Collaborative Research: ABI Development: "The Microbial Genome Atlas (MiGA) project and its expansion to catalogue the uncultivated microbial majority"

地球上原核微生物的多样性非常大，估计有超过10亿种细菌，其中大部分仍未被发现。由于基因组测序可以帮助描述这种多样性，并且最近已成为常规，大多数微生物科学家已被大量可用数据所淹没。对于许多研究人员来说，没有必要对现有的基因组数据进行完整而彻底的分析。相反，这些用户将更好地服务于直接的方法，可以识别他们未知的DNA/RNA序列，并能够区分已经了解的分类群和那些潜在的新分类群。能够帮助研究人员在数千个候选基因中找到最“有趣”的基因组和基因的工具将是重要的。此外，宏基因组学，即环境DNA的测序，允许在实验室中对大多数抵抗培养的原核生物进行遗传表征。然而，目前用于分析宏基因组数据的工具显然落后于测序技术（和数据处理工具）的发展，并且通常局限于基因组组装和基因注释。这是更好地了解、研究和交流未培养微生物的生物多样性的主要限制，这些微生物在地球上维持生命的生物地球化学循环中运行，与植物和动物宿主形成关键联系，或生产具有生物技术价值的产品。因此，将新兴的基因组和宏基因组序列信息提供给非专业用户是及时和必要的，以促进我们对生态学、系统学、进化、工程、农业和医学等领域微生物群落多样性和功能的理解。该项目的总体目标是开发一个计算框架，以组织和编目“未培养的大多数”细菌和古细菌的基因组和宏基因组信息，这些信息将随着现有和即将到来的宏基因组数据集而扩大规模。为了实现这一目标，微生物基因组图谱项目（MiGA）将被使用，并通过新的工具和计算解决方案进行扩展，使其能够涵盖“未开垦的大多数”。MiGA最初设计的目的是对分离基因组的多样性进行编目。新工具包括——但不限于——基于kmer的方法，以取代基于比对的基因组平均核苷酸同一性（ANI）度量，用于估计基因组之间的遗传相关性，以及用于评估基因组完整性和质量的高通量工具，一组基因组的泛基因组，以及自然序列离散群体内的遗传变异水平。这项研究工作将解决当前基于16S rRNA基因的微生物多样性编录方法的关键局限性（例如，缺乏物种水平及以下的分辨率），并将为在线分析来自未培养微生物的高通量基因组和宏基因组数据提供急需的工具。该项目还将为本科生和研究生提供多方面的学习经验，涉及微生物学，进化，基因组学，生物信息学和计算生物学，这是当代研究和教育的关键领域。详见多边投资担保机构网站：www.microbial-genomes.org。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The diversity of prokaryotic microbes on the planet is very large, estimated at over a billion species of bacteria, and most of it remains undiscovered. As genome sequencing can help characterizing this diversity and has recently become routine, most microbial scientists have been overwhelmed by the amount of available data. For many researchers, a complete and thorough analysis of the available genome data is not necessary. Instead, these users would be better served with straightforward methods that can identify their unknown DNA/RNA sequence(s), and be able to discriminate between well-understood taxa and those that are potentially novel. Tools that can help direct researchers to the most "interesting" genomes and genes among thousands of candidates will be important. Furthermore, metagenomics, which is the sequencing of environmental DNA, allows the genetic characterization of the majority of these prokaryotes that have resisted cultivation in the laboratory. However, current tools to analyze metagenomic data are clearly lagging behind the development of sequencing technologies (and data processing tools), and are typically limited to genome assembly and gene annotation. This is a major limitation for better understanding, studying and communicating about the biodiversity of uncultivated microorganisms that run the life-sustaining biogeochemical cycles on the planet, form critical associations with their plant and animal hosts, or produce products of biotechnological value. Therefore, new approaches to make the emerging genomic and metagenomic sequence information readily available to the non-expert user are timely and essential in order to advance our understanding of the diversity and function of microbial communities across the fields of ecology, systematics, evolution, engineering, agriculture and medicine. The overarching goal of this project is to develop a computational framework to organize and catalogue the genomic and metagenomic information of the "uncultivated majority" of bacteria and archaea that will scale-up with the available and forthcoming metagenomic data sets. To achieve this goal, the Microbial Genomes Atlas project (MiGA), which was originally designed to catalogue the diversity among isolate genomes, will be used and expanded with new tools and computational solutions that will allow it to encompass the "uncultivated majority". The new tools include -but are not limited to- a kmer-based approach to replace the alignment-based genome-average nucleotide identity (ANI) metric for estimating genetic relatedness among genomes and high-throughput tools for assessing genome completeness and quality, the pangenome of a group of genomes, and the level of genetic variation within natural sequence-discrete populations. This research effort will address critical limitations of the current 16S rRNA gene-based approaches in cataloging microbial diversity (e.g., lack of resolution at the species level and below), and will provide highly needed tools for the online analysis of high throughput genomic and metagenomic data from uncultivated microorganisms. The project will also provide multifaceted learning experiences to both undergraduate and graduate students at the interface of microbiology, evolution, genomics, bioinformatics, and computational biology, a pivotal area of contemporary research and education. See MiGA's website for further details at: www.microbial-genomes.org .This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.