Abstract
BackgroundThe genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. With increasing volumes of transcriptomics data available for these species, Gene Co-expression Network (GCN) analysis is a viable option for predicting gene function at a genome-wide scale. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related biological processes may exhibit similar expression patterns across diverse sets of experimental conditions. While bioinformatics resources such as GCN analysis are widely available for efficient gene function prediction in model plant species including Arabidopsis, soybean and rice, in citrus these tools are not yet developed.ResultsWe have constructed a comprehensive GCN for citrus inferred from 297 publicly available Affymetrix Genechip Citrus Genome microarray datasets, providing gene co-expression relationships at a genome-wide scale (33,000 transcripts). The comprehensive citrus GCN consists of a global GCN (condition-independent) and four condition-dependent GCNs that survey the sweet orange species only, all citrus fruit tissues, all citrus leaf tissues, or stress-exposed plants. All of these GCNs are clustered using genome-wide, gene-centric (guide) and graph clustering algorithms for flexibility of gene function prediction. For each putative cluster, gene ontology (GO) enrichment and gene expression specificity analyses were performed to enhance gene function, expression and regulation pattern prediction. The guide-gene approach was used to infer novel roles of genes involved in disease susceptibility and vitamin C metabolism, and graph-clustering approaches were used to investigate isoprenoid/phenylpropanoid metabolism in citrus peel, and citric acid catabolism via the GABA shunt in citrus fruit.ConclusionsIntegration of citrus gene co-expression networks, functional enrichment analysis and gene expression information provide opportunities to infer gene function in citrus. We present a publicly accessible tool, Network Inference for Citrus Co-Expression (NICCE, http://citrus.adelaide.edu.au/nicce/home.aspx), for the gene co-expression analysis in citrus.
Highlights
The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops
Descriptions pertaining to each array dataset can be found in Additional file 1: Table S1. Classification of these datasets according to sub-species, tissue type and experiment type showed that the majority of samples were from sweet orange (67%) and mandarin orange (14%), mainly from fruit (63%) and leaf (23%) tissues, and often from biotic stress treatments (66%) (Figure 1; Additional file 1: Table S2)
Given the low level of functional annotation for each probeset within the Genechip citrus genome array initially compiled by Affymetrix, the latest gene annotation of the sweet orange genome [2] was retrieved from the Citrus sinensis Annotation Project (CAP) [25]
Summary
The genus Citrus encompasses major cultivated plants such as sweet orange, mandarin, lemon and grapefruit, among the world’s most economically important fruit crops. GCN analysis is based on a “guilt-by-association” principle whereby genes encoding proteins involved in similar and/or related biological processes may exhibit similar expression patterns across diverse sets of experimental conditions While bioinformatics resources such as GCN analysis are widely available for efficient gene function prediction in model plant species including Arabidopsis, soybean and rice, in citrus these tools are not yet developed. Comprehensive transcriptome sequencing has revealed insights into the molecular mechanisms underpinning key traits important for citrus fruit biology, such as vitamin C metabolism, regulation of fruit ripening and identification of disease resistance genes [2] Taken together, these pieces of information form an invaluable resource for understanding molecular plant-pathogen interactions, abiotic stress tolerance and improvement of economically and agronomically important traits in citrus plants. Despite recent efforts in sequencing the sweet orange genome, the majority of genes encoded in the genome remain uncharacterised, while sequencing efforts of other citrus genomes are still in progress [3]
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