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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

Work flow used for networks construction and clustering in the present study.
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fig1: Work flow used for networks construction and clustering in the present study.

Mentions: As shown in Figure 1, 231 Affymetrix citrus microarrays were downloaded from the NCBI GEO. After quality check, 230 high-quality microarrays (Table S1) were chosen for downstream analyses. Based on the hierarchical cluster analysis (Figure S1), these microarrays were first distributed into seven organ groups: flower, stem, leaves, fruit, seed, roots, and epicotyls. In the fruit group, they were further divided into flavedo, albedo, flesh, and vascular core (also called central core) subgroup. The data from albedo and vascular core were first clustered together and then clustered with data from other parts of fruit. This is reasonable considering that albedo and vascular core are composed of a colorless, spongy network of parenchymatous cells. These data sets were combined into one group, and labeled “albedo”, because neither was large enough for RMTGeneNet analysis. Five groups (flower, stem, seed, roots, and epicotyls), which had fewer microarrays than the minimum requirement of RMTGeneNet (Table 1), were not included for condition-dependent coexpression analysis. Within groups, microarrays of the same treatment were clustered together. Two major diseases of citrus40, citrus canker and HLB, constituted 38.3% of the experiments (citrus canker: 30, HLB: 58), or 81.5% of the experiments if controls were not included. Other treatments were not included for network construction because of insufficient numbers of microarrays. For citrus canker, all microarrays are included in the leaves group. However, HLB data covered five groups (stem, leaves, fruit, seed, and roots). Only 36 microarrays in the fruit group were used for constructing “HLB” coexpression network. Therefore, these 230 microarrays (called “all data”) were divided into sub-data sets of “citrus canker”, “HLB”, “leaves”, “flavedo”, “albedo”, and “flesh” based on their experimental conditions or organ types. Data from these seven groups were analyzed individually to construct coexpression networks.


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

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

Work flow used for networks construction and clustering in the present study.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig1: Work flow used for networks construction and clustering in the present study.
Mentions: As shown in Figure 1, 231 Affymetrix citrus microarrays were downloaded from the NCBI GEO. After quality check, 230 high-quality microarrays (Table S1) were chosen for downstream analyses. Based on the hierarchical cluster analysis (Figure S1), these microarrays were first distributed into seven organ groups: flower, stem, leaves, fruit, seed, roots, and epicotyls. In the fruit group, they were further divided into flavedo, albedo, flesh, and vascular core (also called central core) subgroup. The data from albedo and vascular core were first clustered together and then clustered with data from other parts of fruit. This is reasonable considering that albedo and vascular core are composed of a colorless, spongy network of parenchymatous cells. These data sets were combined into one group, and labeled “albedo”, because neither was large enough for RMTGeneNet analysis. Five groups (flower, stem, seed, roots, and epicotyls), which had fewer microarrays than the minimum requirement of RMTGeneNet (Table 1), were not included for condition-dependent coexpression analysis. Within groups, microarrays of the same treatment were clustered together. Two major diseases of citrus40, citrus canker and HLB, constituted 38.3% of the experiments (citrus canker: 30, HLB: 58), or 81.5% of the experiments if controls were not included. Other treatments were not included for network construction because of insufficient numbers of microarrays. For citrus canker, all microarrays are included in the leaves group. However, HLB data covered five groups (stem, leaves, fruit, seed, and roots). Only 36 microarrays in the fruit group were used for constructing “HLB” coexpression network. Therefore, these 230 microarrays (called “all data”) were divided into sub-data sets of “citrus canker”, “HLB”, “leaves”, “flavedo”, “albedo”, and “flesh” based on their experimental conditions or organ types. Data from these seven groups were analyzed individually to construct coexpression networks.

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