eQTL Analysis Research Articles

Cell-type specific inference from bulk RNA-sequencing data by integrating single cell reference profiles via EPIC-unmix.

Cell type specific (CTS) analysis is essential to reveal biological insights obscured in bulk tissue data. However, single-cell (sc) or single-nuclei (sn) resolution data are still cost-prohibitive for large-scale samples. Thus, computational methods to perform deconvolution from bulk tissue data are highly valuable. We here present EPIC-unmix, a novel two-step empirical Bayesian method integrating reference sc/sn RNA-seq data and bulk RNA-seq data from target samples to enhance the accuracy of CTS inference. We demonstrate through comprehensive simulations across three tissues that EPIC-unmix achieved 4.6% - 109.8% higher accuracy compared to alternative methods. By applying EPIC-unmix to human bulk brain RNA-seq data from the ROSMAP and MSBB cohorts, we identified multiple genes differentially expressed between Alzheimer's disease (AD) cases versus controls in a CTS manner, including 57.4% novel genes not identified using similar sample size sc/snRNA-seq data, indicating the power of our in-silico approach. Among the 6-69% overlapping, 83%-100% are in consistent direction with those from sc/snRNA-seq data, supporting the reliability of our findings. EPIC-unmix inferred CTS expression profiles similarly empowers CTS eQTL analysis. Among the novel eQTLs, we highlight a microglia eQTL for AD risk gene AP3B2, obscured in bulk and missed by sc/snRNA-seq based eQTL analysis. The variant resides in a microglia-specific cCRE, forming chromatin loop with AP3B2 promoter region in microglia. Taken together, we believe EPIC-unmix will be a valuable tool to enable more powerful CTS analysis.

Potential marker genes for chronic obstructive pulmonary disease revealed based on single-cell sequencing and Mendelian randomization analysis.

Progress is being made in the prevention and treatment of chronic obstructive pulmonary disease (COPD), but it is still unsatisfactory. With the development of genetic technology, validated genetic information can better explain COPD. The study utilized scRNA-seq and Mendelian randomization analysis of eQTLs to identify crucial genes and potential mechanistic pathways underlying COPD pathogenesis. Single-cell sequencing data were used to identify marker genes for immune cells in the COPD process. Data on eQTLs for immune cell marker genes were obtained from the eQTLGen consortium. To estimate the causal effect of marker genes on COPD, we selected an independent cohort (ukb-b-16751) derived from the UK Biobank database for two-sample Mendelian randomization analysis. Subsequently, we performed immune infiltration analysis, gene set enrichment analysis (GSEA), and co-expression network analysis on the key genes. The 154 immune cell-associated marker genes identified were mainly involved in pathways such as vacuolar cleavage, positive regulation of immune response and regulation of cell activation. Mendelian randomization analysis screened four pairs of marker genes (GZMH, COTL1, CSTA and CD14) were causally associated with COPD. These four key genes were significantly associated with immune cells. In addition, we have identified potential transcription factors associated with these key genes using the Cistrome database, thus contributing to a deeper understanding of the regulatory network of these gene expressions. This eQTLs Mendelian randomization study identified four key genes (GZMH, COTL1, CSTA, and CD14) causally associated with COPD, providing new insights for prevention and treatment of COPD.

The GWAS SNP rs80207740 modulates erythrocyte traits via allele-specific binding of IKZF1 and targeting XPO7 gene.

