Cited by 222Genomics and Phylogenetic StudiesGene expression and cancer classificationSingle-cell and spatial transcriptomics

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

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Bainbridge, Matthew N, Warren, René L, Hirst, Martin, Romanuik, Tammy, Zeng, Thomas, Go, Anne, Delaney, Allen, Griffith, Malachi +7 more·2006·BMC Genomics

Abstract

BACKGROUND: 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. RESULTS: 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. CONCLUSION: 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.

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Crossref · 10.1186/1471-2164-7-246

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  • Transcript abundance is directly proportional to the number of sequencing reads that map to a specific transcript, resulting in lower false-negative and false-positive discovery rates and a greater linear range.

    “Transcript abundance is directly proportional to the number of sequencing reads that map to a specific transcript, resulting in lower falsenegative and false-positive discovery rates in addition to a greater linear range (Bainbridge et al., 2006;Cloonan et al., 2008;Marioni et al., 2008;Mortazavi et al., 2008;Nagalakshmi et al., 2008;Sultan et al., 2008;Wilhelm et al., 2008;Trapnell et al., 2010;W”

    From An RNA-Sequencing Transcriptome and Splicing Database of Glia, Neurons, and Vascular Cells of the Cerebral Cortex (2014) · cites this paper as Bainbridge et al., 2006

    The Results and discussion and Conclusion (pages not supplied) use mapped EST counts to assess transcript abundance, but report only modest agreement with SAGE. The Conclusion says read counts also depend on transcript length and shearing efficiency, so it does not establish direct proportionality. Our copy does not report lower false-negative or false-positive discovery rates or a greater linear range. (LLM, conf=0.86)

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  1. dbEST [http://www.ncbi.nlm.nih.gov/dbEST/]

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Authors
Bainbridge, M. N., Warren, R. L., Hirst, M., Romanuik, T., Zeng, T., Go, A., Delaney, A., Griffith, M., Hickenbotham, M., Magrini, V., Mardis, E. R., Sadar, M. D., Siddiqui, A. S., Marra, M. A., & Jones, S. J.
Affiliations
  • BC Cancer Agency (CA)
  • Washington University in St. Louis (US)
Corresponding author
Jones, Steven JM
Venue
BMC Genomics
Published
2006-09-29
Volume
7
Issue
1
Pages
246-246
ISSN
1471-2164 (ISSN-L)
OpenAlex
W2125013165
Cited by
222
References
33
Citations by year
2026: 6 · 2025: 6 · 2024: 15 · 2023: 15 · 2022: 12 · 2021: 21 · 2020: 8 · 2019: 10 · 2018: 6 · 2017: 6 · 2016: 3 · 2015: 10 · 2014: 5 · 2013: 9 · 2012: 8
FWCI
7.62
Type
journal article
Language
en
Open access
Locations
  • BMC Genomics (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Michael Smith Health Research BC
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
Keywords
LNCaP cells, prostate cancer, gene expression profiling, sequencing by synthesis, expressed sequence tags, alternative splicing, single nucleotide polymorphisms, R1881, androgen therapy, novel transcripts, genome mapping
MeSH terms
Adenocarcinoma, Androgens, Chromosome Mapping, Chromosomes, Human, Exons, Humans, Male, Neoplasms, Hormone-Dependent, Prostatic Neoplasms, RNA, Messenger, RNA, Neoplasm, Sequence Homology, Nucleic Acid, Transcription, Genetic, Metribolone, Gene Expression Regulation, Neoplastic, Sequence Alignment, Alternative Splicing, Sequence Analysis, DNA, DNA, Complementary, Expressed Sequence Tags, Polymorphism, Single Nucleotide, Gene Expression Profiling, Cell Line, Tumor

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