مجله بیوتکنولوژی کشاورزی (Feb 2018)

Estimation of linkage disequilibrium and whole-genome scan for detection of loci under selection associated with body weight in Zandi sheep breed

  • Hossin Mohammadi,
  • Abbas Raffat,
  • Hossin Moradi,
  • Jalil Shoja,
  • Mohammad Hossien Moradi

DOI
https://doi.org/10.22103/jab.2018.2020
Journal volume & issue
Vol. 9, no. 4
pp. 151 – 172

Abstract

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Body weight is the most economically important trait in sheep industry. In genome-wide association study and genomic selection, determining of extent and level of linkage disequilibrium (LD) is critical in sample size and marker density. Moreover, selection for increasing of frequency in new mutations that are advantageous only in a subset of populations leaves some signatures in the genome. Locations of selection signatures are often correlated with genes and QTLs affecting economically important traits. Therefore, the objectives of this research were to study LD pattern and identify the genomic regions that have been under artificial and natural selection in Zandi sheep breeds with different body weight. For this purpose, the blood samples were collected form 73 Zandi sheep and 54241 markers were genotyped by using Illumina Ovine SNP50K BeadChip array based on latest assembly (Oar_4.0) sheep genome. After quality control, 40879 SNPs belonging to 71 animals were used in the final analysis. LD was calculated between all pairs were calculated with r2 by PLINK software. To detect the selection sweep, due to linkage disequilibrium, associated with these signatures we carried out the cross-population Extended Haplotype Homozygosity (XP-EHH) test. In this study, the extent of LD in this study was 40 kb with r2=0.2. The results revealed ten genomic regions on 1, 2, 3, 5, 6, 9, 12, 13, 21 and 22 chromosomes. Bioinformatics analysis demonstrated that some of these genomic regions overlapped with reported genes included in the growth traits, fat metabolism, development of the skeletal system, energy metabolism and meat quality traits such as FBP1, FAM184B, PKD2, FGF19, SPP1, MEPE CAPN2 genes.

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