Genome-wide association studies have identified many single nucleotide polymorphisms (SNPs) associated with erythrocyte traits. However, the functional variants and their working mechanisms remain largely unknown. Here, we reported that the SNP of rs80207740, which was associated with red blood cell (RBC) volume and hemoglobin content across populations, conferred enhancer activity to XPO7 gene via allele-differentially binding to Ikaros family zinc finger 1 (IKZF1). We showed that the region around rs80207740 was an erythroid-specific enhancer using reporter assays, and that the G-allele further enhanced activity. 3D genome evidence showed that the enhancer interacted with the XPO7 promoter, and eQTL analysis suggested that the G-allele upregulated expression of XPO7. We further showed that the rs80207740-G allele facilitated the binding of transcription factor IKZF1 in EMSA and ChIP analyses. Knockdown of IKZF1 and GATA1 resulted in decreased expression of Xpo7 in both human and mouse erythroid cells. Finally, we constructed Xpo7 knockout mouse by CRISPR/Cas9 and observed anemic phenotype with reduced volume and hemoglobin content of RBC, consistent to the effect of rs80207740 on erythrocyte traits. Overall, our study demonstrated that rs80207740 modulated erythroid indices by regulating IKZF1 binding and Xpo7 expression.

Critical reasoning on the co-expression module QTL in the dorsolateral prefrontal cortex

Expression quantitative trait locus (eQTL) analysis is a popular method of gaining insight into the function of regulatory variation. While cis-eQTL resources have been instrumental in linking genome-wide association study variants to gene function, complex trait heritability may be additionally mediated by other forms of gene regulation. Toward this end, novel eQTL methods leverage gene co-expression (module-QTL) to investigate joint regulation of gene modules by single genetic variants. Here we broadly define a "module-QTL" as the association of a genetic variant with a summary measure of gene co-expression. This approach aims to reduce the multiple testing burden of a trans-eQTL search through the consolidation of gene-based testing and provide biological context to eQTLs shared between genes. In this article we provide an in-depth examination of the co-expression module eQTL (module-QTL) through literature review, theoretical investigation, and real-data application of the module-QTL to three large prefrontal cortex genotype-RNA sequencing datasets. We find module-QTLs in our study that are disease associated and reproducible are not additionally informative beyond cis- or trans-eQTLs for module genes. Through comparison to prior studies, we highlight promises and limitations of the module-QTL across study designs and provide recommendations for further investigation of the module-QTL framework.

ARID5B is a negative modulator of IL-6 production in rheumatoid arthritis synovial fibroblasts

Recent single-cell RNA-sequencing analysis of rheumatoid arthritis (RA) synovial tissues revealed the heterogeneity of RA synovial fibroblasts (SFs) with distinct functions such as high IL-6 production. The molecular mechanisms responsible for high IL-6 production will become a promising drug target of RASFs to treat RA. In this study, we performed siRNA screening of 65 transcription factors (TFs) differentially expressed among RASF subsets to identify TFs involved in IL-6 production. The siRNA screening identified 7 TFs including ARID5B, a RA risk gene, that affected IL-6 production. Both long and short isoforms of ARID5B were expressed and negatively regulated by TNF-α in RASFs. The siRNA knockdown and lentiviral overexpression of long and short isoforms of ARID5B revealed that the long isoform suppressed IL-6 production stimulated with TNF-α. eQTL analysis using 58 SFs demonstrated that RA risk allele, rs10821944, in intron 4 of the ARID5B gene had a trend of eQTL effects to the expression of long isoform of ARID5B in SFs treated with TNF-α. ARID5B was found to be a negative modulator of IL-6 production in RASFs. The RA risk allele of ARID5B intron may cause high IL-6 production, suggesting that ARID5B will become a promising drug target to treat RA.

Novel putative causal mutations associated with fat traits in Nellore cattle uncovered by eQTLs located in open chromatin regions

