Identification of stable senescence‐associated reference genes
Open accessAbstract
Cellular senescence is a state of permanent cell cycle arrest activated in response to damaging stimuli. Many hallmarks associated with senescent cells are measured by quantitative real‐time PCR (qPCR). As the selection of stable reference genes for interpretation of qPCR data is often overlooked, we performed a systematic review to understand normalization strategies entailed in experiments involving senescent cells. We found that, in violation of the Minimum Information for publication of qPCR Experiments (MIQE) guidelines, most reports used only one reference gene to normalize qPCR data, and that stability of the reference genes was either not tested or not reported. To identify new and more stable reference genes in senescent fibroblasts, we analyzed the Shapiro–Wilk normality test and the coefficient of variation per gene using in public RNAseq datasets. We then compared the new reference gene candidates with commonly used ones by using both RNAseq and qPCR data. Finally, we defined the best reference genes to be used universally or in a strain‐dependent manner. This study intends to raise awareness of the instability of classical reference genes in senescent cells and to serve as a first attempt to define guidelines for the selection of more reliable normalization methods.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Suitable house-keeping genes are critical for normalization.
“It is also critical that suitable ‘house-keeping’ genes are used for normalization47.”
From Algorithmic assessment of cellular senescence in experimental and clinical specimens (2021) · cites this paper as [47]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Vandesompele, J., De Preter, K., Pattyn, F., Poppe, B., Van Roy, N., De Paepe, A., & Speleman, F. (2002) · Genome Biology · doi:10.1186/gb-2002-3-7-research0034 · Cited by 20,038 · see citing works
The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments
Bustin, S. A., Benes, V., Garson, J. A., Hellemans, J., Huggett, J., Kubista, M., Mueller, R., Nolan, T., Pfaffl, M. W., Shipley, G. L., et al. (2009) · Clinical Chemistry · doi:10.1373/clinchem.2008.112797 · Cited by 16,303 · see citing works
Andersen, C. L., Jensen, J. L., & Ørntoft, T. F. (2004) · Cancer Research · doi:10.1158/0008-5472.can-04-0496 · Cited by 7,127 · see citing works
Raise standards for preclinical cancer research
Begley, C. G., & Ellis, L. M. (2012) · Nature · doi:10.1038/483531a · Cited by 2,979 · cited 1× · see citing works
“It is important that the field makes a shift toward better laboratory practices, particularly in times in which reproducibility of reports has been questioned (Baker & Dolgin, 2017; Begley & Ellis, 2012; eLife, 2017; Gutierrez, Mauriat, Pelloux, Bellini, & Van Wuytswinkel, 2008).”
BackgroundCellular senescence: from physiology to pathology
Muñoz-Espín, D., & Serrano, M. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3823 · Cited by 2,818 · see citing works
Hallmarks of Cellular Senescence
Hernandez-Segura, A., Nehme, J., & Demaria, M. (2018) · Trends in Cell Biology · doi:10.1016/j.tcb.2018.02.001 · Cited by 2,605 · see citing works
Self-citationHuman housekeeping genes, revisited
Eisenberg, E., & Levanon, E. Y. (2013) · Trends in Genetics · doi:10.1016/j.tig.2013.05.010 · Cited by 1,249 · see citing works
Unmasking Transcriptional Heterogeneity in Senescent Cells
Hernandez-Segura, A., de Jong, T. V., Melov, S., Guryev, V., Campisi, J., & Demaria, M. (2017) · Current Biology · doi:10.1016/j.cub.2017.07.033 · Cited by 972 · see citing works
Self-citationReference genes in real-time PCR
Kozera, B., & Rapacz, M. (2013) · Journal of Applied Genetics · doi:10.1007/s13353-013-0173-x · Cited by 971 · see citing works
mTOR regulates MAPKAPK2 translation to control the senescence-associated secretory phenotype
Herranz, N., Gallage, S., Mellone, M., Wuestefeld, T., Klotz, S., Hanley, C. J., Raguz, S., Acosta, J. C., Innes, A. J., Banito, A., et al. (2015) · Nature Cell Biology · doi:10.1038/ncb3225 · Cited by 788 · see citing works
Data Normalization Strategies for MicroRNA Quantification
Schwarzenbach, H., da Silva, A. M., Calin, G., & Pantel, K. (2015) · Clinical Chemistry · doi:10.1373/clinchem.2015.239459 · Cited by 426 · see citing works
Chapman, J. R., & Waldenström, J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0141853 · Cited by 315 · see citing works
The need for transparency and good practices in the qPCR literature
Bustin, S. A., Benes, V., Garson, J., Hellemans, J., Huggett, J., Kubista, M., Mueller, R., Nolan, T., Pfaffl, M. W., Shipley, G., et al. (2013) · Nature Methods · doi:10.1038/nmeth.2697 · Cited by 281 · see citing works
Reference Gene Validation for RT-qPCR, a Note on Different Available Software Packages
Spiegelaere, W. D., Dern-Wieloch, J., Weigel, R., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0122515 · Cited by 262 · see citing works
Wiley, C. D., Flynn, J. M., Morrissey, C., Lebofsky, R., Shuga, J., Dong, X., Unger, M. A., Vijg, J., Melov, S., & Campisi, J. (2017) · Aging Cell · doi:10.1111/acel.12632 · Cited by 234 · cited 2× · see citing works
“However, studies from many research groups, including ours, have highlighted that the senescence program is complex and heterogeneous (Chen, Ozanne, & Hales, 2005; Hernandez‐Segura, De Jong, Melov, Guryev, & Campisi, 2017; Wiley et al., 2017).”
