Emergent dynamics of adult stem cell lineages from single nucleus and single cell RNA-Seq of Drosophila testes

Raz, Amelie A, Vida, Gabriela S, Stern, Sarah R, Mahadevaraju, Sharvani, Fingerhut, Jaclyn M, Viveiros, Jennifer M, Pal, Soumitra, Grey, Jasmine R, Grace, Mara R, Berry, Cameron W, Li, Hongjie, Janssens, Jasper, Saelens, Wouter, Shao, Zhantao, Hu, Chun, Yamshita, Yukiko M, Przytycka, Teresa, Oliver, Brian, Brill, Julie A, Krause, Henry, Matunis, Erika L, White-Cooper, Helen ORCID: https://orcid.org/0000-0002-3373-8023, DiNardo, Stephen and Fuller, Margaret T 2023. Emergent dynamics of adult stem cell lineages from single nucleus and single cell RNA-Seq of Drosophila testes. eLife 12 , e82201. 10.7554/elife.82201

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Abstract

Proper differentiation of sperm from germline stem cells, essential for production of the next generation, requires dramatic changes in gene expression that drive remodeling of almost all cellular components, from chromatin to organelles to cell shape itself. Here, we provide a single nucleus and single cell RNA-seq resource covering all of spermatogenesis in Drosophila starting from in-depth analysis of adult testis single nucleus RNA-seq (snRNA-seq) data from the Fly Cell Atlas (FCA) study. With over 44,000 nuclei and 6000 cells analyzed, the data provide identification of rare cell types, mapping of intermediate steps in differentiation, and the potential to identify new factors impacting fertility or controlling differentiation of germline and supporting somatic cells. We justify assignment of key germline and somatic cell types using combinations of known markers, in situ hybridization, and analysis of extant protein traps. Comparison of single cell and single nucleus datasets proved particularly revealing of dynamic developmental transitions in germline differentiation. To complement the web-based portals for data analysis hosted by the FCA, we provide datasets compatible with commonly used software such as Seurat and Monocle. The foundation provided here will enable communities studying spermatogenesis to interrogate the datasets to identify candidate genes to test for function in vivo.

Item Type:	Article
Date Type:	Published Online
Status:	Published
Schools:	Biosciences
Additional Information:	License information from Publisher: LICENSE 1: URL: http://creativecommons.org/publicdomain/zero/1.0/
Publisher:	eLife Sciences Publications
Date of First Compliant Deposit:	17 February 2023
Date of Acceptance:	19 January 2023
Last Modified:	11 Oct 2023 18:31
URI:	https://orca.cardiff.ac.uk/id/eprint/157106

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