The International Mouse Phenotyping Consortium: comprehensive knockout phenotyping underpinning the study of human disease.

The International Mouse Phenotyping Consortium (IMPC; https://www.mousephenotype.org/) web portal makes available curated, integrated and analysed knockout mouse phenotyping data generated by the IMPC project consisting of 85M data points and over 95,000 statistically significant phenotype hits mapped to human diseases. The IMPC portal delivers a substantial reference dataset that supports the enrichment of various domain-specific projects and databases, as well as the wider research and clinical community, where the IMPC genotype-phenotype knowledge contributes to the molecular diagnosis of patients affected by rare disorders. Data from 9,000 mouse lines and 750 000 images provides vital resources enabling the interpretation of the ignorome, and advancing our knowledge on mammalian gene function and the mechanisms underlying phenotypes associated with human diseases. The resource is widely integrated and the lines have been used in over 4,600 publications indicating the value of the data and the materials.

The International Mouse Phenotyping Consortium (IMPC): a functional catalogue of the mammalian genome that informs conservation.

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.

Knockout mice are an important tool for human monogenic heart disease studies.

Mouse models are relevant to studying the functionality of genes involved in human diseases; however, translation of phenotypes can be challenging. Here, we investigated genes related to monogenic forms of cardiovascular disease based on the Genomics England PanelApp and aligned them to International Mouse Phenotyping Consortium (IMPC) data. We found 153 genes associated with cardiomyopathy, cardiac arrhythmias or congenital heart disease in humans, of which 151 have one-to-one mouse orthologues. For 37.7% (57/151), viability and heart data captured by electrocardiography, transthoracic echocardiography, morphology and pathology from embryos and young adult mice are available. In knockout mice, 75.4% (43/57) of these genes showed non-viable phenotypes, whereas records of prenatal, neonatal or infant death in humans were found for 35.1% (20/57). Multisystem phenotypes are common, with 58.8% (20/34) of heterozygous (homozygous lethal) and 78.6% (11/14) of homozygous (viable) mice showing cardiovascular, metabolic/homeostasis, musculoskeletal, hematopoietic, nervous system and/or growth abnormalities mimicking the clinical manifestations observed in patients. These IMPC data are critical beyond cardiac diagnostics given their multisystemic nature, allowing detection of abnormalities across physiological systems and providing a valuable resource to understand pleiotropic effects.