Evidence map›Paper›PMID 37066341›Full record

ArticlebioRxiv : the preprint server for biology2023

Systematic visualisation of molecular QTLs reveals variant mechanisms at GWAS loci.

Nurlan Kerimov, Ralf Tambets, James D Hayhurst, Ida Rahu, Peep Kolberg, Uku Raudvere, Ivan Kuzmin, Anshika Chowdhary, Andreas Vija, Hans J Teras and 13 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. 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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

23 authors at 6 institutions in 4 countries.

Nurlan KerimovInstitute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
Ralf TambetsInstitute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
James D HayhurstOpen Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
Ida RahuInstitute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
Peep KolbergInstitute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
Uku RaudvereInstitute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
Ivan KuzminInstitute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
Anshika ChowdharyInstitute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany.
Andreas VijaInstitute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
Hans J TerasInstitute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
Masahiro KanaiAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
Jacob UlirschAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
Mina RytenDepartment of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London.
John HardyDepartment of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London.
Sebastian GuelfiDepartment of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London.
Daniah TrabzuniDepartment of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London.
Sarah Kim-HellmuthInstitute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany.
Will RaynerInstitute of Translational Genomics, Helmholtz Munich, Neuherberg, Germany.
Hilary FinucaneAnalytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
Hedi PetersonInstitute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
Abayomi MosakuOpen Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
Helen ParkinsonOpen Targets, South Building, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK.
Kaur AlasooInstitute of Computer Science, University of Tartu, Tartu, 51009, Estonia.
University of Tartu · EEUniversity College London · GBBroad Institute · USEuropean Bioinformatics Institute · GBHelmholtz Zentrum München · DEOpen Targets · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Splicing quantitative trait loci (QTLs) have been implicated as a common mechanism underlying complex trait associations. However, utilising splicing QTLs in target discovery and prioritisation has been challenging due to extensive data normalisation which often renders the direction of the genetic effect as well as its magnitude difficult to interpret. This is further complicated by the fact that strong expression QTLs often manifest as weak splicing QTLs and vice versa, making it difficult to uniquely identify the underlying molecular mechanism at each locus. We find that these ambiguities can be mitigated by visualising the association between the genotype and average RNA sequencing read coverage in the region. Here, we generate these QTL coverage plots for 1.7 million molecular QTL associations in the eQTL Catalogue identified with five quantification methods. We illustrate the utility of these QTL coverage plots by performing colocalisation between vitamin D levels in the UK Biobank and all molecular QTLs in the eQTL Catalogue. We find that while visually confirmed splicing QTLs explain just 6/53 of the colocalising signals, they are significantly less pleiotropic than eQTLs and identify a prioritised causal gene in 4/6 cases. All our association summary statistics and QTL coverage plots are freely available at https://www.ebi.ac.uk/eqtl/.

Identifiers

PMID37066341
PMCPMC10104061
OpenAlexW4362706456

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.