Dataset Information

Construction and validation of a gene co-expression network in grapevine (Vitis vinifera. L.).

ABSTRACT: Gene co-expression analysis has been widely used for predicting gene functions because genes within modules of a co-expression network may be involved in similar biological processes and exhibit similar biological functions. To detect gene relationships in the grapevine genome, we constructed a grapevine gene co-expression network (GGCN) by compiling a total of 374 publically available grapevine microarray datasets. The GGCN consisted of 557 modules containing a total of 3834 nodes with 13?479 edges. The functions of the subnetwork modules were inferred by Gene ontology (GO) enrichment analysis. In 127 of the 557 modules containing two or more GO terms, 38 modules exhibited the most significantly enriched GO terms, including 'protein catabolism process', 'photosynthesis', 'cell biosynthesis process', 'biosynthesis of plant cell wall', 'stress response' and other important biological processes. The 'response to heat' GO term was highly represented in module 17, which is composed of many heat shock proteins. To further determine the potential functions of genes in module 17, we performed a Pearson correlation coefficient test, analyzed orthologous relationships with Arabidopsis genes and established gene expression correlations with real-time quantitative reverse transcriptase PCR (qRT-PCR). Our results indicated that many genes in module 17 were upregulated during the heat shock and recovery processes and downregulated in response to low temperature. Furthermore, two putative genes, Vit_07s0185g00040 and Vit_02s0025g04060, were highly expressed in response to heat shock and recovery. This study provides insight into GGCN gene modules and offers important references for gene functions and the discovery of new genes at the module level.

SUBMITTER: Liang YH

PROVIDER: S-EPMC4596334 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Construction and validation of a gene co-expression network in grapevine (Vitis vinifera. L.).

Liang Ying-Hai YH Cai Bin B Chen Fei F Wang Gang G Wang Min M Zhong Yan Y Cheng Zong-Ming Max ZM

Horticulture research 20140813

Gene co-expression analysis has been widely used for predicting gene functions because genes within modules of a co-expression network may be involved in similar biological processes and exhibit similar biological functions. To detect gene relationships in the grapevine genome, we constructed a grapevine gene co-expression network (GGCN) by compiling a total of 374 publically available grapevine microarray datasets. The GGCN consisted of 557 modules containing a total of 3834 nodes with 13 479 e ...[more]

PMID: 26504546

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Dataset Information

Construction and validation of a gene co-expression network in grapevine (Vitis vinifera. L.).

Publications

Construction and validation of a gene co-expression network in grapevine (Vitis vinifera. L.).

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