English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Understanding the causal processes that contribute to disease onset and progression is essential for developing novel therapies. Although  trans -acting expression quantitative trait loci ( trans -eQTLs) can directly reveal cellular processes modulated by disease variants, detecting  trans -eQTLs remains challenging due to their small effect sizes. Here, we analysed gene expression and genotype data from six blood cell types from 226 to 710 individuals. We used co-expression modules inferred from gene expression data with five methods as traits in  trans -eQTL analysis to limit multiple testing and improve interpretability. In addition to replicating three established associations, we discovered a novel  trans -eQTL near  SLC39A8  regulating a module of metallothionein genes in LPS-stimulated monocytes. Interestingly, this effect was mediated by a transient  cis -eQTL present only in early LPS response and lost before the  trans  effect appeared. Our analyses highlight how co-expression combined with functional enrichment analysis improves the identification and prioritisation of  trans -eQTLs when applied to emerging cell-type-specific datasets.

Co-expression analysis reveals interpretable gene modules controlled by trans -acting genetic variants