Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Perspective
  • Published:

Overcoming challenges and dogmas to understand the functions of pseudogenes

Nature Reviews Genetics volume 21, pages 191–201 (2020)Cite this article

Subjects

Abstract

Pseudogenes are defined as regions of the genome that contain defective copies of genes. They exist across almost all forms of life, and in mammalian genomes are annotated in similar numbers to recognized protein-coding genes. Although often presumed to lack function, growing numbers of pseudogenes are being found to play important biological roles. In consideration of their evolutionary origins and inherent limitations in genome annotation practices, we posit that pseudogenes have been classified on a scientifically unsubstantiated basis. We reflect that a broad misunderstanding of pseudogenes, perpetuated in part by the pejorative inference of the ‘pseudogene’ label, has led to their frequent dismissal from functional assessment and exclusion from genomic analyses. With the advent of technologies that simplify the study of pseudogenes, we propose that an objective reassessment of these genomic elements will reveal valuable insights into genome function and evolution.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Major classes of eukaryotic pseudogenes.
Fig. 2: Examples of pseudogene functions.
Fig. 3: Challenges and solutions to understanding pseudogene functions.
Fig. 4: CRISPR–Cas9-based approaches to understanding pseudogene functions.

Similar content being viewed by others

References

  1. Jacq, C., Miller, J. R. & Brownlee, G. G. A pseudogene structure in 5S DNA of Xenopus laevis. Cell 12, 109–120 (1977).

    Article  CAS  PubMed  Google Scholar 

  2. Vierna, J., Wehner, S., Höner zu Siederdissen, C., Martínez-Lage, A. & Marz, M. Systematic analysis and evolution of 5S ribosomal DNA in metazoans. Heredity 111, 410–421 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Vanin, E. F. Processed pseudogenes: characteristics and evolution. Annu. Rev. Genet. 19, 253–272 (1985).

    Article  CAS  PubMed  Google Scholar 

  4. Esnault, C., Maestre, J. & Heidmann, T. Human LINE retrotransposons generate processed pseudogenes. Nat. Genet. 24, 363–367 (2000).

    Article  CAS  PubMed  Google Scholar 

  5. Pei, B. et al. The GENCODE pseudogene resource. Genome Biol. 13, R51 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Frankish, A. et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res. 47, D766–D773 (2019).

    Article  CAS  PubMed  Google Scholar 

  7. Zhang, Z., Harrison, P. M., Liu, Y. & Gerstein, M. Millions of years of evolution preserved: a comprehensive catalog of the processed pseudogenes in the human genome. Genome Res. 13, 2541–2558 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Baertsch, R., Diekhans, M., Kent, W. J., Haussler, D. & Brosius, J. Retrocopy contributions to the evolution of the human genome. BMC Genomics 9, 466 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Navarro, F. C. P. & Galante, P. A. F. RCPedia: a database of retrocopied genes. Bioinformatics 29, 1235–1237 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Kaessmann, H., Vinckenbosch, N. & Long, M. RNA-based gene duplication: mechanistic and evolutionary insights. Nat. Rev. Genet. 10, 19–31 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kaessmann, H. Origins, evolution, and phenotypic impact of new genes. Genome Res. 20, 1313–1326 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Ewing, A. D. et al. Retrotransposition of gene transcripts leads to structural variation in mammalian genomes. Genome Biol. 14, R22 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  13. Richardson, S. R., Salvador-Palomeque, C. & Faulkner, G. J. Diversity through duplication: whole-genome sequencing reveals novel gene retrocopies in the human population. Bioessays 36, 475–481 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Abyzov, A. et al. Analysis of variable retroduplications in human populations suggests coupling of retrotransposition to cell division. Genome Res. 23, 2042–2052 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Schrider, D. R. et al. Gene copy-number polymorphism caused by retrotransposition in humans. PLOS Genet. 9, e1003242 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sisu, C. et al. Comparative analysis of pseudogenes across three phyla. Proc. Natl Acad. Sci. USA 111, 13361–13366 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Wang, T. et al. Identification and characterization of essential genes in the human genome. Science 350, 1096–1101 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Tsherniak, A. et al. Defining a cancer dependency map. Cell 170, 564–576.e16 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Ghandi, M. et al. Next-generation characterization of the Cancer Cell Line Encyclopedia. Nature 569, 503–508 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Zhang, Z. & Gerstein, M. Large-scale analysis of pseudogenes in the human genome. Curr. Opin. Genet. Dev. 14, 328–335 (2004).

