Literature DB >> 35512700

High-resolution 3D spatiotemporal transcriptomic maps of developing Drosophila embryos and larvae.

Mingyue Wang1, Qinan Hu2, Tianhang Lv3, Yuhang Wang4, Qing Lan5, Rong Xiang5, Zhencheng Tu3, Yanrong Wei6, Kai Han7, Chang Shi5, Junfu Guo5, Chao Liu5, Tao Yang8, Wensi Du8, Yanru An5, Mengnan Cheng3, Jiangshan Xu3, Haorong Lu9, Wangsheng Li8, Shaofang Zhang8, Ao Chen5, Wei Chen10, Yuxiang Li11, Xiaoshan Wang12, Xun Xu13, Yuhui Hu14, Longqi Liu15.   

Abstract

Drosophila has long been a successful model organism in multiple biomedical fields. Spatial gene expression patterns are critical for the understanding of complex pathways and interactions, whereas temporal gene expression changes are vital for studying highly dynamic physiological activities. Systematic studies in Drosophila are still impeded by the lack of spatiotemporal transcriptomic information. Here, utilizing spatial enhanced resolution omics-sequencing (Stereo-seq), we dissected the spatiotemporal transcriptomic changes of developing Drosophila with high resolution and sensitivity. We demonstrated that Stereo-seq data can be used for the 3D reconstruction of the spatial transcriptomes of Drosophila embryos and larvae. With these 3D models, we identified functional subregions in embryonic and larval midguts, uncovered spatial cell state dynamics of larval testis, and revealed known and potential regulons of transcription factors within their topographic background. Our data provide the Drosophila research community with useful resources of organism-wide spatiotemporally resolved transcriptomic information across developmental stages.
Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Drosophila development; Stereo-seq; gene regulatory networks; spatial transcriptomics

Mesh:

Substances:

Year:  2022        PMID: 35512700     DOI: 10.1016/j.devcel.2022.04.006

Source DB:  PubMed          Journal:  Dev Cell        ISSN: 1534-5807            Impact factor:   12.270


  5 in total

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Authors:  Michael Eisenstein
Journal:  Nature       Date:  2022-06       Impact factor: 49.962

Review 2.  The emerging landscape of spatial profiling technologies.

Authors:  Jeffrey R Moffitt; Emma Lundberg; Holger Heyn
Journal:  Nat Rev Genet       Date:  2022-07-20       Impact factor: 59.581

Review 3.  Transcriptome-scale methods for uncovering subcellular RNA localization mechanisms.

Authors:  J Matthew Taliaferro
Journal:  Biochim Biophys Acta Mol Cell Res       Date:  2022-01-06       Impact factor: 5.011

Review 4.  Computational solutions for spatial transcriptomics.

Authors:  Iivari Kleino; Paulina Frolovaitė; Tomi Suomi; Laura L Elo
Journal:  Comput Struct Biotechnol J       Date:  2022-09-01       Impact factor: 6.155

5.  The continuum of Drosophila embryonic development at single-cell resolution.

Authors:  Diego Calderon; Ronnie Blecher-Gonen; Xingfan Huang; Stefano Secchia; James Kentro; Riza M Daza; Beth Martin; Alessandro Dulja; Christoph Schaub; Cole Trapnell; Erica Larschan; Kate M O'Connor-Giles; Eileen E M Furlong; Jay Shendure
Journal:  Science       Date:  2022-08-05       Impact factor: 63.714

  5 in total

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