The mutational constraint spectrum quantified from variation in 141,456 humans
Open accessPreprint — published as 10.1038/s41586-020-2308-7 · Paper page
Abstract
Summary: Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes critical for an organism’s function will be depleted for such variants in natural populations, while non-essential genes will tolerate their accumulation. However, predicted loss-of-function (pLoF) 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 1 . Here, we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence pLoF variants in this cohort after filtering for sequencing and annotation artifacts. Using an improved human mutation rate model, we classify human protein-coding genes along a spectrum representing tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve gene discovery power for both common and rare diseases.
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Increasing availability of reference datasets cataloguing population genetic variation across diverse ethnic backgrounds has supported robust causal inference.
“Increasing availability of reference datasets cataloguing population genetic variation across diverse ethnic backgrounds has supported robust causal inference2,3,5,6.”
From A brief history of human disease genetics (2020) · cites this paper as [6]
Access to resources cataloguing genetic variation across populations has enabled confident exclusion of variants too common to be plausible causes of rare, penetrant early-onset genetic diseases.
“Access to resources that catalogue genetic variation across populations (such as ExAC and its successor gnomAD)5,6 has enabled the confident exclusion of genetic variants too common in population-level data to be plausible causes of rare, penetrant early-onset genetic diseases24.”
From A brief history of human disease genetics (2020) · cites this paper as [6]
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UMAP: Uniform Manifold Approximation and Projection
McInnes, L., Healy, J., Saul, N., & Großberger, L. (2018) · Journal of Open Source Software · doi:10.21105/joss.00861 · Cited by 9,826 · see citing works
Analysis of protein-coding genetic variation in 60,706 humans
Exome Aggregation Consortium, Lek, M., Karczewski, K. J., Minikel, E. V., Samocha, K. E., Banks, E., Fennell, T., O’Donnell-Luria, A. H., Ware, J. S., Hill, A. J., et al. (2016) · Nature · doi:10.1038/nature19057 · Cited by 9,587 · see citing works
Self-citationAn integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711 · see citing works
Genetic effects on gene expression across human tissues
GTEx Consortium (2017) · Nature · doi:10.1038/nature24277 · Cited by 4,036 · see citing works
Self-citationSequence Variations in <i>PCSK9,</i> Low LDL, and Protection against Coronary Heart Disease
Cohen, J. C., Boerwinkle, E., Mosley, T. H., & Hobbs, H. H. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa054013 · Cited by 3,181 · see citing works
Clinical use of current polygenic risk scores may exacerbate health disparities
Martin, A. R., Kanai, M., Kamatani, Y., Okada, Y., Neale, B. M., & Daly, M. J. (2019) · Nature Genetics · doi:10.1038/s41588-019-0379-x · Cited by 2,831 · see citing works
Self-citationCurrent clinical use of polygenic scores will risk exacerbating health disparities
Martin, A. R., Kanai, M., Kamatani, Y., Okada, Y., Neale, B. M., & Daly, M. J. (2018) · doi:10.1101/441261 · Cited by 2,813 · see citing works
Self-citationPatterns and rates of exonic de novo mutations in autism spectrum disorders
Neale, B. M., Kou, Y., Liu, L., Ma’ayan, A., Samocha, K. E., Sabo, A., Lin, C.-F., Stevens, C., Wang, L.-S., Makarov, V., et al. (2012) · Nature · doi:10.1038/nature11011 · Cited by 1,734 · see citing works
Self-citationDe novo mutations in schizophrenia implicate synaptic networks
