|Hardie, Lydia - Iowa State University|
|Vandehaar, Michael - Michigan State University|
|Tempelman, Rob - Michigan State University|
|Weigel, Kent - University Of Wisconsin|
|Armentano, Lou - University Of Wisconsin|
|Wiggans, George - Retired ARS Employee|
|Veerkamp, Roel - Wageningen University|
|Haas, Yvette - Wageningen University|
|Coffey, Mike - Scottish Agricultural College|
|Hanigan, Mike - Virginia Polytechnic Institution & State University|
|Staples, Charlie - University Of Florida|
|Zhiquan, Wang - University Of Alberta|
|Dekkers, Jack - Iowa State University|
|Spurlock, Diane - Iowa State University|
Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/12/2017
Publication Date: 8/23/2017
Citation: Hardie, L.C., Vandehaar, M.J., Tempelman, R.J., Weigel, K.A., Armentano, L.E., Wiggans, G.R., Veerkamp, R.F., Haas, Y., Coffey, M.P., Connor, E.E., Hanigan, M.D., Staples, C., Zhiquan, W., Dekkers, J.C., Spurlock, D.M. 2017. The genetic and biological basis of feed efficiency in mid-lactation Holstein dairy cows. Journal of Dairy Science. 100(11):9061-9075. https://doi.org/10.3168/jds.2017-12604.
DOI: https://doi.org/10.3168/jds.2017-12604 Interpretive Summary: Improving dairy cow feed conversion efficiency to milk and body tissues is important for economic and environmental sustainability of the dairy industry. It is known that there is a genetic basis to the efficient use of feed by the dairy cow, but which underlying genes contribute to the trait are not known. Results of this study suggest that many genes, each with a small effect, impact feed efficiency and that the genetic basis of feed efficiency differs by parity. Chromosomal regions and candidate genes related to feed efficiency and other relevant biologically and economically important traits also are identified. The work is important to dairy scientists and animal breeders for identifying targets for genetic improvement of feed efficiency in dairy cattle.
Technical Abstract: The objective of this study was to characterize the genetic architecture and biological basis of feed efficiency in lactating Holstein cows. In total, 4,916 cows with actual or imputed genotypes for 60,671 SNP had individual feed intake, milk yield, milk composition, and body weight records. Cows were from research herds located in the United States, Canada, the Netherlands, and Scotland. Feed efficiency defined as residual feed intake (RFI) was calculated within location as the residual of the regression of dry matter intake (DMI) on milk energy (MilkE), metabolic body weight (MBW), change in body weight, and systematic effects. For RFI, DMI, MilkE, and MBW, bivariate analyses were performed in ASReml 4.0, considering each trait as separate traits within parity group in order to estimate variance components and genetic correlations between them. Animal relationships were established using a genomic relationship matrix. Genome-wide association studies were performed separately by parity group for RFI, DMI, MilkE, and MBW using the Bayes B method in GenSel version 4.0 with prior assumption that 1% of SNP have a non-zero effect. One megabase (Mb) windows with the greatest percent of the total genetic variation explained by the markers (TGVM) were identified, and neighboring regions explaining a large proportion of the TGVM were combined and reanalyzed. Heritabilities estimated for RFI were 0.14 in primiparous cows and 0.13 in multiparous cows. Genetic correlations between primiparous and multiparous cows were 0.76 for RFI, 0.78 for DMI, 0.92 for MBW and 0.61 for MilkE. No single 1-Mb window explained a significant proportion of the TGVM for RFI; however, analyses identified adjacent regions explaining the greatest percent of the TGVM on chromosome 27 in primiparous cows and on chromosome 4 in multiparous cows. Candidate genes in these regions include beta-3 adrenergic receptor and leptin, respectively. Between the two parity groups, 3 of the 10 windows with the greatest effect on DMI also were located nearby windows with greatest effects on RFI, but not in the top 10 regions for MilkE or MBW. This result suggests there is a genetic basis for intake that is unrelated to energy consumption required for milk production or maintenance. In conclusion, feed efficiency measured as RFI is a polygenic trait exhibiting a dynamic genetic basis and genetic variation distinct from that underlying expected maintenance requirements and milk energy output.