Marker-assisted breeding value estimation for mastitis resistance in Finnish Ayrshire cattle.

Marker-assisted breeding value estimation is expected to increase the accuracy of estimated breeding values, especially for traits with low heritability. Several quantitative trait loci (QTL) have been found for somatic cell score and clinical mastitis. The objective of this study was to demonstrate marker-assisted breeding value estimation, combining data of genotyped and ungenotyped animals in a large pedigree population using either identical-by-descent (IBD) or identical-by-state (IBS) haplotypes for some previously identified QTL regions for somatic cell score and clinical mastitis in Finnish Ayrshire cattle. For both methods, QTL variances were estimated based on daughter yield deviations of genotyped bulls. The QTL explained only a small proportion of genetic variance, especially with IBS haplotypes. Using IBD haplotypes gave more reranking of bulls and cows than using IBS haplotypes. Cross-validation showed no increase in predictive ability when using IBS haplotypes compared with conventional breeding value estimation, whereas a decrease in predictive ability was observed with IBD haplotypes. Furthermore, computing time was lower and convergence was better with IBS haplotypes than with IBD haplotypes. In this study on mastitis resistance in Finnish Ayrshire, conventional breeding value estimation would be advocated because of the lack in improvement of accuracy and predictive ability when using marker-assisted breeding value estimation. However, in situations where IBS haplotypes would explain 10 to 20% or more of the genetic variance, marker-assisted breeding value estimation with IBS haplotypes may yield greater accuracy and predictive ability than conventional breeding value estimation.

Mapping of fertility traits in Finnish Ayrshire by genome-wide association analysis.

A whole-genome scan using single marker association was used to detect chromosome regions associated with seven female fertility traits in Finnish Ayrshire dairy cattle. The phenotypic data consisted of de-regressed estimated breeding values for 340 bulls which were estimated using a single trait model. Genotypes were obtained with the Illumina BovineSNP50 panel and a total of 35 630 informative, high-quality single nucleotide polymorphism (SNP) markers were used. The association analysis was performed using a mixed-model approach which fitted a fixed effect for each SNP and a random polygenic effect. We detected eleven genome-wide significant associations on eight different chromosomes. With at least chromosome-wise significance after Bonferroni correction, sixteen SNPs on nine chromosomes showed significant associations with one or more fertility traits. The results confirmed quantitative trait loci on three chromosomes (1, 2 and 20) for fertility traits previously reported for the same breed and one on chromosome four previously detected in Holstein cattle.

Fine mapping of quantitative trait loci for mastitis resistance on bovine chromosome 11.

Quantitative trait loci (QTL) affecting clinical mastitis (CM) and somatic cell score (SCS) were mapped on bovine chromosome 11. The mapping population consisted of 14 grandsire families belonging to three Nordic red cattle breeds: Finnish Ayrshire (FA), Swedish Red and White (SRB) and Danish Red. The families had previously been shown to segregate for udder health QTL. A total of 524 progeny tested bulls were included in the analysis. A linkage map including 33 microsatellite and five SNP markers was constructed. We performed combined linkage disequilibrium and linkage analysis (LDLA) using the whole data set. Further analyses were performed for FA and SRB separately to study the origin of the identified QTL/haplotype and to examine if it was common in both populations. Finally, different two-trait models were fitted. These postulated either a pleiotropic QTL affecting both traits; two linked QTL, each affecting one trait; or one QTL affecting a single trait. A QTL affecting CM was fine-mapped. In FA, a haplotype having a strong association with a high negative effect on mastitis resistance was identified. The mapping precision of an earlier detected SCS-QTL was not improved by the LDLA analysis because of lack of linkage disequilibrium between the markers used and the QTL in the region.

Quantitative trait Loci for health traits in Finnish Ayrshire cattle.

A whole-genome scan was conducted to search for quantitative trait loci (QTL) affecting health traits in Finnish Ayrshire dairy cattle. The mapping population consisted of 12 bulls and their 491 sons in a granddaughter design. A total of 150 markers were typed covering all 29 autosomes. The traits under study were somatic cell score, mastitis, and a group of other veterinary treatments. Effects of the QTL and positions were estimated with the regression method. When carrying out interval mapping on each chromosome, cofactors were used to adjust for QTL identified at other chromosomes. Empirical P-values were obtained by permutation. Altogether 17 QTL were detected with genomewise significant P-values in the across family analysis. Quantitative trait loci affecting SCS were identified on chromosomes 1, 3, 11, 18, 21, 24, 27, 29, and QTL for mastitis on chromosomes 14, 18. Quantitative trait loci for other veterinary treatments were found on chromosomes 1, 2, 5, 8, 15, 22, and 23. The allele substitution effects were from 0.5 to 1.7 genetic standard deviations. The positions of these health QTL did not overlap with milk QTL detected in previous studies of the same population.

Quantitative trait loci affecting milk production traits in Finnish Ayrshire dairy cattle.

A whole genome scan of Finnish Ayrshire was conducted to map 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.