Search

Your search keyword '"Karczewski, Konrad J."' showing total 453 results
Start Over Author "Karczewski, Konrad J."
453 results on '"Karczewski, Konrad J."'

1. Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation

Author

Carey, Caitlin E., Shafee, Rebecca, Wedow, Robbee, Elliott, Amanda, Palmer, Duncan S., Compitello, John, Kanai, Masahiro, Abbott, Liam, Schultz, Patrick, Karczewski, Konrad J., Bryant, Samuel C., Cusick, Caroline M., Churchhouse, Claire, Howrigan, Daniel P., King, Daniel, Davey Smith, George, Neale, Benjamin M., Walters, Raymond K., and Robinson, Elise B.

Published
2024
Full Text
View/download PDF

3. A genomic mutational constraint map using variation in 76,156 human genomes

Author

Chen, Siwei, Francioli, Laurent C., Goodrich, Julia K., Collins, Ryan L., Kanai, Masahiro, Wang, Qingbo, Alföldi, Jessica, Watts, Nicholas A., Vittal, Christopher, Gauthier, Laura D., Poterba, Timothy, Wilson, Michael W., Tarasova, Yekaterina, Phu, William, Grant, Riley, Yohannes, Mary T., Koenig, Zan, Farjoun, Yossi, Banks, Eric, Donnelly, Stacey, Gabriel, Stacey, Gupta, Namrata, Ferriera, Steven, Tolonen, Charlotte, Novod, Sam, Bergelson, Louis, Roazen, David, Ruano-Rubio, Valentin, Covarrubias, Miguel, Llanwarne, Christopher, Petrillo, Nikelle, Wade, Gordon, Jeandet, Thibault, Munshi, Ruchi, Tibbetts, Kathleen, O’Donnell-Luria, Anne, Solomonson, Matthew, Seed, Cotton, Martin, Alicia R., Talkowski, Michael E., Rehm, Heidi L., Daly, Mark J., Tiao, Grace, Neale, Benjamin M., MacArthur, Daniel G., and Karczewski, Konrad J.

Published
2024
Full Text
View/download PDF

4. Inferring compound heterozygosity from large-scale exome sequencing data

Author

Guo, Michael H., Francioli, Laurent C., Stenton, Sarah L., Goodrich, Julia K., Watts, Nicholas A., Singer-Berk, Moriel, Groopman, Emily, Darnowsky, Philip W., Solomonson, Matthew, Baxter, Samantha, Tiao, Grace, Neale, Benjamin M., Hirschhorn, Joel N., Rehm, Heidi L., Daly, Mark J., O’Donnell-Luria, Anne, Karczewski, Konrad J., MacArthur, Daniel G., and Samocha, Kaitlin E.

Published
2024
Full Text
View/download PDF

8. Rare coding variants in ten genes confer substantial risk for schizophrenia.

Author

Singh, Tarjinder, Poterba, Timothy, Curtis, David, Akil, Huda, Al Eissa, Mariam, Barchas, Jack D, Bass, Nicholas, Bigdeli, Tim B, Breen, Gerome, Bromet, Evelyn J, Buckley, Peter F, Bunney, William E, Bybjerg-Grauholm, Jonas, Byerley, William F, Chapman, Sinéad B, Chen, Wei J, Churchhouse, Claire, Craddock, Nicholas, Cusick, Caroline M, DeLisi, Lynn, Dodge, Sheila, Escamilla, Michael A, Eskelinen, Saana, Fanous, Ayman H, Faraone, Stephen V, Fiorentino, Alessia, Francioli, Laurent, Gabriel, Stacey B, Gage, Diane, Gagliano Taliun, Sarah A, Ganna, Andrea, Genovese, Giulio, Glahn, David C, Grove, Jakob, Hall, Mei-Hua, Hämäläinen, Eija, Heyne, Henrike O, Holi, Matti, Hougaard, David M, Howrigan, Daniel P, Huang, Hailiang, Hwu, Hai-Gwo, Kahn, René S, Kang, Hyun Min, Karczewski, Konrad J, Kirov, George, Knowles, James A, Lee, Francis S, Lehrer, Douglas S, Lescai, Francesco, Malaspina, Dolores, Marder, Stephen R, McCarroll, Steven A, McIntosh, Andrew M, Medeiros, Helena, Milani, Lili, Morley, Christopher P, Morris, Derek W, Mortensen, Preben Bo, Myers, Richard M, Nordentoft, Merete, O'Brien, Niamh L, Olivares, Ana Maria, Ongur, Dost, Ouwehand, Willem H, Palmer, Duncan S, Paunio, Tiina, Quested, Digby, Rapaport, Mark H, Rees, Elliott, Rollins, Brandi, Satterstrom, F Kyle, Schatzberg, Alan, Scolnick, Edward, Scott, Laura J, Sharp, Sally I, Sklar, Pamela, Smoller, Jordan W, Sobell, Janet L, Solomonson, Matthew, Stahl, Eli A, Stevens, Christine R, Suvisaari, Jaana, Tiao, Grace, Watson, Stanley J, Watts, Nicholas A, Blackwood, Douglas H, Børglum, Anders D, Cohen, Bruce M, Corvin, Aiden P, Esko, Tõnu, Freimer, Nelson B, Glatt, Stephen J, Hultman, Christina M, McQuillin, Andrew, Palotie, Aarno, Pato, Carlos N, Pato, Michele T, Pulver, Ann E, and St Clair, David

Subjects
Humans, Genetic Predisposition to Disease, Receptors, N-Methyl-D-Aspartate, Case-Control Studies, Schizophrenia, Mutation, Exome, Neurodevelopmental Disorders, Human Genome, Biotechnology, Mental Health, Neurosciences, Brain Disorders, Genetics, Serious Mental Illness, Aetiology, 2.1 Biological and endogenous factors, Mental health, Neurological, General Science & Technology
Abstract

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, P

Published
2022

10. Genome-wide screen of otosclerosis in population biobanks: 27 loci and shared associations with skeletal structure

Author

Rämö, Joel T., Kiiskinen, Tuomo, Seist, Richard, Krebs, Kristi, Kanai, Masahiro, Karjalainen, Juha, Kurki, Mitja, Hämäläinen, Eija, Häppölä, Paavo, Havulinna, Aki S., Hautakangas, Heidi, Mägi, Reedik, Palta, Priit, Esko, Tõnu, Metspalu, Andres, Pirinen, Matti, Karczewski, Konrad J., Ripatti, Samuli, Milani, Lili, Stankovic, Konstantina M., Mäkitie, Antti, Daly, Mark J., and Palotie, Aarno

Published
2023
Full Text
View/download PDF

12. Author Correction: A genomic mutational constraint map using variation in 76,156 human genomes

Author

Chen, Siwei, Francioli, Laurent C., Goodrich, Julia K., Collins, Ryan L., Kanai, Masahiro, Wang, Qingbo, Alföldi, Jessica, Watts, Nicholas A., Vittal, Christopher, Gauthier, Laura D., Poterba, Timothy, Wilson, Michael W., Tarasova, Yekaterina, Phu, William, Grant, Riley, Yohannes, Mary T., Koenig, Zan, Farjoun, Yossi, Banks, Eric, Donnelly, Stacey, Gabriel, Stacey, Gupta, Namrata, Ferriera, Steven, Tolonen, Charlotte, Novod, Sam, Bergelson, Louis, Roazen, David, Ruano-Rubio, Valentin, Covarrubias, Miguel, Llanwarne, Christopher, Petrillo, Nikelle, Wade, Gordon, Jeandet, Thibault, Munshi, Ruchi, Tibbetts, Kathleen, O’Donnell-Luria, Anne, Solomonson, Matthew, Seed, Cotton, Martin, Alicia R., Talkowski, Michael E., Rehm, Heidi L., Daly, Mark J., Tiao, Grace, Neale, Benjamin M., MacArthur, Daniel G., and Karczewski, Konrad J.

Published
2024
Full Text
View/download PDF

17. A structural variation reference for medical and population genetics

Author

Collins, Ryan L, Brand, Harrison, Karczewski, Konrad J, Zhao, Xuefang, Alföldi, Jessica, Francioli, Laurent C, Khera, Amit V, Lowther, Chelsea, Gauthier, Laura D, Wang, Harold, Watts, Nicholas A, Solomonson, Matthew, O’Donnell-Luria, Anne, Baumann, Alexander, Munshi, Ruchi, Walker, Mark, Whelan, Christopher W, Huang, Yongqing, Brookings, Ted, Sharpe, Ted, Stone, Matthew R, Valkanas, Elise, Fu, Jack, Tiao, Grace, Laricchia, Kristen M, Ruano-Rubio, Valentin, Stevens, Christine, Gupta, Namrata, Cusick, Caroline, Margolin, Lauren, Taylor, Kent D, Lin, Henry J, Rich, Stephen S, Post, Wendy S, Chen, Yii-Der Ida, Rotter, Jerome I, Nusbaum, Chad, Philippakis, Anthony, Lander, Eric, Gabriel, Stacey, Neale, Benjamin M, Kathiresan, Sekar, Daly, Mark J, Banks, Eric, MacArthur, Daniel G, and Talkowski, Michael E

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Human Genome, Generic health relevance, Disease, Female, Genetic Testing, Genetic Variation, Genetics, Medical, Genetics, Population, Genome, Human, Genotyping Techniques, Humans, Male, Middle Aged, Mutation, Polymorphism, Single Nucleotide, Racial Groups, Reference Standards, Selection, Genetic, Whole Genome Sequencing, Genome Aggregation Database Production Team, Genome Aggregation Database Consortium, General Science & Technology
Abstract

Structural variants (SVs) rearrange large segments of DNA1 and can have profound consequences in evolution and human disease2,3. As national biobanks, disease-association studies, and clinical genetic testing have grown increasingly reliant on genome sequencing, population references such as the Genome Aggregation Database (gnomAD)4 have become integral in the interpretation of single-nucleotide variants (SNVs)5. However, there are no reference maps of SVs from high-coverage genome sequencing comparable to those for SNVs. Here we present a reference of sequence-resolved SVs constructed from 14,891 genomes across diverse global populations (54% non-European) in gnomAD. We discovered a rich and complex landscape of 433,371 SVs, from which we estimate that SVs are responsible for 25-29% of all rare protein-truncating events per genome. We found strong correlations between natural selection against damaging SNVs and rare SVs that disrupt or duplicate protein-coding sequence, which suggests that genes that are highly intolerant to loss-of-function are also sensitive to increased dosage6. We also uncovered modest selection against noncoding SVs in cis-regulatory elements, although selection against protein-truncating SVs was stronger than all noncoding effects. Finally, we identified very large (over one megabase), rare SVs in 3.9% of samples, and estimate that 0.13% of individuals may carry an SV that meets the existing criteria for clinically important incidental findings7. This SV resource is freely distributed via the gnomAD browser8 and will have broad utility in population genetics, disease-association studies, and diagnostic screening.