    Article  CAS  PubMed  Google Scholar 

  21. van Baren, M. J. & Brent, M. R. Iterative gene prediction and pseudogene removal improves genome annotation. Genome Res. 16, 678–685 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Torrents, D., Suyama, M., Zdobnov, E. & Bork, P. A genome-wide survey of human pseudogenes. Genome Res. 13, 2559–2567 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Zhang, Z. et al. PseudoPipe: an automated pseudogene identification pipeline. Bioinformatics 22, 1437–1439 (2006).

    Article  CAS  PubMed  Google Scholar 

  24. Frith, M. C. et al. Pseudo-messenger RNA: phantoms of the transcriptome. PLOS Genet. 2, e23 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Vinckenbosch, N., Dupanloup, I. & Kaessmann, H. Evolutionary fate of retroposed gene copies in the human genome. Proc. Natl Acad. Sci. USA 103, 3220–3225 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Jorquera, R. et al. SinEx DB: a database for single exon coding sequences in mammalian genomes. Database (Oxford) 2016, baw095 (2016).

    Article  CAS  Google Scholar 

  27. Hurst, L. D. The Ka/Ks ratio: diagnosing the form of sequence evolution. Trends Genet. 18, 486 (2002).

    Article  PubMed  Google Scholar 

  28. Chiang, J. J. et al. Viral unmasking of cellular 5S rRNA pseudogene transcripts induces RIG-I-mediated immunity. Nat. Immunol. 19, 53–62 (2018).

    Article  CAS  PubMed  Google Scholar 

  29. Pink, R. C. et al. Pseudogenes: pseudo-functional or key regulators in health and disease? RNA 17, 792–798 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Pink, R. C. & Carter, D. R. F. Pseudogenes as regulators of biological function. Essays Biochem. 54, 103–112 (2013).

    Article  CAS  PubMed  Google Scholar 

  31. Kovalenko, T. F. & Patrushev, L. I. Pseudogenes as functionally significant elements of the genome. Biochemistry 83, 1332–1349 (2018).

    CAS  PubMed  Google Scholar 

  32. McCarrey, J. R. & Thomas, K. Human testis-specific PGK gene lacks introns and possesses characteristics of a processed gene. Nature 326, 501–505 (1987).

    Article  CAS  PubMed  Google Scholar 

  33. McCarrey, J. R. Nucleotide sequence of the promoter region of a tissue-specific human retroposon: comparison with its housekeeping progenitor. Gene 61, 291–298 (1987).

    Article  CAS  PubMed  Google Scholar 

  34. Sayah, D. M., Sokolskaja, E., Berthoux, L. & Luban, J. Cyclophilin A retrotransposition into TRIM5 explains owl monkey resistance to HIV-1. Nature 430, 569–573 (2004).

    Article  CAS  PubMed  Google Scholar 

  35. Burki, F. & Kaessmann, H. Birth and adaptive evolution of a hominoid gene that supports high neurotransmitter flux. Nat. Genet. 36, 1061–1063 (2004).

    Article  CAS  PubMed  Google Scholar 

  36. Hayashi, H. et al. The OCT4 pseudogene POU5F1B is amplified and promotes an aggressive phenotype in gastric cancer. Oncogene 34, 199–208 (2015).

