Global analysis of the impact of environmental perturbation on cis-regulation of gene expression

Investigating the tissue specificity and prognostic impact of cis-regulatory cancer risk variants

The tissue-specific incidence of cancers and their genetic basis are poorly understood. Although prior studies have shown global correlation across tissues for cancer risk single-nucleotide polymorphisms (SNPs) identified through genome-wide association studies (GWAS), any shared functional regulation of gene expression on a per SNP basis has not been well characterized. We set to quantify cis-mediated gene regulation and tissue sharing for SNPs associated with eight common cancers. We identify significant tissue sharing for individual SNPs and global enrichment for breast, colorectal, and Hodgkin lymphoma cancer risk SNPs in multiple tissues. In addition, we observe increasing tissue sharing for cancer risk SNPs overlapping with super-enhancers for breast cancer and Hodgkin lymphoma providing further evidence of tissue specificity. Finally, for genes under cis-regulation by breast cancer SNPs, we identify a phenotype characterized by low expression of tumor suppressors and negative regulators of the WNT pathway associated with worse freedom from progression and overall survival in patients who eventually develop breast cancer. Our results introduce a paradigm for functionally annotating individual cancer risk SNPs and will inform the design of future translational studies aimed to personalize assessment of inherited cancer risk across tissues.

The rs705708 A allele of the ERBB3 gene is associated with lower prevalence of diabetic retinopathy and arterial hypertension and with improved renal function in type 1 diabetic patients

INTRODUCTION

The Erb-b2 receptor tyrosine kinase 3 (ERBB3) is involved in autoimmune processes related to type 1 diabetes mellitus (T1DM) pathogenesis. Accordingly, some studies have suggested that single nucleotide polymorphisms (SNPs) in the ERBB3 gene confer risk for T1DM. Proliferation-associated protein 2G4 (PA2G4) is another candidate gene for this disease because it regulates cell proliferation and adaptive immunity. Moreover, PA2G4 regulates ERBB3. To date, no study has evaluated the association of PA2G4 SNPs and T1DM.

AIM

To evaluate the association of ERBB3 rs705708 (G/A) and PA2G4 rs773120 (C/T) SNPs with T1DM and its clinical and laboratory characteristics.

METHODS

This case-control study included 976 white subjects from Southern Brazil, categorized into 501 cases with T1DM and 475 non-diabetic controls. The ERBB3 and PA2G4 SNPs were genotyped by allelic discrimination-real-time PCR.

RESULTS

ERBB3 rs705708 and PA2G4 rs773120 SNPs were not associated with T1DM considering different inheritance models and also when controlling for covariables. However, T1DM patients carrying the ERBB3 rs705708 A allele developed T1DM at an earlier age vs. G/G patients. Interestingly, in the T1DM group, the rs705708 A allele was associated with lower prevalence of diabetic retinopathy and arterial hypertension as well as with improved renal function (higher estimated glomerular filtration rate and lower urinary albumin excretion levels) compared to G/G patients.

CONCLUSIONS

Although no association was observed between the ERBB3 rs705708 and PA2G4 rs773120 SNPs and T1DM, the rs705708 A allele was associated, for the first time in literature, with lower prevalence of diabetic retinopathy and arterial hypertension. Additionally, this SNP was associated with improved renal function.

Wnt-Signaling Regulated by Glucocorticoid-Induced miRNAs

Glucocorticoids (GCs) are pleiotropic hormones which regulate innumerable physiological processes. Their comprehensive effects are due to the diversity of signaling mechanism networks. MiRNAs, small, non-coding RNAs contribute to the fine tuning of signaling pathways and reciprocal regulation between GCs and miRNAs has been suggested. Our aim was to investigate the expressional change and potential function of GC mediated miRNAs. The miRNA expression profile was measured in three models: human adrenocortical adenoma vs. normal tissue, steroid-producing H295R cells and in hormonally inactive HeLa cells before and after dexamethasone treatment. The gene expression profile in 82 control and 57 GC-affected samples was evaluated in GC producing and six different GC target tissue types. Tissue-specific target prediction (TSTP) was applied to identify the most relevant miRNA-mRNA interactions. Glucocorticoid treatment resulted in cell type-dependent miRNA expression changes. However, 19.5% of the influenced signaling pathways were common in all three experiments, of which the Wnt-signaling pathway seemed to be the most affected. Transcriptome data and TSTP showed similar results, as the Wnt pathway was significantly altered in both the GC-producing adrenal gland and all investigated GC target tissue types. In different cell types, different miRNAs led to the regulation of similar pathways. Wnt signaling may be one of the most important signaling pathways affected by hypercortisolism. It is, at least in part, regulated by miRNAs that mediate the glucocorticoid effect. Our findings on GC producing and GC target tissues suggest that the alteration of Wnt signaling (together with other pathways) may be responsible for the leading symptoms observed in Cushing's syndrome.