Intramuscular fat (IMF) and backfat thickness (BFT) are critical economic traits impacting meat quality. However, the genetic variants controlling these traits need to be better understood. To advance knowledge in this area, we integrated RNA-seq and single nucleotide polymorphisms (SNPs) identified in genomic and transcriptomic data to generate a linkage disequilibrium filtered panel of 553,581 variants. Expression quantitative trait loci (eQTL) analysis revealed 36,916 cis-eQTLs and 14,408 trans-eQTLs. Association analysis resulted in three eQTLs associated with BFT and 24 with IMF. Functional enrichment analysis of genes regulated by these 27 eQTLs revealed noteworthy pathways that can play a fundamental role in lipid metabolism and fat deposition, such as immune response, cytoskeleton remodeling, iron transport, and phospholipid metabolism. We next used ATAC-Seq assay to identify and overlap eQTL and open chromatin regions. Six eQTLs were in regulatory regions, four in predicted insulators and possible CCCTC-binding factor DNA binding sites, one in an active enhancer region, and the last in a low signal region. Our results provided novel insights into the transcriptional regulation of IMF and BFT, unraveling putative regulatory variants.

Leaf morphology related genes revealed by integrating Pan-transcriptome, GWAS and eQTL analyses in a Liriodendron population.

Leaf plays an indispensable role in plant development and growth. Although many known genes related to leaf morphology development have been identified, elucidating the complex genetic basis of leaf morphological traits remains a challenge. Liriodendron plants are common ornamental trees due to their unique leaf shapes, while the molecular mechanism underlying Liriodendron leaf morphogenesis has remained unknown. Herein, we firstly constructed a population-level pan-transcriptome of Liriodendron from 81 accessions to explore the expression presence or absence variations (ePAVs), global expression differences at the population level, as well as differentially expressed genes (DEGs) between the Liriodendron chinense and Liriodendron tulipifera accessions. Subsequently, we integrated a genome-wide association study (GWAS), expression quantitative trait loci (eQTL), and transcriptome-wide association study (TWAS) to identify candidate genes related to leaf morphology. Through GWAS analysis, we identified 18 and 17 significant allelic loci in the leaf size and leaf shape modules, respectively. In addition, we discerned 16 candidate genes in relation to leaf morphological traits via TWAS. Further, integrating the co-localization results of GWAS and eQTL, we determined two regulatory hotspot regions, hot88 and hot758, related to leaf size and leaf shape, respectively. Finally, co-expression analysis, eQTL, and linkage mapping together demonstrated that Lchi_4g10795 regulate their own expression levels through cis-eQTL to affect the expression of downstream genes and cooperatively participate in the development of Liriodendron leaf morphology. These findings will improve our understanding of the molecular regulatory mechanism of Liriodendron leaf morphogenesis and will also accelerate molecular breeding of Liriodendron.

Cotton transposon-related variome reveals roles of transposon-related variations in modern cotton cultivation

IntroductionTransposon plays a vital role in cotton genome evolution, contributing to the expansion and divergence of genomes within the Gossypium genus. However, knowledge of transposon activity in modern cotton cultivation is limited. ObjectivesIn this study, we aimed to construct transposon-related variome within Gossypium genus and reveal role of transposon-related variations during cotton cultivation. In addition, we try to identify valuable transposon-related variations for cotton breeding. MethodsWe utilized graphical genome construction to build up the graphical transposon-related variome. Based on the graphical variome, we integrated t-test, eQTL analysis and Mendelian Randomization (MR) to identify valuable transposon activities and elite genes. In addition, a convolutional neural network (CNN) model was constructed to evaluate epigenomic effects of transposon-related variations. ResultsWe identified 35,980 transposon activities among 10 cotton genomes, and the diversity of genomic and epigenomic features was observed among 21 transposon categories. The graphical cotton transposon-related variome was constructed, and 9,614 transposon-related variations with plasticity in the modern cotton cohort were used for eQTL, phenotypic t-test and Mendelian Randomization. 128 genes were identified as gene resources improving fiber length and strength simultaneously. 4 genes were selected from 128 genes to construct the elite gene panel whose utility has been validated in a natural cotton cohort and 2 accessions with phenotypic divergence. Based on the eQTL analysis results, we identified transposon-related variations involved in cotton’s environmental adaption and human domestication, providing evidence of their role in cotton’s adaption-domestication cooperation. ConclusionsThe cotton transposon-related variome revealed the role of transposon-related variations in modern cotton cultivation, providing genomic resources for cotton molecular breeding.