    Article  CAS  PubMed  Google Scholar 

  37. Suzuki, I. K. et al. Human-specific NOTCH2NL genes expand cortical neurogenesis through Delta/Notch regulation. Cell 173, 1370–1384.e16 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Fiddes, I. T. et al. Human-specific NOTCH2NL genes affect notch signaling and cortical neurogenesis. Cell 173, 1356–1369.e22 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Dennis, M. Y. et al. Evolution of human-specific neural SRGAP2 genes by incomplete segmental duplication. Cell 149, 912–922 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Charrier, C. et al. Inhibition of SRGAP2 function by its human-specific paralogs induces neoteny during spine maturation. Cell 149, 923–935 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Korneev, S. A., Park, J. H. & O’Shea, M. Neuronal expression of neural nitric oxide synthase (nNOS) protein is suppressed by an antisense RNA transcribed from an NOS pseudogene. J. Neurosci. 19, 7711–7720 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Tam, O. H. et al. Pseudogene-derived small interfering RNAs regulate gene expression in mouse oocytes. Nature 453, 534–538 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Watanabe, T. et al. Endogenous siRNAs from naturally formed dsRNAs regulate transcripts in mouse oocytes. Nature 453, 539–543 (2008).

    Article  CAS  PubMed  Google Scholar 

  44. Rapicavoli, N. A. et al. A mammalian pseudogene lncRNA at the interface of inflammation and anti-inflammatory therapeutics. eLife 2, e00762 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  45. Poliseno, L. et al. A coding-independent function of gene and pseudogene mRNAs regulates tumour biology. Nature 465, 1033–1038 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Karreth, F. A. et al. The BRAF pseudogene functions as a competitive endogenous RNA and induces lymphoma in vivo. Cell 161, 319–332 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Salmena, L., Poliseno, L., Tay, Y., Kats, L. & Pandolfi, P. P. A ceRNA hypothesis: the Rosetta Stone of a hidden RNA language? Cell 146, 353–358 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Denzler, R., Agarwal, V., Stefano, J., Bartel, D. P. & Stoffel, M. Assessing the ceRNA hypothesis with quantitative measurements of miRNA and target abundance. Mol. Cell 54, 766–776 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Thomson, D. W. & Dinger, M. E. Endogenous microRNA sponges: evidence and controversy. Nat. Rev. Genet. 17, 272–283 (2016).

    Article  CAS  PubMed  Google Scholar 

  50. Huang, P. et al. Comparative analysis of three-dimensional chromosomal architecture identifies a novel fetal hemoglobin regulatory element. Genes Dev. 31, 1704–1713 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Vergés, L. et al. An exploratory study of predisposing genetic factors for DiGeorge/velocardiofacial syndrome. Sci. Rep. 7, 40031 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Lai, J. et al. A variant of the KLK4 gene is expressed as a cis sense–antisense chimeric transcript in prostate cancer cells. RNA 16, 1156–1166 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Chakravarthi, B. V. et al. Pseudogene associated recurrent gene fusion in prostate cancer. Neoplasia 21, 989–1002 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Bischof, J. M. et al. Genome-wide identification of pseudogenes capable of disease-causing gene conversion. Hum. Mutat. 27, 545–552 (2006).

    Article  CAS  PubMed  Google Scholar 

  55. Rygiel, A. M. et al. Gene conversion between cationic trypsinogen (PRSS1) and the pseudogene trypsinogen 6 (PRSS3P2) in patients with chronic pancreatitis. Hum. Mutat. 36, 350–356 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Concolino, P. & Costella, A. Congenital adrenal hyperplasia (CAH) due to 21-hydroxylase deficiency: a comprehensive focus on 233 pathogenic variants of CYP21A2 gene. Mol. Diagn. Ther. 22, 261–280 (2018).

    Article  CAS  PubMed  Google Scholar 

  57. Watnick, T., Gandolph, M. A., Weber, H., Neumann, H. P. & Germino, G. G. Gene conversion is a likely cause of mutation in PKD1. Hum. Mol. Genet. 7, 1239–1243 (1998).

