Description
NMD is a cellular quality control mechanism that
detects and degrades mRNAs containing premature termination codons (PTCs),
preventing the accumulation of truncated, potentially harmful proteins.
However, not all PTCs trigger NMD. PTCs in certain regions of a transcript are
predicted to escape NMD, meaning the truncated mRNA may be translated into a
protein with unpredictable functional consequences.
The NMD Escape container includes several tracks that display putative regions where
PTC variants are assumed to escape the NMD mechanism. These are typically located
close to the first or last splice junction, within unusually long coding exons,
or in transcripts without any junction.
Subtracks
NMD escape regions
Rule-based predictions of NMD escape regions, computed from transcript
annotations. Three transcript sets are provided:
- NMD escape MANE:
NMD escape regions derived from the MANE Select plus MANE Plus Clinical
transcript set, a jointly curated NCBI/EBI annotation that defines a
single high-confidence transcript per protein-coding gene (Select),
supplemented by additional transcripts of clinical importance
(Plus Clinical).
- NMD escape Gencode:
NMD escape regions derived from GENCODE V49 transcripts.
- NMD escape NCBI RefSeq:
NMD escape regions derived from NCBI RefSeq Curated transcripts
(NM_ and NR_ accessions only).
Click either of the links to the track details here or above to show the four rules
that were used (50 bp, intronless, 100 bp, long exon >400 nt).
NMDetective scores
Machine-learning predictions of NMD efficiency from
Lindeboom
et al. 2016 (A and B models) and from Veiner et al.
(NMDetective-AI, pre-print 2026). Positive scores indicate predicted NMD
triggering; negative scores indicate predicted escape.
- NMDetective-A:
Random forest model for all possible PTCs from nonsense variants.
- NMDetective-B:
Decision tree model for all possible PTCs from nonsense variants.
- NMDetective-A PTC:
Random forest model for the first out-of-frame PTC from frameshifting indels.
- NMDetective-B PTC:
Decision tree model for the first out-of-frame PTC from frameshifting indels.
- NMDetective-AI and
NMDetective-AI variants:
Deep-learning model on MANE Select transcripts (GENCODE V46). Signal track
shows the position-averaged prediction; variants track shows one item per
stop-gain mutation per codon.
Background
The ACMG guidelines say under PVS1:
(ii) One must also be cautious when interpreting truncating variants downstream of the most 3′ truncating variant established as pathogenic in the literature. This is especially true if the predicted stop codon occurs in the last exon or in the last 50 base pairs of the penultimate exon, such that nonsense-mediated decay would not be predicted, and there is a higher likelihood of an expressed protein.
Data Access
The data underlying these tracks can be explored interactively with the
Table Browser or the
Data Integrator. For automated analysis,
the data may be queried from our
REST API. Please refer to our
mailing list archives for questions, or our
Data Access FAQ for more
information.
Credits
Thanks to Guido Neidhardt for suggesting this track at HUGO VEPTC 2025 and Andreas Lahner
for feedback. Thanks to the Decipher Genome Browser team for introducing the idea of a
track. Thanks to Rik Lindeboom for providing custom tracks.
References
Kurosaki T, Popp MW, Maquat LE.
Quality and quantity control of gene expression by nonsense-mediated mRNA decay.
Nat Rev Mol Cell Biol. 2019 Jul;20(7):406-420.
PMID: 30992545; PMC: PMC6855384
Lindeboom RGH, Supek F, Lehner B.
The rules and impact of nonsense-mediated mRNA decay in human cancers.
Nat Genet. 2016 Oct;48(10):1112-8.
PMID: 27618451; PMC: PMC5045715
Lindeboom RGH, Vermeulen M, Lehner B, Supek F.
The impact of nonsense-mediated mRNA decay on genetic disease, gene editing and cancer
immunotherapy.
Nat Genet. 2019 Nov;51(11):1645-1651.
PMID: 31659324; PMC: PMC6858879
Nagy E, Maquat LE.
A rule for termination-codon position within intron-containing genes: when nonsense
affects RNA abundance.
Trends Biochem Sci. 1998 Jun;23(6):198-9.
PMID: 9644970