Cis-eQTLs in seven duck tissues identify novel candidate genes for growth and carcass traits

BackgroundExpression 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.ResultsIn 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.ConclusionsOur 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.

Multiple genetic variants at the SLC30A8 locus affect local super-enhancer activity and influence pancreatic β-cell survival and function.

Variants at the SLC30A8 locus are associated with type 2 diabetes (T2D) risk. The lead variant, rs13266634, encodes an amino acid change, Arg325Trp (R325W), at the C-terminus of the secretory granule-enriched zinc transporter, ZnT8. Although this protein-coding variant was previously thought to be the sole driver of T2D risk at this locus, recent studies have provided evidence for lowered expression of SLC30A8 mRNA in protective allele carriers. In the present study, we examined multiple variants that influence SLC30A8 allele-specific expression. Epigenomic mapping has previously identified an islet-selective enhancer cluster at the SLC30A8 locus, hosting multiple T2D risk and cASE associations, which is spatially associated with the SLC30A8 promoter and additional neighboring genes. Here, we show that deletion of variant-bearing enhancer regions using CRISPR-Cas9 in human-derived EndoC-βH3 cells lowers the expression of SLC30A8 and several neighboring genes and improves glucose-stimulated insulin secretion. While downregulation of SLC30A8 had no effect on beta cell survival, loss of UTP23, RAD21, or MED30 markedly reduced cell viability. Although eQTL or cASE analyses in human islets did not support the association between these additional genes and diabetes risk, the transcriptional regulator JQ1 lowered the expression of multiple genes at the SLC30A8 locus and enhanced stimulated insulin secretion.

Germline genetic regulation of the colorectal tumor immune microenvironment

ObjectiveTo evaluate the contribution of germline genetics to regulating the briskness and diversity of T cell responses in CRC, we conducted a genome-wide association study to examine the associations between germline genetic variation and quantitative measures of T cell landscapes in 2,876 colorectal tumors from participants in the Molecular Epidemiology of Colorectal Cancer Study (MECC).MethodsGermline DNA samples were genotyped and imputed using genome-wide arrays. Tumor DNA samples were extracted from paraffin blocks, and T cell receptor clonality and abundance were quantified by immunoSEQ (Adaptive Biotechnologies, Seattle, WA). Tumor infiltrating lymphocytes per high powered field (TILs/hpf) were scored by a gastrointestinal pathologist. Regression models were used to evaluate the associations between each variant and the three T-cell features, adjusting for sex, age, genotyping platform, and global ancestry. Three independent datasets were used for replication.ResultsWe identified a SNP (rs4918567) near RBM20 associated with clonality at a genome-wide significant threshold of 5 × 10− 8, with a consistent direction of association in both discovery and replication datasets. Expression quantitative trait (eQTL) analyses and in silico functional annotation for these loci provided insights into potential functional roles, including a statistically significant eQTL between the T allele at rs4918567 and higher expression of ADRA2A (P = 0.012) in healthy colon mucosa.ConclusionsOur study suggests that germline genetic variation is associated with the quantity and diversity of adaptive immune responses in CRC. Further studies are warranted to replicate these findings in additional samples and to investigate functional genomic mechanisms.

