A comparative analysis of genes differentially expressed between rete testis cells and Sertoli cells of the mouse testis.

The rete testis (RT) is a region of the mammalian testis that plays an important role in testicular physiology. The RT epithelium consists of cells sharing some well-known gene markers with supporting Sertoli cells (SCs). However, little is known about the differences in gene expression between these two cell populations. Here, we used fluorescence-activated cell sorting (FACS) to obtain pure cultures of neonatal RT cells and SCs and identified differentially expressed genes (DEGs) between these cell types using RNA sequencing (RNA-seq). We then compared our data with the RNA-seq data of other studies that examined RT cells and SCs of mice of different ages and generated a list of DEGs permanently upregulated in RT cells throughout testis development and in culture, which included 86 genes, and a list of 79 DEGs permanently upregulated in SCs. The analysis of studies on DMRT1 function revealed that nearly half of the permanent DEGs could be regulated by this SC upregulated transcription factor. We suggest that useful cell lineage markers and candidate genes for the specification of both RT cells and SCs may be present among these permanent DEGs.

Complex Analysis of Single-Cell RNA Sequencing Data.

Single-cell RNA sequencing (scRNA-seq) is a revolutionary tool for studying the physiology of normal and pathologically altered tissues. This approach provides information about molecular features (gene expression, mutations, chromatin accessibility, etc.) of cells, opens up the possibility to analyze the trajectories/phylogeny of cell differentiation and cell-cell interactions, and helps in discovery of new cell types and previously unexplored processes. From a clinical point of view, scRNA-seq facilitates deeper and more detailed analysis of molecular mechanisms of diseases and serves as a basis for the development of new preventive, diagnostic, and therapeutic strategies. The review describes different approaches to the analysis of scRNA-seq data, discusses the advantages and disadvantages of bioinformatics tools, provides recommendations and examples of their successful use, and suggests potential directions for improvement. We also emphasize the need for creating new protocols, including multiomics ones, for the preparation of DNA/RNA libraries of single cells with the purpose of more complete understanding of individual cells.