Transcriptional Regulation of Stem Cell Differentiation into Motor Neurons

干细胞分化为运动神经元的转录调控

基本信息

  • 批准号:
    7920094
  • 负责人:
  • 金额:
    $ 128.52万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2006
  • 资助国家:
    美国
  • 起止时间:
    2006-09-15 至 2013-02-28
  • 项目状态:
    已结题

项目摘要

We propose to further our understanding of the molecular mechanisms that direct stem cells during neural development with the ultimate goal of enabling stem cell based regenerative medicine for neurodegenerative diseases. We will study the etiology of Spinal Muscular Atrophy (SMA) in the context of the mechanisms that we elucidate with the goal of developing clues to potential therapeutic targets for this developmental disease. To understand how external cues direct development, we will elucidate the transcriptional regulatory networks underlying neural development and represent this understanding in predictive computational models. Our studies will begin with undifferentiated embryonic stem (ES) cells, and using protocols that we have pioneered, we will elucidate the mechanism of ES cell development and fate commitment in specific neuron subtypes. Our work is structured into three projects. Project 1 will identify the transcription factors potentially involved in motor neuron identity, iteratively define transcriptional networks, and characterize the transcriptional consequences of SMA. Drawing upon these results, Project 2 will discover how key transcriptional and chromatin regulators control the gene expression programs of mouse and human embryonic stem cells and discover how this regulatory circuitry changes upon differentiation into spinal progenitor cells and then specific classes of central nervous system cells such as motor neurons. Using data from both of these projects, Project 3 will build a model of transcriptional regulation during neural development that integrates expression data, factor binding data, chromatin data, shRNA knock down data, and genome sequence in both human and mouse, examine the gene expression consequences of our SMA model in the context of the deduced regulatory networks, and explore the validity of the mouse model for human ES cell differentiation. Both Project 1 and 2 will test the models produced in Project 3.
我们建议进一步了解在神经发育过程中指导干细胞的分子机制,最终目标是实现基于干细胞的再生医学来治疗神经退行性疾病。我们将研究脊髓性肌萎缩症(SMA)的发病机制, 我们阐明的目标是为这种发育性疾病的潜在治疗靶点提供线索。为了了解外部线索如何指导发展,我们将阐明神经发育的转录调控网络,并在预测计算模型中表示这种理解。我们的研究将开始与未分化的胚胎干细胞(ES),并使用 通过我们开创的实验方案,我们将阐明特定神经元亚型中ES细胞发育和命运承诺的机制。我们的工作分为三个项目。项目1将确定可能参与运动神经元身份的转录因子,迭代定义转录因子, 网络,并表征SMA的转录后果。利用这些结果,项目2将发现关键的转录和染色质调节因子如何控制小鼠和人类胚胎干细胞的基因表达程序,并发现这种调节回路在分化为脊髓祖细胞和特定类别的中枢神经系统细胞(如运动神经元)后如何变化。利用这两个项目的数据,项目3将建立一个神经发育过程中的转录调控模型,该模型整合了人类和小鼠的表达数据、因子结合数据、染色质数据、shRNA敲低数据和基因组序列,在推导的调控网络的背景下检查我们的SMA模型的基因表达结果,探讨小鼠ES细胞分化模型的有效性。项目1和项目2都将测试项目3中生成的模型。

项目成果

期刊论文数量(21)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Mir-17-3p controls spinal neural progenitor patterning by regulating Olig2/Irx3 cross-repressive loop.
  • DOI:
    10.1016/j.neuron.2011.01.014
  • 发表时间:
    2011-02-24
  • 期刊:
  • 影响因子:
    16.2
  • 作者:
    Chen JA;Huang YP;Mazzoni EO;Tan GC;Zavadil J;Wichterle H
  • 通讯作者:
    Wichterle H
Self-Cloning CRISPR.
MicroRNA regulation of neural stem cells and neurogenesis.
Cas9 Functionally Opens Chromatin.
  • DOI:
    10.1371/journal.pone.0152683
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Barkal AA;Srinivasan S;Hashimoto T;Gifford DK;Sherwood RI
  • 通讯作者:
    Sherwood RI
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David K Gifford其他文献

Computational discovery of gene modules and regulatory networks
基因模块和调控网络的计算发现
  • DOI:
    10.1038/nbt890
  • 发表时间:
    2003-10-12
  • 期刊:
  • 影响因子:
    41.700
  • 作者:
    Ziv Bar-Joseph;Georg K Gerber;Tong Ihn Lee;Nicola J Rinaldi;Jane Y Yoo;François Robert;D Benjamin Gordon;Ernest Fraenkel;Tommi S Jaakkola;Richard A Young;David K Gifford
  • 通讯作者:
    David K Gifford

David K Gifford的其他文献

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{{ truncateString('David K Gifford', 18)}}的其他基金

Machine learning optimized autoimmune therapeutics with a focus on Type 1 Diabetes
机器学习优化自身免疫疗法,重点关注 1 型糖尿病
  • 批准号:
    10697204
  • 财政年份:
    2023
  • 资助金额:
    $ 128.52万
  • 项目类别:
Deep learning based antibody design using high-throughput affinity testing of synthetic sequences
使用合成序列的高通量亲和力测试进行基于深度学习的抗体设计
  • 批准号:
    10116306
  • 财政年份:
    2018
  • 资助金额:
    $ 128.52万
  • 项目类别:
Deep learning based antibody design using high-throughput affinity testing of synthetic sequences
使用合成序列的高通量亲和力测试进行基于深度学习的抗体设计
  • 批准号:
    10362725
  • 财政年份:
    2018
  • 资助金额:
    $ 128.52万
  • 项目类别:
High-Throughput Native Context Mapping and Modeling of Regulatory DNA
监管 DNA 的高通量本地上下文映射和建模
  • 批准号:
    9350382
  • 财政年份:
    2016
  • 资助金额:
    $ 128.52万
  • 项目类别:
High-throughput methods for elucidating the control of chromatin accessibility
阐明染色质可及性控制的高通量方法
  • 批准号:
    9066734
  • 财政年份:
    2015
  • 资助金额:
    $ 128.52万
  • 项目类别:
High-throughput methods for elucidating the control of chromatin accessibility
阐明染色质可及性控制的高通量方法
  • 批准号:
    8861021
  • 财政年份:
    2015
  • 资助金额:
    $ 128.52万
  • 项目类别:
High-throughput methods for elucidating the control of chromatin accessibility
阐明染色质可及性控制的高通量方法
  • 批准号:
    9267524
  • 财政年份:
    2015
  • 资助金额:
    $ 128.52万
  • 项目类别:
Integrated Genome Discovery at Single Base Pair Resolution
单碱基对分辨率的综合基因组发现
  • 批准号:
    9041894
  • 财政年份:
    2012
  • 资助金额:
    $ 128.52万
  • 项目类别:
Integrated Genome Discovery at Single Base Pair Resolution
单碱基对分辨率的综合基因组发现
  • 批准号:
    8546274
  • 财政年份:
    2012
  • 资助金额:
    $ 128.52万
  • 项目类别:
Integrated Genome Discovery at Single Base Pair Resolution
单碱基对分辨率的综合基因组发现
  • 批准号:
    8402454
  • 财政年份:
    2012
  • 资助金额:
    $ 128.52万
  • 项目类别:

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