Genic constraint against nonsynonymous variation across the mouse genome.

BMC Genomics

Li Ka Shing Centre for Health Information and Discovery, Big Data Institute, University of Oxford, Oxford, UK.

Published: September 2023

Background: Selective constraint, the depletion of variation due to negative selection, provides insights into the functional impact of variants and disease mechanisms. However, its characterization in mice, the most commonly used mammalian model, remains limited. This study aims to quantify mouse gene constraint using a new metric called the nonsynonymous observed expected ratio (NOER) and investigate its relationship with gene function.

Results: NOER was calculated using whole-genome sequencing data from wild mouse populations (Mus musculus sp and Mus spretus). Positive correlations were observed between mouse gene constraint and the number of associated knockout phenotypes, indicating stronger constraint on pleiotropic genes. Furthermore, mouse gene constraint showed a positive correlation with the number of pathogenic variant sites in their human orthologues, supporting the relevance of mouse models in studying human disease variants.

Conclusions: NOER provides a resource for assessing the fitness consequences of genetic variants in mouse genes and understanding the relationship between gene constraint and function. The study's findings highlight the importance of pleiotropy in selective constraint and support the utility of mouse models in investigating human disease variants. Further research with larger sample sizes can refine constraint estimates in mice and enable more comprehensive comparisons of constraint between mouse and human orthologues.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10514939PMC
http://dx.doi.org/10.1186/s12864-023-09637-2DOI Listing

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