1- University of Tehran
Abstract: (304 Views)
Extended abstract
Introduction and Objective: In recent years, wide access to molecular polymorphism data has increased attention to identifying patterns within the genome that indicate positive selections occurring continuously in populations. The basic view about positive selection is the phenomenon of Genetic Hitchhiking. When a beneficial allele is the target of positive selection during different times, it creates signs at the genome level and these signs can be identified and tracked by different methods. The meta-analysis of different methods of selection signature at the genome level can lead to a much more accurate identification of these signature, because each of the different methods of identifying selection signature follow different criteria for identifying marks in the genome of organisms. In fact, the purpose of performing different methods of identification of selection signature is to improve the discovery and identification by using the combination of information and increase the accuracy and precision of the results.
Materials and methods: The number of samples in this study included 111 Thoroughbred and Turkoman horses (44 and 67 respectively). Blood samples were obtained from the veins of the vedic and subcaudal veins of horses. In this research, single nucleotide polymorphism data (SNP chips, 60k) were used. Genotyping of the samples was done using 60 K arrays from Illumina company at the University of Kentucky. To ensure the quality of the genotyped genomic data, quality control analyzes were performed with a series of filters including MAF, SNP-CR, Animal-CR, HWE test. One of the important points in identifying signature of selection is to consider subpopulations in each population, for this reason, the principal components in this section was obtained based on the kinship matrix. Principal components analysis was done in R software. In this research, Fst, iHS (EHH), Rsb methods were used to identify the selection signature, and finally meta-analysis was performed. The regions under genome selection and the genomic positions obtained from whole genome linkage studies were further investigated to find the genes present in these regions. The genes reported in these regions in horses and related regions in cattle were identified using the ENSEMBL database and based on the assembly of the latest horse genome version available from the NCBI and BioMart databases. The identification code related to the identified genes was done in DAVID software to check the biological pathways related to the selected regions.
Results: Primary quality control was performed on 111 animals from 2 populations (67 Turkoman and 44 Thoroughbred). 3 Turkoman animals were excluded from further analysis due to the missing genotype rate of more than 9%, and finally 108 samples remained. A total of 59,349 SNP markers, 52,036 markers remained after quality control. A total of 118 SNPs were excluded due to the minimum allelic frequency of less than 1%, 704 SNPs out of Hardy-Weinberg equilibrium, 6493 SNPs with a missing genotype rate greater than 5%. The results of PCA analysis show that the samples examined in this study were placed in two completely separate groups. Finally, 5 regions on the genome were selected for further investigation. 5 regions with theta value higher than 0.28 between Turkmen and Thoroughbred horse breeds are located on chromosomes 4, 5, 10, 13, and 15, respectively. The highest number of selected markers were located on chromosome 5, and the lowest number of identified markers were located on chromosomes 13 and 15. According to the results obtained from the iHS analysis, the number of 8 and 23 snps, , in Thoroughbred and Turkmen breeds had the highest iHS value respectively, and the number of 3, 2, 2, 1 snps were respectively on chromosomes 28, 21, 1 and The highest iHS value is for the BIEC2_548092 snp located on chromosome 21 of this breed. The results of meta-analysis showed that these regions are located on chromosomes 10, 12, 14, 15, 16, 17, 32. Rsb analysis was performed between two populations of Thoroughbred and Turkoman horses, and the results showed that selection markers are located on chromosomes 12, 16, 17, 31, 32. After examining the genes in the obtained regions, the most important genes were involved in glycosylation, cellular response to stress, metabolic process of cellular macromolecules, repair of broken peptides.
Conclusion: The present research, taking into account the various methods of identifying selection marks in Turkmen and Thoroughbred horses and combining the results of each of the methods, implements a new approach to infer the positive points of selection marks in the horse genome. From the results of this research, it can be concluded that the combination of methods to identify the signs of selection increases the strength and accuracy of the results. Also, the genes identified in this research are involved in important pathways such as glycosylation, cellular response to stress, metabolic process of peptides and organization of protein subunits, cellular macromolecules catabolic process and extracellular transport.
