ArticlePhysiologia plantarum
Gene Co-Expression Networks Highlight Key Nodes Associated With Ammonium Nitrate in Sugarcane.
Article in Physiologia plantarum. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Gene Co-Expression Networks Highlight Key Nodes Associated With Ammonium Nitrate in Sugarcane.Physiologia plantarumArticle
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5 authors.
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Abstract
This study aimed to investigate molecular mechanisms underlying nitrogen use efficiency (NUE) in sugarcane by analyzing transcriptome profiles of two genotypes (responsive, RB975375; non-responsive, RB937570) under contrasting nitrogen conditions, and along the leaf development gradient. Using RNA-seq data from 48 leaf segment samples, the analyses integrated gene co-expression network approaches to uncover genotype-specific regulatory modules and metabolic pathways linked to NUE. The responsive genotype prioritized carbon metabolism and defense under high nitrogen, while the non-responsive genotype activated photosynthesis and stress responses. Co-expression analysis revealed 44 nitrogen-responsive and 20 genotype-correlated modules. Module 20, enriched in MYB/MYB-related transcription factors, emerged as a central regulator of nitrogen response. Key metabolic markers (RUBISCO, PEPCASE) correlated with specific modules, and novel candidate genes (e.g., NewTr2475430.gen) showed genotype-specific expression. Generated resources include (1) RNA-seq datasets (NCBI BioProject PRJNA1176579); (2) a de novo transcriptome assembly (3.8 million transcripts clustered into 2.48 million transcript groups); (3) co-expression networks (1109 nodes, 199 modules); (4) annotated DEGs (2723) and metabolic correlations (e.g., RUBISCO, chlorophyll); (5) genotype-specific expression profiles and candidate genes (e.g., MYB transcription factors, uncharacterized transcripts). This resource provides actionable targets (e.g., MYB TFs, uncharacterized transcripts) for improving NUE in sugarcane breeding. The network modules and metabolic correlations offer a systems-level framework to study complex nitrogen-responsive mechanisms in polyploid C4 crops. Publicly available datasets enable comparative studies on nutrient use efficiency in polyploid crops, advancing sustainable agriculture.
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