Published
2020

18. Comprehensive Analysis of Genetic Ancestry and Its Molecular Correlates in Cancer

Author

Carrot-Zhang, Jian, Chambwe, Nyasha, Damrauer, Jeffrey S, Knijnenburg, Theo A, Robertson, A Gordon, Yau, Christina, Zhou, Wanding, Berger, Ashton C, Huang, Kuan-lin, Newberg, Justin Y, Mashl, R Jay, Romanel, Alessandro, Sayaman, Rosalyn W, Demichelis, Francesca, Felau, Ina, Frampton, Garrett M, Han, Seunghun, Hoadley, Katherine A, Kemal, Anab, Laird, Peter W, Lazar, Alexander J, Le, Xiuning, Oak, Ninad, Shen, Hui, Wong, Christopher K, Zenklusen, Jean C, Ziv, Elad, Network, Cancer Genome Atlas Analysis, Aguet, Francois, Ding, Li, Demchok, John A, Mensah, Michael KA, Caesar-Johnson, Samantha, Tarnuzzer, Roy, Wang, Zhining, Yang, Liming, Alfoldi, Jessica, Karczewski, Konrad J, MacArthur, Daniel G, Meyerson, Matthew, Benz, Christopher, Stuart, Joshua M, Cherniack, Andrew D, and Beroukhim, Rameen

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Genetics, Human Genome, Clinical Research, Cancer, Biotechnology, DNA Methylation, DNA-Binding Proteins, Ethnicity, F-Box-WD Repeat-Containing Protein 7, Gene Expression Regulation, Neoplastic, Genetic Predisposition to Disease, Genetics, Population, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing, Humans, MicroRNAs, Mutation, Neoplasm Proteins, Neoplasms, Transcription Factors, Von Hippel-Lindau Tumor Suppressor Protein, Cancer Genome Atlas Analysis Network, TCGA, admixture, ancestry, cancer, eQTL, genomics, mRNA, methylation, miRNA, mutation, Neurosciences, Oncology & Carcinogenesis, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

We evaluated ancestry effects on mutation rates, DNA methylation, and mRNA and miRNA expression among 10,678 patients across 33 cancer types from The Cancer Genome Atlas. We demonstrated that cancer subtypes and ancestry-related technical artifacts are important confounders that have been insufficiently accounted for. Once accounted for, ancestry-associated differences spanned all molecular features and hundreds of genes. Biologically significant differences were usually tissue specific but not specific to cancer. However, admixture and pathway analyses suggested some of these differences are causally related to cancer. Specific findings included increased FBXW7 mutations in patients of African origin, decreased VHL and PBRM1 mutations in renal cancer patients of African origin, and decreased immune activity in bladder cancer patients of East Asian origin.

Published
2020

19. Systematic single-variant and gene-based association testing of thousands of phenotypes in 394,841 UK Biobank exomes

Author

Karczewski, Konrad J., Solomonson, Matthew, Chao, Katherine R., Goodrich, Julia K., Tiao, Grace, Lu, Wenhan, Riley-Gillis, Bridget M., Tsai, Ellen A., Kim, Hye In, Zheng, Xiuwen, Rahimov, Fedik, Esmaeeli, Sahar, Grundstad, A. Jason, Reppell, Mark, Waring, Jeff, Jacob, Howard, Sexton, David, Bronson, Paola G., Chen, Xing, Hu, Xinli, Goldstein, Jacqueline I., King, Daniel, Vittal, Christopher, Poterba, Timothy, Palmer, Duncan S., Churchhouse, Claire, Howrigan, Daniel P., Zhou, Wei, Watts, Nicholas A., Nguyen, Kevin, Nguyen, Huy, Mason, Cara, Farnham, Christopher, Tolonen, Charlotte, Gauthier, Laura D., Gupta, Namrata, MacArthur, Daniel G., Rehm, Heidi L., Seed, Cotton, Philippakis, Anthony A., Daly, Mark J., Davis, J. Wade, Runz, Heiko, Miller, Melissa R., and Neale, Benjamin M.

Published
2022
Full Text
View/download PDF

20. Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis

Author

Yang, Fan, Wang, Jiebiao, Consortium, The GTEx, Pierce, Brandon L, Chen, Lin S, Aguet, François, Ardlie, Kristin G, Cummings, Beryl B, Gelfand, Ellen T, Getz, Gad, Hadley, Kane, Handsaker, Robert E, Huang, Katherine H, Kashin, Seva, Karczewski, Konrad J, Lek, Monkol, Li, Xiao, MacArthur, Daniel G, Nedzel, Jared L, Nguyen, Duyen T, Noble, Michael S, Segrè, Ayellet V, Trowbridge, Casandra A, Tukiainen, Taru, Abell, Nathan S, Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K, Brown, Andrew, Brown, Christopher D, Castel, Stephane E, Chiang, Colby, Conrad, Donald F, Cox, Nancy J, Damani, Farhan N, Davis, Joe R, Delaneau, Olivier, Dermitzakis, Emmanouil T, Engelhardt, Barbara E, Eskin, Eleazar, Ferreira, Pedro G, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gewirtz, Ariel DH, Gliner, Genna, Gloudemans, Michael J, Guigo, Roderic, Hall, Ira M, Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Im, Hae Kyung, Jo, Brian, Kang, Eun Yong, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I, McDowell, Ian C, Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B, Muñoz-Aguirre, Manuel, Ndungu, Anne W, Nicolae, Dan L, Nobel, Andrew B, Oliva, Meritxell, Ongen, Halit, Palowitch, John J, Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J, Peterson, Christine B, Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J, Shabalin, Andrey A, Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E, Strober, Benjamin J, Sul, Jae Hoon, Tsang, Emily K, Urbut, Sarah, van de Bunt, Martijn, and Wang, Gao

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Human Genome, 2.1 Biological and endogenous factors, Underpinning research, Aetiology, 1.1 Normal biological development and functioning, Generic health relevance, Good Health and Well Being, Databases, Genetic, Gene Expression Profiling, Gene Expression Regulation, Gene Regulatory Networks, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Selection, Genetic, Tissue Distribution, GTEx Consortium, Medical and Health Sciences, Bioinformatics
Abstract

The impact of inherited genetic variation on gene expression in humans is well-established. The majority of known expression quantitative trait loci (eQTLs) impact expression of local genes (cis-eQTLs). More research is needed to identify effects of genetic variation on distant genes (trans-eQTLs) and understand their biological mechanisms. One common trans-eQTLs mechanism is "mediation" by a local (cis) transcript. Thus, mediation analysis can be applied to genome-wide SNP and expression data in order to identify transcripts that are "cis-mediators" of trans-eQTLs, including those "cis-hubs" involved in regulation of many trans-genes. Identifying such mediators helps us understand regulatory networks and suggests biological mechanisms underlying trans-eQTLs, both of which are relevant for understanding susceptibility to complex diseases. The multitissue expression data from the Genotype-Tissue Expression (GTEx) program provides a unique opportunity to study cis-mediation across human tissue types. However, the presence of complex hidden confounding effects in biological systems can make mediation analyses challenging and prone to confounding bias, particularly when conducted among diverse samples. To address this problem, we propose a new method: Genomic Mediation analysis with Adaptive Confounding adjustment (GMAC). It enables the search of a very large pool of variables, and adaptively selects potential confounding variables for each mediation test. Analyses of simulated data and GTEx data demonstrate that the adaptive selection of confounders by GMAC improves the power and precision of mediation analysis. Application of GMAC to GTEx data provides new insights into the observed patterns of cis-hubs and trans-eQTL regulation across tissue types.

Published
2017

21. Co-expression networks reveal the tissue-specific regulation of transcription and splicing

Author

Saha, Ashis, Kim, Yungil, Gewirtz, Ariel DH, Jo, Brian, Gao, Chuan, McDowell, Ian C, Consortium, The GTEx, Engelhardt, Barbara E, Battle, Alexis, Aguet, François, Ardlie, Kristin G, Cummings, Beryl B, Gelfand, Ellen T, Getz, Gad, Hadley, Kane, Handsaker, Robert E, Huang, Katherine H, Kashin, Seva, Karczewski, Konrad J, Lek, Monkol, Li, Xiao, MacArthur, Daniel G, Nedzel, Jared L, Nguyen, Duyen T, Noble, Michael S, Segrè, Ayellet V, Trowbridge, Casandra A, Tukiainen, Taru, Abell, Nathan S, Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Bogu, Gireesh K, Brown, Andrew, Brown, Christopher D, Castel, Stephane E, Chen, Lin S, Chiang, Colby, Conrad, Donald F, Cox, Nancy J, Damani, Farhan N, Davis, Joe R, Delaneau, Olivier, Dermitzakis, Emmanouil T, Eskin, Eleazar, Ferreira, Pedro G, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gliner, Genna, Gloudemans, Michael J, Guigo, Roderic, Hall, Ira M, Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Im, Hae Kyung, Kang, Eun Yong, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I, Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B, Muñoz-Aguirre, Manuel, Ndungu, Anne W, Nicolae, Dan L, Nobel, Andrew B, Oliva, Meritxell, Ongen, Halit, Palowitch, John J, Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J, Peterson, Christine B, Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Sammeth, Michael, Scott, Alexandra J, Shabalin, Andrey A, Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E, Strober, Benjamin J, and Sul, Jae Hoon

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Biotechnology, Human Genome, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Generic health relevance, Bayes Theorem, Databases, Genetic, Gene Expression Profiling, Gene Expression Regulation, Gene Regulatory Networks, Genotyping Techniques, Humans, Organ Specificity, Polymorphism, Single Nucleotide, RNA Splicing, Sequence Analysis, RNA, GTEx Consortium, Medical and Health Sciences, Bioinformatics
Abstract

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.

