@article {785, title = {Landscape of multi-nucleotide variants in 125,748 human exomes and 15,708 genomes.}, journal = {Nat Commun}, volume = {11}, year = {2020}, month = {2020 05 27}, pages = {2539}, abstract = {

Multi-nucleotide variants (MNVs), defined as two or more nearby variants existing on the same haplotype in an individual, are a clinically and biologically important class of genetic variation. However, existing tools typically do not accurately classify MNVs, and understanding of their mutational origins remains limited. Here, we systematically survey MNVs in 125,748 whole exomes and 15,708 whole genomes from the Genome Aggregation Database (gnomAD). We identify 1,792,248 MNVs across the genome with constituent variants falling within 2 bp distance of one another, including 18,756 variants with a novel combined effect on protein sequence. Finally, we estimate the relative impact of known mutational mechanisms - CpG deamination, replication error by polymerase zeta, and polymerase slippage at repeat junctions - on the generation of MNVs. Our results demonstrate the value of haplotype-aware variant annotation, and refine our understanding of genome-wide mutational mechanisms of MNVs.

}, keywords = {CpG Islands, Databases, Genetic, DNA Mutational Analysis, Exome, Genetic Variation, Genome, Human, Humans, Mutation}, issn = {2041-1723}, doi = {10.1038/s41467-019-12438-5}, author = {Wang, Qingbo and Pierce-Hoffman, Emma and Cummings, Beryl B and Alf{\"o}ldi, Jessica and Francioli, Laurent C and Gauthier, Laura D and Hill, Andrew J and O{\textquoteright}Donnell-Luria, Anne H and Karczewski, Konrad J and MacArthur, Daniel G} } @article {784, title = {The mutational constraint spectrum quantified from variation in 141,456 humans.}, journal = {Nature}, volume = {581}, year = {2020}, month = {2020 05}, pages = {434-443}, 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. 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.

}, keywords = {Adult, Brain, Cardiovascular Diseases, Cohort Studies, Databases, Genetic, Exome, Female, Genes, Essential, Genetic Predisposition to Disease, Genetic Variation, Genome, Human, Genome-Wide Association Study, Humans, Loss of Function Mutation, Male, Mutation Rate, Proprotein Convertase 9, Reproducibility of Results, RNA, Messenger, Whole Exome Sequencing, Whole Genome Sequencing}, issn = {1476-4687}, doi = {10.1038/s41586-020-2308-7}, author = {Karczewski, Konrad J and Francioli, Laurent C and Tiao, Grace and Cummings, Beryl B and Alf{\"o}ldi, Jessica and Wang, Qingbo and Collins, Ryan L and Laricchia, Kristen M and Ganna, Andrea and Birnbaum, Daniel P and Gauthier, Laura D and Brand, Harrison and Solomonson, Matthew and Watts, Nicholas A and Rhodes, Daniel and Singer-Berk, Moriel and England, Eleina M and Seaby, Eleanor G and Kosmicki, Jack A and Walters, Raymond K and Tashman, Katherine and Farjoun, Yossi and Banks, Eric and Poterba, Timothy and Wang, Arcturus and Seed, Cotton and Whiffin, Nicola and Chong, Jessica X and Samocha, Kaitlin E and Pierce-Hoffman, Emma and Zappala, Zachary and O{\textquoteright}Donnell-Luria, Anne H and Minikel, Eric Vallabh and Weisburd, Ben and Lek, Monkol and Ware, James S and Vittal, Christopher and Armean, Irina M and Bergelson, Louis and Cibulskis, Kristian and Connolly, Kristen M and Covarrubias, Miguel and Donnelly, Stacey and Ferriera, Steven and Gabriel, Stacey and Gentry, Jeff and Gupta, Namrata and Jeandet, Thibault and Kaplan, Diane and Llanwarne, Christopher and Munshi, Ruchi and Novod, Sam and Petrillo, Nikelle and Roazen, David and Ruano-Rubio, Valentin and Saltzman, Andrea and Schleicher, Molly and Soto, Jose and Tibbetts, Kathleen and Tolonen, Charlotte and Wade, Gordon and Talkowski, Michael E and Neale, Benjamin M and Daly, Mark J and MacArthur, Daniel G} } @article {732, title = {The Genetic Landscape of Diamond-Blackfan Anemia.}, journal = {Am J Hum Genet}, volume = {104}, year = {2019}, month = {2019 Feb 07}, pages = {356}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2018.12.011}, author = {Ulirsch, Jacob C and Verboon, Jeffrey M and Kazerounian, Shideh and Guo, Michael H and Yuan, Daniel and Ludwig, Leif S and Handsaker, Robert E and Abdulhay, Nour J and Fiorini, Claudia and Genovese, Giulio and Lim, Elaine T and Cheng, Aaron and Cummings, Beryl B and Chao, Katherine R and Beggs, Alan H and Genetti, Casie A and Sieff, Colin A and Newburger, Peter E and Niewiadomska, Edyta and Matysiak, Michal and Vlachos, Adrianna and Lipton, Jeffrey M and Atsidaftos, Eva and Glader, Bertil and Narla, Anupama and Gleizes, Pierre-Emmanuel and O{\textquoteright}Donohue, Marie-Fran{\c c}oise and Montel-Lehry, Nathalie and Amor, David J and McCarroll, Steven A and O{\textquoteright}Donnell-Luria, Anne H and Gupta, Namrata and Gabriel, Stacey B and MacArthur, Daniel G and Lander, Eric S and Lek, Monkol and Da Costa, Lydie and Nathan, David G and Korostelev, Andrei A and Do, Ron and Sankaran, Vijay G and Gazda, Hanna T} } @article {678, title = {Heterozygous Variants in KMT2E Cause a Spectrum of Neurodevelopmental Disorders and Epilepsy.}, journal = {Am J Hum Genet}, volume = {104}, year = {2019}, month = {2019 Jun 06}, pages = {1210-1222}, abstract = {

