Genetic connectedness refers to a measure of genetic relatedness across management units (e.g., herds and flocks). With the presence of high genetic connectedness in management units, best linear unbiased prediction (BLUP) is known to provide reliable comparisons between estimated genetic values. Genetic connectedness has been studied for pedigree-based BLUP; however, relatively little attention has been paid to using genomic information to measure connectedness. In this study, we assessed genome-based connectedness across management units by applying prediction error variance of difference (PEVD), coefficient of determination (CD), and prediction error correlation r to a combination of computer simulation and real data (mice and cattle). We found that genomic information ([Formula: see text]) increased the estimate of connectedness among individuals from different management units compared to that based on pedigree ([Formula: see text]). A disconnected design benefited the most. In both datasets, PEVD and CD statistics inferred increased connectedness across units when using [Formula: see text]- rather than [Formula: see text]-based relatedness, suggesting stronger connectedness. With r once using allele frequencies equal to one-half or scaling [Formula: see text] to values between 0 and 2, which is intrinsic to [Formula: see text] connectedness also increased with genomic information. However, PEVD occasionally increased, and r decreased when obtained using the alternative form of [Formula: see text] instead suggesting less connectedness. Such inconsistencies were not found with CD. We contend that genomic relatedness strengthens measures of genetic connectedness across units and has the potential to aid genomic evaluation of livestock species.
Keywords: coefficient of determination; genomic connectedness; predication error variance of difference; prediction error correlation; relatedness.
Copyright © 2017 Yu et al.