Estimation of Variance Components and Genome Partitioning According to Minor Allele Frequency for Quantitative Traits in Sheep

Accurate estimation of genetic variance components is essential for the correct prediction of breeding values. The discovery of SNP markers and advances in molecular genetics and the discovery of new methods for sequencing the entire genome of living organisms and the development of bioinformatics methods and computer science, etc. have provided a great deal of molecular data and created a branch of genetics called genomics. This study aimed to estimate the genomic variance components of Border sheep using SNP data.

For this study, the SNP panel, which was genotyped with a 50k marker chip from Illumina, was used. Data were collected at Falkiner Farm in Australia. The studied traits were birth and weaning weights, diameter, and length of wool yarn. To study the relationship between allelic frequency and the amount of justified genetic variance justified, SNPs were classified into five different groups of rare allelic frequency (MAF), with approximately equal numbers in each group. The analyses were performed with the approach of limited genomic maximum likelihood and the method of analysis of complex genome traits with GCTA software.

Genomic heritability estimated by SNPs with a rare allelic frequency of more than one percent for birth weights, weaning, diameter, and length of wool were 0.58, 0.47, 0.59, and 0.2, respectively. The contribution of different groups of SNPs with rare allelic frequencies in justifying genetic variance for different traits was different and in general a significant part of genetic variance was justified by SNPs with

Although the number of SNPs was different in different groups, the amount of genetic variance justified by different MAF groups was different. According to the results, a very large, ideal sample size and better coverage of low-frequency variants are needed to obtain a stronger and more reliable inference.