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Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples

BACKGROUND: Readthrough fusions across adjacent genes in the genome, or transcription-induced chimeras (TICs), have been estimated using expressed sequence tag (EST) libraries to involve 4-6% of all genes. Deep transcriptional sequencing (RNA-Seq) now makes it possible to study the occurrence and ex...

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Autores principales: Nacu, Serban, Yuan, Wenlin, Kan, Zhengyan, Bhatt, Deepali, Rivers, Celina Sanchez, Stinson, Jeremy, Peters, Brock A, Modrusan, Zora, Jung, Kenneth, Seshagiri, Somasekar, Wu, Thomas D
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041646/
https://www.ncbi.nlm.nih.gov/pubmed/21261984
http://dx.doi.org/10.1186/1755-8794-4-11
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author Nacu, Serban
Yuan, Wenlin
Kan, Zhengyan
Bhatt, Deepali
Rivers, Celina Sanchez
Stinson, Jeremy
Peters, Brock A
Modrusan, Zora
Jung, Kenneth
Seshagiri, Somasekar
Wu, Thomas D
author_facet Nacu, Serban
Yuan, Wenlin
Kan, Zhengyan
Bhatt, Deepali
Rivers, Celina Sanchez
Stinson, Jeremy
Peters, Brock A
Modrusan, Zora
Jung, Kenneth
Seshagiri, Somasekar
Wu, Thomas D
author_sort Nacu, Serban
collection PubMed
description BACKGROUND: Readthrough fusions across adjacent genes in the genome, or transcription-induced chimeras (TICs), have been estimated using expressed sequence tag (EST) libraries to involve 4-6% of all genes. Deep transcriptional sequencing (RNA-Seq) now makes it possible to study the occurrence and expression levels of TICs in individual samples across the genome. METHODS: We performed single-end RNA-Seq on three human prostate adenocarcinoma samples and their corresponding normal tissues, as well as brain and universal reference samples. We developed two bioinformatics methods to specifically identify TIC events: a targeted alignment method using artificial exon-exon junctions within 200,000 bp from adjacent genes, and genomic alignment allowing splicing within individual reads. We performed further experimental verification and characterization of selected TIC and fusion events using quantitative RT-PCR and comparative genomic hybridization microarrays. RESULTS: Targeted alignment against artificial exon-exon junctions yielded 339 distinct TIC events, including 32 gene pairs with multiple isoforms. The false discovery rate was estimated to be 1.5%. Spliced alignment to the genome was less sensitive, finding only 18% of those found by targeted alignment in 33-nt reads and 59% of those in 50-nt reads. However, spliced alignment revealed 30 cases of TICs with intervening exons, in addition to distant inversions, scrambled genes, and translocations. Our findings increase the catalog of observed TIC gene pairs by 66%. We verified 6 of 6 predicted TICs in all prostate samples, and 2 of 5 predicted novel distant gene fusions, both private events among 54 prostate tumor samples tested. Expression of TICs correlates with that of the upstream gene, which can explain the prostate-specific pattern of some TIC events and the restriction of the SLC45A3-ELK4 e4-e2 TIC to ERG-negative prostate samples, as confirmed in 20 matched prostate tumor and normal samples and 9 lung cancer cell lines. CONCLUSIONS: Deep transcriptional sequencing and analysis with targeted and spliced alignment methods can effectively identify TIC events across the genome in individual tissues. Prostate and reference samples exhibit a wide range of TIC events, involving more genes than estimated previously using ESTs. Tissue specificity of TIC events is correlated with expression patterns of the upstream gene. Some TIC events, such as MSMB-NCOA4, may play functional roles in cancer.
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spelling pubmed-30416462011-02-19 Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples Nacu, Serban Yuan, Wenlin Kan, Zhengyan Bhatt, Deepali Rivers, Celina Sanchez Stinson, Jeremy Peters, Brock A Modrusan, Zora Jung, Kenneth Seshagiri, Somasekar Wu, Thomas D BMC Med Genomics Research Article BACKGROUND: Readthrough fusions across adjacent genes in the genome, or transcription-induced chimeras (TICs), have been estimated using expressed sequence tag (EST) libraries to involve 4-6% of all genes. Deep transcriptional sequencing (RNA-Seq) now makes it possible to study the occurrence and expression levels of TICs in individual samples across the genome. METHODS: We performed single-end RNA-Seq on three human prostate adenocarcinoma samples and their corresponding normal tissues, as well as brain and universal reference samples. We developed two bioinformatics methods to specifically identify TIC events: a targeted alignment method using artificial exon-exon junctions within 200,000 bp from adjacent genes, and genomic alignment allowing splicing within individual reads. We performed further experimental verification and characterization of selected TIC and fusion events using quantitative RT-PCR and comparative genomic hybridization microarrays. RESULTS: Targeted alignment against artificial exon-exon junctions yielded 339 distinct TIC events, including 32 gene pairs with multiple isoforms. The false discovery rate was estimated to be 1.5%. Spliced alignment to the genome was less sensitive, finding only 18% of those found by targeted alignment in 33-nt reads and 59% of those in 50-nt reads. However, spliced alignment revealed 30 cases of TICs with intervening exons, in addition to distant inversions, scrambled genes, and translocations. Our findings increase the catalog of observed TIC gene pairs by 66%. We verified 6 of 6 predicted TICs in all prostate samples, and 2 of 5 predicted novel distant gene fusions, both private events among 54 prostate tumor samples tested. Expression of TICs correlates with that of the upstream gene, which can explain the prostate-specific pattern of some TIC events and the restriction of the SLC45A3-ELK4 e4-e2 TIC to ERG-negative prostate samples, as confirmed in 20 matched prostate tumor and normal samples and 9 lung cancer cell lines. CONCLUSIONS: Deep transcriptional sequencing and analysis with targeted and spliced alignment methods can effectively identify TIC events across the genome in individual tissues. Prostate and reference samples exhibit a wide range of TIC events, involving more genes than estimated previously using ESTs. Tissue specificity of TIC events is correlated with expression patterns of the upstream gene. Some TIC events, such as MSMB-NCOA4, may play functional roles in cancer. BioMed Central 2011-01-24 /pmc/articles/PMC3041646/ /pubmed/21261984 http://dx.doi.org/10.1186/1755-8794-4-11 Text en Copyright ©2011 Nacu 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
Nacu, Serban
Yuan, Wenlin
Kan, Zhengyan
Bhatt, Deepali
Rivers, Celina Sanchez
Stinson, Jeremy
Peters, Brock A
Modrusan, Zora
Jung, Kenneth
Seshagiri, Somasekar
Wu, Thomas D
Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples
title Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples
title_full Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples
title_fullStr Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples
title_full_unstemmed Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples
title_short Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples
title_sort deep rna sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3041646/
https://www.ncbi.nlm.nih.gov/pubmed/21261984
http://dx.doi.org/10.1186/1755-8794-4-11
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