ArticleBMC genomic data2025
Transcriptomic analysis of maize leaves under different irrigation treatments in field conditions.
Article in BMC genomic data, 2025. 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Transcriptomic analysis of maize leaves under different irrigation treatments in field conditions.BMC genomic data · 2025Article
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10 authors.
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Abstract
objectivesAs one of the most widely cultivated agricultural crops in the world, maize (Zea mays L.) yield is often affected by water stress. In this study, we designed eight different irrigation levels in a field environment, covering a wide range of gradients, and conducted a comprehensive transcriptomic analysis of maize leaves under these eight treatments. The results revealed the molecular mechanisms by which maize responds to drought, optimal irrigation, and excessive irrigation in field conditions. This not only deepens our understanding of maize's response to water stress but also provides valuable genetic resources and theoretical insights for future genetic improvement. DATA DESCRIPTION: This study designed eight different irrigation levels under field conditions and conducted comprehensive transcriptome sequencing of maize ear leaf tissues. Analysis of the transcriptome data identified differentially expressed genes (DEGs), and principal component analysis (PCA) revealed a clear separation trend among samples under varying water conditions. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses highlighted functional categories associated with water response, cellular metabolism, and growth regulation. These findings provide valuable insights into the molecular mechanisms of maize under drought, optimal irrigation, and over-irrigation conditions, laying a foundation for future genetic improvement efforts.
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