Evidence map›Paper›PMID 28062664›Full record

ArticleHuman molecular genetics2017

Mapping eQTLs with RNA-seq reveals novel susceptibility genes, non-coding RNAs and alternative-splicing events in systemic lupus erythematosus.

Christopher A Odhams, Andrea Cortini, Lingyan Chen, Amy L Roberts, Ana Viñuela, Alfonso Buil, Kerrin S Small, Emmanouil T Dermitzakis, David L Morris, Timothy J Vyse and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in Human molecular genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
7.5field-weighted citation impact, top 3% of its field
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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 51 citations in OpenAlex.

  1. Pooled it
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  3. Article
  4. Get Spliced: Uniting Alternative Splicing and Arthritis.International journal of molecular sciences · 2024
    Review
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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

11 authors at 1 institution in 1 country.

Christopher A OdhamsDepartment of Medical & Molecular Genetics, King's College London, London, UK.
Andrea CortiniDepartment of Medical & Molecular Genetics, King's College London, London, UK.
Lingyan ChenDepartment of Medical & Molecular Genetics, King's College London, London, UK.
Amy L RobertsDepartment of Medical & Molecular Genetics, King's College London, London, UK.
Ana ViñuelaDepartment of Twin Research, King's College London, London, UK.
Alfonso Buil
Kerrin S SmallDepartment of Twin Research, King's College London, London, UK.
Emmanouil T Dermitzakis
David L MorrisDepartment of Medical & Molecular Genetics, King's College London, London, UK.
Timothy J VyseDepartment of Medical & Molecular Genetics, King's College London, London, UK.
Deborah S Cunninghame GrahamDepartment of Medical & Molecular Genetics, King's College London, London, UK.
King's College London · GB

Funding

Arthritis Research UKMedical Research Council MR/L01999X/1Medical Research Council MR/M004422/1Versus Arthritis 20265Versus Arthritis 20332Wellcome Trust
6 · The paper itself

Abstract

Studies attempting to functionally interpret complex-disease susceptibility loci by GWAS and eQTL integration have predominantly employed microarrays to quantify gene-expression. RNA-Seq has the potential to discover a more comprehensive set of eQTLs and illuminate the underlying molecular consequence. We examine the functional outcome of 39 variants associated with Systemic Lupus Erythematosus (SLE) through the integration of GWAS and eQTL data from the TwinsUK microarray and RNA-Seq cohort in lymphoblastoid cell lines. We use conditional analysis and a Bayesian colocalisation method to provide evidence of a shared causal-variant, then compare the ability of each quantification type to detect disease relevant eQTLs and eGenes. We discovered the greatest frequency of candidate-causal eQTLs using exon-level RNA-Seq, and identified novel SLE susceptibility genes (e.g. NADSYN1 and TCF7) that were concealed using microarrays, including four non-coding RNAs. Many of these eQTLs were found to influence the expression of several genes, supporting the notion that risk haplotypes may harbour multiple functional effects. Novel SLE associated splicing events were identified in the T-reg restricted transcription factor, IKZF2, and other candidate genes (e.g. WDFY4) through asQTL mapping using the Geuvadis cohort. We have significantly increased our understanding of the genetic control of gene-expression in SLE by maximising the leverage of RNA-Seq and performing integrative GWAS-eQTL analysis against gene, exon, and splice-junction quantifications. We conclude that to better understand the true functional consequence of regulatory variants, quantification by RNA-Seq should be performed at the exon-level as a minimum, and run in parallel with gene and splice-junction level quantification.

Indexed as

Genetic Predisposition to DiseaseAlternative SplicingCarbon-Nitrogen Ligases with Glutamine as Amide-N-DonorChromosome MappingFemaleGene Expression RegulationGenome-Wide Association StudyHaplotypesHumansLupus Erythematosus, SystemicMalePolymorphism, Single NucleotideQuantitative Trait LociRNA, UntranslatedT Cell Transcription Factor 1Carbon-Nitrogen Ligases with Glutamine as Amide-N-DonorNADSYN1 protein, humanRNA, UntranslatedT Cell Transcription Factor 1TCF7 protein, human

Identifiers

PMID28062664
PMCPMC5409091
OpenAlexW2569393612

What OpenQuestion holds

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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.