Evidence map›Paper›PMID 42363761›Full record

ArticleNucleic acids research2026

Intron location and sequence modulate gene expression in Yarrowia lipolytica.

Qi Qi, Pedro Tomaz da Silva, Vasileios Vangalis, Seppe Dockx, Jan Steensels, Karin Voordeckers, Julien Gagneur, Kevin J Verstrepen

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Qi QiCentre of Microbial and Plant Genetics (CMPG), Department of Microbial and Molecular Systems (M2S), KU Leuven, Leuven 3000, Belgium.ORCID 0000-0002-0582-1962
Pedro Tomaz da SilvaSchool of Computation, Information and Technology, Technical University of Munich, Munich 80333, Germany.
Vasileios VangalisCentre of Microbial and Plant Genetics (CMPG), Department of Microbial and Molecular Systems (M2S), KU Leuven, Leuven 3000, Belgium.ORCID 0000-0002-6501-7052
Seppe DockxCentre of Microbial and Plant Genetics (CMPG), Department of Microbial and Molecular Systems (M2S), KU Leuven, Leuven 3000, Belgium.ORCID 0000-0002-3010-1748
Jan SteenselsCentre of Microbial and Plant Genetics (CMPG), Department of Microbial and Molecular Systems (M2S), KU Leuven, Leuven 3000, Belgium.ORCID 0000-0002-8271-2663
Karin VoordeckersCentre of Microbial and Plant Genetics (CMPG), Department of Microbial and Molecular Systems (M2S), KU Leuven, Leuven 3000, Belgium.ORCID 0000-0001-6397-840X
Julien GagneurSchool of Computation, Information and Technology, Technical University of Munich, Munich 80333, Germany.ORCID 0000-0002-8924-8365
Kevin J VerstrepenCentre of Microbial and Plant Genetics (CMPG), Department of Microbial and Molecular Systems (M2S), KU Leuven, Leuven 3000, Belgium.ORCID 0000-0002-3077-6219

Funding

Deutsche ForschungsgemeinschaftERC Synergy 101118521ESI Moonshot project HBC.2023.0550ESI Moonshot project HYBRIDFWO G0E8222NFWO International Research Infrastructure I000925NFWO International Research Infrastructure IBISBA-FLIT Infrastructure for Computational Molecular Medicine 461264291IT Infrastructure for Computational Molecular Medicine 553375143VIB Grand Challenges projectVLAIO Innovation Mandate HBC.2024.0280
6 · The paper itself

Abstract

Introns are widespread among eukaryotic genomes. While intron-containing genes often show higher expression than genes lacking introns, the intron features influencing gene expression remain largely elusive. Here, we systematically characterize the intron landscape of Yarrowia lipolytica, an oleaginous yeast that is increasingly used as a microbial cell factory. Transcriptome analysis across 12 environments identified 2421 introns in 1430 genes, including 1302 newly discovered introns and 479 newly annotated intron-containing genes. We find that intron-containing genes exhibit higher and more stable expression across conditions and identify six key intron features, including the 5' splice motif, 3' splice motif, branch point motif, distance from branch point to 3' splice site, GC content, and intron size, that influence splicing efficiency and gene expression. A linear regression model based on these features robustly captures the intron's effect on gene expression, enabling us to select and test 55 different introns that modulate expression of a reporter gene by 200-fold. Moreover, we demonstrate that intron effects are robust across genomic contexts and identify a previously uncharacterized intron, I3, that strongly enhances gene expression and protein production. Together, our results provide new fundamental insights and open new avenues for using introns as regulatory elements.

Indexed as

Gene Expression Regulation, FungalIntronsYarrowiaBase CompositionGene Expression ProfilingRNA Splice SitesRNA SplicingRNA Splice Sites

Identifiers

PMID42363761
PMCPMC13309789

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.