Identifying highly informative genetic markers for quantification of ancestry proportions in crossbred sheep populations: implications for choosing optimum levels of admixture

摘要

Background Understanding the relationship between genetic admixture and performances is crucial for the success of crossbreeding programs. Use of small sets of ancestry informative markers (AIMs) is a cost effective option to estimate the levels of admixture in situations where pedigree recording is difficult. In this study we select AIMs from Ovine 50KSNP data (SNP – single nucleotide polymorphism) and validate their ability in estimating the contributions of parental breeds to get information about optimum admixture levels for smallholders. Results We estimated admixture levels using ADMIXTURE software based on 74 AIMs selected from Ovine 50KSNP data. Awassi x Ethiopian fat-tailed crossbred sheep populations kept in government farms and farmer villages in different districts were included in the study. Mean Awassi levels estimated based on the selected AIMs were close to the Awassi levels obtained from pedigree information. Estimates from the 74 SNPs were compared to subsets of 65, 55, 45, 35, 25 and 15 SNPs selected based on both top and bottom fixation index (F_ST) rank using Spearman’s rank correlation ( r =?0.862–0.996). A t-test comparison revealed that all SNP subsets had produced similar ( P >?0.05) estimates with the 74 SNPs, except for the bottom 15 SNPs ( P r =?0.969–0.996). Association of admixture levels with lamb growth showed that Awassi level affected ( P Conclusions The results indicate that the Ovine 50KSNP array is a powerful tool to identify small sets of AIMs for admixture studies. The results of this study reveal about 45AIMs to accurately estimate admixture levels. If admixture estimation service with such low cost SNP chip would be available, farmers would have a clear market advantage without the need to rely on incomplete or possibly inaccurate pedigree records. Based on the results presented here, we were able to suggest optimum levels of breed composition for the two farmer environments investigated.