DMS/NIGMS 1: Multilayer network approach to tandem repeat variation in genomes

DMS/NIGMS 1:基因组串联重复变异的多层网络方法

基本信息

  • 批准号:
    10592458
  • 负责人:
  • 金额:
    $ 14.84万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-09-24 至 2025-06-30
  • 项目状态:
    未结题

项目摘要

Understanding the genetic bases of biological function is a fundamental quest ion in biological sciences. Traditionally, the conservation of genetic sequences across species and populations has been a primary concept with which to measure functionality. However, recent biochemical characterizations of the DNA have challenged this definition of functionality and argued up to 80% of the human genome to be functional. Several studies have pursued the possibility that biological function evolves as an adaptive response to rapid changes under environmental pressures whe reby sequence conservation does not directly predict function. By integrating -omics datasets and multilayer network approaches, we will specifically test the following four hypotheses: (1) Among the millions of tandem repeats, a small portion, still corresponding to thousands of loci, are functionally relevant. We further hypothesize that majority of these functional tandem repeats will be evolving under negative selection and pr imarily cluster together in multilayer networks of tandem repeat units. (2) Exonic tandem repeats have evolved as molecular tools to regulate the dosage of a particular functional motif. Thus, we expect that these functional tandem repeats will retain sequence conservation among paralogs as well as among species. (3) There are hundreds of tandem repeats in the mammalian genome that evolve under lineage-specific positive selection. We expect that such positively selected tandem re peats show unusual species-specific copy number expansions or contractions, and may affect gene expression and phenotypic traits more often than neutrally evolving tandem repeats. (4) Tandem-repeat copy numbe r variation, if functional, primarily effects phenotypic variation related to immunity and metabolism in humans. We expect that these repeat loci evolve under positive selection. To test these hypotheses, we will develop mathematical/computational methods to find groups of core nodes in multilayer genetic networks, and then apply them to multilayer networks that we will build, in which each network layer is based on a specific type of relationships between tandem repeat units. RELEVANCE (See instructions): Understanding genetic bases of biological function can alleviate ou r ability to understand and treat human disease. However, variable tandem repeats in the human genome have been difficult to characterize for functional and biomedical relevance. This research will leverage recently available long-read sequencing datasets to develop mathematical methods to investigate tandemly repeated sequences in the human genome, thus providing potentially transformative insights into genetic basis of human disease. P ROJ ECT/ P E R FO R M A N C E SI T E(S) (if ad di tional space is need ed , use
了解生物功能的遗传基础是生物科学的一个基本问题。 传统上,跨物种和种群基因序列的保护一直是首要任务。 用来衡量功能的概念。然而,最近 DNA 的生化特征 对这种功能性定义提出了质疑,并认为人类基因组的 80% 是 功能性的。一些研究探讨了生物功能作为适应性进化的可能性 响应环境压力下的快速变化,而雷比序列守恒则不能 直接预测函数。通过整合组学数据集和多层网络方法,我们将 具体检验以下四个假设:(1)在数百万个串联重复序列中,一小部分, 仍然对应于数千个基因座,具有功能相关性。我们进一步假设大多数 这些功能串联重复序列将在负选择下进化并主要聚集在一起 串联重复单元的多层网络。 (2) 外显子串联重复序列已发展成为分子工具 调节特定功能基序的剂量。因此,我们期望这些功能性串联重复序列 将保留旁系同源物之间以及物种之间的序列保守性。 (3)有数百个 哺乳动物基因组中的串联重复序列在谱系特异性正选择下进化。我们 预计这种积极选择的串联重复会显示出不寻常的物种特异性拷贝数 扩张或收缩,并且可能更频繁地影响基因表达和表型性状 中性进化的串联重复序列。 (4) 串联重复拷贝数变异,如果有功能的话,主要是 影响与人类免疫和新陈代谢相关的表型变异。我们预计这些重复 位点在正选择下进化。为了检验这些假设,我们将开发 在多层遗传网络中查找核心节点组的数学/计算方法,以及 然后将它们应用到我们将构建的多层网络中,其中每个网络层都基于 串联重复单元之间特定类型的关系。 相关性(参见说明): 了解生物功能的遗传基础可以提高我们理解和治疗人类的能力 疾病。然而,人类基因组中的可变串联重复序列很难表征 功能和生物医学相关性。这项研究将利用最近可用的长读长测序 用于开发数学方法来研究人类串联重复序列的数据集 基因组,从而为人类疾病的遗传基础提供潜在的变革性见解。 项目/表演场地(如果需要额外空间,请使用

项目成果

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Naoki Masuda其他文献

Naoki Masuda的其他文献

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{{ truncateString('Naoki Masuda', 18)}}的其他基金

DMS/NIGMS 1: Multilayer network approach to tandem repeat variation in genomes
DMS/NIGMS 1:基因组串联重复变异的多层网络方法
  • 批准号:
    10709591
  • 财政年份:
    2022
  • 资助金额:
    $ 14.84万
  • 项目类别:

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