Identifying causal genetic variants for high-altitude adaptation through blood eQTL analysis in plateau populations

Cross-cohort analysis of expression and splicing quantitative trait loci in TOPMed.

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood (n = 6454) and lung (n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank-derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Integrative cross-tissue transcriptome-wide association and metabolomic analysis reveals novel genetic risk loci for aortic aneurysm

Background Aortic aneurysm (AA) is a life-threatening cardiovascular condition with a strong genetic component, however, its molecular mechanisms remain poorly understood. Although genome-wide association studies (GWAS) have identified numerous risk loci, most prior studies have investigated genetic and metabolic factors separately, leaving the causal pathways from genetic variants to disease largely unexplored. Methods We established an integrative framework combining cross-tissue transcriptome-wide association studies (TWAS) with metabolomic mediation analysis. First, we integrated GWAS data from FinnGen R12 with multi-tissue expression quantitative trait loci (eQTL) data from Genotype-Tissue Expression Project (GTEx) V8, then performed cross-tissue TWAS using the Unified Test for MOlecular SignaTures (UTMOST) and single-tissue validation with the Functional Summary-based Imputation (FUSION) to prioritize susceptibility genes. Second, we applied Mendelian randomization (MR), colocalization, and Fine-mapping Of CaUsal gene Sets (FOCUS) to assess causality and identify high-confidence genes. Third, we performed metabolite mediation analysis to uncover metabolic pathways linking genetic variants to disease risk. Finally, we validated key findings in mouse models of thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA) using Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction (RT-qPCR) and Western blotting. Results We identified multiple novel susceptibility genes for AA and its subtypes. Key genes included ADH family members (ADH1A, ADH1B, ADH4, ADH6) and ZNF827, which showed cross-subtype associations with strong colocalization evidence in vascular tissues. Metabolite mediation analysis revealed significant pathways involving N-acetylphenylalanine and methionine sulfoxide. Functional enrichment revealed distinct biological mechanisms: AA and AAA were primarily associated with metabolic pathways, whereas TAA-related genes were enriched in developmental and contractile processes. PheWAS indicated no significant off-target associations. Critically, experimental validation in mouse models confirmed significant upregulation of ZNF827 in TAA and ADH6 in AAA at both mRNA and protein levels, corroborating the genetic predictions. Conclusion This integrated cross-omics analysis identifies novel genetic loci and, crucially, uncovers specific nutrient-related metabolic pathways that mediate genetic risk. These findings provide a mechanistic basis for future nutritional and metabolic intervention studies in AA and its subtypes.

Multi-layer Cis-molQTLs Reveal Regulatory Architecture and Enhance Heritability Explanation for Complex Traits in Cattle.

Genome-wide association study (GWAS) analyses have identified numerous loci associated with economic traits in cattle. Many of these loci reside in noncoding regions, and the regulatory mechanisms through which they influence complex traits remain poorly understood. Here, we integrated 657 RNA-seq libraries from 275 Huaxi cattle across three tissues (longissimus dorsi muscle, liver, and subcutaneous backfat) with ∼ 10 million imputed SNP genotypes to systematically map cis-molecular quantitative trait loci (cis-molQTLs) across four transcriptomic regulatory layers: gene expression (eQTLs), splicing (sQTLs), alternative polyadenylation (aQTLs), and RNA editing (edQTLs). These cis-molQTL classes display distinct genomic distributions and functional enrichments, yet operate in a coordinated manner within complex trait regulatory networks and are significantly enriched near GWAS- and QTLdb-reported loci for growth, carcass, and meat quality traits. Using 1788 genotyped and phenotyped Huaxi cattle, a GREML framework showed that these multi-layer cis-molQTL SNPs collectively explain 61.9% of total SNP-based heritability across 19 complex traits. Incorporating cis-molQTL annotations into genomic prediction models, including MultiBLUP, BayesRC, and molGBLUP, improved prediction accuracy for most traits relative to the baseline GBLUP model (mean increase of 0.05), highlighting the value of multi-layer regulatory variation for functionally informed genomic prediction and precision breeding.

Identification of novel loci regulating circulating melatonin and its causal relationship with hypertension

Findings reveal novel genetic contributors to melatonin regulation and establish their putative causal relationship with hypertension.

Multimodal gene prioritization reveals nonlinear regulatory architecture in childhood-onset asthma

Integrative exome sequencing and multi-omics analysis elucidates the regulatory role of rare variants in metabolic syndrome