Control of false discoveries in grouped hypothesis testing for eQTL data

BackgroundExpression quantitative trait locus (eQTL) analysis aims to detect the genetic variants that influence the expression of one or more genes. Gene-level eQTL testing forms a natural grouped-hypothesis testing strategy with clear biological importance. Methods to control family-wise error rate or false discovery rate for group testing have been proposed earlier, but may not be powerful or easily apply to eQTL data, for which certain structured alternatives may be defensible and may enable the researcher to avoid overly conservative approaches.ResultsIn an empirical Bayesian setting, we propose a new method to control the false discovery rate (FDR) for grouped hypotheses. Here, each gene forms a group, with SNPs annotated to the gene corresponding to individual hypotheses. The heterogeneity of effect sizes in different groups is considered by the introduction of a random effects component. Our method, entitled Random Effects model and testing procedure for Group-level FDR control (REG-FDR), assumes a model for alternative hypotheses for the eQTL data and controls the FDR by adaptive thresholding. As a convenient alternate approach, we also propose Z-REG-FDR, an approximate version of REG-FDR, that uses only Z-statistics of association between genotype and expression for each gene-SNP pair. The performance of Z-REG-FDR is evaluated using both simulated and real data. Simulations demonstrate that Z-REG-FDR performs similarly to REG-FDR, but with much improved computational speed.ConclusionOur results demonstrate that the Z-REG-FDR method performs favorably compared to other methods in terms of statistical power and control of FDR. It can be of great practical use for grouped hypothesis testing for eQTL analysis or similar problems in statistical genomics due to its fast computation and ability to be fit using only summary data.

Critical gene signature and immunological characterization in peripheral vascular atherosclerosis: novel insights from mendelian randomization and transcriptomics.

Peripheral vascular atherosclerosis (PVA) is a chronic inflammatory disease characterized by lipid accumulation in blood vessel walls, leading to vessel narrowing and inadequate blood supply. However, the molecular mechanisms underlying PVA remain poorly understood. In this study, we employed a combination of Mendelian randomization (MR) analysis and integrated transcriptomics to identify the critical gene signature associated with PVA. This study utilized three public datasets (GSE43292, GSE100927 and GSE28829) related to peripheral vascular atherosclerosis obtained from the Gene Expression Omnibus database. Instrumental variables (IVs) were identified through expression quantitative trait loci (eQTL) analysis, and two-sample MR analysis was performed using publicly available summary statistics. Disease critical genes were identified based on odds ratios and intersected with differentially expressed genes in the disease dataset. GSE28829 dataset was used to validate the screened disease critical genes. Functional enrichment analysis, GSEA analysis, and immune cell infiltration analysis were performed to further characterize the role of these genes in peripheral vascular atherosclerosis. A total of 26,152 gene-related SNPs were identified as IVs, and 242 disease-associated genes were identified through MR analysis. Ten disease critical genes (ARHGAP25, HCLS1, HVCN1, RBM47, LILRB1, PLAU, IFI44L, IL1B, IFI6, and CFL2) were significantly associated with peripheral vascular atherosclerosis. Functional enrichment analysis using KEGG pathways revealed enrichment in the NF-kappa B signaling pathway and osteoclast differentiation. Gene set enrichment analysis further demonstrated functional enrichment of these genes in processes related to vascular functions and immune system activation. Additionally, immune cell infiltration analysis showed differential ratios of B cells and mast cells between the disease and control groups. The correlations analysis highlights the intricate interplay between disease critical genes and immune cells associated with PVA. In conclusion, this study provides new insights into the molecular mechanisms underlying PVA by identifying ten disease critical genes associated with the disease. These findings, supported by differential expression, functional enrichment, and immune system involvement, emphasize the role of these genes in vascular function and immune cell interactions in the context of PVA. These findings contribute to a better understanding of PVA pathogenesis and offer potential targets for further mechanistic exploration and therapeutic interventions.

