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1. Centers for Mendelian Genomics: A decade of facilitating gene discovery

Author

Samantha M. Baxter, Jennifer E. Posey, Nicole J. Lake, Nara Sobreira, Jessica X. Chong, Steven Buyske, Elizabeth E. Blue, Lisa H. Chadwick, Zeynep H. Coban-Akdemir, Kimberly F. Doheny, Colleen P. Davis, Monkol Lek, Christopher Wellington, Shalini N. Jhangiani, Mark Gerstein, Richard A. Gibbs, Richard P. Lifton, Daniel G. MacArthur, Tara C. Matise, James R. Lupski, David Valle, Michael J. Bamshad, Ada Hamosh, Shrikant Mane, Deborah A. Nickerson, Heidi L. Rehm, Anne O’Donnell-Luria, Marcia Adams, François Aguet, Gulsen Akay, Peter Anderson, Corina Antonescu, Harindra M. Arachchi, Mehmed M. Atik, Christina A. Austin-Tse, Larry Babb, Tamara J. Bacus, Vahid Bahrambeigi, Suganthi Balasubramanian, Yavuz Bayram, Arthur L. Beaudet, Christine R. Beck, John W. Belmont, Jennifer E. Below, Kaya Bilguvar, Corinne D. Boehm, Eric Boerwinkle, Philip M. Boone, Sara J. Bowne, Harrison Brand, Kati J. Buckingham, Alicia B. Byrne, Daniel Calame, Ian M. Campbell, Xiaolong Cao, Claudia Carvalho, Varuna Chander, Jaime Chang, Katherine R. Chao, Ivan K. Chinn, Declan Clarke, Ryan L. Collins, Beryl Cummings, Zain Dardas, Moez Dawood, Kayla Delano, Stephanie P. DiTroia, Harshavardhan Doddapaneni, Haowei Du, Renqian Du, Ruizhi Duan, Mohammad Eldomery, Christine M. Eng, Eleina England, Emily Evangelista, Selin Everett, Jawid Fatih, Adam Felsenfeld, Laurent C. Francioli, Christian D. Frazar, Jack Fu, Emmanuel Gamarra, Tomasz Gambin, Weiniu Gan, Mira Gandhi, Vijay S. Ganesh, Kiran V. Garimella, Laura D. Gauthier, Danielle Giroux, Claudia Gonzaga-Jauregui, Julia K. Goodrich, William W. Gordon, Sean Griffith, Christopher M. Grochowski, Shen Gu, Sanna Gudmundsson, Stacey J. Hall, Adam Hansen, Tamar Harel, Arif O. Harmanci, Isabella Herman, Kurt Hetrick, Hadia Hijazi, Martha Horike-Pyne, Elvin Hsu, Jianhong Hu, Yongqing Huang, Jameson R. Hurless, Steve Jahl, Gail P. Jarvik, Yunyun Jiang, Eric Johanson, Angad Jolly, Ender Karaca, Michael Khayat, James Knight, J. Thomas Kolar, Sushant Kumar, Seema Lalani, Kristen M. Laricchia, Kathryn E. Larkin, Suzanne M. Leal, Gabrielle Lemire, Richard A. Lewis, He Li, Hua Ling, Rachel B. Lipson, Pengfei Liu, Alysia Kern Lovgren, Francesc López-Giráldez, Melissa P. MacMillan, Brian E. Mangilog, Stacy Mano, Dana Marafi, Beth Marosy, Jamie L. Marshall, Renan Martin, Colby T. Marvin, Michelle Mawhinney, Sean McGee, Daniel J. McGoldrick, Michelle Mehaffey, Betselote Mekonnen, Xiaolu Meng, Tadahiro Mitani, Christina Y. Miyake, David Mohr, Shaine Morris, Thomas E. Mullen, David R. Murdock, Mullai Murugan, Donna M. Muzny, Ben Myers, Juanita Neira, Kevin K. Nguyen, Patrick M. Nielsen, Natalie Nudelman, Emily O’Heir, Melanie C. O’Leary, Chrissie Ongaco, Jordan Orange, Ikeoluwa A. Osei-Owusu, Ingrid S. Paine, Lynn S. Pais, Justin Paschall, Karynne Patterson, Davut Pehlivan, Benjamin Pelle, Samantha Penney, Jorge Perez de Acha Chavez, Emma Pierce-Hoffman, Cecilia M. Poli, Jaya Punetha, Aparna Radhakrishnan, Matthew A. Richardson, Eliete Rodrigues, Gwendolin T. Roote, Jill A. Rosenfeld, Erica L. Ryke, Aniko Sabo, Alice Sanchez, Isabelle Schrauwen, Daryl A. Scott, Fritz Sedlazeck, Jillian Serrano, Chad A. Shaw, Tameka Shelford, Kathryn M. Shively, Moriel Singer-Berk, Joshua D. Smith, Hana Snow, Grace Snyder, Matthew Solomonson, Rachel G. Son, Xiaofei Song, Pawel Stankiewicz, Taylorlyn Stephan, V. Reid Sutton, Abigail Sveden, Diana Cornejo Sánchez, Monica Tackett, Michael Talkowski, Machiko S. Threlkeld, Grace Tiao, Miriam S. Udler, Laura Vail, Zaheer Valivullah, Elise Valkanas, Grace E. VanNoy, Qingbo S. Wang, Gao Wang, Lu Wang, Michael F. Wangler, Nicholas A. Watts, Ben Weisburd, Jeffrey M. Weiss, Marsha M. Wheeler, Janson J. White, Clara E. Williamson, Michael W. Wilson, Wojciech Wiszniewski, Marjorie A. Withers, Dane Witmer, Lauren Witzgall, Elizabeth Wohler, Monica H. Wojcik, Isaac Wong, Jordan C. Wood, Nan Wu, Jinchuan Xing, Yaping Yang, Qian Yi, Bo Yuan, Jordan E. Zeiger, Chaofan Zhang, Peng Zhang, Yan Zhang, Xiaohong Zhang, Yeting Zhang, Shifa Zhang, Huda Zoghbi, and Igna van den Veyver

Subjects
Phenotype, Exome Sequencing, Humans, Exome, Genomics, Article, Genetic Association Studies, Genetics (clinical)
Abstract

PURPOSE: Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. METHODS: Over the past 10 years, the National Institutes of Health–supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. RESULTS: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. CONCLUSION: The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.

Published
2022
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2. Exome sequencing and characterization of 49,960 individuals in the UK Biobank

Author

David J. Carey, Cristen J. Willer, Anthony Marcketta, Claudia Schurmann, Leland Barnard, John Penn, Suganthi Balasubramanian, Daren Liu, Joseph B. Leader, Gonçalo R. Abecasis, Marcus B. Jones, John C. Whittaker, Ashutosh K. Pandey, Ida Surakka, David H. Ledbetter, Evan Maxwell, John D. Overton, Andrew Blumenfeld, Michael N. Cantor, Robert A. Scott, Wendy K. Chung, Alexander H. Li, Alexander Lopez, Joshua D. Backman, Matthew R. Nelson, Jeffrey Staples, Giovanni Coppola, Jonathan Marchini, Xiaodong Bai, Kavita Praveen, Alan R. Shuldiner, Claudia Gonzaga-Jauregui, Aris N. Economides, Shareef Khalid, William J Salerno, Bin Ye, Cristopher V. Van Hout, Kristian Hveem, Jeffrey G. Reid, Colm O'Dushlaine, Joshua D. Hoffman, Laura M. Yerges-Armstrong, Nilanjana Banerjee, Sean O'Keeffe, Ioanna Tachmazidou, Lon R. Cardon, Alicia Hawes, Aris Baras, Ashish Yadav, George D. Yancopoulos, and Lukas Habegger

Subjects
Male, 0301 basic medicine, Genes, BRCA2, Genes, BRCA1, Hasso-Plattner-Institut für Digital Engineering GmbH, Penetrance, 030204 cardiovascular system & hematology, Ion Channels, 0302 clinical medicine, Bone Density, Loss of Function Mutation, Neoplasms, Databases, Genetic, Genetics research, Genotype, Exome, Exome sequencing, Biological Specimen Banks, education.field_of_study, Multidisciplinary, Genomics, Middle Aged, Biobank, Pedigree, Phenotype, ras GTPase-Activating Proteins, Female, Kidney Diseases, Population, Collagen Type VI, Computational biology, Biology, Article, DNA sequencing, Varicose Veins, 03 medical and health sciences, Exome Sequencing, Humans, education, Alleles, Aged, Demography, Rare variants, Peptide Fragments, United Kingdom, 030104 developmental biology, ddc:000, Next-generation sequencing
Abstract

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world1. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community., Exome sequences from the first 49,960 participants in the UK Biobank highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.

