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，其中大部分尚未被发现。由于基因组测序可以帮助描述这种多样性，并且最近已经成为常规，大多数微生物科学家已经被大量的可用数据所淹没。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和彻底的分析。相反，这些用户将得到更好的服务，直接的方法，可以确定他们的未知DNA/RNA序列，并能够区分良好理解的分类群和那些潜在的新的。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非常重要。此外，宏基因组学，这是环境DNA的测序，允许遗传特性的大多数这些原核生物，已抵制在实验室培养。然而，目前分析宏基因组数据的工具明显落后于测序技术（和数据处理工具）的发展，并且通常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生物多样性的一个主要限制，这些微生物在地球上运行着维持生命的生物地球化学循环，与其植物和动物宿主形成重要的联系，或生产具有生物技术价值的产品。因此，新的方法，使新兴的基因组和宏基因组序列信息容易获得的非专家用户是及时和必要的，以促进我们的理解的多样性和功能的微生物群落在生态学，系统学，进化，工程，农业和医学领域。 该项目的总体目标是开发一个计算框架，以组织和编目细菌和古细菌的“未培养的大多数”的基因组和宏基因组信息，并将利用现有的和即将到来的宏基因组数据集扩大规模。为了实现这一目标，微生物基因组图谱项目（MiGA），最初的目的是编目分离基因组之间的多样性，将使用和扩大新的工具和计算解决方案，使其能够包括“未培养的大多数”。这些新工具包括但不限于：基于kmer的方法，以取代用于估计基因组之间遗传相关性的基于测序的基因组平均核苷酸同一性（ANI）度量，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，以及自然序列离散人群中的遗传变异水平。这项研究工作将解决目前基于16 S rRNA基因的方法在编目微生物多样性方面的关键限制（例如，缺乏物种水平及以下的分辨率），并将为来自未培养微生物的高通量基因组和宏基因组数据的在线分析提供急需的工具。该项目还将为本科生和研究生提供微生物学，进化，基因组学，生物信息学和计算生物学界面的多方面学习经验，这是当代研究和教育的关键领域。请参阅MiGA的网站了解更多细节：www.microbial-genomes.org。该奖项反映了NSF的法定使命，并被认为值得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来支持。

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.