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A map of QTL affecting milk production traits in the Israel Holstein

The objective was to develop a complete map of QTL affecting milk protein percent (PP) in the Israel Holstein cattle population, and investigate the effects of the detected loci on milk yield (MY) and protein yield (PY); and of selected loci on milk somatic cell counts (MSCC) and female fertility (FF). A daughter design, with selective DNA pooling based on milk samples was used. The study involved 18 sires, with a minimum of 1800 daughters per sire. PP, Materials and Methods:

All sires were included in the PP study. Based on estimated breeding values for milk PP (EBVPP), the highest and lowest 10-20% of daughters of each sire were sampled to make up the pools. 177 microsatellite markers distributed over all 29 bovine autosomes were used. Comparison-wise error rates (P-values) for sire by marker tests, and for marker tests across sires were according to Mosig et al. (2001). A Marginal PFP (MPFP) <= 0.05 was required for a declaration of significance at the marker level, and a MPFP <= 0.10 within significant markers, at the sire x marker level. The MPFP (see WP 12) is a modification of the "proportion of false positives (PFP)" criterion (Fernando et al., 2003); and differs from PFP in that significance is set according to the PFP within the last added group of tests. Results: Average heterozygosity among the QTL uncovered in this study was 0.44. Average standardized allele substitution effect of QTL was 0.24 (0.16-0.33). Differences in effects among QTL were not significant, and QTL with large effects were not found.

There were 101 significant markers. Chromosomes with a single QTL containing region (QTLR) were identified as a having group of significant markers flanked by non-significant markers; Multiple QTLR on a chromosomes were identified by groups of significant markers separated by non-significant markers. A total of 60 QTLR were defined; most chromosomes appeared to carry two or more QTL affecting PP; BTA15, 17, 24 and 28 did not carry any.

The total effect of all 60 putative QTL summed to 0.9 EBVPP and appear to account for the total genetic variation in EBVPP in the population. MY and PY, Materials and Methods: The study was based on ten sires. Pools were prepared and genotyped for 134 microsatellite markers distributed over 25 autosomes, many of which had been found previously to be significant for PP. Results: Of the 134 markers, 37 were significant for one trait only, 44 for two traits, and 50 for all three traits. Thus, many of the QTL affecting PP also affect MY and PY. Within the significant sire-marker-trait combinations, there were 342 combinations significant for one trait only, 110 significant for two traits, and 27 for all three traits. When the effects on PP and MY were both significant, 79% of sire-marker combinations with positive effects on PP, had negative effects on MY, but were almost equally divided between positive and negative effects on PY; 65% of sire-marker combinations with positive effects on MY had positive effects on PY.

The overall impression is that the major effect of the QTL is on the PP/MY axis, and effects on PY are a secondary consequence of minor variation in the relative effects of specific QTL on PP or MY. MSCC and FF, Materials and Methods: The study is based on six sires and concentrated on the six chromosomal regions selected for more intensive study by the BovMAS consortium: BTA3, 9, 11, 13, 14, and 20; 24 markers were tested. Results: Significant markers for PP, MSCC and FF were found on all six chromosomes. The 24 markers included a total of 313 sire-marker-trait combinations.

Very few sire-marker combinations were significant for more than one trait. Thus, the relationships between the three traits appear to be limited, compared to the relationships found among PP, PY and MY. Conclusions: The results of these three studies are of general scientific interest, in that they provide the first complete map of a quantitative trait (PP) in a segregating population, and show that essentially all of the additive genetic variation can be explained by mapped QTL.

The results provide a basis for high resolution mapping and cloning of the genes responsible for genetic variation in milk production traits and for MAS programs. The large number of identified QTL show that the potential gains from MAS will extend over a long period of time and result in major increases in productivity. This conclusion is of interest to cattle breeding organizations that are weighing whether to introduce a MAS program. Based on these results, there are ongoing discussions of implementation of a MAS program for the Israel Holstein population.

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Givat Ram Campus
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