An application of MeSH enrichment analysis in livestock

G. Morota, F. Peñagaricano, J. L. Petersen, D. C. Ciobanu, K. Tsuyuzaki, I. Nikaido

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Summary An 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.

Original languageEnglish (US)
Pages (from-to)381-387
Number of pages7
JournalAnimal genetics
Volume46
Issue number4
DOIs
StatePublished - Aug 1 2015

Fingerprint

Medical Subject Headings
Livestock
Gene Ontology
livestock
genes
Genes
Biological Phenomena
Biological Science Disciplines
Vocabulary
Genomics
genomics
Horses
Single Nucleotide Polymorphism
Swine
Genome
Gene Expression
dairy cattle

Keywords

  • Gene
  • Gene Ontology
  • ORA
  • annotation
  • enrichment analysis

ASJC Scopus subject areas

  • Animal Science and Zoology
  • Genetics

Cite this

An application of MeSH enrichment analysis in livestock. / Morota, G.; Peñagaricano, F.; Petersen, J. L.; Ciobanu, D. C.; Tsuyuzaki, K.; Nikaido, I.

In: Animal genetics, Vol. 46, No. 4, 01.08.2015, p. 381-387.

Research output: Contribution to journalArticle

Morota, G. ; Peñagaricano, F. ; Petersen, J. L. ; Ciobanu, D. C. ; Tsuyuzaki, K. ; Nikaido, I. / An application of MeSH enrichment analysis in livestock. In: Animal genetics. 2015 ; Vol. 46, No. 4. pp. 381-387.
@article{7d4ef25e8ed8499e9f82daba6b0ecdc7,
title = "An application of MeSH enrichment analysis in livestock",
abstract = "Summary An 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.",
keywords = "Gene, Gene Ontology, ORA, annotation, enrichment analysis",
author = "G. Morota and F. Pe{\~n}agaricano and Petersen, {J. L.} and Ciobanu, {D. C.} and K. Tsuyuzaki and I. Nikaido",
year = "2015",
month = "8",
day = "1",
doi = "10.1111/age.12307",
language = "English (US)",
volume = "46",
pages = "381--387",
journal = "Animal Genetics",
issn = "0268-9146",
publisher = "Wiley-Blackwell",
number = "4",

}

TY - JOUR

T1 - An application of MeSH enrichment analysis in livestock

AU - Morota, G.

AU - Peñagaricano, F.

AU - Petersen, J. L.

AU - Ciobanu, D. C.

AU - Tsuyuzaki, K.

AU - Nikaido, I.

PY - 2015/8/1

Y1 - 2015/8/1

N2 - Summary An 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.

AB - Summary An 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.

KW - Gene

KW - Gene Ontology

KW - ORA

KW - annotation

KW - enrichment analysis

UR - http://www.scopus.com/inward/record.url?scp=84937969206&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84937969206&partnerID=8YFLogxK

U2 - 10.1111/age.12307

DO - 10.1111/age.12307

M3 - Article

C2 - 26036323

AN - SCOPUS:84937969206

VL - 46

SP - 381

EP - 387

JO - Animal Genetics

JF - Animal Genetics

SN - 0268-9146

IS - 4

ER -