BackgroundTowards a Systematic Validation of References in Real-Time RT-PCR
Gutierrez, L., Mauriat, M., Pelloux, J., et al. (2008) · The Plant Cell · doi:10.1105/tpc.108.059774 · Cited by 222 · see citing works
Senescence-associated lncRNAs: senescence-associated long noncoding RNAs
Abdelmohsen, K., Panda, A. C., Kang, M. J., Xu, J. Z., Selimyan, R., Yoon, J., Martindale, J. L., De, S., Wood, W. H., Becker, K. G., et al. (2013) · Aging Cell · doi:10.1111/acel.12115 · Cited by 208 · see citing works
p38MAPK plays a crucial role in stromal-mediated tumorigenesis
Alspach, E., Flanagan, K. C., Luo, X., Ruhland, M. K., Huang, H., Pazolli, E., Donlin, M. J., Marsh, T., Piwnica-Worms, D., Monahan, J., et al. (2014) · Cancer Discovery · doi:10.1158/2159-8290.cd-13-0743 · Cited by 167 · see citing works
Rai, T. S., Cole, J. J., Nelson, D. M., Dikovskaya, D., Faller, W. J., Vizioli, M. G., Hewitt, R. N., Anannya, O., McBryan, T., Manoharan, I., et al. (2014) · Genes & Development · doi:10.1101/gad.247528.114 · Cited by 162 · see citing works
An inhibitory gate for state transition in cortex
Zucca, S., D’Urso, G., Pasquale, V., Vecchia, D., Pica, G., Bovetti, S., Moretti, C., Varani, S., Molano‐Mazón, M., Chiappalone, M., et al. (2017) · eLife · doi:10.7554/elife.26177 · Cited by 157 · see citing works
Histone H3.3 and its proteolytically processed form drive a cellular senescence programme
Duarte, L. F., Young, A. R. J., Wang, Z., Wu, H., Panda, T., Kou, Y., Kapoor, A., Hasson, D., Mills, N. R., Ma’ayan, A., et al. (2014) · Nature Communications · doi:10.1038/ncomms6210 · Cited by 156 · see citing works
MLL1 is essential for the senescence-associated secretory phenotype
Capell, B. C., Drake, A. M., Zhu, J., Shah, P. P., Dou, Z., Dorsey, J., Simola, D. F., Donahue, G., Sammons, M., Rai, T. S., et al. (2016) · Genes & Development · doi:10.1101/gad.271882.115 · Cited by 156 · see citing works
Cancer reproducibility project releases first results
Baker, M., & Dolgin, E. (2017) · Nature · doi:10.1038/541269a · Cited by 104 · see citing works
Dikovskaya, D., Cole, J. J., Mason, S. M., Nixon, C., Karim, S. A., McGarry, L., Clark, W., Hewitt, R. N., Sammons, M. A., Zhu, J., et al. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.07.055 · Cited by 89 · see citing works
Chorell, E., Andersson, E. K., Evans, M. L., Jain, N., Götheson, A., Ådén, J., Chapman, M. R., Almqvist, F., & Wittung-Stafshede, P. E. (2015) · PLoS ONE · doi:10.1371/journal.pone.0140194 · Cited by 88 · see citing works
Using RNA-Seq Data to Evaluate Reference Genes Suitable for Gene Expression Studies in Soybean
Yim, A. K., Wong‐Bajracharya, J. W. ‐., Ku, Y., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0136343 · Cited by 85 · see citing works
Chen, J., Ozanne, S. E., & Hales, C. N. (2005) · DNA repair · doi:10.1016/j.dnarep.2005.06.003 · Cited by 60 · see citing works
Induction and Validation of Cellular Senescence in Primary Human Cells
Hernandez‐Segura, A., Brandenburg, S. M., & Demaria, M. (2018) · Journal of Visualized Experiments · doi:10.3791/57782 · Cited by 58 · see citing works
Self-citationReference genes for measuring mRNA expression
Dundas, J. B., & Ling, M. H. (2012) · Theory in Biosciences · doi:10.1007/s12064-012-0152-5 · Cited by 57 · see citing works
