Project description:BackgroundLittle is known about how genetics and epigenetics interplay in depression. Evidence suggests that genetic variants may change vulnerability to depression by modulating DNA methylation (DNAm) and non-coding RNA (ncRNA) levels. Therefore, the aim of the study was to investigate the effect of the genetic variation, previously identified in the largest genome-wide association study for depression, on proximal DNAm and ncRNA levels.ResultsWe performed DNAm quantitative trait locus (meQTL) analysis in two independent cohorts (total n = 435 healthy individuals), testing associations between 102 single-nucleotide polymorphisms (SNPs) and DNAm levels in whole blood. We identified and replicated 64 SNP-CpG pairs (padj. < 0.05) with meQTL effect. Lower DNAm at cg02098413 located in the HACE1 promoter conferred by the risk allele (C allele) at rs1933802 was associated with higher risk for depression (praw = 0.014, DNAm = 2.3%). In 1202 CD14+ cells sorted from blood, DNAm at cg02088412 positively correlated with HACE1 mRNA expression. Investigation in postmortem brain tissue of adults diagnosed with major depressive disorder (MDD) indicated 1% higher DNAm at cg02098413 in neurons and lower HACE1 mRNA expression in CA1 hippocampus of MDD patients compared with healthy controls (p = 0.008 and 0.012, respectively). Expression QTL analysis in blood of 74 adolescent revealed that hsa-miR-3664-5p was associated with rs7117514 (SHANK2) (padj. = 0.015, mRNA difference = 5.2%). Gene ontology analysis of the miRNA target genes highlighted implication in neuronal processes.ConclusionsCollectively, our findings from a multi-tissue (blood and brain) and multi-layered (genetic, epigenetic, transcriptomic) approach suggest that genetic factors may influence depression by modulating DNAm and miRNA levels. Alterations at HACE1 and SHANK2 loci imply potential mechanisms, such as oxidative stress in the brain, underlying depression. Our results deepened the knowledge of molecular mechanisms in depression and suggest new epigenetic targets that should be further evaluated.
Project description:Identifying genetic variants that are associated with variation in DNA methylation, an analysis commonly referred to as methylation quantitative trait locus (meQTL) mapping, is an important first step towards understanding the genetic architecture underlying epigenetic variation. Most existing meQTL mapping studies have focused on individuals of European ancestry and are underrepresented in other populations, with a particular absence of large studies in populations with African ancestry. We fill this critical knowledge gap by performing a large-scale cis-meQTL mapping study in 961 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. We identify a total of 4,565,687 cis-acting meQTLs in 320,965 meCpGs. We find that 45% of meCpGs harbor multiple independent meQTLs, suggesting potential polygenic genetic architecture underlying methylation variation. A large percentage of the cis-meQTLs also colocalize with cis-expression QTLs (eQTLs) in the same population. Importantly, the identified cis-meQTLs explain a substantial proportion (median = 24.6%) of methylation variation. In addition, the cis-meQTL associated CpG sites mediate a substantial proportion (median = 24.9%) of SNP effects underlying gene expression. Overall, our results represent an important step toward revealing the co-regulation of methylation and gene expression, facilitating the functional interpretation of epigenetic and gene regulation underlying common diseases in African Americans.
Project description:Methylation quantitative trait loci (meQTL) mapping can provide insight into the genetic architecture underlying the epigenome by identifying single-nucleotide polymorphisms (SNPs) associated with differential methylation at methylation sites (CpGs) across the genome. Given that the epigenetic architecture underlying differences in gene expression can vary across racial populations, performing epigenomic studies in African Americans is crucial for understanding the interplay between genetic variation, DNA methylation, and gene expression in this understudied group. By performing cis-meQTL mapping in African American hepatocytes, we identified 410,186 cis-meQTLs associated with methylation at 24,425 CpGs in the liver. Through colocalization analysis, we found that 18,206 of these meQTLs are also colocalized with known liver eQTLs. Additionally, we found that using African American eQTL data results in an increased ability to detect additional colocalized variants that exhibit strong differences in allele frequency between people of European and African ancestry. Furthermore, the presence of smaller linkage disequilibrium blocks in African Americans allows us to identify narrower genomic regions of potentially causal variants compared to when data from Europeans is used. Importantly, these colocalized SNPs are significantly enriched for genetic associations with lipid and inflammatory traits in the GWAS catalog, suggesting that DNA methylation may contribute to the etiologies of these diseases. Furthermore, while it is generally presumed that the genetic regulation of DNA methylation is shared between blood and liver, we found that only 5.4% of African American liver meQTLs colocalize with blood meQTLs. Overall, our results reveal that studying African American populations results in the identification of additional genetic and epigenetic factors that may regulate gene expression in the liver, thereby expanding our understanding of gene regulation in African Americans.
