Transcriptional Regulatory Networks of Craniofacial Development

颅面发育的转录调控网络

基本信息

  • 批准号:
    10432118
  • 负责人:
  • 金额:
    $ 13.01万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-07-01 至 2026-06-30
  • 项目状态:
    未结题

项目摘要

Abstract Human craniofacial development is a complex process and frequently goes awry to cause a major class of birth defects, orofacial clefting, which affects approximately 1 in 700 live births. Proper facial development in mouse and human requires three sets of paired facial prominences coming together by growth, morphogenesis, and fusion. Embryonic facial development is strikingly similar in human and mouse, making the mouse the best available model system for human. Previous studies have shown that the expression of many thousands of genes changes across tissue layer, age, and/or prominence, as well as cell population during early mouse facial development. However, we still only have a rudimentary understanding of how these changes are regulated by the interaction of transcriptional modulators in the developing face. To understand how genes are transcriptionally regulated during facial development, this research seeks to construct transcriptional regulatory networks in a temporospatial manner by in silico analysis of publicly available multi- omic datasets. Aim 1 will focus on the identification and verification of transcriptional regulatory networks operating in facial mesenchyme with a focus on super-enhancers. Aim 2 will adopt a similar approach to study the ectoderm which acts as a vital signaling center for the mesenchyme. Finally, in Aim 3 I will apply knowledge from Aims 1 and 2 to build transcriptional regulatory networks at the single cell level. These aims will take advantage of available RNA-seq, ATAC-seq, histone marker ChIP-seq, transcription factor ChIP-seq, bulk and single cell RNA-seq data from wild-type or mutant mice, as well as facial enhancer expression databases. Accomplishment of these studies will predict how genes are transcriptionally regulated in a temporospatial manner during facial development and discover sets of core transcription factors and super- enhancers controlling facial development. These transcriptional regulatory networks will be relevant to the genetic and molecular underpinnings of human orofacial clefting, and will provide clear testable predictions about transcription factor function and the consequences of aberrant expression. Performance and accomplishment of these Aims will also act as a major component of my career development plan, in which my goal is to obtain and independent tenure-track faculty position and serve as a mentor to the next generation of scientists. A major aspect of my career development plan is to build on my growing strength in bioinformatics by learning more advanced techniques in this specialty alongside new computational based approaches, such as machine learning. In this respect, my Aims and career development plan are aligned with a Notice of Special Interest (NOSI) of NIDCR in Supporting Dental, Oral, and Craniofacial Research Using Bioinformatic, Computational, and Data Science Approaches (NOT-DE-20-006) for which this application is targeted. I have recruited a mentorship team with specialties in craniofacial biology, bioinformatics, machine learning, and career development to help me achieve these goals.
摘要 人类颅面发育是一个复杂的过程,经常出现错误,导致一大类 出生缺陷,口腔裂伤,影响大约700名活产儿中的1名。面部发育正常 老鼠和人类需要三组成对的面部隆起通过生长结合在一起, 形态发生和融合。人类和小鼠的胚胎面部发育惊人地相似,使得 鼠标是人类可用的最好的模型系统。先前的研究表明, 数以千计的基因会随着组织层、年龄和/或突起以及细胞群体的不同而变化 在老鼠面部发育的早期。然而,我们仍然对这些 这种变化是由发育面孔中转录调节因子的相互作用来调节的。要理解 在面部发育过程中,基因是如何转录调控的,这项研究试图构建 以时间-空间方式转录调控网络--通过对公开可获得的多个 基因组数据集。目标1将侧重于识别和验证转录调控网络 在面部间充质中运作,专注于超级增强剂。目标2将采用类似的方法来研究 作为间充质的重要信号中心的外胚层。最后,在目标3中,我将申请 来自目标1和目标2的知识,以在单细胞水平上建立转录调控网络。这些目标 将利用现有的RNA-SEQ、ATAC-SEQ、组蛋白标记芯片-SEQ、转录因子芯片-SEQ, 来自野生型或突变小鼠的散装和单细胞RNA-seq数据以及面部增强子的表达 数据库。这些研究的完成将预测基因如何在转录水平上调节 在面部发育过程中的时间空间方式,并发现核心转录因子和超 控制面部发育的增强剂。这些转录调控网络将与 人类口裂的遗传和分子基础,并将提供明确的可检验的预测 关于转录因子的功能和异常表达的后果。性能和 实现这些目标也将是我职业发展计划的重要组成部分,在我的职业发展计划中,我 目标是获得独立的终身教职跟踪教师职位,并作为下一代教师的导师 科学家们。我职业发展计划的一个主要方面是加强我在生物信息学方面日益增长的实力 通过学习该专业中更先进的技术,以及基于计算的新方法,例如 作为机器学习。在这方面,我的目标和职业发展计划与一份 NIDCR在使用生物信息学支持牙科、口腔和颅面研究方面的特殊兴趣(NOSI), 计算和数据科学方法(非-DE-20-006)是本应用程序的目标。我有过 招募了一支指导团队,专门从事颅面生物学、生物信息学、机器学习和 职业发展帮助我实现这些目标。