Fromer, M., Pocklington, A. J., Kavanagh, D. H., Williams, H. J., Dwyer, S., Gormley, P., Georgieva, L., Rees, E., Palta, P., Ruderfer, D. M., et al. (2014) · Nature · doi:10.1038/nature12929 · Cited by 1,617 · see citing works
Self-citationA Systematic Survey of Loss-of-Function Variants in Human Protein-Coding Genes
MacArthur, D. G., Balasubramanian, S., Frankish, A., Huang, N., Morris, J., Walter, K., Jostins, L., Habegger, L., Pickrell, J. K., Montgomery, S. B., et al. (2012) · Science · doi:10.1126/science.1215040 · Cited by 1,272 · see citing works
Self-citationGenetic compensation triggered by mutant mRNA degradation
El-Brolosy, M. A., Kontarakis, Z., Rossi, A., Kuenne, C., Günther, S., Fukuda, N., Kikhi, K., Boezio, G. L. M., Takacs, C. M., Lai, S.-L., et al. (2019) · Nature · doi:10.1038/s41586-019-1064-z · Cited by 1,028 · see citing works
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Samocha, K. E., Robinson, E. B., Sanders, S. J., Stevens, C., Sabo, A., McGrath, L. M., Kosmicki, J. A., Rehnström, K., Mallick, S., Kirby, A., et al. (2014) · Nature Genetics · doi:10.1038/ng.3050 · Cited by 979 · see citing works
Self-citationGenic Intolerance to Functional Variation and the Interpretation of Personal Genomes
Petrovski, S., Wang, Q., Heinzen, E. L., Allen, A. S., & Goldstein, D. B. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003709 · Cited by 901 · see citing works
Self-citationAccurate classification of BRCA1 variants with saturation genome editing
Findlay, G. M., Daza, R. M., Martin, B., Zhang, M. D., Leith, A. P., Gasperini, M., Janizek, J. D., Huang, X., Starita, L. M., & Shendure, J. (2018) · Nature · doi:10.1038/s41586-018-0461-z · Cited by 843 · see citing works
Integrating human sequence data sets provides a resource of benchmark SNP and indel genotype calls
Zook, J. M., Chapman, B., Wang, J., Mittelman, D., Hofmann, O., Hide, W., & Salit, M. (2014) · Nature Biotechnology · doi:10.1038/nbt.2835 · Cited by 800 · see citing works
The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities
Chong, J. X., Buckingham, K. J., Jhangiani, S. N., Boehm, C., Sobreira, N., Smith, J. D., Harrell, T. M., McMillin, M. J., Wiszniewski, W., Gambin, T., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.06.009 · Cited by 643 · see citing works
Self-citationEvaluation and Design of Genome-Wide CRISPR/SpCas9 Knockout Screens
Hart, T., Tong, A. H. Y., Chan, K., Van Leeuwen, J., Seetharaman, A., Aregger, M., Chandrashekhar, M., Hustedt, N., Seth, S., Noonan, A., et al. (2017) · G3 Genes|Genomes|Genetics · doi:10.1534/g3.117.041277 · Cited by 599 · see citing works
Parental influence on human germline de novo mutations in 1,548 trios from Iceland
Jónsson, H., Sulem, P., Kehr, B., Kristmundsdottir, S., Zink, F., Hjartarson, E., Hardarson, M. T., Hjorleifsson, K. E., Eggertsson, H. P., Gudjonsson, S. A., et al. (2017) · Nature · doi:10.1038/nature24018 · Cited by 561 · see citing works
Zook, J. M., Chapman, B., Wang, J. J., et al. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1307.4661 · Cited by 551 · see citing works
Predicting the clinical impact of human mutation with deep neural networks
Sundaram, L., Gao, H., Padigepati, S. R., McRae, J. F., Li, Y., Kosmicki, J. A., Fritzilas, N., Hakenberg, J., Dutta, A., Shon, J. C., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0167-z · Cited by 482 · see citing works
Self-citationIncreased burden of ultra-rare protein-altering variants among 4,877 individuals with schizophrenia
Genovese, G., Fromer, M., Stahl, E. A., Ruderfer, D. M., Chambert, K., Landén, M., Moran, J. L., Purcell, S. M., Sklar, P., Sullivan, P. F., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4402 · Cited by 444 · see citing works
Knockouts model the 100 best-selling drugs—will they model the next 100?
