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Comparative aspects and IBD mapping of the resource populations

The objective was to search for QTL containing regions that were identical by descent (IBD) among the pure breed resource populations (RP1, RP2, RP4, RP5). Toward this goal, we looked at chromosomal haplotypes in RP1 for the six regions chosen for intensive analysis by the BovMAS consortium. This led to analysis of linkage disequilibrium (LD) within BTA13 (chosen by the consortium for high resolution mapping studies) across all four purebred RPs.

The assumption was that high LD might identify regions of IBD. We also developed an efficient methodology: co-segregant pools analysis for determining sire haplotypes. Chromosomal haplotypes. Chromosome haplotypes for six QTLR regions chosen for more intensive analysis by the consortium, were constructed for 27 RP1 sires. In many instances the relationship among individuals sharing the same chromosomal haplotype, was not close; and some haplotypes were shared by 4, 5, and in one case 7 individuals.

This indicated the possibility of more extensive IBD in the studied regions. LD studies of BTA13. Materials and Methods: 411 individuals from RP 1, 4 and 5 were genotyped at 19 microsatellite markers distributed over BTA13; 273 individuals from RP2 were genotyped at 35 markers distributed over the same region (including 18 of above 19 markers). Haplotypes were constructed by the Simwalk2 and PowerMarker software. LD measures, calculated separately for each RP were: D, Monte Carlo approximation of Fisher exact test, and the standardized c2.

The c2 measure indicates the potential usefulness of marker-QTL LD as a means of selection. Results: Mean values for D' (known to give artefactually high values in multi-allelic situations) across the entire target region were 0.314, 0.249, 0.281, and 0.487 for RP1, 2, 4, 5, respectively; mean values of c2 were much less (0.124, 0.062, 0.096 and 0.092, respectively). LD decreased with increasing distance between loci according to the accepted expression LD = 1/(1+4bd), where d = distance in Morgans between loci, and b is a regression coefficient that relates to effective population size. For RP1, 2, 4, 5, the b coefficients were 25.6, 86.3, 28.0 and 45.1, respectively.

This is as expected, given the population structure and the intensive one-way selection of the two Holstein populations (RP1,4), as compared to the Brown Swiss (RP5) (selected for dual purpose till 40 years ago) and the dual-purpose selected Simmental (RP2). To search for a selection signature, a moving average of c2, taken 5 markers at a time along the chromosome, was calculated. All populations presented a maximum in the region from 35 to 50 cM, indicating a possible selection signature. Although the values obtained for c2 over 0-5 cM (0.193, 0.109, 0.218 and 0.133, for RP1, 2, 4, 5) were larger than the average values, they were still much too small to be a useful tool for selection. LD values between markers separated by 50 cM or more distributed according to chance expectations; there were no indications of long range LD.

Haplotype identification by co-segregant DNA pools. Haplotype identification of individual dairy sires is essential for interval mapping, and for tracing identified QTL in pedigrees for MAS. Parental genotypes are effective in determining sire haplotypes for informative markers (where sire and parent do not share the same genotype). Progeny genotypes can resolve all markers, but many daughters must be genotyped. In co-segregant pool analysis, progeny of the sire are divided into two groups according to the transmitted sire allele at an "index" marker in the haplotype.

DNA of the two marker allele groups is separately pooled. Markers belonging to one of the sire haplotype centered at the index markers will show high frequency in one of the pools, those belonging to the other haplotype will show high frequency in the alternative pool. In this way, a series of linked markers alleles can be rapidly assigned to the same haplotype. Materials and Methods.

These approaches were compared in a data set consisting of semen samples of 8 RP1 sires and their sires, and milk samples of their daughters. Results: Almost two-thirds of sire markers could be ordered in haplotypes on the basis of the genotypes of their sires. Daughter genotypes were able to resolve all markers, but this required about 50 daughter genotypes. Co-segregant pools were able to resolve sire haplotypes over regions of up to 30 cM to either side of the index marker.

Thus, co-segregant pools can serve as an efficient means for haplotype identification. Conclusions: The LD findings (low LD even across 5 cM wide distances, absence of long distance LD) are important for groups attempting to achieve high resolution LD mapping in dairy cattle or to use LD for MAS. Co-segregant pools can be useful to groups involved in interval and LD mapping, and in MAS of dairy cattle and other animal populations.

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