A genome-wide association study (GWAS) identifies trait-associated loci, but identifying the causal genes can be a bottleneck, due in part to slow decay of linkage disequilibrium (LD). A transcriptome-wide association study (TWAS) addresses this issue by identifying gene expression-phenotype associations or integrating gene expression quantitative trait loci with GWAS results. Here, we used self-pollinated soybean (Glycine max [L.] Merr.) as a model to evaluate the application of TWAS to the genetic dissection of traits in plant species with slow LD decay. We generated RNA sequencing data for a soybean diversity panel and identified the genetic expression regulation of 29 286 soybean genes. Different TWAS solutions were less affected by LD and were robust to the source of expression, identifing known genes related to traits from different tissues and developmental stages. The novel pod-color gene L2 was identified via TWAS and functionally validated by genome editing. By introducing a new exon proportion feature, we significantly improved the detection of expression variations that resulted from structural variations and alternative splicing. As a result, the genes identified through our TWAS approach exhibited a diverse range of causal variations, including SNPs, insertions or deletions, gene fusion, copy number variations, and alternative splicing. Using this approach, we identified genes associated with flowering time, including both previously known genes and novel genes that had not previously been linked to this trait, providing insights complementary to those from GWAS. In summary, this study supports the application of TWAS for candidate gene identification in species with low rates of LD decay.

BACKGROUND: Expression quantitative trait loci (eQTL) studies aim to understand the influence of genetic variants on gene expression. The colocalization of eQTL mapping and GWAS strategy could help identify essential candidate genes and causal DNA variants vital to complex traits in human and many farm animals. However, eQTL mapping has not been conducted in ducks. It is desirable to know whether eQTLs within GWAS signals contributed to duck economic traits.
RESULTS: In this study, we conducted an eQTL analysis using publicly available RNA sequencing data from 820 samples, focusing on liver, muscle, blood, adipose, ovary, spleen, and lung tissues. We identified 113,374 cis-eQTLs for 12,266 genes, a substantial fraction 39.1% of which were discovered in at least two tissues. The cis-eQTLs of blood were less conserved across tissues, while cis-eQTLs from any tissue exhibit a strong sharing pattern to liver tissue. Colocalization between cis-eQTLs and genome-wide association studies (GWAS) of 50 traits uncovered new associations between gene expression and potential loci influencing growth and carcass traits. SRSF4, GSS, and IGF2BP1 in liver, NDUFC2 in muscle, ELF3 in adipose, and RUNDC1 in blood could serve as the candidate genes for duck growth and carcass traits.
CONCLUSIONS: Our findings highlight substantial differences in genetic regulation of gene expression across duck primary tissues, shedding light on potential mechanisms through which candidate genes may impact growth and carcass traits. Furthermore, this availability of eQTL data offers a valuable resource for deciphering further genetic association signals that may arise from ongoing extensive endeavors aimed at enhancing duck production traits.

BACKGROUND: The pathogenesis of urolithiasis is multi-factorial and genetic factors have been shown to play a significant role in the development of urolithiasis. We tried to apply genome-wide Mendelian randomization (MR) analysis and figure out reliable gene susceptibility of urolithiasis from the largest samples to date in two independent genome-wide association studies (GWAS) database of European ancestry.
METHODS: We extracted summary statistics of expression quantitative trait locus (eQTL) from eQTLGen consortium. Urolithiasis phenotype information was obtained from both FinnGen Biobank and UK Biobank. Multiple two-sample MR analysis with a Bonferroni-corrected P threshold (P < 2.5e-06) was conducted. The primary endpoint was the causal effect calculated by random-effect inverse variance weighted (IVW) method. Sensitivity analysis, volcano plots, scatter plots, and regional plots were also performed and visualized.
RESULTS: After multiple MR tests between 19942 eQTLs and urolithiasis phenotype from both cohorts, 30 common eQTLs with consistent effect size direction were found to be causally associated with urolithiasis risk. Finally only one gene (LMAN2) was simultaneously identified among all top significant eQTLs from both FinnGen Biobank (beta = 0.6758, se = 0.0327, P = 6.775e-95) and UK Biobank (beta = 0.0044, se = 0.0009, P = 2.417e-06). We also found that LMAN2 was with the largest beta effect size on urolithiasis phenotype from the two cohorts.
CONCLUSIONS: We for the first time implemented genome-wide MR analysis to investigate the genetic susceptibility of urolithiasis in general population of European ancestry. Our results provided novel insights into common genetic variants of urinary stone disease, which was of great help to subsequent researches.

