In situ detection and genotyping of individual mRNA molecules

Larsson, Chatarina; Grundberg, Ida; Söderberg, Ola; Nilsson, Mats

doi:10.1038/nmeth.1448

Cited by 366 publications

(366 citation statements)

References 16 publications

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“…Existing methods for measuring transcript levels in single cells include RT-qPCR (1), single molecule counting using digital PCR (2) or hybridization probes (3,4), and next generation sequencing (5). Of these, single-cell RT-qPCR provides combined advantages of sensitivity, specificity, and dynamic range, but is limited by low throughput, high reagent cost, and difficulties in accurately measuring low abundance transcripts (6).…”

mentioning

confidence: 99%

High-throughput microfluidic single-cell RT-qPCR

White

VanInsberghe

Petriv

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

409

368

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A long-sought milestone in microfluidics research has been the development of integrated technology for scalable analysis of transcription in single cells. Here we present a fully integrated microfluidic device capable of performing high-precision RT-qPCR measurements of gene expression from hundreds of single cells per run. Our device executes all steps of single-cell processing, including cell capture, cell lysis, reverse transcription, and quantitative PCR. In addition to higher throughput and reduced cost, we show that nanoliter volume processing reduced measurement noise, increased sensitivity, and provided single nucleotide specificity. We apply this technology to 3,300 single-cell measurements of ( i ) miRNA expression in K562 cells, ( ii ) coregulation of a miRNA and one of its target transcripts during differentiation in embryonic stem cells, and ( iii ) single nucleotide variant detection in primary lobular breast cancer cells. The core functionality established here provides the foundation from which a variety of on-chip single-cell transcription analyses will be developed.

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mentioning

confidence: 99%

High-throughput microfluidic single-cell RT-qPCR

White

VanInsberghe

Petriv

et al. 2011

Proc. Natl. Acad. Sci. U.S.A.

409

368

View full text Add to dashboard Cite

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“…The efficiency for detecting single transcript molecules has been estimated to be 30% [13,16] and 3% [15] respectively, which is much lower than the 85% of hybridization efficiency in sm-FISH [4,17]. Such low efficiencies currently prevent these alternative methods from surveying the transcriptome with singlemolecule sensitivity and resolution in situ [18,19].…”

Section: Alternative Methods For Rna Detection In Imagingmentioning

confidence: 99%

Computer vision for image-based transcriptomics

Stoeger

Battich

Herrmann

et al. 2015

Methods

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Single-cell transcriptomics has recently emerged as one of the most promising tools for understanding the diversity of the transcriptome among single cells. Image-based transcriptomics is unique compared to other methods as it does not require conversion of RNA to cDNA prior to signal amplification and transcript quantification. Thus, its efficiency in transcript detection is unmatched by other methods. In addition, image-based transcriptomics allows the study of the spatial organization of the transcriptome in single cells at single-molecule, and, when combined with superresolution microscopy, nanometer resolution. However, in order to unlock the full power of image-based transcriptomics, robust computer vision of single molecules and cells is required. Here, we shortly discuss the setup of the experimental pipeline for image-based transcriptomics, and then describe in detail the algorithms that we developed to extract, at high-throughput, robust multivariate feature sets of transcript molecule abundance, localization and patterning in tens of thousands of single cells across the transcriptome. These computer vision algorithms and pipelines can be downloaded from: https://github.com/pelkmanslab/ImageBasedTranscriptomics. AbstractSingle-cell transcriptomics has recently emerged as one of the most promising tools for

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“…Afterwards, they applied mRNA-based in situ mutation detection technology based on padlock probes for direct mutation detection in sections of formaldehydefixed and paraffin-embedded cancer tissue. The padlock probe technique is highly specific and permits the detection of point mutations in situ in tissue sections (Larsson et al 2010). Using this in situ mutation detection, El-Heliebi et al (2017) were able for instance to clearly localize not only FANCD2 wild type, but also mutated transcripts in certain tumor areas.…”

Section: Visualization Of Genetic Heterogeneity In Morphologically Homentioning

confidence: 99%