학술논문

The International Mouse Phenotyping Consortium (IMPC): a functional catalogue of the mammalian genome that informs conservation
Document Type
article
Source
Conservation Genetics. 19(4)
Subject
Biological Sciences
Bioinformatics and Computational Biology
Genetics
Biotechnology
Human Genome
2.1 Biological and endogenous factors
Underpinning research
1.1 Normal biological development and functioning
Aetiology
Generic health relevance
Life on Land
Cheetah
Endangered species
Loss-of-function
Non-model species
Panda
Polar bear
Phenotype
Wolf
Essential genes
IMPC
Knockout
Mouse
IMPC consortium
Environmental Sciences
Evolutionary Biology
Biological sciences
Environmental sciences
Language
Abstract
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.