Genome-wide analysis for detection of loci under positive selection in Zandi sheep breed

Document Type : Research Paper

Authors

1 Ph.D. Candidate, Department of Animal Science, Faculty of Agricultural Sciences, University of Tabriz, Iran

2 Professor, Department of Animal Science, Faculty of Agricultural Sciences, University of Tabriz, Iran

3 Assistant Professor, Department of Animal Sciences, University College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran

4 Department of Animal Science, Faculty of Agricultural Sciences, University of Tabriz.

5 Assistant Professor, Department of Animal Sciences, Faculty of Agriculture and Natural Resources, University of Arak, Iran

Abstract

Identification of selection targeted genomic regions is one of the main aims of biological research.The objective of this study was a genome-wide scan to identify the genomic regions that have been under artificial and natural selection in Zandi sheep breed. For this purpose, 96 animal of Zandi breed have been genotyped using the Illumina ovine SNP50 BeadChip. The intergrated hapl-type score (iHS) test was used to detect the selection sweep, due to linkage disequilibrium, associated with these signatures. The results revealed eleven genomic regions on 1 (two areas), 3, 6, 7,8, 9, 10, 17, 22 and 26 chromosomes. Bioinformatics analysis demonstrated that some of these genomic regions overlapped with reported genes that directly and indirectly influenced traits for adaptation to hot arid environments (DNAJB4, HSPA4L, MSRB3), immune response (IL23A, STAT6, LY96), body size and development (STAC3, LAP3), development of the skeletal system (SPP1, MEPE, IBSP) and energy and digestive metabolism (ATP5B, GLS2, CS). Finally, study of the reported QTL in these regions of the sheep genome showed that they overlapped with QTL of economically important traits such as carcass yield, growth and wool traits. However, it will be necessary to carry out more association and functional studies to demonstrate the implication of these genes.

Keywords


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