Published
2020
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3. Sequencing of 640,000 exomes identifies GPR75 variants associated with protection from obesity

Author

Jack A. Kosmicki, Charles Paulding, Nan Lin, Andrew J. Murphy, Jerome I. Rotter, Brian Zambrowicz, Niek Verweij, Luca A. Lotta, Michal L. Schwartzman, Giusy Della Gatta, Yii-Der Ida Chen, Alexander H. Li, Suganthi Balasubramanian, Jason M. Torres, Hyun Min Kang, Rory Collins, Parsa Akbari, Michael E. Dunn, Gonçalo R. Abecasis, Christian Benner, David J. Carey, Svati H. Shah, Jonathan Marchini, Giovanni Coppola, Marcus B. Jones, Olle Melander, Christopher D. Still, Yi-Ya Fang, Olukayode A. Sosina, Manuel A. R. Ferreira, Roberto Tapia-Conyer, Michael Cantor, Aris N. Economides, Dylan Sun, Adam E. Locke, Jonathan V. Pascale, Daniel J. Rader, Ankit Gilani, Joelle Mbatchou, Jesus Alegre-Díaz, Mark W. Sleeman, Trikaldarshi Persaud, Jeffrey G. Reid, Pablo Kuri-Morales, Jaime Berumen-Campos, John D. Overton, Aris Baras, Ercument Dirice, Sakib Hossain, Alicia Hawes, George D. Yancopoulos, Jonathan Emberson, Victor Garcia, Judith Altarejos, Lori Khrimian, Katia Karalis, William E. Kraus, Tooraj Mirshahi, Kevin Agostinucci, Alan R. Shuldiner, Center, Regeneron Genetics, and Collaboration, DiscovEHR

Subjects
0301 basic medicine, Genetics, medicine.medical_specialty, Multidisciplinary, Body Weight, Genomics, Organ Size, Biology, medicine.disease, Obesity, Article, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, Genetic variation, medicine, Medical genetics, Humans, medicine.symptom, Body mass index, Weight gain, 030217 neurology & neurosurgery, Exome sequencing, Glycemic
Abstract

Introduction Obesity accounts for a substantial and growing burden of disease globally. Body adiposity is highly heritable, and human genetic studies can lead to biological and therapeutic insights. Rationale Whole-exome sequencing of hundreds of thousands of individuals is complementary to approaches used to date in obesity genetics and has the potential to identify rare protein-coding variants with large phenotypic impact. We sequenced the exomes of 645,626 individuals from the UK, the US, and Mexico and estimated associations of rare coding variants with body mass index (BMI), a measure of overall adiposity used to define obesity in clinical practice. We complemented exome sequencing with fine-mapping of common alleles, polygenic score analysis, and in vitro and in vivo modeling work. Results We identified 16 genes for which the burden of rare nonsynonymous variants was associated with BMI at exome-wide statistical significance (inverse-variance weighted meta-analysis P < 3.6 × 10−7), including associations at five brain-expressed G protein–coupled receptors (CALCR, MC4R, GIPR, GPR151, and GPR75). We observed an overrepresentation of genes highly expressed in the hypothalamus, a key center for the neuroendocrine regulation of energy balance. Protein-truncating variants in GPR75 were found in ~4/10,000 sequenced people and were associated with 1.8 kg/m2 lower BMI, 5.3 kg lower bodyweight, and 54% lower odds of obesity in heterozygous carriers. Knock out of Gpr75 in mice resulted in resistance to weight gain in a high-fat diet model, which was allele-dose dependent (25% and 44% lower weight gain, respectively, for heterozygous Gpr75−/+ mice and knockout Gpr75−/− mice compared with wild type) and accompanied by improved glycemic control and insulin sensitivity. Protein-truncating variants in CALCR were associated with higher BMI and obesity risk, whereas protein-truncating variants in GIPR and two missense alleles [Arg190→Gln (Arg190Gln), Glu288Gly], which we show result in loss of function in vitro, were associated with lower adiposity. Among monogenic obesity genes in the leptin-melanocortin pathway, heterozygous predicted loss-of-function variants in LEP, POMC, PCSK1, and MC4R (but not LEPR) were associated with higher BMI. Rare protein-truncating variants in UBR2, ANO4, and PCSK1 were associated with more than twofold higher odds of obesity in heterozygous carriers, similar to predicted-deleterious nonsynonymous variants in MC4R, which are considered the most common cause of monogenic obesity. Polygenic predisposition due to >2 million common genetic variants influenced the penetrance of obesity in rare variant carriers in an additive fashion. Conclusion These results suggest that inhibition of GPR75 may be a therapeutic strategy for obesity and illustrate the power of massive-scale exome sequencing for the identification of large-effect coding variant associations and drug targets for complex traits.

Published
2022
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4. A catalog of associations between rare coding variants and COVID-19 outcomes

Author

Anurag Verma, Anne E. Justice, Guillaume Butler-Laporte, E. N. Smith, Lukas Habegger, Joelle Mbatchou, Susan P. Walker, Albert Tenesa, Joseph D. Szustakowski, Konrad Rawlik, Dylan Sun, Loukas Moutsianas, Shane McCarthy, Richard H Scott, Aris Baras, Evan Maxwell, Aldo Cordova-Palomera, Tooraj Mirshahi, Dorota Pasko, David J. Carey, Sahar Esmaeli, Adam J. Mansfield, Quanli Wang, Jeffrey S. Reid, Nilanjana Banerjee, Joshua D. Backman, Athanasios Kousathanas, Ashish Yadav, Mark J. Caulfield, Alison M. Meynert, Rouel Lanche, Jack A. Kosmicki, James F. Wilson, J. Brent Richards, Heiko Runz, Gonçalo R. Abecasis, Adam E. Locke, Justin W. Davis, Mark Lathrop, Alan R. Shuldiner, Lauren Gurski, J Kenneth Baillie, Michael N. Cantor, David Goldstein, John D. Overton, Kyoko Watanabe, Amanda O'Neill, Yunfeng Huang, Jonathan Marchini, Xiaodong Bai, Krzysztof Kiryluk, Slavé Petrovski, Sean O'Keeffe, Erika Kvikstad, Anthony Marcketta, Margaret M. Parker, Giorgio Sirugo, Julie E. Horowitz, Emily Wong, Olympe Chazara, Paul Nioi, Manuel A. R. Ferreira, Sándor Szalma, Joseph B. Leader, Shareef Khalid, William J Salerno, Deepika Sharma, Tomoko Nakanishi, Marcus B. Jones, Gundula Povysil, Marylyn D. Ritchie, Colm O'Dushlaine, Xiuwen Zheng, Daniel J. Rader, Suganthi Balasubramanian, Hyun Min Kang, Yi-Pin Lai, Alexander H. Li, Xing Chen, and Erola Pairo-Castineira

Subjects
Coronavirus disease 2019 (COVID-19), business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Genome-wide association study, medicine.disease_cause, Biobank, Article, Genetic association analysis, Immunology, Multiple comparisons problem, Medicine, business, Gene, Coronavirus
Abstract

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease-19 (COVID-19), a respiratory illness that can result in hospitalization or death. We investigated associations between rare genetic variants and seven COVID-19 outcomes in 543,213 individuals, including 8,248 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 14 interferon pathway genes in which rare deleterious variants have been reported in severe COVID-19 patients; (ii) 167 genes located in COVID-19 GWAS risk loci; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, with results publicly browsable athttps://rgc-covid19.regeneron.com.

Published
2020
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5. Profiling and Leveraging Relatedness in a Precision Medicine Cohort of 92,455 Exomes

Author

Shane McCarthy, David H. Ledbetter, Frederick E. Dewey, Lukas Habegger, John Penn, David J. Carey, George D. Yancoupolos, Cristopher V. Van Hout, H. Lester Kirchner, Suganthi Balasubramanian, Joseph B. Leader, Tanya M. Teslovich, Xiaodong Bai, Colm O'Dushlaine, Aris Baras, John D. Overton, Michael F. Murray, Nehal Gosalia, Jeffrey G. Reid, Evan Maxwell, Alan R. Shuldiner, Alexander Lopez, Claudia Gonzaga-Jauregui, Christopher Snyder, Jeffrey Staples, Ricardo Ulloa, and Alicia Hawes

Subjects
Male, 0301 basic medicine, Heterozygote, Population, Genomics, Pedigree chart, Biology, Compound heterozygosity, Article, Cohort Studies, 03 medical and health sciences, Genetics, Electronic Health Records, Humans, Computer Simulation, Exome, Family, Precision Medicine, education, Nuclear family, Genetics (clinical), Exome sequencing, education.field_of_study, Geography, Reproducibility of Results, Exons, Human genetics, Pedigree, Genetics, Population, Phenotype, 030104 developmental biology, Evolutionary biology, Mutation, Cohort, Female, Tandem exon duplication
Abstract

Large-scale human genetics studies are ascertaining increasing proportions of populations as they continue growing in both number and scale. As a result, the amount of cryptic relatedness within these study cohorts is growing rapidly and has significant implications on downstream analyses. We demonstrate this growth empirically among the first 92,455 exomes from the DiscovEHR cohort and, via a custom simulation framework we developed called SimProgeny, show that these measures are in-line with expectations given the underlying population and ascertainment approach. For example, we identified ∼66,000 close (first- and second-degree) relationships within DiscovEHR involving 55.6% of study participants. Our simulation results project that >70% of the cohort will be involved in these close relationships as DiscovEHR scales to 250,000 recruited individuals. We reconstructed 12,574 pedigrees using these relationships (including 2,192 nuclear families) and leveraged them for multiple applications. The pedigrees substantially improved the phasing accuracy of 20,947 rare, deleterious compound heterozygous mutations. Reconstructed nuclear families were critical for identifying 3,415 de novo mutations in ∼1,783 genes. Finally, we demonstrate the segregation of known and suspected disease-causing mutations through reconstructed pedigrees, including a tandem duplication in LDLR causing familial hypercholesterolemia. In summary, this work highlights the prevalence of cryptic relatedness expected among large healthcare population genomic studies and demonstrates several analyses that are uniquely enabled by large amounts of cryptic relatedness.

