the human reference. This includes newly minted gene families within lineage-specific segmental duplications, centromeric DNA, acrocentric chromosomes, and subterminal heterochromatin. This resource should serve as a definitive baseline for all future evolutionary studies of humans and our closest living ape relatives., Competing Interests: COMPETING INTERESTS E.E.E. is a scientific advisory board (SAB) member of Variant Bio, Inc. C.T.W. is a co-founder/CSO of Clareo Biosciences, Inc. W.L. is a co-founder/CIO of Clareo Biosciences, Inc. The other authors declare no competing interests.

Published
2024
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38. Complex genetic variation in nearly complete human genomes.

Author

Logsdon GA, Ebert P, Audano PA, Loftus M, Porubsky D, Ebler J, Yilmaz F, Hallast P, Prodanov T, Yoo D, Paisie CA, Harvey WT, Zhao X, Martino GV, Henglin M, Munson KM, Rabbani K, Chin CS, Gu B, Ashraf H, Austine-Orimoloye O, Balachandran P, Bonder MJ, Cheng H, Chong Z, Crabtree J, Gerstein M, Guethlein LA, Hasenfeld P, Hickey G, Hoekzema K, Hunt SE, Jensen M, Jiang Y, Koren S, Kwon Y, Li C, Li H, Li J, Norman PJ, Oshima KK, Paten B, Phillippy AM, Pollock NR, Rausch T, Rautiainen M, Scholz S, Song Y, Söylev A, Sulovari A, Surapaneni L, Tsapalou V, Zhou W, Zhou Y, Zhu Q, Zody MC, Mills RE, Devine SE, Shi X, Talkowski ME, Chaisson MJP, Dilthey AT, Konkel MK, Korbel JO, Lee C, Beck CR, Eichler EE, and Marschall T

Abstract

Diverse sets of complete human genomes are required to construct a pangenome reference and to understand the extent of complex structural variation. Here, we sequence 65 diverse human genomes and build 130 haplotype-resolved assemblies (130 Mbp median continuity), closing 92% of all previous assembly gaps 1,2 and reaching telomere-to-telomere (T2T) status for 39% of the chromosomes. We highlight complete sequence continuity of complex loci, including the major histocompatibility complex (MHC), SMN1 / SMN2 , NBPF8 , and AMY1/AMY2 , and fully resolve 1,852 complex structural variants (SVs). In addition, we completely assemble and validate 1,246 human centromeres. We find up to 30-fold variation in α-satellite high-order repeat (HOR) array length and characterize the pattern of mobile element insertions into α-satellite HOR arrays. While most centromeres predict a single site of kinetochore attachment, epigenetic analysis suggests the presence of two hypomethylated regions for 7% of centromeres. Combining our data with the draft pangenome reference 1 significantly enhances genotyping accuracy from short-read data, enabling whole-genome inference 3 to a median quality value (QV) of 45. Using this approach, 26,115 SVs per sample are detected, substantially increasing the number of SVs now amenable to downstream disease association studies., Competing Interests: Competing Interests E.E.E. is a scientific advisory board member of Variant Bio, Inc. C. Lee is a scientific advisory board member of Nabsys and Genome Insight. S.K. has received travel funds to speak at events hosted by Oxford Nanopore Technologies. The following authors have previously disclosed a patent application (No. EP19169090) relevant to Strand-seq: J.O.K., T.M., and D.P. The other authors declare no competing interests.

Published
2024
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39. Highly accurate assembly polishing with DeepPolisher.

