Identification and application of plasmatic microRNA expression quantitative trait loci (miR-QTL) at first trimester of pregnancy

BackgroundMicroRNAs (miRNAs) are a class of small non-coding RNAs regulating gene expression. They are involved in many biological processes, including adaptation to pregnancy. The identification of genetic variants associated with gene expression, known as expression quantitative trait loci (eQTL), helps to understand the underlying molecular mechanisms and determinants of complex diseases. Using data from the prospective pre-birth Gen3G cohort, we investigated associations between maternal genotypes and plasmatic miRNA levels measured during the first trimester of pregnancy of 369 women.ResultsAssessing the associations between about 2 million SNPs and miRNA proximal pairs using best practices from the GTEx consortium, a total of 22,140 significant eQTLs involving 147 unique miRNAs were identified. Elastic-net regressions were applied to select the most relevant SNPs to build genetic risk scores (GRS) for each of these 147 miRNAs. For about half of the circulating miRNAs, the GRS captured >10% of the variance abundance. As a demonstration of the usefulness of the identified eQTLs and derived GRS, we used the GRSs as instrumental variables to test for association between the circulating levels of miRNAs quantified before the 16th week of pregnancy and the development of pregnancy complications (gestational diabetes [GDM] or pre-eclampsia [PE]) developing more than three months later on average. Using predicted miRNA levels derived from instrumental variables, we found 18 significant associations of miRNAs with potential support of causal inference for GDM or PE.ConclusionsOur results represent a valuable resource to understand miRNA regulation and highlight the potential of genetic instruments in predicting circulating miRNA levels and their possible contribution in disease development.

Expression quantitative trait loci for ETV4 and MEOX1 are associated with adult asthma in Japanese populations

ETS variant transcription factor 4 (ETV4) is a recently identified transcription factor that regulates gene expression-based biomarkers of asthma and IL6 production in an airway epithelial cell line. Given that ETV4 has not yet been implicated in asthma genetics, we performed genetic association studies of adult asthma in the ETV4 region using two independent Japanese cohorts (a total of 1532 controls and 783 cases). SNPs located between ETV4 and mesenchyme homeobox 1 (MEOX1) were significantly associated with adult asthma, including rs4792901 and rs2880540 (P = 5.63E−5 and 2.77E−5, respectively). The CC haplotype of these two SNPs was also significantly associated with adult asthma (P = 8.43E−7). Even when both SNPs were included in a logistic regression model, the association of either rs4792901 or rs2880540 remained significant (P = 0.013 or 0.007, respectively), suggesting that the two SNPs may have independent effects on the development of asthma. Both SNPs were expression quantitative trait loci, and the asthma risk alleles at both SNPs were correlated with increased levels of ETV4 mRNA expression. In addition, the asthma risk allele at rs4792901 was associated with increased serum IL6 levels (P = 0.041) in 651 healthy adults. Our findings imply that ETV4 is involved in the pathogenesis of asthma, possibly through the heightened production of IL6.

The Association Between STX1B Polymorphisms and Treatment Response in Patients With Epilepsy

Background: Epilepsy is a debilitating brain disease with complex inheritance and frequent treatment resistance. However, the role of STX1B single nucleotide polymorphisms (SNPs) in epilepsy treatment remains unknown.Objective: This study aimed to explore the genetic association of STX1B SNPs with treatment response in patients with epilepsy in a Han Chinese population.Methods: We first examined the associations between STX1B SNPs and epilepsy in 1000 Han Chinese and the associations between STX1B SNPs and drug-resistant epilepsy in 450 subjects. Expression quantitative trait loci analysis was then conducted using 16 drug-resistant epileptic brain tissue samples and results from the BrainCloud database (http://eqtl.brainseq.org).Results: The allelic frequencies of rs140820592 were different between the epilepsy and control groups (p = 0.002) after Bonferroni correction. The rs140820592 was associated with significantly lower epilepsy risk among 1,000 subjects in the dominant model after adjusting for gender and age and Bonferroni correction (OR = 0.542, 95%CI = 0.358–0.819, p = 0.004). The rs140820592 also conferred significantly lower risk of drug-resistant epilepsy among 450 subjects using the same dominant model after adjusting for gender and age and Bonferroni correction (OR = 0.260, 95%CI = 0.103–0.653, p = 0.004). Expression quantitative trait loci analysis revealed that rs140820592 was associated with STX1B expression level in drug-resistant epileptic brain tissues (p = 0.012), and this result was further verified in the BrainCloud database (http://eqtl.brainseq.org) (p = 2.3214 × 10–5).Conclusion: The STX1B rs140820592 may influence the risks of epilepsy and drug-resistant epilepsy by regulating STX1B expression in brain tissues.

Identification of Distant Regulatory Elements Using Expression Quantitative Trait Loci Mapping for Heat-Responsive Genes in Oysters

Many marine ectotherms, especially those inhabiting highly variable intertidal zones, develop high phenotypic plasticity in response to rapid climate change by modulating gene expression levels. Herein, we examined the regulatory architecture of heat-responsive gene expression plasticity in oysters using expression quantitative trait loci (eQTL) analysis. Using a backcross family of Crassostrea gigas and its sister species Crassostrea angulata under acute stress, 56 distant regulatory regions accounting for 6–26.6% of the gene expression variation were identified for 19 heat-responsive genes. In total, 831 genes and 164 single nucleotide polymorphisms (SNPs) that could potentially regulate expression of the target genes were screened in the eQTL region. The association between three SNPs and the corresponding target genes was verified in an independent family. Specifically, Marker13973 was identified for heat shock protein (HSP) family A member 9 (HspA9). Ribosomal protein L10a (RPL10A) was detected approximately 2 kb downstream of the distant regulatory SNP. Further, Marker14346-48 and Marker14346-85 were in complete linkage disequilibrium and identified for autophagy-related gene 7 (ATG7). Nuclear respiratory factor 1 (NRF1) was detected approximately 3 kb upstream of the two SNPs. These results suggested regulatory relationships between RPL10A and HSPA9 and between NRF1 and ATG7. Our findings indicate that distant regulatory mutations play an important role in the regulation of gene expression plasticity by altering upstream regulatory factors in response to heat stress. The identified eQTLs provide candidate biomarkers for predicting the persistence of oysters under future climate change scenarios.

