Research article summary (published 4 Apr 2009):

mRNA-Seq whole-transcriptome analysis of a single cell.

Full Abstract

Next-generation sequencing technology is a powerful tool for transcriptome analysis. However, under certain conditions, only a small amount of material is available, which requires more sensitive techniques that can preferably be used at the single-cell level. Here we describe a single-cell digital gene expression profiling assay. Using our mRNA-Seq assay with only a single mouse blastomere, we detected the expression of 75% (5,270) more genes than microarray techniques and identified 1,753 previously unknown splice junctions called by at least 5 reads. Moreover, 8-19% of the genes with multiple known transcript isoforms expressed at least two isoforms in the same blastomere or oocyte, which unambiguously demonstrated the complexity of the transcript variants at whole-genome scale in individual cells. Finally, for Dicer1(-/-) and Ago2(-/-) (Eif2c2(-/-)) oocytes, we found that 1,696 and 1,553 genes, respectively, were abnormally upregulated compared to wild-type controls, with 619 genes in common.

Author information

Author/s: Tang, Fuchou (F); Barbacioru, Catalin (C); Wang, Yangzhou (Y); Nordman, Ellen (E); Lee, Clarence (C); Xu, Nanlan (N); Wang, Xiaohui (X); Bodeau, John (J); Tuch, Brian B (BB); Siddiqui, Asim (A); Lao, Kaiqin (K); Surani, M Azim (MA);

Affiliation: Wellcome Trust-Cancer Research UK Gurdon Institute of Cancer and Developmental Biology, University of Cambridge, Cambridge, UK.

Grants: (Agency:Wellcome Trust)

Journal and publication information

Publication Type: Journal Article; Research Support, Non-U.S. Gov't

Journal: Nature methods (Nat Methods), published in United States. (Language: eng)

Reference: 2009-May; vol 6 (issue 5) : pp 377-82

Dates: Created 2009/04/30; Completed 2009/05/26;

PMID: 19349980, status: MEDLINE (last retrieval date: 5/26/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Algorithms Animals Blastomeres - cytology; metabolism Cyclin E - genetics DEAD-box RNA Helicases - genetics DNA, Complementary - chemical synthesis; genetics Databases, Nucleic Acid Endoribonucleases - genetics Eukaryotic Initiation Factor-2 - genetics Female Gene Expression Profiling - methods Kruppel-Like Transcription Factors - genetics Mice

Mice Mice, Inbred Strains Mice, Knockout Mice, Transgenic Oligonucleotide Array Sequence Analysis Oocytes - metabolism Polymerase Chain Reaction - methods Protein Isoforms - genetics Proteins - genetics RNA, Messenger - analysis; metabolism Sequence Alignment Sequence Analysis, DNA - methods Up-Regulation - genetics

Associated Chemicals: Cyclin E (0) ; DNA, Complementary (0) ; Dppa5 protein, mouse (0) ; EIF2C2 protein, mouse (0) ; Eukaryotic Initiation Factor-2 (0) ; Klf2 protein, mouse (0) ; Kruppel-Like Transcription Factors (0) ; Protein Isoforms (0) ; Proteins (0) ; RNA, Messenger (0) ; DEAD-box RNA Helicases (EC 2.7.7.-) ; Endoribonucleases (EC 3.1.-) ; Dicer1 protein, mouse (EC 3.1.26.-)

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