Published
2018
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6. Polygenic Risk of Psychiatric Disorders Exhibits Cross-trait Associations in Electronic Health Record Data From European Ancestry Individuals

Author

Rachel L. Kember, Alison K. Merikangas, Shefali S. Verma, Anurag Verma, Renae Judy, Scott M. Damrauer, Marylyn D. Ritchie, Daniel J. Rader, Maja Bućan, Goncalo Abecasis, Aris Baras, Michael Cantor, Giovanni Coppola, Aris Economides, Luca Lotta, John D. Overton, Jeffrey G. Reid, Alan Shuldiner, Christina Beechert, Caitlin Forsythe, Erin D. Fuller, Zhenhua Gu, Michael Lattari, Alexander Lopez, Thomas D. Schleicher, Maria Sotiropoulos Padilla, Karina Toledo, Louis Widom, Sarah E. Wolf, Manasi Pradhan, Kia Manoochehri, Ricardo H. Ulloa, Xiaodong Bai, Suganthi Balasubramanian, Leland Barnard, Andrew Blumenfeld, Gisu Eom, Lukas Habegger, Young Hahn, Alicia Hawes, Shareef Khalid, Evan K. Maxwell, William Salerno, Jeffrey C. Staples, Ashish Yadav, Marcus B. Jones, and Lyndon J. Mitnaul

Subjects
0301 basic medicine, medicine.medical_specialty, Multifactorial Inheritance, Bipolar Disorder, Disease, Article, 03 medical and health sciences, 0302 clinical medicine, medicine, Electronic Health Records, Humans, Genetic Predisposition to Disease, Bipolar disorder, Psychiatry, Biological Psychiatry, Depressive Disorder, Major, business.industry, Odds ratio, medicine.disease, Biobank, Genetic architecture, 030104 developmental biology, Phenotype, Schizophrenia, Anorexia nervosa (differential diagnoses), Major depressive disorder, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Background Prediction of disease risk is a key component of precision medicine. Common traits such as psychiatric disorders have a complex polygenic architecture, making the identification of a single risk predictor difficult. Polygenic risk scores (PRSs) denoting the sum of an individual’s genetic liability for a disorder are a promising biomarker for psychiatric disorders, but they require evaluation in a clinical setting. Methods We developed PRSs for 6 psychiatric disorders (schizophrenia, bipolar disorder, major depressive disorder, cross disorder, attention-deficit/hyperactivity disorder, and anorexia nervosa) and 17 nonpsychiatric traits in more than 10,000 individuals from the Penn Medicine Biobank with accompanying electronic health records. We performed phenome-wide association analyses to test their association across disease categories. Results Four of the 6 psychiatric PRSs were associated with their primary phenotypes (odds ratios from 1.2 to 1.6). Cross-trait associations were identified both within the psychiatric domain and across trait domains. PRSs for coronary artery disease and years of education were significantly associated with psychiatric disorders, largely driven by an association with tobacco use disorder. Conclusions We demonstrated that the genetic architecture of electronic health record–derived psychiatric diagnoses is similar to ascertained research cohorts from large consortia. Psychiatric PRSs are moderately associated with psychiatric diagnoses but are not yet clinically predictive in naive patients. Cross-trait associations for these PRSs suggest a broader effect of genetic liability beyond traditional diagnostic boundaries. As identification of genetic markers increases, including PRSs alongside other clinical risk factors may enhance prediction of psychiatric disorders and associated conditions in clinical registries.

Published
2020

7. A Protein-Truncating HSD17B13 Variant and Protection from Chronic Liver Disease

Author

Shane McCarthy, Jonathan C. Cohen, Frederick E. Dewey, Claudia Schurmann, Matthew D. Still, Panayiotis Stevis, Xin Chu, Daniel J. Rader, David J. Carey, Alan R. Shuldiner, Noura S. Abul-Husn, Semanti Mukherjee, Jonathan S. Packer, Xiping Cheng, Ann Stepanchick, Brian Zambrowicz, Helen H. Hobbs, John Penn, Uyenlinh L. Mirshahi, Scott M. Damrauer, Ingrid B. Borecki, Yurong Xin, G. Craig Wood, Jesper Gromada, Suganthi Balasubramanian, Tanya M. Teslovich, Andrew J. Murphy, Erin D. Fuller, Christopher D. Still, Tooraj Mirshahi, Jonathan Z. Luo, John D. Overton, George D. Yancopoulos, Yashu Liu, Alexander H. Li, Aeron Small, Omri Gottesman, Julia Kozlitina, Jeffrey G. Reid, Stefan Stender, David Esopi, William C. Olson, Michael Feldman, Colm O'Dushlaine, Alexander E. Lopez, Nehal Gosalia, Sun Y. Kim, and Aris Baras

Subjects
0301 basic medicine, Male, medicine.medical_specialty, 17-Hydroxysteroid Dehydrogenases, Genotype, Chronic liver disease, Gastroenterology, Article, 03 medical and health sciences, Liver disease, 0302 clinical medicine, Non-alcoholic Fatty Liver Disease, Loss of Function Mutation, Internal medicine, Exome Sequencing, Medicine, Humans, Exome, Genetic Predisposition to Disease, Aspartate Aminotransferases, Exome sequencing, biology, business.industry, Sequence Analysis, RNA, Liver Diseases, Fatty liver, Genetic Variation, Alanine Transaminase, General Medicine, medicine.disease, Human genetics, Fatty Liver, 030104 developmental biology, Alanine transaminase, Liver, Chronic Disease, biology.protein, Disease Progression, Linear Models, 030211 gastroenterology & hepatology, Female, business, Biomarkers, TM6SF2
Abstract

BACKGROUND: Elucidation of the genetic factors underlying chronic liver disease may reveal new therapeutic targets. METHODS: We used exome sequence data and electronic health records from 46,544 participants in the DiscovEHR human genetics study to identify genetic variants associated with serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Variants that were replicated in three additional cohorts (12,527 persons) were evaluated for association with clinical diagnoses of chronic liver disease in DiscovEHR study participants and two independent cohorts (total of 37,173 persons) and with histopathological severity of liver disease in 2391 human liver samples. RESULTS: A splice variant (rs72613567:TA) in HSD17B13, encoding the hepatic lipid droplet protein hydroxysteroid 17-beta dehydrogenase 13, was found to be associated with reduced levels of ALT (P=4.20×10(−12)) and AST (P=6.2×10(−10)). Among DiscovEHR study participants, this variant was found to be associated with a reduced risk of alcoholic liver disease (by 42% [95% confidence interval {CI}, 20 to 58] among heterozygotes and by 53% [95% CI, 3 to 77] among homozygotes), nonalcoholic liver disease (by 17% [95% CI, 8 to 25] among heterozygotes and by 30% [95% CI, 13 to 43] among homozygotes), alcoholic cirrhosis (by 42% [95% CI, 14 to 61] among heterozygotes and by 73% [95% CI, 15 to 91] among homozygotes), and nonalcoholic cirrhosis (by 26% [95% CI, 7 to 40] among heterozygotes and by 49% [95% CI, 15 to 69] among homozygotes). Associations were confirmed in two independent cohorts. The rs72613567:TA variant was associated with a reduced risk of nonalcoholic steatohepatitis, but not steatosis, in human liver samples. The rs72613567:TA variant mitigated liver injury associated with the risk-increasing PNPLA3 p.I148M allele and resulted in an unstable and truncated protein with reduced enzymatic activity. CONCLUSIONS: A loss-of-function variant in HSD17B13 is associated with a reduced risk of chronic liver disease and of progression from steatosis to steatohepatitis. (Funded by Regeneron Pharmaceuticals and others.)

Published
2018

8. Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes

Author

Yao Fu, Mike Jin, Mark Gerstein, Patrick McGillivray, Mayur Pawashe, Konrad J. Karczewski, Daniel G. MacArthur, Suganthi Balasubramanian, and Jeremy Liu

Subjects
0301 basic medicine, Science, General Physics and Astronomy, Biology, Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, symbols.namesake, Loss of Function Mutation, Neoplasms, Databases, Genetic, Humans, Exome, Genetic Predisposition to Disease, Autistic Disorder, Allele, lcsh:Science, Gene, Loss function, Exome sequencing, Genetics, Multidisciplinary, Molecular Sequence Annotation, General Chemistry, 030104 developmental biology, Mendelian inheritance, symbols, lcsh:Q, Human genome, Common disease-common variant
Abstract

Variants predicted to result in the loss of function of human genes have attracted interest because of their clinical impact and surprising prevalence in healthy individuals. Here, we present ALoFT (annotation of loss-of-function transcripts), a method to annotate and predict the disease-causing potential of loss-of-function variants. Using data from Mendelian disease-gene discovery projects, we show that ALoFT can distinguish between loss-of-function variants that are deleterious as heterozygotes and those causing disease only in the homozygous state. Investigation of variants discovered in healthy populations suggests that each individual carries at least two heterozygous premature stop alleles that could potentially lead to disease if present as homozygotes. When applied to de novo putative loss-of-function variants in autism-affected families, ALoFT distinguishes between deleterious variants in patients and benign variants in unaffected siblings. Finally, analysis of somatic variants in >6500 cancer exomes shows that putative loss-of-function variants predicted to be deleterious by ALoFT are enriched in known driver genes., Variants causing loss of function (LoF) of human genes have clinical implications. Here, the authors present a method to predict disease-causing potential of LoF variants, ALoFT (annotation of Loss-of-Function Transcripts) and show its application to interpreting LoF variants in different contexts.

Published
2017
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9. Personal Omics Profiling Reveals Dynamic Molecular and Medical Phenotypes

Author

Hugo Y. K. Lam, Hua Tang, Suganthi Balasubramanian, Jennifer Li-Pook-Than, Elana Miriami, Alan P. Boyle, Lukas Habegger, Euan A. Ashley, Keith Bettinger, Michael Snyder, Atul J. Butte, Kari C. Nadeau, Phyllis Snyder, Lihua Jiang, Teri E. Klein, Sara Hillenmeyer, Michelle Whirl-Carrillo, Frederick E. Dewey, Maeve O'Huallachain, Joel T. Dudley, Hogune Im, Konrad J. Karczewski, Scott Seki, Fabian Grubert, Mercedes Gallardo, Donald Sharon, Marco Garcia, Mark Gerstein, Manoj Hariharan, Maria A. Blasco, Russ B. Altman, Ghia Euskirchen, Peter L. Greenberg, Yong Cheng, Rui Chen, Michael J. Clark, Phil Lacroute, Rong Chen, George I. Mias, Maya Kasowski, and Rajini R Haraksingh

Subjects
Male, Proteomics, Rhinovirus, Genomics, Computational biology, Biology, Genome, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, 0302 clinical medicine, Metabolomics, Humans, Precision Medicine, 030304 developmental biology, Genetics, 0303 health sciences, Biochemistry, Genetics and Molecular Biology(all), business.industry, Genome, Human, Gene Expression Profiling, Middle Aged, Precision medicine, Omics, 3. Good health, Respiratory Syncytial Viruses, Gene expression profiling, Diabetes Mellitus, Type 2, 030220 oncology & carcinogenesis, Mutation, Female, Personalized medicine, business
Abstract

SummaryPersonalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here, we present an integrative personal omics profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. Our iPOP analysis revealed various medical risks, including type 2 diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions. Extremely high-coverage genomic and transcriptomic data, which provide the basis of our iPOP, revealed extensive heteroallelic changes during healthy and diseased states and an unexpected RNA editing mechanism. This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity.

