Abstract
The concept of breeding values, an individual's phenotypic deviation from the population mean as a result of the sum of the average effects of the genes they carry, is of great importance in livestock, aquaculture, and cash crop industries where emphasis is placed on an individual's potential to pass desirable phenotypes on to the next generation. As breeding or genetic values (as referred to here) cannot be measured directly, estimated genetic values (EGVs) are based on an individual's own phenotype, phenotype information from relatives, and, increasingly, genetic data. Because EGVs represent additive genetic variation, calculating EGVs in an extended human pedigree is expected to provide a more refined phenotype for genetic analyses. To test the utility of EGVs in genome-wide association, EGVs were calculated for 847 members of 20 extended Mexican American families based on 100 replicates of simulated systolic blood pressure. Calculations were performed in GAUSS to solve a variation on the standard Best Linear Unbiased Predictor (BLUP) mixed model equation with age, sex, and the first 3 principal components of sample-wide genetic variability as fixed effects and the EGV as a random effect distributed around the relationship matrix. Three methods of calculating kinship were considered: expected kinship from pedigree relationships, empirical kinship from common variants, and empirical kinship from both rare and common variants. Genome-wide association analysis was conducted on simulated phenotypes and EGVs using the additive measured genotype approach in the SOLAR software package. The EGV-based approach showed only minimal improvement in power to detect causative loci.
Highlights
Given increasing evidence that the majority of variation in common, complex traits is the result of a large number of individual variants with small effects, refining phenotypes to minimize the environmental component is one possible approach to increasing power to detect these variants
Because estimated genetic values (EGVs) are a product of genetic similarities of individuals in the sample, the use of empirically derived relationship matrices in calculating EGVs should increase power to localize genetic factors in genome-wide association (GWA) studies, an observation that has driven the use of relationship matrices in artificial selection [[5] and others]
The heritability of the EGVs is approximately double the heritability of simulated systolic blood pressure (SBP) with covariates included. This is expected as the computation of EGVs removes much of the environmental variation seen in SBP
Summary
Given increasing evidence that the majority of variation in common, complex traits is the result of a large number of individual variants with small effects, refining phenotypes to minimize the environmental component is one possible approach to increasing power to detect these variants. Because EGVs represent predominantly additive genetic variance (some additional environmental variance may be included where it mimics relatedness), the use of EGVs in place of standard phenotypes will increase heritability and may increase power to detect variants of smaller effect. Because EGVs are a product of genetic similarities of individuals in the sample, the use of empirically derived relationship matrices in calculating EGVs should increase power to localize genetic factors in genome-wide association (GWA) studies, an observation that has driven the use of relationship matrices in artificial selection [[5] and others]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
