@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 {836, title = {A structural variation reference for medical and population genetics.}, journal = {Nature}, volume = {581}, year = {2020}, month = {2020 05}, pages = {444-451}, abstract = {

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

}, keywords = {Continental Population Groups, Disease, Female, Genetic Testing, Genetic Variation, Genetics, Medical, Genetics, Population, Genome, Human, Genotyping Techniques, Humans, Male, Middle Aged, Mutation, Polymorphism, Single Nucleotide, Reference Standards, Selection, Genetic, Whole Genome Sequencing}, issn = {1476-4687}, doi = {10.1038/s41586-020-2287-8}, author = {Collins, Ryan L and Brand, Harrison and Karczewski, Konrad J and Zhao, Xuefang and Alf{\"o}ldi, Jessica and Francioli, Laurent C and Khera, Amit V and Lowther, Chelsea and Gauthier, Laura D and Wang, Harold and Watts, Nicholas A and Solomonson, Matthew and O{\textquoteright}Donnell-Luria, Anne and Baumann, Alexander and Munshi, Ruchi and Walker, Mark and Whelan, Christopher W and Huang, Yongqing and Brookings, Ted and Sharpe, Ted and Stone, Matthew R and Valkanas, Elise and Fu, Jack and Tiao, Grace and Laricchia, Kristen M and Ruano-Rubio, Valentin and Stevens, Christine and Gupta, Namrata and Cusick, Caroline and Margolin, Lauren and Taylor, Kent D and Lin, Henry J and Rich, Stephen S and Post, Wendy S and Chen, Yii-Der Ida and Rotter, Jerome I and Nusbaum, Chad and Philippakis, Anthony and Lander, Eric and Gabriel, Stacey and Neale, Benjamin M and Kathiresan, Sekar and Daly, Mark J and Banks, Eric and MacArthur, Daniel G and Talkowski, Michael E} }