Comparative Transcriptome and Weighted Gene Co-Expression Network Analyses Reveal a Shared Core Response and Quantitatively Divergent Regulatory Modules Between Drought-Tolerant and Drought-Sensitive Foxtail Millet.
- 1Institute of Crop Research, Academy of Agricultural Sciences of Xinjiang Uyghur Autonomous Region, Urumqi 830002, China.
- 2State Key Laboratory for Crop Stress Resistance and High-Efficiency Production, College of Life Sciences, Northwest Agriculture and Forestry University, Yangling, Xianyang 712100, China.
Abstract
Drought limits the stability of foxtail millet production and the efficient use of germplasm resources, yet whether drought-tolerant and drought-sensitive accessions engage fundamentally distinct pathways or a shared, quantitatively reprogrammed network remains unclear. We generated 36 leaf transcriptomes from three drought-sensitive (DSEN) and three drought-tolerant (DTOL) accessions under well-watered (WW) and drought-stress (DS) conditions, retaining 25,099 genes for downstream analyses. Principal component analysis confirmed water treatment as the primary driver of global expression variation. DS-versus-WW comparisons identified 10,635 and 6215 drought-responsive DEGs in the DSEN and DTOL groups, respectively, with 5195 shared and a genome-wide response correlation of 0.791. Crucially, accession-level tests revealed no significant DEGs between groups under WW, only 22 under DS, and none for the group × drought-response interaction, underscoring the absence of qualitative pathway shifts. Functional enrichment analyses jointly indicated suppression of photosynthesis and translation, accompanied by reprogramming of carbohydrate metabolism, membrane lipid remodeling, phenylpropanoid and secondary metabolism, protein homeostasis, and stress signaling. WGCNA partitioned 10,000 highly variable genes into 16 modules. The blue module, which showed the strongest drought response in DSEN, was enriched for cell-wall and carbohydrate metabolism, membrane lipid processes, and stress-protection pathways, whereas the brown module, which responded most robustly in DTOL, was enriched for calcium signaling, protein phosphorylation/dephosphorylation, transcriptional regulation, proline biosynthesis, and dehydration protection. The yellow and cyan modules exhibited the largest between-group effect sizes under drought but failed multiple-testing correction, remaining candidate networks. Collectively, our results support a model of shared core response with divergent regulatory intensity, where sensitive accessions undergo broader transcriptional perturbation, while tolerant ones deploy more concentrated and coordinated modules. This study provides modular targets for drought-tolerance breeding and highlights the necessity of accession-level replication and conservative statistical inference in comparative transcriptomics.
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BibTeX
@article{wang2026comparative,
title = {{Comparative Transcriptome and Weighted Gene Co-Expression Network Analyses Reveal a Shared Core Response and Quantitatively Divergent Regulatory Modules Between Drought-Tolerant and Drought-Sensitive Foxtail Millet.}},
author = {Hong-Jin Wang and Yun Zhao and Zaituniguli Kuerban and Hui Wang and Xiangwei Hu and Guojun Feng},
journal = {Biology},
year = {2026},
month = oct,
doi = {10.3390/biology15191757},
url = {https://europepmc.org/article/MED/42883430},
note = {CC BY},
}
RIS
TY - JOUR
TI - Comparative Transcriptome and Weighted Gene Co-Expression Network Analyses Reveal a Shared Core Response and Quantitatively Divergent Regulatory Modules Between Drought-Tolerant and Drought-Sensitive Foxtail Millet.
AU - Hong-Jin Wang
AU - Yun Zhao
AU - Zaituniguli Kuerban
AU - Hui Wang
AU - Xiangwei Hu
AU - Guojun Feng
PY - 2026
DA - 2026/10/02
JO - Biology
DO - 10.3390/biology15191757
UR - https://europepmc.org/article/MED/42883430
AB - Drought limits the stability of foxtail millet production and the efficient use of germplasm resources, yet whether drought-tolerant and drought-sensitive accessions engage fundamentally distinct pathways or a shared, quantitatively reprogrammed network remains unclear. We generated 36 leaf transcriptomes from three drought-sensitive (DSEN) and three drought-tolerant (DTOL) accessions under well-watered (WW) and drought-stress (DS) conditions, retaining 25,099 genes for downstream analyses. Principal component analysis confirmed water treatment as the primary driver of global expression variation. DS-versus-WW comparisons identified 10,635 and 6215 drought-responsive DEGs in the DSEN and DTOL groups, respectively, with 5195 shared and a genome-wide response correlation of 0.791. Crucially, accession-level tests revealed no significant DEGs between groups under WW, only 22 under DS, and none for the group × drought-response interaction, underscoring the absence of qualitative pathway shifts. Functional enrichment analyses jointly indicated suppression of photosynthesis and translation, accompanied by reprogramming of carbohydrate metabolism, membrane lipid remodeling, phenylpropanoid and secondary metabolism, protein homeostasis, and stress signaling. WGCNA partitioned 10,000 highly variable genes into 16 modules. The blue module, which showed the strongest drought response in DSEN, was enriched for cell-wall and carbohydrate metabolism, membrane lipid processes, and stress-protection pathways, whereas the brown module, which responded most robustly in DTOL, was enriched for calcium signaling, protein phosphorylation/dephosphorylation, transcriptional regulation, proline biosynthesis, and dehydration protection. The yellow and cyan modules exhibited the largest between-group effect sizes under drought but failed multiple-testing correction, remaining candidate networks. Collectively, our results support a model of shared core response with divergent regulatory intensity, where sensitive accessions undergo broader transcriptional perturbation, while tolerant ones deploy more concentrated and coordinated modules. This study provides modular targets for drought-tolerance breeding and highlights the necessity of accession-level replication and conservative statistical inference in comparative transcriptomics.
SN - 2079-7737
ER -