Zambrowicz, B., & Sands, A. (2002) · Nature Reviews Drug Discovery · doi:10.1038/nrd987 · Cited by 393 · see citing works
The Mouse Genome Database (MGD): facilitating mouse as a model for human biology and disease
Eppig, J. T., Blake, J. A., Bult, C. J., Kadin, J. A., Richardson, J. E., & The Mouse Genome Database Group (2014) · Nucleic Acids Research · doi:10.1093/nar/gku967 · Cited by 358 · see citing works
Kosmicki, J. A., Samocha, K. E., Howrigan, D. P., Sanders, S. J., Slowikowski, K., Lek, M., Karczewski, K. J., Cutler, D. J., Devlin, B., Roeder, K., et al. (2017) · Nature Genetics · doi:10.1038/ng.3789 · Cited by 340 · see citing works
Self-citationEstimating the mutation load in human genomes
Henn, B. M., Botigué, L. R., Bustamante, C. D., Clark, A. G., & Gravel, S. (2015) · Nature Reviews Genetics · doi:10.1038/nrg3931 · Cited by 281 · see citing works
De novo mutations in regulatory elements in neurodevelopmental disorders
Short, P. J., McRae, J. F., Gallone, G., Sifrim, A., Won, H., Geschwind, D. H., Wright, C. F., Firth, H. V., FitzPatrick, D. R., Barrett, J. C., et al. (2018) · Nature · doi:10.1038/nature25983 · Cited by 274 · see citing works
Mendelian Gene Discovery: Fast and Furious with No End in Sight
Bamshad, M. J., Nickerson, D. A., & Chong, J. X. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.07.011 · Cited by 243 · see citing works
Self-citationUsing next-generation sequencing to isolate mutant genes from forward genetic screens
Schneeberger, K. (2014) · Nature reviews genetics · doi:10.1038/nrg3745 · Cited by 233 · see citing works
Singh, T., Walters, J. T. R., Johnstone, M., Curtis, D., Suvisaari, J., Torniainen, M., Rees, E., Iyegbe, C., Blackwood, D., McIntosh, A. M., et al. (2017) · Nature Genetics · doi:10.1038/ng.3903 · Cited by 231 · see citing works
A synthetic-diploid benchmark for accurate variant-calling evaluation
Li, H., Bloom, J. M., Farjoun, Y., Fleharty, M., Gauthier, L. D., Neale, B. M., & MacArthur, D. G. (2018) · Nature Methods · doi:10.1038/s41592-018-0054-7 · Cited by 231 · see citing works
Self-citationSettling the score: variant prioritization and Mendelian disease
Eilbeck, K. L., Quinlan, A. R., & Yandell, M. D. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2017.52 · Cited by 221 · see citing works
CRISPR-Cas9-based mutagenesis frequently provokes on-target mRNA misregulation
Tuladhar, R., Yeu, Y., Tyler Piazza, J., Tan, Z., Rene Clemenceau, J., Wu, X., Barrett, Q., Herbert, J., Mathews, D. H., Kim, J., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12028-5 · Cited by 219 · see citing works
Evaluating drug targets through human loss-of-function genetic variation
Minikel, E. V., Karczewski, K. J., Martin, H. C., Cummings, B. B., Whiffin, N., Rhodes, D., Alföldi, J., Trembath, R. C., van Heel, D. A., Daly, M. J., et al. (2020) · Nature · doi:10.1038/s41586-020-2267-z · Cited by 182 · see citing works
Self-citationEstimating the selective effects of heterozygous protein-truncating variants from human exome data
Cassa, C. A., Weghorn, D., Balick, D. J., Jordan, D. M., Nusinow, D. P., Samocha, K. E., O’Donnell‐Luria, A., MacArthur, D. G., Daly, M. J., Beier, D. R., et al. (2017) · Nature Genetics · doi:10.1038/ng.3831 · Cited by 151 · see citing works
Self-citationMouseMine: a new data warehouse for MGI
Motenko, H., Neuhauser, S. B., O’Keefe, M., & Richardson, J. E. (2015) · Mammalian Genome · doi:10.1007/s00335-015-9573-z · Cited by 133 · see citing works
The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity
Petrovski, S., Gussow, A. B., Wang, Q., Halvorsen, M., Han, Y., Weir, W. H., Allen, A. S., & Goldstein, D. B. (2015) · PLoS Genetics · doi:10.1371/journal.pgen.1005492 · Cited by 126 · see citing works
Self-citationMedical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study
