eQTL Analysis Research Articles

Decoding the spatial chromatin organization and dynamic epigenetic landscapes of macrophage cells during differentiation and immune activation

Immunocytes dynamically reprogram their gene expression profiles during differentiation and immunoresponse. However, the underlying mechanism remains elusive. Here, we develop a single-cell Hi-C method and systematically delineate the 3D genome and dynamic epigenetic atlas of macrophages during these processes. We propose “degree of disorder” to measure genome organizational patterns inside topologically-associated domains, which is correlated with the chromatin epigenetic states, gene expression, and chromatin structure variability in individual cells. Furthermore, we identify that NF-κB initiates systematic chromatin conformation reorganization upon Mycobacterium tuberculosis infection. The integrated Hi-C, eQTL, and GWAS analysis depicts the atlas of the long-range target genes of mycobacterial disease susceptible loci. Among these, the SNP rs1873613 is located in the anchor of a dynamic chromatin loop with LRRK2, whose inhibitor AdoCbl could be an anti-tuberculosis drug candidate. Our study provides comprehensive resources for the 3D genome structure of immunocytes and sheds insights into the order of genome organization and the coordinated gene transcription during immunoresponse.

Common variant c.-22 + 155C > T of BDNF as a genetic risk factor of opium addiction

Opioid use disorder is largely genetic in nature. The common genetic variants present in population might be modulating the risk by affecting expression level of genes in the brain. Here, we study common variants in promoter region of brain-derived neurotrophic factor (BDNF) and Dopamine receptor D2 (DRD2) in a highly prevalent opium addiction geographical region. We identify highly expressed isoforms using CAGE datasets and its associated promoter. Common variants were extracted from promoters and genotyped in addicts compared to controls. The associated variants obtained through hitchhiking events were removed and eQTL analysis was performed. We identified two mutations (rs7944119:G > T and rs13306221:C > T) in the promoter of BDNF to be significantly associated with the addiction. In the dominant inheritance model, both rs7944119 and rs13306221 increases the risk of addiction. Of these two, rs7944119 was in linkage disequilibrium with rs13306221 and showed association due to hitchhiking. The rs13306221-T was associated with a lower expression level of the short BDNF isoform in the Cerebellar cortex. This finding suggests that rs13306221 (c.-22 + 155C > T) could increase risk of addiction by decreasing the expression level of the short isoform of BDNF, therefore, changes in the expression of the BDNF might not be the effect, but rather a cause of opium addiction disorder. Or, subjects with less expression of BDNF are more prone to addiction and addiction further decreases expression of BDNF short isoform in the brain. Although, it should be explored further in more detail.

EQTLs play critical roles in regulating gene expression and identifying key regulators in rice.

The regulation of gene expression plays an essential role in both the phenotype and adaptation of plants. Transcriptome sequencing enables simultaneous identification of exonic variants and quantification of gene expression. Here, we sequenced the leaf transcriptomes of 287 rice accessions from around the world and obtained a total of 177 853 high-quality single nucleotide polymorphisms after filtering. Genome-wide association study identified 44 354 expression quantitative trait loci (eQTLs), which regulate the expression of 13 201 genes, as well as 17 local eQTL hotspots and 96 distant eQTL hotspots. Furthermore, a transcriptome-wide association study screened 21 candidate genes for starch content in the flag leaves at the heading stage. HS002 was identified as a significant distant eQTL hotspot with five downstream genes enriched for diterpene antitoxin synthesis. Co-expression analysis, eQTL analysis, and linkage mapping together demonstrated that bHLH026 acts as a key regulator to activate the expression of downstream genes. The transgenic assay revealed that bHLH026 is an important regulator of diterpenoid antitoxin synthesis and enhances the disease resistance of rice. These findings improve our knowledge of the regulatory mechanisms of gene expression variation and complex regulatory networks of the rice genome and will facilitate genetic improvement of cultivated rice varieties.

Identification of 14 novel susceptibility loci for diaphragmatic hernia development and their biological and clinical implications: results from the UK Biobank.

