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Lastly, the covariance sign between ROH4Mb and additive SNP effect of a region was heterogeneous across the genome. Multiple potential epistatic interactions were characterized based on the GBM analysis.
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Only one association (BTA7) was found for CI and ROH4Mb for the US population. ResultsĪssociations between yield traits and ROH4Mb were found for regions on BTA13, BTA23 and BTA25 for the US population and BTA3, BTA7, BTA17 for the AU population. Phenotypes to determine ROH4Mb and additive effects were residuals from the two-stage approach and yield deviations, respectively. The relationship between the additive and ROH4Mb of a region was characterized based on the (co)variance of 500 kb estimated genomic breeding values derived from a Bayesian LASSO analysis. In the second stage, these residuals were regressed on ROH4Mb using a single marker regression model and a gradient boosted machine (GBM) algorithm. In the first stage, residuals were obtained from a model that accounted for the portion explained by the estimated breeding value. A ROH statistic (ROH4Mb), which counts the frequency of a SNP being in a ROH of at least 4 Mb was calculated across the genome. Genotyped cows with phenotypes on MY, FY and PY ( n = 6751 US n = 3974 AU) and CI ( n = 5816 US n = 3905 AU) were used in a two-stage analysis. The objective of this study was to characterize regions that have an impact on a runs of homozygosity (ROH) metric and estimate their association with the additive genetic effect of milk (MY), fat (FY) and protein yield (PY) and calving interval (CI) using Australia (AU) and United States (US) Jersey cows. Differences in genome-level homozygosity between countries may give rise to regions that result in inbreeding depression to differ. Variation in environment, management practices, nutrition or selection objectives has led to a variety of different choices being made in the use of genetic material between countries.