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Updated: May 4, 2026
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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
Published on: June 17, 2012
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An expression quantitative trait loci-guided co-expression analysis for constructing regulatory network using a rice
Jia Wang1, Huihui Yu, Xiaoyu Weng
1National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, PR China.
Journal of Experimental Botany
|January 15, 2014
Summary
This study introduces eQTL-guided co-expression analysis to map gene regulatory networks in rice. The method identifies gene regulators and potential candidate genes for traits like flowering and yield.
Area of Science:
- Genomics
- Systems Biology
- Plant Science
Background:
- Understanding gene regulatory networks is crucial for deciphering biological processes.
- Current methods require robust strategies for whole-genome regulatory architecture mapping.
Purpose of the Study:
- To develop and demonstrate an eQTL-guided co-expression analysis for constructing gene regulatory networks.
- To identify putative regulators and candidate genes for complex traits in rice.
Main Methods:
- Performed expression quantitative trait loci (eQTL) analysis on 210 rice recombinant inbred lines.
- Utilized an ultrahigh-density single-nucleotide polymorphism bin map and whole-genome arrays.
- Integrated eQTL data with function-related co-expression analysis.
Main Results:
- Detected 13,647 eQTLs for 10,725 expression traits, including cis- and trans-eQTLs.
- Identified 138 trans-eQTL hotspots regulating multiple gene expressions.
- Successfully identified regulators for flowering-related genes and candidate genes for yield traits.
Conclusions:
- eQTL-guided co-expression analysis is a powerful strategy for constructing gene regulatory networks.
- This approach aids in identifying key regulators and candidate genes for important agronomic traits.
- The method offers a promising framework for understanding complex genetic regulation in organisms.
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