RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.

Accurate quantification of gene expression by qRT-PCR relies on normalization against a consistently expressed control gene. However, control genes in common use often vary greatly between samples, especially in cancer. The advent of Next Generation Sequencing technology offers the possibility to be...

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Main Authors: Tara Macrae, Tobias Sargeant, Sébastien Lemieux, Josée Hébert, Eric Deneault, Guy Sauvageau
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2013-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3775772?pdf=render
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author Tara Macrae
Tobias Sargeant
Sébastien Lemieux
Josée Hébert
Eric Deneault
Guy Sauvageau
author_facet Tara Macrae
Tobias Sargeant
Sébastien Lemieux
Josée Hébert
Eric Deneault
Guy Sauvageau
author_sort Tara Macrae
collection DOAJ
description Accurate quantification of gene expression by qRT-PCR relies on normalization against a consistently expressed control gene. However, control genes in common use often vary greatly between samples, especially in cancer. The advent of Next Generation Sequencing technology offers the possibility to better select control genes with the least cell to cell variability in steady state transcript levels. Here we analyze the transcriptomes of 55 leukemia samples to identify the most consistent genes. This list is enriched for components of the proteasome (ex. PSMA1) and spliceosome (ex. SF3B2), and also includes the translation initiation factor EIF4H, and many heterogeneous nuclear ribonucleoprotein genes (ex. HNRNPL). We have validated the consistency of our new control genes in 1933 cancer and normal tissues using publically available RNA-seq data, and their usefulness in qRT-PCR analysis is clearly demonstrated.
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spelling doaj.art-57cea8ce3b4c4ad59eeec2db8db377872022-12-22T03:02:49ZengPublic Library of Science (PLoS)PLoS ONE1932-62032013-01-0189e7288410.1371/journal.pone.0072884RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.Tara MacraeTobias SargeantSébastien LemieuxJosée HébertEric DeneaultGuy SauvageauAccurate quantification of gene expression by qRT-PCR relies on normalization against a consistently expressed control gene. However, control genes in common use often vary greatly between samples, especially in cancer. The advent of Next Generation Sequencing technology offers the possibility to better select control genes with the least cell to cell variability in steady state transcript levels. Here we analyze the transcriptomes of 55 leukemia samples to identify the most consistent genes. This list is enriched for components of the proteasome (ex. PSMA1) and spliceosome (ex. SF3B2), and also includes the translation initiation factor EIF4H, and many heterogeneous nuclear ribonucleoprotein genes (ex. HNRNPL). We have validated the consistency of our new control genes in 1933 cancer and normal tissues using publically available RNA-seq data, and their usefulness in qRT-PCR analysis is clearly demonstrated.http://europepmc.org/articles/PMC3775772?pdf=render
spellingShingle Tara Macrae
Tobias Sargeant
Sébastien Lemieux
Josée Hébert
Eric Deneault
Guy Sauvageau
RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.
PLoS ONE
title RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.
title_full RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.
title_fullStr RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.
title_full_unstemmed RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.
title_short RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.
title_sort rna seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells
url http://europepmc.org/articles/PMC3775772?pdf=render
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