DeBoever, C., Tanigawa, Y., Lindholm, M. E., McInnes, G., Lavertu, A., Ingelsson, E., Chang, C. C., Ashley, E. A., Bustamante, C. D., Daly, M. J., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03910-9 · Cited by 122 · see citing works
Self-citationQuantifying the impact of rare and ultra-rare coding variation across the phenotypic spectrum
Ganna, A., Satterstrom, F. K., Zekavat, S. M., Das, I., Kurki, M. I., Churchhouse, C., Alfoldi, J., Martin, A. R., Havulinna, A. S., Byrnes, A., et al. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.05.002 · Cited by 110 · see citing works
Self-citationVariable population prevalence estimates of germline TP53 variants: A gnomAD-based analysis
de Andrade, K. C., Frone, M. N., Wegman-Ostrosky, T., Khincha, P. P., Kim, J., Amadou, A., Santiago, K. M., Fortes, F. P., Lemonnier, N., Mirabello, L. J., et al. (2018) · Human Mutation · doi:10.1002/humu.23673 · Cited by 99 · see citing works
Ganna, A., Genovese, G., Howrigan, D. P., Byrnes, A., Kurki, M., Zekavat, S. M., Whelan, C. W., Kals, M., Nivard, M. G., Bloemendal, A., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4404 · Cited by 89 · see citing works
Self-citationEmdin, C. A., Khera, A. V., Chaffin, M. D., Klarin, D. M., Natarajan, P., Aragam, K. G., Haas, M. E., Bick, A. G., Zekavat, S. M., Nomura, A., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03911-8 · Cited by 89 · see citing works
Self-citationGravel, S. (2016) · Genetics · doi:10.1534/genetics.115.184630 · Cited by 81 · see citing works
Evidence for Weak Selective Constraint on Human Gene Expression
Glassberg, E. C., Gao, Z., Harpak, A., Lan, X., & Pritchard, J. K. (2018) · Genetics · doi:10.1534/genetics.118.301833 · Cited by 63 · see citing works
An open resource of structural variation for medical and population geneticsPreprint
Collins, R. L., Brand, H., Karczewski, K. J., Zhao, X., Alföldi, J., Francioli, L. C., Khera, A. V., Lowther, C., Gauthier, L. D., Wang, H., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/578674 · Cited by 61 · see citing works
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Landscape of multi-nucleotide variants in 125,748 human exomes and 15,708 genomesPreprint
Wang, Q. S., Pierce‐Hoffman, E., Cummings, B. B., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/573378 · Cited by 32 · see citing works
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Satterstrom, F., Walters, R. K., Singh, T., Wigdor, E., Lescai, F., Demontis, D., Kosmicki, J. A., Grove, J., Stevens, C. R., Bybjerg-Grauholm, J., et al. (2018) · bioRxiv · doi:10.1101/277707 · Cited by 30 · see citing works
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Diaz-Papkovich, A., Anderson-Trocmé, L., & Gravel, S. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/423632 · Cited by 25 · see citing works
Feiglin, A., Allen, B. K., Kohane, I. S., & Kong, S. W. (2017) · Cell Systems · doi:10.1016/j.cels.2017.06.016 · Cited by 21 · see citing works
Evaluating potential drug targets through human loss-of-function genetic variationPreprint
Minikel, E. V., Karczewski, K. J., Martin, H. C., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/530881 · Cited by 21 · see citing works
Self-citationLaver, T. W., Weedon, M. N., Caswell, R. C., Hussain, K., Ellard, S., & Flanagan, S. E. (2017) · Human Mutation · doi:10.1002/humu.23289 · Cited by 20 · see citing works
Transcript expression-aware annotation improves rare variant discovery and interpretationPreprint
Cummings, B. B., Karczewski, K. J., Kosmicki, J. A., Seaby, E. G., Watts, N. A., Singer‐Berk, M., Mudge, J. M., Karjalainen, J. M., Satterstrom, F. K., O’Donnell‐Luria, A., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/554444 · Cited by 19 · see citing works
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Tuladhar, R., Yeu, Y., Piazza, J. T., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/583138 · Cited by 19 · see citing works
