Abstract
Spermatogenesis is a complex process of cellular division and differentiation that begins with spermatogonia stem cells and leads to functional spermatozoa production. However, many of the molecular mechanisms underlying this process remain unclear. Single-cell RNA sequencing (scRNA-seq) is used to sequence the entire transcriptome at the single-cell level to assess cell-to-cell variability. In this study, more than 33,000 testicular cells from different scRNA-seq datasets with normal spermatogenesis were integrated to identify single-cell heterogeneity on a more comprehensive scale. Clustering, cell type assignments, differential expressed genes and pseudotime analysis characterized 5 spermatogonia, 4 spermatocyte, and 4 spermatid cell types during the spermatogenesis process. The UTF1 and ID4 genes were introduced as the most specific markers that can differentiate two undifferentiated spermatogonia stem cell sub-cellules. The C7orf61 and TNP can differentiate two round spermatid sub-cellules. The topological analysis of the weighted gene co-expression network along with the integrated scRNA-seq data revealed some bridge genes between spermatogenesis’s main stages such as DNAJC5B, C1orf194, HSP90AB1, BST2, EEF1A1, CRISP2, PTMS, NFKBIA, CDKN3, and HLA-DRA. The importance of these key genes is confirmed by their role in male infertility in previous studies. It can be stated that, this integrated scRNA-seq of spermatogenic cells offers novel insights into cell-to-cell heterogeneity and suggests a list of key players with a pivotal role in male infertility from the fertile spermatogenesis datasets. These key functional genes can be introduced as candidates for filtering and prioritizing genotype-to-phenotype association in male infertility.
Highlights
Spermatogenesis is a complex process of cellular division and differentiation that begins with spermatogonia stem cells and leads to functional spermatozoa production
The diverse human spermatogenesis scRNA-seq datasets, including spermatogonia, spermatocyte, spermatid sorted cells, and steady-state spermatogenic cells were collected from the gene expression omnibus (GEO) database
We integrated diverse scRNA-seq datasets of more than 33,000 testicular cells, to identify pure and comprehensive cell profiles for spermatogenesis. Some of these datasets were retrieved from Hermann et al study[22], which contains the steady-state of spermatogenesis and three sorted spermatogenic cell types that are not integrated
Summary
Spermatogenesis is a complex process of cellular division and differentiation that begins with spermatogonia stem cells and leads to functional spermatozoa production. The topological analysis of the weighted gene co-expression network along with the integrated scRNA-seq data revealed some bridge genes between spermatogenesis’s main stages such as DNAJC5B, C1orf[194], HSP90AB1, BST2, EEF1A1, CRISP2, PTMS, NFKBIA, CDKN3, and HLA-DRA The importance of these key genes is confirmed by their role in male infertility in previous studies. Gene expression profiling assays, such as typical microarray or RNA-sequencing (RNA-seq) have been widely used to investigate the changes in testicular gene expression from birth to adulthood[11,12,13,14], and in the molecular mechanisms involved in male infertility[15,16] These studies rely on the bulk RNA analysis of mixed aggregates of spermatogenic cells, that provide the average expression signal for a pool of different cell types[17,18]. These methods can only separate some types of spermatogenic cells and cannot isolate high-purity homogeneous spermatogenic cells from all types[10,20]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