Abstract LB147: Fine-scale mapping of chromosome 9q22.33 identifies candidate causal variant in ovarian cancer

Abstract Ovarian cancer is a complex polygenic disease in which genetic factors play a significant role in disease etiology. Genome-wide association study(GWAS) identified a novel variant on chromosome 9q22.33as a susceptibility locus of epithelial ovarian cancer (EOC) in Han Chinese population. However, the underline mechanism of this region was still unknown. In this study, we conducted a fine-mapping analysis of 130kb region including 1,039 variants in 200 health women. Ten variants were selected to evaluate the association with EOC risk in 1,099 EOC cases and 1,591 controls. We identified two variants were significantly associated with ovarian cancer risk (rs7027650, P=1.91 × 10−7; rs1889268, P=3.71 × 10−2). Expression quantitative trait locus (eQTL) analysis found thatrs7027650was significantly correlated with COL15A1 gene expression (P=0.009). Luciferase reporter gene assay confirmed that rs7027650 could interact with the promoter region of COL15A1 to reduce its activity. Electrophoretic Mobility ShiftAssay (EMSA) showed theallele-specific binding capacity of rs7027650. These findings revealed that rs7027650 may be a potential causal variant at 9q22.33 region and may regulate the expression level of COL15A1. This study provided a clue for the molecular mechanism of potential causal variantaffecting the risk of ovarian cancer. Citation Format: an Li, Tongyu Xing, Yanrui Zhao, Kexin Chen, Hong Zheng. Fine-scale mapping of chromosome 9q22.33 identifies candidate causal variant in ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB147.

Genome-wide Association Studies of Novel Resilience Traits Identify Important Immune QTL Regions and Candidate Genes in Duroc Pigs

Resilience traits in pig populations allow animals to deal better with infectious disease and suboptimal production environments. The data on daily weight, feed intake and feed behaviors in pigs are collected in test period by automated feeding stations, which facilitate to evaluate the resilience traits. In this study, we adopted the mean square error roots (RMSE) of ordinary least squares (OLS) and the negative residuals of quantile regression (QR) to generate four different novel resilience traits using daily records of feed intake and feed duration between 90 and 180 days of age in a population of commercial Duroc pigs. The genome-wide association studies (GWAS) based on single- and two- trait mixed models were carried out on 550 pigs using 48,603 single nucleotide polymorphisms (SNPs) to identify genomic regions associated with resilience traits in growing pigs. We further focused on the GWAS signals to conduct gene annotation, colocalization with multi-tissue eQTL summary statistics of PigGTEx project and identification of enhancers and promoters using the publicly available data. The genomic heritabilities of four novel resilience traits ranged from 0.09 to 0.41. The pairwise genetic and phenotypic correlations ranged from 0.16 to 0.95 and from 0.05 to 0.36, respectively. Twenty-seven SNPs were identified to be significantly associated with these resilience traits. They were distributed on nine chromosomes (SSC1, SSC2, SSC6, SSC7, SSC8, SSC12, SSC14, SSC16, and SSC17). After annotation, 39 QTLs and 49 candidate genes were identified. Several of these are functionally relevant candidate genes including OTUD4, TIFA and CARD14, which are involved in the host immune response, disease susceptibility and signal transduction. Eight unique SNPs were found to be causal in both GWAS and eQTL analyses across 15 tissues. Notably, one SNP (rs80794541) was associated with eQTLs identified concurrently across seven tissues/cell types, including the macrophage cell type. Furthermore, four significant SNPs (rs81467127, rs81356029, rs80794541, and rs81305085) were linked to the function of the primed enhancer, active element, and poised promoter in five pig tissues. Using the porcine fibroblast HiC dataset, SNP (rs81356029) on SSC2 regulates the CARNS1 and SSH3, while SNP (rs80794541) on SSC7 regulates the H2AC6. In this study, we generated four novel resilience traits and identified SNPs significantly associated with these resilience traits in a Duroc pig population. GWAS signals were associated with candidate genes involving in the immune traits, and were linked to the crucial regulatory elements as well. Our findings will contribute to elucidating the genetic mechanism that can enhance genome-enabled breeding and inform further research on resilience in domestic pigs.

Association between novel genetic variants of Notch signaling pathway genes and survival of hepatitis B virus-related hepatocellular carcinoma.