We delineate a KMT2E-related neurodevelopmental disorder on the basis of 38 individuals in 36 families. This study includes 31 distinct heterozygous variants in KMT2E (28 ascertained from Matchmaker Exchange and three previously reported), and four individuals with chromosome 7q22.2-22.23 microdeletions encompassing KMT2E (one previously reported). Almost all variants occurred de novo, and most were truncating. Most affected individuals with protein-truncating variants presented with mild intellectual disability. One-quarter of individuals met criteria for autism. Additional common features include macrocephaly, hypotonia, functional gastrointestinal abnormalities, and a subtle facial gestalt. Epilepsy was present in about one-fifth of individuals with truncating variants and was responsive to treatment with anti-epileptic medications in almost all. More than 70\% of the individuals were male, and expressivity was variable by sex; epilepsy was more common in females and autism more common in males. The four individuals with microdeletions encompassing KMT2E generally presented similarly to those with truncating variants, but the degree of developmental delay was greater. The group of four individuals with missense variants in KMT2E presented with the most severe developmental delays. Epilepsy was present in all individuals with missense variants, often manifesting as treatment-resistant infantile epileptic encephalopathy. Microcephaly was also common in this group. Haploinsufficiency versus gain-of-function or dominant-negative effects specific to these missense variants in KMT2E might explain this divergence in phenotype, but requires independent validation. Disruptive variants in KMT2E are an under-recognized cause of neurodevelopmental abnormalities.