Published
2012
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10. A systematic survey of loss-of-function variants in human protein-coding genes

Author

Klaudia Walter, Yali Xue, Jeffrey C. Barrett, Jennifer Harrow, Catherine E. Snow, Mark Gerstein, Ni Huang, Steven A. McCarroll, Jonathan K. Pritchard, Jeffrey A. Rosenfeld, Zhengdong D. Zhang, Hancheng Zheng, Menachem Fromer, Lukas Habegger, Yingrui Li, Mark A. DePristo, If H. A. Barnes, Bryndis Yngvadottir, James Morris, Alexandra Bignell, David Neil Cooper, Gerton Lunter, Ekta Khurana, Stephen B. Montgomery, Richard A. Gibbs, Donald F. Conrad, Emmanouil T. Dermitzakis, Daniel G. MacArthur, Suzannah Bumpstead, Gary Saunders, Kai Ye, Clara Amid, Marie-Marthe Suner, M. Kay, Joseph K. Pickrell, Adam Frankish, Robert E. Handsaker, Suganthi Balasubramanian, Eric Banks, Toby Hunt, Irene Gallego Romero, Cornelis A. Albers, Chris Tyler-Smith, Qasim Ayub, Denise Carvalho-Silva, Matthew E. Hurles, Min Hu, Luke Jostins, Jun Wang, Mike Jin, and Xinmeng Jasmine Mu

Subjects
Candidate gene, Gene Expression, Biology, Genome, Polymorphism, Single Nucleotide, Article, Genomic disorders and inherited multi-system disorders DCN MP - Plasticity and memory [IGMD 3], Gene Frequency, Genetic variation, Humans, ddc:576.5, Disease, Allele, Selection, Genetic, Gene, Loss function, Genetics, Multidisciplinary, Genome, Human, Genetic Variation, Proteins, Phenotype, Disease/genetics, Proteins/genetics, Human genome
Abstract

Defective Gene Detective Identifying genes that give rise to diseases is one of the major goals of sequencing human genomes. However, putative loss-of-function genes, which are often some of the first identified targets of genome and exome sequencing, have often turned out to be sequencing errors rather than true genetic variants. In order to identify the true scope of loss-of-function genes within the human genome, MacArthur et al. (p. 823 ; see the Perspective by Quintana-Murci ) extensively validated the genomes from the 1000 Genomes Project, as well as an additional European individual, and found that the average person has about 100 true loss-of-function alleles of which approximately 20 have two copies within an individual. Because many known disease-causing genes were identified in “normal” individuals, the process of clinical sequencing needs to reassess how to identify likely causative alleles.

Published
2012
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11. Sequence variation in G-protein-coupled receptors: analysis of single nucleotide polymorphisms

Author

Suganthi Balasubramanian, Elizaveta Freinkman, Mark Gerstein, and Yu Xia

Subjects
dbSNP, Sequence analysis, Entropy, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Article, Receptors, G-Protein-Coupled, Conserved sequence, 03 medical and health sciences, 0302 clinical medicine, Phylogenetics, Genetics, Humans, Genetic Predisposition to Disease, Genotyping, Phylogeny, 030304 developmental biology, Genetic association, 0303 health sciences, Phylogenetic tree, Sequence Analysis, DNA, Amino Acid Substitution, Regression Analysis, Hydrophobic and Hydrophilic Interactions, 030217 neurology & neurosurgery
Abstract

We assessed the disease-causing potential of single nucleotide polymorphisms (SNPs) based on a simple set of sequence-based features. We focused on SNPs from the dbSNP database in G-protein-coupled receptors (GPCRs), a large class of important transmembrane (TM) proteins. Apart from the location of the SNP in the protein, we evaluated the predictive power of three major classes of features to differentiate between disease-causing mutations and neutral changes: (i) properties derived from amino-acid scales, such as volume and hydrophobicity; (ii) position-specific phylogenetic features reflecting evolutionary conservation, such as normalized site entropy, residue frequency and SIFT score; and (iii) substitution-matrix scores, such as those derived from the BLOSUM62, GRANTHAM and PHAT matrices. We validated our approach using a control dataset consisting of known disease-causing mutations and neutral variations. Logistic regression analyses indicated that position-specific phylogenetic features that describe the conservation of an amino acid at a specific site are the best discriminators of disease mutations versus neutral variations, and integration of all our features improves discrimination power. Overall, we identify 115 SNPs in GPCRs from dbSNP that are likely to be associated with disease and thus are good candidates for genotyping in association studies.

Published
2005
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12. Enhanced transcriptome maps from multiple mouse tissues reveal evolutionary constraint in gene expression

Author

Lei Hoon See, Jean Monlong, Huaien Wang, Dmitri D. Pervouchine, Alessandra Breschi, Alexander Dobin, Julien Lagarde, Cedric Notredame, Michael A. Beer, Suganthi Balasubramanian, Thomas R. Gingeras, Arif Harmanci, Meagan Fastuca, Chris Zaleski, Baikang Pei, Roderic Guigó, Pablo Prieto Barja, Mark Gerstein, Jorg Drenkow, Andrea Tanzer, Sarah Djebali, Giovanni Bussotti, and Carrie A. Davis

Subjects
Evolution, General Physics and Astronomy, Computational biology, Biology, Ratolins -- Genètica, Genome, Article, General Biochemistry, Genetics and Molecular Biology, Cell Line, Epigenesis, Genetic, Evolution, Molecular, Histones, Transcriptome, Mice, 03 medical and health sciences, 0302 clinical medicine, Regulació genètica, Gene expression, Genetics, Animals, Humans, Epigenetics, Gene, Gene Library, 030304 developmental biology, Regulation of gene expression, 0303 health sciences, Multidisciplinary, Models, Genetic, Sequence Analysis, RNA, Gene Expression Profiling, Alternative splicing, General Chemistry, Oligonucleotides, Antisense, Biological Evolution, Mice, Inbred C57BL, Gene expression profiling, Alternative Splicing, Biological sciences, Phenotype, Gene Expression Regulation, 030217 neurology & neurosurgery
Abstract

Mice have been a long-standing model for human biology and disease. Here we characterize, by RNA sequencing, the transcriptional profiles of a large and heterogeneous collection of mouse tissues, augmenting the mouse transcriptome with thousands of novel transcript candidates. Comparison with transcriptome profiles in human cell lines reveals substantial conservation of transcriptional programmes, and uncovers a distinct class of genes with levels of expression that have been constrained early in vertebrate evolution. This core set of genes captures a substantial fraction of the transcriptional output of mammalian cells, and participates in basic functional and structural housekeeping processes common to all cell types. Perturbation of these constrained genes is associated with significant phenotypes including embryonic lethality and cancer. Evolutionary constraint in gene expression levels is not reflected in the conservation of the genomic sequences, but is associated with conserved epigenetic marking, as well as with characteristic post-transcriptional regulatory programme, in which sub-cellular localization and alternative splicing play comparatively large roles., The analysis of mammalian transcriptomes could provide new insights into human biology. Here the authors carry out RNA sequencing in a large collection of mouse tissues and compare these data to human transcriptome profiles, identifying a set of constrained genes that carry out basic cellular functions with remarkably constant expression levels across tissues and species.

Published
2015
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13. A global reference for human genetic variation

