eQTL / molecular QTL mapping

The paper develops a Bayesian method to estimate cell-type-specific gene expression from bulk RNA-seq data using priors from scRNA-seq, improving accuracy and enabling downstream analyses like eQTL discovery.

This paper introduces SSEMQ, a method that jointly maps eQTLs and infers gene regulatory networks, improving detection power for both cis- and trans-eQTLs.

The paper uses blood eQTL meta-analysis to explore the polygenic architecture of complex traits, finding that trans-eQTLs are more informative for identifying causal genes than cis-eQTLs.

The paper identifies genetic variants influencing DNA methylation in blood and shows their associations with complex traits and diseases, but finds limited direct causality.

The paper presents the eQTL Catalogue, a resource containing uniformly processed eQTLs from 21 studies, enabling integrative analysis and identification of cell-type-specific eQTLs and disease colocalisations.

The paper improves phenotypic correlation estimation using summary association statistics by proposing a low-MAF Z-score correlation method that reduces bias compared to existing approaches.

This paper introduces BANNs, a probabilistic framework for GWA studies that improves association mapping and enrichment analysis by incorporating biological annotations and variational inference.

The paper compares PCC and PCHiC methods using different restriction enzymes to assess their sensitivity in detecting promoter interactions and their association with regulatory features and genetic variation.

The paper develops GPU-accelerated algorithms for fast eQTL scans in BXD mice, reducing runtime to seconds for large transcriptome datasets.

The paper maps genetic variants to cell types in the kidney to identify disease mechanisms and drug targets.

The paper identifies local gene co-expression patterns across human tissues and links them to eQTLs associated with multiple traits.

The paper identifies master regulator genes and pathways involved in sex dimorphism in Salix purpurea using integrative genomics approaches.

The paper identifies state-dependent eQTLs in memory T cells by analyzing single-cell RNA and protein data from Peruvians, showing that gene regulation varies with cell states and disease-associated variants are enriched in these contexts.

This paper investigates the distribution of disease-associated SNPs relative to 3D genome topological domains and finds that cancer risk loci are preferentially located at TAD borders.

The paper compares genomic prediction and QTL detection methods in grapevine under climate change, finding penalized regression methods like Elastic Net to be effective for prediction and QTL discovery.

The paper develops a repeat-pangenome graph to analyze VNTR variation across populations and identifies population-specific VNTRs and expression quantitative trait loci.

This study identifies 10,618 cis-eQTLs in grapevine (Vitis vinifera L.) using a bioinformatic pipeline, revealing genetic variants regulating 525 genes involved in fruit ripening.

The paper develops TReCASE, a statistical method for eQTL mapping using ASE data, showing it improves power and efficiency compared to existing methods.

The paper explores eQTLs for NLGN4X in relation to language and neurodevelopmental traits using FUSION and GTEx, finding no significant associations in twin samples.

This study evaluates normalization, aggregation, and statistical methods for sc-eQTL mapping to improve eQTL discovery in single-cell RNA-seq data.

This study maps QTLs for grain yield and related traits under normal and late sown conditions in wheat, identifying a major QTL on chromosome 3B associated with heat tolerance.

The paper profiles gene expression in human microglia from 141 patients, identifies population shifts in acute brain injury, maps eQTLs, and fine-maps Alzheimer's risk variants using hIPSC-derived macrophages.

This study uses GWAS summary data to identify 110 traits with significant causal associations with obesity, revealing its broad impact on cardiovascular, anthropometric, and psychiatric conditions.

The paper identifies major and novel QTL for plant height and heading date in wheat using a biparental population, showing that genetic variation is dominated by known variants and moderate-effect QTL.

The paper introduces an exact alternative to the Shen and Faraway F-statistic for gene-based multi-phenotype analysis, showing it performs well in small sample sizes and identifies novel associations in neurodegenerative disease data.

The paper identifies differentially methylated regions and methylation QTLs associated with teen depression and early puberty using longitudinal DNA methylation data from the Fragile Families Child Wellbeing Study.

Meta-analysis of 41,917 European-ancestry bipolar disorder cases versus 371,549 controls yields 64 risk loci (33 novel), neuronal and synaptic gene enrichment, and 15 eQTL-prioritized genes.

The paper introduces POEMColoc, a method to estimate colocalization probability using limited summary statistics, and finds evidence for colocalization between 150,000 trait-gene-tissue triplets.

The paper identifies an atlas of 3QTLs associated with alternative polyadenylation across 46 tissues, showing they explain 16.1% of trait-associated variants and contribute to disease independently of gene expression.

The paper introduces Tejaas, a method for detecting trans-eQTLs by reverse regression, identifying 18851 unique trans-eQTLs across 49 tissues and showing enrichment in regulatory regions.