|Van Tassell, Curtis - Curt|
Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/1/2003
Publication Date: 2/2/2004
Citation: Ashwell, M.S., Heyen, D.W., Sonstegard, T.S., Van Tassell, C.P., Da, Y., Van Raden, P.M., Ron, M., Weller, J.I., Lewin, H.A. 2004. Detection of quantitative trait loci affecting milk production,health, and reproductive traits in Holstein cattle. Journal of Dairy Science. vol. 87(2): pp. 468-75.
Interpretive Summary: Traditional methods of genetic selection have greatly improved milk production, but have difficulty improving traits like reproduction and disease resistance. Lack of selection for these economically important traits has a huge impact on global competitiveness, the sustainability of producers, and the entire dairy industry. The objective of this study was to identify DNA markers that can be used in the selection of bulls, with our long-term goal being to identify chromosomal regions that are important for milk production and female fertility in the US commercial Holstein population. The 29 cattle chromosomes were scanned with 367 DNA markers. Variations at some of these markers were associated with significant effects on pregnancy rate, protein and fat yields, and protein and fat percentages. Application of DNA marker information for these traits should increase the rate of genetic improvement for milk production and fertility.
Technical Abstract: We report putative quantitative trait loci affecting female fertility and milk production traits using the merged data from groups that conducted independent genome scans in Dairy Bull DNA Repository grandsire families to identify quantitative trait loci affecting economically important traits. Six families used by both groups were genotyped for 367 microsatellite markers covering 2713.5 cM of the cattle genome (90%), with an average spacing of 7.4 cM. Regression interval mapping software was used for the analysis within and across families. Phenotypic traits included PTA for pregnancy rate and daughter deviations for milk, protein and fat yields, protein and fat percentages, somatic cell score and productive life. Permutation was used to calculate chromosome-wide significance thresholds. The merged dataset identified putative quantitative trait loci not detected in the separate studies, and for the first time allowed detection of pregnancy rate QTL. Sixty-one putative significant marker effects were identified within families and thirteen were identified across-families. Highly significant effects were found on chromosome 3 affecting fat percentage and protein yield, on chromosome 6 affecting protein and fat percentages, on chromosome 14 affecting fat percentage, on chromosome 18 affecting pregnancy rate, and on chromosome 20 affecting protein percentage.