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
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

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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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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