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模型植物物种的空间分辨转录组分析。

Spatially resolved transcriptome profiling in model plant species.

机构信息

Division of Gene Technology, School of Biotechnology, KTH Royal Institute of Technology, Science for Life Laboratory, 17165 Solna, Sweden.

Department of Biochemistry and Biophysics, Stockholm University, Science for Life Laboratory, 17165 Solna, Sweden.

出版信息

Nat Plants. 2017 May 8;3:17061. doi: 10.1038/nplants.2017.61.

Abstract

Understanding complex biological systems requires functional characterization of specialized tissue domains. However, existing strategies for generating and analysing high-throughput spatial expression profiles were developed for a limited range of organisms, primarily mammals. Here we present the first available approach to generate and study high-resolution, spatially resolved functional profiles in a broad range of model plant systems. Our process includes high-throughput spatial transcriptome profiling followed by spatial gene and pathway analyses. We first demonstrate the feasibility of the technique by generating spatial transcriptome profiles from model angiosperms and gymnosperms microsections. In Arabidopsis thaliana we use the spatial data to identify differences in expression levels of 141 genes and 189 pathways in eight inflorescence tissue domains. Our combined approach of spatial transcriptomics and functional profiling offers a powerful new strategy that can be applied to a broad range of plant species, and is an approach that will be pivotal to answering fundamental questions in developmental and evolutionary biology.

摘要

理解复杂的生物系统需要对专门的组织区域进行功能表征。然而,现有的用于生成和分析高通量空间表达谱的策略主要是针对哺乳动物等有限范围的生物体开发的。在这里,我们提出了第一种可用于在广泛的模式植物系统中生成和研究高分辨率、空间分辨功能谱的方法。我们的过程包括高通量空间转录组谱分析,然后是空间基因和途径分析。我们首先通过对模式被子植物和裸子植物微切片进行空间转录组谱分析来证明该技术的可行性。在拟南芥中,我们利用空间数据鉴定出 8 个花序组织区域中 141 个基因和 189 个途径的表达水平差异。我们的空间转录组学和功能分析相结合的方法提供了一种强大的新策略,可应用于广泛的植物物种,这是一种对于回答发育和进化生物学中的基本问题至关重要的方法。

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