Gene expression profiling of human breast tissue samples using SAGE-Seq

Zhenhua Jeremy Wu, Clifford A. Meyer, Sibgat Choudhury, Michail Shipitsin, Reo Maruyama, Marina Bessarabova, Tatiana Nikolskaya, Saraswati Sukumar, Armin Schwartzman, Jun S. Liu, Kornelia Polyak, X. Shirley Liu

Research output: Contribution to journalArticle

Abstract

We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.

Original languageEnglish (US)
Pages (from-to)1730-1739
Number of pages10
JournalGenome research
Volume20
Issue number12
DOIs
StatePublished - Dec 2010

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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    Wu, Z. J., Meyer, C. A., Choudhury, S., Shipitsin, M., Maruyama, R., Bessarabova, M., Nikolskaya, T., Sukumar, S., Schwartzman, A., Liu, J. S., Polyak, K., & Liu, X. S. (2010). Gene expression profiling of human breast tissue samples using SAGE-Seq. Genome research, 20(12), 1730-1739. https://doi.org/10.1101/gr.108217.110