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Leveraging phylogenetic approaches to investigate the evolution of gene expression

利用系统发育方法研究基因表达的进化

基本信息

批准号：
10716009
负责人：
Matthew Wesley Pennell
金额：
$ 39.75万
依托单位：
UNIVERSITY OF SOUTHERN CALIFORNIA
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-08-01 至 2028-07-31
项目状态：
未结题

项目摘要

SUMMARY Across the biomedical sciences there has been an increased recognition that many key questions in these fields require phylogenetic thinking and approaches. My group has a very strong track record of making fundamental methodological contributions that have changed how biologists think about and analyze phylogenetically structured data and of finding new applications for these methods. My group’s current research is focused on two main themes, both related to the evolution of genomic function. First, we will use phylogenetic comparative approaches to investigate the dynamics of gene expression evolution across species. We will first assess the appropriateness of adopting phylogenetic models of phenotypic evolution for describing changes in gene expression using an approach we have previously developed. This will enable us to assess the robustness of findings regarding the relative importance of different evolutionary processes in generating interspecific diversity and help us develop the next-generation of models, specifically tailored to functional genomic data. We will then build a mechanistic model that will allow us and other researchers to test for associations between gene expression evolution and sequence evolution in the promoter regions. Second, we will study the evolution of Immunoglobulin genes, which encode the unique antigen recognition sequences of B cells, which produce antibodies. We will investigate this at two nested levels: the evolution of the B cell repertoire over time and in response to pathogens and the evolution of the germline Immunoglobulin genes. To examine changes in the B cell repertoire, we will adopt approaches that our research group has pioneered in the context of macroevolution, to characterize the dynamics of the system. We are specifically interested in estimating the rate of somatic mutation and the number of distinct clonal lineages that are expanding in response to an infectious disease. There is accumulating evidence that variation in the evolved response of B cells is associated with inter-individual variation in the germline Immunoglobulin genes. However, the underpinning mechanism remains unclear as do the reasons there appears to be so much diversity at these loci across individuals. We will derive an evolutionary model, and parameterize it using comparative genomic data, to evaluate the plausibility of alternative hypotheses for explaining both of these observations.

概括在整个生物医学科学领域，人们越来越认识到许多关键问题这些领域需要系统发育的思维和方法。我的团队有很强的赛道做出基本方法论贡献的记录改变了生物学家的研究方式思考和分析系统发育结构化数据并寻找新的应用这些方法。我的小组目前的研究集中在两个主题，都与基因组功能的进化。首先，我们将使用系统发育比较方法来研究动态跨物种的基因表达进化。我们将首先评估采用的适当性表型进化的系统发育模型，用于使用我们之前开发的方法。这将使我们能够评估研究结果的稳健性关于不同进化过程在产生种间的相对重要性多样性并帮助我们开发下一代模型，专门针对功能性量身定制基因组数据。然后我们将建立一个机械模型，使我们和其他研究人员能够测试启动子中基因表达进化和序列进化之间的关联地区。其次，我们将研究免疫球蛋白基因的进化，该基因编码独特的 B 细胞的抗原识别序列，产生抗体。我们将对此进行调查两个嵌套级别：B 细胞库随时间的演变以及对病原体的反应以及种系免疫球蛋白基因的进化。检查 B 细胞的变化曲目，我们将采用我们的研究小组在以下背景下开创的方法宏观进化，来表征系统的动力学。我们特别感兴趣的是估计体细胞突变率和不同克隆谱系的数量为应对传染病而扩大规模。越来越多的证据表明，变化 B 细胞的进化反应与种系的个体间变异有关免疫球蛋白基因。然而，其基础机制仍不清楚，这就是为什么个体之间的这些基因座似乎存在如此多的多样性。我们将得出一个进化模型，并使用比较基因组数据对其进行参数化，以评估用于解释这两个观察结果的替代假设的合理性。