Computational Methods for Next-Generation Comparative Genomics

下一代比较基因组学的计算方法

基本信息

批准号：
9765970
负责人：
Jian Ma
金额：
$ 43.36万
依托单位：
CARNEGIE-MELLON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2014
资助国家：
美国
起止时间：
2014-09-01 至 2024-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9765970
关键词：
3-Dimensional Address Algorithms CRISPR/Cas technology Cell Nucleus Cells Communities Complement Computer Simulation Computing Methodologies Crete Cytology DNA Insertion Elements DNA Replication Timing Data Set Development Disease Evolution Genetic Transcription Genome Genomics Health Human Human Biology Human Genome Imagery Knowledge Lamin Type B Link Machine Learning Mammals Maps Measures Mediating Methodology Methods Mission Modeling Molecular Profiling Nature Nuclear Nuclear Lamina Outcome Pattern Phenotype Primates Psyche structure Public Health Research Signal Transduction Statistical Models Techniques Time Translating United States National Institutes of Health Untranslated RNA base comparative genomics computerized tools frontier functional genomics genetic variant genome-wide genomic data improved insight mental function next generation novel predictive modeling

项目摘要

PROJECT SUMMARY Recent advances in regulatory genomics, especially 3D genome organization in cell nucleus, suggest that existing methods for cross-species comparisons are limited in their ability to fully understand the evolution of non-coding genome function. In particular, it is known that genomes are compartmentalized to distinct compartments in the nucleus such as nuclear lamina and nuclear speckles. Such nuclear compartmentalization is an essential feature of higher-order genome organization and is linked to various important genome functions such as DNA replication timing and transcription. Unfortunately, to date no study exists that directly compares nuclear compartmentalization between human and other mammals. In addition, there are no computational models available that consider the continuous nature of multiple features of nuclear compartmentalization and function, which is critical to integrate genome-wide functional genomic data and datasets that measure cytological distance to multiple compartments across species. In this project, we will develop novel algorithms and generate new datasets to directly address two key questions: (1) How to identify the evolutionary patterns of nuclear compartmentalization? (2) What types of sequence evolution may drive spatial localization changes across species? The proposed project represents the first endeavor in comparative genomics for nuclear compartmentalization. Our Specific Aims are: (1) Developing new probabilistic models for identifying evolutionary patterns of nuclear compartmentalization. (2) Identifying genome-wide evolutionary patterns of nuclear compartmentalization in primate species based on TSA-seq and Repli-seq. (3) Developing new algorithms to connect sequence features to nuclear compartmentalization through cross-species comparisons. Successful completion of these aims will result in novel computational tools and new datasets that will be highly valuable for the comparative genomics community. Integrating the new computational tools and unique datasets will provide invaluable insights into the relationship between sequence evolution and changes in nuclear genome organization in mammalian species. Therefore, the proposed research is expected to advance comparative genomics to a new frontier and provide new perspectives for studying human genome function

项目摘要调节基因组学的最新进展，尤其是细胞核中的3D基因组组织，这表明现有的跨物种比较方法的能力有限非编码基因组函数。特别是，众所周知，基因组被分为不同核层和核斑点等细胞核中的隔室。这样的核隔室化是高阶基因组组织的重要特征，与各种重要的基因组函数，例如DNA复制时间和转录。不幸的是，迄今为止没有研究存在直接比较人与其他哺乳动物之间的核分室化。此外，没有可用的计算模型来考虑核的多个特征的连续性分隔和功能，这对于整合全基因组功能基因组数据和测量与物种多个隔室的细胞学距离的数据集。在这个项目中，我们将开发新颖的算法并生成新数据集，以直接解决两个关键问题：（1）如何识别核分室化的进化模式？（2）哪种类型的序列演变可能会驱动物种之间的空间定位变化？拟议的项目代表了核分室化的比较基因组学。我们的具体目的是：（1）开发新的概率模型，用于识别核分室化的进化模式。（2）识别基于TSA-SEQ和 REPEN-seq。（3）开发新算法以将序列特征连接到核分室化通过跨物种比较。这些目标的成功完成将导致新颖的计算对于比较基因组学界来说，工具和新数据集将非常有价值。整合新的计算工具和独特的数据集将提供有关对哺乳动物物种中核基因组组织的序列进化和变化。因此，拟议的研究有望将比较基因组学推向新的边界，并提供新的研究人类基因组功能的观点