Integrating temporal genomic and transcriptomic analyses to decipher genetic basis of feed intake in dairy cattle

Abstract

BackgroundFood intake is a complex trait in living organisms, where the genetics of food intake have been widely studied in humans, mice, Drosophila, cattle, pigs, chicken, and fish. In dairy cattle, intake of feed is highly linked to individuals energy balance, health, production, efficiency, and the environmental footprint of the individual to the society. Recent studies have provided solid evidence of the genetic variation of feed intake (FI) in dairy cattle population, but the genetic basis and molecular mechanism of dairy feed intake is still far from clear especially considering the lactation cycles of dairy cattle. This study aims to integrate stage-dependent genome-wide association (GWA) analyses, regional heritability mapping (RHM), and RNA-seq gene expression analyses to identify temporal functional variants associated with cattle dry matter intake (DMI) across multiple stages in lactation cycles. A total of 750,000 daily DMI records from 7,500 lactations of 2,300 cows were available with animals genotype and pedigree information. Total RNA-seq from blood were generated for 121 individuals in this population from 2 lactation stages. Data were split into multiple lactations stages for GWA, RHM, and transcriptomic analyses. ResultsStage-dependent GWAS and RHM identified 21 significant loci associated with DMI across multiple lactation stages. A total of 45 candidate genes were identified from GWA and RHM. Among all the 45 genes, six genes were later found significantly differently expressed between high and low feed intake animal groups using gene expression information from RNA-seq data. These genes show links to sugar and adipose metabolism, milk production, body weight, dopamine-reward pathways and immune functions. ConclusionsOur multi-omics analyses provide molecular evidence that the genetic basis of cattle DMI across lactation is not static. Temporal genomic variants associated with FI were identified with their transcriptomic patterns investigated, decoding the molecular mechanisms underlying DMI. Overall, the associated variants and candidate genes uncovered herein decoded genetic architecture of dairy feed intake on a temporal and multi-omics basis, enhancing the understanding of basic biology of dairy feed intake and informing breeding strategies aimed at improving dairy feed efficiency.