Abstract
A whole genome scan was carried out to detect quantitative trait loci (QTL) for fertility traits in Finnish Ayrshire cattle. The mapping population consisted of 12 bulls and 493 sons. Estimated breeding values for days open, fertility treatments, maternal calf mortality and paternal non-return rate were used as phenotypic data. In a granddaughter design, 171 markers were typed on all 29 bovine autosomes. Associations between markers and traits were analysed by multiple marker regression. Multi-trait analyses were carried out with a variance component based approach for the chromosomes and trait combinations, which were observed significant in the regression method. Twenty-two chromosome-wise significant QTL were detected. Several of the detected QTL areas were overlapping with milk production QTL previously identified in the same population. Multi-trait QTL analyses were carried out to test if these effects were due to a pleiotropic QTL affecting fertility and milk yield traits or to linked QTL causing the effects. This distinction could only be made with confidence on BTA1 where a QTL affecting milk yield is linked to a pleiotropic QTL affecting days open and fertility treatments.
Highlights
High fertility in cows is economically important for dairy farmers
The objectives of this study were (i) to use the Finnish granddaughter design data to map quantitative trait loci (QTL) for fertility traits; (ii) to distinguish between pleiotropy and linked QTL when a region is affecting more than one fertility trait or at least one fertility trait and milk trait identified previously by Viitala et al [46]
Overall the results indicate that two linked QTL are segregating on BTA1, one QTL affecting Days open (DO) and Fertility treatments (FT) and the other affecting milk yield 1st lactation (MY)
Summary
Low fertility leads to higher replacement costs, veterinary costs, labour costs and costs due to reduced milk production. Genetic progress by traditional breeding can be slow and the negative correlations with production traits are of special concern [34]. Pösö and Mäntysaari [34] have reported that a genetic improvement of 500 kg milk yield would increase cases of ovulatory disorders by 1.7%-units and days open by 4.2 days. These are traits for which marker-assisted selection could increase genetic progress compared to traditional breeding schemes [25, 38]
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