Introduction and Objective: In recent years, wide access to molecular polymorphism data has increased attention to identifying patterns within the genome that indicate positive selections occurring continuously in populations. The basic view about positive selection is the phenomenon of Genetic Hitchhiking. When a beneficial allele is the target of positive selection during different times, it creates signs at the genome level and these signs can be identified and tracked by different methods. The meta-analysis of different methods of selection signature at the genome level can lead to a much more accurate identification of these signature, because each of the different methods of identifying selection signature follow different criteria for identifying marks in the genome of organisms. In fact, the purpose of performing different methods of identification of selection signature is to improve the discovery and identification by using the combination of information and increase the accuracy and precision of the results.
Materials and methods: The number of samples in this study included 111 Thoroughbred and Turkoman horses (44 and 67 respectively). Blood samples were obtained from the veins of the vedic and subcaudal veins of horses. In this research, single nucleotide polymorphism data (SNP chips, 60k) were used. Genotyping of the samples was done using 60 K arrays from Illumina company at the University of Kentucky. To ensure the quality of the genotyped genomic data, quality control analyzes were performed with a series of filters including MAF, SNP-CR, Animal-CR, HWE test. One of the important points in identifying signature of selection is to consider subpopulations in each population, for this reason, the principal components in this section was obtained based on the kinship matrix. Principal components analysis was done in R software. In this research, Fst, iHS (EHH), Rsb methods were used to identify the selection signature, and finally meta-analysis was performed. The regions under genome selection and the genomic positions obtained from whole genome linkage studies were further investigated to find the genes present in these regions. The genes reported in these regions in horses and related regions in cattle were identified using the ENSEMBL database and based on the assembly of the latest horse genome version available from the NCBI and BioMart databases. The identification code related to the identified genes was done in DAVID software to check the biological pathways related to the selected regions.
Results: Primary quality control was performed on 111 animals from 2 populations (67 Turkoman and 44 Thoroughbred). 3 Turkoman animals were excluded from further analysis due to the missing genotype rate of more than 9%, and finally 108 samples remained. A total of 59,349 SNP markers, 52,036 markers remained after quality control. A total of 118 SNPs were excluded due to the minimum allelic frequency of less than 1%, 704 SNPs out of Hardy-Weinberg equilibrium, 6493 SNPs with a missing genotype rate greater than 5%. The results of PCA analysis show that the samples examined in this study were placed in two completely separate groups. Finally, 5 regions on the genome were selected for further investigation. 5 regions with theta value higher than 0.28 between Turkmen and Thoroughbred horse breeds are located on chromosomes 4, 5, 10, 13, and 15, respectively. The highest number of selected markers were located on chromosome 5, and the lowest number of identified markers were located on chromosomes 13 and 15. According to the results obtained from the iHS analysis, the number of 8 and 23 snps, , in Thoroughbred and Turkmen breeds had the highest iHS value respectively, and the number of 3, 2, 2, 1 snps were respectively on chromosomes 28, 21, 1 and The highest iHS value is for the BIEC2_548092 snp located on chromosome 21 of this breed. The results of meta-analysis showed that these regions are located on chromosomes 10, 12, 14, 15, 16, 17, 32. Rsb analysis was performed between two populations of Thoroughbred and Turkoman horses, and the results showed that selection markers are located on chromosomes 12, 16, 17, 31, 32. After examining the genes in the obtained regions, the most important genes were involved in glycosylation, cellular response to stress, metabolic process of cellular macromolecules, repair of broken peptides.
Conclusion: The present research, taking into account the various methods of identifying selection marks in Turkmen and Thoroughbred horses and combining the results of each of the methods, implements a new approach to infer the positive points of selection marks in the horse genome. From the results of this research, it can be concluded that the combination of methods to identify the signs of selection increases the strength and accuracy of the results. Also, the genes identified in this research are involved in important pathways such as glycosylation, cellular response to stress, metabolic process of peptides and organization of protein subunits, cellular macromolecules catabolic process and extracellular transport.
Type of Study: Research |
Subject:
ژنتیک و اصلاح نژاد طیور
Received: 2024/06/22 | Accepted: 2024/09/8
Received: 2024/06/22 | Accepted: 2024/09/8
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