Genetic contributions to hernia development are incompletely understood. This study performed the first comprehensive genome-wide association study (GWAS) for diaphragmatic hernia using a large population-based cohort in the UK Biobank (UKB). Two-stage GWAS (discovery and confirmation) was performed for diaphragmatic hernia in the UKB. Briefly, 275,549 and 91,850 subjects were randomly selected for association tests in Stages 1 and 2, respectively. Association tests between 8,568,156 SNPs (genotyped or imputed with MAF > 0.01) in the autosomal genome and diaphragmatic hernia were performed in Stage 1. SNPs with P < 1 × 10-5 were selected for confirmation in Stage 2, and those with P < 0.05 and the same direction of association as Stage 1 were selected for combined association testing; SNPs with combined P < 5 × 10-8 were considered GWAS-significant. LD clumping analysis identified genetically independent chromosomal regions (loci). A genetic risk score (GRS) measured the cumulative risk of independent SNPs in 91,849 additional subjects using odds ratios (ORs) from Stages 1 and 2. 36,351 patients were identified with diaphragmatic hernia (ICD-10 K44). In Stage 1 analysis, 2654 SNPs were associated (P < 1 × 10-5) with diaphragmatic hernia. Stage 2 analysis confirmed 338 SNPs (P < 0.05). In combined analysis, 245 SNPs reached GWAS significance (P < 5 × 10-8). LD clumping analysis revealed 14 independent loci associated with diaphragmatic hernia. Two loci have been previously associated with inguinal hernia at 2p16 (rs181661155) and 11p13 (rs5030123). eQTL analysis suggested genes CRLF1, UBA52, and CALD1 are also significantly associated with these loci. GRS showed significant increase in cases compared to controls (P < 1 × 10-16) and is associated with increased risk of diaphragmatic hernia (P < 1 × 10-7). We identified 245 SNPs at 14 susceptibility loci associated with diaphragmatic hernia in a large population-based cohort. These results offer insight into pathogenetic mechanisms of diaphragmatic hernia development and may be used in genetic risk scores for pre-operative risk-stratification and clinical prediction models.

Potentially functional variants of MAP3K14 in the NF-κB signaling pathway genes predict survival of HBV-related hepatocellular carcinoma patients.

BackgroundThe NF-κB signaling pathway plays an important role in associating inflammation with tumor development and progression. However, few studies have reported that roles of genetic variants of the NF-κB signaling pathway genes in survival of patients with HBV-related hepatocellular carcinoma (HBV-HCC), especially with regards to potentially functional SNPs.MethodsWe used multivariate Cox proportional hazards regression to evaluate associations between 2,060 single nucleotide polymorphisms (SNPs) in 20 NF-κB signaling pathway genes and survival of 866 HBV-HCC patients, which were randomly split (1:1) into discovery and validation datasets. Expression quantitative trait loci (eQTL) analysis was conducted to identify associations between survival-associated SNPs and mRNA expression of corresponding genes. Furthermore, online database was used to assess mRNA expression of corresponding genes and survival. Finally, receiver operating characteristic (ROC) curves were used to assess the prediction accuracy of models integrating both clinical and genetic variables on HCC survival.ResultsA total of 6 SNPs in MAP3K14 remained significantly associated with OS of HBV-HCC patients (P<0.05, BFDP<0.8). Further eQTL analysis demonstrated that significant correlations between the rs2074292 (G>A) A allele was associated with higher mRNA expression levels of MAP3K14 (P=0.044) in normal liver tissue, which was associated with worse survival of HBV-HCC patients. In the additive model, after adjusting for age, sex, smoking status, drinking status, AFP level, cirrhosis, embolus and BCLC stage, the combined dataset showed that HBV-HCC patients carrying the rs2074292 AA and GA genotypes (HR=1.71, 95%CI= 1.29-2.27, P=0.000) (HR=1.40, 95%CI=1.10-1.77, P=0.005) have worse OS than GG genotype, respectively. The addition of risk genotypes to the prediction models increased the AUC significantly from 71.15% to 73.11% (P=0.012) and from 72.55% to 74.21% (P=0.010) for 1-year and 3-year OS, respectively.ConclusionOur study indicated that MAP3K14 rs2074292 A allele may be a potential predictor of HBV-HCC survival, likely regulating MAP3K14 mRNA expression.

