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/ ).

译文

无精子症是一种疾病,定义为射精中没有精子,但是患有无精子症的男性的睾丸表型可能非常多变,从完全的精子发生到不同阶段的生殖细胞的停滞成熟,再到完全变性的组织与鬼小管。因此,需要有关细胞类型特异性表达模式的信息,以优先考虑导致无精子症发病的潜在致病变异。由于下一代测序技术的进步,现在可以通过单细胞RNA测序在睾丸中获得详细的细胞类型特异性表达模式。但是,要正确解释单细胞RNA测序数据,需要对高度复杂的数据处理和可视化方法有足够的了解。在这里,我们回顾了不同类型的无精子症中人类睾丸的复杂细胞结构,并概述了已知的遗传改变如何影响睾丸的病理。我们将源自人类睾丸的当前可用的单细胞RNA测序数据集合并为一个数据集,覆盖62,751个睾丸细胞,每个具有2637个转录本的中位数。我们展示了最常见的数据处理步骤有什么效果,以及如何使用不同的可视化方法。此外,我们计算了假时间的表达模式,并显示了如何使用剪接速率来确定精子发生过程中的分化速度。通过组合数据集,我们显示了已知与无精子症发病机理有关的基因的表达模式和网络分析。最后,我们将组合数据集作为交互式在线资源提供,可以在其中探索基因的表达和不同的可视化方法 (https://testis.cells.ucsc.edu/ )。

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