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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #395070
Research Project: Enhancing Genetic Merit of Ruminants Through Improved Genome Assembly, Annotation, and Selection

Location: Animal Genomics and Improvement Laboratory

Title: Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle

Author
item XIANG, RUIDONG - University Of Melbourne
item FANG, LINGZHAO - University Of Edinburgh
item LIU, SHULI - Westlake University
item MACLEOD, IONA - Agrobio
item LIU, ZHIQIAN - Agrobio
item BREEN, EDMOND - Agrobio
item GAO, YAHUI - University Of Maryland
item Liu, Ge - George
item TENESA, ALBERT - University Of Edinburgh
item CONSORTIUM, CATTLEGTEX - Collaborator
item MASON, BRETT - Agrobio
item CHAMBERLAIN, AMANDA - Agrobio
item WRAY, NAOMI - University Of Queensland
item GODDARD, MICHAEL - University Of Melbourne

Submitted to: Cell Genomics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/26/2023
Publication Date: 8/23/2023
Citation: Xiang, R., Fang, L., Liu, S., Macleod, I.M., Liu, Z., Breen, E.J., Gao, Y., Liu, G., Tenesa, A., Consortium, C., Mason, B., Chamberlain, A.J., Wray, N.R., Goddard, M.E. 2023. Gene expression and RNA splicing explain large proportions of the heritability for complex traits in cattle. Cell Genomics. 100385. https://doi.org/10.1016/j.xgen.2023.100385.
DOI: https://doi.org/10.1016/j.xgen.2023.100385

Interpretive Summary: Comprehensive analyses of transcriptomes will benefit our understanding of genetic bases for complex traits. We showed that including more regulatory variants in the computer model explains larger proportions of heritability for complex traits and metabolome. Farmers, breeders, scientists, and policy planners who need improve animal health and production based on genome-enabled animal selection will benefit from this study.

Technical Abstract: Many quantitative trait loci (QTL) are located in non-coding genomic regions. Therefore, QTL are assumed to affect gene regulation. Gene expression and RNA splicing are primary steps of transcription so QTL changing gene expression (eQTL) or RNA splicing (sQTL) are expected to significantly contribute to phenotypic variations. Here, we quantify the contribution of eQTL and sQTL detected from 16 tissues (N~5,000) to 37 complex traits of ~120k cattle. Using Bayesian methods, we show that including more regulatory variants in the model explains larger proportions of heritability. Across traits, cis and trans eQTL and sQTL detected from 16 tissues jointly explain ~70% (SE=0.5%) of heritability, 44% more than expected from the same number of random variants, where trans e/sQTL contribute 24% (14% more than expected). Multi-tissue cis and trans e/sQTL also explain 71% (SE=0.3%) of heritability for the metabolome, demonstrating the essential role of proximal and distal regulatory variants in shaping mammalian phenotypes.