Author

Mastoras M, Asri M, Brambrink L, Hebbar P, Kolesnikov A, Cook DE, Nattestad M, Lucas J, Won TS, Chang PC, Carroll A, Paten B, and Shafin K

Abstract

Accurate genome assemblies are essential for biological research, but even the highest quality assemblies retain errors caused by the technologies used to construct them. Base-level errors are typically fixed with an additional polishing step that uses reads aligned to the draft assembly to identify necessary edits. However, current methods struggle to find a balance between over-and under-polishing. Here, we present an encoder-only transformer model for assembly polishing called DeepPolisher, which predicts corrections to the underlying sequence using Pacbio HiFi read alignments to a diploid assembly. Our pipeline introduces a method, PHARAOH (Phasing Reads in Areas Of Homozygosity), which uses ultra-long ONT data to ensure alignments are accurately phased and to correctly introduce heterozygous edits in falsely homozygous regions. We demonstrate that the DeepPolisher pipeline can reduce assembly errors by half, with a greater than 70% reduction in indel errors. We have applied our DeepPolisher-based pipeline to 180 assemblies from the next Human Pangenome Reference Consortium (HPRC) data release, producing an average predicted Quality Value (QV) improvement of 3.4 (54% error reduction) for the majority of the genome., Competing Interests: Conflict of interest A.C, D.E.C, P.C., A.K., L.B., M.N. and K.S. are employees of Google LLC and own Alphabet stock as part of the standard compensation package.

Published
2024
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40. Advancing long-read nanopore genome assembly and accurate variant calling for rare disease detection.

Author

Negi S, Stenton SL, Berger SI, McNulty B, Violich I, Gardner J, Hillaker T, O'Rourke SM, O'Leary MC, Carbonell E, Austin-Tse C, Lemire G, Serrano J, Mangilog B, VanNoy G, Kolmogorov M, Vilain E, O'Donnell-Luria A, Délot E, Miga KH, Monlong J, and Paten B

Abstract

More than 50% of families with suspected rare monogenic diseases remain unsolved after whole genome analysis by short read sequencing (SRS). Long-read sequencing (LRS) could help bridge this diagnostic gap by capturing variants inaccessible to SRS, facilitating long-range mapping and phasing, and providing haplotype-resolved methylation profiling. To evaluate LRS's additional diagnostic yield, we sequenced a rare disease cohort of 98 samples, including 41 probands and some family members, using nanopore sequencing, achieving per sample ∼36x average coverage and 32 kilobase (kb) read N50 from a single flow cell. Our Napu pipeline generated assemblies, phased variants, and methylation calls. LRS covered, on average, coding exons in ∼280 genes and ∼5 known Mendelian disease genes that were not covered by SRS. In comparison to SRS, LRS detected additional rare, functionally annotated variants, including SVs and tandem repeats, and completely phased 87% of protein-coding genes. LRS detected additional de novo variants, and could be used to distinguish postzygotic mosaic variants from prezygotic de novos . Eleven probands were solved, with diverse underlying genetic causes including de novo and compound heterozygous variants, large-scale SVs, and epigenetic modifications. Our study demonstrates LRS's potential to enhance diagnostic yield for rare monogenic diseases, implying utility in future clinical genomics workflows.

Published
2024
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41. DeepSomatic: Accurate somatic small variant discovery for multiple sequencing technologies.

Author

Park J, Cook DE, Chang PC, Kolesnikov A, Brambrink L, Mier JC, Gardner J, McNulty B, Sacco S, Keskus A, Bryant A, Ahmad T, Shetty J, Zhao Y, Tran B, Narzisi G, Helland A, Yoo B, Pushel I, Lansdon LA, Bi C, Walter A, Gibson M, Pastinen T, Farooqi MS, Robine N, Miga KH, Carroll A, Kolmogorov M, Paten B, and Shafin K

Abstract

Somatic variant detection is an integral part of cancer genomics analysis. While most methods have focused on short-read sequencing, long-read technologies now offer potential advantages in terms of repeat mapping and variant phasing. We present DeepSomatic, a deep learning method for detecting somatic SNVs and insertions and deletions (indels) from both short-read and long-read data, with modes for whole-genome and exome sequencing, and able to run on tumor-normal, tumor-only, and with FFPE-prepared samples. To help address the dearth of publicly available training and benchmarking data for somatic variant detection, we generated and make openly available a dataset of five matched tumor-normal cell line pairs sequenced with Illumina, PacBio HiFi, and Oxford Nanopore Technologies, along with benchmark variant sets. Across samples and technologies (short-read and long-read), DeepSomatic consistently outperforms existing callers, particularly for indels., Competing Interests: Competing interests K.S., D.E.C., P.C., A. Kolesnikov, L.B., J.C.M., and A.C. are employees of Google LLC and own Alphabet stock as part of the standard compensation package. M.S.F. is a part of the speakers bureau for Bayer and PacBio.

