Mahyari Eisa, Vigh-Conrad Katinka A, Daube Clément, Lima Ana C, Guo Jingtao, Carrell Douglas T, Hotaling James M, Aston Kenneth I, Conrad Donald F
Division of Genetics, Oregon National Primate Research Center, Oregon Health & Science University, Portland, Oregon, USA.
Andrology and IVF Laboratory, Division of Urology, Department of Surgery, University of Utah School of Medicine, Salt Lake City, Utah, USA.
Andrology. 2024 Apr 5. doi: 10.1111/andr.13637.
Single-cell RNA-seq (scRNA-Seq) has been widely adopted to study gene expression of the human testis. Several datasets of scRNA-Seq from human testis have been generated from different groups processed with different informatics pipelines. An integrated atlas of scRNA-Seq expression constructed from multiple donors, developmental ages, and fertility states would be widely useful for the testis research community.
To describe the generation and use of the human infertility single-cell testis atlas (HISTA), an interactive web tool for understanding human spermatogenesis through scRNA-Seq analysis.
We obtained scRNA-Seq datasets derived from 12 donors, including healthy adult controls, juveniles, and several infertility cases, and reprocessed these data using methods to remove batch effects. Using Shiny, an open-source environment for data visualization, we created numerous interactive tools for exploring the data, some of which support simple statistical hypothesis testing. We used the resulting HISTA browser and its underlying data to demonstrate HISTA's value for testis researchers.
A primary application of HISTA is to search by a single gene or a set of genes; thus, we present various analyses that quantify and visualize gene expression across the testis cells and pathology. HISTA also contains machine-learning-derived gene modules ("components") that capture the entire transcriptional landscape of the testis tissue. We show how the use of these components can simplify the highly complex data in HISTA and assist with the interpretation of genes with unknown functions. Finally, we demonstrate the diverse ways HISTA can be used for new data analysis, including hypothesis testing.
HISTA is a research environment that can help scientists organize and understand the high-dimensional transcriptional landscape of the human testis. HISTA has already contributed to published testis research and can be updated as needed with input from the research community or downloaded and modified for individual needs.
单细胞RNA测序(scRNA-Seq)已被广泛用于研究人类睾丸的基因表达。来自人类睾丸的几个scRNA-Seq数据集是由不同的研究小组使用不同的信息学流程生成的。构建一个整合了多个供体、发育年龄和生育状态的scRNA-Seq表达图谱,将对睾丸研究领域具有广泛的用途。
描述人类不育单细胞睾丸图谱(HISTA)的生成和使用,这是一个通过scRNA-Seq分析来理解人类精子发生的交互式网络工具。
我们获得了来自12个供体的scRNA-Seq数据集,包括健康成年对照、青少年以及一些不育病例,并使用去除批次效应的方法对这些数据进行了重新处理。利用用于数据可视化的开源环境Shiny,我们创建了许多用于探索数据的交互式工具,其中一些支持简单的统计假设检验。我们使用生成的HISTA浏览器及其基础数据来展示HISTA对睾丸研究人员的价值。
HISTA的一个主要应用是通过单个基因或一组基因进行搜索;因此,我们展示了各种分析方法,这些方法可以量化和可视化整个睾丸细胞和病理状态下的基因表达。HISTA还包含机器学习衍生的基因模块(“组件”),这些组件捕捉了睾丸组织的整个转录图谱。我们展示了如何使用这些组件来简化HISTA中高度复杂的数据,并有助于解释功能未知的基因。最后,我们展示了HISTA可用于新数据分析的多种方式,包括假设检验。
HISTA是一个研究环境,可帮助科学家组织和理解人类睾丸的高维转录图谱。HISTA已经为已发表的睾丸研究做出了贡献,并可根据研究界的输入进行必要的更新,或下载并根据个人需求进行修改。