}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2019.03.021}, author = {O{\textquoteright}Donnell-Luria, Anne H and Pais, Lynn S and Faundes, V{\'\i}ctor and Wood, Jordan C and Sveden, Abigail and Luria, Victor and Abou Jamra, Rami and Accogli, Andrea and Amburgey, Kimberly and Anderlid, Britt Marie and Azzarello-Burri, Silvia and Basinger, Alice A and Bianchini, Claudia and Bird, Lynne M and Buchert, Rebecca and Carr{\'e}, Wilfrid and Ceulemans, Sophia and Charles, Perrine and Cox, Helen and Culliton, Lisa and Curr{\`o}, Aurora and Demurger, Florence and Dowling, James J and Duban-Bedu, Benedicte and Dubourg, Christ{\`e}le and Eiset, Saga Elise and Escobar, Luis F and Ferrarini, Alessandra and Haack, Tobias B and Hashim, Mona and Heide, Solveig and Helbig, Katherine L and Helbig, Ingo and Heredia, Raul and H{\'e}ron, Delphine and Isidor, Bertrand and Jonasson, Amy R and Joset, Pascal and Keren, Boris and Kok, Fernando and Kroes, Hester Y and Lavillaureix, Alino{\"e} and Lu, Xin and Maas, Saskia M and Maegawa, Gustavo H B and Marcelis, Carlo L M and Mark, Paul R and Masruha, Marcelo R and McLaughlin, Heather M and McWalter, Kirsty and Melchinger, Esther U and Mercimek-Andrews, Saadet and Nava, Caroline and Pendziwiat, Manuela and Person, Richard and Ramelli, Gian Paolo and Ramos, Luiza L P and Rauch, Anita and Reavey, Caitlin and Renieri, Alessandra and Rie{\ss}, Angelika and Sanchez-Valle, Amarilis and Sattar, Shifteh and Saunders, Carol and Schwarz, Niklas and Smol, Thomas and Srour, Myriam and Steindl, Katharina and Syrbe, Steffen and Taylor, Jenny C and Telegrafi, Aida and Thiffault, Isabelle and Trauner, Doris A and van der Linden, Helio and van Koningsbruggen, Silvana and Villard, Laurent and Vogel, Ida and Vogt, Julie and Weber, Yvonne G and Wentzensen, Ingrid M and Widjaja, Elysa and Zak, Jaroslav and Baxter, Samantha and Banka, Siddharth and Rodan, Lance H} } @article {595, title = {Insights into genetics, human biology and disease gleaned from family based genomic studies.}, journal = {Genet Med}, volume = {21}, year = {2019}, month = {2019 04}, pages = {798-812}, abstract = {

Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of >75\% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in~novel "disease gene" discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.

}, keywords = {Databases, Genetic, Genetic Diseases, Inborn, Genetic Heterogeneity, Genetic Predisposition to Disease, Genome, Human, Genomics, Humans, National Institutes of Health (U.S.), Pedigree, United States, Whole Exome Sequencing}, issn = {1530-0366}, doi = {10.1038/s41436-018-0408-7}, author = {Posey, Jennifer E and O{\textquoteright}Donnell-Luria, Anne H and Chong, Jessica X and Harel, Tamar and Jhangiani, Shalini N and Coban Akdemir, Zeynep H and Buyske, Steven and Pehlivan, Davut and Carvalho, Claudia M B and Baxter, Samantha and Sobreira, Nara and Liu, Pengfei and Wu, Nan and Rosenfeld, Jill A and Kumar, Sushant and Avramopoulos, Dimitri and White, Janson J and Doheny, Kimberly F and Witmer, P Dane and Boehm, Corinne and Sutton, V Reid and Muzny, Donna M and Boerwinkle, Eric and G{\"u}nel, Murat and Nickerson, Deborah A and Mane, Shrikant and MacArthur, Daniel G and Gibbs, Richard A and Hamosh, Ada and Lifton, Richard P and Matise, Tara C and Rehm, Heidi L and Gerstein, Mark and Bamshad, Michael J and Valle, David and Lupski, James R} } @article {653, title = {Unique bioinformatic approach and comprehensive reanalysis improve diagnostic yield of clinical exomes.}, journal = {Eur J Hum Genet}, year = {2019}, month = {2019 Apr 12}, abstract = {

Clinical exome sequencing (CES) is increasingly being utilized; however, a large proportion of patients remain undiagnosed, creating a need for a systematic approach to increase the diagnostic yield. We have reanalyzed CES data for a clinically heterogeneous cohort of 102 probands with likely Mendelian conditions, including 74 negative cases and 28 cases with candidate variants, but reanalysis requested by clinicians. Reanalysis was performed by an interdisciplinary team using a validated custom-built pipeline, "Variant Explorer Pipeline" (VExP). This reanalysis approach and results were compared with existing literature. Reanalysis of candidate variants from CES in 28 cases revealed 1 interpretation that needed to be reclassified. A confirmed or potential genetic diagnosis was identified in 24 of 75 CES-negative/reclassified cases (32.0\%), including variants in known disease-causing genes (n = 6) or candidate genes (n = 18). This yield was higher compared with similar studies demonstrating the utility of this approach. In summary, reanalysis of negative CES in a research setting enhances diagnostic yield by about a third. This study suggests the need for comprehensive, continued reanalysis of exome data when molecular diagnosis is elusive.

