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Consortium Reports on First Efforts To Catalog Mammalian Gene Function

NEW YORK (GenomeWeb) – The International Mouse Phenotyping Consortium has reported the first results of its effort to catalog the function of mammalian genes.

The group aims to systematically create knockout mice to work out what each gene does.

"Although next-generation sequencing has revolutionized the identification of new disease genes, there is still a lack of understanding of how these genes actually cause disease," Queen Mary University of London's Damian Smedley, the study's senior author, said in a statement.

Smedley and his colleagues have now generated knockout mice for more than 3,300 genes, and, as they reported today in Nature Genetics, have developed new disease models and uncovered candidate genes that may be involved in previously genetically uncharacterized diseases.

Using a phenotyping pipeline it developed, the group is analyzing cohorts of male and female knockout mice produced by the International Knockout Mice Consortium. The phenotyping pipeline relies on a standardized approach to measure 502 different parameters, including neurological, behavioral, and musculoskeletal traits.

So far, Smedley and his colleagues have fully or partially phenotyped 3,328 genes, generating more than 20 million data points and 28,406 phenotype annotations. These genes represent about 15 percent of the mouse protein-coding genome. Half had never been studied in a mouse before and about 1,000 of them had no direct experimental evidence of their function.

When they compared their phenotyping approach to previous efforts, the researchers found that 38 percent of the gene-phenotype associations were detected. They attributed some of this discrepancy to variations in genetic background, experimental techniques, and statistical methods.

Overall, they noted that about 90 percent of the gene-phenotype annotations the consortium has found have not been reported before in the literature.

Smedley and his colleagues also developed a translational pipeline to automatically detect phenotypic similarities between what they uncovered in their mice and in the more than 7,000 diseases described in the Online Mendelian Inheritance in Man and Orphanet databases. In particular, this pipeline relies on human phenotype annotations for rare diseases, annotations of phenotypic abnormalities, and the PhenoDigm algorithm developed by the Monarch Initiative.

With their automated pipeline, they uncovered 360 new disease models, including some for which there was no previous mouse model of disease. For instance, they found mouse models of Bernard-Soulier syndrome, Bardet-biedl syndrome-5, and Gordon Holmes syndrome.

The researchers also manually inspected known associations that their pipeline didn't pick up. A dozen of these fell just below the threshold set for phenotype matches, but the researchers argued that altering that threshold would introduce too many false positives. But as manual inspection isn't a viable long-term solution, they said that future implementations would include additional histopathological data.

The knockout mice also suggested new candidate genes for Mendelian conditions, Smedley and his colleagues said. For instance, homozygous Fam53b knockout mice were found to have a phenotype similar to that of people with Diamond-Blackfan anemia. Similarly, heterozygous Klhdc2 knock-out mice have a phenotype matching that of arrhythmogenic right ventricular dysplasia 3 and mice lacking Usmg5 had similar muscle weakness and gait abnormalities as people with Charcot-Marie-Tooth disease.

"Mouse models allow us to speed up patient diagnosis and develop new therapies. But before that can work, we need to understand exactly what each gene does, and what diseases it is associated with," first author Terry Meehan from the European Bioinformatics Institute said in a statement. "This is a significant effort in data collection and curation that goes well beyond the capabilities of individual labs."