    Article  CAS  PubMed  Google Scholar 

  58. Vanita et al. A unique form of autosomal dominant cataract explained by gene conversion between β-crystallin B2 and its pseudogene. J. Med. Genet. 38, 392–396 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Habib, A. M. et al. Microdeletion in a FAAH pseudogene identified in a patient with high anandamide concentrations and pain insensitivity. Br. J. Anaesth. 123, e249–e253 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Ali, H. et al. PKD1 duplicated regions limit clinical utility of whole exome sequencing for genetic diagnosis of autosomal dominant polycystic kidney disease. Sci. Rep. 9, 4141 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Gallagher, M. D. & Chen-Plotkin, A. S. The post-GWAS era: from association to function. Am. J. Hum. Genet. 102, 717–730 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Bartonicek, N. et al. Intergenic disease-associated regions are abundant in novel transcripts. Genome Biol. 18, 241 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. GTEx Consortium et al. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).

    Article  PubMed Central  Google Scholar 

  64. Marques, A. C., Dupanloup, I., Vinckenbosch, N., Reymond, A. & Kaessmann, H. Emergence of young human genes after a burst of retroposition in primates. PLOS Biol. 3, e357 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Kabza, M., Ciomborowska, J. & Makałowska, I. RetrogeneDB—a database of animal retrogenes. Mol. Biol. Evol. 31, 1646–1648 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. van Heesch, S. et al. The translational landscape of the human heart. Cell 178, 242–260.e29 (2019).

    Article  PubMed  CAS  Google Scholar 

  67. Kim, M.-S. et al. A draft map of the human proteome. Nature 509, 575–581 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Ji, Z., Song, R., Regev, A. & Struhl, K. Many lncRNAs, 5′UTRs, and pseudogenes are translated and some are likely to express functional proteins. eLife 4, e08890 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Brosch, M. et al. Shotgun proteomics aids discovery of novel protein-coding genes, alternative splicing, and ‘resurrected’ pseudogenes in the mouse genome. Genome Res. 21, 756–767 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Doolittle, W. F. We simply cannot go on being so vague about ‘function’. Genome Biol. 19, 223 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  71. Kafri, R., Springer, M. & Pilpel, Y. Genetic redundancy: new tricks for old genes. Cell 136, 389–392 (2009).

    Article  CAS  PubMed  Google Scholar 

  72. Duret, L., Chureau, C., Samain, S., Weissenbach, J. & Avner, P. The Xist RNA gene evolved in eutherians by pseudogenization of a protein-coding gene. Science 312, 1653–1655 (2006).

    Article  CAS  PubMed  Google Scholar 

  73. Hezroni, H. et al. A subset of conserved mammalian long non-coding RNAs are fossils of ancestral protein-coding genes. Genome Biol. 18, 162 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  74. Liu, W.-H., Tsai, Z. T.-Y. & Tsai, H.-K. Comparative genomic analyses highlight the contribution of pseudogenized protein-coding genes to human lincRNAs. BMC Genomics 18, 786 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  75. Carninci, P. et al. The transcriptional landscape of the mammalian genome. Science 309, 1559–1563 (2005).

    Article  CAS  PubMed  Google Scholar 

  76. Mattick, J. S. Challenging the dogma: the hidden layer of non-protein-coding RNAs in complex organisms. Bioessays 25, 930–939 (2003).

    Article  CAS  PubMed  Google Scholar 

  77. Gloss, B. S. & Dinger, M. E. The specificity of long noncoding RNA expression. Biochim. Biophys. Acta 1859, 16–22 (2016).

    Article  CAS  PubMed  Google Scholar 

  78. Clark, M. B. et al. Quantitative gene profiling of long noncoding RNAs with targeted RNA sequencing. Nat. Methods 12, 339–342 (2015).

