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Alex Tokolyi @alextokolyi.bsky.social · 28/11/2023

Very excited to share the first manuscript out of my PhD presenting our analysis into the genetic architecture of gene expression and splicing using blood RNA-seq of 4,732 blood donors from the INTERVAL study. (1/7)

medrxiv.org

Genetic determinants of blood gene expression and splicing and their contribution to molecular pheno...

medRxiv - The Preprint Server for Health Sciences

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Alex Tokolyi @alextokolyi.bsky.social · 28/11/2023

I would like to give a huge thank-you to my supervisors and senior authors Emma Davenport, @mikeinouye.bsky.social & Dirk Paul, and the lab at the Sanger institute for their support throughout this project

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Alex Tokolyi @alextokolyi.bsky.social · 28/11/2023

All of these results are publicly available to browse and explore on our portal at: intervalrna.org.uk

intervalrna.org.uk

INTERVAL QTL portal

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Alex Tokolyi @alextokolyi.bsky.social · 28/11/2023

Finally, we assessed the contribution of eQTLs & sQTLs to GWAS risk loci, finding colocalizations both shared and unique to gene expression and splicing. Those overlapping proteomic or metabolic traits revealed potential pathways through which risk loci may be acting. (7/7)

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Alex Tokolyi @alextokolyi.bsky.social · 28/11/2023

Using this colocalized subset, we performed mediation analysis using individuals with overlapping multi-omic traits to interrogate the strength and direction of shared genetic effects, observing 222 molecular phenotypes significantly mediated by gene expression or splicing. (6/7)

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Alex Tokolyi @alextokolyi.bsky.social · 28/11/2023

Using multi-omic data collected from the same individuals and large external cohorts, we performed colocalization analysis to identify eQTLs and sQTLs also regulating proteomic or metabolomic traits, observing a total of 3,430 with a shared association signal. (5/7)

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Alex Tokolyi @alextokolyi.bsky.social · 28/11/2023

We additionally mapped trans-eQTLs and -sQTLs acting through cis-eGenes using the set of independent cis-eQTL variants. With this mechanism, we identified 2,058 trans-eGenes, and 644 splicing events (in 209 trans-sGenes), the most through the RNA-binding splice-factor QKI. (4/7)

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Alex Tokolyi @alextokolyi.bsky.social · 28/11/2023

Linking expression and splicing phenotypes to genotype, we discovered cis-QTLs for 17,233 eGenes, and 29,514 splicing phenotypes (in 6,853 sGenes). (3/7)

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Alex Tokolyi @alextokolyi.bsky.social · 28/11/2023

This was a huge effort by the whole team and particularly my co-first author Elodie Persyn, integrating proteomic and metabolite QTL data from the same individuals, and external health GWAS data to assess the genetic contribution of eQTLs & sQTLs to downstream traits. (2/7)

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