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Biomolecules 2018, 8(3), 70; https://doi.org/10.3390/biom8030070

Functional Annotation of Caenorhabditis elegans Genes by Analysis of Gene Co-Expression Networks

1
School of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China
2
School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen 518172, China
3
Department of Molecular and Cellular Medicine, Texas A&M Health Science Center, College Station, TX 77843-1114, USA
*
Author to whom correspondence should be addressed.
Received: 3 July 2018 / Revised: 30 July 2018 / Accepted: 1 August 2018 / Published: 3 August 2018
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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. View Full-Text
Keywords: Caenorhabditis elegans; transcriptome; gene co-expression network; cuticle; hub gene Caenorhabditis elegans; transcriptome; gene co-expression network; cuticle; hub gene
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Liu, W.; Li, L.; He, Y.; Cai, S.; Zhao, W.; Zheng, H.; Zhong, Y.; Wang, S.; Zou, Y.; Xu, Z.; Zhang, Y.; Tu, W. Functional Annotation of Caenorhabditis elegans Genes by Analysis of Gene Co-Expression Networks. Biomolecules 2018, 8, 70.

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