Geometry, Genetics and Development

几何、遗传学和发育

基本信息

批准号：
2013131
负责人：
Eric Siggia
金额：
$ 89.93万
依托单位：
Rockefeller University
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2025-08-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2013131&HistoricalAwards=false
关键词：
Geometry Genetics Development

项目摘要

Developmental biology has been immensely successful in reducing the seeming miraculous self-organization of a fertilized egg to a fetus and adult to a list of genes and the instructions for their regulation in the noncoding genome. But knowing the parts (essentially all genes) is not commensurate with understanding their capacity to self-organize. Thus, we need to move from reductionism to integration, and physics, particularly condensed matter and statistical physics, has a long and successful history in phenomenological but still quantitative descriptions of Nature. Stem cell technologies allow one to build embryos from cells and thus test one's understanding. New imaging modalities and genetic interventions provide the means to reprogram the earliest steps of development in simple model organisms and quantify the outcomes. Development is about morphogenesis and the progressive specialization of cells as a function of time. The natural mathematical language for dynamics is geometric and the key ideas were formulated in the 20th century. Elements of that work provide a mathematically rigorous landscape analogy to development that enables a very compact phenomenological description that can be fit to data. Prior work by the PI has shown how simply confining stem cells in two dimensions elicits their potential for self-organization, which is surprisingly complex and employs the same cellular communications systems as in the embryo. This project will use the simplicity of synthetic systems and geometrical methods to quantify the genetic systems responsible for self-organization in mammals. Similar mathematical machinery is required to understand recent experiments in the nematode C. elegans that uses RNA interference to reprogram the founder cells in the embryo to new fates. How these new fates accommodate to their ectopic environment provide a strong quantifiable constraint on how the embryo self-organizes and are amenable to phenomenological treatments. The PI will continue to study the exact mutation that leads to Huntington disease in humans, which has a dramatic phenotype in stem cells differentiated on micropatterns.The Waddington landscape is an oft-cited metaphor for development, particularly when discussing stem cells. A theorem of Smale, plausibly applies to the gene regulatory networks as imagined by Waddington and proves that such systems can be represented by potential flow on a Riemannian manifold. The PI will show the utility of this representation in several examples. It is the only general way to implement our intuition that developmental ‘decisions’ take place in a low dimensional space, and it provides a compact functional form with which to challenge that intuition with data, thus reducing the number of dimensions in which the essential degrees of freedom reside, compared to the standard Michaelis-Menten representations of gene regulatory networks, which typically have many more variables than the dimension of the attractor they describe. The PI's experimental collaborations in stem cells and C.elegans development will provide the means to apply these theoretical representations to data.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

发育生物学在减少胎儿和成人的奇迹般的自我组织中取得了巨大成功，并在非编码基因组中调节其调节的指令。但是，了解部分（本质上是所有基因）与了解它们的自我组织能力并不相称。这就是我们需要从还原主义转变为整合，物理学，尤其是凝结的物理和统计物理学，在现象学方面具有悠久而成功的历史，但仍然对自然的定量描述。干细胞技术允许人们从细胞中构建胚胎，从而测试自己的理解。新的成像方式和遗传干预措施提供了在简单模型生物体中重新编程最早发展步骤并量化结果的手段。发展是关于形态发生和细胞随时间的促进性专业化的。动力学的自然数学语言是几何形状，关键思想是在20世纪提出的。该工作的元素提供了与开发的数学严格景观类比，该景观类比可以使非常紧凑的现象学描述适合数据。 PI的先前工作表明，如何简单地将干细胞限制在二维中引起其自我组织的潜力，这非常复杂，并采用了与胚胎中相同的细胞通信系统。该项目将使用合成系统和几何方法的简单性来量化负责哺乳动物自组织的遗传系统。需要类似的数学机制来了解线虫秀丽隐杆线虫中的最新实验，该实验使用RNA干扰重新编程了胚胎中的创始人细胞到新命运。这些新命运如何适应其生态环境，对胚胎如何自组织和适合现象学治疗的胚胎如何自行限制。 PI将继续研究导致人类亨廷顿疾病的确切突变，该突变在人类的干细胞中具有戏剧性的表型。Waddington景观是经常引用的发育隐喻，尤其是在讨论干细胞时。 Smale定理，合理地适用于Waddington想象的基因调节网络，并证明了这种系统可以通过Riemannian歧管上的潜在流动来表示。 PI将在几个示例中显示该表示的实用性。实施我们的直觉是唯一的一般方法，发展性的“决策”是在低维空间中进行的，并且提供了一种紧凑的功能形式，可以通过数据来挑战直觉，从而减少了与基因监管网络的标准迈克尔·梅恩斯（Michaelis-Membern）表示相比，与之相比，自由度的基本维度的数量均与更多的差异相比，这些维度均涉及的范围。 PI在干细胞和C.Elegans开发方面的实验合作将提供将这些理论表述应用于数据的手段。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子和更广泛的影响评估审查标准来通过评估来表现出珍贵的支持。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Geometry of gene regulatory dynamics

DOI：
10.1073/pnas.2109729118
发表时间：
2021-09-21
期刊：
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
影响因子：
11.1
作者：
Rand, David A.;Raju, Archishman;Siggia, Eric D.
通讯作者：
Siggia, Eric D.

Mechanical regulation of early vertebrate embryogenesis