Although the Notch pathway plays an important role in formation and progression of hepatocellular carcinoma (HCC), few studies have reported the associations between functional genetic variants and the survival of hepatitis B virus (HBV)-related HCC. In the present study, we performed multivariable Cox proportional hazard regression analysis to evaluate associations between 36,101 SNPs in 264 Notch pathway-related genes and overall survival (OS) of 866 patients with HBV-related HCC. It was found that three independent SNPs (NEURL1B rs4868192, CNTN1 rs444927 and FCER2 rs1990975) were significantly associated with the HBV-related HCC OS. The number of protective genotypes (NPGs) were significantly associated with better survival in a dose-response manner (ptrend <0.001). Compared with the model with sole clinical factors, the addition of protective genotypes to the predict models significantly increased the AUC, i.e., from 72.72% to 75.13% (p = 0.002) and from 72.04% to 74.76 (p = 0.004) for 3-year and 5-year OS, respectively. The expression quantitative trait loci (eQTL) analysis further revealed that the rs4868192 C allele was associated with lower mRNA expression levels of NEURL1B in the whole blood (p = 1.71 × 10-3), while the rs1990975 T allele was correlated with higher mRNA expression levels of FCER2 in the whole blood and normal liver tissues (p = 3.51 × 10-5 and 0.033, respectively). Three potentially functional SNPs of NEURL1B, CNTN1 and FCER2 may serve as potential prognostic biomarkers for HBV-related HCC.

A common regulatory haplotype doubles lactoferrin concentration in milk

BackgroundBovine lactoferrin (Lf) is an iron absorbing whey protein with antibacterial, antiviral, and antifungal activity. Lactoferrin is economically valuable and has an extremely variable concentration in milk, partly driven by environmental influences such as milking frequency, involution, or mastitis. A significant genetic influence has also been previously observed to regulate lactoferrin content in milk. Here, we conducted genetic mapping of lactoferrin protein concentration in conjunction with RNA-seq, ChIP-seq, and ATAC-seq data to pinpoint candidate causative variants that regulate lactoferrin concentrations in milk.ResultsWe identified a highly-significant lactoferrin protein quantitative trait locus (pQTL), as well as a cislactotransferrin (LTF) expression QTL (cis-eQTL) mapping to the LTF locus. Using ChIP-seq and ATAC-seq datasets representing lactating mammary tissue samples, we also report a number of regions where the openness of chromatin is under genetic influence. Several of these also show highly significant QTL with genetic signatures similar to those highlighted through pQTL and eQTL analysis. By performing correlation analysis between these QTL, we revealed an ATAC-seq peak in the putative promotor region of LTF, that highlights a set of 115 high-frequency variants that are potentially responsible for these effects. One of the 115 variants (rs110000337), which maps within the ATAC-seq peak, was predicted to alter binding sites of transcription factors known to be involved in lactation-related pathways.ConclusionsHere, we report a regulatory haplotype of 115 variants with conspicuously large impacts on milk lactoferrin concentration. These findings could enable the selection of animals for high-producing specialist herds.

Integrative Multi-omics Analysis Identifies Genetic Variants Contributing to Non-syndromic Cleft Lip with or without Cleft Palate.

