4.8 Article

High-throughput discovery of novel developmental phenotypes

Journal

NATURE
Volume 537, Issue 7621, Pages 508-+

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/nature19356

Keywords

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Funding

  1. NIH [U42 OD011185, U54 HG006332, U54 HG006348-S1, OD011174, HG006364-03S1, U42 OD011175, U54 HG006370]
  2. Wellcome Trust
  3. Medical Research Council Strategic Award
  4. Government of Canada through Genome Canada
  5. Ontario Genomics [OGI-051]
  6. Wellcome Trust Strategic Award Deciphering the Mechanisms of Developmental Disorders (DMDD) [WT100160]
  7. National Centre for Scientific Research (CNRS)
  8. French National Institute of Health and Medical Research (INSERM)
  9. University of Strasbourg (UDS)
  10. Centre Europeen de Recherche en Biologie et en Medecine
  11. Agence Nationale de la Recherche [ANR-10-IDEX-0002-02, ANR-10-INBS- 07 PHENOMIN]
  12. German Federal Ministry of Education and Research [01KX1012]
  13. MRC [MC_UP_1502/3, MC_U142684171, MC_U142684172] Funding Source: UKRI
  14. Cancer Research UK [13031] Funding Source: researchfish
  15. Medical Research Council [MC_U142684172, MC_U142684171, MC_UP_1502/3] Funding Source: researchfish
  16. The Francis Crick Institute [100160/C/12/Z] Funding Source: researchfish
  17. Grants-in-Aid for Scientific Research [15K06815, 26250024] Funding Source: KAKEN

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Approximately one-third of all mammalian genes are essential for life. Phenotypes resulting from knockouts of these genes in mice have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5,000 knockout mouse lines, here we identify 410 lethal genes during the production of the first 1,751 unique gene knockouts. Using a standardized phenotyping platform that incorporates high-resolution 3D imaging, we identify phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes, thus providing a dataset that facilitates the prioritization and validation of mutations identified in clinical sequencing efforts.

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