Postdoctoral Research Fellowships in Biology for FY 2009

本行动资助NSF 2009年度博士后研究奖学金。该奖学金支持Philip Johnson的一项名为“从宏基因组数据推断微生物种群参数”的研究和培训计划。这项研究的主办机构是埃默里大学，赞助科学家是Rustom Antia。尽管人们越来越认识到非致病微生物的生态重要性，但影响天然微生物种群进化的力量在很大程度上仍然未知。DNA测序的最新技术进步使得从自然环境中对DNA进行采样和测序的宏基因组项目能够从样本中的优势物种中获得全基因组的种群样本。本研究开发了一种估算微生物间遗传物质交换率（即重组率）的方法。与之前的模型相比，该方法结合了微生物重组率与序列发散负相关的经验证据。两种平行的方法正在被采用：1)标准聚结过程的修改版本，其中聚结事件更有可能发生在重组的谱系之间；2)类似于构建祖先选择图的两阶段过程，其中构建一个大型祖先重组图，应用突变，然后根据序列分歧接受或拒绝重组事件。培训目标包括提高统计和数学建模专业知识，特别是聚结理论，重要抽样和图论，同时进一步与实验生物学家互动。提出的方法的灵感来自两个宏基因组项目，它们对具有严重环境后果的微生物群落进行采样：废水处理厂中的活性污泥和废弃矿山中产生高酸性径流的生物膜。研究这两种种群的进化将指导管理它们的工程策略的设计。外联活动包括让本科生参与数据分析，研究结果将通过在同行评议的期刊上发表而广泛传播。

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.