}, issn = {1476-5438}, doi = {10.1038/s41431-019-0401-x}, author = {Schmitz-Abe, Klaus and Li, Qifei and Rosen, Samantha M and Nori, Neeharika and Madden, Jill A and Genetti, Casie A and Wojcik, Monica H and Ponnaluri, Sadhana and Gubbels, Cynthia S and Picker, Jonathan D and O{\textquoteright}Donnell-Luria, Anne H and Yu, Timothy W and Bodamer, Olaf and Brownstein, Catherine A and Beggs, Alan H and Agrawal, Pankaj B} } @article {578, title = {The Genetic Landscape of Diamond-Blackfan Anemia.}, journal = {Am J Hum Genet}, volume = {103}, year = {2018}, month = {2018 12 06}, pages = {930-947}, abstract = {

Diamond-Blackfan anemia (DBA) is a rare bone marrow failure disorder that affects 7 out of 1,000,000 live births and has been associated with mutations in components of the ribosome. In order to characterize the genetic landscape of this heterogeneous disorder, we recruited a cohort of 472 individuals with a clinical diagnosis of DBA and performed whole-exome sequencing (WES). We identified relevant rare and predicted damaging mutations for 78\% of individuals. The majority of mutations were singletons, absent from population databases, predicted to cause loss of function, and located in 1 of 19 previously reported ribosomal protein (RP)-encoding genes. Using exon coverage estimates, we identified and validated 31 deletions in RP genes. We also observed an enrichment for extended splice site mutations and validated their diverse effects using RNA sequencing in cell lines obtained from individuals with DBA. Leveraging the size of our cohort, we observed robust genotype-phenotype associations with congenital abnormalities and treatment outcomes. We further identified rare mutations in seven previously unreported RP genes that may cause DBA, as well as several distinct disorders that appear to phenocopy DBA, including nine individuals with biallelic CECR1 mutations that result in deficiency of ADA2. However, no new genes were identified at exome-wide significance, suggesting that there are no unidentified genes containing mutations readily identified by WES that explain >5\% of DBA-affected case subjects. Overall, this report should inform not only clinical practice for DBA-affected individuals, but also the design and analysis of rare variant studies for heterogeneous Mendelian disorders.

}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2018.10.027}, author = {Ulirsch, Jacob C and Verboon, Jeffrey M and Kazerounian, Shideh and Guo, Michael H and Yuan, Daniel and Ludwig, Leif S and Handsaker, Robert E and Abdulhay, Nour J and Fiorini, Claudia and Genovese, Giulio and Lim, Elaine T and Cheng, Aaron and Cummings, Beryl B and Chao, Katherine R and Beggs, Alan H and Genetti, Casie A and Sieff, Colin A and Newburger, Peter E and Niewiadomska, Edyta and Matysiak, Michal and Vlachos, Adrianna and Lipton, Jeffrey M and Atsidaftos, Eva and Glader, Bertil and Narla, Anupama and Gleizes, Pierre-Emmanuel and O{\textquoteright}Donohue, Marie-Fran{\c c}oise and Montel-Lehry, Nathalie and Amor, David J and McCarroll, Steven A and O{\textquoteright}Donnell-Luria, Anne H and Gupta, Namrata and Gabriel, Stacey B and MacArthur, Daniel G and Lander, Eric S and Lek, Monkol and Da Costa, Lydie and Nathan, David G and Korostelev, Andrei A and Do, Ron and Sankaran, Vijay G and Gazda, Hanna T} } @article {511, title = {matchbox: An open-source tool for patient matching via the Matchmaker Exchange.}, journal = {Hum Mutat}, volume = {39}, year = {2018}, month = {2018 Dec}, pages = {1827-1834}, abstract = {

