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Abstract Background Integration of high throughput DNA genotyping and RNA-sequencing data enables the discovery of genomic regions that regulate gene expression, known as expression quantitative trait loci (eQTL). In pigs, efforts to date have been mainly focused on purebred lines for traits with commercial relevance as such growth and meat quality. However, little is known on genetic variants and mechanisms associated with the robustness of an animal, thus its overall health status. Here, the liver, lung, spleen, and muscle transcriptomes of 100 three-way crossbred female finishers were studied, with the aim of identifying novel eQTL regulatory regions and transcription factors (TFs) associated with regulation of porcine metabolism and health-related traits. Results An expression genome-wide association study with 535,896 genotypes and the expression of 12,680 genes in liver, 13,310 genes in lung, 12,650 genes in spleen, and 12,595 genes in muscle resulted in 4,293, 10,630, 4,533, and 6,871 eQTL regions for each of these tissues, respectively. Although only a small fraction of the eQTLs were annotated as cis-eQTLs, these presented a higher number of polymorphisms per region and significantly stronger associations with their target gene compared to trans-eQTLs. Between 20 and 115 eQTL hotspots were identified across the four tissues. Interestingly, these were all enriched for immune-related biological processes. In spleen, two TFs were identified: ERF and ZNF45, with key roles in regulation of gene expression. Conclusions This study provides a comprehensive analysis with more than 26,000 eQTL regions identified that are now publicly available. The genomic regions and their variants were mostly associated with tissue-specific regulatory roles. However, some shared regions provide new insights into the complex regulation of genes and their interactions that are involved with important traits related to metabolism and immunity.

Background: Integration of high throughput DNA genotyping and RNA-sequencing data enables the discovery of genomic regions that regulate gene expression, known as expression quantitative trait loci (eQTL). In pigs, efforts to date have been mainly focused on purebred lines for traits with commercial relevance as such growth and meat quality. However, little is known on genetic variants and mechanisms associated with the robustness of an animal, thus its overall health status. Here, the liver, lung, spleen, and muscle transcriptomes of 100 three-way crossbred female finishers were studied, with the aim of identifying novel eQTL regulatory regions and transcription factors (TFs) associated with regulation of porcine metabolism and health-related traits. Results: An expression genome-wide association study with 535,896 genotypes and the expression of 12,680 genes in liver, 13,310 genes in lung, 12,650 genes in spleen, and 12,595 genes in muscle resulted in 4,293, 10,630, 4,533, and 6,871 eQTL regions for each of these tissues, respectively. Although only a small fraction of the eQTLs were annotated as cis-eQTLs, these presented a higher number of polymorphisms per region and significantly stronger associations with their target gene compared to trans-eQTLs. Between 20 and 115 eQTL hotspots were identified across the four tissues. Interestingly, these were all enriched for immune-related biological processes. In spleen, two TFs were identified: ERF and ZNF45, with key roles in regulation of gene expression. Conclusions: This study provides a comprehensive analysis with more than 26,000 eQTL regions identified that are now publicly available. The genomic regions and their variants were mostly associated with tissue-specific regulatory roles. However, some shared regions provide new insights into the complex regulation of genes and their interactions that are involved with important traits related to metabolism and immunity. [ABSTRACT FROM AUTHOR]

Despite collective efforts to understand the complex regulation of reproductive traits, no causative genes and/or mutations have been reported yet. By integrating genomics and transcriptomics data, potential regulatory mechanisms may be unveiled, providing opportunities to dissect the genetic factors governing fertility. Herein, we identified regulatory variants from RNA-Seq data associated with gene expression regulation in the uterine luminal epithelial cells of beef cows. We identified 4676 cis and 7682 trans eQTLs (expression quantitative trait loci) affecting the expression of 1120 and 2503 genes, respectively (FDR < 0.05). These variants affected the expression of transcription factor coding genes (71 cis and 193 trans eQTLs) and genes previously reported as differentially expressed between pregnant and nonpregnant cows. Functional over-representation analysis highlighted pathways related to metabolism, immune response, and hormone signaling (estrogen and GnRH) affected by eQTL-regulated genes (p-value ≤ 0.01). Furthermore, eQTLs were enriched in QTL regions for 13 reproduction-related traits from the CattleQTLdb (FDR ≤ 0.05). Our study provides novel insights into the genetic basis of reproductive processes in cattle. The underlying causal mechanisms modulating the expression of uterine genes warrant further investigation. [ABSTRACT FROM AUTHOR]

Antibodies play a crucial role in activating protective immunity against malaria by interacting with Fc-gamma receptors (FcγRs). Genetic variations in genes encoding FcγRs can affect immune cell responses to the parasite. In this study, our aim was to investigate whether non-coding variants that regulate FcγR expression could influence the prevalence of Plasmodium falciparum infection. Through bioinformatics approaches, we selected expression quantitative trait loci (eQTL) for FCGR2A, FCGR2B, FCGR2C, FCGR3A, and FCGR3B genes encoding FcγRs (FCGR), in whole blood. We prioritized two regulatory variants, rs2099684 and rs1771575, located in open genomic regions. These variants were identified using RegVar, ImmuNexUT, and transcription factor annotations specific to immune cells. In addition to these, we genotyped the coding variants FCGR2A/rs1801274 and FCGR2B/rs1050501 in 234 individuals from a malaria-endemic area in Burkina Faso. We conducted age and family-based analyses to evaluate associations with the prevalence of malarial infection in both children and adults. The analysis revealed that the regulatory rs1771575-CC genotype was predicted to influence FCGR2B/FCGR2C/FCGR3A transcripts in immune cells and was the sole variant associated with a higher prevalence of malarial infection in children. In conclusion, this study identifies the rs1771575 cis-regulatory variant affecting several FcγRs in myeloid and neutrophil cells and associates it with the inter-individual capacity of children living in Burkina Faso to control malarial infection. [ABSTRACT FROM AUTHOR]

Abstract Background Genome-wide association studies have identified ATP2B4 as a severe malaria resistance gene. Recently, 8 potential causal regulatory variants have been shown to be associated with severe malaria. Methods Genotyping of rs10900585, rs11240734, rs1541252, rs1541253, rs1541254, rs1541255, rs10751450, rs10751451 and rs10751452 was performed in 154 unrelated individuals (79 controls and 75 mild malaria patients). rs10751450, rs10751451 and rs10751452 were genotyped by Taqman assays, whereas the fragment of the ATP2B4 gene containing the remaining SNPs was sequenced. Logistic regression analysis was used to assess the association between the SNPs and mild malaria. Results The results showed that mild malaria was associated with rs10900585, rs11240734, rs1541252, rs1541253, rs1541254, rs1541255, rs10751450, rs10751451 and rs10751452. The homozygous genotypes for the major alleles were associated with an increased risk of mild malaria. Furthermore, the haplotype containing the major alleles and that containing the minor alleles were the most frequent haplotypes. Individuals with the major haplotypes had a significantly higher risk of mild malaria compared to the carriers of the minor allele haplotype. Conclusions ATP2B4 polymorphisms that have been associated with severe malaria are also associated with mild malaria.

