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

查看全文 作　　者：Dongliang [1]Du;Nidhi [2]Rawat;Zhanao [2]Deng;Fred G.Gmitter [1]Jr.

机构地区：[1]Citrus Research and Education Center,Institute of Food and Agricultural Sciences,University of Florida,Lake Alfred,FL 33850,USA;[2]Gulf Coast Research and Education Center,Institute of Food and Agricultural Sciences,University of Florida,Wimauma,FL 33598,USA

出　　处：《Horticulture Research》索引2015年第2卷第1期,共8页

基　　金：This work was supported by a grant from the Citrus Research and Development Foundation(CRDF-724). 摘　　要：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 37633 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. 关键词：measurable ORANGE partitioned

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

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