期刊
CONSERVATION GENETICS
卷 19, 期 4, 页码 995-1005出版社
SPRINGER
DOI: 10.1007/s10592-018-1072-9
关键词
Cheetah; Endangered species; Loss-of-function; Non-model species; Panda; Polar bear; Phenotype; Wolf; Essential genes; IMPC; Knockout; Mouse
资金
- United States National Institutes of Health (NIH) [U54 HG006370, U42 OD011185, U54 HG006332, U54 HG006348, U54 HG006364, U42 OD011175, UM1 OD023221]
- Government of Canada through Genome Canada
- Ontario Genomics NorComm2 project [OGI-051]
- Korea Mouse Phenotyping Project of the Ministry of Science and ICT through the Korea National Research Foundation [2017M3A9D5A01052447]
- German Federal Ministry of Education and Research (INFRAFRONTIER grant) [01KX1012]
- MRC [MC_U142684172] Funding Source: UKRI
- National Research Foundation of Korea [2017M3A9D5A01052447] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
The International Mouse Phenotyping Consortium (IMPC) is building a catalogue of mammalian gene function by producing and phenotyping a knockout mouse line for every protein-coding gene. To date, the IMPC has generated and characterised 5186 mutant lines. One-third of the lines have been found to be non-viable and over 300 new mouse models of human disease have been identified thus far. While current bioinformatics efforts are focused on translating results to better understand human disease processes, IMPC data also aids understanding genetic function and processes in other species. Here we show, using gorilla genomic data, how genes essential to development in mice can be used to help assess the potentially deleterious impact of gene variants in other species. This type of analyses could be used to select optimal breeders in endangered species to maintain or increase fitness and avoid variants associated to impaired-health phenotypes or loss-of-function mutations in genes of critical importance. We also show, using selected examples from various mammal species, how IMPC data can aid in the identification of candidate genes for studying a condition of interest, deliver information about the mechanisms involved, or support predictions for the function of genes that may play a role in adaptation. With genotyping costs decreasing and the continued improvements of bioinformatics tools, the analyses we demonstrate can be routinely applied.
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