    Article  CAS  PubMed  Google Scholar 

  79. Mercer, T. R., Dinger, M. E., Sunkin, S. M., Mehler, M. F. & Mattick, J. S. Specific expression of long noncoding RNAs in the mouse brain. Proc. Natl Acad. Sci. USA 105, 716–721 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Dinger, M. E. et al. Long noncoding RNAs in mouse embryonic stem cell pluripotency and differentiation. Genome Res. 18, 1433–1445 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Martianov, I., Ramadass, A., Serra Barros, A., Chow, N. & Akoulitchev, A. Repression of the human dihydrofolate reductase gene by a non-coding interfering transcript. Nature 445, 666–670 (2007).

    Article  CAS  PubMed  Google Scholar 

  82. Rinn, J. L. et al. Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs. Cell 129, 1311–1323 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Morris, K. V. & Mattick, J. S. The rise of regulatory RNA. Nat. Rev. Genet. 15, 423–437 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Cabili, M. N. et al. Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses. Genes Dev. 25, 1915–1927 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Pang, K. C. et al. Genome-wide identification of long noncoding RNAs in CD8+ T cells. J. Immunol. 182, 7738–7748 (2009).

    Article  CAS  PubMed  Google Scholar 

  86. Sunwoo, H. et al. MEN ε/β nuclear-retained non-coding RNAs are up-regulated upon muscle differentiation and are essential components of paraspeckles. Genome Res. 19, 347–359 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Mercer, T. R. et al. Long noncoding RNAs in neuronal–glial fate specification and oligodendrocyte lineage maturation. BMC Neurosci. 11, 14 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  88. Lockhart, D. J. et al. Expression monitoring by hybridization to high-density oligonucleotide arrays. Nat. Biotechnol. 14, 1675–1680 (1996).

    Article  CAS  PubMed  Google Scholar 

  89. Millson, A. et al. Processed pseudogene confounding deletion/duplication assays for SMAD4. J. Mol. Diagn. 17, 576–582 (2015).

    Article  CAS  PubMed  Google Scholar 

  90. Cloonan, N. et al. Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nat. Methods 5, 613–619 (2008).

    Article  CAS  PubMed  Google Scholar 

  91. Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L. & Wold, B. Mapping and quantifying mammalian transcriptomes by RNA-seq. Nat. Methods 5, 621–628 (2008).

    Article  CAS  PubMed  Google Scholar 

  92. Kalyana-Sundaram, S. et al. Expressed pseudogenes in the transcriptional landscape of human cancers. Cell 149, 1622–1634 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Oikonomopoulos, S., Wang, Y. C., Djambazian, H., Badescu, D. & Ragoussis, J. Benchmarking of the Oxford Nanopore MinION sequencing for quantitative and qualitative assessment of cDNA populations. Sci. Rep. 6, 31602 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Au, K. F. et al. Characterization of the human ESC transcriptome by hybrid sequencing. Proc. Natl Acad. Sci. USA 110, E4821–E4830 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Garalde, D. R. et al. Highly parallel direct RNA sequencing on an array of nanopores. Nat. Methods 15, 201–206 (2018).

    Article  CAS  PubMed  Google Scholar 

  96. Jinek, M. et al. RNA-programmed genome editing in human cells. eLife 2, e00471 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  97. Mali, P. et al. RNA-guided human genome engineering via Cas9. Science 339, 823–826 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Cong, L. et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Anderson, E. M. et al. Systematic analysis of CRISPR–Cas9 mismatch tolerance reveals low levels of off-target activity. J. Biotechnol. 211, 56–65 (2015).

    Article  CAS  PubMed  Google Scholar 

  100. Zhang, X.-H., Tee, L. Y., Wang, X.-G., Huang, Q.-S. & Yang, S.-H. Off-target effects in CRISPR/Cas9-mediated genome engineering. Mol. Ther. Nucleic Acids 4, e264 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Kim, D. et al. Genome-wide analysis reveals specificities of Cpf1 endonucleases in human cells. Nat. Biotechnol. 34, 863–868 (2016).

