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High-throughput discovery of novel developmental phenotypes

Version 2 2024-03-25, 16:40
Version 1 2023-10-19, 14:30
journal contribution
posted on 2024-03-25, 16:40 authored by Mary EA Dickinson, Ann MA Flenniken, Xiao Ji, Lydia Teboul, Michael DA Wong, Jacqueline KA White, Terrence FA Meehan, Wolfgang JA Weninger, Henrik Westerberg, Hibret Adissu, Candice NA Baker, Lynette Bower, James MA Brown, LA Brianna Caddle, Francesco Chiani, Dave Clary, James Cleak, Mark JA Daly, James MA Denegre, Brendan Doe, Mary EA Dolan, Sarah MA Edie, Helmut Fuchs, Valerie Gailus-Durner, Antonella Galli, Alessia Gambadoro, Juan Gallegos, Shiying Guo, Neil RA Horner, Chih-Wei Hsu, Sara JA Johnson, Sowmya Kalaga, Lance CA Keith, Louise Lanoue, Thomas NA Lawson, Monkol Lek, Manuel Mark, Susan Marschall, Jeremy Mason, Melissa LA McElwee, Susan Newbigging, Lauryl MA JA Nutter, Kevin AA Peterson, Ramiro Ramirez-Solis, Douglas JA Rowland, Edward Ryder, Kaitlin EA Samocha, John RA Seavitt, Mohammed Selloum, Zsombor Szoke-Kovacs
<p>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.</p>

History

School affiliated with

  • School of Computer Science (Research Outputs)

Publication Title

Nature

Volume

537

Issue

7621

Pages/Article Number

508-514

Publisher

Nature Publishing Group

ISSN

0028-0836

Date Submitted

2019-04-12

Date Accepted

2016-08-10

Date of First Publication

2016-09-14

Date of Final Publication

2016-09-22

ePrints ID

34926

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