{"title":"用于 RNA 原位测序的空间分析工具包。","authors":"Jiayu Chen, Rongqin Ke","doi":"10.1002/wrna.1842","DOIUrl":null,"url":null,"abstract":"<p><p>Spatial transcriptomics (ST) is featured by high-throughput gene expression profiling within their native cell and tissue context, offering a means to investigate gene regulatory networks in tissue microenvironment. In situ sequencing (ISS) is an imaging-based ST technology that simultaneously detects hundreds to thousands of genes at subcellular resolution. As a highly reproducible and robust technique, ISS has been widely adapted and undergone a series of technical iterations. As the interest in ISS-based spatial transcriptomic analysis grows, scalable and integrated data analysis workflows are needed to facilitate the applications of ISS in different research fields. This review presents the state-of-the-art bioinformatic toolkits for ISS data analysis, which covers the upstream and downstream analysis workflows, including image analysis, cell segmentation, clustering, functional enrichment, detection of spatially variable genes and cell clusters, spatial cell-cell interactions, and trajectory inference. To assist the community in choosing the right tools for their research, the application of each tool and its compatibility with ISS data are reviewed in detailed. Finally, future perspectives and challenges concerning how to integrate heterogeneous tools into a user-friendly analysis pipeline are discussed. This article is categorized under: RNA Methods > RNA Analyses In Vitro and In Silico.</p>","PeriodicalId":23886,"journal":{"name":"Wiley Interdisciplinary Reviews: RNA","volume":"15 2","pages":"e1842"},"PeriodicalIF":6.4000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatial analysis toolkits for RNA in situ sequencing.\",\"authors\":\"Jiayu Chen, Rongqin Ke\",\"doi\":\"10.1002/wrna.1842\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Spatial transcriptomics (ST) is featured by high-throughput gene expression profiling within their native cell and tissue context, offering a means to investigate gene regulatory networks in tissue microenvironment. In situ sequencing (ISS) is an imaging-based ST technology that simultaneously detects hundreds to thousands of genes at subcellular resolution. As a highly reproducible and robust technique, ISS has been widely adapted and undergone a series of technical iterations. As the interest in ISS-based spatial transcriptomic analysis grows, scalable and integrated data analysis workflows are needed to facilitate the applications of ISS in different research fields. This review presents the state-of-the-art bioinformatic toolkits for ISS data analysis, which covers the upstream and downstream analysis workflows, including image analysis, cell segmentation, clustering, functional enrichment, detection of spatially variable genes and cell clusters, spatial cell-cell interactions, and trajectory inference. To assist the community in choosing the right tools for their research, the application of each tool and its compatibility with ISS data are reviewed in detailed. Finally, future perspectives and challenges concerning how to integrate heterogeneous tools into a user-friendly analysis pipeline are discussed. This article is categorized under: RNA Methods > RNA Analyses In Vitro and In Silico.</p>\",\"PeriodicalId\":23886,\"journal\":{\"name\":\"Wiley Interdisciplinary Reviews: RNA\",\"volume\":\"15 2\",\"pages\":\"e1842\"},\"PeriodicalIF\":6.4000,\"publicationDate\":\"2024-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Wiley Interdisciplinary Reviews: RNA\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1002/wrna.1842\",\"RegionNum\":2,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CELL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wiley Interdisciplinary Reviews: RNA","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/wrna.1842","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CELL BIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
空间转录组学(ST)的特点是在原生细胞和组织背景下进行高通量基因表达谱分析,为研究组织微环境中的基因调控网络提供了一种手段。原位测序(ISS)是一种基于成像的空间转录组学技术,可同时检测亚细胞分辨率的数百至数千个基因。作为一种具有高度可重复性和稳健性的技术,原位测序已被广泛采用并经历了一系列技术迭代。随着人们对基于 ISS 的空间转录组分析的兴趣与日俱增,需要可扩展的集成数据分析工作流程来促进 ISS 在不同研究领域的应用。本综述介绍了最先进的 ISS 数据分析生物信息学工具包,涵盖了上游和下游分析工作流程,包括图像分析、细胞分割、聚类、功能富集、空间可变基因和细胞簇检测、空间细胞-细胞相互作用以及轨迹推断。为了帮助社区为其研究选择合适的工具,我们详细介绍了每种工具的应用及其与 ISS 数据的兼容性。最后,还讨论了如何将异构工具整合到用户友好的分析管道中的未来展望和挑战。本文归类于RNA 方法 > 体外和硅学 RNA 分析。
Spatial analysis toolkits for RNA in situ sequencing.
Spatial transcriptomics (ST) is featured by high-throughput gene expression profiling within their native cell and tissue context, offering a means to investigate gene regulatory networks in tissue microenvironment. In situ sequencing (ISS) is an imaging-based ST technology that simultaneously detects hundreds to thousands of genes at subcellular resolution. As a highly reproducible and robust technique, ISS has been widely adapted and undergone a series of technical iterations. As the interest in ISS-based spatial transcriptomic analysis grows, scalable and integrated data analysis workflows are needed to facilitate the applications of ISS in different research fields. This review presents the state-of-the-art bioinformatic toolkits for ISS data analysis, which covers the upstream and downstream analysis workflows, including image analysis, cell segmentation, clustering, functional enrichment, detection of spatially variable genes and cell clusters, spatial cell-cell interactions, and trajectory inference. To assist the community in choosing the right tools for their research, the application of each tool and its compatibility with ISS data are reviewed in detailed. Finally, future perspectives and challenges concerning how to integrate heterogeneous tools into a user-friendly analysis pipeline are discussed. This article is categorized under: RNA Methods > RNA Analyses In Vitro and In Silico.
期刊介绍:
WIREs RNA aims to provide comprehensive, up-to-date, and coherent coverage of this interesting and growing field, providing a framework for both RNA experts and interdisciplinary researchers to not only gain perspective in areas of RNA biology, but to generate new insights and applications as well. Major topics to be covered are: RNA Structure and Dynamics; RNA Evolution and Genomics; RNA-Based Catalysis; RNA Interactions with Proteins and Other Molecules; Translation; RNA Processing; RNA Export/Localization; RNA Turnover and Surveillance; Regulatory RNAs/RNAi/Riboswitches; RNA in Disease and Development; and RNA Methods.