Skip to content
naulon

No retraction, correction or concern found when last checked on Oct 31, 2026.

What are housekeeping genes?

Chintan J. Joshi, Wenfan Ke, Anna Drangowska-Way and 2 more

PLOS Computational Biology · 2022 · CC BY

doi:10.1101/2021.02.14.431149

Abstract

The concept of “housekeeping gene” has been used for four decades but remains loosely defined. Housekeeping genes are commonly described as “essential for cellular existence regardless of their specific function in the tissue or organism”, and “stably expressed irrespective of tissue type, developmental stage, cell cycle state, or external signal”. However, experimental support for the tenet that gene essentiality is linked to stable expression across cell types, conditions, and organisms has been limited. Here we use genome-scale functional genomic screens together with bulk and single-cell sequencing technologies to test this link and optimize a quantitative and experimentally validated definition of housekeeping gene. Using the optimized definition, we identify, characterize, and provide as resources, housekeeping gene lists extracted from several human datasets, and 10 other animal species that include primates, chicken, and C . elegans . We find that stably expressed genes are not necessarily essential, and that the individual genes that are essential and stably expressed can considerably differ across organisms; yet the pathways enriched among these genes are conserved. Further, the level of conservation of housekeeping genes across the analyzed organisms captures their taxonomic groups, showing evolutionary relevance for our definition. Therefore, we present a quantitative and experimentally supported definition of housekeeping genes that can contribute to better understanding of their unique biological and evolutionary characteristics.

References 55

  1. 1.

    Eisenberg E, Levanon EY. Human housekeeping genes, revisited. Trends Genet. 2013;29: 569–574

    Not in our library10.1016/j.tig.2013.05.010

  2. 2.

    Tu Z, Wang L, Xu M, Zhou X, Chen T, Sun F. Further understanding human disease genes by comparing with housekeeping genes and other genes. BMC Genomics. 2006;7: 31

    Not in our library10.1186/1471-2164-7-31

  3. 3.

    Butte AJ, Dzau VJ, Glueck SB. Further defining housekeeping, or “maintenance,” genes Focus on “A compendium of gene expression in normal human tissues”. Physiol Genomics. 2001

    Not in our library10.1007/s10857-005-4766-0

  4. 4.

    Zhu J, He F, Hu S, Yu J. On the nature of human housekeeping genes. Trends Genet. 2008;24: 481–484

    Not in our library10.1016/j.tig.2008.08.004

  5. 5.

    Warrington JA, Nair A, Mahadevappa M, Tsyganskaya M. Comparison of human adult and fetal expression and identification of 535 housekeeping/maintenance genes. Physiol Genomics. 2000;2000: 143–147

    Not in our library10.1152/physiolgenomics.2000.2.3.143

  6. 6.

    Thellin O, Zorzi W, Lakaye B, De Borman B, Coumans B, Hennen G, et al. Housekeeping genes as internal standards: Use and limits. J Biotechnol. 1999;75: 291–295

    Not in our library10.1016/s0168-1656(99)00163-7

  7. 7.

    López-Maury L, Marguerat S, Bähler J. Tuning gene expression to changing environments: From rapid responses to evolutionary adaptation. Nature Reviews Genetics. 2008. pp. 583–593

    Not in our library10.1038/nrg2398

  8. 8.

    Zhang L, Li WH. Mammalian Housekeeping Genes Evolve More Slowly than Tissue-Specific Genes. Mol Biol Evol. 2004;21: 236–239

    Not in our library10.1093/molbev/msh010

  9. 9.

    Koonin E V. How many genes can make a cell: The minimal-gene-set concept. Annu Rev Genomics Hum Genet. 2000;1: 99–116

    Not in our library10.1146/annurev.genom.1.1.99

  10. 10.
  11. 11.

    Russo M, Natoli G, Ghisletti S. Housekeeping and tissue-specific cis-regulatory elements: Recipes for specificity and recipes for activity. 2017

    Not in our library10.1080/21541264.2017.1378158

  12. 12.
  13. 13.

    Opdam S, Richelle A, Kellman B, Li S, Zielinski DC, Lewis NE. A Systematic Evaluation of Methods for Tailoring Genome-Scale Metabolic Models. Cell Syst. 2017;4: 318–329.e6

    Not in our library10.1016/j.cels.2017.01.010

  14. 14.

    Lewis NE, Schramm G, Bordbar A, Schellenberger J, Andersen MP, Cheng JK, et al. Large-scale in silico modeling of metabolic interactions between cell types in the human brain. Nat Biotechnol. 2010;28: 1279–1285

    Not in our library10.1038/nbt.1711

  15. 15.

    Mardinoglu A, Agren R, Kampf C, Asplund A, Uhlen M, Nielsen J. Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease. Nat Commun. 2014;5: 3083

    Not in our library10.1038/ncomms4083

  16. 16.