Published
2017

22. Dynamic landscape and regulation of RNA editing in mammals

Author

Aguet, François, Ardlie, Kristin G, Cummings, Beryl B, Gelfand, Ellen T, Getz, Gad, Hadley, Kane, Handsaker, Robert E, Huang, Katherine H, Kashin, Seva, Karczewski, Konrad J, Lek, Monkol, Li, Xiao, MacArthur, Daniel G, Nedzel, Jared L, Nguyen, Duyen T, Noble, Michael S, Segrè, Ayellet V, Trowbridge, Casandra A, Tukiainen, Taru, Abell, Nathan S, Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K, Brown, Andrew, Brown, Christopher D, Castel, Stephane E, Chen, Lin S, Chiang, Colby, Conrad, Donald F, Cox, Nancy J, Damani, Farhan N, Davis, Joe R, Delaneau, Olivier, Dermitzakis, Emmanouil T, Engelhardt, Barbara E, Eskin, Eleazar, Ferreira, Pedro G, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gewirtz, Ariel DH, Gliner, Genna, Gloudemans, Michael J, Guigo, Roderic, Hall, Ira M, Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I, McDowell, Ian C, Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B, Muñoz-Aguirre, Manuel, Ndungu, Anne W, Nicolae, Dan L, Nobel, Andrew B, Oliva, Meritxell, Ongen, Halit, Palowitch, John J, Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J, Peterson, Christine B, Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J, Shabalin, Andrey A, Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E, Strober, Benjamin J, Sul, Jae Hoon, Tsang, Emily K, Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A, Xi, Hualin S, Yeger-Lotem, Esti, and Zappala, Zachary

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Adenosine Deaminase, Animals, Female, Genotype, HEK293 Cells, Humans, Male, Mice, Muscles, Nuclear Proteins, Organ Specificity, Primates, Proteolysis, RNA Editing, RNA-Binding Proteins, Spatio-Temporal Analysis, Species Specificity, Transcriptome, GTEx Consortium, Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, General Science & Technology
Abstract

Adenosine-to-inosine (A-to-I) RNA editing is a conserved post-transcriptional mechanism mediated by ADAR enzymes that diversifies the transcriptome by altering selected nucleotides in RNA molecules. Although many editing sites have recently been discovered, the extent to which most sites are edited and how the editing is regulated in different biological contexts are not fully understood. Here we report dynamic spatiotemporal patterns and new regulators of RNA editing, discovered through an extensive profiling of A-to-I RNA editing in 8,551 human samples (representing 53 body sites from 552 individuals) from the Genotype-Tissue Expression (GTEx) project and in hundreds of other primate and mouse samples. We show that editing levels in non-repetitive coding regions vary more between tissues than editing levels in repetitive regions. Globally, ADAR1 is the primary editor of repetitive sites and ADAR2 is the primary editor of non-repetitive coding sites, whereas the catalytically inactive ADAR3 predominantly acts as an inhibitor of editing. Cross-species analysis of RNA editing in several tissues revealed that species, rather than tissue type, is the primary determinant of editing levels, suggesting stronger cis-directed regulation of RNA editing for most sites, although the small set of conserved coding sites is under stronger trans-regulation. In addition, we curated an extensive set of ADAR1 and ADAR2 targets and showed that many editing sites display distinct tissue-specific regulation by the ADAR enzymes in vivo. Further analysis of the GTEx data revealed several potential regulators of editing, such as AIMP2, which reduces editing in muscles by enhancing the degradation of the ADAR proteins. Collectively, our work provides insights into the complex cis- and trans-regulation of A-to-I editing.

Published
2017

23. Landscape of X chromosome inactivation across human tissues

Author

Aguet, François, Ardlie, Kristin G, Cummings, Beryl B, Gelfand, Ellen T, Getz, Gad, Hadley, Kane, Handsaker, Robert E, Huang, Katherine H, Kashin, Seva, Karczewski, Konrad J, Lek, Monkol, Li, Xiao, MacArthur, Daniel G, Nedzel, Jared L, Nguyen, Duyen T, Noble, Michael S, Segrè, Ayellet V, Trowbridge, Casandra A, Tukiainen, Taru, Abell, Nathan S, Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K, Brown, Andrew, Brown, Christopher D, Castel, Stephane E, Chen, Lin S, Chiang, Colby, Conrad, Donald F, Cox, Nancy J, Damani, Farhan N, Davis, Joe R, Delaneau, Olivier, Dermitzakis, Emmanouil T, Engelhardt, Barbara E, Eskin, Eleazar, Ferreira, Pedro G, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gewirtz, Ariel DH, Gliner, Genna, Gloudemans, Michael J, Guigo, Roderic, Hall, Ira M, Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I, McDowell, Ian C, Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B, Muñoz-Aguirre, Manuel, Ndungu, Anne W, Nicolae, Dan L, Nobel, Andrew B, Oliva, Meritxell, Ongen, Halit, Palowitch, John J, Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J, Peterson, Christine B, Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J, Shabalin, Andrey A, Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E, Strober, Benjamin J, Sul, Jae Hoon, Tsang, Emily K, Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A, Xi, Hualin S, Yeger-Lotem, Esti, and Zappala, Zachary

Subjects
Genetics, Clinical Research, Human Genome, Generic health relevance, Good Health and Well Being, Chromosomes, Human, X, Female, Genes, X-Linked, Genome, Human, Genomics, Humans, Male, Organ Specificity, Phenotype, Sequence Analysis, RNA, Single-Cell Analysis, Transcriptome, X Chromosome Inactivation, GTEx Consortium, Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, General Science & Technology
Abstract

X chromosome inactivation (XCI) silences transcription from one of the two X chromosomes in female mammalian cells to balance expression dosage between XX females and XY males. XCI is, however, incomplete in humans: up to one-third of X-chromosomal genes are expressed from both the active and inactive X chromosomes (Xa and Xi, respectively) in female cells, with the degree of 'escape' from inactivation varying between genes and individuals. The extent to which XCI is shared between cells and tissues remains poorly characterized, as does the degree to which incomplete XCI manifests as detectable sex differences in gene expression and phenotypic traits. Here we describe a systematic survey of XCI, integrating over 5,500 transcriptomes from 449 individuals spanning 29 tissues from GTEx (v6p release) and 940 single-cell transcriptomes, combined with genomic sequence data. We show that XCI at 683 X-chromosomal genes is generally uniform across human tissues, but identify examples of heterogeneity between tissues, individuals and cells. We show that incomplete XCI affects at least 23% of X-chromosomal genes, identify seven genes that escape XCI with support from multiple lines of evidence and demonstrate that escape from XCI results in sex biases in gene expression, establishing incomplete XCI as a mechanism that is likely to introduce phenotypic diversity. Overall, this updated catalogue of XCI across human tissues helps to increase our understanding of the extent and impact of the incompleteness in the maintenance of XCI.

Published
2017

24. The impact of rare variation on gene expression across tissues

Author

Aguet, François, Ardlie, Kristin G, Cummings, Beryl B, Gelfand, Ellen T, Getz, Gad, Hadley, Kane, Handsaker, Robert E, Huang, Katherine H, Kashin, Seva, Karczewski, Konrad J, Lek, Monkol, Li, Xiao, MacArthur, Daniel G, Nedzel, Jared L, Nguyen, Duyen T, Noble, Michael S, Segrè, Ayellet V, Trowbridge, Casandra A, Tukiainen, Taru, Abell, Nathan S, Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K, Brown, Andrew, Brown, Christopher D, Castel, Stephane E, Chen, Lin S, Chiang, Colby, Conrad, Donald F, Cox, Nancy J, Damani, Farhan N, Davis, Joe R, Delaneau, Olivier, Dermitzakis, Emmanouil T, Engelhardt, Barbara E, Eskin, Eleazar, Ferreira, Pedro G, Frésard, Laure, Gamazon, Eric R, Garrido-Martín, Diego, Gewirtz, Ariel DH, Gliner, Genna, Gloudemans, Michael J, Guigo, Roderic, Hall, Ira M, Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I, McDowell, Ian C, Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B, Muñoz-Aguirre, Manuel, Ndungu, Anne W, Nicolae, Dan L, Nobel, Andrew B, Oliva, Meritxell, Ongen, Halit, Palowitch, John J, Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J, Peterson, Christine B, Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J, Shabalin, Andrey A, Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E, Strober, Benjamin J, Sul, Jae Hoon, Tsang, Emily K, Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A, Xi, Hualin S, Yeger-Lotem, Esti, and Zappala, Zachary

Subjects
Bayes Theorem, Female, Gene Expression Profiling, Genetic Variation, Genome, Human, Genomics, Genotype, Humans, Male, Models, Genetic, Organ Specificity, Sequence Analysis, RNA, GTEx Consortium, Laboratory, Data Analysis &Coordinating Center (LDACC)—Analysis Working Group, Statistical Methods groups—Analysis Working Group, Enhancing GTEx (eGTEx) groups, NIH Common Fund, NIH/NCI, NIH/NHGRI, NIH/NIMH, NIH/NIDA, Biospecimen Collection Source Site—NDRI, Biospecimen Collection Source Site—RPCI, Biospecimen Core Resource—VARI, Brain Bank Repository—University of Miami Brain Endowment Bank, Leidos Biomedical—Project Management, ELSI Study, Genome Browser Data Integration &Visualization—EBI, Genome Browser Data Integration &Visualization—UCSC Genomics Institute, University of California Santa Cruz, General Science & Technology
Abstract

Rare genetic variants are abundant in humans and are expected to contribute to individual disease risk. While genetic association studies have successfully identified common genetic variants associated with susceptibility, these studies are not practical for identifying rare variants. Efforts to distinguish pathogenic variants from benign rare variants have leveraged the genetic code to identify deleterious protein-coding alleles, but no analogous code exists for non-coding variants. Therefore, ascertaining which rare variants have phenotypic effects remains a major challenge. Rare non-coding variants have been associated with extreme gene expression in studies using single tissues, but their effects across tissues are unknown. Here we identify gene expression outliers, or individuals showing extreme expression levels for a particular gene, across 44 human tissues by using combined analyses of whole genomes and multi-tissue RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project v6p release. We find that 58% of underexpression and 28% of overexpression outliers have nearby conserved rare variants compared to 8% of non-outliers. Additionally, we developed RIVER (RNA-informed variant effect on regulation), a Bayesian statistical model that incorporates expression data to predict a regulatory effect for rare variants with higher accuracy than models using genomic annotations alone. Overall, we demonstrate that rare variants contribute to large gene expression changes across tissues and provide an integrative method for interpretation of rare variants in individual genomes.

Published
2017

25. Pan-UK Biobank GWAS improves discovery, analysis of genetic architecture, and resolution into ancestry-enriched effects

Author

Karczewski, Konrad J, primary, Gupta, Rahul, additional, Kanai, Masahiro, additional, Lu, Wenhan, additional, Tsuo, Kristin, additional, Wang, Ying, additional, Walters, Raymond K, additional, Turley, Patrick, additional, Callier, Shawneequa, additional, Baya, Nikolas, additional, Palmer, Duncan S, additional, Goldstein, Jacqueline I, additional, Sarma, Gopal, additional, Solomonson, Matthew, additional, Cheng, Nathan, additional, Bryant, Sam, additional, Churchhouse, Claire, additional, Cusick, Caroline M, additional, Poterba, Timothy, additional, Compitello, John, additional, King, Daniel, additional, Zhou, Wei, additional, Seed, Cotton, additional, Finucane, Hilary K, additional, Daly, Mark J, additional, Neale, Benjamin M, additional, Atkinson, Elizabeth G, additional, and Martin, Alicia R, additional

Published
2024
Full Text
View/download PDF

26. Refining the role of de novo protein-truncating variants in neurodevelopmental disorders by using population reference samples

Author

Kosmicki, Jack A, Samocha, Kaitlin E, Howrigan, Daniel P, Sanders, Stephan J, Slowikowski, Kamil, Lek, Monkol, Karczewski, Konrad J, Cutler, David J, Devlin, Bernie, Roeder, Kathryn, Buxbaum, Joseph D, Neale, Benjamin M, MacArthur, Daniel G, Wall, Dennis P, Robinson, Elise B, and Daly, Mark J

Subjects
Biological Sciences, Genetics, Brain Disorders, Neurosciences, Biotechnology, Intellectual and Developmental Disabilities (IDD), Aetiology, 2.1 Biological and endogenous factors, Autism Spectrum Disorder, Exome, Genetic Predisposition to Disease, Genetic Variation, Humans, Intellectual Disability, Neurodevelopmental Disorders, Phenotype, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Recent research has uncovered an important role for de novo variation in neurodevelopmental disorders. Using aggregated data from 9,246 families with autism spectrum disorder, intellectual disability, or developmental delay, we found that ∼1/3 of de novo variants are independently present as standing variation in the Exome Aggregation Consortium's cohort of 60,706 adults, and these de novo variants do not contribute to neurodevelopmental risk. We further used a loss-of-function (LoF)-intolerance metric, pLI, to identify a subset of LoF-intolerant genes containing the observed signal of associated de novo protein-truncating variants (PTVs) in neurodevelopmental disorders. LoF-intolerant genes also carry a modest excess of inherited PTVs, although the strongest de novo-affected genes contribute little to this excess, thus suggesting that the excess of inherited risk resides in lower-penetrant genes. These findings illustrate the importance of population-based reference cohorts for the interpretation of candidate pathogenic variants, even for analyses of complex diseases and de novo variation.