Published
2024
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42. Beyond the Human Genome Project: The Age of Complete Human Genome Sequences and Pangenome References.

Author

Taylor DJ, Eizenga JM, Li Q, Das A, Jenike KM, Kenny EE, Miga KH, Monlong J, McCoy RC, Paten B, and Schatz MC

Subjects
Humans, Genetic Variation, Genomics methods, Sequence Analysis, DNA methods, Telomere genetics, Genome, Human, Human Genome Project
Abstract

The Human Genome Project was an enormous accomplishment, providing a foundation for countless explorations into the genetics and genomics of the human species. Yet for many years, the human genome reference sequence remained incomplete and lacked representation of human genetic diversity. Recently, two major advances have emerged to address these shortcomings: complete gap-free human genome sequences, such as the one developed by the Telomere-to-Telomere Consortium, and high-quality pangenomes, such as the one developed by the Human Pangenome Reference Consortium. Facilitated by advances in long-read DNA sequencing and genome assembly algorithms, complete human genome sequences resolve regions that have been historically difficult to sequence, including centromeres, telomeres, and segmental duplications. In parallel, pangenomes capture the extensive genetic diversity across populations worldwide. Together, these advances usher in a new era of genomics research, enhancing the accuracy of genomic analysis, paving the path for precision medicine, and contributing to deeper insights into human biology.

Published
2024
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43. Local read haplotagging enables accurate long-read small variant calling.

Author

Kolesnikov A, Cook D, Nattestad M, Brambrink L, McNulty B, Gorzynski J, Goenka S, Ashley EA, Jain M, Miga KH, Paten B, Chang PC, Carroll A, and Shafin K

Subjects
Humans, Sequence Analysis, DNA methods, Polymorphism, Single Nucleotide, Genome, Human, Algorithms, Genetic Variation, Neural Networks, Computer, Haplotypes genetics, High-Throughput Nucleotide Sequencing methods
Abstract

Long-read sequencing technology has enabled variant detection in difficult-to-map regions of the genome and enabled rapid genetic diagnosis in clinical settings. Rapidly evolving third-generation sequencing platforms like Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) are introducing newer platforms and data types. It has been demonstrated that variant calling methods based on deep neural networks can use local haplotyping information with long-reads to improve the genotyping accuracy. However, using local haplotype information creates an overhead as variant calling needs to be performed multiple times which ultimately makes it difficult to extend to new data types and platforms as they get introduced. In this work, we have developed a local haplotype approximate method that enables state-of-the-art variant calling performance with multiple sequencing platforms including PacBio Revio system, ONT R10.4 simplex and duplex data. This addition of local haplotype approximation simplifies long-read variant calling with DeepVariant., (© 2024. The Author(s).)

Published
2024
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44. SIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis.

Author

Gonzalez-Ferrer J, Lehrer J, O'Farrell A, Paten B, Teodorescu M, Haussler D, Jonsson VD, and Mostajo-Radji MA

Subjects
Humans, Animals, Brain cytology, Brain metabolism, Neurons metabolism, Neurons cytology, Organoids metabolism, Organoids cytology, Cell Differentiation genetics, Mice, Single-Cell Analysis methods, Deep Learning, Sequence Analysis, RNA methods
Abstract

