Nature CommunicationsGenomicsPeer-reviewed journal article
Human and mouse essentiality screens as a resource for disease gene discovery
Pilar CacheiroiD, Violeta Muñoz‐FuentesiD, Stephen A. MurrayiD, Mary E. DickinsoniD, Maja BućaniD, Lauryl M. J. NutteriD, Kevin A. PetersoniD, Hamed HaselimashhadiiD, Ann Marie FlennikeniD, Hugh Morgan, Henrik WesterbergiD, Tomasz KonopkaiD, Chih‐Wei HsuiD, Audrey E. ChristianseniD, Denise Grant LanzaiD, Arthur L. BeaudetiD, Jason D. HeaneyiD, Helmut FuchsiD, Valérie Gailus‐DurneriD, Tania SorgiD, Jan ProcházkaiD, Vendula NovosadováiD, Christopher J. LelliottiD, Hannah Wardle‐JonesiD, Sara WellsiD, , A. Siddiq
Abstract
Although genomic sequencing has been transformative in the study of rare genetic diseases, identifying causal variants remains a considerable challenge that can be addressed in part by new gene-specific knowledge. Here, we integrate measures of how essential a gene is to supporting life, as inferred from the comprehensive viability and phenotyping screens performed on knockout mice by the International Mouse Phenotyping Consortium and from human cell line essentiality screens. We propose a novel, cross-species gene classification across the Full Spectrum of Intolerance to Loss-of-function (FUSIL) and demonstrate that genes in five mutually exclusive FUSIL categories have differing characteristics in the biological processes they regulate, tissue expression levels and human mutation rates. Most notably, Mendelian disease genes, particularly those associated with developmental disorders, are highly overrepresented in the developmental lethal category, representing genes not essential for cell survival but required for organism development. Exploiting this finding, we have screened developmental disorder cases from three independent disease sequencing consortia and identified potentially pathogenic, de novo variants shared in different patients for several developmental lethal genes that have not previously been associated with rare disease. We therefore propose FUSIL as an efficient resource for disease gene discovery.
- organism: human
- organism: mouse
- assay: CRISPR screen
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 105
- FWCI
- 7.90
- Field percentile
- top 2%
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