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Laser capture microscopy coupled with Smart-seq2 for precise spatial transcriptomic profiling.

Nature communications | 2016

Laser capture microscopy (LCM) coupled with global transcriptome profiling could enable precise analyses of cell populations without the need for tissue dissociation, but has so far required relatively large numbers of cells. Here we report a robust and highly efficient strategy for LCM coupled with full-length mRNA-sequencing (LCM-seq) developed for single-cell transcriptomics. Fixed cells are subjected to direct lysis without RNA extraction, which both simplifies the experimental procedures as well as lowers technical noise. We apply LCM-seq on neurons isolated from mouse tissues, human post-mortem tissues, and illustrate its utility down to single captured cells. Importantly, we demonstrate that LCM-seq can provide biological insight on highly similar neuronal populations, including motor neurons isolated from different levels of the mouse spinal cord, as well as human midbrain dopamine neurons of the substantia nigra compacta and the ventral tegmental area.

Pubmed ID: 27387371 RIS Download

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This is a list of tools and resources that we have found mentioned in this publication.


Ambion Inc. (tool)

RRID:SCR_008406

A division of Applied Biosystems selling products for the isolation, detection, quantification, amplification, and characterization of RNA.

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FISHER (tool)

RRID:SCR_009181

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 1st, 2022. Software application for genetic analysis of classical biometric traits like blood pressure or height that are caused by a combination of polygenic inheritance and complex environmental forces. (entry from Genetic Analysis Software)

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RSeQC (tool)

RRID:SCR_005275

Software package to comprehensively evaluate different aspects of RNA-seq experiments, such as sequence quality, GC bias, polymerase chain reaction bias, nucleotide composition bias, sequencing depth, strand specificity, coverage uniformity and read distribution over the genome structure. RSeQC takes both SAM and BAM files as input, which can be produced by most RNA-seq mapping tools as well as BED files, which are widely used for gene models.

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Systems Transcriptional Activity Reconstruction (tool)

RRID:SCR_005622

A next-generation web-based application that aims to provide an integrated solution for both visualization and analysis of deep-sequencing data, along with simple access to public datasets.

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featureCounts (tool)

RRID:SCR_012919

A read summarization program, which counts mapped reads for the genomic features such as genes and exons.

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Cufflinks (tool)

RRID:SCR_014597

Software tool for transcriptome assembly and differential expression analysis for RNA-Seq. Includes script called cuffmerge that can be used to merge together several Cufflinks assemblies. It also handles running Cuffcompare as well as automatically filtering a number of transfrags that are likely to be artifacts. If the researcher has a reference GTF file, the researcher can provide it to the script to more effectively merge novel isoforms and maximize overall assembly quality.

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topGO (tool)

RRID:SCR_014798

Software package which provides tools for testing GO terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and applied.

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DESeq2 (tool)

RRID:SCR_015687

Software package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.

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