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Pseudogenes

Genetics and Genomics · NLM MeSH · updated 2026-10-29 · version 1

Citations verified against PubMedNot yet clinician-reviewed10 referencesApproximately 5 min read

Genes bearing close resemblance to known genes at different loci, but rendered non-functional by additions or deletions in structure that prevent normal transcription or translation.

Table of Contents

1. Definition2. Research landscape3. Reading the evidence4. Open-access studies5. Key reviews6. References7. About this article

Definition and research guide

This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.

Content available: 4 complete abstracts (882 words), 10 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.

Definition

Genes bearing close resemblance to known genes at different loci, but rendered non-functional by additions or deletions in structure that prevent normal transcription or translation. When lacking introns and containing a poly-A segment near the downstream end (as a result of reverse copying from processed nuclear RNA into double-stranded DNA), they are called processed genes.

Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.

Also known as: Pseudogene; beta-Tubulin Pseudogene; beta Tubulin Pseudogene; beta-Tubulin Pseudogenes; Pseudogene, beta-Tubulin; Pseudogenes, beta-Tubulin; Genes, Processed; Gene, Processed.

Where it fits in the MeSH classification

Broader topics
Genes

Research landscape

PubMed indexes 4,127 records tagged with the MeSH heading “Pseudogenes” (counts retrieved 2026-10-29). 406 of them (9.8%) were published from 2020 onward, and the busiest period so far is through 1999 with 1,461 records.

Reviews account for 269 records (6.5%) and meta-analyses for 4. Randomized controlled trials number 2 (0.0%) as a share of all records on the topic. Randomized trials make up only a small share of this literature, so much of what is known comes from laboratory, observational or descriptive work.

PubMed records by publication periodthrough 1999: 1,461 records; 2000-2009: 1,241 records; 2010-2019: 1,019 records; 2020 onward: 406 records1,461through 19991,2412000-20091,0192010-20194062020 onward
Records in PubMed indexed with this heading, by publication period. Real counts from NCBI E-utilities; the final period covers only part of the current year. Volume reflects how much has been published, not how strong the evidence is.
Show the data
PeriodRecords
through 19991,461
2000-20091,241
2010-20191,019
2020 onward406
Share of records by publication typeReviews: 6.5 percent; Meta-analyses: 0.1 percent; Randomized controlled trials: 0.0 percentReviews6.5% (269)Meta-analyses0.1% (4)Randomized controlled trials0.0% (2)
Share of all PubMed records on this heading that carry each publication type. Types overlap with other records, so the shares do not sum to 100%.
Publication-type chart data
Publication types among 4,127 PubMed records
TypeRecordsShare
Reviews2696.5%
Meta-analyses40.1%
Randomized controlled trials20.0%

Method: PubMed query "Pseudogenes"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.

Reading the evidence in genetics and genomics

Genetic findings vary widely in strength. A variant linked to a condition in one study may not replicate in other ancestries, and most common variants have small effects that are meaningful only in aggregate. Studies of rare, high-impact variants can support strong causal claims about a gene, while association studies describe statistical links that need functional and independent replication. Check the sample size, the ancestry of participants, whether results were replicated, and whether a laboratory or clinical outcome was actually measured.

Evidence from open-access studies

These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.

Study comparison — selected abstracts, not a systematic review
Study / authorsYearSource label / designEurope PMC citationsLicence / source
GENCODE reference annotation for the human and mouse genomes
Frankish A, Diekhans M, Ferreira AM, Johnson R, Jungreis I, Loveland J, et al.
2019Research article
Design not recorded in structured metadata
2,880cc by
PMID 30357393 · DOI · PMC6323946
The GENCODE pseudogene resource
Pei B, Sisu C, Frankish A, Howald C, Habegger L, Mu XJ, et al.
2012Research article
Design not recorded in structured metadata
273cc by
PMID 22951037 · DOI · PMC3491395
Pseudogenes regulate parental gene expression via ceRNA network
An Y, Furber KL, Ji S
2017Review article
Design not recorded in structured metadata
196cc by
PMID 27561207 · DOI · PMC5192809
Regulation of antiviral and antitumor immunity by the BRCA1 pseudogene in human cancers
Han YJ, Zhang J, Shariff M, Wu S, Khramtsova G, Nguyen LC, et al.
2026Research article
Design not recorded in structured metadata
2cc by
PMID 42081726 · DOI · PMC13167737

