Comparative co-expression analysis in plant biology.
ABSTRACT The analysis of gene expression data generated by high-throughput microarray transcript profiling experiments has shown that transcriptionally coordinated genes are often functionally related. Based on large-scale expression compendia grouping multiple experiments, this guilt-by-association principle has been applied to study modular gene programmes, identify cis-regulatory elements or predict functions for unknown genes in different model plants. Recently, several studies have demonstrated how, through the integration of gene homology and expression information, correlated gene expression patterns can be compared between species. The incorporation of detailed functional annotations as well as experimental data describing protein-protein interactions, phenotypes or tissue specific expression, provides an invaluable source of information to identify conserved gene modules and translate biological knowledge from model organisms to crops. In this review, we describe the different steps required to systematically compare expression data across species. Apart from the technical challenges to compute and display expression networks from multiple species, some future applications of plant comparative transcriptomics are highlighted.
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ABSTRACT: As energy producers, mitochondria play a pivotal role in multiple cellular processes. Although several lines of evidence suggest that differential expression of mitochondrial respiratory complexes (MRCs) has a significant impact on mitochondrial function, the role of integrated MRCs in the whole coexpression network has yet to be revealed. In this study, we construct coexpression networks based on microarray datasets from different tissues and chemical treatments to explore the role of integrated MRCs in the coexpression network and the effects of different chemicals on the mitochondrial network. By grouping MRCs as one seed target, the hypergeometric distribution allowed us to identify genes that are significantly coexpress with whole MRCs. Coexpression among 46 MRC genes (approximately 78% of MRC genes tested) was significant in the normal tissue transcriptome dataset. These MRC genes are coexpressed with genes involved in the categories "muscle system process," "metabolic process," and "neurodegenerative disease pathways," whereas, in the chemically treated tissues, coexpression of these genes mostly disappeared. These results indicate that chemical stimuli alter the normal coexpression network of MRC genes. Taken together, the datasets obtained from the different coexpression networks are informative about mitochondrial biogenesis and should contribute to understanding the side effects of drugs on mitochondrial function.International Journal of Plant Genomics 01/2014; 2014:452891.
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ABSTRACT: The analysis of gene expression data has shown that transcriptionally coordinated (co-expressed) genes are often functionally related, enabling scientists to use expression data in gene function prediction. This Focused Review discusses our original paper (Large-scale co-expression approach to dissect secondary cell wall formation across plant species, Frontiers in Plant Science 2:23). In this paper we applied cross-species analysis to co-expression networks of genes involved in cellulose biosynthesis. We showed that the co-expression networks from different species are highly similar, indicating that whole biological pathways are conserved across species. This finding has two important implications. First, the analysis can transfer gene function annotation from well-studied plants, such as Arabidopsis, to other, uncharacterized plant species. As the analysis finds genes that have similar sequence and similar expression pattern across different organisms, functionally equivalent genes can be identified. Second, since co-expression analyses are often noisy, a comparative analysis should have higher performance, as parts of co-expression networks that are conserved are more likely to be functionally relevant. In this Focused Review, we outline the comparative analysis done in the original paper and comment on the recent advances and approaches that allow comparative analyses of co-function networks. We hypothesize that in comparison to simple co-expression analysis, comparative analysis would yield more accurate gene function predictions. Finally, by combining comparative analysis with genomic information of green plants, we propose a possible composition of cellulose biosynthesis machinery during earlier stages of plant evolution.Frontiers in Plant Science 08/2014; 5:394. · 3.64 Impact Factor
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ABSTRACT: Species respond to environmental stress through a combination of genetic adaptation and phenotypic plasticity, both of which may be important for survival in the face of climatic change.By characterizing the molecular basis of plastic responses and comparing patterns among species, it is possible to identify how such traits evolve. Here, we used de novo transcriptome assembly and RNAseq to explore how patterns of gene expression differ in response to temperature, moisture, and light regime treatments in lodgepole pine (Pinus contorta) and interior spruce (a natural hybrid population of Picea glauca and Picea engelmannii).We found wide evidence for an effect of treatment on expression within each species, with 6413 and 11 658 differentially expressed genes identified in spruce and pine, respectively. Comparing patterns of expression among these species, we found that 74% of all orthologs with differential expression had a pattern that was conserved in both species, despite 140 million yr of evolution. We also found that the specific treatments driving expression patterns differed between genes with conserved versus diverged patterns of expression.We conclude that natural selection has probably played a role in shaping plastic responses to environment in these species.New Phytologist 04/2014; · 6.37 Impact Factor