Single-cell transcriptome analysis of endometrial tissue

Abstract STUDY QUESTION How can we study the full transcriptome of endometrial stromal and epithelial cells at the single-cell level? SUMMARY ANSWER By compiling and developing novel analytical tools for biopsy, tissue cryopreservation and disaggregation, single-cell sorting, library preparation, RNA sequencing (RNA-seq) and statistical data analysis. WHAT IS KNOWN ALREADY Although single-cell transcriptome analyses from various biopsied tissues have been published recently, corresponding protocols for human endometrium have not been described. STUDY DESIGN, SIZE, DURATION The frozen-thawed endometrial biopsies were fluorescence-activated cell sorted (FACS) to distinguish CD13-positive stromal and CD9-positive epithelial cells and single-cell transcriptome analysis performed from biopsied tissues without culturing the cells. We studied gene transcription, applying a modern and efficient RNA-seq protocol. In parallel, endometrial stromal cells were cultured and global expression profiles were compared with uncultured cells. PARTICIPANTS/MATERIALS, SETTING, METHODS For method validation, we used two endometrial biopsies, one from mid-secretory phase (Day 21, LH+8) and another from late-secretory phase (Day 25). The samples underwent single-cell FACS sorting, single-cell RNA-seq library preparation and Illumina sequencing. MAIN RESULTS AND THE ROLE OF CHANCE Here we present a complete pipeline for single-cell gene-expression studies, from clinical sampling to statistical data analysis. Tissue manipulation, starting from disaggregation and cell-type-specific labelling and ending with single-cell automated sorting, is managed within 90 min at low temperature to minimize changes in the gene expression profile. The single living stromal and epithelial cells were sorted using CD13- and CD9-specific antibodies, respectively. Of the 8622 detected genes, 2661 were more active in cultured stromal cells than in biopsy cells. In the comparison of biopsy versus cultured cells, 5603 commonly expressed genes were detected, with 241 significantly differentially expressed genes. Of these, 231 genes were up- and 10 down-regulated in cultured cells, respectively. In addition, we performed a gene ontology analysis of the differentially expressed genes and found that these genes are mainly related to cell cycle, translational processes and metabolism. LIMITATIONS, REASONS FOR CAUTION Although CD9-positive single epithelial cells sorting was successfully established in our labora