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1. Recommendations for clinical interpretation of variants found in non-coding regions of the genome

Author

Jamie M. Ellingford, Joo Wook Ahn, Richard D. Bagnall, Diana Baralle, Stephanie Barton, Chris Campbell, Kate Downes, Sian Ellard, Celia Duff-Farrier, David R. FitzPatrick, John M. Greally, Jodie Ingles, Neesha Krishnan, Jenny Lord, Hilary C. Martin, William G. Newman, Anne O’Donnell-Luria, Simon C. Ramsden, Heidi L. Rehm, Ebony Richardson, Moriel Singer-Berk, Jenny C. Taylor, Maggie Williams, Jordan C. Wood, Caroline F. Wright, Steven M. Harrison, and Nicola Whiffin

Subjects
Variant interpretation, Non-coding variation, Gene regulation, Medicine, Genetics, QH426-470
Abstract

Abstract Background The majority of clinical genetic testing focuses almost exclusively on regions of the genome that directly encode proteins. The important role of variants in non-coding regions in penetrant disease is, however, increasingly being demonstrated, and the use of whole genome sequencing in clinical diagnostic settings is rising across a large range of genetic disorders. Despite this, there is no existing guidance on how current guidelines designed primarily for variants in protein-coding regions should be adapted for variants identified in other genomic contexts. Methods We convened a panel of nine clinical and research scientists with wide-ranging expertise in clinical variant interpretation, with specific experience in variants within non-coding regions. This panel discussed and refined an initial draft of the guidelines which were then extensively tested and reviewed by external groups. Results We discuss considerations specifically for variants in non-coding regions of the genome. We outline how to define candidate regulatory elements, highlight examples of mechanisms through which non-coding region variants can lead to penetrant monogenic disease, and outline how existing guidelines can be adapted for the interpretation of these variants. Conclusions These recommendations aim to increase the number and range of non-coding region variants that can be clinically interpreted, which, together with a compatible phenotype, can lead to new diagnoses and catalyse the discovery of novel disease mechanisms.

Published
2022
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2. 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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3. Advanced variant classification framework reduces the false positive rate of predicted loss of function (pLoF) variants in population sequencing data

Author

Moriel Singer-Berk, Sanna Gudmundsson, Samantha Baxter, Eleanor G. Seaby, Eleina England, Jordan C. Wood, Rachel G. Son, Nicholas A. Watts, Konrad J. Karczewski, Steven M. Harrison, Daniel G. MacArthur, Heidi L. Rehm, and Anne O’Donnell-Luria

Subjects
Article
Abstract

Predicted loss of function (pLoF) variants are highly deleterious and play an important role in disease biology, but many of these variants may not actually result in loss-of-function. Here we present a framework that advances interpretation of pLoF variants in research and clinical settings by considering three categories of LoF evasion: (1) predicted rescue by secondary sequence properties, (2) uncertain biological relevance, and (3) potential technical artifacts. We also provide recommendations on adjustments to ACMG/AMP guidelines’s PVS1 criterion. Applying this framework to all high-confidence pLoF variants in 22 autosomal recessive disease-genes from the Genome Aggregation Database (gnomAD, v2.1.1) revealed predicted LoF evasion or potential artifacts in 27.3% (304/1,113) of variants. The major reasons were location in the last exon, in a homopolymer repeat, in low per-base expression (pext) score regions, or the presence of cryptic splice rescues. Variants predicted to be potential artifacts or to evade LoF were enriched for ClinVar benign variants. PVS1 was downgraded in 99.4% (162/163) of LoF evading variants assessed, with 17.2% (28/163) downgraded as a result of our framework, adding to previous guidelines. Variant pathogenicity was affected (mostly from likely pathogenic to VUS) in 20 (71.4%) of these 28 variants. This framework guides assessment of pLoF variants beyond standard annotation pipelines, and substantially reduces false positive rates, which is key to ensure accurate LoF variant prediction in both a research and clinical setting.

Published
2023
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