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Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues
Je Hyuk Lee1,6, Evan R Daugharthy13,6, Jonathan Scheiman1,2, Reza Kalhor2, Thomas C Ferrante1, Richard Terry1, Brian M Turczyk1, Joyce L Yang2, Ho Suk Lee4, John Aach2, Kun Zhang5 & George M Church1,2
1Wyss Institute, Harvard Medical School, Boston, Massachusetts, USA. 2Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA.
3Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA. 4Department of Electrical and Computer Engineering, University of California San Diego, California, USA. 5Department of Bioengineering, University of California San Diego, La Jolla, California, USA. 6These authors contributed equally to this work. Correspondence should be addressed to J.H.L. ([email protected]) or G.M.C. ([email protected]).
Published online 12 February 2015; http://www.nature.com/doifinder/10.1038/nprot.2014.191
Web End =doi:10.1038/nprot.2014.191
RNA-sequencing (RNA-seq) measures the quantitative change in gene expression over the whole transcriptome, but it lacks spatial context. In contrast, in situ hybridization provides the location of gene expression, but only for a small number of genes. Herewe detail a protocol for genome-wide profiling of gene expression in situ in fixed cells and tissues, in which RNA is convertedinto cross-linked cDNA amplicons and sequenced manually on a confocal microscope. Unlike traditional RNA-seq, our method enriches for context-specific transcripts over housekeeping and/or structural RNA, and it preserves the tissue architecture for RNA localization studies. Our protocol is written for researchers experienced in cell microscopy with minimal computing skills. Library construction and sequencing can be completed within 14 d, with image analysis requiring an additional 2 d.
2015Nature America, Inc. All rights reserved.
INTRODUCTIONBackgroundCell type and function in tissues can be inferred from RNA or protein markers1,2, but this approach to functional classification requires well-characterized biomarkers. Ideally, it would be preferable to define cell or tissue types using high-throughput molecular profiling in situ with high-resolution imaging. Indeed, several studies have surveyed global gene expression in situ, in which hundreds of organ tissue slices from multiple animals were individually interrogated using gene-specific probes36;
however, such approaches represent a massive experimental undertaking, and they produce only an average view of tissue-specific gene expression.
In theory, multiplexed in situ RNA detection demands fewer samples, but so far this approach is limited by the number of spectrally distinct fluorophores and the optical diffraction limit...