GENCODE reference annotation for the human and mouse genomes [1]

Research article Frankish A, Diekhans M, Ferreira AM, Johnson R, Jungreis I, Loveland J, et al. · · 2019 · cited 2,880 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics.
Closing excerpt
org.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (155 words)

The accurate identification and description of the genes in the human and mouse genomes is a fundamental requirement for high quality analysis of data informing both genome biology and clinical genomics. Over the last 15 years, the GENCODE consortium has been producing reference quality gene annotations to provide this foundational resource. The GENCODE consortium includes both experimental and computational biology groups who work together to improve and extend the GENCODE gene annotation. Specifically, we generate primary data, create bioinformatics tools and provide analysis to support the work of expert manual gene annotators and automated gene annotation pipelines. In addition, manual and computational annotation workflows use any and all publicly available data and analysis, along with the research literature to identify and characterise gene loci to the highest standard. GENCODE gene annotations are accessible via the Ensembl and UCSC Genome Browsers, the Ensembl FTP site, Ensembl Biomart, Ensembl Perl and REST APIs as well as https://www.gencodegenes.org.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 30357393 · DOI · PMC6323946

The GENCODE pseudogene resource [2]

Research article Pei B, Sisu C, Frankish A, Howald C, Habegger L, Mu XJ, et al. · · 2012 · cited 273 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
BackgroundPseudogenes have long been considered as nonfunctional genomic sequences.
Closing excerpt
The activity data of each pseudogene are stored in an associated resource, psiDR, which will be useful for the initial identification of potentially functional pseudogenes.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (243 words)

BackgroundPseudogenes have long been considered as nonfunctional genomic sequences. However, recent evidence suggests that many of them might have some form of biological activity, and the possibility of functionality has increased interest in their accurate annotation and integration with functional genomics data.ResultsAs part of the GENCODE annotation of the human genome, we present the first genome-wide pseudogene assignment for protein-coding genes, based on both large-scale manual annotation and in silico pipelines. A key aspect of this coupled approach is that it allows us to identify pseudogenes in an unbiased fashion as well as untangle complex events through manual evaluation. We integrate the pseudogene annotations with the extensive ENCODE functional genomics information. In particular, we determine the expression level, transcription-factor and RNA polymerase II binding, and chromatin marks associated with each pseudogene. Based on their distribution, we develop simple statistical models for each type of activity, which we validate with large-scale RT-PCR-Seq experiments. Finally, we compare our pseudogenes with conservation and variation data from primate alignments and the 1000 Genomes project, producing lists of pseudogenes potentially under selection.ConclusionsAt one extreme, some pseudogenes possess conventional characteristics of functionality; these may represent genes that have recently died. On the other hand, we find interesting patterns of partial activity, which may suggest that dead genes are being resurrected as functioning non-coding RNAs. The activity data of each pseudogene are stored in an associated resource, psiDR, which will be useful for the initial identification of potentially functional pseudogenes.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 22951037 · DOI · PMC3491395

Pseudogenes regulate parental gene expression via ceRNA network [3]

Review article An Y, Furber KL, Ji S · · 2017 · cited 196 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
The concept of competitive endogenous RNA (ceRNA) was first proposed by Salmena and colleagues.
Closing excerpt
In this review, we will primarily discuss how pseudogene transcripts regulate expression of parental genes via ceRNA network and biological significance of regulation.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (243 words)

