bioRxivDevelopmental BiologyPreprint
A single-cell 3D spatiotemporal multi-omics atlas from Drosophila embryogenesis to metamorphosis
Mingyue WangiD, Qinan HuiD, Zhencheng TuiD, Lingshi Kong, Jiajun YaoiD, Rong XiangiD, Zhan CheniD, Yan ZhaoiD, Yanfei Zhou, Tengxiang Yu, Yuetian Wang, Zihan JiaiD, Kang Ouyang, Xianzhe WangiD, Yinqi BaiiD, Mingwei LianiD, Zhenyu YangiD, Tao YangiD, Jing CheniD, Yunting Huang, Ni Yin, Wenyuan Mo, Wenfu Liang, Chang LiuiD, Xiumei LiniD, , Yuhui HuiD
Abstract
The development of a multicellular organism is a highly intricate process tightly regulated by numerous genes and pathways in both spatial and temporal manners. Here, we present Flysta3D, a comprehensive multi-omics atlas of the model organism Drosophila, spanning its developmental lifespan from embryo to pupa. Our datasets encompass 3D single-cell spatial transcriptomic, single-cell transcriptomic, and single-cell chromatin accessibility information. By integrating these multi-dimensional data, we constructed cell state trajectories that uncover the detailed profiles of tissue development. With a focus on the central nervous system (CNS) and midgut, we dissected the spatiotemporal dynamics of gene regulatory networks, cell type diversity, and morphological changes from a multi-omics perspective. This extensive atlas provides an unprecedentedly rich resource and serves as a systematic platform for studying Drosophila development with integrated single-cell data at an ultra-high spatiotemporal resolution.
- organism: Drosophila
- assay: spatial transcriptomics
- assay: scRNA-seq
- assay: scATAC-seq
- research focus: trajectory inference
- research focus: gene regulatory network inference
- research focus: cell type annotation
- approach: statistical model
- approach: machine learning (classical)
- Citations
- 4
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