Published
2017

27. Human knockouts and phenotypic analysis in a cohort with a high rate of consanguinity

Author

Saleheen, Danish, Natarajan, Pradeep, Armean, Irina M, Zhao, Wei, Rasheed, Asif, Khetarpal, Sumeet A, Won, Hong-Hee, Karczewski, Konrad J, O’Donnell-Luria, Anne H, Samocha, Kaitlin E, Weisburd, Benjamin, Gupta, Namrata, Zaidi, Mozzam, Samuel, Maria, Imran, Atif, Abbas, Shahid, Majeed, Faisal, Ishaq, Madiha, Akhtar, Saba, Trindade, Kevin, Mucksavage, Megan, Qamar, Nadeem, Zaman, Khan Shah, Yaqoob, Zia, Saghir, Tahir, Rizvi, Syed Nadeem Hasan, Memon, Anis, Hayyat Mallick, Nadeem, Ishaq, Mohammad, Rasheed, Syed Zahed, Memon, Fazal-ur-Rehman, Mahmood, Khalid, Ahmed, Naveeduddin, Do, Ron, Krauss, Ronald M, MacArthur, Daniel G, Gabriel, Stacey, Lander, Eric S, Daly, Mark J, Frossard, Philippe, Danesh, John, Rader, Daniel J, and Kathiresan, Sekar

Subjects
Genetics, Clinical Research, Human Genome, 1-Alkyl-2-acetylglycerophosphocholine Esterase, Apolipoprotein C-III, Cohort Studies, Consanguinity, Coronary Disease, Cytochrome P450 Family 2, DNA Mutational Analysis, Dietary Fats, Exome, Fasting, Female, Gene Deletion, Gene Frequency, Genes, Genetic Association Studies, Homozygote, Humans, Interleukin-8, Male, Middle Aged, Myocardial Infarction, Neuregulins, Pakistan, Pedigree, Phenotype, Phosphoproteins, Postprandial Period, RNA Splice Sites, Reverse Genetics, Sodium-Hydrogen Exchangers, Triglycerides, General Science & Technology
Abstract

A major goal of biomedicine is to understand the function of every gene in the human genome. Loss-of-function mutations can disrupt both copies of a given gene in humans and phenotypic analysis of such 'human knockouts' can provide insight into gene function. Consanguineous unions are more likely to result in offspring carrying homozygous loss-of-function mutations. In Pakistan, consanguinity rates are notably high. Here we sequence the protein-coding regions of 10,503 adult participants in the Pakistan Risk of Myocardial Infarction Study (PROMIS), designed to understand the determinants of cardiometabolic diseases in individuals from South Asia. We identified individuals carrying homozygous predicted loss-of-function (pLoF) mutations, and performed phenotypic analysis involving more than 200 biochemical and disease traits. We enumerated 49,138 rare (

Published
2017

31. Analysis of protein-coding genetic variation in 60,706 humans.

Author

Lek, Monkol, Karczewski, Konrad J, Minikel, Eric V, Samocha, Kaitlin E, Banks, Eric, Fennell, Timothy, O'Donnell-Luria, Anne H, Ware, James S, Hill, Andrew J, Cummings, Beryl B, Tukiainen, Taru, Birnbaum, Daniel P, Kosmicki, Jack A, Duncan, Laramie E, Estrada, Karol, Zhao, Fengmei, Zou, James, Pierce-Hoffman, Emma, Berghout, Joanne, Cooper, David N, Deflaux, Nicole, DePristo, Mark, Do, Ron, Flannick, Jason, Fromer, Menachem, Gauthier, Laura, Goldstein, Jackie, Gupta, Namrata, Howrigan, Daniel, Kiezun, Adam, Kurki, Mitja I, Moonshine, Ami Levy, Natarajan, Pradeep, Orozco, Lorena, Peloso, Gina M, Poplin, Ryan, Rivas, Manuel A, Ruano-Rubio, Valentin, Rose, Samuel A, Ruderfer, Douglas M, Shakir, Khalid, Stenson, Peter D, Stevens, Christine, Thomas, Brett P, Tiao, Grace, Tusie-Luna, Maria T, Weisburd, Ben, Won, Hong-Hee, Yu, Dongmei, Altshuler, David M, Ardissino, Diego, Boehnke, Michael, Danesh, John, Donnelly, Stacey, Elosua, Roberto, Florez, Jose C, Gabriel, Stacey B, Getz, Gad, Glatt, Stephen J, Hultman, Christina M, Kathiresan, Sekar, Laakso, Markku, McCarroll, Steven, McCarthy, Mark I, McGovern, Dermot, McPherson, Ruth, Neale, Benjamin M, Palotie, Aarno, Purcell, Shaun M, Saleheen, Danish, Scharf, Jeremiah M, Sklar, Pamela, Sullivan, Patrick F, Tuomilehto, Jaakko, Tsuang, Ming T, Watkins, Hugh C, Wilson, James G, Daly, Mark J, MacArthur, Daniel G, and Exome Aggregation Consortium

Subjects
Exome Aggregation Consortium, Humans, Rare Diseases, Proteome, Sample Size, DNA Mutational Analysis, Phenotype, Genetic Variation, Exome, Datasets as Topic, Clinical Research, Biotechnology, Human Genome, Genetics, Genetic Testing, 2.1 Biological and endogenous factors, Aetiology, Generic health relevance, General Science & Technology
Abstract

Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

Published
2016

32. De novo mutations in congenital heart disease with neurodevelopmental and other congenital anomalies

Author

Homsy, Jason, Zaidi, Samir, Shen, Yufeng, Ware, James S, Samocha, Kaitlin E, Karczewski, Konrad J, DePalma, Steven R, McKean, David, Wakimoto, Hiroko, Gorham, Josh, Jin, Sheng Chih, Deanfield, John, Giardini, Alessandro, Porter, George A, Kim, Richard, Bilguvar, Kaya, López-Giráldez, Francesc, Tikhonova, Irina, Mane, Shrikant, Romano-Adesman, Angela, Qi, Hongjian, Vardarajan, Badri, Ma, Lijiang, Daly, Mark, Roberts, Amy E, Russell, Mark W, Mital, Seema, Newburger, Jane W, Gaynor, J William, Breitbart, Roger E, Iossifov, Ivan, Ronemus, Michael, Sanders, Stephan J, Kaltman, Jonathan R, Seidman, Jonathan G, Brueckner, Martina, Gelb, Bruce D, Goldmuntz, Elizabeth, Lifton, Richard P, Seidman, Christine E, and Chung, Wendy K

Subjects
Congenital Structural Anomalies, Genetics, Pediatric, Heart Disease, Cardiovascular, Brain, Child, Congenital Abnormalities, Exome, Heart Defects, Congenital, Humans, Mutation, Nervous System Malformations, Neurogenesis, Prognosis, RNA Splicing, RNA Splicing Factors, RNA, Messenger, RNA-Binding Proteins, Repressor Proteins, Transcription, Genetic, General Science & Technology
Abstract

Congenital heart disease (CHD) patients have an increased prevalence of extracardiac congenital anomalies (CAs) and risk of neurodevelopmental disabilities (NDDs). Exome sequencing of 1213 CHD parent-offspring trios identified an excess of protein-damaging de novo mutations, especially in genes highly expressed in the developing heart and brain. These mutations accounted for 20% of patients with CHD, NDD, and CA but only 2% of patients with isolated CHD. Mutations altered genes involved in morphogenesis, chromatin modification, and transcriptional regulation, including multiple mutations in RBFOX2, a regulator of mRNA splicing. Genes mutated in other cohorts examined for NDD were enriched in CHD cases, particularly those with coexisting NDD. These findings reveal shared genetic contributions to CHD, NDD, and CA and provide opportunities for improved prognostic assessment and early therapeutic intervention in CHD patients.

Published
2015

33. The mutational constraint spectrum quantified from variation in 141,456 humans

Author

Karczewski, Konrad J., Francioli, Laurent C., Tiao, Grace, Cummings, Beryl B., Alföldi, Jessica, Wang, Qingbo, and Collins, Ryan L.

Subjects
Gene mutations -- Control -- Analysis, Gene silencing -- Analysis, Genetic variation -- Analysis, Human genome -- Identification and classification -- Analysis, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes.sup.1. Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases. A catalogue of predicted loss-of-function variants in 125,748 whole-exome and 15,708 whole-genome sequencing datasets from the Genome Aggregation Database (gnomAD) reveals the spectrum of mutational constraints that affect these human protein-coding genes., Author(s): Konrad J. Karczewski [sup.1] [sup.2] , Laurent C. Francioli [sup.1] [sup.2] , Grace Tiao [sup.1] [sup.2] , Beryl B. Cummings [sup.1] [sup.2] [sup.3] , Jessica Alföldi [sup.1] [sup.2] , [...]

Published
2020
Full Text
View/download PDF

34. Transcript expression-aware annotation improves rare variant interpretation

Author

Cummings, Beryl B., Karczewski, Konrad J., Kosmicki, Jack A., Seaby, Eleanor G., Watts, Nicholas A., Singer-Berk, Moriel, and Mudge, Jonathan M.

