| چکیده انگلیسی مقاله |
Introduction and Objective: Identification of selection targeted genomic regions is one of the main aims of biological research. Domestication and selection has significantly changed the behavioral and phenotypic traits in modern domestic animals. The selection of animals by humans left detectable signatures on the genome of modern cattle. The identification of these signals can help us to improve the genetic characteristics of economically important traits in cattle. Over the last decade, interest in detection of genes or genomic regions that are targeted by selection has been growing. Identifying signatures of selection can provide valuable insights about the genes or genomic regions that are or have been under selection pressure, which in turn leads to a better understanding of genotype-phenotype relationships. The aim of this study was to identify effective genes and genomic region on positive signature of selection in Beetal goats using selection signature and gene ontology methods.
Material and Methods: In this study, data from 631 Beetal goat genotyped using Caprine 50 K BeadChip were used to identify genomic regions under selection associated with important traits in Beetal goat. Quality control measures were performed in Plink by setting animal call rate of 0.90, SNP call rate of 0.95 and SNPs with minor allele frequencies (MAF) lower than 0.05 or that do not conform to the Hardy–Weinberg expectation (P value ≤ 0.000001) and unknown position. After quality control of the initial data using plink software (v1.90; http://pngu.mgh.harvard.edu/purcell/plink), 36,861 SNP markers in 594 animals of cattle were finally entered for further analysis. To identify the signatures of selection, statistical method iHS was used under REHH software packages. Candidate genes were identified by SNPs located at 1% upper range of iHS using Plink v1.9 software and the gene list of Illumina in R. Additionally, the latest published version of Animal genome database was used for defining QTLs associated with economic important traits in identified locations. In addition, the DAVID database (http://david.abcc.ncifcrf.gov) was used to determine biological routes. At this stage, it is assumed that genes that belong to a functional class can be considered as a group of genes that have some specific and common characteristics. GeneCards (http://www.genecards.org) and UniProtKB (http://www.uniprot.org) databases were also used to interpret the function of the obtained genes Also, Gene ontology analysis for identified genes was performed using DAVID online database.
Results: After quality control filters; 36,861 SNPs were left while 9761 SNPs were removed due to Hardy Weinberg Equilibrium, 1342 SNPs were removed due unknown position, 3963 removed due to minor allele threshold and 1342 removed due to missing genotypes and 37 individuals were removed after quality control measures. Using iHS approach, we identified ten genomic regions on chromosomes 4, 6, 7, 11 (two regions per chromosome), 13, 14, 15, 17, and 18 chromosome. Some of the genes located in identified regions under selection were associated with the body size (SPP1, SCN9A and TNPO2), fat metabolism (SDCBP), skeletal development (IBSP and MEPE), and energy metabolism (UCP2, TRPC3 and FBP1). Some of the genes under selection were found are consistent with some previous studies|. Results of gene ontology analysis identified two biological pathways namely skeletal system development and calcium channel complex with two important KEGG pathway including glucagon signaling pathway and AMPK signaling pathway which play an important role in the glucose metabolism and homeostasis and skeletal system development.
Conclusion: By the way, various genes that were founded within these regions can be considered as candidates under selection based on function. Most of the genes under selection were found are consistent with some previous studies and to be involved in number of processes such as growth, body weight, metabolic pathways and domestication-related changes include system development and immune systems. Also, survey on extracted QTLs was shown that these QTLs involved in some economical important traits in goat such as feed conversion ratio, subcutaneous fat, Marbling score, meat tenderness, body weight, average daily gain, and conformation traits, length of productive life and carcass traits and composition carcass traits. However, it will be necessary to carry out more association and functional studies to demonstrate the implication of these genes. However, it will be necessary to carry out more association and functional studies to demonstrate the implication of these genes and survey on QTLs related to selected regions. However, will be necessary to carry out more association and functional studies to demonstrate the implication of genes obtained from association analyses. Using these findings can accelerate the genetic progress in the breeding programs and can be used to understand the genetic mechanism controlling this trait.
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