Abstract
Caenorhabditis elegans (C. elegans) is a well-characterized metazoan, whose transcriptome has been profiled in different tissues, development stages, or other conditions. Large-scale transcriptomes can be reused for gene function annotation through systematic analysis of gene co-expression relationships. We collected 2101 microarray data from National Center for Biotechnology Information Gene Expression Omnibus (NCBI GEO), and identified 48 modules of co-expressed genes that correspond to tissues, development stages, and other experimental conditions. These modules provide an overview of the transcriptional organizations that may work under different conditions. By analyzing higher-order module networks, we found that nucleus and plasma membrane modules are more connected than other intracellular modules. Module-based gene function annotation may help to extend the candidate cuticle gene list. A comparison with other published data validates the credibility of our result. Our findings provide a new source for future gene discovery in C. elegans.
Highlights
High-throughput transcriptomics technology has been extensively applied to investigate the mechanisms of gene regulation
Skyblue has the lowest module stability, while white has the highest module stability. These results indicate that the relationships between module genes were robust to the exclusion of 50% of the data
Previous C. elegans transcriptome studies are limited by their sample size and specific conditions
Summary
High-throughput transcriptomics technology has been extensively applied to investigate the mechanisms of gene regulation. A promising strategy to find the gene functions of unknown genes is the gene co-expression method, which infers gene functions by similar gene expression patterns. Weighted gene co-expression network analysis (WGCNA) groups genes that have similar expression patterns across biological samples. In a gene co-expression network, a module is a subset of genes, whose expression patterns are similar to each other while different from genes in other modules. These genes are members from the same pathway or biological process. Those modules were compared with previous publications to confirm the validity of our results
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