Subjects
Genetic variation -- Analysis -- Usage, Human genome -- Identification and classification -- Analysis -- Usage, Genetic transcription -- Usage -- Analysis, Citation indexes -- Management -- Analysis -- Usage, Company business management, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

The acceleration of DNA sequencing in samples from patients and population studies has resulted in extensive catalogues of human genetic variation, but the interpretation of rare genetic variants remains problematic. A notable example of this challenge is the existence of disruptive variants in dosage-sensitive disease genes, even in apparently healthy individuals. Here, by manual curation of putative loss-of-function (pLoF) variants in haploinsufficient disease genes in the Genome Aggregation Database (gnomAD).sup.1, we show that one explanation for this paradox involves alternative splicing of mRNA, which allows exons of a gene to be expressed at varying levels across different cell types. Currently, no existing annotation tool systematically incorporates information about exon expression into the interpretation of variants. We develop a transcript-level annotation metric known as the 'proportion expressed across transcripts', which quantifies isoform expression for variants. We calculate this metric using 11,706 tissue samples from the Genotype Tissue Expression (GTEx) project.sup.2 and show that it can differentiate between weakly and highly evolutionarily conserved exons, a proxy for functional importance. We demonstrate that expression-based annotation selectively filters 22.8% of falsely annotated pLoF variants found in haploinsufficient disease genes in gnomAD, while removing less than 4% of high-confidence pathogenic variants in the same genes. Finally, we apply our expression filter to the analysis of de novo variants in patients with autism spectrum disorder and intellectual disability or developmental disorders to show that pLoF variants in weakly expressed regions have similar effect sizes to those of synonymous variants, whereas pLoF variants in highly expressed exons are most strongly enriched among cases. Our annotation is fast, flexible and generalizable, making it possible for any variant file to be annotated with any isoform expression dataset, and will be valuable for the genetic diagnosis of rare diseases, the analysis of rare variant burden in complex disorders, and the curation and prioritization of variants in recall-by-genotype studies. A novel variant annotation metric that quantifies the level of expression of genetic variants across tissues is validated in the Genome Aggregation Database (gnomAD) and is shown to improve rare variant interpretation., Author(s): Beryl B. Cummings [sup.1] [sup.2] [sup.3] , Konrad J. Karczewski [sup.1] [sup.2] , Jack A. Kosmicki [sup.1] [sup.2] [sup.4] , Eleanor G. Seaby [sup.1] [sup.2] [sup.5] , Nicholas A. [...]

Published
2020
Full Text
View/download PDF

35. Evaluating drug targets through human loss-of-function genetic variation

Author

Minikel, Eric Vallabh, Karczewski, Konrad J., Martin, Hilary C., Cummings, Beryl B., Whiffin, Nicola, Rhodes, Daniel, and Alföldi, Jessica

Subjects
Gene silencing -- Analysis -- Genetic aspects, Drug targeting -- Analysis -- Genetic aspects, Genetic variation -- Analysis -- Genetic aspects, Genetic engineering -- Analysis -- Genetic aspects, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Naturally occurring human genetic variants that are predicted to inactivate protein-coding genes provide an in vivo model of human gene inactivation that complements knockout studies in cells and model organisms. Here we report three key findings regarding the assessment of candidate drug targets using human loss-of-function variants. First, even essential genes, in which loss-of-function variants are not tolerated, can be highly successful as targets of inhibitory drugs. Second, in most genes, loss-of-function variants are sufficiently rare that genotype-based ascertainment of homozygous or compound heterozygous 'knockout' humans will await sample sizes that are approximately 1,000 times those presently available, unless recruitment focuses on consanguineous individuals. Third, automated variant annotation and filtering are powerful, but manual curation remains crucial for removing artefacts, and is a prerequisite for recall-by-genotype efforts. Our results provide a roadmap for human knockout studies and should guide the interpretation of loss-of-function variants in drug development. Analysis of predicted loss-of-function variants from 125,748 human exomes and 15,708 whole genomes in the Genome Aggregation Database (gnomAD) provides a roadmap for human 'knockout' studies and a guide for future research into disease biology and drug-target selection., Author(s): Eric Vallabh Minikel [sup.1] [sup.2] [sup.3] [sup.4] [sup.5] [sup.6] [sup.7] [sup.8] , Konrad J. Karczewski [sup.1] [sup.4] , Hilary C. Martin [sup.9] , Beryl B. Cummings [sup.1] [sup.4] [sup.5] [...]

Published
2020
Full Text
View/download PDF

36. The effect of LRRK2 loss-of-function variants in humans

Author

Whiffin, Nicola, Armean, Irina M., Kleinman, Aaron, Marshall, Jamie L., Minikel, Eric V., Goodrich, Julia K., Quaife, Nicholas M., Cole, Joanne B., Wang, Qingbo, Karczewski, Konrad J., Cummings, Beryl B., Francioli, Laurent, Laricchia, Kristen, Guan, Anna, Alipanahi, Babak, Morrison, Peter, Baptista, Marco A. S., Merchant, Kalpana M., Ware, James S., Havulinna, Aki S., Iliadou, Bozenna, Lee, Jung-Jin, Nadkarni, Girish N., Whiteman, Cole, Daly, Mark, Esko, Tõnu, Hultman, Christina, Loos, Ruth J. F., Milani, Lili, Palotie, Aarno, Pato, Carlos, Pato, Michele, Saleheen, Danish, Sullivan, Patrick F., Alföldi, Jessica, Cannon, Paul, and MacArthur, Daniel G.

Published
2020
Full Text
View/download PDF

37. Hematologic setpoints are a stable and patient-specific deep phenotype

Author

Foy, Brody H, primary, Petherbridge, Rachel, additional, Roth, Maxwell, additional, Mow, Christopher, additional, Patel, Hasmukh R, additional, Patel, Chhaya H, additional, Ho, Samantha N, additional, Lam, Evie, additional, Karczewski, Konrad J, additional, Tozzo, Veronica, additional, and Higgins, John H, additional

Published
2023
Full Text
View/download PDF

38. Systematic functional regulatory assessment of disease-associated variants.

Author

Karczewski, Konrad J, Dudley, Joel T, Kukurba, Kimberly R, Chen, Rong, Butte, Atul J, Montgomery, Stephen B, and Snyder, Michael

Subjects
Humans, Genetic Diseases, Inborn, NF-kappa B, Transcription Factors, Gene Expression Profiling, Computational Biology, Systems Biology, Protein Binding, Polymorphism, Single Nucleotide, Genetic Variation, Genome-Wide Association Study, regulatory genomics, systems biology, translational bioinformatics, Arthritis, Lung, Human Genome, Atherosclerosis, Biotechnology, Asthma, Genetics, 2.1 Biological and endogenous factors, Aetiology, Inflammatory and immune system, Generic health relevance, Cardiovascular
Abstract

Genome-wide association studies have discovered many genetic loci associated with disease traits, but the functional molecular basis of these associations is often unresolved. Genome-wide regulatory and gene expression profiles measured across individuals and diseases reflect downstream effects of genetic variation and may allow for functional assessment of disease-associated loci. Here, we present a unique approach for systematic integration of genetic disease associations, transcription factor binding among individuals, and gene expression data to assess the functional consequences of variants associated with hundreds of human diseases. In an analysis of genome-wide binding profiles of NFκB, we find that disease-associated SNPs are enriched in NFκB binding regions overall, and specifically for inflammatory-mediated diseases, such as asthma, rheumatoid arthritis, and coronary artery disease. Using genome-wide variation in transcription factor-binding data, we find that NFκB binding is often correlated with disease-associated variants in a genotype-specific and allele-specific manner. Furthermore, we show that this binding variation is often related to expression of nearby genes, which are also found to have altered expression in independent profiling of the variant-associated disease condition. Thus, using this integrative approach, we provide a unique means to assign putative function to many disease-associated SNPs.

Published
2013

39. Phased whole-genome genetic risk in a family quartet using a major allele reference sequence.

Author

Dewey, Frederick E, Chen, Rong, Cordero, Sergio P, Ormond, Kelly E, Caleshu, Colleen, Karczewski, Konrad J, Whirl-Carrillo, Michelle, Wheeler, Matthew T, Dudley, Joel T, Byrnes, Jake K, Cornejo, Omar E, Knowles, Joshua W, Woon, Mark, Sangkuhl, Katrin, Gong, Li, Thorn, Caroline F, Hebert, Joan M, Capriotti, Emidio, David, Sean P, Pavlovic, Aleksandra, West, Anne, Thakuria, Joseph V, Ball, Madeleine P, Zaranek, Alexander W, Rehm, Heidi L, Church, George M, West, John S, Bustamante, Carlos D, Snyder, Michael, Altman, Russ B, Klein, Teri E, Butte, Atul J, and Ashley, Euan A

Subjects
Humans, Thrombophilia, Genetic Predisposition to Disease, Risk Assessment, Pedigree, Sequence Alignment, Sequence Analysis, DNA, DNA Mutational Analysis, Base Sequence, Genotype, Haplotypes, Alleles, Genes, Synthetic, Genome, Human, Reference Standards, Female, Male, Genetic Variation, Genome-Wide Association Study, Biotechnology, Genetics, Human Genome, 2.1 Biological and endogenous factors, Generic health relevance, Developmental Biology
Abstract

Whole-genome sequencing harbors unprecedented potential for characterization of individual and family genetic variation. Here, we develop a novel synthetic human reference sequence that is ethnically concordant and use it for the analysis of genomes from a nuclear family with history of familial thrombophilia. We demonstrate that the use of the major allele reference sequence results in improved genotype accuracy for disease-associated variant loci. We infer recombination sites to the lowest median resolution demonstrated to date (< 1,000 base pairs). We use family inheritance state analysis to control sequencing error and inform family-wide haplotype phasing, allowing quantification of genome-wide compound heterozygosity. We develop a sequence-based methodology for Human Leukocyte Antigen typing that contributes to disease risk prediction. Finally, we advance methods for analysis of disease and pharmacogenomic risk across the coding and non-coding genome that incorporate phased variant data. We show these methods are capable of identifying multigenic risk for inherited thrombophilia and informing the appropriate pharmacological therapy. These ethnicity-specific, family-based approaches to interpretation of genetic variation are emblematic of the next generation of genetic risk assessment using whole-genome sequencing.

Published
2011

40. CHARR efficiently estimates contamination from DNA sequencing data

Author

Lu, Wenhan, primary, Gauthier, Laura D., additional, Poterba, Timothy, additional, Giacopuzzi, Edoardo, additional, Goodrich, Julia K., additional, Stevens, Christine R., additional, King, Daniel, additional, Daly, Mark J., additional, Neale, Benjamin M., additional, and Karczewski, Konrad J., additional

Published
2023
Full Text
View/download PDF

42. A harmonized public resource of deeply sequenced diverse human genomes

Author

Koenig, Zan, Yohannes, Mary T., Nkambule, Lethukuthula L., Zhao, Xuefang, Goodrich, Julia K., Kim, Heesu Ally, Wilson, Michael W., Tiao, Grace, Hao, Stephanie P., Sahakian, Nareh, Chao, Katherine R., Walker, Mark A., Lyu, Yunfei, Rehm, Heidi L., Neale, Benjamin M., Talkowski, Michael E., Daly, Mark J., Brand, Harrison, Karczewski, Konrad J., Atkinson, Elizabeth G., and Martin, Alicia R.

