Application of housekeeping npcRNAs for quantitative expression analysis of human transcriptome by real-time PCR.

In recent years the improvements in high-throughput gene expression analysis have led to the discovery of numerous non-protein-coding RNA (npcRNA) molecules. They form an abundant class of untranslated RNAs that have shown to play a crucial role in different biochemical pathways in the cell. Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is an efficient tool to measure RNA abundance and gene expression levels in tiny amounts of material. Despite its sensitivity, the lack of appropriate internal controls necessary for accurate data analysis is a limiting factor for its application in npcRNA research. Common internal controls applied are protein-coding reference genes, also termed "housekeeping" genes (HKGs). However, their expression levels reportedly vary among tissues and different experimental conditions. Moreover, application of HKGs as reference in npcRNA expression analyses is questionable, due to the differences in biogenesis. To address the issue of optimal RT-qPCR normalizers in npcRNA analysis, we performed a systematic evaluation of 18 npcRNAs along with four common HKGs in 20 different human tissues. To determine the most suitable internal control with least expression variance, four evaluation strategies, geNORM, NormFinder, BestKeeper, and the comparative delta C(q) method, were applied. Our data strongly suggest that five npcRNAs, which we term housekeeping RNAs (HKRs), exhibit significantly better constitutive expression levels in 20 different human tissues than common HKGs. Determined HKRs are ideal candidates for RT-qPCR data normalization in human transcriptome analysis, and might also be used as reference genes irrespective of the nature of the genes under investigation.

[1]  Jörg Vogel,et al.  Experimental approaches to identify non-coding RNAs , 2006, Nucleic acids research.

[2]  P. Stadler,et al.  Mapping of conserved RNA secondary structures predicts thousands of functional noncoding RNAs in the human genome , 2005, Nature Biotechnology.

[3]  Laurent Lestrade,et al.  snoRNA-LBME-db, a comprehensive database of human H/ACA and C/D box snoRNAs , 2005, Nucleic Acids Res..

[4]  B. Bass,et al.  A starvation-induced noncoding RNA modulates expression of Dicer-regulated genes , 2008, Proceedings of the National Academy of Sciences.

[5]  P. J. Higgins,et al.  Control selection for RNA quantitation. , 2000, BioTechniques.

[6]  J. Mattick,et al.  Raising the estimate of functional human sequences. , 2007, Genome research.

[7]  Thomas D. Schmittgen,et al.  Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR. , 2000, Journal of biochemical and biophysical methods.

[8]  Claus Lindbjerg Andersen,et al.  Normalization of Real-Time Quantitative Reverse Transcription-PCR Data: A Model-Based Variance Estimation Approach to Identify Genes Suited for Normalization, Applied to Bladder and Colon Cancer Data Sets , 2004, Cancer Research.

[9]  K Dheda,et al.  Real-time RT-PCR normalisation; strategies and considerations , 2005, Genes and Immunity.

[10]  W. Filipowicz,et al.  Biogenesis of small nucleolar ribonucleoproteins. , 2002, Current opinion in cell biology.

[11]  Andrea Didier,et al.  Inhibition of Real-time Rt –pcr Quantification Due to Tissue-specific Contaminants , 2003 .

[12]  Frank Speleman,et al.  A novel and universal method for microRNA RT-qPCR data normalization , 2009, Genome Biology.

[13]  B. Cullen,et al.  Adenovirus VA1 Noncoding RNA Can Inhibit Small Interfering RNA and MicroRNA Biogenesis , 2004, Journal of Virology.

[14]  R. Terns,et al.  Non-coding RNAs: lessons from the small nuclear and small nucleolar RNAs , 2007, Nature Reviews Molecular Cell Biology.

[15]  Peter F Stadler,et al.  Fast and reliable prediction of noncoding RNAs , 2005, Proc. Natl. Acad. Sci. USA.

[16]  Jan Barciszewski,et al.  Beyond the proteome: non-coding regulatory RNAs , 2002, Genome Biology.

[17]  Tania Nolan,et al.  Quantification of mRNA using real-time RT-PCR , 2006, Nature Protocols.

