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Developmental CellDevelopmental BiologyPeer-reviewed journal article

Spatiotemporal mapping of gene expression landscapes and developmental trajectories during zebrafish embryogenesis

Chang Xin LiuiD, Rui LiiD, Young Li, Xiumei LiniD, Kaichen Zhao, Qun LiuiD, Shuowen WangiD, Xueqian Yang, Xuyang Shi, Yuting Ma, Chenyu Pei, Hui WangiD, Wendai Bao, Junhou Hui, Tao YangiD, Zhicheng XuiD, Tingting LaiiD, Michael A. Berberoglu, Sunil Kumar SahuiD, Miguel Angel EstebaniD, Kailong MaiD, Guangyi FaniD, Yuxiang LiiD, Shiping LiuiD, Ao CheniD, , Longqi LiuiD

PDFDOIPreprint

Abstract

Vertebrate embryogenesis is a remarkably dynamic process during which numerous cell types of different lineages generate, change, or disappear within a short period of time. A major challenge in understanding this process is the lack of topographical transcriptomic information that can help correlate microenvironmental cues within the hierarchy of cell fate decisions. Here, we employed Stereo-seq, a high-definition spatially resolved transcriptomic technology, to dissect the spatiotemporal dynamics of gene expression and regulatory networks in the developing zebrafish embryos. We profiled 91 embryo sections covering six critical time points during the first 24 hours of development, obtaining a total of 139,391 spots at cellular size ([~]100 m2) with spatial coordinates. Meanwhile, we identified spatial modules and co-varying genes for specific tissue organizations. By performing the integrative analysis of the Stereo-seq and scRNA-seq data from each time point, we reconstructed the spatially resolved developmental trajectories of cell fate transitions and molecular changes during zebrafish embryogenesis. We further investigated the spatial distribution of ligand-receptor pairs for major signaling pathways and identified novel interactions that potentially crosstalk with the Notch signaling pathway during zebrafish development. Our study constitutes a fundamental reference for further studies aiming to understand vertebrate development.

Citations
169
FWCI
11.10
Field percentile
top 1%

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