Whiffin, N., Armean, I. M., Kleinman, A., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/561472 · Cited by 16 · see citing works
Self-citationWhiffin, N., Karczewski, K. J., Zhang, X., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/543504 · Cited by 12 · see citing works
Self-citationMeasuring “Intolerance to Mutation” in Human GeneticsPreprint
Fuller, Z. L., Berg, J. J., Mostafavi, H., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/382481 · Cited by 8 · see citing works
Kurki, M., Saarentaus, E., Pietiläinen, O. P. H., Gormley, P., Lal, D., Kerminen, S., Torniainen‐Holm, M., Hämäläinen, E., Rahikkala, E., Keski‐Filppula, R., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/332023 · Cited by 5 · see citing works
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Satterstrom, F. K., Kosmicki, J. A., Wang, J., Breen, M. S., De Rubeis, S., An, J.-Y., Peng, M., Collins, R., Grove, J., Klei, L., et al. (2020) · Cell · doi:10.1016/j.cell.2019.12.036 · Cited by 2,321 · see citing works
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Liao, W.-W., Asri, M., Ebler, J., Doerr, D., Haukness, M., Hickey, G., Lu, S., Lucas, J. K., Monlong, J., Abel, H. J., et al. (2023) · Nature · doi:10.1038/s41586-023-05896-x · Cited by 1,129 · see citing works
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Singh, T., Poterba, T., Curtis, D., Akil, H., Al Eissa, M., Barchas, J. D., Bass, N., Bigdeli, T. B., Breen, G., Bromet, E. J., et al. (2022) · Nature · doi:10.1038/s41586-022-04556-w · Cited by 983 · see citing works
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The All of Us Research Program Genomics Investigators, Manuscript Writing Group, Bick, A. G., Metcalf, G. A., Mayo, K. R., Lichtenstein, L., Rura, S., Carroll, R. J., Musick, A., Linder, J. E., et al. (2024) · Nature · doi:10.1038/s41586-023-06957-x · Cited by 829 · see citing works
Self-citationA brief history of human disease genetics
Claussnitzer, M., Cho, J. H., Collins, R., Cox, N. J., Dermitzakis, E. T., Hurles, M. E., Kathiresan, S., Kenny, E. E., Lindgren, C. M., MacArthur, D. G., et al. (2020) · Nature · doi:10.1038/s41586-019-1879-7 · Cited by 697 · see citing works
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Bick, A. G., Weinstock, J. S., Nandakumar, S. K., Fulco, C. P., Bao, E. L., Zekavat, S. M., Szeto, M. D., Liao, X., Leventhal, M. J., Nasser, J., et al. (2020) · Nature · doi:10.1038/s41586-020-2819-2 · Cited by 733 · see citing works
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Kaplanis, J., Samocha, K. E., Wiel, L., Zhang, Z., Arvai, K. J., Eberhardt, R. Y., Gallone, G., Lelieveld, S. H., Martin, H. C., McRae, J. F., et al. (2020) · Nature · doi:10.1038/s41586-020-2832-5 · Cited by 615 · see citing works
Self-citationBernard, E., Nannya, Y., Hasserjian, R. P., Devlin, S. M., Tuechler, H., Medina-Martinez, J. S., Yoshizato, T., Shiozawa, Y., Saiki, R., Malcovati, L., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1008-z · Cited by 648 · see citing works
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Morales, J., Pujar, S., Loveland, J. E., Astashyn, A., Bennett, R., Berry, A., Cox, E., Davidson, C., Ermolaeva, O., Farrell, C. M., et al. (2022) · Nature · doi:10.1038/s41586-022-04558-8 · Cited by 571 · see citing works
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Ruzzo, E. K., Pérez-Cano, L., Jung, J.-Y., Wang, L.-K., Kashef-Haghighi, D., Hartl, C., Singh, C., Xu, J., Hoekstra, J. N., Leventhal, O., et al. (2019) · Cell · doi:10.1016/j.cell.2019.07.015 · Cited by 457 · see citing works
Chia, R., Sabir, M. S., Bandres-Ciga, S., Saez-Atienzar, S., Reynolds, R. H., Gustavsson, E., Walton, R. L., Ahmed, S., Viollet, C., Ding, J., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00785-3 · Cited by 438 · see citing works
