#GeneSky #Bioinformatics #RNA #genomics 🧬 🖥️

Can you please add me as a contributor? Thank you!
orcid.org/0000-0001-83...

Huge thanks to my co-authors, especially my advisors Eric Gamazon and @m-aldrich.bsky.social!

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Finally, we mapped eRNA and canonical gene eQTLs and performed colocalization for ~1 million independent UKBB GWAS associations. We show that a substantially greater proportion (63%) of GWAS associations can be explained by an eQTL when eRNA eQTLs are included in colocalization analyses.

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We next performed eRNA-based TWAS across nearly 5,000 complex traits in the UK Biobank, uncovering over 88,000 highly significant eRNA–tissue associations.

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Using these models, we imputed both eRNA and canonical gene GReX in ~70,000 individuals. We then trained a neural network-based regression model to predict 3D chromatin contact frequency between enhancer–enhancer and enhancer–gene pairs using GReX.

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In this work, we trained predictive models of genetically regulated expression (GReX) of eRNAs across 49 human cell and tissue types.

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While the roles of enhancers in chromatin regulation and gene expression have been widely studied, the biological function of enhancer RNAs (eRNAs)—especially in the context of human disease—remains under-explored.

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