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A transcriptional sketch of a primary human breast cancer by 454 deep sequencing

BACKGROUND: The cancer transcriptome is difficult to explore due to the heterogeneity of quantitative and qualitative changes in gene expression linked to the disease status. An increasing number of "unconventional" transcripts, such as novel isoforms, non-coding RNAs, somatic gene fusions...

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Detalles Bibliográficos
Autores principales: Guffanti, Alessandro, Iacono, Michele, Pelucchi, Paride, Kim, Namshin, Soldà, Giulia, Croft, Larry J, Taft, Ryan J, Rizzi, Ermanno, Askarian-Amiri, Marjan, Bonnal, Raoul J, Callari, Maurizio, Mignone, Flavio, Pesole, Graziano, Bertalot, Giovanni, Bernardi, Luigi Rossi, Albertini, Alberto, Lee, Christopher, Mattick, John S, Zucchi, Ileana, De Bellis, Gianluca
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2678161/
https://www.ncbi.nlm.nih.gov/pubmed/19379481
http://dx.doi.org/10.1186/1471-2164-10-163
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author Guffanti, Alessandro
Iacono, Michele
Pelucchi, Paride
Kim, Namshin
Soldà, Giulia
Croft, Larry J
Taft, Ryan J
Rizzi, Ermanno
Askarian-Amiri, Marjan
Bonnal, Raoul J
Callari, Maurizio
Mignone, Flavio
Pesole, Graziano
Bertalot, Giovanni
Bernardi, Luigi Rossi
Albertini, Alberto
Lee, Christopher
Mattick, John S
Zucchi, Ileana
De Bellis, Gianluca
author_facet Guffanti, Alessandro
Iacono, Michele
Pelucchi, Paride
Kim, Namshin
Soldà, Giulia
Croft, Larry J
Taft, Ryan J
Rizzi, Ermanno
Askarian-Amiri, Marjan
Bonnal, Raoul J
Callari, Maurizio
Mignone, Flavio
Pesole, Graziano
Bertalot, Giovanni
Bernardi, Luigi Rossi
Albertini, Alberto
Lee, Christopher
Mattick, John S
Zucchi, Ileana
De Bellis, Gianluca
author_sort Guffanti, Alessandro
collection PubMed
description BACKGROUND: The cancer transcriptome is difficult to explore due to the heterogeneity of quantitative and qualitative changes in gene expression linked to the disease status. An increasing number of "unconventional" transcripts, such as novel isoforms, non-coding RNAs, somatic gene fusions and deletions have been associated with the tumoral state. Massively parallel sequencing techniques provide a framework for exploring the transcriptional complexity inherent to cancer with a limited laboratory and financial effort. We developed a deep sequencing and bioinformatics analysis protocol to investigate the molecular composition of a breast cancer poly(A)(+ )transcriptome. This method utilizes a cDNA library normalization step to diminish the representation of highly expressed transcripts and biology-oriented bioinformatic analyses to facilitate detection of rare and novel transcripts. RESULTS: We analyzed over 132,000 Roche 454 high-confidence deep sequencing reads from a primary human lobular breast cancer tissue specimen, and detected a range of unusual transcriptional events that were subsequently validated by RT-PCR in additional eight primary human breast cancer samples. We identified and validated one deletion, two novel ncRNAs (one intergenic and one intragenic), ten previously unknown or rare transcript isoforms and a novel gene fusion specific to a single primary tissue sample. We also explored the non-protein-coding portion of the breast cancer transcriptome, identifying thousands of novel non-coding transcripts and more than three hundred reads corresponding to the non-coding RNA MALAT1, which is highly expressed in many human carcinomas. CONCLUSION: Our results demonstrate that combining 454 deep sequencing with a normalization step and careful bioinformatic analysis facilitates the discovery and quantification of rare transcripts or ncRNAs, and can be used as a qualitative tool to characterize transcriptome complexity, revealing many hitherto unknown transcripts, splice isoforms, gene fusion events and ncRNAs, even at a relatively low sequence sampling.
