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

The DOI matches its Crossref record; 31 of the 33 references it cites were found in a registry or an index.

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

Open access
Bainbridge, Matthew N, Warren, René L, Hirst, Martin, Romanuik, Tammy, Zeng, Thomas, Go, Anne, Delaney, Allen, Griffith, Malachi, Hickenbotham, Matthew, Magrini, Vincent, Mardis, Elaine R, Sadar, Marianne D, Siddiqui, Asim S, Marra, Marco A, Jones, Steven JM·2006·BMC Genomics
DOI 10.1186/1471-2164-7-246PMC PMC1592491
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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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Figures

Figure 1 A histogram showing the number of gene loci hit by a given number of ESTs.
Figure 1 A histogram showing the number of gene loci hit by a given number of ESTs.CC BY · PubMed Central
Figure 2 A histogram showing the start of EST alignments to human transcript sequences (length > 500). Position is given as a percentage of the length of the transcript. ESTs which align to the positive or negative strands of the cDNA are shown in light or dark grey, respectively.
Figure 2 A histogram showing the start of EST alignments to human transcript sequences (length > 500). Position is given as a percentage of the length of the transcript. ESTs which align to the positive or negative strands of the cDNA are shown in light or dark grey, respectively.CC BY · PubMed Central
Figure 3 Alternative splicing of Brain Protein I3 (ENSG00000164713) showing a short insertion between two exons. 5' and 3' ends of two exons are shown in black text, interspaced by an intron (full sequence not shown) in orange. Base positions where the EST aligns to the transcript indicated with bold and italic type. The 40 base insertion is high-lighted in blue.
Figure 3 Alternative splicing of Brain Protein I3 (ENSG00000164713) showing a short insertion between two exons. 5' and 3' ends of two exons are shown in black text, interspaced by an intron (full sequence not shown) in orange. Base positions where the EST aligns to the transcript indicated with bold and italic type. The 40 base insertion is high-lighted in blue.CC BY · PubMed Central
Figure 4 A histogram of ESTs that fail to map to the human genome at various p-values.
Figure 4 A histogram of ESTs that fail to map to the human genome at various p-values.CC BY · PubMed Central

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Research works printed but not linked: 1

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

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Metadata

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
ORCID
Venue
BMC Genomics
Publisher
Springer Science and Business Media LLC
Published
2006-09-29
Volume
7
Issue
1
Pages
246-246
ISSN
1471-2164 (ISSN-L)
DOI
10.1186/1471-2164-7-246
PMC
PMC1592491
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
Licence
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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