EP16.03-041 Single Cell RNA Sequencing Reveals Phenotypic Predispositions to Developing Lung Cancer in Never-Smokers

There is a paucity of research into why never-smoking patients develop lung cancer. Preliminary results suggest there may be deficiencies in the genes which deal with cellular repair of DNA damage and response to chronic inflammation. These deficiencies may arise from small differences in the genetic variation of these genes. The relationship between genetic variation and gene expression can be studied through an expression QuantiTative Loci (eQTL) analysis, and our lab has developed methods to perform this at a cellular level.

Mapping of promoter usage QTL using RNA-seq data reveals their contributions to complex traits.

Genomic variations are associated with gene expression levels, which are called expression quantitative trait loci (eQTL). Most eQTL may affect the total gene expression levels by regulating transcriptional activities of a specific promoter. However, the direct exploration of genomic loci associated with promoter activities using RNA-seq data has been challenging because eQTL analyses treat the total expression levels estimated by summing those of all isoforms transcribed from distinct promoters. Here we propose a new method for identifying genomic loci associated with promoter activities, called promoter usage quantitative trait loci (puQTL), using conventional RNA-seq data. By leveraging public RNA-seq datasets from the lymphoblastoid cell lines of 438 individuals from the GEUVADIS project, we obtained promoter activity estimates and mapped 2,592 puQTL at the 10% FDR level. The results of puQTL mapping enabled us to interpret the manner in which genomic variations regulate gene expression. We found that 310 puQTL genes (16.1%) were not detected by eQTL analysis, suggesting that our pipeline can identify novel variant-gene associations. Furthermore, we identified genomic loci associated with the activity of "hidden" promoters, which the standard eQTL studies have ignored. We found that most puQTL signals were concordant with at least one genome-wide association study (GWAS) signal, enabling novel interpretations of the molecular mechanisms of complex traits. Our results emphasize the importance of the re-analysis of public RNA-seq datasets to obtain novel insights into gene regulation by genomic variations and their contributions to complex traits.

Telescoping bimodal latent Dirichlet allocation to identify expression QTLs across tissues.

Expression quantitative trait loci (eQTLs), or single-nucleotide polymorphisms that affect average gene expression levels, provide important insights into context-specific gene regulation. Classic eQTL analyses use one-to-one association tests, which test gene-variant pairs individually and ignore correlations induced by gene regulatory networks and linkage disequilibrium. Probabilistic topic models, such as latent Dirichlet allocation, estimate latent topics for a collection of count observations. Prior multimodal frameworks that bridge genotype and expression data assume matched sample numbers between modalities. However, many data sets have a nested structure where one individual has several associated gene expression samples and a single germline genotype vector. Here, we build a telescoping bimodal latent Dirichlet allocation (TBLDA) framework to learn shared topics across gene expression and genotype data that allows multiple RNA sequencing samples to correspond to a single individual's genotype. By using raw count data, our model avoids possible adulteration via normalization procedures. Ancestral structure is captured in a genotype-specific latent space, effectively removing it from shared components. Using GTEx v8 expression data across 10 tissues and genotype data, we show that the estimated topics capture meaningful and robust biological signal in both modalities and identify associations within and across tissue types. We identify 4,645 cis-eQTLs and 995 trans-eQTLs by conducting eQTL mapping between the most informative features in each topic. Our TBLDA model is able to identify associations using raw sequencing count data when the samples in two separate data modalities are matched one-to-many, as is often the case in biological data. Our code is freely available at https://github.com/gewirtz/TBLDA.

EQTL analysis of laying hens divergently selected for feather pecking identifies KLF14 as a potential key regulator for this behavioral disorder.

