Construction of citrus gene coexpression networks from microarray data using random matrix theory.
Identifieur interne : 000167 ( PubMed/Curation ); précédent : 000166; suivant : 000168Construction of citrus gene coexpression networks from microarray data using random matrix theory.
Auteurs : Dongliang Du [États-Unis] ; Nidhi Rawat [États-Unis] ; Zhanao Deng [États-Unis] ; Fred G. Gmitter [États-Unis]Source :
- Horticulture research ; 2015.
Abstract
After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus.
DOI: 10.1038/hortres.2015.26
PubMed: 26504573
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Gmitter</name><affiliation wicri:level="1"><nlm:affiliation>Citrus Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida , Lake Alfred, FL 33850, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Citrus Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida , Lake Alfred, FL 33850</wicri:regionArea></affiliation></author></analytic><series><title level="j">Horticulture research</title><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. This study provides new targets for further functional analyses in citrus.</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">26504573</PMID><DateCreated><Year>2015</Year><Month>10</Month><Day>27</Day></DateCreated><DateCompleted><Year>2015</Year><Month>10</Month><Day>27</Day></DateCompleted><DateRevised><Year>2015</Year><Month>10</Month><Day>29</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><JournalIssue CitedMedium="Print"><Volume>2</Volume><PubDate><Year>2015</Year></PubDate></JournalIssue><Title>Horticulture research</Title><ISOAbbreviation>Hortic Res</ISOAbbreviation></Journal><ArticleTitle>Construction of citrus gene coexpression networks from microarray data using random matrix theory.</ArticleTitle><Pagination><MedlinePgn>15026</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1038/hortres.2015.26</ELocationID><Abstract><AbstractText>After the sequencing of citrus genomes, gene function annotation is becoming a new challenge. Gene coexpression analysis can be employed for function annotation using publicly available microarray data sets. In this study, 230 sweet orange (Citrus sinensis) microarrays were used to construct seven coexpression networks, including one condition-independent and six condition-dependent (Citrus canker, Huanglongbing, leaves, flavedo, albedo, and flesh) networks. In total, these networks contain 37 633 edges among 6256 nodes (genes), which accounts for 52.11% measurable genes of the citrus microarray. Then, these networks were partitioned into functional modules using the Markov Cluster Algorithm. Significantly enriched Gene Ontology biological process terms and KEGG pathway terms were detected for 343 and 60 modules, respectively. Finally, independent verification of these networks was performed using another expression data of 371 genes. 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