Patterns of Molecular Evolution

在我们的小组中，我们使用生物信息学来研究分子进化和群体遗传学。我们保持一个活跃的研究小组培训人员在生物信息学的跨学科性质。这包括每年聘用的博士后、研究助理、技术人员、研究生和本科生。我们的工作试图通过包含更多关于基因转移、重排和其他基因组事件的信息来构建一个更完整的细菌基因组进化图景。在本提案中，我们将进一步发展细菌基因组进化模型的方法，特别关注现代NGS（下一代测序方法）序列。由于这些基因组中的大多数是不完整的，因此将使用一种包括缺失数据的统计方法的方法。我们最近的发现包括来自古细菌基因组序列的证据，这些证据表明，一些古细菌整齐地落在现存基因组的系统发育结构内，而另一些古细菌似乎是进化的死胡同。******我们的研究小组还发现，高重复、低复杂性的序列是真核蛋白之间最常见的共享肽，并表明这些区域的初级序列非常不稳定。我们已经证明，真核蛋白的这些非常不寻常的特征是在积极的选择下，因此有助于生物体的适应能力。在这项资助的任期内，我们将通过检查真核蛋白质的基因组进化模式来确定这一观点的正确性。我们最近还表明，替代率增加发生在低复杂性区域周围，这一现象也在微卫星中观察到，但现在显示发生在蛋白质编码序列中。我们需要进一步探索这一观察结果的后果。为了做到这一点，我们将开发更好的贝叶斯方法来识别和划分低复杂度区域的边界。********

In our group we use bioinformatics to study molecular evolution and population genetics. We maintain an active research group training personnel in the interdisciplinary nature of bioinformatics.  This includes postdoctoral fellows, research associates, technicians, graduate students and undergraduates hired each year to help with the work.  Our work attempts to construct a more complete picture of bacterial genome evolution by including more information on gene transfers, rearrangements and other genomic events. In this proposal we will further develop methods to model bacterial genome evolution with particular attention given to modern NGS (Next Generation Sequencing methods) sequences. Since most of these genomes are incomplete, an approach that includes statistical  methods for missing data will be used. Among the discoveries we have made recently is evidence from ancient bacterial genomic sequences which indicate that some ancient bacteria fall neatly within the phylogenetic structure of extant genomes while other ancient bacteria appear to be evolutionary dead ends.******Our group have also discovered that highly repetitive, low complexity sequences are the most commonly shared peptide between eukaryotic proteins and have shown that the primary sequence of these regions is extremely labile.  We have demonstrated that these highly unusual features of eukaryotic proteins are under positive selection and hence contribute to the adaptive ability of organisms. During the tenure of this grant we will determine how broadly true this is by examining genome wide patterns of evolution in eukaryotic proteins.  We have also recently shown that increased substitution rates occur surrounding low complexity regions, a phenomena also observed for microsatellites, but one now shown to occur within protein coding sequences.  We need to further explore the consequences of this observation. In order to do this, we will develop better Bayesian methods to identify and delimit the boundaries of low complexity regions.********