Abstract

Underrepresented populations are often excluded from genomic studies owing in part to a lack of resources supporting their analyses. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high-quality set of 4094 whole genomes from 80 populations in the HGDP and 1kGP with data from the Genome Aggregation Database (gnomAD) and identified over 153 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also show substantial added value from this data set compared with the prior versions of the component resources, typically combined via liftOver and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared with previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality-control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

Published
2024
Full Text
View/download PDF

43. Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative

Author

Butler-Laporte, Guillaume, Povysil, Gundula, Kosmicki, Jack A, Cirulli, Elizabeth T, Drivas, Theodore, Furini, Simone, Saad, Chadi, Schmidt, Axel, Olszewski, Pawel, Korotko, Urszula, Quinodoz, Mathieu, Çelik, Elifnaz, Kundu, Kousik, Walter, Klaudia, Jung, Junghyun, Stockwell, Amy D, Sloofman, Laura G, Jordan, Daniel M, Thompson, Ryan C, Del Valle, Diane, Simons, Nicole, Cheng, Esther, Sebra, Robert, Schadt, Eric E, Kim-Schulze, Seunghee, Gnjatic, Sacha, Merad, Miriam, Buxbaum, Joseph D, Beckmann, Noam D, Charney, Alexander W, Przychodzen, Bartlomiej, Chang, Timothy, Pottinger, Tess D, Shang, Ning, Brand, Fabian, Fava, Francesca, Mari, Francesca, Chwialkowska, Karolina, Niemira, Magdalena, Pula, Szymon, Baillie, J Kenneth, Stuckey, Alex, Salas, Antonio, Bello, Xabier, Pardo-Seco, Jacobo, Gómez-Carballa, Alberto, Rivero-Calle, Irene, Martinón-Torres, Federico, Ganna, Andrea, Karczewski, Konrad J, Veerapen, Kumar, Bourgey, Mathieu, Bourque, Guillaume, Eveleigh, Robert Jm, Forgetta, Vincenzo, Morrison, David, Langlais, David, Lathrop, Mark, Mooser, Vincent, Nakanishi, Tomoko, Frithiof, Robert, Hultström, Michael, Lipcsey, Miklos, Marincevic-Zuniga, Yanara, Nordlund, Jessica, Schiabor Barrett, Kelly M, Lee, William, Bolze, Alexandre, White, Simon, Riffle, Stephen, Tanudjaja, Francisco, Sandoval, Efren, Neveux, Iva, Dabe, Shaun, Casadei, Nicolas, Motameny, Susanne, Alaamery, Manal, Massadeh, Salam, Aljawini, Nora, Almutairi, Mansour S, Arabi, Yaseen M, Alqahtani, Saleh A, Al Harthi, Fawz S, Almutairi, Amal, Alqubaishi, Fatima, Alotaibi, Sarah, Binowayn, Albandari, Alsolm, Ebtehal A, El Bardisy, Hadeel, Fawzy, Mohammad, Cai, Fang, Soranzo, Nicole, Butterworth, Adam, COVID-19 Host Genetics Initiative, DeCOI Host Genetics Group, GEN-COVID Multicenter Study (Italy), Mount Sinai Clinical Intelligence Center, GEN-COVID Consortium (Spain), GenOMICC Consortium, Japan COVID-19 Task Force, Regeneron Genetics Center, Geschwind, Daniel H, Arteaga, Stephanie, Stephens, Alexis, Butte, Manish J, Boutros, Paul C, Yamaguchi, Takafumi N, Tao, Shu, Eng, Stefan, Sanders, Timothy, Tung, Paul J, Broudy, Michael E, Pan, Yu, Gonzalez, Alfredo, Chavan, Nikhil, Johnson, Ruth, Pasaniuc, Bogdan, Yaspan, Brian, Smieszek, Sandra, Rivolta, Carlo, Bibert, Stephanie, Bochud, Pierre-Yves, Dabrowski, Maciej, Zawadzki, Pawel, Sypniewski, Mateusz, Kaja, Elżbieta, Chariyavilaskul, Pajaree, Nilaratanakul, Voraphoj, Hirankarn, Nattiya, Shotelersuk, Vorasuk, Pongpanich, Monnat, Phokaew, Chureerat, Chetruengchai, Wanna, Tokunaga, Katsushi, Sugiyama, Masaya, Kawai, Yosuke, Hasegawa, Takanori, Naito, Tatsuhiko, Namkoong, Ho, Edahiro, Ryuya, Kimura, Akinori, Ogawa, Seishi, Kanai, Takanori, Fukunaga, Koichi, Okada, Yukinori, Imoto, Seiya, Miyano, Satoru, Mangul, Serghei, Abedalthagafi, Malak S, Zeberg, Hugo, Grzymski, Joseph J, Washington, Nicole L, Ossowski, Stephan, Ludwig, Kerstin U, Schulte, Eva C, Riess, Olaf, Moniuszko, Marcin, Kwasniewski, Miroslaw, Mbarek, Hamdi, Ismail, Said I, Verma, Anurag, Goldstein, David B, Kiryluk, Krzysztof, Renieri, Alessandra, Ferreira, Manuel AR, Richards, J Brent, Butler-Laporte, Guillaume [0000-0001-5388-0396], Povysil, Gundula [0000-0003-4625-5909], Kosmicki, Jack A [0000-0003-1252-6192], Cirulli, Elizabeth T [0000-0001-7808-2809], Drivas, Theodore [0000-0002-8717-0111], Saad, Chadi [0000-0001-6963-9126], Olszewski, Pawel [0000-0003-1010-8843], Korotko, Urszula [0000-0002-1779-8368], Quinodoz, Mathieu [0000-0002-9841-4433], Çelik, Elifnaz [0000-0002-0324-5228], Kundu, Kousik [0000-0002-1019-8351], Walter, Klaudia [0000-0003-4448-0301], Sloofman, Laura G [0000-0001-7628-4378], Jordan, Daniel M [0000-0002-5318-8225], Thompson, Ryan C [0000-0002-0450-8181], Del Valle, Diane [0000-0001-6983-5362], Simons, Nicole [0000-0002-3952-1458], Chang, Timothy [0000-0002-9225-9874], Brand, Fabian [0000-0003-1885-7021], Chwialkowska, Karolina [0000-0001-8053-8959], Niemira, Magdalena [0000-0002-0701-4961], Pula, Szymon [0000-0002-5684-5358], Stuckey, Alex [0000-0001-8636-737X], Bello, Xabier [0000-0002-4990-8496], Karczewski, Konrad J [0000-0003-2878-4671], Bourgey, Mathieu [0000-0002-8432-834X], Bourque, Guillaume [0000-0002-3933-9656], Eveleigh, Robert Jm [0000-0002-4147-382X], Morrison, David [0000-0001-8380-3615], Langlais, David [0000-0003-4429-0110], Mooser, Vincent [0000-0002-8632-0448], Nakanishi, Tomoko [0000-0001-9510-5646], Frithiof, Robert [0000-0003-2278-7951], Hultström, Michael [0000-0003-4675-1099], Lipcsey, Miklos [0000-0002-1976-4129], Nordlund, Jessica [0000-0001-8699-9959], Schiabor Barrett, Kelly M [0000-0001-6194-787X], Bolze, Alexandre [0000-0001-7399-2766], White, Simon [0000-0001-6375-2363], Dabe, Shaun [0000-0002-2494-962X], Casadei, Nicolas [0000-0003-2209-0580], Motameny, Susanne [0000-0003-1186-1108], Massadeh, Salam [0000-0001-9193-0008], Almutairi, Mansour S [0000-0003-2736-8991], Arabi, Yaseen M [0000-0001-5735-6241], Fawzy, Mohammad [0000-0002-1318-9979], Arteaga, Stephanie [0000-0003-1441-8849], Stephens, Alexis [0000-0002-5979-6838], Yamaguchi, Takafumi N [0000-0003-1082-3871], Eng, Stefan [0000-0002-5245-6507], Gonzalez, Alfredo [0000-0001-8963-3135], Johnson, Ruth [0000-0002-1929-0998], Yaspan, Brian [0000-0002-3787-2510], Smieszek, Sandra [0000-0002-8006-0454], Rivolta, Carlo [0000-0002-0733-9950], Bochud, Pierre-Yves [0000-0002-2208-4757], Dabrowski, Maciej [0000-0003-4150-3985], Zawadzki, Pawel [0000-0002-9032-2315], Kaja, Elżbieta [0000-0003-1277-6140], Chariyavilaskul, Pajaree [0000-0003-1096-6020], Nilaratanakul, Voraphoj [0000-0002-3964-5477], Hirankarn, Nattiya [0000-0003-2224-6856], Shotelersuk, Vorasuk [0000-0002-1856-0589], Pongpanich, Monnat [0000-0003-3228-3351], Phokaew, Chureerat [0000-0002-4246-2604], Chetruengchai, Wanna [0000-0003-2495-6595], Sugiyama, Masaya [0000-0002-9084-7197], Kawai, Yosuke [0000-0003-0666-1224], Hasegawa, Takanori [0000-0001-7251-9950], Namkoong, Ho [0000-0001-6181-4284], Miyano, Satoru [0000-0002-1753-6616], Mangul, Serghei [0000-0003-4770-3443], Zeberg, Hugo [0000-0001-7118-1249], Grzymski, Joseph J [0000-0003-2646-8958], Ossowski, Stephan [0000-0002-7416-9568], Ludwig, Kerstin U [0000-0002-8541-2519], Schulte, Eva C [0000-0003-3105-5672], Verma, Anurag [0000-0002-5063-9107], Goldstein, David B [0000-0001-7627-0259], Kiryluk, Krzysztof [0000-0002-5047-6715], Renieri, Alessandra [0000-0002-0846-9220], Richards, J Brent [0000-0002-3746-9086], and Apollo - University of Cambridge Repository

Subjects
Medicine and health sciences, Research and analysis methods, Physical sciences, Toll-Like Receptor 7, Biology and life sciences, SARS-CoV-2, FOS: Physical sciences, Humans, COVID-19, Exome, Genetic Predisposition to Disease, Genome-Wide Association Study, Research Article
Abstract

Acknowledgements: We thank the patients who volunteered to all participating cohorts, and the researchers and clinicians who enrolled them into the respective studies. A full list of acknowledgments can be found in S1 and S2 Tables., Funder: Lady Davis Institute of the Jewish General Hospital, Funder: Canadian Foundation for Innovation, Funder: NIH Foundation, Funder: Fonds de Recherche Québec Santé (FRQS), Funder: McGill Interdisciplinary Initiative in Infection and Immunity (MI4), Funder: Jewish General Hospital Foundation, Funder: Génome Québec; funder-id: http://dx.doi.org/10.13039/100013062, Funder: Public Health Agency of Canada, Funder: McGill University; funder-id: http://dx.doi.org/10.13039/100008582, Funder: Calcul Québec and Compute Canada, Funder: Compute Canada; funder-id: http://dx.doi.org/10.13039/100013020, Funder: Stiftung Universitätsmedizin Essen; funder-id: http://dx.doi.org/10.13039/501100010380, Funder: State of Saarland, Funder: Dr. Rolf M. Schwiete Foundation, Funder: Munich Clinician Scientist Programm, Funder: Netzwerk-Universitaetsmedizin-COVIM; Grant(s): NaFoUniMedCovid19, FKZ: 01KX2021, Funder: Federal Ministry of Education and Research, Funder: Leenaards Foundation, Funder: Santos-Suarez Foundation, Funder: Carigest, Funder: Istituto Buddista Italiano Soka Gakkai; Grant(s): 2020-2016_RIC_3 via project “PAT-COVID: Host genetics and pathogenetic mechanisms of COVID-19”, Funder: e-ASIA Joint Research Program (National Science and Technology Development Agency), Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Published
2022

