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Analysis of the prostate cancer cell line LNCaP transcriptome using a sequencing-by-synthesis approach

Matthew N Bainbridge1, René L Warren1, Martin Hirst1, Tammy Romanuik1, Thomas Zeng1, Anne Go1, Allen Delaney1, Malachi Griffith1, Matthew Hickenbotham2, Vincent Magrini2, Elaine R Mardis2, Marianne D Sadar1, Asim S Siddiqui1, Marco A Marra1 and Steven JM Jones1*

Author Affiliations

1 British Columbia Cancer Agency (BCCA) Genome Sciences Centre, Vancouver, British Columbia, Canada

2 Washington University School of Medicine, Genome Sequencing Center, St. Louis, Missouri 63108, USA

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BMC Genomics 2006, 7:246  doi:10.1186/1471-2164-7-246

Published: 29 September 2006



High throughput sequencing-by-synthesis is an emerging technology that allows the rapid production of millions of bases of data. Although the sequence reads are short, they can readily be used for re-sequencing. By re-sequencing the mRNA products of a cell, one may rapidly discover polymorphisms and splice variants particular to that cell.


We present the utility of massively parallel sequencing by synthesis for profiling the transcriptome of a human prostate cancer cell-line, LNCaP, that has been treated with the synthetic androgen, R1881. Through the generation of approximately 20 megabases (MB) of EST data, we detect transcription from over 10,000 gene loci, 25 previously undescribed alternative splicing events involving known exons, and over 1,500 high quality single nucleotide discrepancies with the reference human sequence. Further, we map nearly 10,000 ESTs to positions on the genome where no transcription is currently predicted to occur. We also characterize various obstacles with using sequencing by synthesis for transcriptome analysis and propose solutions to these problems.


The use of high-throughput sequencing-by-synthesis methods for transcript profiling allows the specific and sensitive detection of many of a cell's transcripts, and also allows the discovery of high quality base discrepancies, and alternative splice variants. Thus, this technology may provide an effective means of understanding various disease states, discovering novel targets for disease treatment, and discovery of novel transcripts.