ArticlePlant physiology2022
Rice co-expression network analysis identifies gene modules associated with agronomic traits.
Article in Plant physiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Protein-protein interactions reveal key genes in rice response to salt stress: a meta-analysis.Biologia futura · 2026Pooled it
- A yield-reducing introgression linked to sd1 in rice.The plant genome · 2026Article
- Knockout of OsRbohD (the NADPH Oxidase Gene) Enhances Saline-Alkaline Stress Tolerance and Grain Yield in Rice by Reducing ROS Accumulation.Rice (New York, N.Y.) · 2026Article
- Predicting rice drought-responsive genes via distance-based prototypical graph neural network with path aggregation mechanism.Plant methods · 2026Article
- An Introduction to Network Analysis in Plant Biology.Plant direct · 2025Article
- Unlocking gene regulatory networks for crop resilience and sustainable agriculture.Nature biotechnology · 2025Review
- A transcription factor ensemble orchestrates bundle sheath expression in rice.Nature communications · 2025Article
- Distinct and redundant roles of the Arabidopsis OCTOPUS gene family in plant growth beyond phloem development.Journal of experimental botany · 2025Article
- A large-scale gene co-expression network analysis reveals Glutamate Dehydrogenase 2 (GhGDH2_D03) as a hub regulator of salt and salt-alkali tolerance in cotton.Plant molecular biology · 2025Article
- Candidate Gene for Kernel-Related Traits in Maize Revealed by a Combination of GWAS and Meta-QTL Analyses.Plants (Basel, Switzerland) · 2025Article
- Identification and validation of hub genes associated with biotic and abiotic stresses by modular gene co-expression analysis in Oryza sativa L.Scientific reports · 2025Article
- CRISPR/Cas knockout of the NADPH oxidase gene OsRbohB reduces ROS overaccumulation and enhances heat stress tolerance in rice.Plant biotechnology journal · 2025Article
- Identification of Drought Stress-Responsive Genes in Rice by Random Walk with Multi-Restart Probability on MultiPlex Biological Networks.International journal of molecular sciences · 2024Article
- Single-cell network analysis reveals gene expression programs for Arabidopsis root development and metabolism.Plant communications · 2024Article
- Transcriptome-wide expression landscape and starch synthesis pathway co-expression network in sorghum.The plant genome · 2024Article
- PRMD: an integrated database for plant RNA modifications.Nucleic acids research · 2024Article
- Recent advances in exploring transcriptional regulatory landscape of crops.Frontiers in plant science · 2024Review
- Co-expression network of heat-response transcripts: A glimpse into how splicing factors impact rice basal thermotolerance.Frontiers in molecular biosciences · 2023Article
- Review
- Large-scale analyses of angiospermFrontiers in plant science · 2022Article
Corrections and comments
- Erratum issued
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifying trait-associated genes is critical for rice (Oryza sativa) improvement, which usually relies on map-based cloning, quantitative trait locus analysis, or genome-wide association studies. Here we show that trait-associated genes tend to form modules within rice gene co-expression networks, a feature that can be exploited to discover additional trait-associated genes using reverse genetics. We constructed a rice gene co-expression network based on the graphical Gaussian model using 8,456 RNA-seq transcriptomes, which assembled into 1,286 gene co-expression modules functioning in diverse pathways. A number of the modules were enriched with genes associated with agronomic traits, such as grain size, grain number, tiller number, grain quality, leaf angle, stem strength, and anthocyanin content, and these modules are considered to be trait-associated gene modules. These trait-associated gene modules can be used to dissect the genetic basis of rice agronomic traits and to facilitate the identification of trait genes. As an example, we identified a candidate gene, OCTOPUS-LIKE 1 (OsOPL1), a homolog of the Arabidopsis (Arabidopsis thaliana) OCTOPUS gene, from a grain size module and verified it as a regulator of grain size via functional studies. Thus, our network represents a valuable resource for studying trait-associated genes in rice.
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