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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
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The Arabidopsis gene co-expression network.

David J Burks1, Soham Sengupta1, Ronika De1

  • 1Department of Biological Sciences and BioDiscovery Institute, College of Science University of North Texas Denton Texas USA.

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Summary
This summary is machine-generated.

We constructed a comprehensive gene co-expression network for Arabidopsis thaliana using all available RNA-Seq data. This network aids in understanding gene function and identifying novel genes involved in biological processes.

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Area of Science:

  • Plant genomics and functional genomics.
  • Computational biology and bioinformatics.

Background:

  • Functional genomics aims to identify interacting genes responsible for biological functions.
  • High-throughput gene expression technologies enable systems-level analysis of gene pathways and networks.

Purpose of the Study:

  • To construct a novel, comprehensive gene co-expression network for *Arabidopsis thaliana* using extensive RNA-Seq data.
  • To develop a resource for deciphering gene functions and identifying novel genes through network analysis.

Main Methods:

  • Leveraged publicly available RNA-Seq datasets from the NCBI SRA database for *Arabidopsis thaliana* (>20,000 datasets).
  • Constructed a gene co-expression network and partitioned it into gene modules.
  • Performed gene ontology and pathway enrichment analyses on gene modules.
  • Mapped differentially expressed genes onto the co-expression network.

Main Results:

  • Developed the first *A. thaliana* co-expression network using the entire mRNA-Seq dataset available.
  • Identified gene modules enriched for specific functional terms and pathways.
  • Demonstrated the network's capability to uncover novel, transcriptionally active genes missed by standard methods.

Conclusions:

  • The developed *A. thaliana* co-expression network is a valuable resource for researchers.
  • The network facilitates interrogation of gene function, identification of interactomes, and understanding of transcriptional changes under various conditions.