An application of Me SH enrichment analysis in livestock

Abstract

SummaryAn integral part of functional genomics studies is to assess the enrichment of specific biological terms in lists of genes found to be playing an important role in biological phenomena. Contrasting the observed frequency of annotated terms with those of the background is at the core of overrepresentation analysis (ORA). Gene Ontology (GO) is a means to consistently classify and annotate gene products and has become a mainstay in ORA. Alternatively, Medical Subject Headings (MeSH) offers a comprehensive life science vocabulary including additional categories that are not covered by GO. Although MeSH is applied predominantly in human and model organism research, its full potential in livestock genetics is yet to be explored. In this study, MeSH ORA was evaluated to discern biological properties of identified genes and contrast them with the results obtained from GO enrichment analysis. Three published datasets were employed for this purpose, representing a gene expression study in dairy cattle, the use of SNPs for genome‐wide prediction in swine and the identification of genomic regions targeted by selection in horses. We found that several overrepresented MeSH annotations linked to these gene sets share similar concepts with those of GO terms. Moreover, MeSH yielded unique annotations, which are not directly provided by GO terms, suggesting that MeSH has the potential to refine and enrich the representation of biological knowledge. We demonstrated that MeSH can be regarded as another choice of annotation to draw biological inferences from genes identified via experimental analyses. When used in combination with GO terms, our results indicate that MeSH can enhance our functional interpretations for specific biological conditions or the genetic basis of complex traits in livestock species.

Genetic dissection of bull fertility in US Jersey dairy cattle

“…), and the MeSH enrichment analysis was carried out using the R package meshr (Morota et al . ; Tsuyuzaki et al . ).…”

Transcriptomic Analysis of the Mouse Mammary Gland Reveals New Insights for the Role of Serotonin in Lactation

“…For each comparison of interest, genes that showed a FDR ≤ 0.10 and had ENSEMBL annotations were tested against the background set of all expressed genes with ENSEMBL annotations. The GO and MeSH enrichment analyses were performed using goseq package [ 25 ] and meshr package [ 26 , 27 ], respectively, which are available in the R environment [ 28 ]. Functional categories with a FDR ≤ 0.01 were considered significant.…”

Unravelling the genomic architecture of bull fertility in Holstein cattle

“…The GO gene set enrichment analysis was performed using the R package goseq (using method hypergeometric) [38] while the MeSH enrichment analysis was carried out using the R package meshr [39, 40]. Additionally, the semantic similarities among GO functional terms were calculated based on the GO hierarchy using the R package GOSemSim [41].…”