Reliability of direct genomic values for animals with different relationships within and to the reference population
Pszczola, M.J. ; Strabel, T. ; Mulder, H.A. ; Calus, M.P.L. - \ 2012
Journal of Dairy Science 95 (2012)1. - ISSN 0022-0302 - p. 389 - 400.
quantitative trait loci - genetic-relationship information - estimated breeding values - dairy-cattle - linkage disequilibrium - holstein population - selection - accuracy - association - predictions
Accuracy of genomic selection depends on the accuracy of prediction of single nucleotide polymorphism effects and the proportion of genetic variance explained by markers. Design of the reference population with respect to its family structure may influence the accuracy of genomic selection. The objective of this study was to investigate the effect of various relationship levels within the reference population and different level of relationship of evaluated animals to the reference population on the reliability of direct genomic breeding values (DGV). The DGV reliabilities, expressed as squared correlation between estimated and true breeding value, were calculated for evaluated animals at 3 heritability levels. To emulate a trait that is difficult or expensive to measure, such as methane emission, reference populations were kept small and consisted of females with own performance records. A population reflecting a dairy cattle population structure was simulated. Four chosen reference populations consisted of all females available in the first genotyped generation. They consisted of highly (HR), moderately (MR), or lowly (LR) related animals, by selecting paternal half-sib families of decreasing size, or consisted of randomly chosen animals (RND). Of those 4 reference populations, RND had the lowest average relationship. Three sets of evaluated animals were chosen from 3 consecutive generations of genotyped animals, starting from the same generation as the reference population. Reliabilities of DGV predictions were calculated deterministically using selection index theory. The randomly chosen reference population had the lowest average relationship within the reference population. Average reliabilities increased when average relationship within the reference population decreased and the highest average reliabilities were achieved for RND (e.g., from 0.53 in HR to 0.61 in RND for a heritability of 0.30). A higher relationship to the reference population resulted in higher reliability values. At the average squared relationship of evaluated animals to the reference population of 0.005, reliabilities were, on average, 0.49 (HR) and 0.63 (RND) for a heritability of 0.30; 0.20 (HR) and 0.27 (RND) for a heritability of 0.05; and 0.07 (HR) and 0.09 (RND) for a heritability of 0.01. Substantial decrease in the reliability was observed when the number of generations to the reference population increased [e.g., for heritability of 0.30, the decrease from evaluated set I (chosen from the same generation as the reference population) to II (one generation younger than the reference population) was 0.04 for HR, and 0.07 for RND]. In this study, the importance of the design of a reference population consisting of cows was shown and optimal designs of the reference population for genomic prediction were suggested.
Whole Genome Scan to Detect Chromosomal Regions Affecting Multiple Traits in Dairy Cattle
Schrooten, C. ; Bink, M.C.A.M. ; Bovenhuis, H. - \ 2004
Journal of Dairy Science 87 (2004)10. - ISSN 0022-0302 - p. 3550 - 3560.
marker-assisted selection - false discovery rate - milk-production - holstein population - daughter design - loci - linkage - yield - efficiency - complexes
Chromosomal regions affecting multiple traits ( multiple trait quantitative trait regions or MQR) in dairy cattle were detected using a method based on results from single trait analyses to detect quantitative trait loci (QTL). The covariance between contrasts for different traits in single trait regression analysis was computed. A chromosomal region was considered an MQR when the observed covariance between contrasts deviated from the expected covariance under the null hypothesis of no pleiotropy or close linkage. The expected covariance and the confidence interval for the expected covariance were determined by permutation of the data. Four categories of traits were analyzed: production ( 5 traits), udder conformation ( 6 traits), udder health ( 2 traits), and fertility ( 2 traits). The analysis of a granddaughter design involving 833 sons of 20 grandsires resulted in 59 MQR(alpha = 0.01, chromosomewise). Fifteen MQR were found on Bos taurus autosome (BTA) 14. Four or more MQR were found on BTA 6, 13, 19, 22, 23, and 25. Eight MQR involving udder conformation and udder health and 4 MQR involving production traits and udder health were found. Five MQR were identified for combinations of fertility and udder conformation traits, and another 5 MQR were identified for combinations of fertility and production traits. For 22 MQR, the difference between the correlation attributable to the MQR and the overall genetic correlation was > 0.60. Although the false discovery rate was relatively high (0.52), it was considered important to present these results to assess potential consequences of using these MQR for marker-assisted selection.
Quantitative trait loci affecting milk production traits in Finnish Ayrshire dairy cattle
Viitala, S.M. ; Schulman, N.F. ; Koning, D.J. de; Elo, K. ; Kinos, R. ; Virta, A. ; Virta, J. ; Maki-Tanila, A. ; Vilkki, J.H. - \ 2003
Journal of Dairy Science 86 (2003)5. - ISSN 0022-0302 - p. 1828 - 1836.
genetic-linkage map - bovine genome - holstein population - health traits - chromosome-6 - regression - daughter - designs - scan - qtl
A whole genome scan of Finnish Ayrshire was conducted tomap quantitative trait loci (QTL) affecting milk production. The analysis included 12 half-sib families containing a total of 494 bulls in a granddaughter design. The families were genotyped with 150 markers to construct a 2764 cM (Haldane) male linkage map. In this study interval mapping with multiple-marker regression approach was extended to analyse multiple chromosomes simultaneously. The method uses identified QTL on other chromosomes as cofactors to increase mapping power. The existence of multiple QTL on the same linkage group was also analyzed by fitting a two-QTL model to the analysis. Empirical values for chromosome-wise significance thresholds were determined using a permutation test. Two genome-wise significant QTL were identified when chromosomes were analyzed individually, one affecting fat percentage on chromosome (BTA) 14 and another affecting fat yield on BTA12. The cofactor analysis revealed in total 31 genome-wise significant QTL. The result of two-QTL analysis suggests the existence of two QTL for fat percentage on BTA3. In general, most of the identified QTL confirm results from previous studies of Holstein-Friesian cattle. A new QTL for all yield components was identified on BTA12 in Finnish Ayrshire.