Feather pecking in chickens is a damaging behavior, seriously impacting animal welfare and leading to economic losses. Feather pecking is a complex trait, which is partly under genetic control. Different hypotheses have been proposed to explain the etiology of feather pecking and notably, several studies have identified similarities between feather pecking and human mental disorders such as obsessive-compulsive disorder and schizophrenia. This study uses transcriptomic and phenotypic data from 167 chickens to map expression quantitative trait loci and to identify regulatory genes with a significant effect on this behavioral disorder using an association weight matrix approach. From 70 of the analyzed differentially expressed genes, 11,790 genome wide significantly associated variants were detected, of which 23 showed multiple associations (≥15). These were located in proximity to a number of genes, which are transcription regulators involved in chromatin binding, nucleic acid metabolism, protein translation and putative regulatory RNAs. The association weight matrix identified 36 genes and the two transcription factors: SP6 (synonym: KLF14) and ENSGALG00000042129 (synonym: CHTOP) as the most significant, with an enrichment of KLF14 binding sites being detectable in 40 differentially expressed genes. This indicates that differential expression between animals showing high and low levels of feather pecking was significantly associated with a genetic variant in proximity to KLF14. This multiallelic variant was located 652 bp downstream of KLF14 and is a deletion of 1-3 bp. We propose that a deletion downstream of the transcription factor KLF14 has a negative impact on the level of T cells in the developing brain of high feather pecking chickens, which leads to developmental and behavioral abnormalities. The lack of CD4 T cells and gamma-Aminobutyric acid (GABA) receptors are important factors for the increased propensity of laying hens to perform feather pecking. As such, KLF14 is a clear candidate regulator for the expression of genes involved in the pathogenic development. By further elucidating the regulatory pathways involved in feather pecking we hope to take significant steps forward in explaining and understanding other mental disorders, not just in chickens.

In silico identification and in vitro expression analysis of breast cancer-related m6A-SNPs

The research on m6A-associated SNPs (m6A-SNPs) has emerged recently due to their possible critical roles in many key biological processes. In this sense, several investigations have identified m6A-SNPs in different diseases. In order to have a more complete understanding of the role that m6A-SNPs could play in breast cancer, we performed an in silico analysis to identify the m6A-SNPs associated with breast cancer and to evaluate their possible effects. For this purpose, we downloaded SNPs related to breast cancer and the list of m6A-SNPs from public databases in order to identify which ones appear in both. Subsequently, we assessed the identified m6A-SNPs in silico by expression quantitative trait loci (eQTL) analysis and differential gene expression analysis. We genotyped the m6A-SNPs found in the in silico analysis in 35 patients with breast cancer and we carried out a gene expression analysis experimentally on those that showed differences. Our results identified 981 m6A-SNPs related to breast cancer. Four m6A-SNPs showed an eQTL effect and only three were in genes that presented an altered gene expression. When the three m6A-SNPs were evaluated in the tissue sample of our breast cancer patients, only the m6A-SNP rs76563149 located in ZNF354A gene presented differences in allele frequencies and a low gene expression in breast cancer tissues, especially in luminal B HER2+ subtype. Future investigations in these m6A-SNPs should expand the study in different ethnic groups and increase the sample sizes to test their association with breast cancer and elucidate their molecular function.

Genetic variant rs11136000 upregulates clusterin expression and reduces Alzheimer's disease risk.

Clusterin (CLU) is an extracellular chaperone involved in reducing amyloid beta (Aβ) toxicity and aggregation. Although previous genome-wide association studies (GWAS) have reported a potential protective effect of CLU on Alzheimer’s disease (AD) patients, how intron-located rs11136000 (CLU) affects AD risk by regulating CLU expression remains unknown. In this study, we integrated multiple omics data to construct the regulated pathway of rs11136000-CLU-AD. In step 1, we investigated the effects of variant rs11136000 on AD risk with different genders and diagnostic methods using GWAS summary statistics for AD from International Genomics of Alzheimer’s Project (IGAP) and UK Biobank. In step 2, we assessed the regulation of rs11136000 on CLU expression in AD brain samples from Mayo clinic and controls from Genotype-Tissue Expression (GTEx). In step 3, we investigated the differential gene/protein expression of CLU in AD and controls from four large cohorts. The results showed that rs11136000 T allele reduced AD risk in either clinically diagnosed or proxy AD patients. By using expression quantitative trait loci (eQTL) analysis, rs11136000 variant downregulated CLU expression in 13 normal brain tissues, but upregulated CLU expression in cerebellum and temporal cortex of AD samples. Importantly, CLU was significantly differentially expressed in temporal cortex, dorsolateral prefrontal cortex and anterior prefrontal cortex of AD patients compared with normal controls. Together, rs11136000 may reduce AD risk by regulating CLU expression, which may provide important information about the biological mechanism of rs9848497 in AD progress.