    Shen Y, Liu J, Estiu G, Isin B, Ahn Y-Y, Lee D-S, et al. Blueprint for antimicrobial hit discovery targeting metabolic networks. Proc Natl Acad Sci U S A. 2010;107: 1082–7

    Not in our library10.1073/pnas.0909181107

  17. 17.

    Kim MK, Lun DS. Methods for integration of transcriptomic data in genome-scale metabolic models. Comput Struct Biotechnol J. 2014;11: 59–65

    Not in our library10.1016/j.csbj.2014.08.009

  18. 18.

    Cao J, Packer JS, Ramani V, Cusanovich DA, Huynh C, Daza R, et al. Comprehensive single-cell transcriptional profiling of a multicellular organism. Science. 2017;357: 661–667

    Not in our library10.1126/science.aam8940

  19. 19.

    Uhlen M, Zhang C, Lee S, Sjöstedt E, Fagerberg L, Bidkhori G, et al. A pathology atlas of the human cancer transcriptome. Science. 2017;357: eaan2507

    Not in our library10.1126/science.aan2507

  20. 20.

    Creecy JP, Conway T. Quantitative bacterial transcriptomics with RNA-seq. Curr Opin Microbiol. 2015;23: 133–40

    Not in our library10.1016/j.mib.2014.11.011

  21. 21.

    Han X, Wang R, Zhou Y, Fei L, Sun H, Lai S, et al. Mapping the Mouse Cell Atlas by Microwell-Seq. Cell. 2018;172: 1091–1107.e17

    Not in our library10.1016/j.cell.2018.02.001

  22. 22.

    Uhlen M, Fagerberg L, Hallstrom BM, Lindskog C, Oksvold P, Mardinoglu A, et al. Tissue-based map of the human proteome. Science (80-). 2015;347: 1260419–1260419

    Not in our library10.1126/science.1260419

  23. 23.

    Barbosa-Morais NL, Irimia M, Pan Q, Xiong HY, Gueroussov S, Lee LJ, et al. The Evolutionary Landscape of Alternative Splicing in Vertebrate Species. Science (80-). 2012;338: 1587–1593

    Not in our library10.1126/science.1230612

  24. 24.

    Song Q, Ando A, Jiang N, Ikeda Y, Chen ZJ. Single-cell RNA-seq analysis reveals ploidy-dependent and cell-specific transcriptome changes in Arabidopsis female gametophytes. Genome Biol. 2020;21: 178

    Not in our library10.1186/s13059-020-02094-0

  25. 25.

    Ning K, Ding C, Huang Q, Zhang W, Yang C, Liang D, et al. Transcriptome profiling revealed diverse gene expression patterns in poplar (Populus × euramericana) under different planting densities. 2019

    Not in our library10.1371/journal.pone.0217066

  26. 26.

    Breschi A, Djebali S, Gillis J, Pervouchine DD, Dobin A, Davis CA, et al. Gene-specific patterns of expression variation across organs and species. Genome Biol. 2016;17: 151

    Not in our library10.1186/s13059-016-1008-y

  27. 27.

    Yang Y, Yang Y-CT, Yuan J, Lu ZJ, Li JJ. Large-scale mapping of mammalian transcriptomes identifies conserved genes associated with different cell states. Nucleic Acids Res. 2016;45: 1657–1672

    Not in our library10.1093/nar/gkw1256

  28. 28.

    Tilli TM, Da C, Castro S, Tuszynski JA, Carels N. A strategy to identify housekeeping genes suitable for analysis in breast cancer diseases. 2016 [cited 27 Jan 2020]

    Not in our library10.1186/s12864-016-2946-1

  29. 29.

    Bartha I, Di Iulio J, Venter JC, Telenti A. Human gene essentiality. Nat Rev Genet. 2018;19: 51–62

    Not in our library10.1038/nrg.2017.75

  30. 30.

    Chen H, Zhang Z, Jiang S, Li R, Li W, Zhao C, et al. New insights on human essential genes based on integrated analysis and the construction of the HEGIAP web-based platform. Brief Bioinform. 2019;21: 1397–1410

    Not in our library10.1093/bib/bbz072

  31. 31.

    Cacheiro P, Muñoz-Fuentes V, Murray SA, Dickinson ME, Bucan M, Nutter LMJ, et al. Human and mouse essentiality screens as a resource for disease gene discovery. Nat Commun. 2020;11

    Not in our library10.1038/s41467-020-14284-2

  32. 32.

    O’Hagan S, Wright Muelas M, Day PJ, Lundberg E, Kell DB. GeneGini: Assessment via the Gini Coefficient of Reference “Housekeeping” Genes and Diverse Human Transporter Expression Profiles. Cell Syst. 2018;6: 230–244.e1

    Not in our library10.1016/j.cels.2018.01.003

  33. 33.

    Wright Muelas M, Mughal F, O’Hagan S, Day PJ, Kell DB. The role and robustness of the Gini coefficient as an unbiased tool for the selection of Gini genes for normalising expression profiling data. Sci Rep. 2019;9: 718007

    Not in our library10.1038/s41598-019-54288-7

  34. 34.

