ArticlePloS one2013
RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
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- A transcriptomic based deconvolution framework for assessing differentiation stages and drug responses of AML.NPJ precision oncology · 2024Article
- Mapping AML heterogeneity - multi-cohort transcriptomic analysis identifies novel clusters and divergent ex-vivo drug responses.Leukemia · 2024Article
- MAJIQlopedia: an encyclopedia of RNA splicing variations in human tissues and cancer.Nucleic acids research · 2024Article
- KMT2D Deficiency Promotes Myeloid Leukemias which Is Vulnerable to Ribosome Biogenesis Inhibition.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
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- RNAi-Mediated Screen of Primary AML Cells Nominates MDM4 as a Therapeutic Target in NK-AML withCells · 2022Article
- METTL1-mediated mMolecular cell · 2021Article
- SETBP1 overexpression acts in the place of class-defining mutations to drive FLT3-ITD-mutant AML.Blood advances · 2021Article
- Determination of novel reference genes for improving gene expression data normalization in selected canine reproductive tissues - a multistudy analysis.BMC veterinary research · 2020Article
- Whole-Transcriptome Sequencing Identifies Key Differentially Expressed mRNAs, miRNAs, lncRNAs, and circRNAs Associated with CHOL.Molecular therapy. Nucleic acids · 2020Article
- RNAmut: robust identification of somatic mutations in acute myeloid leukemia using RNA-sequencing.Haematologica · 2020Article
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Authors and funding
6 authors.
Funding
Abstract
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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