Integrative Analysis Between Genome-Wide Association Study and Expression Quantitative Trait Loci Reveals Bovine Muscle Gene Expression Regulatory Polymorphisms Associated With Intramuscular Fat and Backfat Thickness.

Understanding the architecture of gene expression is fundamental to unravel the molecular mechanisms regulating complex traits in bovine, such as intramuscular fat content (IMF) and backfat thickness (BFT). These traits are economically important for the beef industry since they affect carcass and meat quality. Our main goal was to identify gene expression regulatory polymorphisms within genomic regions (QTL) associated with IMF and BFT in Nellore cattle. For that, we used RNA-Seq data from 193 Nellore steers to perform SNP calling analysis. Then, we combined the RNA-Seq SNP and a high-density SNP panel to obtain a new dataset for further genome-wide association analysis (GWAS), totaling 534,928 SNPs. GWAS was performed using the Bayes B model. Twenty-one relevant QTL were associated with our target traits. The expression quantitative trait loci (eQTL) analysis was performed using Matrix eQTL with the complete SNP dataset and 12,991 genes, revealing a total of 71,033 cis and 36,497 trans-eQTL (FDR < 0.05). Intersecting with QTL for IMF, we found 231 eQTL regulating the expression levels of 117 genes. Within those eQTL, three predicted deleterious SNPs were identified. We also identified 109 eQTL associated with BFT and affecting the expression of 54 genes. This study revealed genomic regions and regulatory SNPs associated with fat deposition in Nellore cattle. We highlight the transcription factors FOXP4, FOXO3, ZSCAN2, and EBF4, involved in lipid metabolism-related pathways. These results helped us to improve our knowledge about the genetic architecture behind important traits in cattle.

Shared genetic susceptibility between trigger finger and carpal tunnel syndrome: a genome-wide association study.

SummaryBackgroundTrigger finger and carpal tunnel syndrome are the two most common non-traumatic connective tissue disorders of the hand. Both of these conditions frequently co-occur, often in patients with rheumatoid arthritis. However, this phenotypic association is poorly understood. Hypothesising that the co-occurrence of trigger finger and carpal tunnel syndrome might be explained by shared germline predisposition, we aimed to identify a specific genetic locus associated with both diseases.MethodsIn this genome-wide association study (GWAS), we identified 2908 patients with trigger finger and 436579 controls from the UK Biobank prospective cohort. We conducted a case-control GWAS for trigger finger, followed by co-localisation analyses with carpal tunnel syndrome summary statistics. To identify putative causal variants and establish their biological relevance, we did fine-mapping analyses and expression quantitative trait loci (eQTL) analyses, using fibroblasts from healthy donors (n=79) and tenosynovium samples from patients with carpal tunnel syndrome (n=77). We conducted a Cox regression for time to trigger finger and carpal tunnel syndrome diagnosis against plasma IGF-1 concentrations in the UK Biobank cohort.FindingsPhenome-wide analyses confirmed a marked association between carpal tunnel syndrome and trigger finger in the participants from UK Biobank (odds ratio [OR] 11·97, 95% CI 11·1–13·0; p<1 × 10–300). GWAS for trigger finger identified five independent loci, including one locus, DIRC3, that was co-localised with carpal tunnel syndrome and could be fine-mapped to rs62175241 (0·76, 0·68–0·84; p=5·03 × 10–13). eQTL analyses found a fibroblast-specific association between the protective T allele of rs62175241 and increased DIRC3 and IGFBP5 expression. Increased plasma IGF-1 concentrations were associated with both carpal tunnel syndrome and trigger finger in participants from UK Biobank (hazard ratio >1·04, p<0·02).InterpretationIn this GWAS, the DIRC3 locus on chromosome 2 was significantly associated with both carpal tunnel syndrome and trigger finger, possibly explaining their co-occurrence. The disease-protective allele of rs62175241 was associated with increased expression of long non-coding RNA DIRC3 and its transcriptional target, IGBP5, an antagonist of IGF-1 signalling. These findings suggest a model in which IGF-1 is a driver of both carpal tunnel syndrome and trigger finger, and in which the DIRC3-IGFBP5 axis directly antagonises fibroblastic IGF-1 signalling.FundingWellcome Trust, National Institute for Health Research, Medical Research Council.

Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders.

To date, most expression quantitative trait loci (eQTL) studies, which investigate how genetic variants contribute to gene expression, have been performed in heterogeneous brain tissues rather than specific cell types. In this study, we performed an eQTL analysis using single-nuclei RNA sequencing from 192 individuals in eight brain cell types derived from the prefrontal cortex, temporal cortex and white matter. We identified 7,607 eGenes, a substantial fraction (46%, 3,537/7,607) of which show cell-type-specific effects, with strongest effects in microglia. Cell-type-level eQTLs affected more constrained genes and had larger effect sizes than tissue-level eQTLs. Integration of brain cell type eQTLs with genome-wide association studies (GWAS) revealed novel relationships between expression and disease risk for neuropsychiatric and neurodegenerative diseases. For most GWAS loci, a single gene co-localized in a single cell type, providing new clues into disease etiology. Our findings demonstrate substantial contrast in genetic regulation of gene expression among brain cell types and reveal potential mechanisms by which disease risk genes influence brain disorders.

Genome-wide association study of handgrip strength in the Northern Chinese adult twins

ABSTRACT Purpose Currently, new loci related to handgrip strength have been identified in genome-wide association studies. However, this topic is an understudied area in the Chinese population. Materials and Methods A total of 135 dizygotic twin pairs recruited from the Qingdao Twin Registry system were included in the present study. Using GEMMA, VEAGSE2, and PASCAL software for SNP-based analysis, gene-based analysis, and pathway-based analysis, respectively. The resulting SNPs were subjected to eQTL analysis. Results Although none of the loci reach the statistically significant level (p < 5 × 10−8), we found 19 SNPs exceeding the suggestive significant level (p < 1 × 10−5). After imputation, 162 SNPs reached suggestive evidence level for handgrip strength. A total of 1,118 genes reached the nominal significance level (p < 0.05) in gene-based analysis. A total of 626 potential biological pathways were associated with handgrip strength (p < 0.05). The results of eQTL analysis were mainly enriched in tissues such as the muscle-skeletal, brain, visceral fat, and brain-cortical. Conclusions Genetic variants may involve in regulatory domains, functional genes, and biological pathways that mediate handgrip strength.

Integrated analysis of mRNA-single nucleotide polymorphism-microRNA interaction network to identify biomarkers associated with prostate cancer.

Background: Prostate cancer is one of the most common malignancies among men worldwide currently. However, specific mechanisms of prostate cancer were still not fully understood due to lack of integrated molecular analyses. We performed this study to establish an mRNA-single nucleotide polymorphism (SNP)-microRNA (miRNA) interaction network by comprehensive bioinformatics analysis, and search for novel biomarkers for prostate cancer. Materials and methods: mRNA, miRNA, and SNP data were acquired from Gene Expression Omnibus (GEO) database. Differential expression analysis was performed to identify differentially expressed genes (DEGs) and miRNAs (DEMs). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, protein-protein interaction (PPI) analysis and expression quantitative trait loci (eQTL) analysis of DEGs were conducted. SNPs related to DEMs (miRSNPs) were downloaded from the open-source website MirSNP and PolymiRTS 3.0. TargetScan and miRDB databases were used for the target mRNA prediction of miRNA. The mRNA-SNP-miRNA interaction network was then constructed and visualized by Cytoscape 3.9.0. Selected key biomarkers were further validated using the Cancer Genome Atlas (TCGA) database. A nomogram model was constructed to predict the risk of prostate cancer. Results: In our study, 266 DEGs and 11 DEMs were identified. KEGG pathway analysis showed that DEGs were strikingly enriched in focal adhesion and PI3K-Akt signaling pathway. A total of 60 mRNA-SNP-miRNAs trios were identified to establish the mRNA-SNP-miRNA interaction network. Seven mRNAs in mRNA-SNP-miRNA network were consistent with the predicted target mRNAs of miRNA. These results were largely validated by the TCGA database analysis. A nomogram was constructed that contained four variables (ITGB8, hsa-miR-21, hsa-miR-30b and prostate-specific antigen (PSA) value) for predicting the risk of prostate cancer. Conclusion: Our study established the mRNA-SNP-miRNA interaction network in prostate cancer. The interaction network showed that hsa-miR-21, hsa-miR-30b, and ITGB8 may be utilized as new biomarkers for prostate cancer.