Cell atlases serve as vital references for automating cell labeling in new samples, yet existing classification algorithms struggle with accuracy. Here we introduce SIMS (scalable, interpretable machine learning for single cell), a low-code data-efficient pipeline for single-cell RNA classification. We benchmark SIMS against datasets from different tissues and species. We demonstrate SIMS's efficacy in classifying cells in the brain, achieving high accuracy even with small training sets (<3,500 cells) and across different samples. SIMS accurately predicts neuronal subtypes in the developing brain, shedding light on genetic changes during neuronal differentiation and postmitotic fate refinement. Finally, we apply SIMS to single-cell RNA datasets of cortical organoids to predict cell identities and uncover genetic variations between cell lines. SIMS identifies cell-line differences and misannotated cell lineages in human cortical organoids derived from different pluripotent stem cell lines. Altogether, we show that SIMS is a versatile and robust tool for cell-type classification from single-cell datasets., Competing Interests: Declaration of interests J.L., V.D.J., and M.A.M.-R. have submitted patent applications related to the work in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Published
2024
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45. The complete sequence and comparative analysis of ape sex chromosomes.

Author

Makova KD, Pickett BD, Harris RS, Hartley GA, Cechova M, Pal K, Nurk S, Yoo D, Li Q, Hebbar P, McGrath BC, Antonacci F, Aubel M, Biddanda A, Borchers M, Bornberg-Bauer E, Bouffard GG, Brooks SY, Carbone L, Carrel L, Carroll A, Chang PC, Chin CS, Cook DE, Craig SJC, de Gennaro L, Diekhans M, Dutra A, Garcia GH, Grady PGS, Green RE, Haddad D, Hallast P, Harvey WT, Hickey G, Hillis DA, Hoyt SJ, Jeong H, Kamali K, Pond SLK, LaPolice TM, Lee C, Lewis AP, Loh YE, Masterson P, McGarvey KM, McCoy RC, Medvedev P, Miga KH, Munson KM, Pak E, Paten B, Pinto BJ, Potapova T, Rhie A, Rocha JL, Ryabov F, Ryder OA, Sacco S, Shafin K, Shepelev VA, Slon V, Solar SJ, Storer JM, Sudmant PH, Sweetalana, Sweeten A, Tassia MG, Thibaud-Nissen F, Ventura M, Wilson MA, Young AC, Zeng H, Zhang X, Szpiech ZA, Huber CD, Gerton JL, Yi SV, Schatz MC, Alexandrov IA, Koren S, O'Neill RJ, Eichler EE, and Phillippy AM

Subjects
Animals, Female, Male, Gorilla gorilla genetics, Hylobatidae genetics, Pan paniscus genetics, Pan troglodytes genetics, Phylogeny, Pongo abelii genetics, Pongo pygmaeus genetics, Telomere genetics, Evolution, Molecular, DNA Copy Number Variations genetics, Humans, Endangered Species, Reference Standards, Hominidae genetics, Hominidae classification, X Chromosome genetics, Y Chromosome genetics
Abstract

Apes possess two sex chromosomes-the male-specific Y chromosome and the X chromosome, which is present in both males and females. The Y chromosome is crucial for male reproduction, with deletions being linked to infertility 1 . The X chromosome is vital for reproduction and cognition 2 . Variation in mating patterns and brain function among apes suggests corresponding differences in their sex chromosomes. However, owing to their repetitive nature and incomplete reference assemblies, ape sex chromosomes have been challenging to study. Here, using the methodology developed for the telomere-to-telomere (T2T) human genome, we produced gapless assemblies of the X and Y chromosomes for five great apes (bonobo (Pan paniscus), chimpanzee (Pan troglodytes), western lowland gorilla (Gorilla gorilla gorilla), Bornean orangutan (Pongo pygmaeus) and Sumatran orangutan (Pongo abelii)) and a lesser ape (the siamang gibbon (Symphalangus syndactylus)), and untangled the intricacies of their evolution. Compared with the X chromosomes, the ape Y chromosomes vary greatly in size and have low alignability and high levels of structural rearrangements-owing to the accumulation of lineage-specific ampliconic regions, palindromes, transposable elements and satellites. Many Y chromosome genes expand in multi-copy families and some evolve under purifying selection. Thus, the Y chromosome exhibits dynamic evolution, whereas the X chromosome is more stable. Mapping short-read sequencing data to these assemblies revealed diversity and selection patterns on sex chromosomes of more than 100 individual great apes. These reference assemblies are expected to inform human evolution and conservation genetics of non-human apes, all of which are endangered species., (© 2024. The Author(s).)