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spelling pubmed-26781612009-05-07 A transcriptional sketch of a primary human breast cancer by 454 deep sequencing Guffanti, Alessandro Iacono, Michele Pelucchi, Paride Kim, Namshin Soldà, Giulia Croft, Larry J Taft, Ryan J Rizzi, Ermanno Askarian-Amiri, Marjan Bonnal, Raoul J Callari, Maurizio Mignone, Flavio Pesole, Graziano Bertalot, Giovanni Bernardi, Luigi Rossi Albertini, Alberto Lee, Christopher Mattick, John S Zucchi, Ileana De Bellis, Gianluca BMC Genomics Research Article BACKGROUND: The cancer transcriptome is difficult to explore due to the heterogeneity of quantitative and qualitative changes in gene expression linked to the disease status. An increasing number of "unconventional" transcripts, such as novel isoforms, non-coding RNAs, somatic gene fusions and deletions have been associated with the tumoral state. Massively parallel sequencing techniques provide a framework for exploring the transcriptional complexity inherent to cancer with a limited laboratory and financial effort. We developed a deep sequencing and bioinformatics analysis protocol to investigate the molecular composition of a breast cancer poly(A)(+ )transcriptome. This method utilizes a cDNA library normalization step to diminish the representation of highly expressed transcripts and biology-oriented bioinformatic analyses to facilitate detection of rare and novel transcripts. RESULTS: We analyzed over 132,000 Roche 454 high-confidence deep sequencing reads from a primary human lobular breast cancer tissue specimen, and detected a range of unusual transcriptional events that were subsequently validated by RT-PCR in additional eight primary human breast cancer samples. We identified and validated one deletion, two novel ncRNAs (one intergenic and one intragenic), ten previously unknown or rare transcript isoforms and a novel gene fusion specific to a single primary tissue sample. We also explored the non-protein-coding portion of the breast cancer transcriptome, identifying thousands of novel non-coding transcripts and more than three hundred reads corresponding to the non-coding RNA MALAT1, which is highly expressed in many human carcinomas. CONCLUSION: Our results demonstrate that combining 454 deep sequencing with a normalization step and careful bioinformatic analysis facilitates the discovery and quantification of rare transcripts or ncRNAs, and can be used as a qualitative tool to characterize transcriptome complexity, revealing many hitherto unknown transcripts, splice isoforms, gene fusion events and ncRNAs, even at a relatively low sequence sampling. BioMed Central 2009-04-20 /pmc/articles/PMC2678161/ /pubmed/19379481 http://dx.doi.org/10.1186/1471-2164-10-163 Text en Copyright © 2009 Guffanti et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Guffanti, Alessandro
Iacono, Michele
Pelucchi, Paride
Kim, Namshin
Soldà, Giulia
Croft, Larry J
Taft, Ryan J
Rizzi, Ermanno
Askarian-Amiri, Marjan
Bonnal, Raoul J
Callari, Maurizio
Mignone, Flavio
Pesole, Graziano
Bertalot, Giovanni
Bernardi, Luigi Rossi
Albertini, Alberto
Lee, Christopher
Mattick, John S
Zucchi, Ileana
De Bellis, Gianluca
A transcriptional sketch of a primary human breast cancer by 454 deep sequencing
title A transcriptional sketch of a primary human breast cancer by 454 deep sequencing
title_full A transcriptional sketch of a primary human breast cancer by 454 deep sequencing
title_fullStr A transcriptional sketch of a primary human breast cancer by 454 deep sequencing
title_full_unstemmed A transcriptional sketch of a primary human breast cancer by 454 deep sequencing
title_short A transcriptional sketch of a primary human breast cancer by 454 deep sequencing
title_sort transcriptional sketch of a primary human breast cancer by 454 deep sequencing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2678161/
https://www.ncbi.nlm.nih.gov/pubmed/19379481
http://dx.doi.org/10.1186/1471-2164-10-163
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