Genetic variants in RNA m5 C modification genes associated with survival and chemotherapy efficacy of colorectal cancer.

Colorectal cancer is one of the most common malignant digestive tract tumors with a poor prognosis. RNA 5-methylcytosine (m5 C) is an important posttranscriptional widespread modification involved in many biological processes. However, the association between genetic variations of m5 C modification genes and the prognostic value of colorectal cancer remains unclear. We investigated the association between candidate single nucleotide polymorphisms (SNPs) in 13 m5 C modification genes and colorectal cancer overall survival (OS) after chemotherapy by the Cox regression model. The combined effect of selected SNPs on OS, progression-free survival (PFS), and disease control rate (DCR) was assessed by the number of risk alleles (NRA). The GTEx and TCGA database were used to perform expression qualitative trait locus (eQTL) analysis. We identified that two SNPs in YBX1 were associated with OS after chemotherapy (HR=1.43, p=0.001 for rs10890208; HR=1.36, p=0.025 for rs3862218). A striking dose-response effect between NRA and OS after chemotherapy was found (ptrend =0.002). The DCR of patients receiving oxaliplatin chemotherapy in the 3-4 NRA group was markedly reduced in comparison to that in the 0-2 NRA group (OR=1.49, p=0.036). Moreover, YBX1 mRNA expression was significantly overexpressed in tumor tissues (p < 0.05) in the TCGA database, and eQTL analysis demonstrated that the two SNPs were associated with YBX1 (p=0.003 for rs10890208 and p=0.024 for rs3862218). Our study indicates that genetic variants in m5 C modification genes may mediate changes in YBX1 mRNA levels and affect the chemotherapeutic efficacy of colorectal cancer patients.

Identification of eQTLs and differential gene expression associated with fetal programming in beef cattle.

This study assessed differential gene expression and identified expression quantitative trait loci (eQTLs) from samples of Longissimus lumborum muscle from bulls at 15months of age submitted to different prenatal nutrition. Upon confirmation of pregnancy, 126 dams were separated into three diet treatments varying the period of inclusion of energy protein supplementation (NP, PP, and FP). At calving, 63 males were genotyped with GGP LD BeadChip. The skeletal muscle of 15 bulls was sequenced (RNA-seq) at 15months of age. The EdgeR package was used for differential gene expression and principal component analysis (PCA), and the Matrix eQTL package was used for the eQTLs analysis (R statistical). The functional enrichment analysis was performed using the MetaCore® software. No genes differentially expressed were found between treatments (FDR > 0.05); nevertheless, we found 179 cis-tag-eQTLs and 20,762 trans-tag-eQTLs (FDR < 0.05) after linkage disequilibrium analysis. The functional enrichment analysis identified terms from gene ontology related to genes associated to trans-eQTLs (FDR < 0.05) as well as metabolic pathways (> gScore). Most biological pathways and genes found had been previously associated to fetal programming. The different prenatal supplementation strategies did not impact on muscle transcriptome of bulls. Additionally, there is a link between genotype and gene expression levels related to developmental traits in Nellore cattle.