Haplotype associated RNA expression (HARE) improves prediction of complex traits in maize

Genomic prediction typically relies on associations between single-site polymorphisms and traits of interest. This representation of genomic variability has been successful for predicting many complex traits. However, it usually cannot capture the combination of alleles in haplotypes and it has generated little insight about the biological function of polymorphisms. Here we present a novel and cost-effective method for imputing cis haplotype associated RNA expression (HARE), studied their transferability across tissues, and evaluated genomic prediction models within and across populations. HARE focuses on tightly linked cis acting causal variants in the immediate vicinity of the gene, while excluding trans effects from diffusion and metabolism. Therefore, HARE estimates were more transferrable across different tissues and populations compared to measured transcript expression. We also showed that HARE estimates captured one-third of the variation in gene expression. HARE estimates were used in genomic prediction models evaluated within and across two diverse maize panels–a diverse association panel (Goodman Association panel) and a large half-sib panel (Nested Association Mapping panel)–for predicting 26 complex traits. HARE resulted in up to 15% higher prediction accuracy than control approaches that preserved haplotype structure, suggesting that HARE carried functional information in addition to information about haplotype structure. The largest increase was observed when the model was trained in the Nested Association Mapping panel and tested in the Goodman Association panel. Additionally, HARE yielded higher within-population prediction accuracy as compared to measured expression values. The accuracy achieved by measured expression was variable across tissues, whereas accuracy by HARE was more stable across tissues. Therefore, imputing RNA expression of genes by haplotype is stable, cost-effective, and transferable across populations.

Genomic marker data is widely used in the prediction of many traits. However, prediction has been primarily carried out within populations and without explicit modeling of RNA or protein expression. In this study, we explored the prediction of field traits within and across populations using estimated RNA expression attributable to only the DNA sequence around a gene. We showed that the estimated RNA expression was more transferable across populations and tissues than measured RNA expression. We improved prediction of field traits up to 15% using estimated gene expression as compared to observed expression or gene sequence alone. Overall, these findings indicate that structural and functional information in the gene sequence is highly transferable.

Common variants at 21q22.3 locus influence MX1 and TMPRSS2 gene expression and susceptibility to severe COVID-19

The established risk factors of coronavirus disease 2019 (COVID-19) are advanced age, male sex, and comorbidities, but they do not fully explain the wide spectrum of disease manifestations. Genetic factors implicated in the host antiviral response provide for novel insights into its pathogenesis. We performed an in-depth genetic analysis of chromosome 21 exploiting the genome-wide association study data, including 6,406 individuals hospitalized for COVID-19 and 902,088 controls with European genetic ancestry from the COVID-19 Host Genetics Initiative. We found that five single nucleotide polymorphisms within TMPRSS2 and near MX1 gene show associations with severe COVID-19. The minor alleles of the five single nucleotide polymorphisms (SNPs) correlated with a reduced risk of developing severe COVID-19 and high level of MX1 expression in blood. Our findings demonstrate that host genetic factors can influence the different clinical presentations of COVID-19 and that MX1 could be a potential therapeutic target.

Genome-wide Association Studies Reveal Novel Locus With Sex-/Therapy-Specific Fracture Risk Effects in Childhood Cancer Survivors

Childhood cancer survivors treated with radiation therapy (RT) and osteotoxic chemotherapies are at increased risk for fractures. However, understanding of how genetic and clinical susceptibility factors jointly contribute to fracture risk among survivors is limited. To address this gap, we conducted genome-wide association studies of fracture risk after cancer diagnosis in 2453 participants of European ancestry from the Childhood Cancer Survivor Study (CCSS) with 930 incident fractures using Cox regression models (ie, time-to-event analysis) and prioritized sex- and treatment-stratified genetic associations. We performed replication analyses in 1417 survivors of European ancestry with 652 incident fractures from the St. Jude Lifetime Cohort Study (SJLIFE). In discovery, we identified a genome-wide significant (p < 5 × 10^-8 ) fracture risk locus, 16p13.3 (HAGHL), among female CCSS survivors (n = 1289) with strong evidence of sex-specific effects (p_{sex-heterogeneity}  < 7 × 10^-6 ). Combining discovery and replication data, rs1406815 showed the strongest association (hazard ratio [HR] = 1.43, p = 8.2 × 10^-9 ; n = 1935 women) at this locus. In treatment-stratified analyses in the discovery cohort, the association between rs1406815 and fracture risk among female survivors with no RT exposures was weak (HR = 1.22, 95% confidence interval [CI] 0.95-1.57, p = 0.11) but increased substantially among those with greater head/neck RT doses (any RT: HR = 1.88, 95% CI 1.54-2.28, p = 2.4 × 10^-10 ; >36 Gray only: HR = 3.79, 95% CI 1.95-7.34, p = 8.2 × 10^-5 ). These head/neck RT-specific HAGHL single-nucleotide polymorphism (SNP) effects were replicated in female SJLIFE survivors. In silico bioinformatics analyses suggest these fracture risk alleles regulate HAGHL gene expression and related bone resorption pathways. Genetic risk profiles integrating this locus may help identify female survivors who would benefit from targeted interventions to reduce fracture risk. © 2020 American Society for Bone and Mineral Research (ASBMR).

