Literature DB >> 32394391

In Situ Sequencing: A High-Throughput, Multi-Targeted Gene Expression Profiling Technique for Cell Typing in Tissue Sections.

Markus M Hilscher1, Daniel Gyllborg2, Chika Yokota2,3, Mats Nilsson2.   

Abstract

Recent advances of image-based in situ mRNA quantification methods allow to visualize where in a tissue section a set of genes is expressed. It enables to map large numbers of genes in parallel and by capturing cellular boundaries allows to assign genes to cells. Here, we present a high-throughput, multi-targeted gene expression profiling technique called in situ sequencing that is capable of localizing hundreds of genes simultaneously and supports cell type classifications that follow transcriptome-based taxonomy. In situ sequencing is a targeted, amplified, and barcoded approach using padlock probes (PLPs) and rolling circle amplification (RCA). The current protocol relies on mRNA fixation, mRNA reverse transcription, residual mRNA degradation, and PLP hybridization. PLPs are amplified by RCA and labeled with fluorophore-conjugated probes, allowing their detection under conventional fluorescence microscopes.

Entities:  

Keywords:  In situ sequencing; Padlock probe; Rolling circle amplification; Single-cell; Single-molecule; Spatial transcriptomics

Mesh:

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Year:  2020        PMID: 32394391     DOI: 10.1007/978-1-0716-0623-0_20

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  3 in total

1.  Spatial and temporal heterogeneity in the lineage progression of fine oligodendrocyte subtypes.

Authors:  Mats Nilsson; Gonçalo Castelo-Branco; Markus M Hilscher; Christoffer Mattsson Langseth; Petra Kukanja; Chika Yokota
Journal:  BMC Biol       Date:  2022-05-25       Impact factor: 7.364

2.  Automated identification of the mouse brain's spatial compartments from in situ sequencing data.

Authors:  Gabriele Partel; Markus M Hilscher; Giorgia Milli; Leslie Solorzano; Anna H Klemm; Mats Nilsson; Carolina Wählby
Journal:  BMC Biol       Date:  2020-10-19       Impact factor: 7.431

3.  Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps.

Authors:  Sergio Marco Salas; Daniel Gyllborg; Christoffer Mattsson Langseth; Mats Nilsson
Journal:  BMC Bioinformatics       Date:  2021-07-31       Impact factor: 3.169

  3 in total

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