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引用本文:罗建桦,陶晔,邢鹏,吴庆龙.湖泊微生物宏基因组学研究进展.湖泊科学,2020,32(1):271-280. DOI:10.18307/2020.0125
LUO Jianhua,TAO Ye,XING Peng,WU Qinglong.Mini-review: Advances of metagenomics research for lake microbiomes. J. Lake Sci.2020,32(1):271-280. DOI:10.18307/2020.0125
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湖泊微生物宏基因组学研究进展
罗建桦1,2, 陶晔1,3, 邢鹏1, 吴庆龙1,2
1.中国科学院南京地理与湖泊研究所, 湖泊与环境国家重点实验室, 南京 210008;2.中国科学院大学中丹学院, 北京 100049;3.中国科学院大学, 北京 100049
摘要:
湖泊微生物作为湖泊生态系统重要组成部分,在局域和区域的元素循环中发挥着关键作用.由于自然环境中微生物之间的复杂关系和对微生物认知的片面性,可在实验室培养的湖泊微生物比例不足1%.近10年来,宏基因组学技术在微生物生态学研究中得到了广泛应用,不仅扩展了对湖泊微生物群落组成和多样性的认识,更揭示了湖泊微生物的功能多样性和微生物之间的相互作用.特别是基于宏基因组数据的分装(Binning)手段,可以获取大量湖泊中未培养微生物的基因组信息,用于后续的比较基因组、生态进化和培养组学等研究.随着宏基因组学相关学科和技术的不断发展,其将在湖泊微生物生态学基础理论研究和环境生物监测应用中发挥更为重要的作用,成为人类了解湖泊生态系统功能和维持机制的有力工具.
关键词:  湖泊微生物  宏基因组学  生态基因组学  数据分装  宏基因组拼接基因组  功能
DOI:10.18307/2020.0125
分类号:
基金项目:国家自然科学基金项目(31722008,91751111)和中国科学院青年创新促进会项目(2014273)联合资助.
Mini-review: Advances of metagenomics research for lake microbiomes
LUO Jianhua1,2, TAO Ye1,3, XING Peng1, WU Qinglong1,2
1.State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, P. R. China;2.Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049, P. R. China;3.University of Chinese Academy of Sciences, Beijing 100049, P. R. China
Abstract:
As one of the essential components, microorganisms are the cores of biogeochemical circulation in lakes. However, due to the complex interaction among microorganisms and the incomplete description of their habitats, less than 1% of microorganisms in lakes can be cultivated in the laboratory. In the past ten years, metagenomic methods has been widely applied to the microbial researches, which enormously contribute to the understanding of microbiomes in lake ecosystems. The obtained results not only uncovered the composition and diversity of microbial communities, but also revealed the ecological functions of microbes as well as the interactions among microorganisms. Moreover, metagenome-assembled genomes (MAGs) of uncultured microorganisms can be obtained by various contig binning strategies based on metagenomic data mining, which can be subsequently used for comparative genomics and ecological evolution studies. With the continuous development of bioinformatics discipline and the relevant sequencing technologies, metagenomics will become a more powerful tool in basic ecological principle exploration and routine environmental biomonitoring, and also become the cornerstone of understanding the ecosystem function and maintaining the ecological services of lakes.
Key words:  Lake microbiomes  metagenomics  ecological genomics  binning  Metagenome-assembled genomes (MAGs)  function
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