Author

Colonna V. (1000 Genomes Project Consortium) Adam Auton, Gonçalo R Abecasis, David M Altshuler, Richard M Durbin, David R Bentley, Aravinda Chakravarti, Andrew G Clark, Peter Donnelly, Evan E Eichler, Paul Flicek, Stacey B Gabriel, Richard A Gibbs, Eric D Green, Matthew E Hurles, Bartha M Knoppers, Jan O Korbel, Eric S Lander, Charles Lee, Hans Lehrach, Elaine R Mardis, Gabor T Marth, Gil A McVean, Deborah A Nickerson, Jeanette P Schmidt, Stephen T Sherry, Jun Wang, Richard K Wilson, Eric Boerwinkle, Harsha Doddapaneni, Yi Han, Viktoriya Korchina, Christie Kovar, Sandra Lee, Donna Muzny, Jeffrey G Reid, Yiming Zhu, Yuqi Chang, Qiang Feng, Xiaodong Fang, Xiaosen Guo, Min Jian, Hui Jiang, Xin Jin, Tianming Lan, Guoqing Li, Jingxiang Li, Yingrui Li, Shengmao Liu, Xiao Liu, Yao Lu, Xuedi Ma, Meifang Tang, Bo Wang, Guangbiao Wang, Honglong Wu, Renhua Wu, Xun Xu, Ye Yin, Dandan Zhang, Wenwei Zhang, Jiao Zhao, Meiru Zhao, Xiaole Zheng, Namrata Gupta, Neda Gharani, Lorraine H Toji, Norman P Gerry, Alissa M Resch, Jonathan Barker, Laura Clarke, Laurent Gil, Sarah E Hunt, Gavin Kelman, Eugene Kulesha, Rasko Leinonen, William M McLaren, Rajesh Radhakrishnan, Asier Roa, Dmitriy Smirnov, Richard E Smith, Ian Streeter, Anja Thormann, Iliana Toneva, Brendan Vaughan, Xiangqun Zheng-Bradley, Russell Grocock, Sean Humphray, Terena James, Zoya Kingsbury, Ralf Sudbrak, Marcus W Albrecht, Vyacheslav S Amstislavskiy, Tatiana A Borodina, Matthias Lienhard, Florian Mertes, Marc Sultan, Bernd Timmermann, Marie-Laure Yaspo, Lucinda Fulton, Robert Fulton, Victor Ananiev, Zinaida Belaia, Dimitriy Beloslyudtsev, Nathan Bouk, Chao Chen, Deanna Church, Robert Cohen, Charles Cook, John Garner, Timothy Hefferon, Mikhail Kimelman, Chunlei Liu, John Lopez, Peter Meric, Chris O'Sullivan, Yuri Ostapchuk, Lon Phan, Sergiy Ponomarov, Valerie Schneider, Eugene Shekhtman, Karl Sirotkin, Douglas Slotta, Hua Zhang, Senduran Balasubramaniam, John Burton, Petr Danecek, Thomas M Keane, Anja Kolb-Kokocinski, Shane McCarthy, James Stalker, Michael Quail, Christopher J Davies, Jeremy Gollub, Teresa Webster, Brant Wong, Yiping Zhan, Adam Auton, Christopher L Campbell, Yu Kong, Anthony Marcketta, Fuli Yu, Lilian Antunes, Matthew Bainbridge, Aniko Sabo, Zhuoyi Huang, Lachlan J M Coin, Lin Fang, Qibin Li, Zhenyu Li, Haoxiang Lin, Binghang Liu, Ruibang Luo, Haojing Shao, Yinlong Xie, Chen Ye, Chang Yu, Fan Zhang, Hancheng Zheng, Hongmei Zhu, Can Alkan, Elif Dal, Fatma Kahveci, Erik P Garrison, Deniz Kural, Wan-Ping Lee, Wen Fung Leong, Michael Stromberg, Alistair N Ward, Jiantao Wu, Mengyao Zhang, Mark J Daly, Mark A DePristo, Robert E Handsaker, Eric Banks, Gaurav Bhatia, Guillermo Del Angel, Giulio Genovese, Heng Li, Seva Kashin, Steven A McCarroll, James C Nemesh, Ryan E Poplin, Seungtai C Yoon, Jayon Lihm, Vladimir Makarov, Srikanth Gottipati, Alon Keinan, Juan L Rodriguez-Flores, Tobias Rausch, Markus H Fritz, Adrian M Stütz, Kathryn Beal, Avik Datta, Javier Herrero, Graham R S Ritchie, Daniel Zerbino, Pardis C Sabeti, Ilya Shlyakhter, Stephen F Schaffner, Joseph Vitti, David N Cooper, Edward V Ball, Peter D Stenson, Bret Barnes, Markus Bauer, R Keira Cheetham, Anthony Cox, Michael Eberle, Scott Kahn, Lisa Murray, John Peden, Richard Shaw, Eimear E Kenny, Mark A Batzer, Miriam K Konkel, Jerilyn A Walker, Daniel G MacArthur, Monkol Lek, Ralf Herwig, Li Ding, Daniel C Koboldt, David Larson, Kai Ye, Simon Gravel, Anand Swaroop, Emily Chew, Tuuli Lappalainen, Yaniv Erlich, Melissa Gymrek, Thomas Frederick Willems, Jared T Simpson, Mark D Shriver, Jeffrey A Rosenfeld, Carlos D Bustamante, Stephen B Montgomery, Francisco M De La Vega, Jake K Byrnes, Andrew W Carroll, Marianne K DeGorter, Phil Lacroute, Brian K Maples, Alicia R Martin, Andres Moreno-Estrada, Suyash S Shringarpure, Fouad Zakharia, Eran Halperin, Yael Baran, Eliza Cerveira, Jaeho Hwang, Ankit Malhotra, Dariusz Plewczynski, Kamen Radew, Mallory Romanovitch, Chengsheng Zhang, Fiona C L Hyland, David W Craig, Alexis Christoforides, Nils Homer, Tyler Izatt, Ahmet A Kurdoglu, Shripad A Sinari, Kevin Squire, Chunlin Xiao, Jonathan Sebat, Danny Antaki, Madhusudan Gujral, Amina Noor, Kenny Ye, Esteban G Burchard, Ryan D Hernandez, Christopher R Gignoux, David Haussler, Sol J Katzman, W James Kent, Bryan Howie, Andres Ruiz-Linares, Emmanouil T Dermitzakis, Scott E Devine, Hyun Min Kang, Jeffrey M Kidd, Tom Blackwell, Sean Caron, Wei Chen, Sarah Emery, Lars Fritsche, Christian Fuchsberger, Goo Jun, Bingshan Li, Robert Lyons, Chris Scheller, Carlo Sidore, Shiya Song, Elzbieta Sliwerska, Daniel Taliun, Adrian Tan, Ryan Welch, Mary Kate Wing, Xiaowei Zhan, Philip Awadalla, Alan Hodgkinson, Yun Li, Xinghua Shi, Andrew Quitadamo, Gerton Lunter, Jonathan L Marchini, Simon Myers, Claire Churchhouse, Olivier Delaneau, Anjali Gupta-Hinch, Warren Kretzschmar, Zamin Iqbal, Iain Mathieson, Androniki Menelaou, Andy Rimmer, Dionysia K Xifara, Taras K Oleksyk, Yunxin Fu, Xiaoming Liu, Momiao Xiong, Lynn Jorde, David Witherspoon, Jinchuan Xing, Brian L Browning, Sharon R Browning, Fereydoun Hormozdiari, Peter H Sudmant, Ekta Khurana, Chris Tyler-Smith, Cornelis A Albers, Qasim Ayub, Yuan Chen, Vincenza Colonna, Luke Jostins, Klaudia Walter, Yali Xue, Mark B Gerstein, Alexej Abyzov, Suganthi Balasubramanian, Jieming Chen, Declan Clarke, Yao Fu, Arif O Harmanci, Mike Jin, Donghoon Lee, Jeremy Liu, Xinmeng Jasmine Mu, Jing Zhang, Yan Zhang, Chris Hartl, Khalid Shakir, Jeremiah Degenhardt, Sascha Meiers, Benjamin Raeder, Francesco Paolo Casale, Oliver Stegle, Eric-Wubbo Lameijer, Ira Hall, Vineet Bafna, Jacob Michaelson, Eugene J Gardner, Ryan E Mills, Gargi Dayama, Ken Chen, Xian Fan, Zechen Chong, Tenghui Chen, Mark J Chaisson, John Huddleston, Maika Malig, Bradley J Nelson, Nicholas F Parrish, Ben Blackburne, Sarah J Lindsay, Zemin Ning, Yujun Zhang, Hugo Lam, Cristina Sisu, Danny Challis, Uday S Evani, James Lu, Uma Nagaswamy, Jin Yu, Wangshen Li, Lukas Habegger, Haiyuan Yu, Fiona Cunningham, Ian Dunham, Kasper Lage, Jakob Berg Jespersen, Heiko Horn, Donghoon Kim, Rob Desalle, Apurva Narechania, Melissa A Wilson Sayres, Fernando L Mendez, G David Poznik, Peter A Underhill, Lachlan Coin, David Mittelman, Ruby Banerjee, Maria Cerezo, Thomas W Fitzgerald, Sandra Louzada, Andrea Massaia, Graham R Ritchie, Fengtang Yang, Divya Kalra, Walker Hale, Xu Dan, Kathleen C Barnes, Christine Beiswanger, Hongyu Cai, Hongzhi Cao, Brenna Henn, Danielle Jones, Jane S Kaye, Alastair Kent, Angeliki Kerasidou, Rasika Mathias, Pilar N Ossorio, Michael Parker, Charles N Rotimi, Charmaine D Royal, Karla Sandoval, Yeyang Su, Zhongming Tian, Sarah Tishkoff, Marc Via, Yuhong Wang, Huanming Yang, Ling Yang, Jiayong Zhu, Walter Bodmer, Gabriel Bedoya, Zhiming Cai, Yang Gao, Jiayou Chu, Leena Peltonen, Andres Garcia-Montero, Alberto Orfao, Julie Dutil, Juan C Martinez-Cruzado, Rasika A Mathias, Anselm Hennis, Harold Watson, Colin McKenzie, Firdausi Qadri, Regina LaRocque, Xiaoyan Deng, Danny Asogun, Onikepe Folarin, Christian Happi, Omonwunmi Omoniwa, Matt Stremlau, Ridhi Tariyal, Muminatou Jallow, Fatoumatta Sisay Joof, Tumani Corrah, Kirk Rockett, Dominic Kwiatkowski, Jaspal Kooner, Trân T?nh Hiên, Sarah J Dunstan, Nguyen Thuy Hang, Richard Fonnie, Robert Garry, Lansana Kanneh, Lina Moses, John Schieffelin, Donald S Grant, Carla Gallo, Giovanni Poletti, Danish Saleheen, Asif Rasheed, Lisa D Brooks, Adam L Felsenfeld, Jean E McEwen, Yekaterina Vaydylevich, Audrey Duncanson, Michael Dunn, Jeffery A Schloss, 1000 Genomes Project Consortium, Institute for Medical Engineering and Science, Broad Institute of MIT and Harvard, Lincoln Laboratory, Massachusetts Institute of Technology. Department of Biology, Gabriel, Stacey, Lander, Eric Steven, Daly, Mark J, Banks, Eric, Bhatia, Gaurav, Kashin, Seva, McCarroll, Steven A, Nemesh, James, Poplin, Ryan E., Sabeti, Pardis, Shlyakhter, Ilya, Schaffner, Stephen F, Vitti, Joseph, Gymrek, Melissa A, Hartler, Christina M., and Tariyal, Ridhi