The concept of competitive endogenous RNA (ceRNA) was first proposed by Salmena and colleagues. Evidence suggests that pseudogene RNAs can act as a 'sponge' through competitive binding of common miRNA, releasing or attenuating repression through sequestering miRNAs away from parental mRNA. In theory, ceRNAs refer to all transcripts such as mRNA, tRNA, rRNA, long non-coding RNA, pseudogene RNA and circular RNA, because all of them may become the targets of miRNA depending on spatiotemporal situation. As binding of miRNA to the target RNA is not 100% complementary, it is possible that one miRNA can bind to multiple target RNAs and vice versa. All RNAs crosstalk through competitively binding to miRNAvia miRNA response elements (MREs) contained within the RNA sequences, thus forming a complex regulatory network. The ratio of a subset of miRNAs to the corresponding number of MREs determines repression strength on a given mRNA translation or stability. An increase in pseudogene RNA level can sequester miRNA and release repression on the parental gene, leading to an increase in parental gene expression. A massive number of transcripts constitute a complicated network that regulates each other through this proposed mechanism, though some regulatory significance may be mild or even undetectable. It is possible that the regulation of gene and pseudogene expression occurring in this manor involves all RNAs bearing common MREs. In this review, we will primarily discuss how pseudogene transcripts regulate expression of parental genes via ceRNA network and biological significance of regulation.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 27561207 · DOI · PMC5192809

Regulation of antiviral and antitumor immunity by the BRCA1 pseudogene in human cancers [4]

Research article Han YJ, Zhang J, Shariff M, Wu S, Khramtsova G, Nguyen LC, et al. · · 2026 · cited 2 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Pseudogenes have been regarded as nonfunctional byproducts of evolutionary processes.
Closing excerpt
These findings support a critical role for BRCA1P1 in regulating innate immune defense and antitumor responses across cancer types, suggesting that targeting pseudogene-derived RNAs may offer innovative therapeutic strategies to enhance antitumor immunity in breast and other cancers.
Interpretation limits
Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (241 words)

Pseudogenes have been regarded as nonfunctional byproducts of evolutionary processes. However, emerging evidence indicates that pseudogenes perform diverse biological roles in human physiology and pathology. We identified the BRCA1 pseudogene (BRCA1P1), a fusion pseudogene derived from the BRCA1 tumor suppressor and RPLP1 ribosomal protein genes, as an immunoregulatory RNA in breast cancer. In this study, we show that BRCA1P1 expression varies across multiple cancer cell types, with no significant association with BRCA1 or BRCA2 somatic mutations in breast and ovarian tumors. Interestingly, BRCA1P1 inhibition elicits antitumor effects in multiple cancer cell types and preclinical tumor models through an antiviral defense mechanism. Loss of BRCA1P1 induces antiviral gene expression, promotes apoptosis, and increases sensitivity to chemotherapy in various cancer cells, without inducing apoptosis in nonmalignant cells. This antiviral response also enhances macrophage-mediated phagocytosis of BRCA1P1-deficient cancer cells. Mechanistically, the majority of BRCA1P1 transcripts are circular RNAs and regulate NF-κB-driven antiviral gene expression. Furthermore, intratumoral expression of BRCA1P1 is elevated in tumor cells, compared to normal breast tissue, and its depletion significantly inhibits the growth of both primary and metastatic breast tumor organoids. Finally, in a humanized mouse model of breast cancer, BRCA1P1 loss stimulates antiviral gene expression and increases T cell infiltration into tumors. These findings support a critical role for BRCA1P1 in regulating innate immune defense and antitumor responses across cancer types, suggesting that targeting pseudogene-derived RNAs may offer innovative therapeutic strategies to enhance antitumor immunity in breast and other cancers.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42081726 · DOI · PMC13167737

Key reviews and meta-analyses

The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.

