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全基因组鉴定与分析在营养生长阶段对低温胁迫有响应的、在粳稻和籼稻品种间保守的基因

Genome-Wide Identification and Analysis of Genes, Conserved between and Rice Cultivars, that Respond to Low-Temperature Stress at the Vegetative Growth Stage.

作者信息

Kumar Manu, Gho Yun-Shil, Jung Ki-Hong, Kim Seong-Ryong

机构信息

Department of Life Sciences, Sogang UniversitySeoul, South Korea.

Graduate School of Biotechnology and Crop Biotech Institute, Kyung Hee UniversityYongin, South Korea.

出版信息

Front Plant Sci. 2017 Jun 30;8:1120. doi: 10.3389/fpls.2017.01120. eCollection 2017.

DOI:10.3389/fpls.2017.01120
PMID:28713404
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5491850/
Abstract

Cold stress is very detrimental to crop production. However, only a few genes in rice have been identified with known functions related to cold tolerance. To meet this agronomic challenge more effectively, researchers must take global approaches to select useful candidate genes and find the major regulatory factors. We used five Gene expression omnibus series data series of Affymetrix array data, produced with cold stress-treated samples from the NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/), and identified 502 cold-inducible genes common to both and rice cultivars. From them, we confirmed that the expression of two randomly chosen genes was increased by cold stress . In addition, overexpression of enhanced cold tolerance in 'Dongjin,' the tested cultivar. Comparisons between and rice, based on calculations of plant survival rates and chlorophyll fluorescence, confirmed that the rice was more cold-tolerant. Gene Ontology enrichment analysis indicate that the 'L-phenylalanine catabolic process,' within the Biological Process category, was the most highly overrepresented under cold-stress conditions, implying its significance in that response in rice. MapMan analysis classified 'Major Metabolic' processes and 'Regulatory Gene Modules' as two other major determinants of the cold-stress response and suggested several key -regulatory elements. Based on these results, we proposed a model that includes a pathway for cold stress-responsive signaling. Results from our functional analysis of the main signal transduction and transcription regulation factors identified in that pathway will provide insight into novel regulatory metabolism(s), as well as a foundation by which we can develop crop plants with enhanced cold tolerance.

摘要

冷胁迫对作物生产极为不利。然而,在水稻中仅鉴定出少数几个具有已知耐寒相关功能的基因。为了更有效地应对这一农艺挑战,研究人员必须采用全局方法来选择有用的候选基因并找到主要调控因子。我们使用了来自NCBI基因表达综合数据库(http://www.ncbi.nlm.nih.gov/geo/)的经冷胁迫处理样本产生的五个基因表达综合系列数据系列的Affymetrix阵列数据,鉴定出粳稻和籼稻品种共有的502个冷诱导基因。从中,我们证实随机选择的两个基因的表达在冷胁迫下增加。此外,在受试粳稻品种“东津”中过表达该基因增强了耐寒性。基于植物存活率和叶绿素荧光计算对粳稻和籼稻进行比较,证实粳稻更耐寒。基因本体富集分析表明,生物过程类别中的“L-苯丙氨酸分解代谢过程”在冷胁迫条件下代表性最高,这意味着其在水稻的这种反应中具有重要意义。MapMan分析将“主要代谢”过程和“调控基因模块”归类为冷胁迫反应的另外两个主要决定因素,并提出了几个关键调控元件。基于这些结果,我们提出了一个包含冷胁迫响应信号通路的模型。我们对该通路中鉴定出的主要信号转导和转录调控因子的功能分析结果将为新的调控代谢提供见解,并为我们培育耐寒性增强的作物奠定基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/3f49615d82c8/fpls-08-01120-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/7e5c5be78aa0/fpls-08-01120-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/5c06e9f9487b/fpls-08-01120-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/600741e70568/fpls-08-01120-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/d861347a2d02/fpls-08-01120-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/10237ac5a358/fpls-08-01120-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/a6d3a3b8e9e1/fpls-08-01120-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/aef7b306a4c7/fpls-08-01120-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/9e8a0c0e2b10/fpls-08-01120-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/3f49615d82c8/fpls-08-01120-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/7e5c5be78aa0/fpls-08-01120-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/5c06e9f9487b/fpls-08-01120-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/600741e70568/fpls-08-01120-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/d861347a2d02/fpls-08-01120-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/10237ac5a358/fpls-08-01120-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/a6d3a3b8e9e1/fpls-08-01120-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/aef7b306a4c7/fpls-08-01120-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/9e8a0c0e2b10/fpls-08-01120-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92f6/5491850/3f49615d82c8/fpls-08-01120-g009.jpg

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