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Untranslated Regions

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

Citations verified against PubMedNot yet clinician-reviewed10 referencesApproximately 3 min read

The parts of the messenger RNA sequence that do not code for product, i.e.

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 (588 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

The parts of the messenger RNA sequence that do not code for product, i.e. the 5' untranslated regions and 3' untranslated regions.

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: Regions, Untranslated; Region, Untranslated; Untranslated Region; UTRs.

Where it fits in the MeSH classification

Broader topics
RNA, Messenger; RNA, Untranslated; DNA, Intergenic; Gene Components
Narrower topics
3' Untranslated Regions; 5' Untranslated Regions; Regulatory Sequences, Ribonucleic Acid

Related concepts

  • Untranslated Regions

Research landscape

PubMed indexes 27,759 records tagged with the MeSH heading “Untranslated Regions” (counts retrieved 2026-10-29). 5,097 of them (18.4%) were published from 2020 onward, and the busiest period so far is 2010-2019 with 13,963 records.

Reviews account for 1,330 records (4.8%) and meta-analyses for 85. Randomized controlled trials number 30 (0.1%) 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: 656 records; 2000-2009: 8,043 records; 2010-2019: 13,963 records; 2020 onward: 5,097 records656through 19998,0432000-200913,9632010-20195,0972020 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 1999656
2000-20098,043
2010-201913,963
2020 onward5,097
Share of records by publication typeReviews: 4.8 percent; Meta-analyses: 0.3 percent; Randomized controlled trials: 0.1 percentReviews4.8% (1,330)Meta-analyses0.3% (85)Randomized controlled trials0.1% (30)
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 27,759 PubMed records
TypeRecordsShare
Reviews1,3304.8%
Meta-analyses850.3%
Randomized controlled trials300.1%

Method: PubMed query "Untranslated Regions"[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
Optimizing 5'UTRs for mRNA-delivered gene editing using deep learning
Castillo-Hair S, Fedak S, Wang B, Linder J, Havens K, Certo M, et al.
2024Research article
Design not recorded in structured metadata
80cc by
PMID 38902240 · DOI · PMC11189900
IGF2BP3 promotes mRNA degradation through internal m7G modification
Liu C, Dou X, Zhao Y, Zhang L, Zhang L, Dai Q, et al.
2024Research article
Design not recorded in structured metadata
64cc by
PMID 39198433 · DOI · PMC11358264
Riboswitches
Salvail H, Breaker RR
2023Research article
Design not recorded in structured metadata
60cc by
PMID 37160088 · DOI · PMC11207198
The mechanism of ribosomal recruitment during translation initiation on the Type 2 encephalomyocarditis virus IRES
Bhattacharjee S, Abaeva IS, Brown ZP, Arhab Y, Fallah H, Hellen CUT, et al.
2026Research article
Design not recorded in structured metadata
4cc by
PMID 41851500 · DOI · PMC13084055

Optimizing 5'UTRs for mRNA-delivered gene editing using deep learning [1]

Research article Castillo-Hair S, Fedak S, Wang B, Linder J, Havens K, Certo M, et al. · · 2024 · cited 80 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
mRNA therapeutics are revolutionizing the pharmaceutical industry, but methods to optimize the primary sequence for increased expression are still lacking.
Closing excerpt
Our results highlight the potential of model-based sequence design for mRNA therapeutics.
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 (149 words)

mRNA therapeutics are revolutionizing the pharmaceutical industry, but methods to optimize the primary sequence for increased expression are still lacking. Here, we design 5'UTRs for efficient mRNA translation using deep learning. We perform polysome profiling of fully or partially randomized 5'UTR libraries in three cell types and find that UTR performance is highly correlated across cell types. We train models on our datasets and use them to guide the design of high-performing 5'UTRs using gradient descent and generative neural networks. We experimentally test designed 5'UTRs with mRNA encoding megaTALTM gene editing enzymes for two different gene targets and in two different cell lines. We find that the designed 5'UTRs support strong gene editing activity. Editing efficiency is correlated between cell types and gene targets, although the best performing UTR was specific to one cargo and cell type. Our results highlight the potential of model-based sequence design for mRNA therapeutics.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 38902240 · DOI · PMC11189900