Rare disease investigators constantly face challenges in identifying additional cases to build evidence for gene-disease causality. The Matchmaker Exchange (MME) addresses this limitation by providing a mechanism for matching patients across genomic centers via a federated network. The MME has revolutionized searching for additional cases by making it possible to query across institutional boundaries, so that what was once a laborious and manual process of contacting researchers is now automated and computable. However, while the MME network is beginning to scale, the growth of additional nodes is limited by the lack of easy-to-use solutions that can be implemented by any rare disease database owner, even one without significant software engineering resources. Here, we describe matchbox, which is an open-source, platform-independent, portable bridge between any given rare disease genomic center and the MME network, which has already led to novel gene discoveries. We also describe how matchbox greatly reduces the barrier to participation by overcoming challenges for new databases to join the MME.

}, issn = {1098-1004}, doi = {10.1002/humu.23655}, author = {Arachchi, Harindra and Wojcik, Monica H and Weisburd, Benjamin and Jacobsen, Julius O B and Valkanas, Elise and Baxter, Samantha and Byrne, Alicia B and O{\textquoteright}Donnell-Luria, Anne H and Haendel, Melissa and Smedley, Damian and MacArthur, Daniel G and Philippakis, Anthony A and Rehm, Heidi L} } @article {364, title = {Improving genetic diagnosis in Mendelian disease with transcriptome sequencing.}, journal = {Sci Transl Med}, volume = {9}, year = {2017}, month = {2017 04 19}, abstract = {

Exome and whole-genome sequencing are becoming increasingly routine approaches in Mendelian disease diagnosis. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25 to 50\%. We explore the utility of transcriptome sequencing [RNA sequencing (RNA-seq)] as a complementary diagnostic tool in a cohort of 50 patients with genetically undiagnosed rare muscle disorders. We describe an integrated approach to analyze patient muscle RNA-seq, leveraging an analysis framework focused on the detection of transcript-level changes that are unique to the patient compared to more than 180 control skeletal muscle samples. We demonstrate the power of RNA-seq to validate candidate splice-disrupting mutations and to identify splice-altering variants in both exonic and deep intronic regions, yielding an overall diagnosis rate of 35\%. We also report the discovery of a highly recurrent de novo intronic mutation in that results in a dominantly acting splice-gain event, disrupting the critical glycine repeat motif of the triple helical domain. We identify this pathogenic variant in a total of 27 genetically unsolved patients in an external collagen VI-like dystrophy cohort, thus explaining approximately 25\% of patients clinically suggestive of having collagen VI dystrophy in whom prior genetic analysis is negative. Overall, this study represents a large systematic application of transcriptome sequencing to rare disease diagnosis and highlights its utility for the detection and interpretation of variants missed by current standard diagnostic approaches.

}, keywords = {Collagen Type VI, High-Throughput Nucleotide Sequencing, Humans, Muscular Diseases, Mutation, Transcriptome}, issn = {1946-6242}, doi = {10.1126/scitranslmed.aal5209}, author = {Cummings, Beryl B and Marshall, Jamie L and Tukiainen, Taru and Lek, Monkol and Donkervoort, Sandra and Foley, A Reghan and Bolduc, Veronique and Waddell, Leigh B and Sandaradura, Sarah A and O{\textquoteright}Grady, Gina L and Estrella, Elicia and Reddy, Hemakumar M and Zhao, Fengmei and Weisburd, Ben and Karczewski, Konrad J and O{\textquoteright}Donnell-Luria, Anne H and Birnbaum, Daniel and Sarkozy, Anna and Hu, Ying and Gonorazky, Hernan and Claeys, Kristl and Joshi, Himanshu and Bournazos, Adam and Oates, Emily C and Ghaoui, Roula and Davis, Mark R and Laing, Nigel G and Topf, Ana and Kang, Peter B and Beggs, Alan H and North, Kathryn N and Straub, Volker and Dowling, James J and Muntoni, Francesco and Clarke, Nigel F and Cooper, Sandra T and B{\"o}nnemann, Carsten G and MacArthur, Daniel G} }