Abstract

Male gametes are generated through a specialised differentiation pathway involving a series of developmental transitions that are poorly characterised at the molecular level. Here, we use droplet-based single-cell RNA-Sequencing to profile spermatogenesis in adult animals and at multiple stages during juvenile development. By exploiting the first wave of spermatogenesis, we both precisely stage germ cell development and enrich for rare somatic cell-types and spermatogonia. To capture the full complexity of spermatogenesis including cells that have low transcriptional activity, we apply a statistical tool that identifies previously uncharacterised populations of leptotene and zygotene spermatocytes. Focusing on post-meiotic events, we characterise the temporal dynamics of X chromosome re-activation and profile the associated chromatin state using CUT&RUN. This identifies a set of genes strongly repressed by H3K9me3 in spermatocytes, which then undergo extensive chromatin remodelling post-meiosis, thus acquiring an active chromatin state and spermatid-specific expression.

The transcriptional regulation of murine spermatogenesis is not well understood. Here, the authors use single-cell and bulk RNA-Sequencing of juvenile and adult mice to characterise somatic and germ cell development, and chromatin profile the X chromosome to show that spermatid-specific genes are repressed by H3K9me3 during meiosis.

Details

Title
Staged developmental mapping and X chromosome transcriptional dynamics during mouse spermatogenesis
Author
Ernst, Christina 1 ; Eling Nils 1 ; Martinez-Jimenez, Celia P 2   VIAFID ORCID Logo  ; Marioni, John C 3   VIAFID ORCID Logo  ; Odom, Duncan T 4   VIAFID ORCID Logo 

 European Bioinformatics Institute, (EMBL-EBI), Wellcome Genome Campus, European Molecular Biology Laboratory, Hinxton, Cambridge, UK (GRID:grid.225360.0) (ISNI:0000 0000 9709 7726); University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK (GRID:grid.470869.4) (ISNI:0000 0004 0634 2060) 
 University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK (GRID:grid.470869.4) (ISNI:0000 0004 0634 2060); Wellcome Sanger Institute, Welcome Genome Campus, Hinxton, Cambridge, UK (GRID:grid.10306.34) (ISNI:0000 0004 0606 5382) 
 European Bioinformatics Institute, (EMBL-EBI), Wellcome Genome Campus, European Molecular Biology Laboratory, Hinxton, Cambridge, UK (GRID:grid.225360.0) (ISNI:0000 0000 9709 7726); University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK (GRID:grid.470869.4) (ISNI:0000 0004 0634 2060); Wellcome Sanger Institute, Welcome Genome Campus, Hinxton, Cambridge, UK (GRID:grid.10306.34) (ISNI:0000 0004 0606 5382) 
 University of Cambridge, Cancer Research UK Cambridge Institute, Robinson Way, Cambridge, UK (GRID:grid.470869.4) (ISNI:0000 0004 0634 2060); German Cancer Research Center (DKFZ), Division Signaling and Functional Genomics, Heidelberg, Germany (GRID:grid.7497.d) (ISNI:0000 0004 0492 0584) 
Publication year
2019
Publication date
Dec 2019
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2194117772
Copyright
This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.