PLoS ONE (Jan 2009)

High-resolution analysis of the 5'-end transcriptome using a next generation DNA sequencer.

  • Shin-ichi Hashimoto,
  • Wei Qu,
  • Budrul Ahsan,
  • Katsumi Ogoshi,
  • Atsushi Sasaki,
  • Yoichiro Nakatani,
  • Yongjun Lee,
  • Masako Ogawa,
  • Akio Ametani,
  • Yutaka Suzuki,
  • Sumio Sugano,
  • Clarence C Lee,
  • Robert C Nutter,
  • Shinichi Morishita,
  • Kouji Matsushima

DOI
https://doi.org/10.1371/journal.pone.0004108
Journal volume & issue
Vol. 4, no. 1
p. e4108

Abstract

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Massively parallel, tag-based sequencing systems, such as the SOLiD system, hold the promise of revolutionizing the study of whole genome gene expression due to the number of data points that can be generated in a simple and cost-effective manner. We describe the development of a 5'-end transcriptome workflow for the SOLiD system and demonstrate the advantages in sensitivity and dynamic range offered by this tag-based application over traditional approaches for the study of whole genome gene expression. 5'-end transcriptome analysis was used to study whole genome gene expression within a colon cancer cell line, HT-29, treated with the DNA methyltransferase inhibitor, 5-aza-2'-deoxycytidine (5Aza). More than 20 million 25-base 5'-end tags were obtained from untreated and 5Aza-treated cells and matched to sequences within the human genome. Seventy three percent of the mapped unique tags were associated with RefSeq cDNA sequences, corresponding to approximately 14,000 different protein-coding genes in this single cell type. The level of expression of these genes ranged from 0.02 to 4,704 transcripts per cell. The sensitivity of a single sequence run of the SOLiD platform was 100-1,000 fold greater than that observed from 5'end SAGE data generated from the analysis of 70,000 tags obtained by Sanger sequencing. The high-resolution 5'end gene expression profiling presented in this study will not only provide novel insight into the transcriptional machinery but should also serve as a basis for a better understanding of cell biology.