Genetic Architecture of Feed Efficiency in Mid-Lactation Holstein Dairy Cows

L.C. Hardie, M.J. van de Haar, R.J. Tempelman, K.A. Weigel, L.E. Armentano, G.R. Wiggans, R.F. Veerkamp, Y. de Haas, M.P. Coffey, E.E. Connor, M.D. Hanigan, C.R. Staples, Z. Wang, D.M. Spurlock

Research output: Contribution to conferenceAbstract

Abstract

The objective of this study was to explore the genetic architecture and biological basis of feed efficiency in lactating Holstein cows. In total, 4,918 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 as the residual of the regression of DMI on milk energy (MilkE), metabolic body weight (MBW), and body weight change along with systematic effects of parity class by days in milk fitted as a fifth order Legendre polynomial (fixed), ration within experiment within location (random) and test week (random). Adjusted phenotypes for DMI, MilkE, and MBW were calculated as the sum of the animal and residual components from the regression of each trait on the same systematic effects used for RFI. Animal relationships were represented with a genomic relationship matrix. Genome-wide association studies were performed for RFI, DMI, MilkE, and MBW using the Bayes B method in GenSel version 4.4 with 1% of SNP assumed to have a non-zero effect. One megabase windows with the greatest percent of the total genetic variation explained by the markers (TGVM) were identified, and within windows explaining more than 0.5% of the TGVM, the SNP with the highest posterior probability of a non-zero effect was tested for significant additive and dominance effects. Marker-based heritabilities were estimated for RFI (0.10), DMI (0.25), MilkE (0.20), and MBW (0.44). Tentative results for RFI identified regions explaining the greatest percent of the TGVM on chromosomes X, 9, and 14, and all tested SNP had significant additive effects (p < 0.05). Four of the 10 regions with the greatest effect on DMI also were included in the 10 regions with greatest effects on RFI, but not in the top 10 regions for MilkE or MBW, suggesting a genetic basis for intake that is unrelated to energy consumption required for milk production or maintenance. Candidate genes found within windows explaining the greatest percent of the TGVM for RFI include solute carrier family 25 member 14 and leptin. In conclusion, feed efficiency is a polygenic trait exhibiting genetic variation distinct from that underlying maintenance requirements and milk energy output.

Conference

ConferenceJoint Annual Meeting of the American Dairy Science Association®, the Canadian Society of Animal Science and the Western Section of the American Society of Animal Science
CountryUnited States
CitySalt Lake City
Period19/07/1623/07/16

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    Hardie, L. C., van de Haar, M. J., Tempelman, R. J., Weigel, K. A., Armentano, L. E., Wiggans, G. R., Veerkamp, R. F., de Haas, Y., Coffey, M. P., Connor, E. E., Hanigan, M. D., Staples, C. R., Wang, Z., & Spurlock, D. M. (2016). Genetic Architecture of Feed Efficiency in Mid-Lactation Holstein Dairy Cows. Abstract from Joint Annual Meeting of the American Dairy Science Association®, the Canadian Society of Animal Science and the Western Section of the American Society of Animal Science , Salt Lake City, United States.