Genetic Correlation Guides Mega-Analysis Identifying Genes
Mullis et al. (published Feb. 27, 2026) implement Haseman–Elston regression to estimate genetic correlations among 7,233 phenotypes across eleven Diversity Outbred mouse studies. They used correlation-driven clustering to perform mega-analyses that discovered 884 QTL for 383 meta-phenotypes, explained an average 40.36% of genetic variance, and nominated candidate genes such as Cdkn2b for aorta extracellular matrix and implicated pulmonary neuroendocrine cell signaling in lung pathophenotypes.
Key Points
- 1Implements Haseman-Elston regression on 7,233 phenotypes across eleven DO mouse studies.
- 2Discovers 884 QTL for 383 meta-phenotypes, explaining average 40.36% of genetic variance.
- 3Enables cross-cohort genetic clustering, revealing candidate genes like Cdkn2b and lung pathogenesis links.
Scoring Rationale
Robust, peer-reviewed mega-analysis with actionable methods and many QTL; limitation: findings largely specific to Diversity Outbred mice.
Sources
Public references used for this report.
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