Physiological and Transcriptome Analyses Reveal Short-Term Responses and Formation of Memory Under Drought Stress in Rice.

Front Genet

Key Laboratory for Economic Plants and Biotechnology, Germplasm Bank of Wild Species, Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Yunnan Key Laboratory for Wild Plant Resources, Kunming, China.

Published: February 2019

In some plants, exposure to stress can induce a memory response, which appears to play an important role in adaptation to recurrent stress environments. However, whether rice exhibits drought stress memory and the molecular mechanisms that might underlie this process have remained unclear. Here, we ensured that rice drought memory was established after cycles of mild drought and re-watering treatment, and studied gene expression by whole-transcriptome strand-specific RNA sequencing (ssRNA-seq). We detected 6,885 transcripts and 238 lncRNAs involved in the drought memory response, grouped into 16 distinct patterns. Notably, the identified genes of dosage memory generally did not respond to the initial drought treatment. Our results demonstrate that stress memory can be developed in rice under appropriate water deficient stress, and lncRNA, DNA methylation and endogenous phytohormones (especially abscisic acid) participate in rice short-term drought memory, possibly acting as memory factors to activate drought-related memory transcripts in pathways such as photosynthesis and proline biosynthesis, to respond to the subsequent stresses.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6375884PMC
http://dx.doi.org/10.3389/fgene.2019.00055DOI Listing

Publication Analysis

Top Keywords

drought memory
12
memory
10
drought stress
8
memory response
8
stress memory
8
drought
7
stress
6
rice
5
physiological transcriptome
4
transcriptome analyses
4

Similar Publications

Premise: Tree structure and function are constrained by and acclimate to climatic conditions. Drought limits plant growth and carbon acquisition and can result in "legacy" effects that last beyond the period of water stress. Leaf and twig-level legacy effects of past water abundance, such as that experienced by trees that established under wetter conditions are unknown.

View Article and Find Full Text PDF

Drought is a complex phenomenon with multifactorial impacts, requiring a multiscale approach for effective understanding and management. This study presents an innovative operational framework, "Drought Scan," designed to deepen drought understanding, improve monitoring, and streamline climate services to support effective adaptation and mitigation against drought impacts. At the core of the framework is a methodology that integrates two standardized indices: the standardized precipitation and streamflow indices (SPI and SQI, respectively).

View Article and Find Full Text PDF

The global impacts of climate change have become increasingly pronounced in recent years due to the rise in greenhouse gas emissions from fossil fuels. This trend threatens water resources, ecological balance, and could lead to desertification and drought. To address these challenges, reducing fossil fuel consumption and embracing renewable energy sources is crucial.

View Article and Find Full Text PDF

The frequency and severity of drought events are predicted to increase due to anthropogenic climate change, with cascading effects across forested ecosystems. Management activities such as forest thinning and prescribed burning, which are often intended to mitigate fire hazard and restore ecosystem processes, may also help promote tree resistance to drought. However, it is unclear whether these treatments remain effective during the most severe drought conditions or whether their impacts differ across environmental gradients.

View Article and Find Full Text PDF

Plant stress reduction research has advanced significantly with the use of Artificial Intelligence (AI) techniques, such as machine learning and deep learning. This is a significant step toward sustainable agriculture. Innovative insights into the physiological responses of plants mostly crops to drought stress have been revealed through the use of complex algorithms like gradient boosting, support vector machines (SVM), recurrent neural network (RNN), and long short-term memory (LSTM), combined with a thorough examination of the TYRKC and RBR-E3 domains in stress-associated signaling proteins across a range of crop species.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!