Literature DB >> 25446315

Spatially resolved transcriptomics and beyond.

Nicola Crosetto1, Magda Bienko1, Alexander van Oudenaarden2.   

Abstract

Considerable progress in sequencing technologies makes it now possible to study the genomic and transcriptomic landscape of single cells. However, to better understand the complexity of multicellular organisms, we must devise ways to perform high-throughput measurements while preserving spatial information about the tissue context or subcellular localization of analysed nucleic acids. In this Innovation article, we summarize pioneering technologies that enable spatially resolved transcriptomics and discuss how these methods have the potential to extend beyond transcriptomics to encompass spatially resolved genomics, proteomics and possibly other omic disciplines.

Mesh:

Year:  2014        PMID: 25446315     DOI: 10.1038/nrg3832

Source DB:  PubMed          Journal:  Nat Rev Genet        ISSN: 1471-0056            Impact factor:   53.242


  95 in total

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2.  Mutation detection and single-molecule counting using isothermal rolling-circle amplification.

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Review 4.  Intra-tumour heterogeneity: a looking glass for cancer?

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6.  Direct observation of individual endogenous protein complexes in situ by proximity ligation.

Authors:  Ola Söderberg; Mats Gullberg; Malin Jarvius; Karin Ridderstråle; Karl-Johan Leuchowius; Jonas Jarvius; Kenneth Wester; Per Hydbring; Fuad Bahram; Lars-Gunnar Larsson; Ulf Landegren
Journal:  Nat Methods       Date:  2006-10-29       Impact factor: 28.547

7.  Intratumor heterogeneity in localized lung adenocarcinomas delineated by multiregion sequencing.

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Journal:  Science       Date:  2014-10-10       Impact factor: 47.728

8.  FuseFISH: robust detection of transcribed gene fusions in single cells.

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10.  Allele-specific detection of single mRNA molecules in situ.

Authors:  Clinton H Hansen; Alexander van Oudenaarden
Journal:  Nat Methods       Date:  2013-08-11       Impact factor: 28.547

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  148 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2015-11-02       Impact factor: 11.205

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4.  Statistical analysis of spatial expression patterns for spatially resolved transcriptomic studies.

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Review 5.  Advances and applications of single-cell sequencing technologies.

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7.  A Bayesian model for single cell transcript expression analysis on MERFISH data.

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Review 10.  Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

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