[18]  Heidi J. Peltier,et al.  Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues. , 2008, RNA.

[19]  S. Thein,et al.  Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR , 2006, BMC Molecular Biology.

[20]  S. Wolin,et al.  Competition between the Rex1 exonuclease and the La protein affects both Trf4p-mediated RNA quality control and pre-tRNA maturation. , 2008, RNA.

[21]  M. Day,et al.  Real-time RT-PCR: considerations for efficient and sensitive assay design. , 2004, Journal of immunological methods.

[22]  J. Brosius,et al.  RNomenclature , 2004, RNA biology.

[23]  Michael Z Michael,et al.  Reduced accumulation of specific microRNAs in colorectal neoplasia. , 2003, Molecular cancer research : MCR.

[24]  A. Hüttenhofer,et al.  Identification of 86 candidates for small non-messenger RNAs from the archaeon Archaeoglobus fulgidus , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[25]  J. Mattick,et al.  The relationship between non-protein-coding DNA and eukaryotic complexity. , 2007, BioEssays : news and reviews in molecular, cellular and developmental biology.

[26]  Mario Pazzagli,et al.  Quantitative real-time reverse transcription polymerase chain reaction: normalization to rRNA or single housekeeping genes is inappropriate for human tissue biopsies. , 2002, Analytical biochemistry.

[27]  V. Beneš,et al.  The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. , 2009, Clinical chemistry.

[28]  J. Steitz,et al.  Epstein-Barr virus noncoding RNAs are confined to the nucleus, whereas their partner, the human La protein, undergoes nucleocytoplasmic shuttling , 2006, The Journal of cell biology.

[29]  Nigel J Walker,et al.  Tech.Sight. A technique whose time has come. , 2002, Science.

[30]  M. Pfaffl,et al.  Standardized determination of real-time PCR efficiency from a single reaction set-up. , 2003, Nucleic acids research.

[31]  Jürgen Brosius,et al.  Waste not, want not--transcript excess in multicellular eukaryotes. , 2005, Trends in genetics : TIG.

[32]  H. Lehrach,et al.  Fibroblast Growth Factor 2 Modulates Transforming Growth Factor β Signaling in Mouse Embryonic Fibroblasts and Human ESCs (hESCs) to Support hESC Self‐Renewal , 2007, Stem cells.

[33]  F. Speleman,et al.  Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes , 2002, Genome Biology.

[34]  S A Bustin,et al.  Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): trends and problems. , 2002, Journal of molecular endocrinology.

[35]  M. Pfaffl,et al.  Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper – Excel-based tool using pair-wise correlations , 2004, Biotechnology Letters.

[36]  S. P. Fodor,et al.  Large-Scale Transcriptional Activity in Chromosomes 21 and 22 , 2002, Science.

[37]  J. Mattick.  The Functional Genomics of Noncoding RNA , 2005, Science.

[38]  Yuriy Gusev,et al.  Real-time expression profiling of microRNA precursors in human cancer cell lines , 2005, Nucleic acids research.

[39]  Nigel J. Walker,et al.  A Technique Whose Time Has Come , 2002, Science.

[40]  Tariq M Rana,et al.  Small RNAs: Regulators and guardians of the genome , 2007, Journal of cellular physiology.

[41]  J. Warrington,et al.  Comparison of human adult and fetal expression and identification of 535 housekeeping/maintenance genes. , 2000, Physiological genomics.

[42]  A. Hüttenhofer,et al.  RNomics: an experimental approach that identifies 201 candidates for novel, small, non‐messenger RNAs in mouse , 2001, The EMBO journal.

[43]  J. Mattick.  RNA regulation: a new genetics? , 2004, Nature Reviews Genetics.

[44]  W. Siegert,et al.  Guideline to reference gene selection for quantitative real-time PCR. , 2004, Biochemical and biophysical research communications.

[45]  A. Sandford,et al.  Selection of reference genes for gene expression studies in human neutrophils by real-time PCR , 2005, BMC Molecular Biology.