We evaluate whether human induced pluripotent stem cell-derived retinal pigment epithelium (iPSC-RPE) cells can be used to prioritize and functionally characterize causal variants at age-related macular degeneration (AMD) risk loci. We generated iPSC-RPE from six subjects and show that they have morphological and molecular characteristics similar to those of native RPE. We generated RNA-seq, ATAC-seq, and H3K27ac ChIP-seq data and observed high similarity in gene expression and enriched transcription factor motif profiles between iPSC-RPE and human fetal RPE. We performed fine mapping of AMD risk loci by integrating molecular data from the iPSC-RPE, adult retina, and adult RPE, which identified rs943080 as the probable causal variant at VEGFA. We show that rs943080 is associated with altered chromatin accessibility of a distal ATAC-seq peak, decreased overall gene expression of VEGFA, and allele-specific expression of a non-coding transcript. Our study thus provides a potential mechanism underlying the association of the VEGFA locus with AMD.

Background: Genome-wide association studies have identified ATP2B4 as a severe malaria resistance gene. Recently, 8 potential causal regulatory variants have been shown to be associated with severe malaria. Methods: Genotyping of rs10900585, rs11240734, rs1541252, rs1541253, rs1541254, rs1541255, rs10751450, rs10751451 and rs10751452 was performed in 154 unrelated individuals (79 controls and 75 mild malaria patients). rs10751450, rs10751451 and rs10751452 were genotyped by Taqman assays, whereas the fragment of the ATP2B4 gene containing the remaining SNPs was sequenced. Logistic regression analysis was used to assess the association between the SNPs and mild malaria. Results: The results showed that mild malaria was associated with rs10900585, rs11240734, rs1541252, rs1541253, rs1541254, rs1541255, rs10751450, rs10751451 and rs10751452. The homozygous genotypes for the major alleles were associated with an increased risk of mild malaria. Furthermore, the haplotype containing the major alleles and that containing the minor alleles were the most frequent haplotypes. Individuals with the major haplotypes had a significantly higher risk of mild malaria compared to the carriers of the minor allele haplotype. Conclusions: ATP2B4 polymorphisms that have been associated with severe malaria are also associated with mild malaria. [ABSTRACT FROM AUTHOR]

Plants activate a variable response to drought stress by modulating transcription of key genes. However, our knowledge of genetic variations governing gene expression in response to drought stress remains limited in natural germplasm. Here, we performed a comprehensive analysis of the transcriptional variability of 200 wheat accessions in response to drought stress by using a systems genetics approach integrating pan-transcriptome, co-expression networks, transcriptome-wide association study (TWAS), and expression quantitative trait loci (eQTLs) mapping. We identified 1621 genes and eight co-expression modules significantly correlated with wheat drought tolerance. We also defined 620 664 and 654 798 independent eQTLs associated with the expression of 17 429 and 18 080 eGenes under normal and drought stress conditions. Focusing on dynamic regulatory variants, we further identified 572 eQTL hotspots and constructed transcription factors governed drought-responsive network by the XGBoost model. Subsequently, by combining with genome-wide association study (GWAS), we uncovered a 369-bp insertion variant in the TaKCS3 promoter containing multiple cis-regulatory elements recognized by eQTL hotspot-associated transcription factors that enhance its transcription. Further functional analysis indicated that elevating TaKCS3 expression affects cuticular wax composition to reduce water loss during drought stress, and thereby increase drought tolerance. This study sheds light on the genome-wide genetic variants that influence dynamic transcriptional changes during drought stress and provides a valuable resource for the mining of drought-tolerant genes in the future., (© 2025 The Author(s). Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

Background: Causal variants for complex traits, such as eQTL are often found in non-coding regions of the genome, where they are hypothesised to influence phenotypes by regulating gene expression. Many regulatory regions are marked by histone modifications, which can be assayed by chromatin immunoprecipitation followed by sequencing (ChIP-seq). Sequence reads from ChIP-seq form peaks at putative regulatory regions, which may reflect the amount of regulatory activity at this region. Therefore, eQTL which are also associated with differences in histone modifications are excellent candidate causal variants. Results: We assayed the histone modifications H3K4Me3, H3K4Me1 and H3K27ac and mRNA in the mammary gland of up to 400 animals. We identified QTL for peak height (histone QTL), exon expression (eeQTL), allele specific expression (aseQTL) and allele specific binding (asbQTL). By intersecting these results, we identify variants which may influence gene expression by altering regulatory regions of the genome, and may be causal variants for other traits. Lastly, we find that these variants are found in putative transcription factor binding sites, identifying a mechanism for the effect of many eQTL. Conclusions: We find that allele specific and traditional QTL analysis often identify the same genetic variants and provide evidence that many eQTL are regulatory variants which alter activity at regulatory regions of the bovine genome. Our work provides methodological and biological updates on how regulatory mechanisms interplay at multi-omics levels. [ABSTRACT FROM AUTHOR]

There is growing evidence for the role of DNA methylation (DNAm) quantitative trait loci (mQTLs) in the genetics of complex traits, including psychiatric disorders. However, due to extensive linkage disequilibrium (LD) of the genome, it is challenging to identify causal genetic variations that drive DNAm levels by population-based genetic association studies. This limits the utility of mQTLs for fine-mapping risk loci underlying psychiatric disorders identified by genome-wide association studies (GWAS). Here we present INTERACT, a deep learning model that integrates convolutional neural networks with transformer, to predict effects of genetic variations on DNAm levels at CpG sites in the human brain. We show that INTERACT-derived DNAm regulatory variants are not confounded by LD, are concentrated in regulatory genomic regions in the human brain, and are convergent with mQTL evidence from genetic association analysis. We further demonstrate that predicted DNAm regulatory variants are enriched for heritability of brain-related traits and improve polygenic risk prediction for schizophrenia across diverse ancestry samples. Finally, we applied predicted DNAm regulatory variants for fine-mapping schizophrenia GWAS risk loci to identify potential novel risk genes. Our study shows the power of a deep learning approach to identify functional regulatory variants that may elucidate the genetic basis of complex traits. [ABSTRACT FROM AUTHOR]

Abstract Background Congenital heart disease (CHD) is the leading cause of mortality from birth defects. In adult CHD patients with successful surgical repair, cardiac complications including heart failure develop at late stage, likely due to genetic causes. To date, many mutations in cardiac developmental genes have been associated with CHD. Recently, regulatory variants in genes have been linked to many human diseases. Although mutations and splicing variants in GATA4 gene have been reported in CHD patients, few regulatory variants of GATA4 gene are identified in CHD patients. Methods GATA4 gene regulatory region was investigated in the patients with atrial septal defects (ASD) (n = 332) and ethnic-matched controls (n = 336). Results Five heterozygous regulatory variants including four SNPs [g.31360 T>C (rs372004083), g.31436G>A, g.31437C>A (rs769262495), g.31487C>G (rs1053351749) and g.31856C>T (rs1385460518)] were only identified in ASD patients. Functional analysis indicated that the regulatory variants significantly affected the transcriptional activity of GATA4 gene promoter. Furthermore, two of the five regulatory variants have evidently effected on transcription factor binding sites. Conclusions Our data suggested that GATA4 gene regulatory variants may confer ASD susceptibility by decreasing GATA4 levels.

