Non-invasive Transcriptomic Cell Profiling of the Human Endometrium with Generative Deep Learning
Non-invasive Transcriptomic Cell Profiling of the Human Endometrium with Generative Deep Learning
The detailed sample collection criteria are described in Apostolov et al., 2025. According to the provided summary, paired transcriptomic samples of endometrial tissue and uterine fluid extracellular vesicles (UF-EVs) were obtained from 19 fertile, healthy women. These samples were collected across four specific phases of the menstrual cycle: proliferative (n=4), early-secretory (n=5), mid-secretory (n=5), and late-secretory (n=5). Additionally, two unpaired UF-EV samples were collected from two healthy donors, one in the mid-secretory and one in the late-secretory phase.  The nucleic acid library construction protocol began with RNA extraction using QIAzol and miRNeasy micro kits, a process which consecutively separated the large and small RNA fractions. Quality and quantity of the extracted RNA were then assessed; a Bioanalyzer TapeStation 2100 was used for general quality checks, while the small RNA fraction was specifically quantified using a Qubit microRNA assay. For library construction, different kits were used depending on the target. Small RNA libraries were generated from 20 ng of starting material using a NEXTflex small RNA library preparation kit v4. In contrast, mRNA libraries were constructed using the TruSeq exome RNA library preparation kit (Illumina). This method enriches for coding regions via sequence-specific probes and does not depend on a poly(A) tail. The starting amount for uterine fluid extracellular vesicle (UF-EV) samples was 100 ng of RNA, or the maximum available quantity. Once the libraries were complete, they were pooled and evaluated with a High Sensitivity DNA ScreenTape D1000. 