Article

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

British Columbia Cancer Agency (BCCA) Genome Sciences Centre, Vancouver, British Columbia, Canada. .
BMC Genomics (Impact Factor: 4.04). 02/2006; 7:246. DOI: 10.1186/1471-2164-7-246
Source: PubMed

ABSTRACT 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.

Download full-text

Full-text

Available from: René L Warren, Jun 29, 2015
0 Followers
 · 
177 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We studied the sub-population level evolution of a duck influenza A virus isolate during passage in swine tracheal cells. The complete genomes of the A/mallard/Netherlands/10-Nmkt/1999 strain and its swine cell-passaged descendent were analysed by 454 pyrosequencing with coverage depth ranging from several hundred to several thousand reads at any point. This allowed characterization of defined minority sub-populations of gene segments 2, 3, 4, 5, 7, and 8 present in the original isolate. These minority sub-populations ranged between 9.5% (for segment 2) and 46% (for segment 4) of their respective gene segments in the parental stock. They were likely contributed by one or more viruses circulating within the same area, at the same period and in the same or a sympatric host species. The minority sub-populations of segments 3, 4, and 5 became extinct upon viral passage in swine cells, whereas the minority sub-populations of segments 2, 7 and 8 completely replaced their majority counterparts. The swine cell-passaged virus was therefore a three-segment reassortant and also harboured point mutations in segments 3 and 4. The adapted virus was more homogenous than the parental stock, with only 17 minority single nucleotide polymorphisms present above 5% frequency across the whole genome. Though limited here to one sample, this deep sequencing approach highlights the evolutionary versatility of influenza viruses whereby they exploit their genetic diversity, predilection for mixed infection and reassortment to adapt to a new host environmental niche.
    Infection, genetics and evolution: journal of molecular epidemiology and evolutionary genetics in infectious diseases 05/2013; 18. DOI:10.1016/j.meegid.2013.04.034 · 3.26 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In recent years, the introduction of massively parallel sequencing platforms for Next Generation Sequencing (NGS) protocols, able to simultaneously sequence hundred thousand DNA fragments, dramatically changed the landscape of the genetics studies. RNA-Seq for transcriptome studies, Chip-Seq for DNA-proteins interaction, CNV-Seq for large genome nucleotide variations are only some of the intriguing new applications supported by these innovative platforms. Among them RNA-Seq is perhaps the most complex NGS application. Expression levels of specific genes, differential splicing, allele-specific expression of transcripts can be accurately determined by RNA-Seq experiments to address many biological-related issues. All these attributes are not readily achievable from previously widespread hybridization-based or tag sequence-based approaches. However, the unprecedented level of sensitivity and the large amount of available data produced by NGS platforms provide clear advantages as well as new challenges and issues. This technology brings the great power to make several new biological observations and discoveries, it also requires a considerable effort in the development of new bioinformatics tools to deal with these massive data files. The paper aims to give a survey of the RNA-Seq methodology, particularly focusing on the challenges that this application presents both from a biological and a bioinformatics point of view.
    BioMed Research International 06/2010; 2010:853916. DOI:10.1155/2010/853916 · 2.71 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The genetics of complex diseases has been given a tremendous boost in recent years by the introduction of high-throughput laboratory methods that make it possible to approach larger questions in larger populations and to cover the genome more comprehensively. The ability to determine genotypes of many individuals accurately and efficiently has allowed genetic studies that cover more of the variation within individual genes, instead of focusing only on one or a few coding variants, and to do so in study samples of reasonable power. Chip-based genotyping assays, combined with knowledge of the patterns of coinheritance of markers (linkage disequilibrium [LD]), have stimulated genome-wide association studies (GWAS) of complex diseases. Recent successes of GWAS in identifying specific genes that affect risk for common diseases are dramatic illustrations of how improved technology can lead to scientific breakthroughs. A key issue in high-throughput genotyping is to choose the appropriate technology for your goals and for the stage of your experiment, being cognizant of your sample numbers and resources. This article introduces some of the commonly used methods of high-throughput single-nucleotide polymorphism (SNP) genotyping for different stages of genetic studies and briefly reviews some of the high-throughput sequencing methods just coming into use. It also mentions some recent developments in "next-generation" sequencing that will enable other kinds of studies. This article is not intended to be comprehensive, and because technology in this area is rapidly changing, our comments should be taken as a starting point for further investigation.
    Cold Spring Harbor Protocols 11/2009; 2009(11):pdb.top62. DOI:10.1101/pdb.top62 · 4.63 Impact Factor