BACKGROUND: Frailty is associated with a variety of diseases, but the relationship between frailty and psoriasis remains unclear.
METHODS: First, we conducted a two-sample Mendelian randomization based on genome-wide association studies (GWAS) to investigate genetic causality between frailty index and common diseases in dermatology. Inverse variance weighted was used to estimate causality. Second, expression quantitative trait locus (eQTLs) analysis was conducted to identify the genes affected by Single nucleotide polymorphisms (SNPs). Third, we performed function and pathway enrichment, transcriptome-wide association studies (TWAS) analysis based on eQTLs.
RESULTS: It was shown that the rise of frailty index could increase the risk of psoriasis (IVW, beta = 0.916, OR = 2.500, 95%CI:1.418-4.408, p = 0.002) through Mendelian randomization (MR), and there was no heterogeneity and pleiotropy. There was no causality between the frailty index and other common diseases in dermatology. We found 31 eQTLs based on strongly correlated SNPs in the causality. TWAS analysis found that the expressions of four genes were closely related to psoriasis, including HLA-DQA1, HLA-DQA2, HLA-DRB1 and HLA-DQB1.
CONCLUSIONS: It suggested that the frailty index had a significant positive causality on the risk of psoriasis, which was well documented by combined genomic, transcriptome, and proteome analyses.

Expression quantitative trait loci (eQTL) offer insights into the regulatory mechanisms of trait-associated variants, but their effects often rely on contexts that are unknown or unmeasured. We introduce PICALO, a method for hidden variable inference of eQTL contexts. PICALO identifies and disentangles technical from biological context in heterogeneous blood and brain bulk eQTL datasets. These contexts are biologically informative and reproducible, outperforming cell counts or expression-based principal components. Furthermore, we show that RNA quality and cell type proportions interact with thousands of eQTLs. Knowledge of hidden eQTL contexts may aid in the inference of functional mechanisms underlying disease variants.

Transcriptome studies disentangle functional mechanisms of gene expression regulation and may elucidate the underlying biology of disease processes. However, the types of tissues currently collected typically assay a single post-mortem timepoint or are limited to investigating cell types found in blood. Noninvasive tissues may improve disease-relevant discovery by enabling more complex longitudinal study designs, by capturing different and potentially more applicable cell types, and by increasing sample sizes due to reduced collection costs and possible higher enrollment from vulnerable populations. Here, we develop methods for sampling noninvasive biospecimens, investigate their performance across commercial and in-house library preparations, characterize their biology, and assess the feasibility of using noninvasive tissues in a multitude of transcriptomic applications. We collected buccal swabs, hair follicles, saliva, and urine cell pellets from 19 individuals over three to four timepoints, for a total of 300 unique biological samples, which we then prepared with replicates across three library preparations, for a final tally of 472 transcriptomes. Of the four tissues we studied, we found hair follicles and urine cell pellets to be most promising due to the consistency of sample quality, the cell types and expression profiles we observed, and their performance in disease-relevant applications. This is the first study to thoroughly delineate biological and technical features of noninvasive samples and demonstrate their use in a wide array of transcriptomic and clinical analyses. We anticipate future use of these biospecimens will facilitate discovery and development of clinical applications.

Celiac disease (CeD) is an immune-mediated disorder that develops in genetically predisposed individuals upon gluten consumption. HLA risk alleles explain 40% of the genetic component of CeD, so there have been continuing efforts to uncover non-HLA loci that can explain the remaining heritability. As in most autoimmune disorders, the prevalence of CeD is significantly higher in women. Here, we investigated the possible involvement of the X chromosome on the sex bias of CeD.
We performed a X chromosome-wide association study (XWAS) and a gene-based association study in women from the CeD Immunochip (7062 cases, 5446 controls). We also constructed a database of X chromosome cis-expression quantitative trait loci (eQTLs) in monocytes from unstimulated (n = 226) and lipopolysaccharide (LPS)-stimulated (n = 130) female donors and performed a Summary-data-based MR (SMR) analysis to integrate XWAS and eQTL information. We interrogated the expression of the potentially causal gene (TMEM187) in peripheral blood mononuclear cells (PBMCs) from celiac patients at onset, on a gluten-free diet, potential celiac patients and non-celiac controls.
The XWAS and gene-based analyses identified 13 SNPs and 25 genes, respectively, 22 of which had not been previously associated with CeD. The X chromosome cis-eQTL analysis found 18 genes with at least one cis-eQTL in naïve female monocytes and 8 genes in LPS-stimulated female monocytes, 2 of which were common to both situations and 6 were unique to LPS stimulation. SMR identified a potentially causal association of TMEM187 expression in naïve monocytes with CeD in women, regulated by CeD-associated, eQTL-SNPs rs7350355 and rs5945386. The CeD-risk alleles were correlated with lower TMEM187 expression. These results were replicated using eQTLs from LPS-stimulated monocytes. We observed higher levels of TMEM187 expression in PBMCs from female CeD patients at onset compared to female non-celiac controls, but not in male CeD individuals.
Using X chromosome genotypes and gene expression data from female monocytes, SMR has identified TMEM187 as a potentially causal candidate in CeD. Further studies are needed to understand the implication of the X chromosome in the higher prevalence of CeD in women.
Celiac disease (CeD) is an immune-related condition triggered by gluten consumption in genetically susceptible individuals. Women present higher prevalence of CeD than men, but the biological explanation of such difference has not been elucidated. In this study, we investigated whether specific genetic variations on the X chromosome were associated with CeD in each sex. Surprisingly, we found 13 genetic variants and 25 genes significantly linked to CeD in women, but not in men. Additionally, we identified genetic variants on the X chromosome associated with gene expression of monocytes, a type of immune cells that is activated in CeD after gluten intake. Integrating these data with our previous findings, we found that lower expression of a gene termed TMEM187 might be associated with a potential increase in CeD risk in women. Finally, validation experiments confirmed higher TMEM187 levels in blood cells from female CeD patients compared to non-celiac women, while no such difference was seen in males. In summary, our study suggests that the X-chromosome gene TMEM187 may play a key role in CeD development, providing insights into the higher prevalence of CeD in females.

