Identification of genomic regions under positive selection that control the type traits in different goat breeds

Introduction: Molecular markers that reveal polymorphisms at the DNA level now play a key role in animal genetics. However, the selection of molecular markers is crucial depending on the purpose, viz. this depends on different molecular biology techniques and their effects. Over the last decade, interest in identifying genes or genomic regions targeted by selection has grown. Identifying selection signatures can provide valuable insights into 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. Type characteristics are important for breed identification and classification and are also positively correlated with body weight. This study aimed to identify effective genes and genomic regions under positive selection signatures in different goat breeds using selection signature methods. For this purpose, F_ST and hapFLK analyses were performed using the genome-wide single nucleotide polymorphisms (SNPs).
Materials and methods: In this research, the information from 728 goats of four different breeds was used to identify genomic regions associated with type traits. To determine the genotype of the samples, Illumina caprine Bead Chip 50K was used. The genomic information of goat breeds was extracted from the Figshare database. Quality control was performed using the Plink software. The markers or individuals were excluded from further study based on the following criteria: unknown chromosomal or physical location, call rate <0.95, missing genotype frequency >0.05, minor allele frequency (MAF) <0.05, and a P-value for Hardy-Weinberg equilibrium test less than 10^-3. After quality control, 36861 SNPs from goat SNP chip 50K from 691 goats remained for further analysis. To identify the signatures of selection, two statistical methods of F_ST and hapFLK were used under the software packages F_ST and hapFLK, respectively. Candidate genes were identified using the Plink v1.9 software and the Illumina gene list in R by SNPs located in the highest  F_ST and hapFLK values. In addition, the latest published version of the animal genome database was used to define QTLs associated with economically important traits at identified loci. The GeneCards (http://www.genecards.org) and UniProtKB (http://www.uniprot.org) databases were also used to interpret the function of the obtained genes.
Results and discussion: The F_ST and hapFLK statistics were used to identify genomic regions subjected to positive selection associated with type traits in four goat breeds. Using the F_ST approach, we identified eight genomic regions on chromosomes 3, 4, 7, 13, 15, 18, 20, and 29. The identified candidate genes associated with type traits in these genomic regions included TGFBR3, CALCR, ACAD8, BCAR1, and ADAMTS6. Some of the genes located in the identified selection regions were directly and indirectly related to cell differentiation and proliferation, skeletal muscle growth and development, body length, calcium channel regulation, muscle fiber homeostasis, protein synthesis, and muscle cell size. Some of these genes in the selected regions were consistent with previous studies. The results of the reported QTLs in the selected regions and the bovine orthologous regions were QTLs located in the identified regions that were related to average daily gain, body weight, trunk width, and metabolic body weight. Furthermore, the results of the hapFLK statistics in this research led to the identification of five genomic regions on chromosomes 1, 5, 6, 13, and 30, and they were in the 99.9^th percentile of all hapFLK values. The identified candidate genes associated with the type trait in these genomic regions included FNDC3B, STAB2, and CCNY. They were found to have different functions in fibroblast proliferation and bone cell differentiation.
Conclusions: Various/different genes that emerged in studied regions can be considered candidates for selection based on their function. By the way, various genes found in these regions can be considered candidates for selection based on their function. Most of the selected genes were found to be consistent with some previous studies and to be involved in production traits. A survey of extracted QTLs also found that these QTLs are involved in some economically important traits in goats, such as average daily gain and body weight in yearlings. However, further association and functional studies are required to demonstrate the importance of the genes obtained from association analyses. Leveraging these findings can accelerate genetic progress in breeding programs and help understand the genetic mechanism that controls these traits.
Material and Methods: In this research, to identify genomic regions under selection associated with type traits were used the information obtained from 728 goats of different breeds including Beetal, Daira Deen Panah, Barbari, Teddi, In order to determine the genotype of the samples, Illumina caprine Bead Chip 50K were used. The genomic information of goat breeds was extracted from the figshare database. Quality control was conducted using the Plink software. The markers or individuals were excluded from the further study based on the following criteria: unknown chromosomal or physical location, call rate <0.95, missing genotype frequency >0.05, minor allele frequency (MAF) < 0.05, and a P-value for Hardy–Weinberg equilibrium test less than 10-3. After quality control, 36,861 SNPs from Goat SNP chip 50K on 691 goats were remained for the future analysis. To identify the signatures of selection, two statistical methods of FST and hapFLK were used under FST and hapFLK software packages, respectively. Candidate genes were identified by SNPs located at 1% upper range of FST and hapFLK 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. GeneCards (http://www.genecards.org) and UniProtKB (http://www.uniprot.org) databases were also used to interpret the function of the obtained genes.
Results and Discussion: We used the FST and hapFLK statistics to identify genomic regions that have been under positive selection associated with type traits in four goat breeds. Using FST approach, we identified eight genomic regions on chromosomes 3, 4, 7, 13, 15, 18, 20, and 29 chromosome. The identified candidate genes associated with type trait in these genomic regions included TGFBR3, CALCR, ACAD8, BCAR1, ADAMTS6. Some of the genes located in identified regions under selection were associated with the cell differentiation and proliferation, skeletal muscle growth and development, body length, calcium channel regulation, muscle fiber homeostasis, protein synthesis and muscle cell size which can be directly and indirectly related to the trait of the type traits. Some of these genes in the selected regions were consistent with previous studies. Result of the reported QTLs in the selected regions and the orthologous regions of cattle were located in the identified regions, QTLs related to average daily gain, body weight, rump width and body metabolic weight. Also, the results of hapFLK statistics in this research led to the identification of five genomic regions on chromosomes 1, 5, 6, 13, and 30, and they were in the 99.9 percentile of all hapFLK values. The identified candidate genes associated with the type trait in these genomic regions included FNDC3B, STAB2 and CCNY. It was determined that they had different functions in proliferation of fibroblasts and differentiation of bone cells. Result of the reported QTLs in the selected regions and orthologous cattle in the identified regions, QTLs related to metabolic body weight were located.
Conclusion: 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 production traits. Also, survey on extracted QTLs was shown that these QTLs involved in some economical important traits in goat such as average daily gain and body weight in yearling. 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.