IGF2BP3 promotes mRNA degradation through internal m7G modification [2]

Research article Liu C, Dou X, Zhao Y, Zhang L, Zhang L, Dai Q, et al. · · 2024 · cited 64 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Recent studies have suggested that mRNA internal m7G and its writer protein METTL1 are closely related to cell metabolism and cancer regulation.
Closing excerpt
In glioblastoma, the methylation level and the half lifetime of the modified transcript could be modulated by tuning IGF2BP3, or by site-specific targeting of m7G through a dCas13b-guided system, resulting in modulation of cancer progression and chemosensitivity.
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 (123 words)

Recent studies have suggested that mRNA internal m7G and its writer protein METTL1 are closely related to cell metabolism and cancer regulation. Here, we identify that IGF2BP family proteins IGF2BP1-3 can preferentially bind internal mRNA m7G. Such interactions, especially IGF2BP3 with m7G, could promote the degradation of m7G target transcripts in cancer cells. IGF2BP3 is more responsive to changes of m7G modification, while IGF2BP1 prefers m6A to stabilize the bound transcripts. We also demonstrate that p53 transcript, TP53, is m7G-modified at its 3'UTR in cancer cells. In glioblastoma, the methylation level and the half lifetime of the modified transcript could be modulated by tuning IGF2BP3, or by site-specific targeting of m7G through a dCas13b-guided system, resulting in modulation of cancer progression and chemosensitivity.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 39198433 · DOI · PMC11358264

Riboswitches [3]

Research article Salvail H, Breaker RR · · 2023 · cited 60 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
Riboswitches are structured noncoding RNA domains that are typically found embedded in messenger RNAs, where they sense specific target molecules or elemental ions and regulate gene expression.
Closing excerpt
However, as the number of experimentally validated riboswitch classes increases, and their true biochemical sophistication is recognized, it is becoming clearer that many species from all three domains of life entrust RNAs to make important chemical sensing and gene control decisions without the necessary participation of protein factors.
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 (125 words)

Riboswitches are structured noncoding RNA domains that are typically found embedded in messenger RNAs, where they sense specific target molecules or elemental ions and regulate gene expression. These RNAs thus serve as genetic switches that can activate or repress gene expression in response to changing levels of their target ligand. To many observers, riboswitches might seem like rare oddities that are not as sophisticated as, or competitive with, the various protein factors that perform these same roles. However, as the number of experimentally validated riboswitch classes increases, and their true biochemical sophistication is recognized, it is becoming clearer that many species from all three domains of life entrust RNAs to make important chemical sensing and gene control decisions without the necessary participation of protein factors.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 37160088 · DOI · PMC11207198

The mechanism of ribosomal recruitment during translation initiation on the Type 2 encephalomyocarditis virus IRES [4]

Research article Bhattacharjee S, Abaeva IS, Brown ZP, Arhab Y, Fallah H, Hellen CUT, et al. · · 2026 · cited 4 times (Europe PMC)

Abstract reading summary — source excerpts
Opening excerpt
The encephalomyocarditis virus (EMCV) internal ribosomal entry side (IRES) and other Type 2 IRESs favor translation of the viral genome during infection.
Closing excerpt
The strong conservation of the apex of domain I amongst Type 2 IRESs suggests that the reported interactions provide a common general mechanism of ribosomal attachment on them all.
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 (191 words)

The encephalomyocarditis virus (EMCV) internal ribosomal entry side (IRES) and other Type 2 IRESs favor translation of the viral genome during infection. The domains H-L of these IRESs specifically interact with the cellular translation initiation factors eIF4G/eIF4A through their essential JK domain. However, the JK domain is not sufficient for IRES activity, which also strictly requires the preceding domain I of unknown function. To identify interactions that drive ribosomal attachment to eIF4G/eIF4A-bound Type 2 IRESs, we determined the cryo-EM structure of 48S initiation complexes formed on the EMCV IRES. The apical cloverleaf of domain I contacts ribosomal proteins uS13 and uS19 via its subdomain Id, whereas the essential GNRA tetraloop in subdomain Ic interacts with the TψC domain of initiator tRNA. The IRES-tRNA interaction also provides a mechanism for release of the IRES after eIF2 is replaced by eIF5B during subunit joining to allow attachment of 60S subunits. Functional assays supported the exceptional role of these interactions for initiation on this IRES. The strong conservation of the apex of domain I amongst Type 2 IRESs suggests that the reported interactions provide a common general mechanism of ribosomal attachment on them all.

Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41851500 · DOI · PMC13084055

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 Alternative polyadenylation of mRNA precursors [5]
    Tian B, Manley JL · Nat Rev Mol Cell Biol · 2017 · cited 1,080 times (Europe PMC)
  • Research article Translational control by 5'-untranslated regions of eukaryotic mRNAs [6]
    Hinnebusch AG, Ivanov IP, Ivanov IP, Sonenberg N · Science · 2016 · cited 982 times (Europe PMC)
  • Research article Functional 5' UTR mRNA structures in eukaryotic translation regulation and how to find them [7]
    Leppek K, Das R, Barna M · Nat Rev Mol Cell Biol · 2018 · cited 833 times (Europe PMC)
  • Research article A decade of riboswitches [8]
    Serganov A, Nudler E · Cell · 2013 · cited 812 times (Europe PMC)
  • Research article Untranslated regions of mRNAs [9]
    Mignone F, Gissi C, Liuni S, Pesole G · Genome Biol · 2002 · cited 716 times (Europe PMC)
  • Research article Metal homeostasis and resistance in bacteria [10]
    Chandrangsu P, Rensing C, Helmann JD · Nat Rev Microbiol · 2017 · cited 623 times (Europe PMC)

References

  1. Castillo-Hair S, Fedak S, Wang B, Linder J, Havens K, Certo M, et al.. Optimizing 5'UTRs for mRNA-delivered gene editing using deep learning. . 2024. PMID 38902240 · DOI · PMC11189900
  2. Liu C, Dou X, Zhao Y, Zhang L, Zhang L, Dai Q, et al.. IGF2BP3 promotes mRNA degradation through internal m7G modification. . 2024. PMID 39198433 · DOI · PMC11358264
  3. Salvail H, Breaker RR. Riboswitches. . 2023. PMID 37160088 · DOI · PMC11207198
  4. Bhattacharjee S, Abaeva IS, Brown ZP, Arhab Y, Fallah H, Hellen CUT, et al.. The mechanism of ribosomal recruitment during translation initiation on the Type 2 encephalomyocarditis virus IRES. . 2026. PMID 41851500 · DOI · PMC13084055
  5. Tian B, Manley JL. Alternative polyadenylation of mRNA precursors. Nat Rev Mol Cell Biol. 2017. PMID 27677860 · DOI · PMC5483950
  6. Hinnebusch AG, Ivanov IP, Ivanov IP, Sonenberg N. Translational control by 5'-untranslated regions of eukaryotic mRNAs. Science. 2016. PMID 27313038 · DOI · PMC7422601
  7. Leppek K, Das R, Barna M. Functional 5' UTR mRNA structures in eukaryotic translation regulation and how to find them. Nat Rev Mol Cell Biol. 2018. PMID 29165424 · DOI · PMC5820134
  8. Serganov A, Nudler E. A decade of riboswitches. Cell. 2013. PMID 23332744 · DOI · PMC4215550
  9. Mignone F, Gissi C, Liuni S, Pesole G. Untranslated regions of mRNAs. Genome Biol. 2002. PMID 11897027 · DOI · PMC139023
  10. Chandrangsu P, Rensing C, Helmann JD. Metal homeostasis and resistance in bacteria. Nat Rev Microbiol. 2017. PMID 28344348 · DOI · PMC5963929

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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All 95 articles in Genetics and Genomics →

At a glance

27,759
PubMed records on this heading
18%
published since 2020
1,330
review articles
30
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 →

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  • AllelesGenetics and Genomics
  • AnticodonGenetics and Genomics

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