Allele-specific expression and eQTL analysis in mouse adipose tissue.

BackgroundThe simplest definition of cis-eQTLs versus trans, refers to genetic variants that affect expression in an allele specific manner, with implications on underlying mechanism. Yet, due to technical limitations of expression microarrays, the vast majority of eQTL studies performed in the last decade used a genomic distance based definition as a surrogate for cis, therefore exploring local rather than cis-eQTLs.ResultsIn this study we use RNAseq to explore allele specific expression (ASE) in adipose tissue of male and female F1 mice, produced from reciprocal crosses of C57BL/6J and DBA/2J strains. Comparison of the identified cis-eQTLs, to local-eQTLs, that were obtained from adipose tissue expression in two previous population based studies in our laboratory, yields poor overlap between the two mapping approaches, while both local-eQTL studies show highly concordant results. Specifically, local-eQTL studies show ~60% overlap between themselves, while only 15-20% of local-eQTLs are identified as cis by ASE, and less than 50% of ASE genes are recovered in local-eQTL studies. Utilizing recently published ENCODE data, we also find that ASE genes show significant bias for SNPs prevalence in DNase I hypersensitive sites that is ASE direction specific.ConclusionsWe suggest a new approach to analysis of allele specific expression that is more sensitive and accurate than the commonly used fisher or chi-square statistics. Our analysis indicates that technical differences between the cis and local-eQTL approaches, such as differences in genomic background or sex specificity, account for relatively small fraction of the discrepancy. Therefore, we suggest that the differences between two eQTL mapping approaches may facilitate sorting of SNP-eQTL interactions into true cis and trans, and that a considerable portion of local-eQTL may actually represent trans interactions

Quantitative measurement of odor detection thresholds using an air dilution olfactometer, and association with genetic variants in a sample of diverse ancestry

Genetic association studies require a quantitative and reliable method for odor threshold assessment in order to examine the contribution of genetic variants to complex olfactory phenotypes. Our main goal was to assess the feasibility of a portable Scentroid air dilution olfactometer for use in such studies. Using the Scentroid SM110C and the SK5 n-butanol Sensitivity Kit (IDES Canada Inc.), n-butanol odor thresholds were determined for 182 individuals of diverse ancestry (mean age: 20.4 ± 2.5 years; n = 128 female; n = 54 male). Threshold scores from repeat participants were used to calculate a test–retest reliability coefficient, which was statistically significant (r = 0.754, p < 0.001, n = 29), indicating that the Scentroid provides reliable estimates of odor thresholds. In addition, we performed a preliminary genetic analysis evaluating the potential association of n-butanol odor thresholds to six single-nucleotide polymorphisms (SNPs) putatively involved in general olfactory sensitivity (GOS). The results of multiple linear regression analysis revealed no significant association between the SNPs tested and threshold scores. However, our sample size was relatively small, and our study was only powered to identify genetic markers with strong effects on olfactory sensitivity. Overall, we find that the Scentroid provides reliable quantitative measures of odor detection threshold and is well suited for genetic studies of olfactory sensitivity

Elimination of reference mapping bias reveals robust immune related allele-specific expression in cross-bred sheep

Pervasive allelic variation at both gene and single nucleotide level (SNV) between individuals is commonly associated with complex traits in humans and animals. Allele-specific expression (ASE) analysis, using RNA-Seq, can provide a detailed annotation of allelic imbalance and infer the existence of cis-acting transcriptional regulation. However, variant detection in RNA-Seq data is compromised by biased mapping of reads to the reference DNA sequence. In this manuscript, we describe an unbiased standardized computational pipeline for allele-specific expression analysis using RNA-Seq data, which we have adapted and developed using tools available under open license. The analysis pipeline we present is designed to minimize reference bias while providing accurate profiling of allele-specific expression across tissues and cell types. Using this methodology, we were able to profile pervasive allelic imbalance across tissues and cell types, at both the gene and SNV level, in Texel×Scottish Blackface sheep, using the sheep gene expression atlas data set. ASE profiles were pervasive in each sheep and across all tissue types investigated. However, ASE profiles shared across tissues were limited, and instead, they tended to be highly tissue-specific. These tissue-specific ASE profiles may underlie the expression of economically important traits and could be utilized as weighted SNVs, for example, to improve the accuracy of genomic selection in breeding programs for sheep. An additional benefit of the pipeline is that it does not require parental genotypes and can therefore be applied to other RNA-Seq data sets for livestock, including those available on the Functional Annotation of Animal Genomes (FAANG) data portal. This study is the first global characterization of moderate to extreme ASE in tissues and cell types from sheep. We have applied a robust methodology for ASE profiling to provide both a novel analysis of the multi-dimensional sheep gene expression atlas data set and a foundation for identifying the regulatory and expressed elements of the genome that are driving complex traits in livestock