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Halldorsson, B. V., Eggertsson, H. P., Moore, K. H. S., Hauswedell, H., Eiriksson, O., Ulfarsson, M. O., Palsson, G., Hardarson, M. T., Oddsson, A., Jensson, B. O., et al. (2022) · Nature · doi:10.1038/s41586-022-04965-x · Cited by 448 · see citing works
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Szustakowski, J. D., Balasubramanian, S., Kvikstad, E., Khalid, S., Bronson, P. G., Sasson, A., Wong, E., Liu, D., Wade Davis, J., Haefliger, C., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00885-0 · Cited by 401 · see citing works
Self-citationRives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C. L., Ma, J., et al. (2019) · doi:10.1101/622803 · Cited by 3,280 · see citing works
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Benton, M. L., Abraham, A., LaBella, A. L., Abbot, P., Rokas, A., & Capra, J. A. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-020-00305-9 · Cited by 291 · see citing works
Pirruccello, J. P., Bick, A., Wang, M., Chaffin, M., Friedman, S., Yao, J., Guo, X., Venkatesh, B. A., Taylor, K. D., Post, W. S., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15823-7 · Cited by 267 · see citing works
Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation
Linder, J., Srivastava, D., Yuan, H., Agarwal, V., & Kelley, D. R. (2025) · Nature Genetics · doi:10.1038/s41588-024-02053-6 · Cited by 265 · see citing works
Genetic analyses identify widespread sex-differential participation bias
Pirastu, N., Cordioli, M., Nandakumar, P., Mignogna, G., Abdellaoui, A., Hollis, B., Kanai, M., Rajagopal, V. M., Parolo, P. D. B., Baya, N., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00846-7 · Cited by 251 · see citing works
Self-citationPatterns of de novo tandem repeat mutations and their role in autism
Mitra, I., Huang, B., Mousavi, N., Ma, N., Lamkin, M., Yanicky, R., Shleizer-Burko, S., Lohmueller, K. E., & Gymrek, M. (2021) · Nature · doi:10.1038/s41586-020-03078-7 · Cited by 194 · see citing works
Deep learning enables genetic analysis of the human thoracic aorta
Pirruccello, J. P., Chaffin, M. D., Chou, E. L., Fleming, S. J., Lin, H., Nekoui, M., Khurshid, S., Friedman, S. F., Bick, A. G., Arduini, A., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-00962-4 · Cited by 210 · see citing works
Rare variant associations with plasma protein levels in the UK Biobank
Dhindsa, R. S., Burren, O. S., Sun, B. B., Prins, B. P., Matelska, D., Wheeler, E., Mitchell, J., Oerton, E., Hristova, V. A., Smith, K. R., et al. (2023) · Nature · doi:10.1038/s41586-023-06547-x · Cited by 193 · see citing works
Self-citationPredicting functional effects of missense variants in voltage-gated sodium and calcium channels
Heyne, H. O., Baez-Nieto, D., Iqbal, S., Palmer, D. S., Brunklaus, A., May, P., Collaborative, E., Johannesen, K. M., Lauxmann, S., Lemke, J. R., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aay6848 · Cited by 140 · see citing works
Self-citationGROUP Investigators, Rees, E., Han, J., Morgan, J., Carrera, N., Escott-Price, V., Pocklington, A. J., Duffield, M., Hall, L. S., Legge, S. E., et al. (2020) · Nature Neuroscience · doi:10.1038/s41593-019-0565-2 · Cited by 129 · see citing works
Van Hout, C. V., Tachmazidou, I., Backman, J. D., Hoffman, J. X., Ye, B., Pandey, A. K., Gonzaga-Jauregui, C., Khalid, S., Liu, D., Banerjee, N., et al. (2019) · doi:10.1101/572347 · Cited by 110 · see citing works
Value of systematic genetic screening of patients with amyotrophic lateral sclerosis
Shepheard, S. R., Parker, M. D., Cooper-Knock, J., Verber, N. S., Tuddenham, L., Heath, P., Beauchamp, N., Place, E., Sollars, E. S. A., Turner, M. R., et al. (2021) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp-2020-325014 · Cited by 116 · see citing works
An ancestral recombination graph of human, Neanderthal, and Denisovan genomes