Subjects
demography, genetic association, genotype, Human genomics, Genome-wide association study, Review, SUSCEPTIBILITY, DISEASE, polymorphism, 0302 clinical medicine, quantitative trait locus, INDEL Mutation, genetics, GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries), MUTATION, Exome sequencing, 0303 health sciences, public health, Sequence analysis, High-Throughput Nucleotide Sequencing, standard, Genomics, Reference Standards, Physical Chromosome Mapping, 3. Good health, priority journal, Science & Technology - Other Topics, BAYES FACTORS, Molecular Developmental Biology, Genotype, Genetics, Medical, Quantitative Trait Loci, DNA sequence, rare disease, human genetics, information processing, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, POPULATION HISTORY, human genome, Humans, retroposon, Genetic variability, human, GENOME-WIDE ASSOCIATION, 1000 Genomes Project, Demography, Science & Technology, ancestry, disease predisposition, Genetic Variation, MACULAR DEGENERATION, major clinical study, gene linkage disequilibrium, purl.org/pe-repo/ocde/ford#3.01.02 [https], Genetics, Population, 030217 neurology & neurosurgery, haplotype, Internationality, VARIANT, Datasets as Topic, Human genetic variation, COMPLEMENT FACTOR-H, single nucleotide polymorphism, genetic variability, Exome, chromosome map, Genetics, Variant Call Format, Genome, Multidisciplinary, 1000 Genomes Project Consortium, international cooperation, Multidisciplinary Sciences, standards, Disease Susceptibility, medical genetics, General Science & Technology, Population, Computational biology, Biology, gene frequency, Polymorphism, Single Nucleotide, high throughput sequencing, Rare Diseases, promoter region, MD Multidisciplinary, Genetic variation, QH426, 030304 developmental biology, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Genome, Human, population genetics, population structure, Sequence Analysis, DNA, gene structure, INDIVIDUALS, Haplotypes, Genome-Wide Association Study, purl.org/pe-repo/ocde/ford#1.06.07 [https]
Abstract

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies., Wellcome Trust (London, England) (Core Award 090532/Z/09/Z), Wellcome Trust (London, England) (Senior Investigator Award 095552/Z/11/Z ), Wellcome Trust (London, England) (WT095908), Wellcome Trust (London, England) (WT109497), Wellcome Trust (London, England) (WT098051), Wellcome Trust (London, England) (WT086084/Z/08/Z), Wellcome Trust (London, England) (WT100956/Z/13/Z ), Wellcome Trust (London, England) (WT097307), Wellcome Trust (London, England) (WT0855322/Z/08/Z ), Wellcome Trust (London, England) (WT090770/Z/09/Z ), Wellcome Trust (London, England) (Major Overseas program in Vietnam grant 089276/Z.09/Z), Medical Research Council (Great Britain) (grant G0801823), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I02593X/1), Biotechnology and Biological Sciences Research Council (Great Britain) (grant BB/I021213/1), Zhongguo ke xue ji shu qing bao yan jiu suo. Office of 863 Programme of China (2012AA02A201), National Basic Research Program of China (2011CB809201), National Basic Research Program of China (2011CB809202), National Basic Research Program of China (2011CB809203), National Natural Science Foundation of China (31161130357), Shenzhen Municipal Government of China (grant ZYC201105170397A), Canadian Institutes of Health Research (grant 136855), Quebec Ministry of Economic Development, Innovation, and Exports (PSR-SIIRI-195), Germany. Bundesministerium für Bildung und Forschung (0315428A), Germany. Bundesministerium für Bildung und Forschung (01GS08201), Germany. Bundesministerium für Bildung und Forschung (BMBF-EPITREAT grant 0316190A), Deutsche Forschungsgemeinschaft (Emmy Noether Grant KO4037/1-1), Beatriu de Pinos Program (2006 BP-A 10144), Beatriu de Pinos Program (2009 BP-B 00274), Spanish National Institute for Health (grant PRB2 IPT13/0001-ISCIII-SGEFI/FEDER), Japan Society for the Promotion of Science (fellowship number PE13075), Marie Curie Actions Career Integration (grant 303772), Fonds National Suisse del la Recherche, SNSF, Scientifique (31003A_130342), National Center for Biotechnology Information (U.S.) (U54HG3067), National Center for Biotechnology Information (U.S.) (U54HG3273), National Center for Biotechnology Information (U.S.) (U01HG5211), National Center for Biotechnology Information (U.S.) (U54HG3079), National Center for Biotechnology Information (U.S.) (R01HG2898), National Center for Biotechnology Information (U.S.) (R01HG2385), National Center for Biotechnology Information (U.S.) (RC2HG5552), National Center for Biotechnology Information (U.S.) (U01HG6513), National Center for Biotechnology Information (U.S.) (U01HG5214), National Center for Biotechnology Information (U.S.) (U01HG5715), National Center for Biotechnology Information (U.S.) (U01HG5718), National Center for Biotechnology Information (U.S.) (U01HG5728), National Center for Biotechnology Information (U.S.) (U41HG7635), National Center for Biotechnology Information (U.S.) (U41HG7497), National Center for Biotechnology Information (U.S.) (R01HG4960), National Center for Biotechnology Information (U.S.) (R01HG5701), National Center for Biotechnology Information (U.S.) (R01HG5214), National Center for Biotechnology Information (U.S.) (R01HG6855), National Center for Biotechnology Information (U.S.) (R01HG7068), National Center for Biotechnology Information (U.S.) (R01HG7644), National Center for Biotechnology Information (U.S.) (DP2OD6514), National Center for Biotechnology Information (U.S.) (DP5OD9154), National Center for Biotechnology Information (U.S.) (R01CA166661), National Center for Biotechnology Information (U.S.) (R01CA172652), National Center for Biotechnology Information (U.S.) (P01GM99568), National Center for Biotechnology Information (U.S.) (R01GM59290), National Center for Biotechnology Information (U.S.) (R01GM104390), National Center for Biotechnology Information (U.S.) (T32GM7790), National Center for Biotechnology Information (U.S.) (R01HL87699), National Center for Biotechnology Information (U.S.) (R01HL104608), National Center for Biotechnology Information (U.S.) (T32HL94284), National Center for Biotechnology Information (U.S.) (HHSN268201100040C), National Center for Biotechnology Information (U.S.) (HHSN272201000025C), Lundbeck Foundation (grant R170-2014-1039, Simons Foundation (SFARI award SF51), National Science Foundation (U.S.) (Research Fellowship DGE-1147470)

Published
2015
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14. An integrated encyclopedia of DNA elements in the human genome

