Postdoctoral Research Fellowships in Biology for FY 2009

这一行动为NSF 2009财年博士后研究奖学金提供了资金。该研究金支持菲利普·约翰逊的一项研究和培训计划，该计划题为“从元基因组数据推断微生物种群参数”。这项研究的主办机构是埃默里大学，赞助科学家是Rustom anti.尽管人们越来越意识到非致病微生物的生态重要性，但影响自然微生物种群进化的力量在很大程度上仍然是未知的。DNA测序方面的最新技术进步使从自然环境中采样DNA并对其进行排序的元基因组项目能够从本质上产生样本中优势物种的全基因组种群样本。这项研究开发了一种方法，根据这些数据估计微生物之间的遗传物质交换率(即重组率)。与以前的模型不同，这个新方法结合了微生物重组率与序列分歧负相关的经验证据。正在采取两种并行的方法：1)标准合并过程的修改版本，其中在已经重组的谱系之间更有可能发生合并事件，以及2)类似于构建祖先选择图的两阶段过程，其中构建了大型祖先重组图，应用突变，然后根据序列分歧接受或拒绝重组事件。培训目标包括改进统计和数学建模专业知识，特别是合并理论、重要性抽样和图论，同时促进与实验生物学家的互动。拟议方法的灵感来自两个对具有严重环境后果的微生物群落进行采样的元基因组项目：污水处理厂的活性污泥和在废弃矿山生长的生物膜，后者产生高度酸性的径流。研究这两个种群的进化将指导设计管理它们的工程策略。外展包括让本科生参与数据分析，这项研究的结果将通过发表在同行评议的期刊上广泛传播。

This action funds an NSF Postdoctoral Research Fellowship for FY 2009. The fellowship supports a research and training plan entitled "Inference of microbial population parameters from metagenomic data" for Philip Johnson. The host institution for this research is Emory University and the sponsoring scientist is Rustom Antia.Despite a growing awareness of the ecological importance of non-pathogenic microbes, the forces affecting the evolution of natural microbial populations remain largely unknown. Recent technological advances in DNA sequencing have enabled metagenomic projects that sample and sequence DNA from natural environments to yield, in essence, a genome-wide population sample from the dominant species in the sample. This research develops a method for estimating the rate of exchange of genetic material among microbes (i.e. the recombination rate) from such data. In contrast to previous models, this new method incorporates empirical evidence that microbial recombination rates are negatively correlated with sequence divergence. Two parallel approaches are being taken: 1) a modified version of the standard coalescent process in which coalescent events are more likely between lineages that have recombined and 2) a two-stage procedure analogous to constructing an ancestral selection graph in which a large ancestral recombination graph is constructed, mutations are applied and then recombination events are accepted or rejected depending on sequence divergence.Training goals include improving statistical and mathematical modeling expertise, specifically coalescent theory, importance sampling, and graph theory, while furthering interactions with experimental biologists. The inspiration for the proposed methods came from two metagenomic projects that sample microbial communities with serious environmental consequences: activated sludge in wastewater treatment plants and biofilms that grow in abandoned mines producing highly acidic runoff. Studying the evolution of these two populations will guide the design of engineering strategies to manage them. Outreach includes involvement of undergraduate students with data analysis, and the results of this research will be broadly disseminated through publication in peer-reviewed journals.