Abstract Background Type 2 diabetes mellitus (T2D) is a common and complex disease. Dysfunction of pancreatic β cells, which cannot release sufficient insulin, plays a central role in T2D. Genetics plays a critical role in T2D etiology. Transcription factor GATA4 is required for the pancreatic development, and GATA4 gene mutations are implicated in neonatal or childhood-onset diabetes. In this study, we aimed to investigate whether regulatory variants in GATA4 gene may change GATA4 levels, conferring susceptibility to T2D development. Methods The promoter region of GATA4 gene was analyzed by targeted sequencing in T2D patients (n = 255) and ethnic-matched controls (n = 371). Dual luciferase activity assay was used for functional study, and EMSA (electrophoretic mobility shift assay) was performed for detecting transcription factor binding. Results Thirteen regulatory variants including 5 SNPs were identified. A novel heterozygous variant (32124C > T) and one SNP [31487C > G (rs1053351749)] were only identified in T2D. Both regulatory variants significantly affected GATA4 gene promoter activity in cultured HEK-293 and INS-1 cells. Furthermore, the variant (32124C > T) evidently enhanced the binding of unknown transcriptional activator. Conclusions Our data suggested that GATA4 gene regulatory variants may contribute to T2D development as a rare risk factor.

Abstract Background Gene expression is a key determinant of cellular response. Natural variation in gene expression bridges genetic variation to phenotypic alteration. Identification of the regulatory variants controlling the gene expression in response to drought, a major environmental threat of crop production worldwide, is of great value for drought-tolerant gene identification. Results A total of 627 RNA-seq analyses are performed for 224 maize accessions which represent a wide genetic diversity under three water regimes; 73,573 eQTLs are detected for about 30,000 expressing genes with high-density genome-wide single nucleotide polymorphisms, reflecting a comprehensive and dynamic genetic architecture of gene expression in response to drought. The regulatory variants controlling the gene expression constitutively or drought-dynamically are unraveled. Focusing on dynamic regulatory variants resolved to genes encoding transcription factors, a drought-responsive network reflecting a hierarchy of transcription factors and their target genes is built. Moreover, 97 genes are prioritized to associate with drought tolerance due to their expression variations through the Mendelian randomization analysis. One of the candidate genes, Abscisic acid 8′-hydroxylase, is verified to play a negative role in plant drought tolerance. Conclusions This study unravels the effects of genetic variants on gene expression dynamics in drought response which allows us to better understand the role of distal and proximal genetic effects on gene expression and phenotypic plasticity. The prioritized drought-associated genes may serve as direct targets for functional investigation or allelic mining.

Dopaminergic neurons (DA neurons) are controlled by multiple factors, many involved in neurological disease. Parkinson's disease motor symptoms are caused by the demise of nigral DA neurons, leading to loss of striatal dopamine (DA). Here, we measured DA concentration in the dorsal striatum of 32 members of Collaborative Cross (CC) family and their eight founder strains. Striatal DA varied greatly in founders, and differences were highly heritable in the inbred CC progeny. We identified a locus, containing 164 genes, linked to DA concentration in the dorsal striatum on chromosome X. We used RNAseq profiling of the ventral midbrain of two founders with substantial difference in striatal DA–C56BL/6 J and A/J—to highlight potential protein‐coding candidates modulating this trait. Among the five differentially expressed genes within the locus, we found that the gene coding for the collagen IV alpha 6 chain (Col4a6) was expressed nine times less in A/J than in C57BL/6J. Using single cell RNA‐seq data from developing human midbrain, we found that COL4A6 is highly expressed in radial glia‐like cells and neuronal progenitors, indicating a role in neuronal development. Collagen IV alpha‐6 chain (COL4A6) controls axogenesis in simple model organisms. Consistent with these findings, A/J mice had less striatal axonal branching than C57BL/6J mice. We tentatively conclude that DA concentration and axonal branching in dorsal striatum are modulated by COL4A6, possibly during development. Our study shows that genetic mapping based on an easily measured Central Nervous System (CNS) trait, using the CC population, combined with follow‐up observations, can parse heritability of such a trait, and nominate novel functions for commonly expressed proteins. [ABSTRACT FROM AUTHOR]

We sequenced the genomes of 200 individuals from 41 families multiply affected with bipolar disorder (BD) to identify contributions of rare variants to genetic risk. We initially focused on 3,087 candidate genes with known synaptic functions or prior evidence from genome-wide association studies. BD pedigrees had an increased burden of rare variants in genes encoding neuronal ion channels, including subunits of GABAA receptors and voltage-gated calcium channels. Four uncommon coding and regulatory variants also showed significant association, including a missense variant in GABRA6. Targeted sequencing of 26 of these candidate genes in an additional 3,014 cases and 1,717 controls confirmed rare variant associations in ANK3, CACNA1B, CACNA1C, CACNA1D, CACNG2, CAMK2A, and NGF. Variants in promoters and 5' and 3' UTRs contributed more strongly than coding variants to risk for BD, both in pedigrees and in the case-control cohort. The genes and pathways identified in this study regulate diverse aspects of neuronal excitability. We conclude that rare variants in neuronal excitability genes contribute to risk for BD.

• Non-coding variants can have a significant impact on both common and rare diseases. • In silico analysis could identify non-coding variants exerting regulatory effects. • Comprehensive in silico analysis of non-coding variants within the ACE2 gene locus. • Identification of non-coding variants modulating ACE2 function and expression levels. The surge in human whole-genome sequencing data has facilitated the study of non-coding region variations, yet understanding their biological significance remains a challenge. We used a computational workflow to assess the regulatory potential of non-coding variants, with a particular focus on the Angiotensin Converting Enzyme 2 (ACE2) gene. This gene is crucial in physiological processes and serves as the entry point for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus causing coronavirus disease 19 (COVID-19). In our analysis, using data from the gnomAD population database and functional annotation, we identified 17 significant Single Nucleotide Variants (SNVs) in ACE2 , particularly in its enhancers, promoters, and 3′ untranslated regions (UTRs). We found preliminary evidence supporting the regulatory impact of some of these variants on ACE2 expression. Our detailed examination of two SNVs, rs147718775 and rs140394675, in the ACE2 promoter revealed that these co-occurring SNVs, when mutated, significantly enhance promoter activity, suggesting a possible increase in specific ACE2 isoform expression. This method proves effective in identifying and interpreting impactful non-coding variants, aiding in further studies and enhancing understanding of molecular bases of monogenic and complex traits. [ABSTRACT FROM AUTHOR]

Genetic effects on gene expression and splicing can be modulated by cellular and environmental factors; yet interactions between genotypes, cell type, and treatment have not been comprehensively studied together. We used an induced pluripotent stem cell system to study multiple cell types derived from the same individuals and exposed them to a large panel of treatments. Cellular responses involved different genes and pathways for gene expression and splicing and were highly variable across contexts. For thousands of genes, we identified variable allelic expression across contexts and characterized different types of gene-environment interactions, many of which are associated with complex traits. Promoter functional and evolutionary features distinguished genes with elevated allelic imbalance mean and variance. On average, half of the genes with dynamic regulatory interactions were missed by large eQTL mapping studies, indicating the importance of exploring multiple treatments to reveal previously unrecognized regulatory loci that may be important for disease.