Author

Robert Altshuler, Laura Elnitski, Michael Anaya, Alec Victorsen, Deborah Winter, Javier Herrero, Katherine Varley, Andrea Sboner, Oscar Junhong Luo, Marco Mariotti, Cristina Sisu, Mike Kay, Timothy Dreszer, Jane Loveland, Alexandra Bignell, Ewan Birney, Tim @timjph Hubbard, Kuljeet Sandhu, Eric Haugen, Chris Gunter, Alexej Abyzov, Lucas Ward, Georgi Marinov, Michael Pazin, Thomas Gingeras, Alexander Dobin, Kimberly Foss, Xianjun Dong, Benoit Miotto, Piotr Mieczkowski, Cedric Notredame, Andrew Berry, Shawn Gillespie, Axel Visel, Shawn Levy, Richard Sandstrom, Jose M Gonzalez, Melissa Fullwood, Timo Lassmann, Michael Tress, Julien Lagarde, Kevin Yip, Leslie Adams, Sylvain Foissac, Bronwen Aken, Piero Carninci, Suganthi Balasubramanian, Andrea Tanzer, Sarah Djebali, Michael Hoffman, Gloria Despacio-Reyes, Peter Park, Felix Kokocinski, Katherine Fisher-Aylor, Juan M Vaquerizas, Peggy Farnham, Patrick Collins, Amonida Zadissa, Pedro Ferreira, Philippe Batut, Michael Snyder, Electra Tapanari, Adam Frankish, Paul Flicek, AMARTYA SANYAL, Tyler Alioto, Giovanni Bussotti, Laurence Meyer, Jingyi Jessica Li, Matthew Blow, Tristan FRUM, Roger Alexander, Rory Johnson, Charles Steward, Meizhen Zheng, Margus Lukk, Ross Hardison, Claire Davidson, Gary Saunders, Alan Boyle, Luiz Penalva, Rajinder Kaul, Lazaro Centanin, Florencia Pauli Behn, Thomas Derrien, Nathan Sheffield, Toby Hunt, Eric Nguyen, Jeff Vierstra, Konrad Karczewski, Kimberly Bell, Yanbao Yu, Hagen U Tilgner, James Taylor, Balázs Bánfai, Catherine Snow, Benjamin Vernot, Stephan Kirchmaier, Michael Sammeth, Steven Wilder, Angelika Merkel, Joanna Mieczkowska, Guoliang Li, Wei Lin, Jennifer Harrow, Thomas Oliver Auer, Daniel Barrell, Eddie Park, Alvis Brazma, Hazuki Takahashi, Nathan Johnson, Daniel Sobral, Terry Furey, Alexandre Reymond, Jonathan Mudge, Anshul Kundaje, Jose Rodriguez, Akshay Bhinge, James Gilbert, Jakub Karczewski, Venkat Malladi, Troy Whitfield, Orion Buske, Ian Dunham, Jennifer Moran, Joachim Wittbrodt, Charles B. Epstein, Laurens Wilming, Jason Gertz, Joshua Akey, Joel Rozowsky, Laboratoire de Génétique Cellulaire (LGC), Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA), National Human Genome Research Institute (NHGRI), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Antonarakis, Stylianos, Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Altshuler, Robert Charles, Ernst, Jason, Kellis, Manolis, Kheradpour, Pouya, Ward, Lucas D., Eaton, Matthew Lucas, Hendrix, David A., Jungreis, Irwin, Lin, Michael F., Washietl, Stefan, Lists of participants and their affiliations appear at the end of the paper and in the 'Collaboration/Projet' field., The Consortium is funded by grants from the NHGRI as follows: production grants: U54HG004570 (B. E. Bernstein), U01HG004695 (E. Birney), U54HG004563 (G. E. Crawford), U54HG004557 (T. R. Gingeras), U54HG004555 (T. J. Hubbard), U41HG004568 (W. J. Kent), U54HG004576 (R. M. Myers), U54HG004558 (M. Snyder), U54HG004592 (J. A. Stamatoyannopoulos). Pilot grants: R01HG003143 (J. Dekker), RC2HG005591 and R01HG003700 (M. C. Giddings), R01HG004456-03 (Y. Ruan), U01HG004571 (S. A. Tenenbaum), U01HG004561 (Z. Weng), RC2HG005679 (K. P. White). This project was supported in part by American Recovery and Reinvestment Act (ARRA) funds from the NHGRI through grants U54HG004570, U54HG004563, U41HG004568, U54HG004592, R01HG003143, RC2HG005591, R01HG003541,U01HG004561,RC2HG005679andR01HG003988(L. Pennacchio). In addition, work from NHGRI Groups was supported by the Intramural Research Program of the NHGRI (L. Elnitski, ZIAHG200323, E. H. Margulies, ZIAHG200341). Research in the Pennachio laboratory was performed at Lawrence Berkeley National Laboratory and at the United States Department of Energy Joint Genome Institute, Department of Energy Contract DE-AC02-05CH11231, University of California., Dunham I, Kundaje A, Aldred SF, Collins PJ, Davis CA, Doyle F, Epstein CB, Frietze S, Harrow J, Kaul R, Khatun J, Lajoie BR, Landt SG, Lee BK, Pauli F, Rosenbloom KR, Sabo P, Safi A, Sanyal A, Shoresh N, Simon JM, Song L, Trinklein ND, Altshuler RC, Birney E, Brown JB, Cheng C, Djebali S, Dong X, Dunham I, Ernst J, Furey TS, Gerstein M, Giardine B, Greven M, Hardison RC, Harris RS, Herrero J, Hoffman MM, Iyer S, Kellis M, Khatun J, Kheradpour P, Kundaje A, Lassmann T, Li Q, Lin X, Marinov GK, Merkel A, Mortazavi A, Parker SC, Reddy TE, Rozowsky J, Schlesinger F, Thurman RE, Wang J, Ward LD, Whitfield TW, Wilder SP, Wu W, Xi HS, Yip KY, Zhuang J, Pazin MJ, Lowdon RF, Dillon LA, Adams LB, Kelly CJ, Zhang J, Wexler JR, Green ED, Good PJ, Feingold EA, Bernstein BE, Birney E, Crawford GE, Dekker J, Elnitski L, Farnham PJ, Gerstein M, Giddings MC, Gingeras TR, Green ED, Guigó R, Hardison RC, Hubbard TJ, Kellis M, Kent W, Lieb JD, Margulies EH, Myers RM, Snyder M, Stamatoyannopoulos JA, Tenenbaum SA, Weng Z, White KP, Wold B, Khatun J, Yu Y, Wrobel J, Risk BA, Gunawardena HP, Kuiper HC, Maier CW, Xie L, Chen X, Giddings MC, Bernstein BE, Epstein CB, Shoresh N, Ernst J, Kheradpour P, Mikkelsen TS, Gillespie S, Goren A, Ram O, Zhang X, Wang L, Issner R, Coyne MJ, Durham T, Ku M, Truong T, Ward LD, Altshuler RC, Eaton ML, Kellis M, Djebali S, Davis CA, Merkel A, Dobin A, Lassmann T, Mortazavi A, Tanzer A, Lagarde J, Lin W, Schlesinger F, Xue C, Marinov GK, Khatun J, Williams BA, Zaleski C, Rozowsky J, Röder M, Kokocinski F, Abdelhamid RF, Alioto T, Antoshechkin I, Baer MT, Batut P, Bell I, Bell K, Chakrabortty S, Chen X, Chrast J, Curado J, Derrien T, Drenkow J, Dumais E, Dumais J, Duttagupta R, Fastuca M, Fejes-Toth K, Ferreira P, Foissac S, Fullwood MJ, Gao H, Gonzalez D, Gordon A, Gunawardena HP, Howald C, Jha S, Johnson R, Kapranov P, King B, Kingswood C, Li G, Luo OJ, Park E, Preall JB, Presaud K, Ribeca P, Risk BA, Robyr D, Ruan X, Sammeth M, Sandhu KS, Schaeffer L, See LH, Shahab A, Skancke J, Suzuki AM, Takahashi H, Tilgner H, Trout D, Walters N, Wang H, Wrobel J, Yu Y, Hayashizaki Y, Harrow J, Gerstein M, Hubbard TJ, Reymond A, Antonarakis SE, Hannon GJ, Giddings MC, Ruan Y, Wold B, Carninci P, Guigó R, Gingeras TR, Rosenbloom KR, Sloan CA, Learned K, Malladi VS, Wong MC, Barber GP, Cline MS, Dreszer TR, Heitner SG, Karolchik D, Kent W, Kirkup VM, Meyer LR, Long JC, Maddren M, Raney BJ, Furey TS, Song L, Grasfeder LL, Giresi PG, Lee BK, Battenhouse A, Sheffield NC, Simon JM, Showers KA, Safi A, London D, Bhinge AA, Shestak C, Schaner MR, Kim SK, Zhang ZZ, Mieczkowski PA, Mieczkowska JO, Liu Z, McDaniell RM, Ni Y, Rashid NU, Kim MJ, Adar S, Zhang Z, Wang T, Winter D, Keefe D, Birney E, Iyer VR, Lieb JD, Crawford GE, Li G, Sandhu KS, Zheng M, Wang P, Luo OJ, Shahab A, Fullwood MJ, Ruan X, Ruan Y, Myers RM, Pauli F, Williams BA, Gertz J, Marinov GK, Reddy TE, Vielmetter J, Partridge E, Trout D, Varley KE, Gasper C, Bansal A, Pepke S, Jain P, Amrhein H, Bowling KM, Anaya M, Cross MK, King B, Muratet MA, Antoshechkin I, Newberry KM, McCue K, Nesmith AS, Fisher-Aylor KI, Pusey B, DeSalvo G, Parker SL, Balasubramanian S, Davis NS, Meadows SK, Eggleston T, Gunter C, Newberry J, Levy SE, Absher DM, Mortazavi A, Wong WH, Wold B, Blow MJ, Visel A, Pennachio LA, Elnitski L, Margulies EH, Parker SC, Petrykowska HM, Abyzov A, Aken B, Barrell D, Barson G, Berry A, Bignell A, Boychenko V, Bussotti G, Chrast J, Davidson C, Derrien T, Despacio-Reyes G, Diekhans M, Ezkurdia I, Frankish A, Gilbert J, Gonzalez JM, Griffiths E, Harte R, Hendrix DA, Howald C, Hunt T, Jungreis I, Kay M, Khurana E, Kokocinski F, Leng J, Lin MF, Loveland J, Lu Z, Manthravadi D, Mariotti M, Mudge J, Mukherjee G, Notredame C, Pei B, Rodriguez JM, Saunders G, Sboner A, Searle S, Sisu C, Snow C, Steward C, Tanzer A, Tapanari E, Tress ML, van Baren MJ, Walters N, Washietl S, Wilming L, Zadissa A, Zhang Z, Brent M, Haussler D, Kellis M, Valencia A, Gerstein M, Reymond A, Guigó R, Harrow J, Hubbard TJ, Landt SG, Frietze S, Abyzov A, Addleman N, Alexander RP, Auerbach RK, Balasubramanian S, Bettinger K, Bhardwaj N, Boyle AP, Cao AR, Cayting P, Charos A, Cheng Y, Cheng C, Eastman C, Euskirchen G, Fleming JD, Grubert F, Habegger L, Hariharan M, Harmanci A, Iyengar S, Jin VX, Karczewski KJ, Kasowski M, Lacroute P, Lam H, Lamarre-Vincent N, Leng J, Lian J, Lindahl-Allen M, Min R, Miotto B, Monahan H, Moqtaderi Z, Mu XJ, O'Geen H, Ouyang Z, Patacsil D, Pei B, Raha D, Ramirez L, Reed B, Rozowsky J, Sboner A, Shi M, Sisu C, Slifer T, Witt H, Wu L, Xu X, Yan KK, Yang X, Yip KY, Zhang Z, Struhl K, Weissman SM, Gerstein M, Farnham PJ, Snyder M, Tenenbaum SA, Penalva LO, Doyle F, Karmakar S, Landt SG, Bhanvadia RR, Choudhury A, Domanus M, Ma L, Moran J, Patacsil D, Slifer T, Victorsen A, Yang X, Snyder M, Auer T, Centanin L, Eichenlaub M, Gruhl F, Heermann S, Hoeckendorf B, Inoue D, Kellner T, Kirchmaier S, Mueller C, Reinhardt R, Schertel L, Schneider S, Sinn R, Wittbrodt B, Wittbrodt J, Weng Z, Whitfield TW, Wang J, Collins PJ, Aldred SF, Trinklein ND, Partridge EC, Myers RM, Dekker J, Jain G, Lajoie BR, Sanyal A, Balasundaram G, Bates DL, Byron R, Canfield TK, Diegel MJ, Dunn D, Ebersol AK, Frum T, Garg K, Gist E, Hansen R, Boatman L, Haugen E, Humbert R, Jain G, Johnson AK, Johnson EM, Kutyavin TV, Lajoie BR, Lee K, Lotakis D, Maurano MT, Neph SJ, Neri FV, Nguyen ED, Qu H, Reynolds AP, Roach V, Rynes E, Sabo P, Sanchez ME, Sandstrom RS, Sanyal A, Shafer AO, Stergachis AB, Thomas S, Thurman RE, Vernot B, Vierstra J, Vong S, Wang H, Weaver MA, Yan Y, Zhang M, Akey JM, Bender M, Dorschner MO, Groudine M, MacCoss MJ, Navas P, Stamatoyannopoulos G, Kaul R, Dekker J, Stamatoyannopoulos JA, Dunham I, Beal K, Brazma A, Flicek P, Herrero J, Johnson N, Keefe D, Lukk M, Luscombe NM, Sobral D, Vaquerizas JM, Wilder SP, Batzoglou S, Sidow A, Hussami N, Kyriazopoulou-Panagiotopoulou S, Libbrecht MW, Schaub MA, Kundaje A, Hardison RC, Miller W, Giardine B, Harris RS, Wu W, Bickel PJ, Banfai B, Boley NP, Brown JB, Huang H, Li Q, Li JJ, Noble WS, Bilmes JA, Buske OJ, Hoffman MM, Sahu AD, Kharchenko PV, Park PJ, Baker D, Taylor J, Weng Z, Iyer S, Dong X, Greven M, Lin X, Wang J, Xi HS, Zhuang J, Gerstein M, Alexander RP, Balasubramanian S, Cheng C, Harmanci A, Lochovsky L, Min R, Mu XJ, Rozowsky J, Yan KK, Yip KY, Birney E., and Miotto, Benoit

