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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.

摘要在整个生物医学科学中，人们越来越多地认识到许多关键问题在这些领域需要系统发展的思维和方法。我的团队有一个非常强大的轨道在方法论上做出根本性贡献的记录改变了生物学家思考和分析系统发生结构数据，并寻找新的这些方法。我的小组目前的研究集中在两个主要主题上，都与基因组功能的进化。首先，我们将使用系统发育比较的方法来研究跨物种的基因表达进化。我们将首先评估采用用于描述基因表达变化的表型进化的系统发育模型我们之前开发的方法。这将使我们能够评估结果的稳健性关于不同进化过程在产生种间关系中的相对重要性多样性，并帮助我们开发下一代型号，专门针对功能基因组数据。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启动子中基因表达进化和序列进化之间的相关性检验地区。第二，我们将研究免疫球蛋白基因的进化，它编码唯一的 B细胞的抗原识别序列，产生抗体。我们将在以下地址调查此事两个嵌套水平：B细胞谱系随时间的演变和对病原体的反应以及生殖系免疫球蛋白基因的进化。检查B细胞中的变化，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，以刻画系统的动态。我们特别感兴趣的是估计体细胞突变率和不同克隆系的数量为了应对传染病而扩张的。有越来越多的证据表明， B细胞的进化反应与生殖系的个体间变异有关免疫球蛋白基因。然而，支撑机制仍然不清楚，就像原因是这些基因座在不同个体之间似乎存在如此大的多样性。我们将派生出一个进化模型，并使用比较基因组数据将其参数化，以评估解释这两种观察结果的其他假设的合理性。