Background: Congenital heart disease (CHD) is the leading cause of mortality from birth defects. In adult CHD patients with successful surgical repair, cardiac complications including heart failure develop at late stage, likely due to genetic causes. To date, many mutations in cardiac developmental genes have been associated with CHD. Recently, regulatory variants in genes have been linked to many human diseases. Although mutations and splicing variants in GATA4 gene have been reported in CHD patients, few regulatory variants of GATA4 gene are identified in CHD patients.Methods: GATA4 gene regulatory region was investigated in the patients with atrial septal defects (ASD) (n = 332) and ethnic-matched controls (n = 336).Results: Five heterozygous regulatory variants including four SNPs [g.31360 T>C (rs372004083), g.31436G>A, g.31437C>A (rs769262495), g.31487C>G (rs1053351749) and g.31856C>T (rs1385460518)] were only identified in ASD patients. Functional analysis indicated that the regulatory variants significantly affected the transcriptional activity of GATA4 gene promoter. Furthermore, two of the five regulatory variants have evidently effected on transcription factor binding sites.Conclusions: Our data suggested that GATA4 gene regulatory variants may confer ASD susceptibility by decreasing GATA4 levels. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes mellitus (T2D) is a common and complex disease. Dysfunction of pancreatic β cells, which cannot release sufficient insulin, plays a central role in T2D. Genetics plays a critical role in T2D etiology. Transcription factor GATA4 is required for the pancreatic development, and GATA4 gene mutations are implicated in neonatal or childhood-onset diabetes. In this study, we aimed to investigate whether regulatory variants in GATA4 gene may change GATA4 levels, conferring susceptibility to T2D development. Methods: The promoter region of GATA4 gene was analyzed by targeted sequencing in T2D patients (n = 255) and ethnic-matched controls (n = 371). Dual luciferase activity assay was used for functional study, and EMSA (electrophoretic mobility shift assay) was performed for detecting transcription factor binding. Results: Thirteen regulatory variants including 5 SNPs were identified. A novel heterozygous variant (32124C > T) and one SNP [31487C > G (rs1053351749)] were only identified in T2D. Both regulatory variants significantly affected GATA4 gene promoter activity in cultured HEK-293 and INS-1 cells. Furthermore, the variant (32124C > T) evidently enhanced the binding of unknown transcriptional activator. Conclusions: Our data suggested that GATA4 gene regulatory variants may contribute to T2D development as a rare risk factor. [ABSTRACT FROM AUTHOR]

BackgroundAnalysis of variants in distant regulatory elements could improve the current 25–50% yield of genetic testing for monogenic diseases. However, the vast size of the regulome, great number of variants, and the difficulty in predicting their phenotypic impact make searching for pathogenic variants in the regulatory genome challenging. New tools for the identification of regulatory variants based on their relevance to the phenotype are needed.MethodsWe used tissue-specific regulatory loci mapped by ENCODE and FANTOM, together with miRNA–gene interactions from miRTarBase and miRWalk, to develop Remus, a web application for the identification of tissue-specific regulatory regions. Remus searches for regulatory features linked to the known disease-associated genes and filters them using activity status in the target tissues relevant for the studied disorder. For user convenience, Remus provides a web interface and facilitates in-browser filtering of variant files suitable for sensitive patient data.ResultsTo evaluate our approach, we used a set of 146 regulatory mutations reported causative for 68 distinct monogenic disorders and a manually curated a list of tissues affected by these disorders. In 89.7% of cases, Remus identified the regulator containing the pathogenic mutation. The tissue-specific search limited the number of considered variants by 82.5% as compared to a tissue-agnostic search.ConclusionRemus facilitates the identification of regulatory regions potentially associated with a monogenic disease and can supplement classical analysis of coding variations with the aim of improving the diagnostic yield in whole-genome sequencing experiments.

Abstract Background The genetic architecture underlying central cornea thickness (CCT) is far from understood. Most of the CCT-associated variants are located in the non-coding regions, raising the difficulty of following functional characterizations. Thus, integrative functional analyses on CCT-associated loci might benefit in overcoming these issues by prioritizing the hub genes that are located in the center of CCT genetic network. Methods Integrative analyses including functional annotations, enrichment analysis, and protein-protein interaction analyses were performed on all reported CCT GWAS lead SNPs, together with their proxy variants. Functional annotations were conducted by CADD, GWAVA, and Eigen. Enrichment analyses for CCT-associated genes were performed using ToppGene suite. Protein-protein interaction network and gene co-expression analyses were performed by GeneMANIA. Results Functional annotations prioritized eight genes (ADAMSTS6, ARID5B, FOXO1, AKAP13, COL4A3, COL8A2, TBL1XR1, and KCMB2) harboring SNPs with strong evidence of regulatory potential. It was also shown that CCT-associated genes were significantly enriched in collagen-related pathways and the phenotype of keratoconus, and some of them were found to be involved in one interaction network. Conclusion This study revealed the hub genes that were located in the center of CCT genetic network and provided a new insight into the genetic regulation underlying CCT GWAS findings.

