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ORIGINAL RESEARCH article
Front. Plant Sci.
Sec. Plant Abiotic Stress
Volume 16 - 2025 | doi: 10.3389/fpls.2025.1562718
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Thioredoxins(TRX) are small redox-active proteins that play a crucial role in plant growth, development, and stress resistance. Nucleoredoxin (NRX), a member of the thioredoxin superfamily, plays a crucial role in maintaining redox balance in plant cells, particularly under drought stress. However, a systematic identification and analysis of the NRX gene family in rice (Oryza sativa) under drought conditions had been lacking. In this study, 10 OsNRX genes were identified across three rice varieties-Minghui63, Nipponbare, and 9311. Based on conserved protein domains, these genes were classified into three subfamilies, with consistent gene structures and conserved motifs within each subfamily. Cis-acting element analysis revealed that OsNRX family genes generally contain elements associated with ABA, JA, SA, and drought induction.Expression analysis during different developmental stages in Nipponbare showed that NRX1a is highly expressed in roots and hulls, whereas NRX1b and NRX2 are predominantly expressed in the endosperm, with expression levels varying among tissues and developmental stages. Drought stress experiments demonstrated that OsNRX gene expression is significantly influenced by drought, with distinct patterns observed across varieties with varying drought tolerance. Furthermore, based on the expression patterns of OsNRX genes in glumes, embryos, and endosperm, it is hypothesized that this gene family may also be involved in the regulation of grain size in rice.
Keywords: rice, Nucleoredoxin gene family, Drought stress, Genome-wide identification, Expression pattern
Received: 18 Jan 2025; Accepted: 28 Mar 2025.
Copyright: © 2025 Liu, Zheng, Yang, Li and Yin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Lanzhi Li, Hunan Engineering & Technology Research Center for Agricultural Big Data Analysis & Decision-making, College of Plant Protection, Hunan Agricultural University, Changsha, China
Hexing Yin, Huazhi Biotechnology Co. Ltd, Changsha, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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