Cold pain sensitivity is associated with single-nucleotide polymorphisms of PAR2/F2RL1 and TRPM8

Pain sensitivity differs individually, but the mechanisms and genetic factors that underlie these differences are not fully understood. To investigate genetic factors that are involved in sensing cold pain, we applied a cold-induced pain test and evaluated protease-activated receptor 2 (PAR2/F2RL1) and transient receptor potential melastatin 8 (TRPM8), which are related to pain. We statistically investigated the associations between genetic polymorphisms and cold pain sensitivity in 461 healthy patients who were scheduled to undergo cosmetic orthognathic surgery for mandibular prognathism. We found an association between cold pain sensitivity and the rs2243057 polymorphism of the PAR2 gene. We also found a significant association between cold pain sensitivity and the rs12992084 polymorphism of the TRPM8 gene. Carriers of the minor A allele of the rs2243057 polymorphism of PAR2 and minor C allele of the rs12992084 polymorphism of TRPM8 exhibited a longer latency to pain perception in the cold-induced pain test, reflecting a decrease in cold pain sensitivity. These results suggest that genetic polymorphisms of both PAR2 and TRPM8 are involved in individual differences in cold pain sensitivity.

How does race and ethnicity effect the precision treatment of asthma?

Introduction

Asthma is a common condition that affects large numbers of children and adults, yet the burden of disease is not equally distributed amongst groups. In the United States, African Americans and Puerto Ricans have higher rates of asthma and its complications when compared with European Americans. However, clinical trials and genetic studies have largely focused on the latter group.

Areas covered

Here we examine what is known regarding differences in asthma treatment response by race-ethnicity. We also review existing genetic studies related to the use of asthma medications, paying special attention to studies that included substantial numbers of non-white population groups. Publicly accessible search engines of the medical literature were queried using combinations of the terms asthma, race, ethnicity, pharmacogenomics, and pharmacogenetics, as well as the names of individual asthma medication classes. The list of articles reviewed was supplemented by bibliographies and expert knowledge.

Expert opinion

A substantial and coordinated effort is still needed to both identify and validate genetic biomarkers of asthma medication response, as currently there are no clinically actionable genetic markers available for this purpose. The path to identifying such markers in non-white populations is even more formidable, since these groups are underrepresented in existing data.

Single Nucleotide Polymorphisms at a Distance from Aryl Hydrocarbon Receptor (AHR) Binding Sites Influence AHR Ligand-Dependent Gene Expression

Greater than 90% of significant genome-wide association study (GWAS) single-nucleotide polymorphisms (SNPs) are in noncoding regions of the genome, but only 25.6% are known expression quantitative trait loci (eQTLs). Therefore, the function of many significant GWAS SNPs remains unclear. We have identified a novel type of eQTL for which SNPs distant from ligand-activated transcription factor (TF) binding sites can alter target gene expression in a SNP genotype-by-ligand–dependent fashion that we refer to as pharmacogenomic eQTLs (PGx-eQTLs)—loci that may have important pharmacotherapeutic implications. In the present study, we integrated chromatin immunoprecipitation-seq with RNA-seq and SNP genotype data for a panel of lymphoblastoid cell lines to identify 10 novel cis PGx-eQTLs dependent on the ligand-activated TF aryl hydrocarbon receptor (AHR)—a critical environmental sensor for xenobiotic (drug) and immune response. Those 10 cis PGx-eQTLs were eQTLs only after AHR ligand treatment, even though the SNPs did not create/destroy an AHR response element—the DNA sequence motif recognized and bound by AHR. Additional functional studies in multiple cell lines demonstrated that some cis PGx-eQTLs are functional in multiple cell types, whereas others displayed SNP-by-ligand–dependent effects in just one cell type. Furthermore, four of those cis PGx-eQTLs had previously been associated with clinical phenotypes, indicating that those loci might have the potential to inform clinical decisions. Therefore, SNPs across the genome that are distant from TF binding sites for ligand-activated TFs might function as PGx-eQTLs and, as a result, might have important clinical implications for interindividual variation in drug response.