Published
2024
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46. Phased nanopore assembly with Shasta and modular graph phasing with GFAse.

Author

Lorig-Roach R, Meredith M, Monlong J, Jain M, Olsen HE, McNulty B, Porubsky D, Montague TG, Lucas JK, Condon C, Eizenga JM, Juul S, McKenzie SK, Simmonds SE, Park J, Asri M, Koren S, Eichler EE, Axel R, Martin B, Carnevali P, Miga KH, and Paten B

Subjects
Humans, Sequence Analysis, DNA methods, Nanopore Sequencing methods, High-Throughput Nucleotide Sequencing methods, Software, Genomics methods, Nanopores
Abstract

Reference-free genome phasing is vital for understanding allele inheritance and the impact of single-molecule DNA variation on phenotypes. To achieve thorough phasing across homozygous or repetitive regions of the genome, long-read sequencing technologies are often used to perform phased de novo assembly. As a step toward reducing the cost and complexity of this type of analysis, we describe new methods for accurately phasing Oxford Nanopore Technologies (ONT) sequence data with the Shasta genome assembler and a modular tool for extending phasing to the chromosome scale called GFAse. We test using new variants of ONT PromethION sequencing, including those using proximity ligation, and show that newer, higher accuracy ONT reads substantially improve assembly quality., (© 2024 Lorig-Roach et al.; Published by Cold Spring Harbor Laboratory Press.)

Published
2024
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47. A region of suppressed recombination misleads neoavian phylogenomics.

Author

Mirarab S, Rivas-González I, Feng S, Stiller J, Fang Q, Mai U, Hickey G, Chen G, Brajuka N, Fedrigo O, Formenti G, Wolf JBW, Howe K, Antunes A, Schierup MH, Paten B, Jarvis ED, Zhang G, and Braun EL

Subjects
Animals, Phylogeny, Birds, Recombination, Genetic, Biological Evolution, Genome genetics
Abstract

Genomes are typically mosaics of regions with different evolutionary histories. When speciation events are closely spaced in time, recombination makes the regions sharing the same history small, and the evolutionary history changes rapidly as we move along the genome. When examining rapid radiations such as the early diversification of Neoaves 66 Mya, typically no consistent history is observed across segments exceeding kilobases of the genome. Here, we report an exception. We found that a 21-Mb region in avian genomes, mapped to chicken chromosome 4, shows an extremely strong and discordance-free signal for a history different from that of the inferred species tree. Such a strong discordance-free signal, indicative of suppressed recombination across many millions of base pairs, is not observed elsewhere in the genome for any deep avian relationships. Although long regions with suppressed recombination have been documented in recently diverged species, our results pertain to relationships dating circa 65 Mya. We provide evidence that this strong signal may be due to an ancient rearrangement that blocked recombination and remained polymorphic for several million years prior to fixation. We show that the presence of this region has misled previous phylogenomic efforts with lower taxon sampling, showing the interplay between taxon and locus sampling. We predict that similar ancient rearrangements may confound phylogenetic analyses in other clades, pointing to a need for new analytical models that incorporate the possibility of such events., Competing Interests: Competing interests statement:The authors declare no competing interest.

Published
2024
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48. Pangenome graph construction from genome alignments with Minigraph-Cactus.

