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Transcriptome sequencing of the Microarray Quality Control (MAQC) RNA reference samples using next generation sequencing

BACKGROUND: Transcriptome sequencing using next-generation sequencing platforms will soon be competing with DNA microarray technologies for global gene expression analysis. As a preliminary evaluation of these promising technologies, we performed deep sequencing of cDNA synthesized from the Microarr...

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Autores principales: Mane, Shrinivasrao P, Evans, Clive, Cooper, Kristal L, Crasta, Oswald R, Folkerts, Otto, Hutchison, Stephen K, Harkins, Timothy T, Thierry-Mieg, Danielle, Thierry-Mieg, Jean, Jensen, Roderick V
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2707382/
https://www.ncbi.nlm.nih.gov/pubmed/19523228
http://dx.doi.org/10.1186/1471-2164-10-264
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author Mane, Shrinivasrao P
Evans, Clive
Cooper, Kristal L
Crasta, Oswald R
Folkerts, Otto
Hutchison, Stephen K
Harkins, Timothy T
Thierry-Mieg, Danielle
Thierry-Mieg, Jean
Jensen, Roderick V
author_facet Mane, Shrinivasrao P
Evans, Clive
Cooper, Kristal L
Crasta, Oswald R
Folkerts, Otto
Hutchison, Stephen K
Harkins, Timothy T
Thierry-Mieg, Danielle
Thierry-Mieg, Jean
Jensen, Roderick V
author_sort Mane, Shrinivasrao P
collection PubMed
description BACKGROUND: Transcriptome sequencing using next-generation sequencing platforms will soon be competing with DNA microarray technologies for global gene expression analysis. As a preliminary evaluation of these promising technologies, we performed deep sequencing of cDNA synthesized from the Microarray Quality Control (MAQC) reference RNA samples using Roche's 454 Genome Sequencer FLX. RESULTS: We generated more that 3.6 million sequence reads of average length 250 bp for the MAQC A and B samples and introduced a data analysis pipeline for translating cDNA read counts into gene expression levels. Using BLAST, 90% of the reads mapped to the human genome and 64% of the reads mapped to the RefSeq database of well annotated genes with e-values ≤ 10(-20). We measured gene expression levels in the A and B samples by counting the numbers of reads that mapped to individual RefSeq genes in multiple sequencing runs to evaluate the MAQC quality metrics for reproducibility, sensitivity, specificity, and accuracy and compared the results with DNA microarrays and Quantitative RT-PCR (QRTPCR) from the MAQC studies. In addition, 88% of the reads were successfully aligned directly to the human genome using the AceView alignment programs with an average 90% sequence similarity to identify 137,899 unique exon junctions, including 22,193 new exon junctions not yet contained in the RefSeq database. CONCLUSION: Using the MAQC metrics for evaluating the performance of gene expression platforms, the ExpressSeq results for gene expression levels showed excellent reproducibility, sensitivity, and specificity that improved systematically with increasing shotgun sequencing depth, and quantitative accuracy that was comparable to DNA microarrays and QRTPCR. In addition, a careful mapping of the reads to the genome using the AceView alignment programs shed new light on the complexity of the human transcriptome including the discovery of thousands of new splice variants.
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spelling pubmed-27073822009-07-09 Transcriptome sequencing of the Microarray Quality Control (MAQC) RNA reference samples using next generation sequencing Mane, Shrinivasrao P Evans, Clive Cooper, Kristal L Crasta, Oswald R Folkerts, Otto Hutchison, Stephen K Harkins, Timothy T Thierry-Mieg, Danielle Thierry-Mieg, Jean Jensen, Roderick V BMC Genomics Research Article BACKGROUND: Transcriptome sequencing using next-generation sequencing platforms will soon be competing with DNA microarray technologies for global gene expression analysis. As a preliminary evaluation of these promising technologies, we performed deep sequencing of cDNA synthesized from the Microarray Quality Control (MAQC) reference RNA samples using Roche's 454 Genome Sequencer FLX. RESULTS: We generated more that 3.6 million sequence reads of average length 250 bp for the MAQC A and B samples and introduced a data analysis pipeline for translating cDNA read counts into gene expression levels. Using BLAST, 90% of the reads mapped to the human genome and 64% of the reads mapped to the RefSeq database of well annotated genes with e-values ≤ 10(-20). We measured gene expression levels in the A and B samples by counting the numbers of reads that mapped to individual RefSeq genes in multiple sequencing runs to evaluate the MAQC quality metrics for reproducibility, sensitivity, specificity, and accuracy and compared the results with DNA microarrays and Quantitative RT-PCR (QRTPCR) from the MAQC studies. In addition, 88% of the reads were successfully aligned directly to the human genome using the AceView alignment programs with an average 90% sequence similarity to identify 137,899 unique exon junctions, including 22,193 new exon junctions not yet contained in the RefSeq database. CONCLUSION: Using the MAQC metrics for evaluating the performance of gene expression platforms, the ExpressSeq results for gene expression levels showed excellent reproducibility, sensitivity, and specificity that improved systematically with increasing shotgun sequencing depth, and quantitative accuracy that was comparable to DNA microarrays and QRTPCR. In addition, a careful mapping of the reads to the genome using the AceView alignment programs shed new light on the complexity of the human transcriptome including the discovery of thousands of new splice variants. BioMed Central 2009-06-12 /pmc/articles/PMC2707382/ /pubmed/19523228 http://dx.doi.org/10.1186/1471-2164-10-264 Text en Copyright © 2009 Mane 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
Mane, Shrinivasrao P
Evans, Clive
Cooper, Kristal L
Crasta, Oswald R
Folkerts, Otto
Hutchison, Stephen K
Harkins, Timothy T
Thierry-Mieg, Danielle
Thierry-Mieg, Jean
Jensen, Roderick V
Transcriptome sequencing of the Microarray Quality Control (MAQC) RNA reference samples using next generation sequencing
title Transcriptome sequencing of the Microarray Quality Control (MAQC) RNA reference samples using next generation sequencing
title_full Transcriptome sequencing of the Microarray Quality Control (MAQC) RNA reference samples using next generation sequencing
title_fullStr Transcriptome sequencing of the Microarray Quality Control (MAQC) RNA reference samples using next generation sequencing
title_full_unstemmed Transcriptome sequencing of the Microarray Quality Control (MAQC) RNA reference samples using next generation sequencing
title_short Transcriptome sequencing of the Microarray Quality Control (MAQC) RNA reference samples using next generation sequencing
title_sort transcriptome sequencing of the microarray quality control (maqc) rna reference samples using next generation sequencing
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2707382/
https://www.ncbi.nlm.nih.gov/pubmed/19523228
http://dx.doi.org/10.1186/1471-2164-10-264
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