Schaefer, N. K., Shapiro, B., & Green, R. E. (2021) · Science Advances · doi:10.1126/sciadv.abc0776 · Cited by 106 · see citing works
Scalable genetic screening for regulatory circuits using compressed Perturb-seq
Yao, D., Binan, L., Bezney, J., Simonton, B., Freedman, J., Frangieh, C. J., Dey, K., Geiger-Schuller, K., Eraslan, B., Gusev, A., et al. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-01964-9 · Cited by 101 · see citing works
Genome-wide mapping of somatic mutation rates uncovers drivers of cancer
Sherman, M. A., Yaari, A. U., Priebe, O., Dietlein, F., Loh, P.-R., & Berger, B. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01353-8 · Cited by 80 · see citing works
A cross-species proteomic map reveals neoteny of human synapse development
Wang, L., Pang, K., Zhou, L., Cebrián-Silla, A., González-Granero, S., Wang, S., Bi, Q., White, M. L., Ho, B., Li, J., et al. (2023) · Nature · doi:10.1038/s41586-023-06542-2 · Cited by 82 · see citing works
Transcriptome-wide analysis of differential expression in perturbation atlases
Nadig, A., Replogle, J. M., Pogson, A. N., Murthy, M., McCarroll, S. A., Weissman, J. S., Robinson, E. B., & O’Connor, L. J. (2025) · Nature Genetics · doi:10.1038/s41588-025-02169-3 · Cited by 70 · see citing works
Kröll‐Hermi, A., Ebstein, F., Stoetzel, C., Geoffroy, V., Schaefer, E., Scheidecker, S., Bär, S., Takamiya, M., Kawakami, K., Zieba, B. A., et al. (2020) · EMBO Molecular Medicine · doi:10.15252/emmm.201911861 · Cited by 65 · see citing works
Pilot study of bempegaldesleukin in combination with nivolumab in patients with metastatic sarcoma
D’Angelo, S. P., Richards, A. L., Conley, A. P., Woo, H. J., Dickson, M. A., Gounder, M., Kelly, C., Keohan, M. L., Movva, S., Thornton, K., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30874-8 · Cited by 60 · see citing works
Kaplanis, J., Samocha, K. E., Wiel, L., Zhang, Z., Arvai, K. J., Eberhardt, R. Y., Gallone, G., Lelieveld, S. H., Martin, H. C., McRae, J. F., et al. (2019) · doi:10.1101/797787 · Cited by 36 · see citing works
Self-citationVIPdb, a genetic variant impact predictor database
Hu, Z., Yu, C., Furutsuki, M., Andreoletti, G., Ly, M., Hoskins, R., Adhikari, A. N., & Brenner, S. E. (2019) · Human Mutation · doi:10.1002/humu.23858 · Cited by 37 · see citing works
Li, Z., Gaudreault, N., Arsenault, B. J., Mathieu, P., Bossé, Y., & Thériault, S. (2020) · Communications Biology · doi:10.1038/s42003-020-01210-x · Cited by 23 · see citing works
<i><scp>KCNT2</scp>‐</i>Related Disorders: Phenotypes, Functional, and Pharmacological Properties
Cioclu, M. C., Mosca, I., Ambrosino, P., Puzo, D., Bayat, A., Wortmann, S. B., Koch, J., Strehlow, V., Shirai, K., Matsumoto, N., et al. (2023) · Annals of Neurology · doi:10.1002/ana.26662 · Cited by 23 · see citing works
González-del Pozo, M., Fernández-Suárez, E., Bravo-Gil, N., Méndez-Vidal, C., Martín-Sánchez, M., Rodríguez-de la Rúa, E., Ramos-Jiménez, M., Morillo-Sánchez, M. J., Borrego, S., & Antiñolo, G. (2022) · npj Genomic Medicine · doi:10.1038/s41525-022-00286-0 · Cited by 21 · see citing works
Rossi, J. J., Rosenfeld, J. A., Chan, K. M., Streff, H., Nankivell, V., Peet, D. J., Whitelaw, M. L., & Bersten, D. C. (2021) · Scientific Reports · doi:10.1038/s41598-021-86041-4 · Cited by 17 · see citing works
Richmond, C. M., Campbell, S., Foo, H. W., Lunke, S., Stark, Z., Moody, A., Bannister, E., Greenway, A., & Brown, N. (2020) · Molecular Syndromology · doi:10.1159/000505886 · Cited by 12 · see citing works
Jung, B., Ahn, K., Justice, C., Norman, L., Price, J., Sudre, G., & Shaw, P. (2023) · Molecular Psychiatry · doi:10.1038/s41380-022-01906-y · Cited by 10 · see citing works
Ancient roots: A Cambrian explosion of autism susceptibility genes
Casanova, E. L. (2023) · Autism Research · doi:10.1002/aur.2984 · Cited by 5 · see citing works
