Genomic prediction for growth using a low-density SNP panel in dromedary camels

Abstract For thousands of years, camels have produced meat, milk, and fiber in harsh desert conditions. a sustainable development to provide protein resources from areas, it is necessary pay attention genetic improvement camel breeding. By using genotyping-by-sequencing (GBS) method we over 14,500 genome wide markers conduct genome- association study (GWAS) for investigating the birth weight, daily gain, body weight 96 dromedaries Iranian central desert. A total 99 SNPs were associated with (p-value < 0.002). Genomic breeding values (GEBVs) estimated BGLR package (i) all 14,522 (ii) by GWAS. Twenty-eight 0.001). Annotation genomic region (s) within ± 100 kb facilitated prediction 36 candidate genes. The accuracy GEBVs was more than 0.65 based on SNPs, but regression coefficients 0.39, 0.20, 0.23, respectively. Because low sample size, predicted 0.62, 0.82, 0.57 weight. This report first GWAS GBS dromedary identifies growth traits that could help plan program improvement. Further researches larger size collaboration farmers profound understanding will permit verification identified this project. preliminary results show selection be appropriate way camels, which challenging due long generation interval, seasonal reproduction, lack records pedigrees.