To provide novel insights into the aetiology of non-syndromic cleft lip with or without cleft palate (NSCL/P) by integrating multi-omics data and exploring susceptibility genes associated with NSCL/P. A two-stage genome-wide association study (GWAS) of NSCL/P was performed, involving a total of 1,069 cases and 1,724 controls. Using promoter capture Hi-C (pCHi-C) datasets in human embryonic stem cells (hESC) and chromatin immunoprecipitation sequencing (ChIP-seq) in craniofacial tissues, we filtered out single nucleotide polymorphisms (SNPs) with active cis-regulation and their target genes. Additionally, we employed expression quantitative trait loci (eQTL) analysis to identify candidate genes. Thirteen SNPs were identified as cis-regulation units associated with the risk of NSCL/P. Five of these were proven to be active in chromatin states in early human craniofacial development (rs7218002: odds ratio [OR] 1.50, P = 8.14E-08; rs835367: OR 0.78, P = 3.48E- 05; rs77022994: OR 0.55, P = 1.05E-04; rs961470: OR 0.73, P = 1.38E-04; rs17314727: OR 0.73, P = 1.85E-04). Additionally, pCHi-C and eQTL analysis prioritised three candidate genes (rs7218002: NTN1, rs835367: FGGY, LINC01135). NTN1 and FGGY were expressed in mouse orofacial development. Deficiencies in NTN1, FGGY and LINC01135 were associated with cleft palate and cleft lip, abnormal facial shape and bifid uvula, and abnormality of the face, respectively. Our study identified five SNPs (rs7218002, rs835367, rs77022994, rs961470 and rs17314727) and three susceptibility genes (NTN1, FGGY and LINC01135) associated with NSCL/P. These findings contribute to a better understanding of the genetic factors involved.

Integration of apaQTL and eQTL analysis reveals novel SNPs associated with occupational pulmonary fibrosis risk.

To explore the association between apaQTL/eQTL-SNPs and the susceptibility to silicosis. A silicosis-related GWAS was initially conducted to screen for single nucleotide polymorphisms (SNPs) associated with the risk of silicosis. Candidate SNPs with apaQTL and eQTL functions were then obtained from the 3'aQTL-atlas and GTEx databases. Subsequently, additional case-control studies were performed to validate the relationship between the candidate apaQTL/eQTL-SNPs and the risk of silicosis. Finally, experiments were conducted to illustrate APA events occurring at different alleles of the identified apaQTL/eQTL-SNPs. The combined results of the GWAS and iMLDR validations indicate that the variant T allele of the rs2974341 located on SMIM19 (additive model: OR = 0.66, the 95% CI = 0.53-0.84, P = 0.001) and the variant T allele of the rs2390488 located on TMTC4 (additive model: OR = 0.72, 95% CI = 0.57-0.90, P = 0.005) were significantly associated with decreased risk of developing silicosis susceptibility. Furthermore, 3'RACE experiments verified the presence of two poly (A) sites (proximal and distal) in SMIM19, rs2974341 may remotely regulate the binding between miRNA-3646 and SMIM19 with its high LD locus rs2974353 to affect the expression level of SMIM19. The rs2974341 variant T allele may contribute to the generation of the shorter 3'UTR transcript of SMIM19 and affect the binding of miRNA-3646 to the target gene SMIM19. The apaQTL/eQTL-SNPs may provide new perspectives for evaluating the regulatory function of SNPs in the development of silicosis.

Epigenome-augmented eQTL-hotspots reveal genome-wide transcriptional programs in 36 human tissues.

Expression quantitative trait loci (eQTLs) are used to inform the mechanisms of transcriptional regulation in eukaryotic cells. However, the specificity of genome-wide eQTL identification is limited by stringent control for false discoveries. Here, we described a method based on the non-homogeneous Poisson process to identify 125489 regions with highly frequent, multiple eQTL associations, or 'eQTL-hotspots', from the public database of 59 human tissues or cell types. We stratified the eQTL-hotspots into two classes with their distinct sequence and epigenomic characteristics. Based on these classifications, we developed a machine-learning model, E-SpotFinder, for augmented discovery of tissue- or cell-type-specific eQTL-hotspots. We applied this model to 36 tissues or cell types. Using augmented eQTL-hotspots, we recovered 655402 eSNPs and reconstructed a comprehensive regulatory network of 2725380 cis-interactions among eQTL-hotspots. We further identified 52012 modules representing transcriptional programs with unique functional backgrounds. In summary, our study provided a framework of epigenome-augmented eQTL analysis and thereby constructed comprehensive genome-wide networks of cis-regulations across diverse human tissues or cell types.