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Here, we present the Genome Aggregation Database version 4 (gnomAD v4), including 730,947 with exome sequences, a fivefold increase over previous releases. We demonstrate that statistical power to detect strong selective constraint continues to increase with sample size. We develop a new loss-of-function annotation pipeline, which learns genomic features predictive of nonsense-mediated decay and splicing effects from selection signals, achieving 90% precision for distinguishing likely true versus false positive loss-of-function variants. This improved pipeline, along with incorporation of highly deleterious missense variants into measures of loss-of-function intolerance, improves disease gene detection, particularly for short genes and those with gain-of-function mechanisms. To improve disease gene prediction, we systematically extract gene\u2013disease associations from biomedical literature, map these to gene-level biological features, and integrate both with refined constraint metrics within a Bayesian framework, yielding state-of-the-art prediction of gene\u2013disease relevance. We highlight genes under strong constraint but with limited clinical characterization, which are enriched in embryonic lethal and fertility phenotypes, thus prioritizing previously under-characterized disease genes. Together, these advances establish a unified framework for accelerating gene discovery and improving rare disease diagnosis.<\/jats:p>","DOI":"10.64898\/2026.03.23.26349081","type":"posted-content","created":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T23:45:19Z","timestamp":1774482319000},"source":"Crossref","is-referenced-by-count":41,"title":["Integrating 730,947 exome sequences with clinical literature improves gene discovery"],"prefix":"10.64898","author":[{"given":"Jeremy","family":"Guez","sequence":"first","affiliation":[{"name":"Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA"},{"name":"Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA"},{"name":"Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Julia K.","family":"Goodrich","sequence":"additional","affiliation":[{"name":"Center for Genomic 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