Integrative physiological evaluation and whole-transcriptome analysis reveal non-coding RNA–associated drought responses in oat (Avena sativa L.)

Abstract Background Oat ( Avena sativa L.) is an important cereal crop used for both food and forage production, but its productivity is severely constrained by drought stress. Although non-coding RNAs (ncRNAs) are increasingly recognized as key regulators of plant responses to abiotic stress, the coordinated regulatory roles of long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs) in oat drought adaptation remain poorly understood. Results In this study, four oat cultivars with contrasting drought tolerance were evaluated at the seedling stage under controlled drought conditions using 21 morphological, physiological, and photosynthetic traits. Principal component analysis (PCA) was performed to calculate a comprehensive drought resistance index ( F value), allowing an integrated assessment of drought tolerance among the cultivars. Zhongyan No.1 (Z1) exhibited the highest drought tolerance, followed by Baiyan No.7 (B7), Denmark 440 (D4), and Longyan No.3 (L3). Based on these results, leaves from Z1 plants exposed to drought for 6 days were selected for whole-transcriptome sequencing. Transcriptome analysis identified 10,446 differentially expressed mRNAs, 116 differentially expressed lncRNAs, and 13 differentially expressed miRNAs. Functional enrichment analyses revealed that these drought-responsive transcripts were significantly enriched in pathways related to photosynthetic carbon fixation, starch and sucrose metabolism, glycolysis/gluconeogenesis, and glyoxylate and dicarboxylate metabolism, suggesting extensive transcriptional reprogramming of carbon metabolism in response to drought stress. Furthermore, an lncRNA–miRNA–mRNA competing endogenous RNA (ceRNA) network was constructed, identifying a drought-responsive regulatory module centered on miR156 and comprising two lncRNAs, one miRNA, and eleven target mRNAs. Conclusions By integrating physiological evaluation with whole-transcriptome profiling, this study provided a comprehensive overview of ncRNA-mediated drought responses in oat seedlings by integrating physiological evaluation with whole-transcriptome profiling. The predicted regulatory networks, particularly the miR156-centered ceRNA module, provided valuable candidate regulatory modules for future functional validation and molecular breeding aimed at improving drought tolerance in oat.

Authors

Institutions

Publication Details

Journal
BMC Plant Biology
Published
2026-09-01
DOI
https://doi.org/10.1186/s12870-026-09808-9
Primary Topic
Plant Molecular Biology Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Integrative physiological evaluation and whole-transcriptome analysis reveal non-coding RNA–associated drought responses in oat (Avena sativa L.)

Guangxin Cui, Hongshan Yang, Yujie Li, Fang Wu et al.
BMC Plant Biology
Plant Molecular Biology Research
article

Integrative physiological evaluation and whole-transcriptome analysis reveal non-coding RNA–associated drought responses in oat (Avena sativa L.)

Guangxin Cui, Hongshan Yang, Yujie Li, Fang Wu, Huirong Duan, Lei Xu, Xinqiang Zhu, Jing Zhang, Ruixin Zhang
article en

Abstract

Abstract Background Oat ( Avena sativa L.) is an important cereal crop used for both food and forage production, but its productivity is severely constrained by drought stress. Although non-coding RNAs (ncRNAs) are increasingly recognized as key regulators of plant responses to abiotic stress, the coordinated regulatory roles of long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and microRNAs (miRNAs) in oat drought adaptation remain poorly understood. Results In this study, four oat cultivars with contrasting drought tolerance were evaluated at the seedling stage under controlled drought conditions using 21 morphological, physiological, and photosynthetic traits. Principal component analysis (PCA) was performed to calculate a comprehensive drought resistance index ( F value), allowing an integrated assessment of drought tolerance among the cultivars. Zhongyan No.1 (Z1) exhibited the highest drought tolerance, followed by Baiyan No.7 (B7), Denmark 440 (D4), and Longyan No.3 (L3). Based on these results, leaves from Z1 plants exposed to drought for 6 days were selected for whole-transcriptome sequencing. Transcriptome analysis identified 10,446 differentially expressed mRNAs, 116 differentially expressed lncRNAs, and 13 differentially expressed miRNAs. Functional enrichment analyses revealed that these drought-responsive transcripts were significantly enriched in pathways related to photosynthetic carbon fixation, starch and sucrose metabolism, glycolysis/gluconeogenesis, and glyoxylate and dicarboxylate metabolism, suggesting extensive transcriptional reprogramming of carbon metabolism in response to drought stress. Furthermore, an lncRNA–miRNA–mRNA competing endogenous RNA (ceRNA) network was constructed, identifying a drought-responsive regulatory module centered on miR156 and comprising two lncRNAs, one miRNA, and eleven target mRNAs. Conclusions By integrating physiological evaluation with whole-transcriptome profiling, this study provided a comprehensive overview of ncRNA-mediated drought responses in oat seedlings by integrating physiological evaluation with whole-transcriptome profiling. The predicted regulatory networks, particularly the miR156-centered ceRNA module, provided valuable candidate regulatory modules for future functional validation and molecular breeding aimed at improving drought tolerance in oat.

BMC Plant Biology
Lanzhou Institute of Husbandry and Pharmaceutical Sciences (CN), Chinese Academy of Agricultural Sciences (CN)
Zero hunger
Openalex Percentile: Top 12%
Plant Molecular Biology Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.