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

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.

LSMMD-MA：用于单细胞基因组学数据分析的多模式数据集成。

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