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ArticleMolecular biology reports2025

Comparative transcriptome analysis of Isatis indigotica under different precipitation conditions.

Wenlong Zhao, Ziqi Wei, Honggang Chen, Jinbao Zhang, Haijing Duan, Ling Jin

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Article in Molecular biology reports, 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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1 citing paper in PubMed.

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6 authors.

Wenlong ZhaoCollege of Pharmacy, Gansu University of Traditional Chinese Medicine, Lanzhou, China.
Ziqi WeiCollege of Pharmacy, Gansu University of Traditional Chinese Medicine, Lanzhou, China.
Honggang ChenCollege of Pharmacy, Gansu University of Traditional Chinese Medicine, Lanzhou, China.
Jinbao ZhangCollege of Pharmacy, Gansu University of Traditional Chinese Medicine, Lanzhou, China.
Haijing DuanCollege of Pharmacy, Gansu University of Traditional Chinese Medicine, Lanzhou, China.
Ling JinCollege of Pharmacy, Gansu University of Traditional Chinese Medicine, Lanzhou, China. zyxyjl@163.com.

Funding

Central Guidance for Local Science and Technology Development Fund Project 24ZYQA041Enhancing Security and Innovation Capabilities of Traditional Chinese Medicine Project Gansu TCM General Letter [2024] No. 14Gansu Provincial Science and Technology Major Project 23ZDFA013-1Major Project of Institutional-Local Cooperation of the Chinese Academy of Engineering GS2021ZDA06
6 · The paper itself

Abstract

backgroundPlant adaptation to environmental stress is crucial for improving crop resilience and productivity. The growth and yield of Isatis indigotica are significantly affected by water conditions. In this study, high-throughput transcriptome sequencing was performed on leaf samples from Isatis indigotica after different treatments: normal precipitation (CK), 40% rainfall reduction (R1), 80% rainfall reduction (R2), 40% rainfall enhancement (I1) and 80% rainfall enhancement (I2).

resultsUnder 80% rainfall augmentation (I2), the malondialdehyde (MDA) content of Isatis indigotica leaves was the lowest, and the proline (pro) and catalase (CAT) activities were the highest. These findings indicate that normal precipitation conditions do not meet the optimal water requirements for the growth of Isatis indigotica and that appropriate irrigation can be used to improve the accumulation and quality of medicinal substances from this species. Transcriptome analysis of Isatis indigotica leaves compared with those in the control group (CK) revealed 896, 2551, 1294, and 3082 differentially expressed genes in the reduced rainfall reduction groups (R1, R2) and increased rainfall groups (I1, 12), respectively. The number of differentially expressed genes (DEGs) gradually increased with increasing rainfall and decreased after rainfall reduction. The GO enrichment results revealed that the DEGs were significantly enriched in functions such as cellular processes, metabolic processes, stimulus response, cell structure, and catalytic and binding activities. KEGG analysis revealed that metabolic pathways such as glutathione metabolism, phenylpropanoid biosynthesis, and plant hormone signaling were significantly enriched, with the greatest number of enriched genes. This study revealed 32 antioxidant system-related genes, 49 phenylpropanoid biosynthesis-related genes, and 49 plant hormone signaling pathway-related genes among the significantly enriched pathways.

conclusionsThis study provides new insights into the regulation of Isatis indigotica leaves in response to different water contents at the molecular level. The findings also provide a reference for optimizing the field management of Isatis indigotica and improving the quality and yield of medicinal materials.

Indexed as

IsatisRainTranscriptomeGene Expression ProfilingGene Expression Regulation, PlantMalondialdehydePlant LeavesStress, PhysiologicalMalondialdehydeAntioxidant systemIsatis indigoticaPhenylpropanoid biosynthesisPlant hormone signal transductionPrecipitation conditionsTranscriptome analysis

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.