  • Research article Endogenous microRNA sponges: evidence and controversy [5]
    Thomson DW, Thomson DW, Dinger ME · Nat Rev Genet · 2016 · cited 1,743 times (Europe PMC)
  • Research article Comparison of cytochrome P450 (CYP) genes from the mouse and human genomes, including nomenclature recommendations for genes, pseudogenes and alternative-splice variants [6]
    Nelson DR, Zeldin DC, Hoffman SM, Maltais LJ, Wain HM, Nebert DW · Pharmacogenetics · 2004 · cited 715 times (Europe PMC)
  • Research article ceRNA cross-talk in cancer: when ce-bling rivalries go awry [7]
    Karreth FA, Pandolfi PP · Cancer Discov · 2013 · cited 706 times (Europe PMC)
  • Research article Pseudogenes: are they "junk" or functional DNA? [8]
    Balakirev ES, Ayala FJ · Annu Rev Genet · 2003 · cited 353 times (Europe PMC)
  • Research article Pseudogenes: pseudo-functional or key regulators in health and disease? [9]
    Pink RC, Wicks K, Caley DP, Punch EK, Jacobs L, Carter DR · RNA · 2011 · cited 347 times (Europe PMC)
  • Research article Vertebrate pseudogenes [10]
    Mighell AJ, Smith NR, Robinson PA, Markham AF · FEBS Lett · 2000 · cited 330 times (Europe PMC)

References

  1. Frankish A, Diekhans M, Ferreira AM, Johnson R, Jungreis I, Loveland J, et al.. GENCODE reference annotation for the human and mouse genomes. . 2019. PMID 30357393 · DOI · PMC6323946
  2. Pei B, Sisu C, Frankish A, Howald C, Habegger L, Mu XJ, et al.. The GENCODE pseudogene resource. . 2012. PMID 22951037 · DOI · PMC3491395
  3. An Y, Furber KL, Ji S. Pseudogenes regulate parental gene expression via ceRNA network. . 2017. PMID 27561207 · DOI · PMC5192809
  4. Han YJ, Zhang J, Shariff M, Wu S, Khramtsova G, Nguyen LC, et al.. Regulation of antiviral and antitumor immunity by the BRCA1 pseudogene in human cancers. . 2026. PMID 42081726 · DOI · PMC13167737
  5. Thomson DW, Thomson DW, Dinger ME. Endogenous microRNA sponges: evidence and controversy. Nat Rev Genet. 2016. PMID 27040487 · DOI
  6. Nelson DR, Zeldin DC, Hoffman SM, Maltais LJ, Wain HM, Nebert DW. Comparison of cytochrome P450 (CYP) genes from the mouse and human genomes, including nomenclature recommendations for genes, pseudogenes and alternative-splice variants. Pharmacogenetics. 2004. PMID 15128046 · DOI
  7. Karreth FA, Pandolfi PP. ceRNA cross-talk in cancer: when ce-bling rivalries go awry. Cancer Discov. 2013. PMID 24072616 · DOI · PMC3801300
  8. Balakirev ES, Ayala FJ. Pseudogenes: are they "junk" or functional DNA?. Annu Rev Genet. 2003. PMID 14616058 · DOI
  9. Pink RC, Wicks K, Caley DP, Punch EK, Jacobs L, Carter DR. Pseudogenes: pseudo-functional or key regulators in health and disease?. RNA. 2011. PMID 21398401 · DOI · PMC3078729
  10. Mighell AJ, Smith NR, Robinson PA, Markham AF. Vertebrate pseudogenes. FEBS Lett. 2000. PMID 10692568 · DOI

About this article

Sources
NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
Verification
Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
Review state
automated source verified; no human expert review has been recorded yet.
Version
1, last updated 2026-10-29.

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At a glance

4,127
PubMed records on this heading
10%
published since 2020
269
review articles
2
randomized trials
10
verified references below

Counts come from PubMed on 2026-10-29; they show how much has been written, not how strong the evidence is.

Related topics See all →

  • GenesGenetics and Genomics
  • Multigene FamilyGenetics and Genomics
  • OncogenesGenetics and Genomics
  • Genomic LibraryGenetics and Genomics
  • GenomeGenetics and Genomics

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