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Annotation of gene function in citrus using gene expression information and co-expression networks - PubMed

  • ️Wed Jan 01 2014

Annotation of gene function in citrus using gene expression information and co-expression networks

Darren C J Wong et al. BMC Plant Biol. 2014.

Abstract

Background: The 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.

Results: We 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.

Conclusions: Integration 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.

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Figures

Figure 1
Figure 1

Bar charts illustrating the classification of the citrus microarray experiments. A total of 19 publicly available citrus microarray studies containing 297 datasets encompassing a wide range of experimental conditions and tissues were used in this study and classified according to (A) citrus sub-species and (B) organ. Additional statistics are available in Additional file 1.

Figure 2
Figure 2

Predicted cluster involved in citrus peel isoprenoid and phenylpropanoid metabolism (citrus_cluster14). (A) The predicted Citrus MCL cluster 14 contained 328 nodes densely connected by 1509 edges. Genes involved in secondary metabolism (isoprenoid and phenylpropanoid), cytochrome p450/methyltransferases, lipid metabolism, hormone metabolism and signalling/transcriptional regulation were over-represented in this cluster and are coloured in purple, dark blue, orange, red and green respectively. Nodes coloured in light blue represent genes encoding proteins of miscellaneous functions (See additional files for full details). An illustration of sub-clusters for (B) putative zinc finger/E3 ubiquitin ligase protein (Cit.7748.1.S1_at) and (C) ERF13/ Ethylene response element (ERE) binding protein 1 (Cit.17124.1.S1_at, Cit.17124.1.S1_s_at, Cit.29675.1.S1_s_at, Cit.4691.1.S1_at), showing high node degree (i.e. dense connections) with many other genes within the cluster at a neighbourhood distance of 1. (D) Graph representation of cESI across the 297 tissues and conditions used in this study, with an expression specificity index greater than 1. Coloured boxes highlight the experimental conditions used for fruit peels (flavedo) of grapefruit (red) and sweet oranges (green), and for whole fruits of lemon (yellow).

Figure 3
Figure 3

Predicted cluster involved in GABA shunt (fruit_cluster102) and citric Acid Catabolism (fruit_cluster11). (A) The predicted fruit MCL cluster 102 contains 76 genes connected by 242 edges. Genes involved in protein metabolism, redox, amino acid metabolism, lipid metabolism and transcriptional regulation are represented by blue, purple, red, orange and green respectively. Nodes coloured in light blue represents genes encoding proteins of miscellaneous functions/ unknown (See additional files for full details). (B) The predicted fruit MCL cluster 11 contains 238 genes densely connected by 1330 edges forming a central cluster. Genes involved in protein metabolism, stress, transcriptional regulation, TCA cycle/mitochondrial electron transcript and signalling are represented by orange, red, green, yellow and purple respectively. Nodes coloured in light blue represents genes encoding proteins of miscellaneous functions/ unknown (See additional files for full details). (C) Graph representation of cluster ESI across the 186 fruit related tissues with an expression specificity index greater than 1, in fruit MCL clusters 102 (orange bar) and 11 (yellow bar). Red boxes highlight the expression specificity of fruit-specific cluster 102 and 11 members in fruit vesicles of various sweet orange cultivars.

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