Single-cell analysis of pathology in Klinefelter syndrome and idiopathic male infertility

Klinefelter syndrome (KS), also known as 47,XXY,  is characterized by a distinct set of physiological abnormalities, commonly including infertility. The molecular basis for Klinefelter-related infertility is still unclear, largely due to the cellular complexity of the testis and the intricate endocrine and paracrine signaling that regulates spermatogenesis. Here, we demonstrate an analysis framework for dissecting human testis pathology that uses comparative analysis of single-cell RNA-sequencing data from the biopsies of 13 human donors. By comparing donors from a range of ages and forms of infertility, we generate gene expression signatures that characterize normal testicular function and distinguish clinically distinct forms of male infertility. Unexpectedly, we identified a subpopulation of Sertoli cells within multiple cases of KS that lack transcription from the XIST locus, with the consequence of increased X-linked gene expression compared to all other KS cell populations. By systematic assessment of known signaling pathways, we identify 72 pathways potentially active in testis, dozens of which appear upregulated in KS.  Altogether our data support a model of pathogenic changes in interstitial cells cascading from loss of X-inactivation in pubertal Sertoli cells, and nominate testicular GNRH1 as a dosage-sensitive factor secreted by Sertoli cells that may contribute to the process. Our findings demonstrate the value of comparative patient analysis in mapping genetic mechanisms of disease, and identify an epigenetic phenomenon in KS Sertoli cells that may prove important for understanding causes of infertility and sex chromosome evolution. To dissect the pathological biology in Klinefelter syndrome (KS) and idiopathic male infertility, we combined and analyzed 26300 single cell transcriptomes derived from the testis of 12 carefully selected donors, chosen to allow us to isolate expression changes that are attributes of the specific defects of KS, versus changes that are general hallmarks of defects in spermatogenesis, and endocrine dysfunction. Our primary analysis framework is called Sparse Decomposition of Arrays (SDA), a matrix factorization method that we find very useful for summarizing large, multi-donor scRNA-seq data into manageable sets of co-regulated genes, known as SDA components. We have recently shown the value of SDA in interpreting testis pathology in mice13 and herein we expand on its application by showing utility in humans.