Genomic Relatedness Strengthens Genetic Connectedness Across Management Units

Genetic connectedness refers to a measure of genetic relatedness across management units (e.g., herds and flocks) in animal breeding. Connectedness has shown to be an important measure of reliability when comparing genetic values derived from pedigree-based best linear unbiased prediction (BLUP) among management units. With the presence of high genetic connectedness in management units, BLUP is known to provide less biased comparisons between genetic values. Genetic connectedness has been applied successfully to pedigree-based BLUP; however, relatively little attention has been paid to using genomic information such as single nucleotide polymorphisms to estimate genetic connectedness. Thus, it remains unclear whether and to what extent genome-based information enhances connectedness. In this study, we assessed genome-based genetic 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). Relationship matrices were constructed from three different sources: pedigree (A), genomics (G), and hybrid of these two. We found that genomic information increased the estimate of connectedness among individuals from different management units compared to that of pedigree, and a disconnected design benefited the greatest. In the well-structured mice data (full-sib families), regardless of heritability (0.2 vs. 0.8), all 3 statistics inferred increased connectedness across-units when using G- rather than A-based relationships. With the cattle data, genomic relationships decreased PEVD across-units suggesting stronger connectedness. With r once scaling G to values between 0 and 2, which is intrinsic to A, connectedness also increased with genomic information. However, PEVD often increased and r often decreased when obtained using the alternative form of G, instead suggesting less connectedness. Such inconsistencies were not found with CD. Caution should be exercised when interpreting connectedness measures derived using genomic data as the underlying assumption is that relationships are built based on alleles being identical by state and not necessarily being identical by descent. We contend that genomic relatedness strengthens estimates of genetic connectedness across management units and has a potential to aid genomic evaluation of livestock species.