471 Integrated psoriasis GWAS and eQTL analysis reveals risk-associated genetic control of TRAF3IP2-AS1 expression in activated CD8 T-cells

We performed an international meta-GWAS of psoriasis, increasing effective sample size by 3.4-fold. Using COJO, we identified 191 independent psoriasis loci at genome-wide (GW) significance (179 outside the MHC). We conducted eQTL analysis of 1,195 strand-specific RNA-seq libraries passing QC (MQ30, ∼25M reads/sample) from 9 FACS-purified immune cell types (CD4/CD8, CLA-/CLA+, and 0h/24 h CD3-CD28-activated T-cells; also resting mDC) from 153 genotyped individuals, yielding 9,091 significant (p<5x10-3) cis-eQTLs mapping to the 179 non-MHC 95% Bayesian credible sets. Here we focus on TRAF3IP2 encoding Act1, an adaptor that transduces signals through IL-17R. COJO found 14 independent risk signals for this region (2 potentially protein-altering and 12 potentially regulatory). The lead protein-coding variant, rs33980500 C/T encoding Act1 D10N, is the top GWAS hit with a posterior probability of 1.00 on unconditional analysis. We have shown that rs33980500-T increases psoriasis risk and promotes Th17 expansion. We identified cis-eQTLs for the lncRNA TRAF3IP2-AS1 in activated CD8 T-cells, but not in activated CD4 or resting T-cells. In contrast, cis-eQTL signals for TRAF3IP2 itself were markedly reduced after CD8 T-cell activation. Moreover, the best cis-eQTL signal for TRAF3IP2-AS1 in activated CD8 T-cells (rs11153301, p=2.9x10-6) is a GW-significant psoriasis hit (p=3.7x10-8) after conditioning on Act1 D10N. The risk allele rs11153301-T results in reduced expression of TRAF3IP2-AS1 in activated CD8 T-cells, and a recent study (J Immunol 206:2353) describes an inhibitory effect of TRAF3IP2-AS1 on Act1 protein level and IL-17 signaling. Notably, the expanded GWAS also implicates a cluster of noncoding variants near IL17RA (p=3.9x10-9), which encodes a key subunit of IL-17R targeted by brodalumab, a highly effective psoriasis treatment. These results suggest that TRAF3IP2-AS1 acts as a brake on psoriasis via its effects on IL-17 signaling in activated CD8 T-cells.

Interaction of polygenic variants specific for abdominal obesity risk with energy metabolism in large Korean cohorts.

We examined the hypothesis that the genetic variants associated with abdominal obesity (AO) risk, excluding skeletal muscle mass impact, interact with lifestyle characteristics of adults aged >40 years in three cohorts from the Korean Genome and Epidemiology Study. Participants from a large city hospital-based cohort, excluding those with cancers, thyroid diseases, chronic kidney disease or brain-related diseases, were divided into AO (case; n=17 545) and control (n=36 283) using the cut-offs for waist circumference of 90 cm for men and 85 cm for women. The genetic variants affecting AO risk were chosen from a genome-wide association study in this cohort with obesity-related covariates, including and excluding skeletal muscle mass as a covariate. The genetic variants were confirmed in the other two cohorts. The interaction between the genetic variants was identified by generalised multifactor dimensionality reduction analysis (GMDR). The polygenic risk scores (PRS)-nutrient interactions were determined. Abdominal obesity was associated with SEC16B_rs543874, KCNQ5_rs2796052, CDKAL1_rs9356744, BDNF_rs6265, FTO_rs1421085, MC4R_rs17782313 and GIPR_rs1444988703 adjusting for covariates excluding LBM. However, the best model with 5 single nucleotide polymorphisms (SNP) contained COL3A1_rs3106801, ADAMTS3_rs13105983, KCNQ5_rs2796044, ZFHX3_rs9938769 and MIR17HG_rs7318578 from GMDR when including LBM in covariates. These genetic variants were specific for AO risk. The expression quantitative trait locus (eQTL) analysis showed that the SNP effects were associated with the corresponding gene expression. The high PRS with the 5 SNP model was positively associated with an increased risk of AO of 1.639 (1.463-1.836). The PRS interacted with the age of menarche, energy intake and physical activity. In conclusion, adults with a high PRS, particularly those experiencing early menarche, may particularly benefit from not exceeding energy requirements and from regular physical exercise in order to prevent abdominal obesity. This finding can be applied to personalised nutrition advice to prevent abdominal obesity.