Background: Analysis of variants in distant regulatory elements could improve the current 25–50% yield of genetic testing for monogenic diseases. However, the vast size of the regulome, great number of variants, and the difficulty in predicting their phenotypic impact make searching for pathogenic variants in the regulatory genome challenging. New tools for the identification of regulatory variants based on their relevance to the phenotype are needed. Methods: We used tissue-specific regulatory loci mapped by ENCODE and FANTOM, together with miRNA–gene interactions from miRTarBase and miRWalk, to develop Remus, a web application for the identification of tissue-specific regulatory regions. Remus searches for regulatory features linked to the known disease-associated genes and filters them using activity status in the target tissues relevant for the studied disorder. For user convenience, Remus provides a web interface and facilitates in-browser filtering of variant files suitable for sensitive patient data. Results: To evaluate our approach, we used a set of 146 regulatory mutations reported causative for 68 distinct monogenic disorders and a manually curated a list of tissues affected by these disorders. In 89.7% of cases, Remus identified the regulator containing the pathogenic mutation. The tissue-specific search limited the number of considered variants by 82.5% as compared to a tissue-agnostic search. Conclusion: Remus facilitates the identification of regulatory regions potentially associated with a monogenic disease and can supplement classical analysis of coding variations with the aim of improving the diagnostic yield in whole-genome sequencing experiments. [ABSTRACT FROM AUTHOR]

Autism is a complex disease with genetic predisposition factors. Real factors for treatment and early diagnosis are yet to be defined. This study integrated transcriptome and exome genotyping for identifying functional variants associated with autism spectrum disorder and their impact on gene expression to find significant variations. More than 1800 patients were screened, and 70 (47 male/23 female) with an average age of 7.56 ± 3.68 years fulfilled the DSM-5 criteria for autism. Analysis revealed 682 SNPs of 589 genes significantly (p < 0.001) associated with autism among the putative functional exonic variants (n = 243,345) studied. Olfactory receptor genes on chromosome 6 were significant after Bonferroni correction (α = 0.05/243345 = 2.05 × 10−7) with a high degree of linkage disequilibrium on 6p22.1 (p = 6.71 × 10−9). The differentially expressed gene analysis of autistic patients compared to controls in whole RNA sequencing identified significantly upregulated (foldchange ≥0.8 and p-value ≤ 0.05; n = 125) and downregulated (foldchange ≤−0.8 and p-value ≤ 0.05; n = 117) genes. The integration of significantly up- and downregulated genes and genes of significant SNPs identified regulatory variants (rs6657480, rs3130780, and rs1940475) associated with the up- (ITGB3BP) and downregulation (DDR1 and MMP8) of genes in autism spectrum disorder in people of Arab ancestries. The significant variants could be a biomarker of interest for identifying early autism among Arabs and helping to characterize the genes involved in the susceptibility mechanisms for autistic subjects.

Abstract Background Genome–phenome studies have identified thousands of variants that are statistically associated with disease or traits; however, their functional roles are largely unclear. A comprehensive investigation of regulatory mechanisms and the gene regulatory networks between phenome-wide association study (PheWAS) and genome-wide association study (GWAS) is needed to identify novel regulatory variants contributing to risk for human diseases. Methods In this study, we developed an integrative functional genomics framework that maps 215,107 significant single nucleotide polymorphism (SNP) traits generated from the PheWAS Catalog and 28,870 genome-wide significant SNP traits collected from the GWAS Catalog into a global human genome regulatory map via incorporating various functional annotation data, including transcription factor (TF)-based motifs, promoters, enhancers, and expression quantitative trait loci (eQTLs) generated from four major functional genomics databases: FANTOM5, ENCODE, NIH Roadmap, and Genotype-Tissue Expression (GTEx). In addition, we performed a tissue-specific regulatory circuit analysis through the integration of the identified regulatory variants and tissue-specific gene expression profiles in 7051 samples across 32 tissues from GTEx. Results We found that the disease-associated loci in both the PheWAS and GWAS Catalogs were significantly enriched with functional SNPs. The integration of functional annotations significantly improved the power of detecting novel associations in PheWAS, through which we found a number of functional associations with strong regulatory evidence in the PheWAS Catalog. Finally, we constructed tissue-specific regulatory circuits for several complex traits: mental diseases, autoimmune diseases, and cancer, via exploring tissue-specific TF-promoter/enhancer-target gene interaction networks. We uncovered several promising tissue-specific regulatory TFs or genes for Alzheimer’s disease (e.g. ZIC1 and STX1B) and asthma (e.g. CSF3 and IL1RL1). Conclusions This study offers powerful tools for exploring the functional consequences of variants generated from genome–phenome association studies in terms of their mechanisms on affecting multiple complex diseases and traits.

Abstract Background Most cancer risk-associated single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) are noncoding and it is challenging to assess their functional impacts. To systematically identify the SNPs that affect gene expression by modulating activities of distal regulatory elements, we adapt the self-transcribing active regulatory region sequencing (STARR-seq) strategy, a high-throughput technique to functionally quantify enhancer activities. Results From 10,673 SNPs linked with 996 cancer risk-associated SNPs identified in previous GWAS studies, we identify 575 SNPs in the fragments that positively regulate gene expression, and 758 SNPs in the fragments with negative regulatory activities. Among them, 70 variants are regulatory variants for which the two alleles confer different regulatory activities. We analyze in depth two regulatory variants—breast cancer risk SNP rs11055880 and leukemia risk-associated SNP rs12142375—and demonstrate their endogenous regulatory activities on expression of ATF7IP and PDE4B genes, respectively, using a CRISPR-Cas9 approach. Conclusions By identifying regulatory variants associated with cancer susceptibility and studying their molecular functions, we hope to help the interpretation of GWAS results and provide improved information for cancer risk assessment.

Many problems of modern genetics and functional genomics require the assessment of functional effects of sequence variants, including gene expression changes. Machine learning is considered to be a promising approach for solving this task, but its practical applications remain a challenge due to the insufficient volume and diversity of training data. A promising source of valuable data is a saturation mutagenesis massively parallel reporter assay, which quantitatively measures changes in transcription activity caused by sequence variants. Here, we explore the computational predictions of the effects of individual single-nucleotide variants on gene transcription measured in the massively parallel reporter assays, based on the data from the recent “Regulation Saturation” Critical Assessment of Genome Interpretation challenge. We show that the estimated prediction quality strongly depends on the structure of the training and validation data. Particularly, training on the sequence segments located next to the validation data results in the “information leakage” caused by the local context. This information leakage allows reproducing the prediction quality of the best CAGI challenge submissions with a fairly simple machine learning approach, and even obtaining notably better-than-random predictions using irrelevant genomic regions. Validation scenarios preventing such information leakage dramatically reduce the measured prediction quality. The performance at independent regulatory regions entirely excluded from the training set appears to be much lower than needed for practical applications, and even the performance estimation will become reliable only in the future with richer data from multiple reporters. The source code and data are available at https://bitbucket.org/autosomeru_cagi2018/cagi2018_regsat and https://genomeinterpretation.org/content/expression-variants.

