Evaluating genetic causes of azoospermia: What can we learn from a complex cellular structure and single-cell transcriptomics of the human testis?

Azoospermia is a condition defined as the absence of spermatozoa in the ejaculate, but the testicular phenotype of men with azoospermia may be very variable, ranging from full spermatogenesis, through arrested maturation of germ cells at different stages, to completely degenerated tissue with ghost tubules. Hence, information regarding the cell-type-specific expression patterns is needed to prioritise potential pathogenic variants that contribute to the pathogenesis of azoospermia. Thanks to technological advances within next-generation sequencing, it is now possible to obtain detailed cell-type-specific expression patterns in the testis by single-cell RNA sequencing. However, to interpret single-cell RNA sequencing data properly, substantial knowledge of the highly sophisticated data processing and visualisation methods is needed. Here we review the complex cellular structure of the human testis in different types of azoospermia and outline how known genetic alterations affect the pathology of the testis. We combined the currently available single-cell RNA sequencing datasets originating from the human testis into one dataset covering 62,751 testicular cells, each with a median of 2637 transcripts quantified. We show what effects the most common data-processing steps have, and how different visualisation methods can be used. Furthermore, we calculated expression patterns in pseudotime, and show how splicing rates can be used to determine the velocity of differentiation during spermatogenesis. With the combined dataset we show expression patterns and network analysis of genes known to be involved in the pathogenesis of azoospermia. Finally, we provide the combined dataset as an interactive online resource where expression of genes and different visualisation methods can be explored ( https://testis.cells.ucsc.edu/ ).

The Mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates.

In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various nonhuman species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and appropriately accounting for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a 'Mutationathon,' a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a twofold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria, and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.

Small RNAs in Seminal Plasma as Novel Biomarkers for Germ Cell Tumors.

Circulating miRNAs secreted by testicular germ cell tumors (TGCT) show great potential as novel non-invasive biomarkers for diagnosis of TGCT. Seminal plasma (SP) represents a biofluid closer to the primary site. Here, we investigate whether small RNAs in SP can be used to diagnose men with TGCTs or the precursor lesions, germ cell neoplasia in situ (GCNIS). Small RNAs isolated from SP from men with TGCTs (n = 18), GCNIS-only (n = 5), and controls (n = 25) were sequenced. SP from men with TGCT/GCNIS (n = 37) and controls (n = 22) were used for validation by RT-qPCR. In general, piRNAs were found at lower levels in SP from men with TGCTs. Ten small RNAs were found at significantly (q-value < 0.05) different levels in SP from men with TGCT/GCNIS than controls. Random forests classification identified sets of small RNAs that could detect either TGCT/GCNIS or GCNIS-only with an area under the curve of 0.98 and 1 in ROC analyses, respectively. RT-qPCR validated hsa-miR-6782-5p to be present at 2.3-fold lower levels (p = 0.02) in the SP from men with TGCTs compared with controls. Small RNAs in SP show potential as novel biomarkers for diagnosing men with TGCT/GCNIS but validation in larger cohorts is needed.

Epigenomic profiling of primate lymphoblastoid cell lines reveals the evolutionary patterns of epigenetic activities in gene regulatory architectures.

Changes in the epigenetic regulation of gene expression have a central role in evolution. Here, we extensively profiled a panel of human, chimpanzee, gorilla, orangutan, and macaque lymphoblastoid cell lines (LCLs), using ChIP-seq for five histone marks, ATAC-seq and RNA-seq, further complemented with whole genome sequencing (WGS) and whole genome bisulfite sequencing (WGBS). We annotated regulatory elements (RE) and integrated chromatin contact maps to define gene regulatory architectures, creating the largest catalog of RE in primates to date. We report that epigenetic conservation and its correlation with sequence conservation in primates depends on the activity state of the regulatory element. Our gene regulatory architectures reveal the coordination of different types of components and highlight the role of promoters and intragenic enhancers (gE) in the regulation of gene expression. We observe that most regulatory changes occur in weakly active gE. Remarkably, novel human-specific gE with weak activities are enriched in human-specific nucleotide changes. These elements appear in genes with signals of positive selection and human acceleration, tissue-specific expression, and particular functional enrichments, suggesting that the regulatory evolution of these genes may have contributed to human adaptation.