Hossein Mohammadi; Hossein Moradi Shahrebabak; mohammad shamsollahi
Volume 25, Issue 3 , October 2023, , Pages 241-254
Abstract
Introduction: Identifying of genes with large effects on economically important traits, has been one of the important goal to sheep breeding. Over recent years, advances in DNA-based marker technology have made it possible to identify genomic regions or quantitative trait loci (QTLs) underlying complex ...
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Introduction: Identifying of genes with large effects on economically important traits, has been one of the important goal to sheep breeding. Over recent years, advances in DNA-based marker technology have made it possible to identify genomic regions or quantitative trait loci (QTLs) underlying complex traits, such as fleece traits, in sheep. The present study aimed to conduct a genome wide association studies (GWAS) based on gene-set enrichment analysis for identifying the loci associated with wool traits in native Zandi sheep using the 50K arrays.
Material and Methods: A total of 300 Iranian Zandi sheep used in this study came from the Zandi sheep breeding station. Wool sampling coincided with the maximum wool growth prior to the shearing of wool. In order to facilitate sampling, sheep were restrained in a lateral position and true wool from the left mid-side site was cut from a 5×5 cm2 close to the skin using regular scissors. Each sample was separately packaged and labeled with ear tag number of the sheep. We measured and recorded four wool production traits: staple length (SL), mean fiber diameter (MFD), fiber diameter coefficient of variation (CVFD), and the proportion of fiber that are equal or more than 30 µm (PR), kemp percentage (KEMP%) and outer coat fiber (OCF) were measured. Genomic DNA extraction from sheep blood was performed by the applying a modified salting out protocol and genotyping of the Sheep SNPChip 50 K SNP Bead from Illumina Inc. The gene set analysis consists basically in three different steps: the assignment of SNPs to genes, the assignment of genes to functional categories, and finally the association analysis between each functional category and the phenotype of interest. Genome wide association study was performed with wool traits using GEMMA software. Using the biomaRt2 R package, the SNP were assigned to genes if they were within the genomic sequence of the gene or within a flanking region of 50 kb up- and downstream of the gene and bioinformatics analysis was implemented to identify the biological pathways performed in GO, KEEG, DAVID and PANTHER databases. The GO database designates biological descriptors to genes based on attributes of their encoded products and it is further partitioned into 3 components: biological process, molecular function, and cellular component. The KEGG pathway database contains metabolic and regulatory pathways, representing the actual knowledge on molecular interactions and reaction networks. Finally, a Fisher’s exact test was performed to test for overrepresentation of the significant genes for each gene-set. In the next step, a bioinformatics analysis was implemented to identify the biological pathways performed in GeneCards databases.
Result and Discussion: The result from genomic control showed weak population stratification with for woot traits among Zandi sheep population. We identified different sets of candidate genes related to wool traits including: CEP290, PRKCZ, TMTC3, RHPN2, TNFSF4, NLGN1, SPHKAP, PLCE1, FAT1 and PIK3R4 in Zandi sheep. Some of the found genes, are consistent with some of the previous studies related to reproductive traits. According to pathway analysis, 21 pathways from gene ontology and biological pathways were associated with the wool traits (P˂0.05). Some of the genes were found are consistent with some prior studies and to be involved biological pathways related to hair follicle development, keratinocytes differentiation, synthesizes an enzyme of threonine kinases, development of epidermal and Wnt signaling pathway.
Conclusion: In total, this study supported previous results from GWAS of wool traits, also revealed additional regions in the sheep genome associated with these economically important traits. These findings could potentially be useful for genetic selection in the breeding programs and can be used to understand the genetic mechanism controlling this trait.