Background: Dopamine-β-hydroxylase (DBH, EC 1.14.17.1), which converts dopamine to norepinephrine, is a candidate gene in neuropsychiatric diseases.Aim: To assess the effect of regulatory variants in DBH on schizophrenia and its endophenotypes -cognition and tardive dyskinesia.Methods: We tested association of functional variants 19bp Ins/Del, rs1989787 and rs1611115 in DBH with i) schizophrenia (1236 cases, 1136 controls), ii) tardive dyskinesia (83 positive, 162 negative) and iii) performance functions of cognition (357 cases, 306 controls) estimated by the Penn Computerized Neurocognitive Battery.Results: A modest haplotypic (Ins-C; 19bp Ins/Del - rs1989787 C>T; p=0.04) association was observed with schizophrenia. We observed ~39% reduction in activity of 19bp Del allele on luciferase assay. Analysis of covariance revealed interactions of tardive dyskinesia status and: i) 19bp Ins/Del (genotypic, p=0.04) and ii) rs1989787 and rs1611115 (combined genotypic, p=0.004) on Abnormal Involuntary Movement Scale total score. Association of rs1611115 with positive and negative syndrome scale (PANSS) total score (p=0.05) and allelic/genotypic association with lower positive (p=0.03/0.04), general psychopathology (p=0.01/0.01) PANSS scales in tardive dyskinesia-positive; and allelic/genotypic (p=0.02/0.05) with higher score of depressive factors in tardive dyskinesia-negative subgroups were observed. Analysis of covariance with continuous variable of cognition showed interaction of health status with: i) rs1989787 on accuracy and efficiency (p=0.03) of abstraction and mental flexibility; ii) rs1611115 on accuracy of working memory and emotion (p=0.05); iii) 19bp Ins/Del on processing speed of emotion (p=0.03). Allelic/genotypic association of rs1989787 with spatial ability (p=0.02-0.05) among healthy controls; association of rs1611115 with Global Assessment Scale scores in the past month (p=0.05) among schizophrenia subjects of cognition cohort was also observed.Conclusions: With modest genotype-phenotype correlations available for DBH variants, personalized treatment regimens based on DBH activity for ameliorating tardive dyskinesia and cognitive symptoms may be plausible. [ABSTRACT FROM AUTHOR]

Purpose: Protein kinase C alpha (gene: PRKCA) is a key regulator of cardiac contractility. Two genetic variants have recently been discovered to regulate PRKCA expression in failing human heart tissue (rs9909004 [T → C] and rs9303504 [C → G]). The association of those variants with clinical outcomes in patients with heart failure (HF), and their interaction with HF drug efficacy, is unknown. Methods: Patients with HF in a prospective registry starting in 2007 were genotyped by whole genome array (n = 951). The primary outcome was all-cause mortality. Cox proportional hazards models adjusted for established clinical risk factors and genomic ancestry tested the independent association of rs9909004 or rs9303504 and the variant interactions with cornerstone HF pharmacotherapies (beta-blockers or angiotensin-converting enzyme inhibitors/angiotensin receptor blockers) in additive genetic models. Results: The minor allele of rs9909004, but not of rs9303504, was independently associated with a decreased risk for all-cause mortality: adjusted HR = 0.81 (95% CI = 0.67–0.98), p = 0.032. The variants did not significantly interact with mortality benefit associated with cornerstone HF pharmacotherapies (p > 0.1 for all). Conclusions: A recently discovered cardiac-specific regulatory variant for PRKCA (rs9909004) was independently associated with a decreased risk for all-cause mortality in patients with HF. The variant did not interact with mortality benefit associated with cornerstone HF pharmacotherapies. [ABSTRACT FROM AUTHOR]

Variants within non-coding genomic regions can greatly affect disease. In recent years, increasing focus has been given to these variants, and how they can alter regulatory elements, such as enhancers, transcription factor binding sites and DNA methylation regions. Such variants can be considered regulatory variants. Concurrently, much effort has been put into establishing international consortia to undertake large projects aimed at discovering regulatory elements in different tissues, cell lines and organisms, and probing the effects of genetic variants on regulation by measuring gene expression. Here, we describe methods and techniques for discovering disease-associated non-coding variants using sequencing technologies. We then explain the computational procedures that can be used for annotating these variants using the information from the aforementioned projects, and prediction of their putative effects, including potential pathogenicity, based on rule-based and machine learning approaches. We provide the details of techniques to validate these predictions, by mapping chromatin–chromatin and chromatin–protein interactions, and introduce Clustered Regularly Interspaced Short Palindromic Repeats-Associated Protein 9 (CRISPR-Cas9) technology, which has already been used in this field and is likely to have a big impact on its future evolution. We also give examples of regulatory variants associated with multiple complex diseases. This review is aimed at bioinformaticians interested in the characterization of regulatory variants, molecular biologists and geneticists interested in understanding more about the nature and potential role of such variants from a functional point of views, and clinicians who may wish to learn about variants in non-coding genomic regions associated with a given disease and find out what to do next to uncover how they impact on the underlying mechanisms. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWASs) have identified numerous variants associated with polygenic traits and diseases. However, with few exceptions, a mechanistic understanding of which variants affect which genes in which tissues to modulate trait variation is lacking. Here, we present genomic analyses to explain trait heritability of blood pressure (BP) through the genetics of transcriptional regulation using GWASs, multiomics data from different tissues, and machine learning approaches. Approximately 500,000 predicted regulatory variants across four tissues explain 33.4% of variant heritability: 2.5%, 5.3%, 7.7%, and 11.8% for kidney-, adrenal-, heart-, and artery-specific variants, respectively. Variation in the enhancers involved shows greater tissue specificity than in the genes they regulate, suggesting that gene regulatory networks perturbed by enhancer variants in a tissue relevant to a phenotype are the major source of interindividual variation in BP. Thus, our study provides an approach to scan human tissue and cell types for their physiological contribution to any trait. [Display omitted] • Variants in enhancers exhibit greater tissue specificity than gene expression • Enhancer variants disentangle tissue-specific dysregulation of genes and CREs • Artery-specific enhancer variants explain the most heritability of blood pressure Investigating tissue-specific effects of sequence variants on complex traits through a gene regulatory network is challenging. Lee et al. demonstrate that the heritability of blood pressure is largely explained by predicted tissue-specific enhancer variants and that artery-specific enhancer variants are the greatest source of interindividual variation in blood pressure regulation. [ABSTRACT FROM AUTHOR]

Background: Genome-phenome studies have identified thousands of variants that are statistically associated with disease or traits; however, their functional roles are largely unclear. A comprehensive investigation of regulatory mechanisms and the gene regulatory networks between phenome-wide association study (PheWAS) and genomewide association study (GWAS) is needed to identify novel regulatory variants contributing to risk for human diseases. Methods: In this study, we developed an integrative functional genomics framework that maps 215,107 significant single nucleotide polymorphism (SNP) traits generated from the PheWAS Catalog and 28,870 genome-wide significant SNP traits collected from the GWAS Catalog into a global human genome regulatory map via incorporating various functional annotation data, including transcription factor (TF)-based motifs, promoters, enhancers, and expression quantitative trait loci (eQTLs) generated from four major functional genomics databases: FANTOM5, ENCODE, NIH Roadmap, and Genotype-Tissue Expression (GTEx). In addition, we performed a tissue-specific regulatory circuit analysis through the integration of the identified regulatory variants and tissue-specific gene expression profiles in 7051 samples across 32 tissues from GTEx. Results: We found that the disease-associated loci in both the PheWAS and GWAS Catalogs were significantly enriched with functional SNPs. The integration of functional annotations significantly improved the power of detecting novel associations in PheWAS, through which we found a number of functional associations with strong regulatory evidence in the PheWAS Catalog. Finally, we constructed tissue-specific regulatory circuits for several complex traits: mental diseases, autoimmune diseases, and cancer, via exploring tissue-specific TF-promoter/enhancer-target gene interaction networks. We uncovered several promising tissue-specific regulatory TFs or genes for Alzheimer's disease (e.g. ZIC1 and STX1B) and asthma (e.g. CSF3 and IL1RL1). Conclusions: This study offers powerful tools for exploring the functional consequences of variants generated from genome-phenome association studies in terms of their mechanisms on affecting multiple complex diseases and traits. [ABSTRACT FROM AUTHOR]