Genetic architecture modulates diet-induced hepatic mRNA and miRNA expression profiles in Diversity Outbred mice

Genetic approaches in model organisms have consistently demonstrated that molecular traits such as gene expression are under genetic regulation, similar to clinical traits. The resulting expression quantitative trait loci (eQTL) have revolutionized our understanding of genetic regulation and identified numerous candidate genes for clinically relevant traits. More recently, these analyses have been extended to other molecular traits such as protein abundance, metabolite levels, and miRNA expression. Here, we performed global hepatic eQTL and microRNA expression quantitative trait loci (mirQTL) analysis in a population of Diversity Outbred mice fed two different diets. We identified several key features of eQTL and mirQTL, namely differences in the mode of genetic regulation (cis or trans) between mRNA and miRNA. Approximately 50% of mirQTL are regulated by a trans-acting factor, compared to ∼25% of eQTL. We note differences in the heritability of mRNA and miRNA expression and variance explained by each eQTL or mirQTL. In general, cis-acting variants affecting mRNA or miRNA expression explain more phenotypic variance than trans-acting variants. Finally, we investigated the effect of diet on the genetic architecture of eQTL and mirQTL, highlighting the critical effects of environment on both eQTL and mirQTL. Overall, these data underscore the complex genetic regulation of two well-characterized RNA classes (mRNA and miRNA) that have critical roles in the regulation of clinical traits and disease susceptibility

Analysis of expression Quantitative Trait Loci for NLGN4X in relation to language and neurodevelopmental function: an exploratory analysis using FUSION and GTEx workflows

Language disorders in children are highly heritable, but progress in identifying genetic variants that contribute to language phenotypes has been slow. Here we applied a novel approach by identifying SNPs that are associated with gene expression in the brain, taking as our focus a gene on the X chromosome, NLGN4X, which has been postulated to play a role in neurodevelopmental disorders affecting language and communication. We found no significant associations between expression quantitative trait loci (eQTLs) and phenotypes of nonword repetition, general language ability or neurodevelopmental disorder in two samples of twin children, who had been selected for a relatively high rate of language problems. We report here our experiences with two methods, FUSION and GTEx, for eQTL analysis. It is likely that our null result represents a true negative, but for the interest of others interested in using these methods, we note specific challenges encountered in applying this approach to our data: a) complications associated with studying a gene on the X chromosome; b) lack of agreement between expression estimates from FUSION and GTEx; c) software compatibility issues with different versions of the R programming language.

Expression Quantitative Trait Loci (eQTLs) Associated with Retrotransposons Demonstrate Their Modulatory Effect on the Transcriptome

Transposable elements (TEs) are repetitive elements that belong to a variety of functional classes and have an important role in shaping genome evolution. Around 50% of the human genome contains TEs, and they have been termed the “dark matter” of the genome because relatively little is known about their function. While TEs have been shown to participate in aberrant gene regulation and the pathogenesis of diseases, only a few studies have explored the systemic effect of TEs on gene expression. In the present study, we analysed whole genome sequences and blood whole transcriptome data from 570 individuals within the Parkinson’s Progressive Markers Initiative (PPMI) cohort to identify expression quantitative trait loci (eQTL) regulating genome-wide gene expression associated with TEs. We identified 2132 reference TEs that were polymorphic for their presence or absence in our study cohort. The presence or absence of the TE element could change the expression of the gene or gene clusters from zero to tens of thousands of copies of RNA. The main finding is that many TEs possess very strong regulatory effects, and they have the potential to modulate large genetic networks with hundreds of target genes over the genome. We illustrate the plethora of regulatory mechanisms using examples of their action at the HLA gene cluster and data showing different TEs' convergence to modulate WFS1 gene expression. In conclusion, the presence or absence of polymorphisms of TEs has an eminent genome-wide regulatory function with large effect size at the level of the whole transcriptome. The role of TEs in explaining, in part, the missing heritability for complex traits is convincing and should be considered.

Integrated Genome-Wide Analysis of MicroRNA Expression Quantitative Trait Loci in Pig Longissimus Dorsi Muscle

Determining mechanisms regulating complex traits in pigs is essential to improve the production efficiency of this globally important protein source. MicroRNAs (miRNAs) are a class of non-coding RNAs known to post-transcriptionally regulate gene expression affecting numerous phenotypes, including those important to the pig industry. To facilitate a more comprehensive understanding of the regulatory mechanisms controlling growth, carcass composition, and meat quality phenotypes in pigs, we integrated miRNA and gene expression data from longissimus dorsi muscle samples with genotypic and phenotypic data from the same animals. We identified 23 miRNA expression Quantitative Trait Loci (miR-eQTL) at the genome-wide level and examined their potential effects on these important production phenotypes through miRNA target prediction, correlation, and colocalization analyses. One miR-eQTL miRNA, miR-874, has target genes that colocalize with phenotypic QTL for 12 production traits across the genome including backfat thickness, dressing percentage, muscle pH at 24 h post-mortem, and cook yield. The results of our study reveal genomic regions underlying variation in miRNA expression and identify miRNAs and genes for future validation of their regulatory effects on traits of economic importance to the global pig industry.