Evolutionary Analysis of Bacterial Genomes: High-Throughput Computational Tools

描述（由申请人提供）： 像所有形式的生命一样，细菌也经历着进化。然而，与许多其他生物体不同，细菌的进化不是严格的垂直下降。水平基因转移（horizontal gene transfer，HGT）是遗传物质在亲缘关系较远的物种间转移的过程，在生命之树的原核生物分支中普遍存在。在HGT的存在下，一组生物的进化历史不是树状的，而是网状的。HGT在微生物基因组多样化中起着重要作用，并且据称在细菌的各种基因组中猖獗。此外，它是细菌对抗生素产生耐药性的主要机制。 细菌基因组研究面临的两个主要挑战是估计基因水平转移的程度，以及重建它们的进化历史。前者对于理解HGT所起的进化作用并预测其发生具有重要意义，后者相当于检测水平转移基因的供体和受体，有助于了解细菌如何获得抗生素抗性以及如何开发更有效的抗生素。为应对第一项挑战所作的努力导致了相互矛盾的结果，而为应对第二项挑战所作的努力却很有限。关于细菌中HGT程度的估计从一个极端（HGT如此猖獗，使得细菌系统发育树无用）到另一个极端（HGT仅仅是被线性下降信号覆盖的背景噪声）。至于重建网状进化历史的挑战，进展更不令人满意，主要是由于缺乏准确和有效的方法来重建系统发育网络。我们的目标是开发用于细菌基因组的高通量全基因组进化分析的计算工具，重点是HGT的检测和重建。为了实现这一目标，我们将开发： (1)细菌基因组的微观水平分析方案，以估计HGT率。 (2)一个结合群体遗传学和遗传学理论的随机框架，用于中等水平的分析。 (3)用于检测HGT的基因组系统发育（宏观水平）分析的化学技术。 (4)实施协议和方法并使其可供研究界使用的软件工具。

DESCRIPTION (provided by applicant): Like all forms of life, bacteria undergo evolution. However, unlike many other organisms, bacterial evolution is not one of strict vertical descent. Horizontal (or lateral) gene transfer (HGT), a process by which genetic material is transferred among distantly related species, is ubiquitous in the prokaryotic branch of the Tree of Life. In the presence of HGT, the evolutionary history of a set of organisms is not treelike; rather, it is reticulate. HGT plays a major role in microbial genome diversification, and is claimed to be rampant among various groups of genes in bacteria. Further, it is a major mechanism by which bacteria develop resistance to antibiotics. Two major challenges that face studies of bacterial genomes involve estimating the extent of horizontally transferred genes in them, and reconstructing their evolutionary history. The former bears great significance on understanding the evolutionary role HGT plays and making predictions about its occurrence, and the latter amounts to detecting the donors and recipients of horizontally transferred genes, helping to understand how bacteria acquire antibiotic resistance and how to develop more effective ones. Attempts at addressing the first challenge have led to conflicting results, whereas attempts at the second challenge have been limited. Estimates as to the extent of HGT in bacteria range from one extreme (HGT is so rampant, rendering a bacterial phylogenetic tree useless) to another (HGT is mere background noise overridden by the lineal descent signal). As for the challenge of reconstructing reticulate evolutionary histories, the progress is even less satisfactory, mainly due to the lack of accurate and efficient methods for reconstructing phylogenetic networks. Our objective is to develop computational tools for high-throughput genome-wide evolutionary analysis of bacterial genomes, with focus on the detection and reconstruction of HGT. To achieve this objective, we will develop: (1) Protocols for micro-level analyses of bacterial genomes, to estimate HGT rates. (2) A stochastic framework that combined population genetics and phylogenetics theories for medium-level analyses. (3) Algorithmic techniques for phylogenetic (macro-level) analyses of genomes for detecting HGT. (4) Software tools that implement the protocols and methodologies and make them available to the research community.