eQTL / molecular QTL mapping

The paper develops GECS regression to estimate how much disease heritability is mediated by gene expression levels, finding that 21% of heritability is mediated across 30 traits.

The paper introduces a Bayesian framework to integrate molecular QTL data into genetic association analysis, assessing enrichment and colocalization of genetic variants.

The paper trains a machine learning model on MPRA data to predict regulatory activity, eQTLs, and GWAS hits across the genome.

The paper identifies trans-meQTLs linking disease variants to methylation changes at transcription factor binding sites, revealing eight-fold more downstream effects than trans-eQTLs.

The paper identifies context-dependent eQTLs in peripheral blood RNA-seq data from Dutch individuals using a hypothesis-free approach, revealing gene expression influenced by cell type and signaling pathways.

This paper introduces eCAVIAR, a method to compute colocalization posterior probability between GWAS and eQTL signals to identify target genes and tissues for complex traits.

The paper uses a network-based approach to analyze eQTLs across 13 tissues, identifying cis- and trans-eQTLs and linking SNPs to biological processes and disease associations.

The paper introduces a method to assess enrichment of GWAS loci in regulatory regions, identifying novel biological insights across 27 traits.

This study examines how variable mutation rates and epistasis affect the phylogenetically-conditioned site frequency spectrum in humans using ExAC and primate genome data.

This study uses RNA-Seq and GWAS-eQTL integration to identify novel SLE susceptibility genes, non-coding RNAs, and splicing events not detectable by microarrays.

The paper identifies trans-eQTLs in multiple human tissues and shows their tissue-specific effects and association with disease.

This study identifies cis-eQTLs across 44 human tissues using GTEx data, showing 88% of genes have cis-eQTLs and demonstrating their utility in understanding complex trait etiology.

This paper introduces a quantile regression method to identify eQTLs associated with gene expression distribution, finding new eQTLs with tissue-specific effects and enrichment in GWAS SNPs.

This study identifies brain expression quantitative trait loci (eQTLs) associated with schizophrenia and affective disorders using genetic and transcriptomic data from human brain tissue.

This study maps eQTLs in natural Arabidopsis thaliana accessions and identifies structural variants contributing to transcriptional variation.

The paper identifies non-coding variants affecting gene expression in Sardinian individuals and links them to population history and genetic risk.

This study identifies 7,200 eQTL regulating transcript levels of 5,300 genes in tomato, revealing complex genetic architecture and associations with biological processes and phenotypes.

This paper introduces DAP, a method for efficient integrative multi-SNP association analysis that improves computational efficiency and rigor in incorporating genomic annotations into GWAS and molecular QTL mapping.

This study identifies that about 25% of autoimmune disease loci have eQTLs driven by the same genetic effect using a shared effect modeling approach.

This study partitions the heritability of local and distal gene expression regulation across 15 human tissues, identifying enriched functional categories and tissue-specific patterns.

The paper identifies genetic variants associated with social deprivation and household income using UK Biobank data, finding shared genetic links with health and cognitive traits.

The paper uses imputed sequence variants from key ancestors to identify twelve QTL for mammary gland morphology in Fleckvieh cattle, highlighting regulatory mutations as key factors.

This paper introduces a method to estimate phenotypic variance explained by regional genetic associations using summary statistics, showing most genetic variance is concentrated in a small genomic proportion.

The paper identifies 2,060 expression STRs (eSTRs) contributing 10%-15% of cis-heritability to gene expression, highlighting their role as regulatory variants.

This paper presents a method to estimate effect sizes and replication probabilities from GWAS summary statistics, showing it accurately predicts true effect sizes and replication probabilities in multistage GWAS designs.

The paper introduces TORUS, a method for QTL discovery that incorporates genomic annotations, improving power and efficiency over existing approaches.

The paper characterizes expression quantitative trait loci (eQTL) in bipolar disorder pedigrees to understand genetic regulation and heritability.

The paper shows that adjusting for expression factors reduces eQTL detection but proposes a buffet-style approach to balance power and accuracy.

The paper identifies lymphoma risk SNPs enriched in regulatory elements using a multiscale approach and develops an algorithm to analyze GWAS results.

The paper tests mutation-selection balance theory by analyzing eQTLs and aseQTLs in Capsella grandiflora, finding rare alleles with negative frequency-effect size correlations.