Evidence map›Paper›PMID 41959360›Full record

ArticlebioRxiv : the preprint server for biology2026

Distinct genetic architecture of gene and isoform level QTL in the Diversity Outbred (DO) mouse population.

Charles I Opara, Kelly A Mitok, Christopher H Emfinger, Katheryn L Schueler, Donnie S Stapleton, Nancy A Benkusky, Udaya Gardiparthi, Kalynn H Willis, Victor Ruotti, Brian S Yandell and 2 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

12 authors.

Charles I OparaDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Kelly A MitokDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Christopher H EmfingerBarnstable Brown Diabetes Centre, University of Kentucky, Lexington, Kentucky, United States of America.
Katheryn L SchuelerDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Donnie S StapletonDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Nancy A BenkuskyDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Udaya GardiparthiDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Kalynn H WillisDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Victor RuottiDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Brian S YandellDepartment of Statistics, University of Wisconsin-Madison, Madison, WI, 53706, USA.
Mark P KellerDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Alan D AttieDepartment of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic association studies of mRNA abundance phenotypes link regulatory gene loci to mRNA abundance (quantitative trait loci; QTL). The majority of eQTL studies are limited to gene-level mRNAs and have not focused on mRNA isoforms. Here, we utilized a large, genetically diverse mouse population to map QTL for both gene and transcript isoform abundance. We identified largely overlapping sets of locally regulated mRNAs, which contrasted with the predominantly non-overlapping distally regulated mRNAs, particularly those influenced by sex and diet. Using allele-effect patterns from local QTL for proteincoding gene-isoform pairs, we show that genetic variation drives allele-specific isoform usage, generating isoforms whose genetic signals diverge from their aggregated genelevel effects through predominantly post-transcriptional mechanisms. We conducted pathway enrichment on distal mRNA hotspots and uncovered isoform-level pathways not detected with gene-level traits. We then applied a composite mediation approach at distal hotspots that compares gene-gene, isoform-isoform, and isoform-gene mediator models. By contrasting these causal models of transcriptional regulation, we identified unique associations between mRNA isoforms that were undetected at the gene level. We also characterized the influence of sex and diet on mRNA expression. Our data also suggest that sex and diet influence expression primarily through distal-acting gene loci. We integrated our QTL data with human genetic data, prioritizing effector genes in loci associated with metabolically relevant traits that suggest conditional dependence on sex and diet in humans. Overall, our findings highlight distinctive mechanisms of transcriptional regulation and emphasize the need to prioritize an isoform-level focus for genetic association studies to avoid missed signals that may arise from the gene-level only QTL mapping.

Identifiers

PMID41959360
PMCPMC13060904

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