Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học quốc tế đề tài: Different genomic relationship matrices for single-step analysis using phenotypic, pedigree and genomic information | Forni et al. Genetics Selection Evolution 2011 43 1 http content 43 1 1 GSE Ge n et i cs Selection Evolution RESEARCH Open Access Different genomic relationship matrices for single-step analysis using phenotypic pedigree and genomic information Selma Forni1 Ignacio Aguilar2 3 Ignacy Misztal3 Abstract Background The incorporation of genomic coefficients into the numerator relationship matrix allows estimation of breeding values using all phenotypic pedigree and genomic information simultaneously. In such a single-step procedure genomic and pedigree-based relationships have to be compatible. As there are many options to create genomic relationships there is a question of which is optimal and what the effects of deviations from optimality are. Methods Data of litter size total number born per litter for 338 346 sows were analyzed. Illumina PorcineSNP60 BeadChip genotypes were available for 1 989. Analyses were carried out with the complete data set and with a subset of genotyped animals and three generations pedigree 5 090 animals . A single-trait animal model was used to estimate variance components and breeding values. Genomic relationship matrices were constructed using allele frequencies equal to G05 equal to the average minor allele frequency GMF or equal to observed frequencies GOF . A genomic matrix considering random ascertainment of allele frequencies was also used GOF . A normalized matrix GN was obtained to have average diagonal coefficients equal to 1. The genomic matrices were combined with the numerator relationship matrix creating H matrices. Results In G05 and GMF both diagonal and off-diagonal elements were on average greater than the pedigreebased coefficients. In GOF and GOF the average diagonal elements were smaller than pedigree-based coefficients. The mean of off-diagonal coefficients was zero in GOF and GOF . Choices of G with average diagonal coefficients different from 1 led to greater estimates of additive variance in .