The haplotype harboring the SPINK1 c.101A>G (p.Asn34Ser) variant (also known as rs17107315:T>C) represents the most important heritable risk factor for idiopathic chronic pancreatitis identified to date. The causal variant contained within this risk haplotype has however remained stubbornly elusive. Herein, we set out to resolve this enigma by employing a hypothesis-driven approach. First, we searched for variants in strong linkage disequilibrium (LD) with rs17107315:T>C using HaploReg v4.1. Second, we identified two candidate SNPs by visual inspection of sequences spanning all 25 SNPs found to be in LD with rs17107315:T>C, guided by prior knowledge of pancreas-specific transcription factors and their cognate binding sites. Third, employing a novel cis-regulatory module (CRM)-guided approach to further filter the two candidate SNPs yielded a solitary candidate causal variant. Finally, combining data from phylogenetic conservation and chromatin accessibility, cotransfection transactivation experiments, and population genetic studies, we suggest that rs142703147:C>A, which disrupts a PTF1L-binding site within an evolutionarily conserved HNF1A−PTF1L CRM located ∼4 kb upstream of the SPINK1 promoter, contributes to the aforementioned chronic pancreatitis risk haplotype. Further studies are required not only to improve the characterization of this functional SNP but also to identify other functional components that might contribute to this high-risk haplotype. [ABSTRACT FROM AUTHOR]

The Na/taurocholate cotransporter NTCP (encoded by SLC10A1 ) was identified as a cellular entry receptor for the human hepatitis B virus (HBV), advancing our understanding of the molecular mechanism of HBV infection. An alternative hypothesis was put forward that regulatory variants in SLC10A1 might play an important role in HBV susceptibility by potentially influencing expression levels of NTCP. The three regulatory SNPs (rs8011311, rs7154439, rs111409076) were genotyped in 1023 HBV-persistent carriers, 735 subjects with HBV natural clearance and 732 HBV marker-negative subjects in a Han Chinese population. Real-time reverse transcription PCR analysis and luciferase assays have been performed to dissect the potential functionality. In logistic regression analysis, when subjects with HBV natural clearance were compared with HBV marker-negative subjects, no significant associations with the risk of HBV infection were observed for any of the three SNPs after adjusting for age, sex, smoking status and alcohol consumption ( P > 0.05). Similar negative results were also found for the three SNPs when HBV-persistent carriers were compared with HBV marker-negative subjects. Likewise, no significant associations with the risk of HBV clearance were observed when HBV-persistent carriers were compared with subjects with HBV natural clearance ( P > 0.05). Quantitative RT/PCR showed no significant difference in NTCP expression levels in normal liver tissue amongst individuals with different rs111409076 genotypes ( P = 0.317 for the general linear model). Moreover, no evident effect of the SLC10A1 rs111409076 AACA/− polymorphism on transcriptional activity was found by luciferase assay in either HepG2 ( P = 0.161) or Hep3b ( P = 0.129) cell lines. The present study indicated that the common variants in the regulatory region of SLC10A1 may not influence the expression of NTCP at the level of transcriptional regulation, and ultimately may not be associated with HBV susceptibility in this Chinese population. [ABSTRACT FROM AUTHOR]

Background: The regulatory effect of inherited or de novo genetic variants occurring in promoters as well as in transcribed or even coding gene regions is gaining greater recognition as a contributing factor to disease processes in addition to mutations affecting protein functionality. Thousands of such regulatory mutations are already recorded in HGMD, OMIM, ClinVar and other databases containing published disease causing and associated mutations. It is therefore important to properly annotate genetic variants occurring in experimentally verified and predicted transcription factor binding sites (TFBS) that could thus influence the factor binding event. Selection of the promoter sequence used is an important factor in the analysis as it directly influences the composition of the sequence available for transcription factor binding analysis. Results: In this study we first establish genomic regions likely to be involved in regulation of gene expression. TRANSFAC uses a method of virtual transcription start sites (vTSS) calculation to define the best supported promoter for a gene. We have performed a comparison of the virtually calculated promoters between the best supported and secondary promoters in hg19 and hg38 reference genomes to test and validate the approach. Next we create and utilize a workflow for systematic analysis of casual disease associated variants in TFBS using Genome Trax and TRANSFAC databases. A total of 841 and 736 experimentally verified TFBSs within best supported promoters were mapped over HGMD and ClinVar mutation sites respectively. Tens of thousands of predicted ChIP-Seq derived TFBSs were mapped over mutations as well. We have further analyzed some of these mutations for potential gain or loss in transcription factor binding. Conclusions: We have confirmed the validity of TRANSFAC's approach to define the best supported promoters and established a workflow of their use in annotation of regulatory genetic variants. [ABSTRACT FROM AUTHOR]

• Screening of upstream variants in FH-related genes of clinically diagnosed FH cases. • Five SNVs prioritized as regulatory variants using prediction and annotation tools. • rs934197, rs9282606, rs36218923, rs538300761, g.55038486A > G as potential regulatory. • APOB rs934197 had the highest HepG2-dependent regulatory prediction score. Familial hypercholesterolemia (FH) is a prevalent autosomal genetic disease associated with increased risk of early cardiovascular events and death due to chronic exposure to very high levels of low-density lipoprotein cholesterol (LDL-c). Pathogenic variants in the coding regions of LDLR , APOB and PCSK9 account for most FH cases, and variants in non-coding regions maybe involved in FH as well. Variants in the upstream region of LDLR , APOB and PCSK9 were screened by targeted next-generation sequencing and their effects were explored using in silico tools. Twenty-five patients without pathogenic variants in FH-related genes were selected. 3 kb upstream regions of LDLR , APOB and PCSK9 were sequenced using the AmpliSeq (Illumina) and Miseq Reagent Nano Kit v2 (Illumina). Sequencing data were analyzed using variant discovery and functional annotation tools. Potentially regulatory variants were selected by integrating data from public databases, published data and context-dependent regulatory prediction score. Thirty-four single nucleotide variants (SNVs) in upstream regions were identified (6 in LDLR , 15 in APOB , and 13 in PCSK9). Five SNVs were prioritized as potentially regulatory variants (rs934197, rs9282606, rs36218923, rs538300761, g.55038486A > G). APOB rs934197 was previously associated with increased rate of transcription, which in silico analysis suggests that could be due to reducing binding affinity of a transcriptional repressor. Our findings highlight the importance of variant screening outside of coding regions of all relevant genes. Further functional studies are necessary to confirm that prioritized variants could impact gene regulation and contribute to the FH phenotype. [ABSTRACT FROM AUTHOR]