A Multi-mRNA Prognostic Signature for Anti-TNFα Therapy Response in Patients with Inflammatory Bowel Disease

Background: Anti-TNF-alpha (anti-TNFα) therapies have transformed the care and management of inflammatory bowel disease (IBD). However, they are expensive and ineffective in greater than 50% of patients, and they increase the risk of infections, liver issues, arthritis, and lymphoma. With 1.6 million Americans suffering from IBD and global prevalence on the rise, there is a critical unmet need in the use of anti-TNFα therapies: a test for the likelihood of therapy response. Here, as a proof-of-concept, we present a multi-mRNA signature for predicting response to anti-TNFα treatment to improve the efficacy and cost-to-benefit ratio of these biologics. Methods: We surveyed public data repositories and curated four transcriptomic datasets (n = 136) from colonic and ileal mucosal biopsies of IBD patients (pretreatment) who were subjected to anti-TNFα therapy and subsequently adjudicated for response. We applied a multicohort analysis with a leave-one-study-out (LOSO) approach, MetaIntegrator, to identify significant differentially expressed (DE) genes between responders and non-responders and then used a greedy forward search to identify a parsimonious gene signature. We then calculated an anti-TNFα response (ATR) score based on this parsimonious gene signature to predict responder status and assessed discriminatory performance via an area-under-receiver operating-characteristic curve (AUROC). Results: We identified 324 significant DE genes between responders and non-responders. The greedy forward search yielded seven genes that robustly distinguish anti-TNFα responders from non-responders, with an AUROC of 0.88 (95% CI: 0.70–1). The Youden index yielded a mean sensitivity of 91%, mean specificity of 76%, and mean accuracy of 86%. Conclusions: Our findings suggest that there is a robust transcriptomic signature for predicting anti-TNFα response in mucosal biopsies from IBD patients prior to treatment initiation. This seven-gene signature should be further investigated for its potential to be translated into a predictive test for clinical use

Diet, gonadal sex, and sex chromosome complement influence white adipose tissue miRNA expression

Abstract Background MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression by targeting specific mRNA species for degradation or interfering with translation. Specific miRNAs are key regulators of adipogenesis, and are expressed at different levels in adipose tissue from lean and obese mice. The degree of lipid accumulation and distribution of white adipose tissue differs between males and females, and it is unknown whether sex differences in adipose tissue-specific miRNA expression may contribute to this dimorphism. Typically, sex differences are attributed to hormones secreted from ovaries or testes. However, the sex chromosome complement (XX versus XY) is also a determinant of sex differences and may regulate miRNA expression in adipocytes. Results To identify sex differences in adipose tissue miRNA expression and to understand the underlying mechanisms, we performed high-throughput miRNA sequencing in gonadal fat depots of the Four Core Genotypes mouse model. This model, which consists of XX female, XX male, XY female, and XY male mice, allowed us to assess independent effects of gonadal type (male vs . female) and sex chromosome complement (XX vs . XY) on miRNA expression profiles. We have also assessed the effects of a high fat diet on sex differences in adipose tissue miRNA profiles. We identified a male\u2013female effect on the overall miRNA expression profile in mice fed a chow diet, with a bias toward higher expression in male compared to female gonadal adipose tissue. This sex bias disappeared after gonadectomy, suggesting that circulating levels of gonadal secretions modulate the miRNA expression profile. After 16\ua0weeks of high fat diet, the miRNA expression distribution was shifted toward higher expression in XY vs . XX adipose tissue. Principal component analysis revealed that high fat diet has a substantial effect on miRNA profile variance, while gonadal secretions and sex chromosome complement each have milder effects. Conclusions Our results demonstrate that the overall miRNA expression profile in adipose tissue is influenced by gonadal hormones and the sex chromosome complement, and that expression profiles change in response to gonadectomy and high fat diet. Differential miRNA expression profiles may contribute to sex differences in adipose tissue gene expression, adipose tissue development, and diet-induced obesity