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Genic constraint against nonsynonymous variation across the mouse genome

Abstract:
Abstract 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
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1186/s12864-023-09637-2

Authors

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Institution:
University of Oxford
Department:
Big Data Institute
Role:
Author
ORCID:
0000-0002-8378-0043
More by this author
Role:
Author
ORCID:
0009-0006-7154-4568
More by this author
Institution:
University of Oxford
Department:
Big Data Institute
Role:
Author
ORCID:
0000-0002-2502-3669
More by this author
Institution:
University of Oxford
Department:
Big Data Institute
Role:
Author
ORCID:
0000-0002-4903-9374


Publisher:
BioMed Central
Journal:
BMC Genomics More from this journal
Volume:
24
Issue:
1
Pages:
562-562
Article number:
562
Publication date:
2023-09-22
DOI:
EISSN:
1471-2164
ISSN:
1471-2164


Language:
English
Keywords:
Pubs id:
1540433
Local pid:
pubs:1540433
Source identifiers:
W4386944745
Deposit date:
2026-05-17
ARK identifier:
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