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Gene regulatory network controlling neural crest derived formation of facial cartilage

Gene regulatory network controlling neural crest derived formation of facial cartilage
控制面部软骨神经嵴衍生形成的基因调控网络
批准号:
10358599
负责人:
Marianne Bronner
金额:
$37.91万
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:
未结题
起止时间:
2014-06-01 至 2026-03-31

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中文摘要
翻译
在之前的资助期间,我们探索了颅神经脊和躯干神经脊之间的调节差异。 细胞。比较转录组学结合功能紊乱揭示了一种迁徙前的“头颅特异性”。 神经脊GRN亚路,将前向特性与分化为面部软骨的能力联系起来。在这里,我们 建议阐明这一颅脑特异性亚回路下游的基因调控网络(GRN) 这赋予了区分成面部骨骼的能力。目标是了解潜在的计划 颅面软骨的分化和形态形成。首先,我们将探索干线的监管变化 神经脊细胞导入颅脊亚回路基因后。接下来,我们将描述迁徙较晚的人 在单个细胞水平上凝聚成面软骨的颅顶细胞以了解GRN的变化 作为时间的函数,在单个细胞分辨率和功能水平上。最后,我们建议将活跃的 体内联合促进剂及其对晚期迁移和凝聚颅顶细胞的直接输入 用高通量基因组方法在鸡胚胎中构建报告基因的电穿孔。对这些人 最后,我们将实现以下目标: 具体目标1:“重新编程”主干神经脊细胞特性的影响。颅骨异位表达 CREST亚电路基因使主干CREST细胞在移植到头部后具有软骨形成潜力。在这里我们 威尔:描述重新编程的树冠细胞随着时间的推移而发生的转录变化;测试这种能力 在正常环境中重新编程的躯干神经脊来形成异位软骨;测试 颅亚回路赋予ES细胞和眼球来源细胞成软骨的能力。 具体目标2:浓缩颅神经脊的转录图谱和功能验证 使用单细胞rna-seq和多重原位杂交获得高细胞分辨率的细胞。为了获得 深入了解神经沟来源的细胞如何分化以及哪些基因调控程序控制它们的 对于面部骨骼,我们建议对浓缩的颅骨细胞进行单细胞RNA-SEQ。 颧弓的目的是确定软骨形成模块的候选GRN组件。 我们将在高分辨率下验证候选转录因子的表达,并使用 CRISPR-Cas9淘汰赛。 具体目的3:通过鉴定顺式软骨基因构建颅骨软骨基因调控网络。 调节元件和直接下游靶点的颅脊特异性亚电路基因。在……里面 为了在颧弓神经脊中建立调节联系,我们将描述它们的染色质景观。 使用低输入转座酶可及染色质测定法(ATAC-SEQ)优化至1500个细胞 PER复制并执行切割和运行,以确认亚电路基因下游的直接输入。
英文摘要
In the previous grant period, we explored regulatory differences between cranial and trunk neural crest cells. Comparative transcriptomics coupled with functional perturbation revealed a premigratory “cranial-specific” neural crest GRN subcircuit that links anterior identity to ability to differentiate into facial cartilage. Here, we propose to elucidate the gene regulatory network (GRN) downstream of this cranial-specific subcircuit that confers ability to differentiate into facial skeleton. The goal is to understand the program underlying differentiation and pattern formation of craniofacial cartilage. First, we will explore regulatory changes in trunk neural crest cells after introduction of cranial crest subcircuit genes. Next, we will characterize late-migrating cranial crest cells as they condense to form facial cartilage at the single cell level to understand GRN changes as a function of time, at single cell resolution and a functional level. Finally, we propose to identify active enhancers and their direct inputs in late migrating and condensing cranial crest cells by combining in vivo electroporation of reporter constructs in the chick embryo with high throughput genomic approaches. To these ends, we will conduct the following aims: Specific Aim 1: Effects of “reprogramming” trunk neural crest cell identity. Ectopic expression of cranial crest subcircuit genes imbues trunk crest cells with chondrogenic potential after grafting to the head. Here we will: characterize transcriptional changes that occur in reprogrammed trunk crest cells over time; test the ability of reprogrammed trunk neural crest to form ectopic cartilage in their normal environment; test the ability of the cranial subcircuit to confer chondrogenic ability onto ES cells and crestosphere-derived cells. Specific Aim 2: Transcriptional profiling and functional validation of condensing cranial neural crest cells at high cell resolution using single cell RNA-seq and multiplex in situ hybridization. To gain insights into how neural crest-derived cells differentiate and what gene regulatory programs control their progression to facial skeleton, we propose to perform single cell RNA-seq of condensing cranial crest cells in the branchial arches with the goal of identifying candidate GRN components of the cartilage-forming module. We will validate expression of candidate transcription factors at high resolution and test their function using CRISPR-Cas9 knockout. Specific Aim 3: Construction of a cranial cartilage gene regulatory network (GRN) by identifying cis- regulatory elements and direct downstream targets of the cranial crest-specific subcircuit genes. In order to build regulatory linkages in branchial arch neural crest, we will characterize their chromatin landscape using low-input Assay for Transposase-Accessible Chromatin (ATAC-seq) optimized for as few as 1500 cells per replicate and perform CUT&RUN to confirm direct inputs downstream of subcircuit genes.
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