Accurate imputation of tissue-specific gene expression can be a powerful tool for understanding the biological mechanisms underlying human complex traits. Existing imputation methods can be grouped into two categories according to the types of predictors used. The first category uses genotype data, while the second category uses whole-blood expression data. Both data types can be easily collected from blood, avoiding invasive tissue biopsies. In this study, we attempted to build an optimal predictive model for imputing tissue-specific gene expression by combining the genotype and whole-blood expression data. We first evaluated the imputation performance of each standalone model (using genotype data [GEN model] and using whole-blood expression data [WBE model]) using their respective data types across 47 human tissues. The WBE model outperformed the GEN model in most tissues by a large gain. Then, we developed several combined models that leverage both types of predictors to further improve imputation performance. We tried various strategies, including utilizing a merged dataset of the two data types (MERGED models) and integrating the imputation outcomes of the two standalone models (inverse variance-weighted [IVW] models). We found that one of the MERGED models noticeably outperformed the standalone models. This model involved a fixed ratio between the two regularization penalty factors for the two predictor types so that the contribution of the whole-blood transcriptome is upweighted compared with the genotype. Our study suggests that one can improve the imputation of tissue-specific gene expression by combining the genotype and whole-blood expression, but the improvement can be largely dependent on the combination strategy chosen.

BACKGROUND: Expression quantitative trait loci (eQTL) studies provide insights into regulatory mechanisms underlying disease risk. Expanding studies of gene regulation to underexplored populations and to medically relevant tissues offers potential to reveal yet unknown regulatory variants and to better understand disease mechanisms. Here, we performed eQTL mapping in subcutaneous (S) and visceral (V) adipose tissue from 106 Greek individuals (Greek Metabolic study, GM) and compared our findings to those from the Genotype-Tissue Expression (GTEx) resource.
RESULTS: We identified 1,930 and 1,515 eGenes in S and V respectively, over 13% of which are not observed in GTEx adipose tissue, and that do not arise due to different ancestry. We report additional context-specific regulatory effects in genes of clinical interest (e.g. oncogene ST7) and in genes regulating responses to environmental stimuli (e.g. MIR21, SNX33). We suggest that a fraction of the reported differences across populations is due to environmental effects on gene expression, driving context-specific eQTLs, and suggest that environmental effects can determine the penetrance of disease variants thus shaping disease risk. We report that over half of GM eQTLs colocalize with GWAS SNPs and of these colocalizations 41% are not detected in GTEx. We also highlight the clinical relevance of S adipose tissue by revealing that inflammatory processes are upregulated in individuals with obesity, not only in V, but also in S tissue.
CONCLUSIONS: By focusing on an understudied population, our results provide further candidate genes for investigation regarding their role in adipose tissue biology and their contribution to disease risk and pathogenesis.

The associations of vitamin D level with venous thromboembolism (VTE) reported in observational studies, whereas these causal associations were uncertain in European population. Therefore, we used Mendelian randomization (MR) method to explore the causal associations between 25-hydroxyvitamin D (25(OH)D) concentrations and the risk of VTE and its subtypes [including deep vein thrombosis (DVT) and pulmonary embolism (PE)].
We used three kinds of genetic instruments to proxy the exposure of 25(OH)D, including genetic variants significantly associated with 25(OH)D, expression quantitative trait loci of 25(OH)D target genes, and genetic variants within or nearby 25(OH)D target genes. MR analyses did not provide any evidence for the associations of 25(OH)D levels with VTE and its subtypes (p > 0.05). The summary-data-based MR (SMR) analyses indicated that elevated expression of VDR was associated with decreased risk of VTE (OR = 0.81; 95% CI, 0.65-0.998; p = 0.047) and PE (OR = 0.67; 95% CI, 0.50-0.91; p = 0.011), and expression of AMDHD1 was associated with PE (OR = 0.93; 95% CI, 0.88-0.99; p = 0.027). MR analysis provided a significant causal effect of 25(OH)D level mediated by gene AMDHD1 on PE risk (OR = 0.09; 95% CI, 0.01-0.60; p = 0.012).
Our MR analysis did not support causal association of 25(OH)D level with the risk of VTE and its subtypes. In addition, the expression of VDR and AMDHD1 involved in vitamin D metabolism showed a strong association with VTE or PE and might represent targets for these conditions.