Subjects
Encyclopedias as Topic, [SDV]Life Sciences [q-bio], DNA Footprinting, Genoma humà, Binding Sites/genetics, Histones/chemistry/metabolism, 0302 clinical medicine, Exons/genetics, ddc:576.5, 0303 health sciences, Multidisciplinary, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], DNA-Binding Proteins/metabolism, region, Chemistry, Genetic Predisposition to Disease/genetics, Genomics, Polymorphism, Single Nucleotide/genetics, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Neoplasms/genetics, Chromatin, Cell biology, in vivo, Genetic Variation/genetics, 030220 oncology & carcinogenesis, Deoxyribonuclease I/metabolism, Proteins/genetics, transcription factor-binding, chromosome conformation capture, DNA Methylation/genetics, Chromosomes, Human/genetics/metabolism, Chromatin Immunoprecipitation, Mammals/genetics, DNA/genetics, determinant, Article, 03 medical and health sciences, map, Animals, Humans, Transcription Factors/metabolism, Alleles, mouse, 030304 developmental biology, Transcription, Genetic/genetics, Chromatin/genetics/metabolism, Sequence Analysis, RNA, human cell, Molecular Sequence Annotation, Regulatory Sequences, Nucleic Acid/genetics, Promoter Regions, Genetic/genetics, DNA binding site, Genòmica, Genome, Human/genetics, chromatin, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Genètica, Genome-Wide Association Study
Abstract

The human genome encodes the blueprint of life, but the function of the vast majority of its nearly three billion bases is unknown. The Encyclopedia of DNA Elements (ENCODE) project has systematically mapped regions of transcription, transcription factor association, chromatin structure and histone modification. These data enabled us to assign biochemical functions for 80% of the genome, in particular outside of the well-studied protein-coding regions. Many discovered candidate regulatory elements are physically associated with one another and with expressed genes, providing new insights into the mechanisms of gene regulation. The newly identified elements also show a statistical correspondence to sequence variants linked to human disease, and can thereby guide interpretation of this variation. Overall, the project provides new insights into the organization and regulation of our genes and genome, and is an expansive resource of functional annotations for biomedical research. The Consortium is funded by grants from the NHGRI as follows: production grants: U54HG004570 (B. E. Bernstein); U01HG004695 (E. Birney); U54HG004563 (G. E. Crawford); U54HG004557 (T. R. Gingeras); U54HG004555 (T. J. Hubbard); U41HG004568 /n(W. J. Kent); U54HG004576 (R. M. Myers); U54HG004558 (M. Snyder);/nU54HG004592 (J. A. Stamatoyannopoulos). Pilot grants: R01HG003143 (J. Dekker); RC2HG005591 and R01HG003700 (M. C. Giddings); R01HG004456-03 (Y. Ruan); U01HG004571 (S. A. Tenenbaum); U01HG004561 (Z. Weng); RC2HG005679 (K. P. White). This project was supported in part by American Recovery and/nReinvestment Act (ARRA) funds from the NHGRI through grants U54HG004570, U54HG004563, U41HG004568, U54HG004592, R01HG003143, RC2HG005591,R01HG003541, U01HG004561, RC2HG005679andR01HG003988(L. Pennacchio). In addition, work from NHGRI Groups was supported by the Intramural Research/nProgram of the NHGRI (L. Elnitski, ZIAHG200323; E. H. Margulies, ZIAHG200341). Research in the Pennachio laboratory was performed at Lawrence Berkeley National Laboratory and at the United States Department of Energy Joint Genome Institute, Department of Energy Contract DE-AC02-05CH11231, University of California.

Published
2012
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15. Proteomics of Mycoplasma genitalium: identification and characterization of unannotated and atypical proteins in a small model genome

Author

Mark Gerstein, Suganthi Balasubramanian, Lynne Regan, and Tamara Schneider

Subjects
Proteome, Globular protein, Molecular Sequence Data, Proteomics, Genome, Article, Conserved sequence, Structural genomics, Open Reading Frames, Mycoplasma, Bacterial Proteins, Genetics, Animals, Humans, Amino Acid Sequence, ORFS, Conserved Sequence, chemistry.chemical_classification, biology, Sequence Homology, Amino Acid, biology.organism_classification, chemistry, Thermodynamics, Mycoplasma genitalium, Sequence Alignment, Genome, Bacterial
Abstract

We present the results of a comprehensive analysis of the proteome of Mycoplasma genitalium (MG), the smallest autonomously replicating organism that has been completely sequenced. Our aim was to identify and characterize all soluble proteins in MG that are structurally and functionally uncharacterized. We were particularly interested in identifying proteins that differed significantly from typical globular proteins, for example, proteins which are unstructured in the absence of a ‘partner’ molecule or those that exhibit unusual thermodynamic properties. This work is complementary to other structural genomics projects whose primary aim is to determine the threedimensional structures of proteins with unknown folds. We have identified all the full-length open reading frames (ORFs) in MG that have no homologs of known structure and are of unknown function. Twenty-five of the total 483 ORFs fall into this category and we have expressed, purified and characterized 11 of them. We have used circular dichroism (CD) to rapidly investigate their biophysical properties. Our studies reveal that these proteins have a wide range of structures varying from highly helical to partially structured to unfolded or random coil. They also display a variety of thermodynamic properties ranging from cooperative unfolding to no detectable unfolding upon thermal denaturation. Several of these proteins are highly conserved from mycoplasma to man. Further information about target selection and CD results is available at http:// bioinfo.mbb.yale.edu/genome

Published
2000

16. Comprehensive analysis of amino acid and nucleotide composition in eukaryotic genomes, comparing genes and pseudogenes

Author

Nicholas M. Luscombe, Zhaolei Zhang, Suganthi Balasubramanian, Nathaniel Echols, Paul M. Harrison, Paul Bertone, and Mark Gerstein

Subjects
Proteome, Chromosomes, Human, Pair 21, Pseudogene, Chromosomes, Human, Pair 20, Genomics, Saccharomyces cerevisiae, Genome, Article, Evolution, Molecular, chemistry.chemical_compound, Intergenic region, Bias, Databases, Genetic, Genetics, Animals, Humans, Amino Acid Sequence, Caenorhabditis elegans, Codon, Gene, Peptide sequence, Base Composition, Internet, Base Sequence, biology, biology.organism_classification, Drosophila melanogaster, Eukaryotic Cells, Genes, chemistry, Mutagenesis, Pseudogenes, DNA
Abstract

Based on searches for disabled homologs to known proteins, we have identified a large population of pseudogenes in four sequenced eukaryotic genomes—the worm, yeast, fly and human (chromosomes 21 and 22 only). Each of our nearly 2500 pseudogenes is characterized by one or more disablements mid-domain, such as premature stops and frameshifts. Here, we perform a comprehensive survey of the amino acid and nucleotide composition of these pseudogenes in comparison to that of functional genes and intergenic DNA. We show that pseudogenes invariably have an amino acid composition intermediate between genes and translated intergenic DNA. Although the degree of intermediacy varies among the four organisms, in all cases, it is most evident for amino acid types that differ most in occurrence between genes and intergenic regions. The same intermediacy also applies to codon frequencies, especially in the worm and human. Moreover, the intermediate composition of pseudogenes applies even though the composition of the genes in the four organisms is markedly different, showing a strong correlation with the overall A/T content of the genomic sequence. Pseudogenes can be divided into ‘ancient’ and ‘modern’ subsets, based on the level of sequence identity with their closest matching homolog (within the same genome). Modern pseudogenes usually have a much closer sequence composition to genes than ancient pseudogenes. Collectively, our results indicate that the composition of pseudogenes that are under no selective constraints progressively drifts from that of coding DNA towards non-coding DNA. Therefore, we propose that the degree to which pseudogenes approach a random sequence composition may be useful in dating different sets of pseudogenes, as well as to assess the rate at which intergenic DNA accumulates mutations. Our compositional analyses with the interactive viewer are available over the web at http://genecensus.org/pseudogene.

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