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Construction of citrus gene coexpression networks from microarray data using random matrix theory.

Du D, Rawat N, Deng Z, Gmitter FG - Hortic Res (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Citrus Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida , Lake Alfred, FL 33850, USA.

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.

No MeSH data available.


Related in: MedlinePlus

Distribution of absolute value of correlation coefficients.
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fig7: Distribution of absolute value of correlation coefficients.

Mentions: To confirm the coexpression networks in this study, 500 edges among 371 genes were randomly selected from the “all data” network. The expression of these genes was examined using another gene expression data set (Table S9) in CAP34. The correlation coefficients (r) between them were computed. The distribution of these correlation coefficients was highly skewed, as shown in Figure 7. For 353 edges (70.6%), r values were higher than the PCC thresholds that were used to construct the “all data” networks (0.882). R values of 385 edges (77.0%) were higher than 0.8. These results suggest that the coexpression networks in this study are reliable.


Construction of citrus gene coexpression networks from microarray data using random matrix theory.

Du D, Rawat N, Deng Z, Gmitter FG - Hortic Res (2015)

Distribution of absolute value of correlation coefficients.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4595991&req=5

fig7: Distribution of absolute value of correlation coefficients.
Mentions: To confirm the coexpression networks in this study, 500 edges among 371 genes were randomly selected from the “all data” network. The expression of these genes was examined using another gene expression data set (Table S9) in CAP34. The correlation coefficients (r) between them were computed. The distribution of these correlation coefficients was highly skewed, as shown in Figure 7. For 353 edges (70.6%), r values were higher than the PCC thresholds that were used to construct the “all data” networks (0.882). R values of 385 edges (77.0%) were higher than 0.8. These results suggest that the coexpression networks in this study are reliable.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: Citrus Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida , Lake Alfred, FL 33850, USA.

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.

No MeSH data available.


Related in: MedlinePlus