44. The impact of rare variation on gene expression across tissues

Author

Li, Xin, Kim, Yungil, Tsang, Emily K., Davis, Joe R., Damani, Farhan N., Chiang, Colby, Hess, Gaelen T., Zappala, Zachary, Strober, Benjamin J., Scott, Alexandra J., Li, Amy, Ganna, Andrea, Bassik, Michael C., Merker, Jason D., Aguet, Franois, Ardlie, Kristin G., Cummings, Beryl B., Gelfand, Ellen T., Getz, Gad, Hadley, Kane, Handsaker, Robert E., Huang, Katherine H., Kashin, Seva, Karczewski, Konrad J., Lek, Monkol, Li, Xiao, MacArthur, Daniel G., Nedzel, Jared L., Nguyen, Duyen T., Noble, Michael S., Segr, Ayellet V., Trowbridge, Casandra A., Tukiainen, Taru, Abell, Nathan S., Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K., Brown, Andrew, Brown, Christopher D., Castel, Stephane E., Chen, Lin S., Conrad, Donald F., Cox, Nancy J., Delaneau, Olivier, Dermitzakis, Emmanouil T., Engelhardt, Barbara E., Eskin, Eleazar, Ferreira, Pedro G., Frsard, Laure, Gamazon, Eric R., Garrido-Martn, Diego, Gewirtz, Ariel D.H., Gliner, Genna, Gloudemans, Michael J., Guigo, Roderic, Hall, Ira M., Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I., McDowell, Ian C., Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B., Muoz-Aguirre, Manuel, Ndungu, Anne W., Nicolae, Dan L., Nobel, Andrew B., Oliva, Meritxell, Ongen, Halit, Palowitch, John J., Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J., Peterson, Christine B., Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Shabalin, Andrey A., Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E., Sul, Jae Hoon, Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A., Xi, Hualin S., Yeger-Lotem, Esti, Zaugg, Judith B., Zhou, Yi-Hui, Akey, Joshua M., Bates, Daniel, Chan, Joanne, Claussnitzer, Melina, Demanelis, Kathryn, Diegel, Morgan, Doherty, Jennifer A., Feinberg, Andrew P., Fernando, Marian S., Halow, Jessica, Hansen, Kasper D., Haugen, Eric, Hickey, Peter F., Hou, Lei, Jasmine, Farzana, Jian, Ruiqi, Jiang, Lihua, Johnson, Audra, Kaul, Rajinder, Kellis, Manolis, Kibriya, Muhammad G., Lee, Kristen, Billy Li, Jin, Li, Qin, Lin, Jessica, Lin, Shin, Linder, Sandra, Linke, Caroline, Liu, Yaping, Maurano, Matthew T., Molinie, Benoit, Nelson, Jemma, Neri, Fidencio J., Park, Yongjin, Pierce, Brandon L., Rinaldi, Nicola J., Rizzardi, Lindsay F., Sandstrom, Richard, Skol, Andrew, Smith, Kevin S., Snyder, Michael P., Stamatoyannopoulos, John, Tang, Hua, Wang, Li, Wang, Meng, Van Wittenberghe, Nicholas, Wu, Fan, Zhang, Rui, Nierras, Concepcion R., Branton, Philip A., Carithers, Latarsha J., Guan, Ping, Moore, Helen M., Rao, Abhi, Vaught, Jimmie B., Gould, Sarah E., Lockart, Nicole C., Martin, Casey, Struewing, Jeffery P., Volpi, Simona, Addington, Anjene M., Koester, Susan E., Little, A. Roger, Brigham, Lori E., Hasz, Richard, Hunter, Marcus, Johns, Christopher, Johnson, Mark, Kopen, Gene, Leinweber, William F., Lonsdale, John T., McDonald, Alisa, Mestichelli, Bernadette, Myer, Kevin, Roe, Brian, Salvatore, Michael, Shad, Saboor, Thomas, Jeffrey A., Walters, Gary, Washington, Michael, Wheeler, Joseph, Bridge, Jason, Foster, Barbara A., Gillard, Bryan M., Karasik, Ellen, Kumar, Rachna, Miklos, Mark, Moser, Michael T., Jewell, Scott D., Montroy, Robert G., Rohrer, Daniel C., Valley, Dana R., Davis, David A., Mash, Deborah C., Undale, Anita H., Smith, Anna M., Tabor, David E., Roche, Nancy V., McLean, Jeffrey A., Vatanian, Negin, Robinson, Karna L., Sobin, Leslie, Barcus, Mary E., Valentino, Kimberly M., Qi, Liqun, Hunter, Steven, Hariharan, Pushpa, Singh, Shilpi, Um, Ki Sung, Matose, Takunda, Tomaszewski, Maria M., Barker, Laura K., Mosavel, Maghboeba, Siminoff, Laura A., Traino, Heather M., Flicek, Paul, Juettemann, Thomas, Ruffier, Magali, Sheppard, Dan, Taylor, Kieron, Trevanion, Stephen J., Zerbino, Daniel R., Craft, Brian, Goldman, Mary, Haeussler, Maximilian, Kent, W. James, Lee, Christopher M., Paten, Benedict, Rosenbloom, Kate R., Vivian, John, and Zhu, Jingchun

Subjects
Disease susceptibility -- Genetic aspects, Genetic variation -- Observations, Gene expression -- Observations, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): Xin Li [1]; Yungil Kim [2]; Emily K. Tsang [1, 3]; Joe R. Davis [1, 4]; Farhan N. Damani [2]; Colby Chiang [5]; Gaelen T. Hess [4]; Zachary Zappala [...]

Published
2017
Full Text
View/download PDF

45. Dynamic landscape and regulation of RNA editing in mammals

Author

Tan, Meng How, Li, Qin, Shanmugam, Raghuvaran, Piskol, Robert, Kohler, Jennefer, Young, Amy N., Liu, Kaiwen Ivy, Zhang, Rui, Ramaswami, Gokul, Ariyoshi, Kentaro, Gupte, Ankita, Keegan, Liam P., George, Cyril X., Ramu, Avinash, Huang, Ni, Pollina, Elizabeth A., Leeman, Dena S., Rustighi, Alessandra, Goh, Y. P. Sharon, Aguet, Franois, Ardlie, Kristin G., Cummings, Beryl B., Gelfand, Ellen T., Getz, Gad, Hadley, Kane, Handsaker, Robert E., Huang, Katherine H., Kashin, Seva, Karczewski, Konrad J., Lek, Monkol, Li, Xiao, MacArthur, Daniel G., Nedzel, Jared L., Nguyen, Duyen T., Noble, Michael S., Segr, Ayellet V., Trowbridge, Casandra A., Tukiainen, Taru, Abell, Nathan S., Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K., Brown, Andrew, Brown, Christopher D., Castel, Stephane E., Chen, Lin S., Chiang, Colby, Conrad, Donald F., Cox, Nancy J., Damani, Farhan N., Davis, Joe R., Delaneau, Olivier, Dermitzakis, Emmanouil T., Engelhardt, Barbara E., Eskin, Eleazar, Ferreira, Pedro G., Frsard, Laure, Gamazon, Eric R., Garrido-Martn, Diego, Gewirtz, Ariel D. H., Gliner, Genna, Gloudemans, Michael J., Guigo, Roderic, Hall, Ira M., Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I., McDowell, Ian C., Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B., Muoz-Aguirre, Manuel, Ndungu, Anne W., Nicolae, Dan L., Nobel, Andrew B., Oliva, Meritxell, Ongen, Halit, Palowitch, John J., Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J., Peterson, Christine B., Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J., Shabalin, Andrey A., Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E., Strober, Benjamin J., Sul, Jae Hoon, Tsang, Emily K., Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A., Xi, Hualin S., Yeger-Lotem, Esti, Zappala, Zachary, Zaugg, Judith B., Zhou, Yi-Hui, Akey, Joshua M., Bates, Daniel, Chan, Joanne, Claussnitzer, Melina, Demanelis, Kathryn, Diegel, Morgan, Doherty, Jennifer A., Feinberg, Andrew P., Fernando, Marian S., Halow, Jessica, Hansen, Kasper D., Haugen, Eric, Hickey, Peter F., Hou, Lei, Jasmine, Farzana, Jian, Ruiqi, Jiang, Lihua, Johnson, Audra, Kaul, Rajinder, Kellis, Manolis, Kibriya, Muhammad G., Lee, Kristen, Li, Jin Billy, Lin, Jessica, Lin, Shin, Linder, Sandra, Linke, Caroline, Liu, Yaping, Maurano, Matthew T., Molinie, Benoit, Nelson, Jemma, Neri, Fidencio J., Park, Yongjin, Pierce, Brandon L., Rinaldi, Nicola J., Rizzardi, Lindsay F., Sandstrom, Richard, Skol, Andrew, Smith, Kevin S., Snyder, Michael P., Stamatoyannopoulos, John, Tang, Hua, Wang, Li, Wang, Meng, Van Wittenberghe, Nicholas, Wu, Fan, Nierras, Concepcion R., Branton, Philip A., Carithers, Latarsha J., Guan, Ping, Moore, Helen M., Rao, Abhi, Vaught, Jimmie B., Gould, Sarah E., Lockart, Nicole C., Martin, Casey, Struewing, Jeffery P., Volpi, Simona, Addington, Anjene M., Koester, Susan E., Little, A. Roger, Brigham, Lori E., Hasz, Richard, Hunter, Marcus, Johns, Christopher, Johnson, Mark, Kopen, Gene, Leinweber, William F., Lonsdale, John T., McDonald, Alisa, Mestichelli, Bernadette, Myer, Kevin, Roe, Brian, Salvatore, Michael, Shad, Saboor, Thomas, Jeffrey A., Walters, Gary, Washington, Michael, Wheeler, Joseph, Bridge, Jason, Foster, Barbara A., Gillard, Bryan M., Karasik, Ellen, Kumar, Rachna, Miklos, Mark, Moser, Michael T., Jewell, Scott D., Montroy, Robert G., Rohrer, Daniel C., Valley, Dana R., Davis, David A., Mash, Deborah C., Undale, Anita H., Smith, Anna M., Tabor, David E., Roche, Nancy V., McLean, Jeffrey A., Vatanian, Negin, Robinson, Karna L., Sobin, Leslie, Barcus, Mary E., Valentino, Kimberly M., Qi, Liqun, Hunter, Steven, Hariharan, Pushpa, Singh, Shilpi, Um, Ki Sung, Matose, Takunda, Tomaszewski, Maria M., Barker, Laura K., Mosavel, Maghboeba, Siminoff, Laura A., Traino, Heather M., Flicek, Paul, Juettemann, Thomas, Ruffier, Magali, Sheppard, Dan, Taylor, Kieron, Trevanion, Stephen J., Zerbino, Daniel R., Craft, Brian, Goldman, Mary, Haeussler, Maximilian, Kent, W. James, Lee, Christopher M., Paten, Benedict, Rosenbloom, Kate R., Vivian, John, Zhu, Jingchun, Chawla, Ajay, Del Sal, Giannino, Peltz, Gary, Brunet, Anne, Samuel, Charles E., OConnell, Mary A., Walkley, Carl R., and Nishikura, Kazuko

Subjects
Genetic research, Mammals -- Genetic aspects, RNA processing -- Research, Genetic regulation, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): Meng How Tan (corresponding author) [1, 2, 3]; Qin Li [1]; Raghuvaran Shanmugam [2, 3]; Robert Piskol [1]; Jennefer Kohler [1]; Amy N. Young [1]; Kaiwen Ivy Liu [3]; [...]

