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Identifying regulators of morphogenesis with a transcriptional lineage of C. elegans development

Identifying regulators of morphogenesis with a transcriptional lineage of C. elegans development
鉴定形态发生的调节因子与秀丽隐杆线虫发育的转录谱系
批准号:
9208057
负责人:
Sophia Tintori
金额:
$3.44万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-01-06 至 2017-12-31

项目摘要

项目成果

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中文摘要
翻译
 描述(申请人提供):形态发生,即细胞在胚胎中移动以形成身体的形状和结构的过程,对多细胞生命周期至关重要。它的错误调控导致了一系列疾病,包括出生缺陷、癌症转移和伤口愈合不当。基因筛选对于识别参与这些过程的基因至关重要,但传统的基因筛选对大类基因视而不见,例如那些与其他途径具有部分冗余功能的基因,以及多效性基因。基因表达谱技术,如rna-seq,通过获取每个基因的转录水平的快照来揭示这些盲点,无论它是否是多效性的。 或部分冗余。我假设,有一些尚未发现的多效性或部分冗余基因,以及一些只是通过遗传学方法尚未发现的基因,它们对形态发生至关重要,并将通过RNA-SEQ揭示。自从描述线虫发育的不变细胞谱系以来,线虫一直是一个强大的胚胎学工具,使研究人员能够准确预测感兴趣的事件将在何时何地发生。在单个细胞的空间分辨率和分钟的时间分辨率下,可以预测神经元指定、细胞凋亡、极化细胞分裂或细胞迁移等现象。但这种细胞谱系并没有直接解决这些现象是如何发生的,以及哪些基因对此负责。单细胞RNA-seq使我们能够描述这些细胞在整个发育过程中的转录水平,以识别与已有充分记录的发育现象相关的基因。我将对线虫胚胎的每个单独细胞进行单细胞RNA-SEQ,直到16细胞阶段,从而创建一个分子谱系来补充已知的细胞发育谱系。很难确定形态发生的调节因子,这在很大程度上是由于这些基因往往具有多效性或部分冗余的功能。我将分析各种原肠形成细胞随着时间的推移而导致原肠形成的转录本。我假设,当每种细胞类型启动原肠形成时,存在其在不同细胞类型中表达相关的基因,并且这些基因在调节形态发生方面具有功能作用。该项目的主要贡献之一将是转录谱系,它将作为细胞和 发育生物学家。为了保证这一资源的实用性,我将编写一个交互式数据可视化Web工具。该工具将允许用户通过可视化方式查询我的数据 描述感兴趣的时空表达模式,并接收关于与所述模式匹配的所有基因的信息。这一工具将弥合计算生物学家和非计算生物学家之间的沟通鸿沟。虽然这些数据将与发育和细胞生物学中的许多问题相关,但我将使用它们来生成关于形态发生调控的假设,然后我将在原肠线虫中进行测试。
英文摘要
 DESCRIPTION (provided by applicant): Morphogenesis, the process by which cells move through the embryo to form the shapes and structures of the body, is critical for multicellular lif. Its misregulation leads to a wide range of diseases including birth defects, cancer metastasis and improper wound healing. Genetic screens have been crucial for identifying genes involved in these processes, but traditional genetic screens are blind to large categories of genes, such as those that have a partially redundant function with other pathways, as well as pleiotropic genes. Gene expression profiling techniques such as RNA-seq shed light on these blind spots by taking a snapshot of the transcript level of every gene, regardless of whether it is pleiotropic or partially redundant. I hypothesize that there are undiscovered pleiotropic or partially redundant genes, as well as genes simply not yet found by genetic approaches, that are critical to morphogenesis and which will be revealed by RNA-seq. Ever since the description of the invariant cell lineage of C. elegans development, the nematode has been a powerful embryological tool, allowing researchers to predict exactly when and where an event of interest will take place. Phenomena such as neuron specification, apoptosis, polarized cell division, or cell migration can be anticipated with a spatial resolution of a single cell, and a temporal resolution of minutes. But this cell lineage does not directly address how these phenomena are taking place, and what genes are responsible. Single-cell RNA-seq allows us to profile transcripts levels from each of these cells throughout development, to identify genes that correlate with the well-documented phenomena of development. I will perform single-cell RNA-seq on each individual cell of the C. elegans embryo until the 16-cell stage, thereby creating a molecular lineage to complement the known cellular lineage of development. Regulators of morphogenesis have been difficult to identify, in large part due to the often pleiotropic or partialy redundant functions of these genes. I will analyze the transcriptomes of a variety of gastrulating cell types over time leading up to gastrulation. I hypothesize that there are genes whose expression correlates across cell types as each cell type initiates gastrulation, and that these genes have functional roles in regulating morphogenesis. One of the main contributions of this project will be the transcriptional lineage, which will be made available as a resource to cell and developmental biologists. In order to ensure the utility of this resource, I will program an interactive data visualization web tool. This tool will allow the user to query my data by visually describing a spatiotemporal expression pattern of interest, and receiving information about all the genes that match the described pattern. This tool will bridge a communication gap between computational and non-computational biologists. While these data will be relevant to many questions in developmental and cell biology, I will use them to generate hypotheses about the regulation of morphogenesis, which I will then test in the gastrulating nematode.
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