Single-cell transcriptomics illuminates regulatory steps driving anterior-posterior patterning of Drosophila embryonic mesoderm

Creators: Sun, Jingjing; Zhang, Chen; Gao, Fan¹; Stathopoulos, Angelike¹

1. California Institute of Technology

Abstract

Single-cell technologies promise to uncover how transcriptional programs orchestrate complex processes during embryogenesis. Here, we apply a combination of single-cell technology and genetic analysis to investigate the dynamic transcriptional changes associated with Drosophila embryo morphogenesis at gastrulation. Our dataset encompassing the blastoderm-to-gastrula transition provides a comprehensive single-cell map of gene expression across cell lineages validated by genetic analysis. Subclustering and trajectory analyses revealed a surprising stepwise progression in patterning to transition zygotic gene expression and specify germ layers as well as uncovered an early role for ecdysone signaling in epithelial-to-mesenchymal transition in the mesoderm. We also show multipotent progenitors arise prior to gastrulation by analyzing the transcription trajectory of caudal mesoderm cells, including a derivative that ultimately incorporates into visceral muscles of the midgut and hindgut. This study provides a rich resource of gastrulation and elucidates spatially regulated temporal transitions of transcription states during the process.

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Acknowledgement

We are grateful to Deborah Andrew, Lauren Anllo, Peter Gergen, and Michael O'Connor for sharing fly stocks and antibodies; Siyu Chen and Jeff Park of Caltech SPEC, Michael O'Connor, Frank Macabenta, and Vince Stepanik for helpful discussions and technical support; and Isaryhia Rodriguez and Life Science Editors for comments on the manuscript. This study was supported by funding from National Institutes of Health grants R35GM118146 and R01HD100189 to A.S,

Contributions

A.S. and J.S. conceived the project. J.S. planned the experimental approach. A.S. directed the project. J.S. performed all experiments and F.G. performed the computational work. J.S., C.Z. and F.G. analyzed the data with input from A.S. The manuscript was written by J.S. and A.S. with input from F.G. and C.Z.

Data Availability

The raw sc-RNA sequencing data generated in this study has been submitted to NCBI database (https://www.ncbi.nlm.nih.gov/geo/) and is available under accession number GEO: GSE222660
A github repository was generated and publicly available with the analysis codes for all datasets (https://github.com/StathopoulosLab/Single_Cell_RNAseq_Analysis_supplementary or https://zenodo.org/badge/latestdoi/668423939)
Additional Rds objects, R script and installation instructions for visualizing RNA sequencing UMAP graphs are deposited into Mendeley Data Respository (Mendeley data: https://doi.org/10.17632/s25d8y9pvz.1)
Any additional information required to reanalyze the data shown in this paper is available from the lead contact upon request.

Conflict of Interest

The authors declare no competing interests.

Additional Information

We support inclusive, diverse, and equitable conduct of research.

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