Zhang, Y., Li, D., & Sun, B. (2015) · PLoS ONE · doi:10.1371/journal.pone.0123691 · Cited by 56 · see citing works
Marthandan, S., Menzel, U., Priebe, S., Groth, M., Guthke, R., Platzer, M., Hemmerich, P., Kaether, C., & Diekmann, S. (2016) · Biological Research · doi:10.1186/s40659-016-0095-2 · Cited by 39 · see citing works
(2017) · eLife · doi:10.7554/elife.23693 · Cited by 27 · see citing works
Hormetic effect of rotenone in primary human fibroblasts
Marthandan, S., Priebe, S., Groth, M., Guthke, R., Platzer, M., Hemmerich, P. H., & Diekmann, S. (2015) · Immunity & Ageing · doi:10.1186/s12979-015-0038-8 · Cited by 26 · see citing works
Induction and Validation of Cellular Senescence in Primary Human Cells
Hernandez‐Segura, A., Brandenburg, S. M., & Demaria, M. (2018) · Journal of Visualized Experiments · doi:10.3791/57782-v · Cited by 16 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
A guide to assessing cellular senescence <i>in vitro</i> and <i>in vivo</i>
González‐Gualda, E., Baker, A. G., Fruk, L., & Muñoz‐Espín, D. (2021) · The FEBS Journal · doi:10.1111/febs.15570 · Cited by 645 · see citing works
Algorithmic assessment of cellular senescence in experimental and clinical specimens
Kohli, J., Wang, B., Brandenburg, S. M., Basisty, N., Evangelou, K., Varela-Eirin, M., Campisi, J., Schilling, B., Gorgoulis, V., & Demaria, M. (2021) · Nature Protocols · doi:10.1038/s41596-021-00505-5 · Cited by 196 · see citing works
Self-citationKirsch, V., Ramge, J.-M., Schoppa, A., Ignatius, A., & Riegger, J. (2022) · Cells · doi:10.3390/cells11071106 · Cited by 47 · see citing works
Herman, A. B., Anerillas, C., Harris, S. C., Munk, R., Martindale, J. L., Yang, X., Mazan-Mamczarz, K., Zhang, Y., Heckenbach, I. J., Scheibye-Knudsen, M., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab538 · Cited by 31 · see citing works
- Authors
- Hernandez‐Segura, A., Rubingh, R., & Demaria, M.
- Affiliations
- University Medical Center Groningen (NL)
- Corresponding author
- Demaria, Marco
- ORCID
- Demaria, Marco
- Venue
- Aging Cell
- Publisher
- Wiley
- Published
- 2019-02
- Volume
- 18
- Issue
- 2
- Pages
- e12911-e12911
- ISSN
- 1474-9718 (ISSN-L)
- 1474-9726
- PMC
- PMC6413663
- OpenAlex
- W2911885304
- Cited by
- 54
- References
- 34
- Citations by year
- 2026: 2 · 2025: 8 · 2024: 13 · 2023: 6 · 2022: 7 · 2021: 11 · 2020: 5 · 2019: 2
- FWCI
- 2.07
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Aging Cell (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion, cc-by)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
- Funders
- KWF Kankerbestrijding
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
- Health Sciences › Medicine › Physiology › Telomeres, Telomerase, and Senescence
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- cellular senescence, reference genes, gene expression normalization, qPCR normalization, senescent fibroblasts, MIQE guidelines, reference gene stability, RNA-seq, coefficient of variation
- MeSH terms
- Fibroblasts, Humans, Reference Standards, Cellular Senescence, Sequence Analysis, RNA, Real-Time Polymerase Chain Reaction
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