    Gini C. Measurement of Inequality of Incomes. Source Econ J. 1921.

    Not in our library

  35. 35.

    Brawand D, Soumillon M, Necsulea A, Julien P, Csárdi G, Harrigan P, et al. The evolution of gene expression levels in mammalian organs. Nature. 2011;478: 343–348

    Not in our library10.1038/nature10532

  36. 36.

    GTEx Consortium TGte. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013;45: 580–5

    Not in our library10.1038/ng.2653

  37. 37.

    Klijn C, Durinck S, Stawiski EW, Haverty PM, Jiang Z, Liu H, et al. A comprehensive transcriptional portrait of human cancer cell lines. Nat Biotechnol. 2015;33: 306–312

    Not in our library10.1038/nbt.3080

  38. 38.

    W.C R M. S, S. V, J. D. CellMiner, a systems pharmacological web-application for the NCI-60 cancerous cell-lines: Updates, data integration, and translationally relevant results. Cancer Research. 2016. p. no pagination. Available: http://cancerres.aacrjournals.org/content/76/14_Supplement/75%5Cnhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&PAGE=reference&D=emed18b&NEWS=N&AN=613611346

    Not in our library

  39. 39.

    Xiong K, la Cour Karottki KJ, Hefzi H, Li S, Grav LM, Li S, et al. An optimized genome-wide, virus-free CRISPR screen for mammalian cells. Cell Reports Methods. 2021;1: 100062

    Not in our library10.1016/j.crmeth.2021.100062

  40. 40.

    Aguirre AJ, Meyers RM, Weir BA, Vazquez F, Zhang C-Z, Ben-David U, et al. Genomic Copy Number Dictates a Gene-Independent Cell Response to CRISPR/Cas9 Targeting. Cancer Discov. 2016;6: 914–29

    Not in our library10.1158/2159-8290.cd-16-0154

  41. 41.

    Meyers RM, Bryan JG, McFarland JM, Weir BA, Sizemore AE, Xu H, et al. Computational correction of copy number effect improves specificity of CRISPR–Cas9 essentiality screens in cancer cells. Nat Genet. 2017;49: 1779–1784

    Not in our library10.1038/ng.3984

  42. 42.

    Doench JG, Fusi N, Sullender M, Hegde M, Vaimberg EW, Donovan KF, et al. Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat Biotechnol. 2016;34: 184–191

    Not in our library10.1038/nbt.3437

  43. 43.

    Škrtić M, Sriskanthadevan S, Jhas B, Gebbia M, Wang X, Wang Z, et al. Inhibition of Mitochondrial Translation as a Therapeutic Strategy for Human Acute Myeloid Leukemia. Cancer Cell. 2011;20: 674–688

    Not in our library10.1016/j.ccr.2011.10.015

  44. 44.

    Hu B, Guo Y. Inhibition of mitochondrial translation as a therapeutic strategy for human ovarian cancer to overcome chemoresistance. Biochem Biophys Res Commun. 2019;509: 373–378

    Not in our library10.1016/j.bbrc.2018.12.127

  45. 45.
  46. 46.

    Shamie I, Duttke SH, Karottki KJLC, Han CZ, Hansen AH, Hefzi H, et al. A Chinese hamster transcription start site atlas that enables targeted editing of CHO cells. NAR genomics Bioinforma. 2021;3

    Not in our library10.1093/nargab/lqab061

  47. 47.
    Do housekeeping genes exist? · 2015
    Not checked
  48. 48.

    Rubie C, Kempf K, Hans J, Su T, Tilton B, Georg T, et al. Housekeeping gene variability in normal and cancerous colorectal, pancreatic, esophageal, gastric and hepatic tissues. [cited 4 May 2022]

    Not in our library10.1016/j.mcp.2004.10.001

  49. 49.

    Papalexi E, Satija R. Single-cell RNA sequencing to explore immune cell heterogeneity. Nat Rev Immunol 2017 181. 2017;18: 35–45

    Not in our library10.1038/nri.2017.76

  50. 50.
  51. 51.

    Harzing AW. Publish or Perish. In: available from http://www.harzing.com/pop.htm [Internet]. 2007 [cited 15 Oct 2020]. Available: http://harzing.com/pop.htm.

    Not in our library

  52. 52.
  53. 53.

    Ke W, Drangowska-Way A, Katz D, Siller K, O’Rourke EJ. The ancient genetic networks of obesity: Whole-animal automated screening for conserved fat regulators. Methods in Molecular Biology. Humana Press Inc.; 2018. pp. 129–146

    Not in our library10.1007/978-1-4939-7847-2_10

  54. 54.

    Shorrocks A. Income inequality and income mobility. J Econ Theory. 1978;19: 376–393

    Not in our library10.1016/0022-0531(78)90101-1

  55. 55.

    Thomas V, Wang Y, Fan X, Bank W. Measuring Education Inequality: Gini Coefficients of Education. World. 2000; 1–37. doi: 11851138

    Not in our library10.1596/1813-9450-2525

Cited by papers we hold 1

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.