项目成果

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Hong Li其他文献

Low temperature methane steam reforming for SOFC
SOFC 低温甲烷蒸汽重整
  • DOI:
  • 发表时间:
    2015-06
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Zhongchao Dong;Chunwen Sun;Hong Li;Liquan Chen
  • 通讯作者:
    Liquan Chen

Hong Li的其他文献

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{{ truncateString('Hong Li', 18)}}的其他基金

In utero rescue of cleft lip and palate in a humanized mouse model
人源化小鼠模型中唇裂和腭裂的子宫内抢救
  • 批准号:
    10645829
  • 财政年份:
    2023
  • 资助金额:
    $ 13.01万
  • 项目类别:
Core D – Biostatistics Core
核心 D — 生物统计学核心
  • 批准号:
    10172475
  • 财政年份:
    2021
  • 资助金额:
    $ 13.01万
  • 项目类别:
Transcriptional Regulatory Networks of Craniofacial Development
颅面发育的转录调控网络
  • 批准号:
    10633187
  • 财政年份:
    2021
  • 资助金额:
    $ 13.01万
  • 项目类别:
Transcriptional Regulatory Networks of Craniofacial Development
颅面发育的转录调控网络
  • 批准号:
    10284443
  • 财政年份:
    2021
  • 资助金额:
    $ 13.01万
  • 项目类别:
Core D – Biostatistics Core
核心 D — 生物统计学核心
  • 批准号:
    10634595
  • 财政年份:
    2021
  • 资助金额:
    $ 13.01万
  • 项目类别:
Core D – Biostatistics Core
核心 D — 生物统计学核心
  • 批准号:
    10441218
  • 财政年份:
    2021
  • 资助金额:
    $ 13.01万
  • 项目类别:
Structural Biology Studies of Ribosome Biogenesis Network
核糖体生物发生网络的结构生物学研究
  • 批准号:
    10389719
  • 财政年份:
    2018
  • 资助金额:
    $ 13.01万
  • 项目类别:
Structural Biology Studies of Ribosome Biogenesis Network
核糖体生物发生网络的结构生物学研究
  • 批准号:
    10249225
  • 财政年份:
    2018
  • 资助金额:
    $ 13.01万
  • 项目类别:
Structures of RNA processing and Silencing Enzymes in Prokaryotes
原核生物中 RNA 加工和沉默酶的结构
  • 批准号:
    8461958
  • 财政年份:
    2012
  • 资助金额:
    $ 13.01万
  • 项目类别:
Structures of RNA Processing and Silencing Enzymes in Prokaryotes
原核生物中 RNA 加工和沉默酶的结构
  • 批准号:
    9247630
  • 财政年份:
    2012
  • 资助金额:
    $ 13.01万
  • 项目类别:

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