Published
2017
Full Text
View/download PDF

46. Landscape of X chromosome inactivation across human tissues

Author

Tukiainen, Taru, Villani, Alexandra-Chlo, Yen, Angela, Rivas, Manuel A., Marshall, Jamie L., Satija, Rahul, Aguirre, Matt, Gauthier, Laura, Fleharty, Mark, Kirby, Andrew, Cummings, Beryl B., Castel, Stephane E., Karczewski, Konrad J., Aguet, Franois, Byrnes, Andrea, Ardlie, Kristin G., Gelfand, Ellen T., Getz, Gad, Hadley, Kane, Handsaker, Robert E., Huang, Katherine H., Kashin, Seva, Lek, Monkol, Li, Xiao, MacArthur, Daniel G., Nedzel, Jared L., Nguyen, Duyen T., Noble, Michael S., Segr, Ayellet V., Trowbridge, Casandra A., Abell, Nathan S., Balliu, Brunilda, Barshir, Ruth, Basha, Omer, Battle, Alexis, Bogu, Gireesh K., Brown, Andrew, Brown, Christopher D., Chen, Lin S., Chiang, Colby, Conrad, Donald F., Cox, Nancy J., Damani, Farhan N., Davis, Joe R., Delaneau, Olivier, Dermitzakis, Emmanouil T., Engelhardt, Barbara E., Eskin, Eleazar, Ferreira, Pedro G., Frsard, Laure, Gamazon, Eric R., Garrido-Martn, Diego, Gewirtz, Ariel D. H., Gliner, Genna, Gloudemans, Michael J., Guigo, Roderic, Hall, Ira M., Han, Buhm, He, Yuan, Hormozdiari, Farhad, Howald, Cedric, Kyung Im, Hae, Jo, Brian, Yong Kang, Eun, Kim, Yungil, Kim-Hellmuth, Sarah, Lappalainen, Tuuli, Li, Gen, Li, Xin, Liu, Boxiang, Mangul, Serghei, McCarthy, Mark I., McDowell, Ian C., Mohammadi, Pejman, Monlong, Jean, Montgomery, Stephen B., Muoz-Aguirre, Manuel, Ndungu, Anne W., Nicolae, Dan L., Nobel, Andrew B., Oliva, Meritxell, Ongen, Halit, Palowitch, John J., Panousis, Nikolaos, Papasaikas, Panagiotis, Park, YoSon, Parsana, Princy, Payne, Anthony J., Peterson, Christine B., Quan, Jie, Reverter, Ferran, Sabatti, Chiara, Saha, Ashis, Sammeth, Michael, Scott, Alexandra J., Shabalin, Andrey A., Sodaei, Reza, Stephens, Matthew, Stranger, Barbara E., Strober, Benjamin J., Sul, Jae Hoon, Tsang, Emily K., Urbut, Sarah, van de Bunt, Martijn, Wang, Gao, Wen, Xiaoquan, Wright, Fred A., Xi, Hualin S., Yeger-Lotem, Esti, Zappala, Zachary, Zaugg, Judith B., Zhou, Yi-Hui, Akey, Joshua M., Bates, Daniel, Chan, Joanne, Claussnitzer, Melina, Demanelis, Kathryn, Diegel, Morgan, Doherty, Jennifer A., Feinberg, Andrew P., Fernando, Marian S., Halow, Jessica, Hansen, Kasper D., Haugen, Eric, Hickey, Peter F., Hou, Lei, Jasmine, Farzana, Jian, Ruiqi, Jiang, Lihua, Johnson, Audra, Kaul, Rajinder, Kellis, Manolis, Kibriya, Muhammad G., Lee, Kristen, Li, Jin Billy, Li, Qin, Lin, Jessica, Lin, Shin, Linder, Sandra, Linke, Caroline, Liu, Yaping, Maurano, Matthew T., Molinie, Benoit, Nelson, Jemma, Neri, Fidencio J., Park, Yongjin, Pierce, Brandon L., Rinaldi, Nicola J., Rizzardi, Lindsay F., Sandstrom, Richard, Skol, Andrew, Smith, Kevin S., Snyder, Michael P., Stamatoyannopoulos, John, Tang, Hua, Wang, Li, Wang, Meng, Van Wittenberghe, Nicholas, Wu, Fan, Zhang, Rui, Nierras, Concepcion R., Branton, Philip A., Carithers, Latarsha J., Guan, Ping, Moore, Helen M., Rao, Abhi, Vaught, Jimmie B., Gould, Sarah E., Lockart, Nicole C., Martin, Casey, Struewing, Jeffery P., Volpi, Simona, Addington, Anjene M., Koester, Susan E., Little, A. Roger, Brigham, Lori E., Hasz, Richard, Hunter, Marcus, Johns, Christopher, Johnson, Mark, Kopen, Gene, Leinweber, William F., Lonsdale, John T., McDonald, Alisa, Mestichelli, Bernadette, Myer, Kevin, Roe, Brian, Salvatore, Michael, Shad, Saboor, Thomas, Jeffrey A., Walters, Gary, Washington, Michael, Wheeler, Joseph, Bridge, Jason, Foster, Barbara A., Gillard, Bryan M., Karasik, Ellen, Kumar, Rachna, Miklos, Mark, Moser, Michael T., Jewell, Scott D., Montroy, Robert G., Rohrer, Daniel C., Valley, Dana R., Davis, David A., Mash, Deborah C., Undale, Anita H., Smith, Anna M., Tabor, David E., Roche, Nancy V., McLean, Jeffrey A., Vatanian, Negin, Robinson, Karna L., Sobin, Leslie, Barcus, Mary E., Valentino, Kimberly M., Qi, Liqun, Hunter, Steven, Hariharan, Pushpa, Singh, Shilpi, Um, Ki Sung, Matose, Takunda, Tomaszewski, Maria M., Barker, Laura K., Mosavel, Maghboeba, Siminoff, Laura A., Traino, Heather M., Flicek, Paul, Juettemann, Thomas, Ruffier, Magali, Sheppard, Dan, Taylor, Kieron, Trevanion, Stephen J., Zerbino, Daniel R., Craft, Brian, Goldman, Mary, Haeussler, Maximilian, Kent, W. James, Lee, Christopher M., Paten, Benedict, Rosenbloom, Kate R., Vivian, John, Zhu, Jingchun, Regev, Aviv, and Hacohen, Nir

Subjects
Chromosomes -- Physiological aspects, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): Taru Tukiainen (corresponding author) [1, 2]; Alexandra-Chlo Villani [2, 3]; Angela Yen [2, 4]; Manuel A. Rivas [1, 2, 5]; Jamie L. Marshall [1, 2]; Rahul Satija [2, 6, [...]

Published
2017
Full Text
View/download PDF

48. Health and population effects of rare gene knockouts in adult humans with related parents

Author

Narasimhan, Vagheesh M., Hunt, Karen A., Mason, Dan, Baker, Christopher L., Karczewski, Konrad J., Barnes, Michael R., Barnett, Anthony H., Bates, Chris, Bellary, Srikanth, Bockett, Nicholas A., Giorda, Kristina, Griffiths, Christopher J., Hemingway, Harry, Jia, Zhilong, Kelly, M. Ann, Khawaja, Hajrah A., Lek, Monkol, McCarthy, Shane, McEachan, Rosie, O'Donnell-Luria, Anne, Paigen, Kenneth, Parisinos, Constantinos A., Sheridan, Eamonn, Southgate, Laura, Tee, Louise, Thomas, Mark, Xue, Yali, Schnall-Levin, Michael, Petkov, Petko M., Tyler-Smith, Chris, Maher, Eamonn R., Trembath, Richard C., MacArthur, Daniel G., Wright, John, Durbin, Richard, and van Heel, David A.

Published
2016

49. Inferring compound heterozygosity from large-scale exome sequencing data

Author

Guo, Michael H., Francioli, Laurent C., Stenton, Sarah L., Goodrich, Julia K., Watts, Nicholas A., Singer-Berk, Moriel, Groopman, Emily, Darnowsky, Philip W., Solomonson, Matthew, Baxter, Samantha, Tiao, Grace, Neale, Benjamin M., Hirschhorn, Joel N., Rehm, Heidi L., Daly, Mark J., O’Donnell-Luria, Anne, Karczewski, Konrad J., MacArthur, Daniel G., and Samocha, Kaitlin E.

Subjects
Article
Abstract

Severe recessive diseases arise when both the maternal and the paternal copies of a gene carry, or are impacted by, a damaging genetic variant in the affected individual. When a patient carries two different potentially causal variants, accurate diagnosis requires determining that these two variants occur on different copies of the chromosome (i.e., are in trans ) rather than on the same copy (i.e., in cis ). However, current approaches for determining phase, beyond parental testing, are limited in clinical settings. We developed a strategy for inferring phase for rare variant pairs within genes, leveraging haplotype patterns observed in exome sequencing data from the Genome Aggregation Database (gnomAD v2, n=125,748). When applied to trio data where phase is known, our approach estimates phase with high accuracy, even for very rare variants (frequency

Published
2023

50. A harmonized public resource of deeply sequenced diverse human genomes

Author

Koenig, Zan, Yohannes, Mary T., Nkambule, Lethukuthula L., Goodrich, Julia K., Kim, Heesu Ally, Zhao, Xuefang, Wilson, Michael W., Tiao, Grace, Hao, Stephanie P., Sahakian, Nareh, Chao, Katherine R., Talkowski, Michael E., Daly, Mark J., Brand, Harrison, Karczewski, Konrad J., Atkinson, Elizabeth G., and Martin, Alicia R.

Subjects
Article
Abstract

Underrepresented populations are often excluded from genomic studies due in part to a lack of resources supporting their analysis. The 1000 Genomes Project (1kGP) and Human Genome Diversity Project (HGDP), which have recently been sequenced to high coverage, are valuable genomic resources because of the global diversity they capture and their open data sharing policies. Here, we harmonized a high quality set of 4,096 whole genomes from HGDP and 1kGP with data from gnomAD and identified over 155 million high-quality SNVs, indels, and SVs. We performed a detailed ancestry analysis of this cohort, characterizing population structure and patterns of admixture across populations, analyzing site frequency spectra, and measuring variant counts at global and subcontinental levels. We also demonstrate substantial added value from this dataset compared to the prior versions of the component resources, typically combined via liftover and variant intersection; for example, we catalog millions of new genetic variants, mostly rare, compared to previous releases. In addition to unrestricted individual-level public release, we provide detailed tutorials for conducting many of the most common quality control steps and analyses with these data in a scalable cloud-computing environment and publicly release this new phased joint callset for use as a haplotype resource in phasing and imputation pipelines. This jointly called reference panel will serve as a key resource to support research of diverse ancestry populations.

Published
2023

Catalog

Books, media, physical & digital resources
See catalog results