Transcriptomic analysis of maize leaves under different irrigation treatments in field conditions

Abstract Objectives As 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 comprehensiv...

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Main Authors: Yuan-Xin Li, Ru-Zhi Li, Jing Yang, Zhi-Wei Wang, Xiao-Guang Li, Hou-Zhen Yi, Xin-Ping Guo, Hang Zhou, Kai-Hua Jia, Peng-Fei Chu
Format: Article
Language:English
Published: BMC 2025-03-01
Series:BMC Genomic Data
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Online Access:https://doi.org/10.1186/s12863-025-01302-9
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author Yuan-Xin Li
Ru-Zhi Li
Jing Yang
Zhi-Wei Wang
Xiao-Guang Li
Hou-Zhen Yi
Xin-Ping Guo
Hang Zhou
Kai-Hua Jia
Peng-Fei Chu
author_facet Yuan-Xin Li
Ru-Zhi Li
Jing Yang
Zhi-Wei Wang
Xiao-Guang Li
Hou-Zhen Yi
Xin-Ping Guo
Hang Zhou
Kai-Hua Jia
Peng-Fei Chu
author_sort Yuan-Xin Li
collection DOAJ
description Abstract Objectives As 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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institution Kabale University
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spelling doaj-art-e2041df90d594dc7aaa9785c834e9ae22025-08-20T03:41:50ZengBMCBMC Genomic Data2730-68442025-03-012611410.1186/s12863-025-01302-9Transcriptomic analysis of maize leaves under different irrigation treatments in field conditionsYuan-Xin Li0Ru-Zhi Li1Jing Yang2Zhi-Wei Wang3Xiao-Guang Li4Hou-Zhen Yi5Xin-Ping Guo6Hang Zhou7Kai-Hua Jia8Peng-Fei Chu9College of Agriculture and Biology, Liaocheng UniversityCollege of Agriculture and Biology, Liaocheng UniversityCollege of Agriculture and Biology, Liaocheng UniversityInstitute of Crop Germplasm Resources, Shandong Academy of Agricultural SciencesIrrigation Experiment Station, Weishan Irrigation DistrictIrrigation Experiment Station, Weishan Irrigation DistrictCollege of Agriculture and Biology, Liaocheng UniversityShandong Shennong Zhiyi Intelligent Technology Co., LtdInstitute of Crop Germplasm Resources, Shandong Academy of Agricultural SciencesCollege of Agriculture and Biology, Liaocheng UniversityAbstract Objectives As 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.https://doi.org/10.1186/s12863-025-01302-9Maize (Zea mays L.)Irrigation managementWater stress responseDifferentially expressed genesRNA-seq
spellingShingle Yuan-Xin Li
Ru-Zhi Li
Jing Yang
Zhi-Wei Wang
Xiao-Guang Li
Hou-Zhen Yi
Xin-Ping Guo
Hang Zhou
Kai-Hua Jia
Peng-Fei Chu
Transcriptomic analysis of maize leaves under different irrigation treatments in field conditions
BMC Genomic Data
Maize (Zea mays L.)
Irrigation management
Water stress response
Differentially expressed genes
RNA-seq
title Transcriptomic analysis of maize leaves under different irrigation treatments in field conditions
title_full Transcriptomic analysis of maize leaves under different irrigation treatments in field conditions
title_fullStr Transcriptomic analysis of maize leaves under different irrigation treatments in field conditions
title_full_unstemmed Transcriptomic analysis of maize leaves under different irrigation treatments in field conditions
title_short Transcriptomic analysis of maize leaves under different irrigation treatments in field conditions
title_sort transcriptomic analysis of maize leaves under different irrigation treatments in field conditions
topic Maize (Zea mays L.)
Irrigation management
Water stress response
Differentially expressed genes
RNA-seq
url https://doi.org/10.1186/s12863-025-01302-9
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