    Article  CAS  PubMed  Google Scholar 

  102. Kleinstiver, B. P. et al. Genome-wide specificities of CRISPR–Cas Cpf1 nucleases in human cells. Nat. Biotechnol. 34, 869–874 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Kocak, D. D. et al. Increasing the specificity of CRISPR systems with engineered RNA secondary structures. Nat. Biotechnol. 37, 657–666 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  104. Groff, A. F. et al. In vivo characterization of Linc-p21 reveals functional cis-regulatory DNA elements. Cell Rep. 16, 2178–2186 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Bassett, A. R. et al. Considerations when investigating lncRNA function in vivo. eLife 3, e03058 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  106. Qi, L. S. et al. Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression. Cell 152, 1173–1183 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Yeo, N. C. et al. An enhanced CRISPR repressor for targeted mammalian gene regulation. Nat. Methods 15, 611–616 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Gilbert, L. A. et al. Genome-scale CRISPR-mediated control of gene repression and activation. Cell 159, 647–661 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  109. Cheng, A. W. et al. Multiplexed activation of endogenous genes by CRISPR-on, an RNA-guided transcriptional activator system. Cell Res. 23, 1163–1171 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Endrizzi, K. et al. Discriminative quantification of cytochrome P4502D6 and 2D7/8 pseudogene expression by TaqMan real-time reverse transcriptase polymerase chain reaction. Anal. Biochem. 300, 121–131 (2002).

    Article  CAS  PubMed  Google Scholar 

  111. Simon, M. D. et al. The genomic binding sites of a noncoding RNA. Proc. Natl Acad. Sci. USA 108, 20497–20502 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Chu, C., Qu, K., Zhong, F. L., Artandi, S. E. & Chang, H. Y. Genomic maps of long noncoding RNA occupancy reveal principles of RNA–chromatin interactions. Mol. Cell 44, 667–678 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Cheetham, S. W. & Brand, A. H. RNA-DamID reveals cell-type-specific binding of roX RNAs at chromatin-entry sites. Nat. Struct. Mol. Biol. 25, 109–114 (2018).

    Article  CAS  PubMed  Google Scholar 

  114. Li, X. et al. GRID-seq reveals the global RNA–chromatin interactome. Nat. Biotechnol. 35, 940–950 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Bell, J. C. et al. Chromatin-associated RNA sequencing (ChAR-seq) maps genome-wide RNA-to-DNA contacts. eLife 7, e27024 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  116. Bonetti, A. et al. RADICL-seq identifies general and cell type-specific principles of genome-wide RNA–chromatin interactions. Preprint at bioRxiv https://doi.org/10.1101/681924 (2019).

  117. Lu, Z. et al. RNA duplex map in living cells reveals higher-order transcriptome structure. Cell 165, 1267–1279 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Kuhn, T. S. The Structure of Scientific Revolutions (Univ. Chicago Press, 1962).

  120. Stanier, R. Y. & van Niel, C. B. The concept of a bacterium. Arch. Mikrobiol. 42, 17–35 (1962).

    Article  CAS  PubMed  Google Scholar 

  121. Woese, C. R. A new biology for a new century. Microbiol. Mol. Biol. Rev. 68, 173–186 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Woese, C. R., Kandler, O. & Wheelis, M. L. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. Proc. Natl Acad. Sci. USA 87, 4576–4579 (1990).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. Woese, C. R. & Goldenfeld, N. How the microbial world saved evolution from the scylla of molecular biology and the charybdis of the modern synthesis. Microbiol. Mol. Biol. Rev. 73, 14–21 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  124. Mercer, T. R., Dinger, M. E. & Mattick, J. S. Long non-coding RNAs: insights into functions. Nat. Rev. Genet. 10, 155–159 (2009).