Author

Hickey G, Monlong J, Ebler J, Novak AM, Eizenga JM, Gao Y, Marschall T, Li H, and Paten B

Subjects
Humans, Animals, Haplotypes genetics, Alleles, Sequence Analysis, DNA, Genome, Human genetics, Drosophila melanogaster genetics, High-Throughput Nucleotide Sequencing methods
Abstract

Pangenome references address biases of reference genomes by storing a representative set of diverse haplotypes and their alignment, usually as a graph. Alternate alleles determined by variant callers can be used to construct pangenome graphs, but advances in long-read sequencing are leading to widely available, high-quality phased assemblies. Constructing a pangenome graph directly from assemblies, as opposed to variant calls, leverages the graph's ability to represent variation at different scales. Here we present the Minigraph-Cactus pangenome pipeline, which creates pangenomes directly from whole-genome alignments, and demonstrate its ability to scale to 90 human haplotypes from the Human Pangenome Reference Consortium. The method builds graphs containing all forms of genetic variation while allowing use of current mapping and genotyping tools. We measure the effect of the quality and completeness of reference genomes used for analysis within the pangenomes and show that using the CHM13 reference from the Telomere-to-Telomere Consortium improves the accuracy of our methods. We also demonstrate construction of a Drosophila melanogaster pangenome., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2024
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49. Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements.

Author

Wirthlin ME, Schmid TA, Elie JE, Zhang X, Kowalczyk A, Redlich R, Shvareva VA, Rakuljic A, Ji MB, Bhat NS, Kaplow IM, Schäffer DE, Lawler AJ, Wang AZ, Phan BN, Annaldasula S, Brown AR, Lu T, Lim BK, Azim E, Clark NL, Meyer WK, Pond SLK, Chikina M, Yartsev MM, Pfenning AR, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, and Zhang X

Subjects
Animals, Chiroptera genetics, Chiroptera physiology, Chromatin metabolism, Larynx physiology, Epigenesis, Genetic, Genome, Amino Acid Sequence, Machine Learning, Vocalization, Animal physiology, Motor Cortex cytology, Motor Cortex physiology, Enhancer Elements, Genetic, Motor Neurons physiology, Gene Expression Regulation, Evolution, Molecular, Proteins genetics, Proteins metabolism, Eutheria genetics, Eutheria physiology
Abstract

Vocal production learning ("vocal learning") is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat ( Rousettus aegyptiacus ) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.

Published
2024
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50. Severus: accurate detection and characterization of somatic structural variation in tumor genomes using long reads.

Author

Keskus A, Bryant A, Ahmad T, Yoo B, Aganezov S, Goretsky A, Donmez A, Lansdon LA, Rodriguez I, Park J, Liu Y, Cui X, Gardner J, McNulty B, Sacco S, Shetty J, Zhao Y, Tran B, Narzisi G, Helland A, Cook DE, Chang PC, Kolesnikov A, Carroll A, Molloy EK, Pushel I, Guest E, Pastinen T, Shafin K, Miga KH, Malikic S, Day CP, Robine N, Sahinalp C, Dean M, Farooqi MS, Paten B, and Kolmogorov M

Abstract

Most current studies rely on short-read sequencing to detect somatic structural variation (SV) in cancer genomes. Long-read sequencing offers the advantage of better mappability and long-range phasing, which results in substantial improvements in germline SV detection. However, current long-read SV detection methods do not generalize well to the analysis of somatic SVs in tumor genomes with complex rearrangements, heterogeneity, and aneuploidy. Here, we present Severus: a method for the accurate detection of different types of somatic SVs using a phased breakpoint graph approach. To benchmark various short- and long-read SV detection methods, we sequenced five tumor/normal cell line pairs with Illumina, Nanopore, and PacBio sequencing platforms; on this benchmark Severus showed the highest F1 scores (harmonic mean of the precision and recall) as compared to long-read and short-read methods. We then applied Severus to three clinical cases of pediatric cancer, demonstrating concordance with known genetic findings as well as revealing clinically relevant cryptic rearrangements missed by standard genomic panels., Competing Interests: Competing interests. S.A. is an employee and stockholder of Oxford Nanopore Technologies. A.K., P.C., K.S., D.C., A.C. are employees of Google LLC and own Alphabet stock as part of the standard compensation package. E.G. served on advisory boards for Jazz Pharmaceuticals and Syndax Pharmaceuticals. M.S.F. is part of the speakers bureau for Bayer and PacBio. The remaining authors declare no competing interests.

Published
2024
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