筇竹钾离子通道QtSKOR2基因的克隆及表达分析
Cloning and Expression Analysis of QtSKOR2 Gene of Qiongzhuea tumidinoda Potassium Ion Channel
王玥琪 1赵小艳 1芮蕊1
作者信息
- 1. 西南林业大学/云南省林下资源保护与利用重点实验室 昆明 650224
- 折叠
摘要
为了研究SKOR家族在筇竹(Qiongzhuea tumidinoda)钾离子运输中发挥的作用,利用克隆技术从筇竹的幼苗中克隆出SKOR基因并命名为QtSKOR2,随后对其理化性质和表达模式进行分析.结果显示,QtSKOR2 基因全长为2 334 bp,开放阅读框为2 139 bp,编码712 个氨基酸.同时,QtSKOR2 蛋白有6个跨膜结构域,且与芦苇(Phragmites australis)的同源相似性最高,为 90.46%.聚类分析表明,QtSKOR2 蛋白与短花稻(Oryza brachyantha)的亲缘关系最近.QtSKOR2 基因在筇竹所有组织中均有表达,且表达量依次为根>笋>叶>茎.在50 mmol/L KCl胁迫处理下,QtSKOR2 基因在筇竹根部表达量最高,且表达量随着时间的延长而增加.而在250 mmol/L NaCl胁迫处理下,QtSKOR2 基因在筇竹叶片中表达量最高,且表达量随着时间的延长而增加.本研究结果揭示了盐胁迫下QtSKOR2 基因在筇竹钾离子运输中可能发挥着重要作用.
Abstract
To investigate the function of the SKOR family in potassium ion transport in Qiongzhuea tumidinoda,a gene named QtSKOR2 is cloned from the young seedlings of Q.tumidinoda using cloning technology,and its physicochemical properties and expression pattern are analyzed.The result shows that the full length of the QtSKOR2 gene is 2 334 bp,with an open reading frame of 2 139 bp,which encodes 712 amino acids.Moreover,the QtSKOR2 protein has six transmembrane domains and exhibited the highest homology similarity with that of Phragmites australis at 90.46%.Cluster analysis suggests that the QtSKOR2 protein is most closely related to that of Oryza brachyantha.Additionally,the QtSKOR2 gene is expressed in all tissues of Q.tumidinoda,with the highest expression level in roots,followed by shoots,leaves,and culms.The expression level of the QtSKOR2 gene is highest in the roots of Q.tumidinoda and increases over time under 50 mmol/L KCl stress treatment.Additionally,the expression of the QtSKOR2 gene leaves is highest in Q.tumidinoda and increases over time under 250 mmol/L NaCl stress treatment.The results of this study reveal that the QtSKOR2 gene might play a significant role in Q.tumidinoda potassium ion transport under salt stress.
关键词
筇竹/钾离子通道/QtSKOR2基因/基因克隆/基因表达/盐胁迫Key words
Qiongzhuea tumidinoda/potassium channel/QtSKOR2 gene/gene clone/gene expression/salt stress引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据