Project description:The discovery of chlorothricin (1) defined a new family of microbial metabolites with potent antitumor antibiotic properties collectively referred to as spirotetronate polyketides. These microbial metabolites are structurally distinguished by the presence of a spirotetronate motif embedded within a macrocyclic core. Glycosylation at the periphery of this core contributes to the structural complexity and bioactivity of this motif. The spirotetronate family displays impressive chemical structures, potent bioactivities, and significant pharmacological potential. This review groups the family members based on structural and biosynthetic considerations and summarizes synthetic and biological studies that aim to elucidate their mode of action and explore their pharmacological potential.
Project description:Autochthonous pig breeds represent an important genetic reserve to be utilized mainly for the production of typical products. To explore its genetic variability, here we present for the first time whole genome sequencing data and SNPs discovered in a male domestic Nero Siciliano pig compared to the last pig reference genome Sus scrofa11.1.A total of 346.8 million paired reads were generated by sequencing. After quality control, 99.03% of the reads were mapped to the reference genome, and over 11 million variants were detected.Additionally, we evaluated sequence diversity in 21 fitness-related loci selected based on their biological function and/or their proximity to relevant QTLs. We focused on genes that have been related to environmental adaptation and reproductive traits in previous studies regarding local breeds. A total of 6,747 variants were identified resulting in a rate of 1 variant every ~276 bases. Among these variants 1,132 were novel to the dbSNP151 database. This study represents a first step in the genetic characterization of Nero Siciliano pig and also provides a platform for future comparative studies between this and other swine breeds.
Project description:DNA methylation is an important epigenetic mechanism for regulating gene expression. Aberrant DNA methylation has been observed in various human diseases, including cancer. Single-nucleotide polymorphisms can contribute to tumor initiation, progression and prognosis by influencing DNA methylation, and DNA methylation quantitative trait loci (meQTL) have been identified in physiological and pathological contexts. However, no database has been developed to systematically analyze meQTLs across multiple cancer types. Here, we present Pancan-meQTL, a database to comprehensively provide meQTLs across 23 cancer types from The Cancer Genome Atlas by integrating genome-wide genotype and DNA methylation data. In total, we identified 8 028 964 cis-meQTLs and 965 050 trans-meQTLs. Among these, 23 432 meQTLs are associated with patient overall survival times. Furthermore, we identified 2 214 458 meQTLs that overlap with known loci identified through genome-wide association studies. Pancan-meQTL provides a user-friendly web interface (http://bioinfo.life.hust.edu.cn/Pancan-meQTL/) that is convenient for browsing, searching and downloading data of interest. This database is a valuable resource for investigating the roles of genetics and epigenetics in cancer.
Project description:BACKGROUND:Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs). METHODS:We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohn's disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals. RESULTS:On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations. CONCLUSION:Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.
Project description:In genomewide mapping of expression quantitative trait loci (eQTL), it is widely believed that thousands of genes are trans-regulated by a small number of genomic regions called "regulatory hotspots," resulting in "trans-regulatory bands" in an eQTL map. As several recent studies have demonstrated, technical confounding factors such as batch effects can complicate eQTL analysis by causing many spurious associations including spurious regulatory hotspots. Yet little is understood about how these technical confounding factors affect eQTL analyses and how to correct for these factors. Our analysis of data sets with biological replicates suggests that it is this intersample correlation structure inherent in expression data that leads to spurious associations between genetic loci and a large number of transcripts inducing spurious regulatory hotspots. We propose a statistical method that corrects for the spurious associations caused by complex intersample correlation of expression measurements in eQTL mapping. Applying our intersample correlation emended (ICE) eQTL mapping method to mouse, yeast, and human identifies many more cis associations while eliminating most of the spurious trans associations. The concordances of cis and trans associations have consistently increased between different replicates, tissues, and populations, demonstrating the higher accuracy of our method to identify real genetic effects.
Project description:Recent years have seen considerable progress in applying single nucleotide polymorphisms (SNPs) to population genetics studies. However, relatively few have attempted to use them to study the genetic differentiation of wild bird populations and none have examined possible differences of exonic and intronic SNPs in these studies. Here, using 144 SNPs, we examined population genetic differentiation in the saker falcon (Falco cherrug) across Eurasia. The position of each SNP was verified using the recently sequenced saker genome with 108 SNPs positioned within the introns of 10 fragments and 36 SNPs in the exons of six genes, comprising MHC, MC1R and four others. In contrast to intronic SNPs, both Bayesian clustering and principal component analyses using exonic SNPs consistently revealed two genetic clusters, within which the least admixed individuals were found in Europe/central Asia and Qinghai (China), respectively. Pairwise D analysis for exonic SNPs showed that the two populations were significantly differentiated and between the two clusters the frequencies of five SNP markers were inferred to be influenced by selection. Central Eurasian populations clustered in as intermediate between the two main groups, consistent with their geographic position. But the westernmost populations of central Europe showed evidence of demographic isolation. Our work highlights the importance of functional exonic SNPs for studying population genetic pattern in a widespread avian species.