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VISTA:可视化神经系统的空间转录组

VISTA: Visualizing the Spatial Transcriptome of the Nervous System.

作者信息

Liska David, Wolfe Zachery, Norris Adam

机构信息

Office of Information Technology, Southern Methodist University. Dallas, TX USA.

Department of Biological Sciences, Southern Methodist University. Dallas, TX USA.

出版信息

bioRxiv. 2023 Jun 22:2023.04.28.538711. doi: 10.1101/2023.04.28.538711.

Abstract

Profiling the transcriptomes of single cells without sacrificing spatial information is a major goal of the field of spatial transcriptomics, but current technologies require tradeoffs between single-cell resolution and whole-transcriptome coverage. In one animal species, the nematode worm , a comprehensive spatial transcriptome with single-cell resolution is attainable using existing datasets, thanks to the worm's invariant cell lineage and a series of recently-generated single cell transcriptomes. Here we present VISTA, which leverages these datasets to provide a visualization of the worm spatial transcriptome, focusing specifically on the nervous system. VISTA allows users to input a query gene and visualize its expression across all neurons in the form of a "spatial heatmap" in which the color of a cell reports the expression level. Underlying gene expression values (in Transcripts Per Million) are displayed when an individual cell is selected. We provide examples of the utility of VISTA for identifying striking new gene expression patterns in specific neurons, and for resolving cellular identities of ambiguous expression patterns generated from reporter genes. The ability to easily obtain gene-level snapshots of the neuronal spatial transcriptome should facilitate studies on neuron-specific gene expression and regulation, and provide a template for the high-resolution spatial transcriptomes the field hopes to obtain for various animal species in the future.

摘要

在不牺牲空间信息的情况下对单细胞转录组进行分析是空间转录组学领域的一个主要目标,但目前的技术需要在单细胞分辨率和全转录组覆盖范围之间进行权衡。在一种动物物种——线虫中,借助线虫不变的细胞谱系和一系列最近生成的单细胞转录组,利用现有数据集可以获得具有单细胞分辨率的全面空间转录组。在这里,我们展示了VISTA,它利用这些数据集来呈现线虫空间转录组的可视化,特别关注神经系统。VISTA允许用户输入一个查询基因,并以“空间热图”的形式可视化其在所有神经元中的表达,其中细胞的颜色表示表达水平。当选择单个细胞时,会显示基础基因表达值(每百万转录本数)。我们提供了VISTA在识别特定神经元中显著的新基因表达模式以及解决由报告基因产生的模糊表达模式的细胞身份方面的实用性示例。轻松获取神经元空间转录组的基因水平快照的能力应有助于对神经元特异性基因表达和调控的研究,并为该领域未来希望为各种动物物种获得的高分辨率空间转录组提供一个模板。

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