Single-cyst transcriptome analysis of Drosophila male germline stem cell lineage.
Zhen ShiCindy LimVuong TranKairong CuiKeji ZhaoXin ChenPublished in: Development (Cambridge, England) (2020)
The Drosophila male germline stem cell (GSC) lineage provides a great model to understand stem cell maintenance, proliferation, differentiation and dedifferentiation. Here, we use the Drosophila GSC lineage to systematically analyze the transcriptome of discrete but continuously differentiating germline cysts. We first isolated single cysts at each recognizable stage from wild-type testes, which were subsequently applied for RNA-seq analyses. Our data delineate a high-resolution transcriptome atlas in the entire male GSC lineage: the most dramatic switch occurs from early to late spermatocyte, followed by the change from the mitotic spermatogonia to early meiotic spermatocyte. By contrast, the transit-amplifying spermatogonia cysts display similar transcriptomes, suggesting common molecular features among these stages, which may underlie their similar behavior during both differentiation and dedifferentiation processes. Finally, distinct differentiating germ cell cyst samples do not exhibit obvious dosage compensation of X-chromosomal genes, even considering the paucity of X-chromosomal gene expression during meiosis, which is different from somatic cells. Together, our single cyst-resolution, genome-wide transcriptional profile analyses provide an unprecedented resource to understand many questions in both germ cell biology and stem cell biology fields.
Keyphrases
- single cell
- stem cells
- rna seq
- germ cell
- genome wide
- gene expression
- copy number
- dna methylation
- high resolution
- wild type
- dna repair
- cell therapy
- contrast enhanced
- induced apoptosis
- magnetic resonance
- signaling pathway
- transcription factor
- magnetic resonance imaging
- mass spectrometry
- single molecule
- cell cycle arrest
- bone marrow
- computed tomography
- mesenchymal stem cells
- oxidative stress
- cell death
- machine learning
- dna damage
- big data
- electronic health record
- deep learning
- heat stress
- data analysis
- high speed