    Article  CAS  PubMed  Google Scholar 

  125. Brosius, J. & Gould, S. J. On ‘genomenclature’: a comprehensive (and respectful) taxonomy for pseudogenes and other ‘junk DNA’. Proc. Natl Acad. Sci. USA 89, 10706–10710 (1992).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Zhang, J. et al. NANOGP8 is a retrogene expressed in cancers. FEBS J. 273, 1723–1730 (2006).

    Article  CAS  PubMed  Google Scholar 

  127. Kandouz, M., Bier, A., Carystinos, G. D., Alaoui-Jamali, M. A. & Batist, G. Connexin43 pseudogene is expressed in tumor cells and inhibits growth. Oncogene 23, 4763–4770 (2004).

    Article  CAS  PubMed  Google Scholar 

  128. Chiefari, E. et al. Pseudogene-mediated posttranscriptional silencing of HMGA1 can result in insulin resistance and type 2 diabetes. Nat. Commun. 1, 40 (2010).

    Article  PubMed  CAS  Google Scholar 

  129. Hawkins, P. G. & Morris, K. V. Transcriptional regulation of Oct4 by a long non-coding RNA antisense to Oct4-pseudogene 5. Transcription 1, 165–175 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  130. Reynaud, C. A., Anquez, V., Grimal, H. & Weill, J. C. A hyperconversion mechanism generates the chicken light chain preimmune repertoire. Cell 48, 379–388 (1987).

    Article  CAS  PubMed  Google Scholar 

  131. Reynaud, C. A., Dahan, A., Anquez, V. & Weill, J. C. Somatic hyperconversion diversifies the single Vh gene of the chicken with a high incidence in the D region. Cell 59, 171–183 (1989).

    Article  CAS  PubMed  Google Scholar 

  132. Wang, J., Pitarque, M. & Ingelman-Sundberg, M. 3′-UTR polymorphism in the human CYP2A6 gene affects mRNA stability and enzyme expression. Biochem. Biophys. Res. Commun. 340, 491–497 (2006).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank J. Mattick for feedback on the manuscript and A. Ewing for helpful discussion. S.W.C. acknowledges support from a National Health and Medical Research Council (NHMRC) Early Career Fellowship (GNT1161832) and the Mater Foundation. G.J.F. acknowledges support from a CSL Centenary Fellowship and the Mater Foundation.

Author information

Authors and Affiliations

  1. Mater Research Institute, University of Queensland, TRI Building, Woolloongabba, QLD, Australia

    Seth W. Cheetham & Geoffrey J. Faulkner

  2. Queensland Brain Institute, University of Queensland, Brisbane, QLD, Australia

    Geoffrey J. Faulkner

  3. School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia

    Marcel E. Dinger

Authors
  1. Seth W. Cheetham
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Geoffrey J. Faulkner
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marcel E. Dinger
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

S.W.C. and M.E.D. contributed to all aspects of the article. G.J.F. revised the manuscript.

Corresponding authors

Correspondence to Seth W. Cheetham or Marcel E. Dinger.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information

Nature Reviews Genetics thanks P. Carninci and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Glossary

Expressed sequence tags

(ESTs). Short fragmented sequences of cDNAs. Mapping ESTs identifies transcribed genes.

Non-synonymous substitutions

Nucleotide substitutions that change the encoded amino acid sequence.

Positive selection

Selection for alleles that increase fitness. Positive selection results in shifts of the allele frequency.

Purifying selection

Selection against alleles that are deleterious to fitness. Purifying selection maintains the amino acid sequence.

Retrotransposition

Insertion of a sequence into the genome via the reverse transcription and integration of an RNA intermediate.

Synonymous substitutions

Nucleotide substitutions that do not change the encoded amino acid sequence.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cheetham, S.W., Faulkner, G.J. & Dinger, M.E. Overcoming challenges and dogmas to understand the functions of pseudogenes. Nat Rev Genet 21, 191–201 (2020). https://doi.org/10.1038/s41576-019-0196-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41576-019-0196-1

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing