Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Oct 5;7(10):3543-3556.
doi: 10.1534/g3.117.300151.

Genomic Relatedness Strengthens Genetic Connectedness Across Management Units

Affiliations
Free PMC article

Genomic Relatedness Strengthens Genetic Connectedness Across Management Units

Haipeng Yu et al. G3 (Bethesda). .
Free PMC article

Abstract

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.

Figures

Figure 1
Figure 1
Prediction error variance of the difference (PEVD) across five management units in the mice dataset. Management units “19F,” “29A,” and “36F” share at least one pair of full-sibs individuals with each other, whereas “12A” and “13C” do not share any individuals across management units. The left and right are pedigree-based (A) and genomic-based (G) connectedness, respectively. Darker color represents less genetic connectedness.
Figure 2
Figure 2
Four simulation scenarios considered in the cattle dataset. Scenario 1: completely disconnected; eight clusters assigned to separate MU. Scenario 2: disconnected; clusters 1, 2, 3, 4, and 5 assigned to MU 1 and clusters 6, 7, and 8 assigned to MU 2. Scenario 3: partially connected; clusters 1, 2, and 3 assigned to MU 1, clusters 7 and 8 assigned to MU 2, and the remaining clusters 4, 5, and 6 assigned to both MUs 1 and 2, which act as links among clusters or individuals that partially connect the two MUs. Scenario 4: connected; all clusters (1–8) were equally assigned to MUs 1 and 2. MU, management unit.
Figure 3
Figure 3
Percentage of relative increase in prediction error variance of the difference (PEVD) across management units in comparison to base scenario 1 (S1). Two heritability values 0.8 and 0.2 were simulated. S1 (completely disconnected), scenario 2 (S2, disconnected), scenario 3 (S3, partially connected), and scenario 4 (S4, connected) represent four management unit scenarios. Left: A matrix. Right: G matrix.
Figure 4
Figure 4
Principal component (PC) plots for scenario 1 (SC1) with coefficient of determination (CD) statistics. The first and second rows are according to heritability of 0.8 and of 0.2. The first and second columns are derived from pedigree-based (A) and genome-based (G) CD, respectively. The PC plots were grouped by clusters and colored in different colors. Individuals within the same cluster were grouped by the circles. var., variance.
Figure 5
Figure 5
Principal component (PC) plots for scenario 4 (SC4) with coefficient of determination (CD) statistics. The first and second rows are according to heritability of 0.8 and of 0.2. The first and second columns are derived from pedigree-based (A) and genome-based (G) CD, respectively. The PC plots were grouped by clusters and colored in different colors. Individuals within the same cluster were grouped by the circles.

Similar articles

See all similar articles

Cited by 3 articles

References

    1. Christensen O. F., Lund M. S., 2010. Genomic prediction when some animals are not genotyped. Genet. Sel. Evol. 42: 2. - PMC - PubMed
    1. Eikje L. S., Lewis R. M., 2015. Strong connectedness within Norwegian Cheviot and Fur sheep ram circles allows reliable estimation of breeding values. J. Anim. Sci. 93: 3322–3330. - PubMed
    1. Fernando R., Grossman M., 1989. Marker assisted selection using best linear unbiased prediction. Genet. Sel. Evol. 21: 467–477.
    1. Fisher R. A., 1918. The correlation between relatives on the supposition of Mendelian inheritance. Trans. R. Soc. Edinb. 52: 399–433.
    1. Fouilloux M. N., Clément V., Laloë D., 2008. Measuring connectedness among herds in mixed linear models: from theory to practice in large-sized genetic evaluations. Genet. Sel. Evol. 40: 145–159. - PMC - PubMed

Publication types

LinkOut - more resources

Feedback