Defining the molecular signatures of Achilles tendinopathy and anterior cruciate ligament ruptures: A whole-exome sequencing approach

Musculoskeletal soft tissue injuries are complex phenotypes with genetics being one of many proposed risk factors. Case-control association studies using the candidate gene approach have predominately been used to identify risk loci for these injuries. However, the ability to identify all risk conferring variants using this approach alone is unlikely. Therefore, this study aimed to further define the genetic profile of these injuries using an integrated omics approach involving whole exome sequencing and a customised analyses pipeline. The exomes of ten exemplar asymptomatic controls and ten exemplar cases with Achilles tendinopathy were individually sequenced using a platform that included the coverage of the untranslated regions and miRBase miRNA genes. Approximately 200 000 variants were identified in the sequenced samples. Previous research was used to guide a targeted analysis of the genes encoding the tenascin-C (TNC) glycoprotein and the α1 chain of type XXVII collagen (COL27A1) located on chromosome 9. Selection of variants within these genes were; however, not predetermined but based on a tiered filtering strategy. Four variants in TNC (rs1061494, rs1138545, rs2104772 and rs1061495) and three variants in the upstream COL27A1 gene (rs2567706, rs2241671 and rs2567705) were genotyped in larger Achilles tendinopathy and anterior cruciate ligament (ACL) rupture sample groups. The CC genotype of TNC rs1061494 (C/T) was associated with the risk of Achilles tendinopathy (p = 0.018, OR: 2.5 95% CI: 1.2-5.1). Furthermore, the AA genotype of the TNC rs2104772 (A/T) variant was significantly associated with ACL ruptures in the female subgroup (p = 0.035, OR: 2.3 95% CI: 1.1-5.5). An inferred haplotype in the TNC gene was also associated with the risk of Achilles tendinopathy. These results provide a proof of concept for the use of a customised pipeline for the exploration of a larger genomic dataset. This approach, using previous research to guide a targeted analysis of the data has generated new genetic signatures in the biology of musculoskeletal soft tissue injuries.

Integrative approach identifies corticosteroid response variant in diverse populations with asthma

BACKGROUND

Although inhaled corticosteroid (ICS) medication is considered the cornerstone treatment for patients with persistent asthma, few ICS pharmacogenomic studies have involved nonwhite populations.

OBJECTIVE

We sought to identify genetic predictors of ICS response in multiple population groups with asthma.

METHODS

The discovery group comprised African American participants from the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) who underwent 6 weeks of monitored ICS therapy (n = 244). A genome-wide scan was performed to identify single nucleotide polymorphism (SNP) variants jointly associated (ie, the combined effect of the SNP and SNP × ICS treatment interaction) with changes in asthma control. Top associations were validated by assessing the joint association with asthma exacerbations in 3 additional groups: African Americans (n = 803 and n = 563) and Latinos (n = 1461). RNA sequencing data from 408 asthmatic patients and 405 control subjects were used to examine whether genotype was associated with gene expression.

RESULTS

One variant, rs3827907, was significantly associated with ICS-mediated changes in asthma control in the discovery set (P = 7.79 × 10^-8) and was jointly associated with asthma exacerbations in 3 validation cohorts (P = .023, P = .029, and P = .041). RNA sequencing analysis found the rs3827907 C-allele to be associated with lower RNASE2 expression (P = 6.10 × 10^-4). RNASE2 encodes eosinophil-derived neurotoxin, and the rs3827907 C-allele appeared to particularly influence ICS treatment response in the presence of eosinophilic inflammation (ie, high pretreatment eosinophil-derived neurotoxin levels or blood eosinophil counts).

CONCLUSION

We identified a variant, rs3827907, that appears to influence response to ICS treatment in multiple population groups and likely mediates its effect through eosinophils.

