UW 4-Dimensional Genomic Organization of Mammalian Embryogenesis Center

威斯康星大学哺乳动物胚胎发生中心 4 维基因组组织

• 批准号: 10885341
• 负责人: Christine M. Disteche
• 金额: $ 15.16万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-18 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10885341
• 关键词: Architecture; Atlases; Cell Line; Cell Separation; Cells; Chromatin; Communities; Data; Data Set; Development; Disease; Embryonic Development; Emerging Technologies; Four-dimensional; Gene Expression; Generations; Genes; Genome; Genomics; Goals; Image; In Vitro; Malignant Neoplasms; Mammalian Cell; Maps; Measurement; Methods; Modeling; Molecular; Morphology; Mus; Mutation; Nuclear; Nuclear Structure; Pathway interactions; Resolution; Shapes; System; Tissues; Universities; Visual; Visualization; Washington; Whole Organism; cell type; human data; in vivo; machine learning model; model organism; mouse model

Project Summary / Abstract A major shortcoming of most efforts to understand the 4D nucleome is that they have mainly focused on in vitro cell lines, rather than on dynamic, in vivo systems. Arguably, the most important in vivo system, which also happens to be the most dynamic, is development itself, wherein the nucleome both shapes and is shaped by the initial emergence of the myriad mammalian cell types. While these in vivo dynamics are presently poorly documented and understood, recently emerged technologies offer a path forward. Here we propose to establish the University of Washington 4-Dimensional Genomic Nuclear Organization of Mammalian Embryogenesis Center (UW 4D GENOME Center), which will address these massive gaps in our understanding by generating systematic datasets on nuclear morphology and associated molecular measurements in mammalian tissues and cell types. These datasets will be generated in the context of the leading model organism for mammalian development, the mouse. Our approach focuses on following nuclear structure, chromatin and gene expression changes at a “whole organism” scale, using a combination of scalable single cell profiling and “visual cell sorting” (VCS) methods, all well-established and mostly developed in our own labs. Our goal is to generate a high- resolution 4DN atlas of mouse embryogenesis for the community. The different types of data will be integrated, including cross-species imputation to integrate with human data, as well as models and navigable maps applied to pathways relevant to mammalian development.

项目摘要 /摘要 了解4D核心的大多数努力的主要缺点是，它们主要集中于体外 细胞系，而不是动态的体内系统。可以说是最重要的体内系统，也是 恰好是最动态的，是发育本身，其中核心既形状又由 无数哺乳动物细胞类型的最初出现。尽管这些体内动力学的呈现很差 有记录和理解，最近出现的技术提供了前进的道路。在这里我们建议建立 华盛顿大学哺乳动物胚胎发生的4维基因组核组织 中心（UW 4D基因组中心），该中心将通过产生我们的理解中的这些巨大差距 哺乳动物组织中的核形态和相关分子测量的系统数据集和 细胞类型。这些数据集将在哺乳动物的领先模型有机体的背景下生成 开发，鼠标。我们的方法着重于遵循核结构，染色质和基因表达 使用可扩展的单细胞分析和“视觉细胞分类”的组合，在“整个生物体”量表上变化 （VCS）方法，所有这些方法都建立了良好，并且主要在我们自己的实验室中开发。我们的目标是产生高 小鼠胚胎发生的第4DN图集针对社区。不同类型的数据将集成， 包括插入跨物种以与人类数据集成，以及应用模型和可通道的地图 到与哺乳动物发展有关的途径。

项目成果

Multimodal Single-Cell Translation and Alignment with Semi-Supervised Learning.

多模式单细胞翻译和半监督学习比对。

• DOI: 10.1089/cmb.2022.0264
• 发表时间: 2022
• 期刊: Journal of computational biology : a journal of computational molecular cell biology
• 作者: Zhang,Ran;Meng-Papaxanthos,Laetitia;Vert,Jean-Philippe;Noble,WilliamStafford
• 通讯作者: Noble,WilliamStafford

Induction and in silico staging of human gastruloids with neural tube, segmented somites & advanced cell types.

具有神经管、分段体节的人类原肠胚的诱导和计算机分期

• DOI: 10.1101/2024.02.10.579769
• 发表时间: 2024
• 期刊: bioRxiv : the preprint server for biology
• 作者: Hamazaki,Nobuhiko;Yang,Wei;Kubo,Connor;Qiu,Chengxiang;Martin,BethK;Garge,RiddhimanK;Regalado,SamuelG;Nichols,Eva;Lee,Choli;Daza,RizaM;Srivatsan,Sanjay;Shendure,Jay
• 通讯作者: Shendure,Jay

Inference of 3D genome architecture by modeling overdispersion of Hi-C data.

• DOI: 10.1093/bioinformatics/btac838
• 发表时间: 2023-01-01
• 期刊: Bioinformatics (Oxford, England)

LSMMD-MA: scaling multimodal data integration for single-cell genomics data analysis.

• DOI: 10.1093/bioinformatics/btad420
• 发表时间: 2023-07-01
• 期刊: Bioinformatics (Oxford, England)