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

      Nature Methods
      Algorithms, Animals, Argonaute Proteins, Blastomeres, cytology, metabolism, Cyclin E, genetics, DEAD-box RNA Helicases, DNA, Complementary, chemical synthesis, Databases, Nucleic Acid, Endoribonucleases, Eukaryotic Initiation Factor-2, Female, Gene Expression Profiling, methods, Kruppel-Like Transcription Factors, Mice, Mice, Inbred Strains, Mice, Knockout, Mice, Transgenic, Oligonucleotide Array Sequence Analysis, Oocytes, Polymerase Chain Reaction, Protein Isoforms, Proteins, RNA, Messenger, analysis, Ribonuclease III, Sequence Alignment, Sequence Analysis, DNA, Up-Regulation

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          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.

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