豆科植物与固氮根瘤菌共生关系的功能基因组学研究。

Q2 Biochemistry, Genetics and Molecular Biology High-Throughput Pub Date : 2018-05-18 DOI:10.3390/ht7020015
Martina Lardi, Gabriella Pessi
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引用次数: 12

摘要

生物固氮使豆科植物在缺氮土壤中具有明显的生长优势,具有相当大的生态和经济效益。作为交换,大气中的氮通常以酰胺或尿素的形式提供给植物,豆科植物为固氮根瘤菌提供营养物质和高度特化的根结构,称为根瘤。为了在全基因组范围内阐明生理适应的分子基础,已经使用了功能基因组学方法,如转录组学、蛋白质组学和代谢组学。本文综述了不同功能基因组学方法在根瘤菌共生中的应用,重点研究了根瘤菌与豆科植物相互作用的分子机制。虽然属于α -变形菌群(α -根瘤菌)的根瘤菌已经得到了很好的研究,但迄今为止很少有研究调查β -变形菌群(β -根瘤菌)的这一过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Functional Genomics Approaches to Studying Symbioses between Legumes and Nitrogen-Fixing Rhizobia.

Biological nitrogen fixation gives legumes a pronounced growth advantage in nitrogen-deprived soils and is of considerable ecological and economic interest. In exchange for reduced atmospheric nitrogen, typically given to the plant in the form of amides or ureides, the legume provides nitrogen-fixing rhizobia with nutrients and highly specialised root structures called nodules. To elucidate the molecular basis underlying physiological adaptations on a genome-wide scale, functional genomics approaches, such as transcriptomics, proteomics, and metabolomics, have been used. This review presents an overview of the different functional genomics approaches that have been performed on rhizobial symbiosis, with a focus on studies investigating the molecular mechanisms used by the bacterial partner to interact with the legume. While rhizobia belonging to the alpha-proteobacterial group (alpha-rhizobia) have been well studied, few studies to date have investigated this process in beta-proteobacteria (beta-rhizobia).

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来源期刊
High-Throughput
High-Throughput Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.60
自引率
0.00%
发文量
0
审稿时长
9 weeks
期刊介绍: High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: -Microarrays -DNA Sequencing -RNA Sequencing -Protein Identification and Quantification -Cell-based Approaches -Omics Technologies -Imaging -Bioinformatics -Computational Biology/Chemistry -Statistics -Integrative Omics -Drug Discovery and Development -Microfluidics -Lab-on-a-chip -Data Mining -Databases -Multiplex Assays
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