|LI, BINGJIE - Oak Ridge Institute For Science And Education (ORISE)|
|FANG, LINGHAO - University Of Edinburgh|
Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/19/2019
Publication Date: 12/1/2019
Citation: Li, B., Fang, L., Null, D.J., Hutchison, J.L., Connor, E.E., Van Raden, P.M., Cole, J.B. 2019. High-density genome-wide association study for residual feed intake in Holstein dairy cattle. Journal of Dairy Science. 102(12):11067-11080. https://doi.org/10.3168/jds.2019-16645.
Interpretive Summary: We carried out a genome-wide association study for residual feed intake (RFI) in Holstein cattle using high-density genotypes to identify candidate genes and biological pathways associated with RFI. Data were from 4,823 lactations of 3,947 Holstein cows in research herds in the USA. RFI was shown to be a highly polygenic trait being regulated by many small-sized effects. The top signals associated with RFI were related to (residual) feed intake, energy balance, digestion and metabolism of carbohydrates and proteins, immunity, mitochondrial activities, rumen development, skeletal development, and spermatogenesis. The regions of 40.7 to 41.5 Mb on chromosome 25 and 57.7 to 58.2 Mb on chromosome 18 were the top associated regions for RFI.
Technical Abstract: Improving feed efficiency (FE) of dairy cattle has implications for improving farm profitability and reducing the environmental footprint of the dairy industry. Residual feed intake (RFI), a candidate FE trait in dairy cattle, can be defined to be genetically uncorrelated with major energy sink traits (e.g., milk production, body weight) by including genomic predicted transmitting ability (GPTA) of energy sink traits in the genetic analyses for RFI. In this study, we aimed to study the genetic basis of RFI through genome-wide association (GWA) analyses and post-GWA enrichment analyses, and to identify candidate genes and biological pathways associated with RFI in dairy cattle. Residual feed intake data were collected from 4,823 lactations of 3,947 Holstein cows in 9 research herds in the USA. Of the 3,947 cows with phenotypes, 3,555 cows were genotyped with high-density chips of 312,614 SNP. A single-step GWA method was used to combine information from genotyped and non-genotyped animals with phenotypes as well as their ancestors’ information. The estimated genomic breeding values from a single-step genomic BLUP were back-solved to obtain the individual single nucleotide polymorphism (SNP) effects for RFI. The proportion of genetic variance explained by each 5-SNP sliding window was also calculated for RFI using the postGSf90 program. Based on our GWA analyses, RFI was shown to be a highly polygenic trait that is regulated by many genes with small effects. The closest genes to the top SNP and sliding windows were related to (residual) feed intake, energy homeostasis and energy balance regulation, digestion and metabolism of carbohydrates and proteins, immune regulation, mitochondrial ATP activities, rumen development, skeletal muscle development, and spermatogenesis. The region of 40.7 to 41.5 Mb on BTA25 was the top associated region for RFI. The closest genes to this region, CARD11 and EIF3B, were related to RFI of dairy cattle and FE of broilers in previous studies, respectively. Another candidate region, 57.7 to 58.2 Mb on BTA18, is associated with RFI but also overlaps a QTL for DMI in dairy cattle. Post-GWA enrichment analyses were carried out afterwards by a sum-based marker-set test using four public annotation databases: gene otology, KEGG pathways, reactome pathways, and medical subject heading (MeSH) terms. The findings from the enrichment analyses were consistent with those from the top GWA signals. Across the four annotation databases, GWA signals for RFI were highly enriched in the biosynthesis and metabolism of amino acids and proteins, digestion and metabolism of carbohydrate, skeletal development, mitochondrial electron transport, immunity, rumen bacteria activities, and sperm motility. The current study of high-density GWA analyses and post-GWAS enrichment analyses offered insight into the genetic basis of RFI and identified candidate regions and biological pathways associated with RFI in dairy cattle.