Human aging involves a gradual decrease in cellular integrity that contributes to multiple complex disorders such as neurodegenerative disorders, cancer, diabetes, and cardiovascular diseases. Genome-wide association studies (GWAS) play a key role in discovering genetic variations that may contribute towards disease vulnerability. However, mostly disease-associated SNPs lie within non-coding part of the genome; majority of the variants are also present in linkage disequilibrium (LD) with the genome-wide significant SNPs (GWAS lead SNPs). Overall 600 SNPs were analyzed, out of which 291 returned RegulomeDB scores of 1-6. It was observed that just 4 out of those 291 SNPs show strong evidence of regulatory effects (RegulomeDB score <3), while none of them includes any GWAS lead SNP. Nevertheless, this study demonstrates that by combining ENCODE project data along with GWAS reported information will provide important insights on the impact of a genetic variant-moving from GWAS towards understanding disease pathways. It is noteworthy that both genome-wide significant SNPs as well as the SNPs in LD must be considered for future studies; this may prove to be crucial in deciphering the potential regulatory elements involved in complex disorders and aging in particular. [ABSTRACT FROM AUTHOR]

It is challenging to study regulatory genetic variants as gene expression is affected by both genetic polymorphisms and non-genetic regulators. The mRNA allele-specific expression (ASE) assay has been increasingly used for the study of cis-acting regulatory variants because cis-acting variants affect gene expression in an allele-specific manner. However, poor correlations between mRNA and protein expressions were observed for many genes, highlighting the importance of studying gene expression regulation at the protein level. In the present study, we conducted a proof-of-concept study to utilize a recently developed allele-specific protein expression (ASPE) assay to identify the cis-acting regulatory variants of CES1 using a large set of human liver samples. The CES1 gene encodes for carboxylesterase 1 (CES1), the most abundant hepatic hydrolase in humans. Two cis-acting regulatory variants were found to be significantly associated with CES1 ASPE, CES1 protein expression, and its catalytic activity on enalapril hydrolysis in human livers. Compared to conventional gene expression-based approaches, ASPE demonstrated an improved statistical power to detect regulatory variants with small effect sizes since allelic protein expression ratios are less prone to the influence of non-genetic regulators (e.g., diseases and inducers). This study suggests that the ASPE approach is a powerful tool for identifying cis-regulatory variants., (© 2022 The Authors. Proteomics published by Wiley-VCH GmbH.)

Background Genome-wide association studies have yet to identify the majority of genetic variants involved in asthma. We hypothesized that expression quantitative trait locus (eQTL) mapping can identify novel asthma genes by enabling prioritization of putative functional variants for association testing. Objective We evaluated 6706 cis-acting expression-associated variants (eSNPs) identified through a genome-wide eQTL survey of CD4 + lymphocytes for association with asthma. Methods eSNPs were tested for association with asthma in 359 asthmatic patients and 846 control subjects from the Childhood Asthma Management Program, with verification by using family-based testing. Significant associations were tested for replication in 579 parent-child trios with asthma from Costa Rica. Further functional validation was performed by using formaldehyde-assisted isolation of regulatory elements (FAIRE) quantitative PCR and chromatin immunoprecipitation PCR in lung-derived epithelial cell lines (Beas-2B and A549) and Jurkat cells, a leukemia cell line derived from T lymphocytes. Results Cis-acting eSNPs demonstrated associations with asthma in both cohorts. We confirmed the previously reported association of ORMDL3 / GSDMB variants with asthma (combined P = 2.9 × 10 −8 ). Reproducible associations were also observed for eSNPs in 3 additional genes: fatty acid desaturase 2 ( FADS2 ; P = .002), N-acetyl-α-D-galactosaminidase ( NAGA ; P = .0002), and Factor XIII, A1 ( F13A1 ; P = .0001). Subsequently, we demonstrated that FADS2 mRNA is increased in CD4 + lymphocytes in asthmatic patients and that the associated eSNPs reside within DNA segments with histone modifications that denote open chromatin status and confer enhancer activity. Conclusions Our results demonstrate the utility of eQTL mapping in the identification of novel asthma genes and provide evidence for the importance of FADS2 , NAGA , and F13A1 in the pathogenesis of asthma. [ABSTRACT FROM AUTHOR]

Understanding the functional mechanisms underlying genetic signals associated with complex traits and common diseases, such as cancer, diabetes and Alzheimer's disease, is a formidable challenge. Many genetic signals discovered through genome-wide association studies map to non-protein coding sequences, where their molecular consequences are difficult to evaluate. This article summarizes concepts for the systematic interpretation of non-coding genetic signals using genome annotation data sets in different cellular systems. We outline strategies for the global analysis of multiple association intervals and the in-depth molecular investigation of individual intervals. We highlight experimental techniques to validate candidate (potential causal) regulatory variants, with a focus on novel genome-editing techniques including CRISPR/Cas9. These approaches are also applicable to low-frequency and rare variants, which have become increasingly important in genomic studies of complex traits and diseases. There is a pressing need to translate genetic signals into biological mechanisms, leading to prognostic, diagnostic and therapeutic advances. [ABSTRACT FROM AUTHOR]

Autism is a complex disease with genetic predisposition factors. Real factors for treatment and early diagnosis are yet to be defined. This study integrated transcriptome and exome genotyping for identifying functional variants associated with autism spectrum disorder and their impact on gene expression to find significant variations. More than 1800 patients were screened, and 70 (47 male/23 female) with an average age of 7.56 ± 3.68 years fulfilled the DSM-5 criteria for autism. Analysis revealed 682 SNPs of 589 genes significantly (p < 0.001) associated with autism among the putative functional exonic variants (n = 243,345) studied. Olfactory receptor genes on chromosome 6 were significant after Bonferroni correction (α = 0.05/243345 = 2.05 × 10−7) with a high degree of linkage disequilibrium on 6p22.1 (p = 6.71 × 10−9). The differentially expressed gene analysis of autistic patients compared to controls in whole RNA sequencing identified significantly upregulated (foldchange ≥0.8 and p-value ≤ 0.05; n = 125) and downregulated (foldchange ≤−0.8 and p-value ≤ 0.05; n = 117) genes. The integration of significantly up- and downregulated genes and genes of significant SNPs identified regulatory variants (rs6657480, rs3130780, and rs1940475) associated with the up- (ITGB3BP) and downregulation (DDR1 and MMP8) of genes in autism spectrum disorder in people of Arab ancestries. The significant variants could be a biomarker of interest for identifying early autism among Arabs and helping to characterize the genes involved in the susceptibility mechanisms for autistic subjects. [ABSTRACT FROM AUTHOR]