Uzuner Odongo, D., İlgün, A., Bozkurt, F. B., & Çakır, T. (2025) · Communications Biology · doi:10.1038/s42003-025-07941-z · Cited by 4 · see citing works
AXIN1 mutations in nonsyndromic craniosynostosis
Timberlake, A. T., Hemal, K., Gustafson, J. A., Hao, L. T., Valenzuela, I., Slavotinek, A., Cunningham, M. L., Kahle, K. T., Lifton, R. P., & Persing, J. A. (2024) · Journal of Neurosurgery: Pediatrics · doi:10.3171/2024.5.peds24115 · Cited by 3 · see citing works
Yoon, J. G., Yu, J. W., Shim, K. W., Kim, Y. O., & Lee, M. G. (2024) · Clinical Genetics · doi:10.1111/cge.14539 · Cited by 1 · see citing works
- Authors
- Karczewski, K. J., Francioli, L. C., Tiao, G., Cummings, B. B., Alföldi, J., Wang, Q., Collins, R. L., Laricchia, K. M., Ganna, A., Birnbaum, D. P., Gauthier, L. D., Brand, H., Solomonson, M., Watts, N. A., Rhodes, D., Singer-Berk, M., England, E. M., Seaby, E. G., Kosmicki, J. A., Walters, R. K., Tashman, K., Farjoun, Y., Banks, E., Poterba, T., Wang, A., Seed, C., Whiffin, N., Chong, J. X., Samocha, K. E., Pierce-Hoffman, E., Zappala, Z., O’Donnell-Luria, A. H., Minikel, E. V., Weisburd, B., Lek, M., Ware, J. S., Vittal, C., Armean, I. M., Bergelson, L., Cibulskis, K., Connolly, K. M., Covarrubias, M., Donnelly, S., Ferriera, S., Gabriel, S., Gentry, J., Gupta, N., Jeandet, T., Kaplan, D., Llanwarne, C., Munshi, R., Novod, S., Petrillo, N., Roazen, D., Ruano-Rubio, V., Saltzman, A., Schleicher, M., Soto, J., Tibbetts, K., Tolonen, C., Wade, G., Talkowski, M. E., Genome Aggregation Database (gnomAD) Consortium, Neale, B. M., Daly, M. J., & MacArthur, D. G.
- Affiliations
- Broad Institute (US)
- Queen Mary University of London (GB)
- University of Washington (US)
- Wellcome Sanger Institute (GB)
- Yale University (US)
- Corresponding author
- Karczewski, Konrad J.
- MacArthur, Daniel G.
- ORCID
- Karczewski, Konrad J.
- Francioli, Laurent C.
- Tiao, Grace
- Cummings, Beryl B.
- Alföldi, Jessica
- Wang, Qingbo
- Collins, Ryan L.
- Laricchia, Kristen M.
- Ganna, Andrea
- Brand, Harrison
- Solomonson, Matthew
- Rhodes, Daniel
- Seaby, Eleanor G.
- Kosmicki, Jack A.
- Walters, Raymond K.
- Tashman, Katherine
- Farjoun, Yossi
- Banks, Eric
- Poterba, Timothy
- Whiffin, Nicola
- Chong, Jessica X.
- Samocha, Kaitlin E.
- Zappala, Zachary
- Minikel, Eric Vallabh
- Weisburd, Ben
- Lek, Monkol
- Ware, James S.
- Armean, Irina M.
- Cibulskis, Kristian
- Donnelly, Stacey
- Gabriel, Stacey
- Gupta, Namrata
- Saltzman, Andrea
- Talkowski, Michael E.
- Neale, Benjamin M.
- Daly, Mark J.
- MacArthur, Daniel G.
- Venue
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Published
- 2019-01-28
- OpenAlex
- W2912491890
- Cited by
- 1,662
- References
- 57
- Citations by year
- 2026: 3 · 2025: 83 · 2024: 154 · 2023: 171 · 2022: 206 · 2021: 302 · 2020: 533 · 2019: 195 · 2018: 1 · 2016: 2 · 2013: 1 · 2012: 1
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Licence
- cc-by
- Locations
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- Funders
- National Science Foundation
- Sanofi
- BioMarin Pharmaceutical
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (177853)
- National Institutes of Health (HG006493)
- Sanofi Genzyme
- National Institute on Aging
- National Heart, Lung, and Blood Institute (HG006493)
- National Human Genome Research Institute (HG006493, HG008956, HG008900, UM1HG008900, UM1HG006493, U24HG008956)
- National Cancer Institute
- National Institute of General Medical Sciences (F32GM115208, R01GM104371, GM115208)
- National Institute of Diabetes and Digestive and Kidney Diseases (U54DK105566)
- Common Fund
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Keywords
- loss-of-function mutations, protein-coding genes, gene essentiality
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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