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Full-length mrna-seq from single-cell levels of rna and individual circulating tumor cells

Academic Article
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Overview

authors

  • Ramskold, D.
  • Luo, S. J.
  • Wang, Y. C.
  • Li, R.
  • Deng, Q. L.
  • Faridani, O. R.
  • Daniels, G. A.
  • Khrebtukova, I.
  • Loring, Jeanne
  • Laurent, L. C.
  • Schroth, G. P.
  • Sandberg, R.

publication date

  • August 2012

journal

  • Nature Biotechnology  Journal

abstract

  • Genome-wide transcriptome analyses are routinely used to monitor tissue-, disease- and cell type–specific gene expression, but it has been technically challenging to generate expression profiles from single cells. Here we describe a robust mRNA-Seq protocol (Smart-Seq) that is applicable down to single cell levels. Compared with existing methods, Smart-Seq has improved read coverage across transcripts, which enhances detailed analyses of alternative transcript isoforms and identification of single-nucleotide polymorphisms. We determined the sensitivity and quantitative accuracy of Smart-Seq for single-cell transcriptomics by evaluating it on total RNA dilution series. We found that although gene expression estimates from single cells have increased noise, hundreds of differentially expressed genes could be identified using few cells per cell type. Applying Smart-Seq to circulating tumor cells from melanomas, we identified distinct gene expression patterns, including candidate biomarkers for melanoma circulating tumor cells. Our protocol will be useful for addressing fundamental biological problems requiring genome-wide transcriptome profiling in rare cells.

subject areas

  • Animals
  • Cluster Analysis
  • Female
  • Gene Expression Profiling
  • Gene Library
  • Humans
  • Melanoma
  • Mice
  • Neoplastic Cells, Circulating
  • Oligonucleotide Array Sequence Analysis
  • RNA, Messenger
  • Sensitivity and Specificity
  • Sequence Analysis, RNA
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Identity

PubMed Central ID

  • PMC3467340

International Standard Serial Number (ISSN)

  • 1087-0156

Digital Object Identifier (DOI)

  • 10.1038/nbt.2282

PubMed ID

  • 22820318
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Additional Document Info

start page

  • 777

end page

  • 782

volume

  • 30

issue

  • 8

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