Computational Methods for Next-Generation Comparative Genomics
Computational Methods for Next-Generation Comparative Genomics
批准号:
9765970
负责人:
Jian Ma
金额:
$43.36万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-01 至 2024-03-31
关键词:
3-DimensionalAddressAlgorithmsCRISPR/Cas technologyCell NucleusCellsCommunitiesComplementComputer SimulationComputing MethodologiesCreteCytologyDNA Insertion ElementsDNA Replication TimingData SetDevelopmentDiseaseEvolutionGenetic TranscriptionGenomeGenomicsHealthHumanHuman BiologyHuman GenomeImageryKnowledgeLamin Type BLinkMachine LearningMammalsMapsMeasuresMediatingMethodologyMethodsMissionModelingMolecular ProfilingNatureNuclearNuclear LaminaOutcomePatternPhenotypePrimatesPsyche structurePublic HealthResearchSignal TransductionStatistical ModelsTechniquesTimeTranslatingUnited States National Institutes of HealthUntranslated RNAbasecomparative genomicscomputerized toolsfrontierfunctional genomicsgenetic variantgenome-widegenomic dataimprovedinsightmental functionnext generationnovelpredictive modeling
中文摘要
项目摘要
调控基因组学的最新进展,特别是细胞核中的3D基因组组织,表明,
现有的跨物种比较方法在充分理解物种进化方面的能力有限。
非编码基因组功能。特别是,已知基因组被划分为不同的区域,
细胞核中的隔室,如核纤层和核斑点。这种核
区室化是高阶基因组组织的基本特征,并且与各种基因组结构相关。
重要的基因组功能,如DNA复制定时和转录。不幸的是,迄今为止,
存在直接比较人类和其他哺乳动物之间的核区室化。此外,本发明还提供了一种方法,
目前还没有计算模型来考虑核武器多个特征的连续性,
区室化和功能,这对于整合全基因组功能基因组数据和
测量跨物种多个区室的细胞学距离的数据集。在这个项目中,我们将
开发新的算法并生成新的数据集,以直接解决两个关键问题:(1)如何识别
核区室化的进化模式(2)什么类型的序列进化可能驱动
物种间的空间定位变化?拟议的项目代表了第一次奋进,
比较基因组学的研究。我们的具体目标是:(1)开发新的
概率模型用于识别核区室化的进化模式。(2)识别
基于TSA-seq的灵长类核区室化全基因组进化模式
- seq. (3)开发新的算法将序列特征与核区室化联系起来
通过跨物种比较。这些目标的成功完成将导致新的计算
工具和新的数据集,这将是非常有价值的比较基因组学社区。整合
新的计算工具和独特的数据集将提供宝贵的见解之间的关系
序列进化和哺乳动物物种核基因组组织的变化。因此
拟议中的研究有望将比较基因组学推向一个新的前沿,并提供新的
人类基因组功能的研究前景
英文摘要
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
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
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批准号:8697559
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资助金额:$32.16万
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批准号:10375481
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资助金额:$35.43万
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批准号:9102153
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批准号:10595048
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负责人:Jian Ma
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依托单位:
IMPROVE GENOME ANNOTATION USING MULTIPLE SEQUENCE ALIGNMENT RELIABILITY SCORES
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批准号:8229724
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项目类别:
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资助金额:$19.13万
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财政年份:2012
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负责人:Jian Ma
-
依托单位:
IMPROVE GENOME ANNOTATION USING MULTIPLE SEQUENCE ALIGNMENT RELIABILITY SCORES
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批准号:8432006
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项目类别:
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资助金额:$19.12万
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财政年份:2012
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负责人:Jian Ma
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依托单位:
Data Analysis and Modeling
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项目类别:
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资助金额:$29.47万
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财政年份:--
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负责人:Jian Ma
-
依托单位:
Data Analysis and Modeling
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批准号:9149252
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项目类别:
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资助金额:$29.37万
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财政年份:--
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负责人:Jian Ma
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依托单位:
海外基金