Genome-wide association study based on pathway analysis related to teat numbers in sheep

Abstract
Introduction:
The number of teat is an important trait in relation to the maternal ability of high litter size sheeps, it is important to know the genetic function and controlling positions of this trait in the genomes of different species. High litter size domestic animals are potentially dependent on colostrum-derived immunoglobulins due to placental structure in the early hours of life. Therefore, the number of teat plays a critical role when there are more offspring born at birth than the number of teats. In some cases, particularly the number of the extra teat and even their position is very important. A method to identify new loci and confirm existing QTL is through genome-wide association studies (GWAS). QTL assisted selection and genomic regions affecting the production traits have been considered to increase the efficiency of selection and improve production performance. Genome wide association studies typically focus on genetic markers with the strongest evidence of association. However, single markers often explain only a small component of the genetic variance and hence offer a limited understanding of the trait under study. A solution to tackle the aforementioned problems, and deepen the understanding of the genetic background of complex traits, is to move up the analysis from the SNP to the gene and gene-set levels. In a gene-set analysis, a group of related genes that harbor significant SNP previously identified in GWAS, is tested for over-representation in a specific pathway. The present study aimed to conduct a genome wide association studies (GWAS) based on Gene-set enrichment analysis for identifying the loci associated with teat number trait using the high-density SNPs.
Materials and methods:
Hu sheep, a descendant of Mongolian sheep, is a famous lambing breed in China. In ewes of the Hu sheep, TT (individuals with two normal teats) and MT (individuals with two normal teats and one or two supernumerary teats) account for 76–62% and 38–24% respectively. For MT ewes, the supernumerary teats are smaller than the normal teats, but some can produce milk. In the current study, we analyzed the complex genetic mechanism of differences in teat number using single-locus GWAS in a total of 160 Hu sheep. The gene set analysis basically consists of 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 birth weight and biometric 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 25 kb up- and downstream of the gene. For the assignment of the genes to functional categories, the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway databases were used. 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. The gene enrichment analysis was performed with the goseq R package. In the next step, a bioinformatics analysis was implemented to identify the biological pathways performed in BioMart, Panther, DAVID and GeneCards databases.
Results and discussion:
Gene set enrichment analysis has proven to be a great complement of genome-wide association analysis (Gambra et al., 2013; Abdalla et al., 2016). Among available gene set databases, GO is probably the most popular, whereas KEGG is a relatively new tool that is gaining ground in livestock genomics (Morota et al., 2015, 2016). We had hypothesized that the use of gene set information could improve prediction. However, neither of the gene set SNP classes outperformed the standard whole-genome approach. Gene sets have been primarily developed using data from model organisms, such as mice and flies, so it is possible that some of the genes included in these terms are irrelevant for meat production. A better understanding of the biology underlying meat production specifically, and an advance in the annotation of the ovine genome, can provide new opportunities for predicting production using gene set information.
In this research, 7 SNP markers on chromosomes 3, 5, 7, 8, 12, 14 and 17 located in CDH11, NUMB, FGF2, ESR1, LGR5, INSR and PTGS2 genes were identified. Some of the found genes, are consistent with some of the previous studies related to teat number traits. According to pathway analysis, 11 pathways from gene ontology and biological pathways were associated with teat number (P˂0.05). Among these pathways, Blastocyst development, Mesenchymal cell development, Developmental growth involved in morphogenesis, Muscle cell differentiation and AMPK signaling pathway have important functions in development of mammary gland and activation of the AMPK signaling pathway. Finally, it is worth noting that our gene-set enrichment analysis was conducted using a panel of SNP obtained from a single marker regression GWAS, which relies on a simplified theory of the genomic background of traits, without considering the joint effect of SNP. Hence, other approaches (e.g., GWAS exploring SNP by SNP interactions) might provide a better basis for biological pathway analysis.
Conclusions
In total, this study supported previous results from GWAS of teat number, also revealed additional regions in the sheep genome associated with these economically important trait. Using these findings could potentially be useful for genetic selection in the breeding programs.