ArticleBMC plant biology2012
Genome-scale identification of cell-wall related genes in Arabidopsis based on co-expression network analysis.
Article in BMC plant biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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34 citing papers in PubMed, 61 citations in OpenAlex.
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- Gene co-expression network analysis identifies trait-related modules in Arabidopsis thaliana.Planta · 2019Article
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- Dynamics of gene expression during development and expansion of vegetative stem internodes of bioenergy sorghum.Biotechnology for biofuels · 2017Article
- Pan- and core- network analysis of co-expression genes in a model plant.Scientific reports · 2016Article
- Construction of co-expression network based on natural expression variation of xylogenesis-related transcripts in Eucalyptus tereticornis.Molecular biology reports · 2016Article
- Co-expression network analysis reveals transcription factors associated to cell wall biosynthesis in sugarcane.Plant molecular biology · 2016Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIdentification of the novel genes relevant to plant cell-wall (PCW) synthesis represents a highly important and challenging problem. Although substantial efforts have been invested into studying this problem, the vast majority of the PCW related genes remain unknown.
resultsHere we present a computational study focused on identification of the novel PCW genes in Arabidopsis based on the co-expression analyses of transcriptomic data collected under 351 conditions, using a bi-clustering technique. Our analysis identified 217 highly co-expressed gene clusters (modules) under some experimental conditions, each containing at least one gene annotated as PCW related according to the Purdue Cell Wall Gene Families database. These co-expression modules cover 349 known/annotated PCW genes and 2,438 new candidates. For each candidate gene, we annotated the specific PCW synthesis stages in which it is involved and predicted the detailed function. In addition, for the co-expressed genes in each module, we predicted and analyzed their cis regulatory motifs in the promoters using our motif discovery pipeline, providing strong evidence that the genes in each co-expression module are transcriptionally co-regulated. From the all co-expression modules, we infer that 108 modules are related to four major PCW synthesis components, using three complementary methods.
conclusionsWe believe our approach and data presented here will be useful for further identification and characterization of PCW genes. All the predicted PCW genes, co-expression modules, motifs and their annotations are available at a web-based database: http://csbl.bmb.uga.edu/publications/materials/shanwang/CWRPdb/index.html.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.