Gene Expression Profiling of Human Breast Tissue Samples Using SAGE-Seq

INSTRUCTIONS: Please enter one of the following Topic Classifications in the section below: Bioinformatics & Computational Biology Genes & Environment Genetic & Molecular Epidemiology Medical Genomics Molecular Genetics Proteomics Statistical Genetics, Genomics, and Omics 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 5 million reads.