Changes in Neuronal Signaling and Cell Stress Response Pathways are Associated with a Multigenic Response of Drosophila melanogaster to DDT Selection

The adaptation of insect populations to insecticidal control is a continual threat to human health and sustainable agricultural practices, but many complex genomic mechanisms involved in this adaption remain poorly understood. This study applied a systems approach to investigate the interconnections between structural and functional variance in response to dichlorodiphenyltrichloroethane (DDT) within the Drosophila melanogaster strain 91-R. Directional selection in 6 selective sweeps coincided with constitutive gene expression differences in DDT resistant flies, including the most highly upregulated transcript, Unc-115 b, which plays a central role in axon guidance, and the most highly downregulated transcript, the angiopoietin-like CG31832, which is involved in directing vascular branching and dendrite outgrowth but likely may be under trans-regulatory control. Direct functions and protein–protein interactions mediated by differentially expressed transcripts control changes in cell migration, signal transduction, and gene regulatory cascades that impact the nervous system. Although changes to cellular stress response pathways involve 8 different cytochrome P450s, stress response, and apoptosis is controlled by a multifacetted regulatory mechanism. These data demonstrate that DDT selection in 91-R may have resulted in genome-wide adaptations that impacts genetic and signal transduction pathways that converge to modify stress response, cell survival, and neurological functions. This study implicates the involvement of a multigenic mechanism in the adaptation to a chemical insecticide, which impact interconnected regulatory cascades. We propose that DDT selection within 91-R might act systemically, wherein pathway interactions function to reinforce the epistatic effects of individual adaptive changes on an additive or nonadditive basis.

Genetics of pleiotropic effects of dexamethasone

OBJECTIVES

Glucocorticoids such as dexamethasone have pleiotropic effects, including desired antileukemic, anti-inflammatory, or immunosuppressive effects, and undesired metabolic or toxic effects. The most serious adverse effects of dexamethasone among patients with acute lymphoblastic leukemia are osteonecrosis and thrombosis. To identify inherited genomic variation involved in these severe adverse effects, we carried out genome-wide association studies (GWAS) by analyzing 14 pleiotropic glucocorticoid phenotypes in 391 patients with acute lymphoblastic leukemia.

PATIENTS AND METHODS

We used the Projection Onto the Most Interesting Statistical Evidence integrative analysis technique to identify genetic variants associated with pleiotropic dexamethasone phenotypes, stratifying for age, sex, race, and treatment, and compared the results with conventional single-phenotype GWAS. The phenotypes were osteonecrosis, central nervous system toxicity, hyperglycemia, hypokalemia, thrombosis, dexamethasone exposure, BMI, growth trajectory, and levels of cortisol, albumin, and asparaginase antibodies, and changes in cholesterol, triglycerides, and low-density lipoproteins after dexamethasone.

RESULTS

The integrative analysis identified more pleiotropic single nucleotide polymorphism variants (P=1.46×10(-215), and these variants were more likely to be in gene-regulatory regions (P=1.22×10(-6)) than traditional single-phenotype GWAS. The integrative analysis yielded genomic variants (rs2243057 and rs6453253) in F2RL1, a receptor that functions in hemostasis, thrombosis, and inflammation, which were associated with pleiotropic effects, including osteonecrosis and thrombosis, and were in regulatory gene regions.

CONCLUSION

The integrative pleiotropic analysis identified risk variants for osteonecrosis and thrombosis not identified by single-phenotype analysis that may have importance for patients with underlying sensitivity to multiple dexamethasone adverse effects.

Interactions between genetic variation and cellular environment in skeletal muscle gene expression

From whole organisms to individual cells, responses to environmental conditions are influenced by genetic makeup, where the effect of genetic variation on a trait depends on the environmental context. RNA-sequencing quantifies gene expression as a molecular trait, and is capable of capturing both genetic and environmental effects. In this study, we explore opportunities of using allele-specific expression (ASE) to discover cis-acting genotype-environment interactions (GxE)—genetic effects on gene expression that depend on an environmental condition. Treating 17 common, clinical traits as approximations of the cellular environment of 267 skeletal muscle biopsies, we identify 10 candidate environmental response expression quantitative trait loci (reQTLs) across 6 traits (12 unique gene-environment trait pairs; 10% FDR per trait) including sex, systolic blood pressure, and low-density lipoprotein cholesterol. Although using ASE is in principle a promising approach to detect GxE effects, replication of such signals can be challenging as validation requires harmonization of environmental traits across cohorts and a sufficient sampling of heterozygotes for a transcribed SNP. Comprehensive discovery and replication will require large human transcriptome datasets, or the integration of multiple transcribed SNPs, coupled with standardized clinical phenotyping.

Dyslexia risk variant rs600753 is linked with dyslexia-specific differential allelic expression of DYX1C1

An increasing number of genetic variants involved in dyslexia development were discovered during the last years, yet little is known about the molecular functional mechanisms of these SNPs. In this study we investigated whether dyslexia candidate SNPs have a direct, disease-specific effect on local expression levels of the assumed target gene by using a differential allelic expression assay. In total, 12 SNPs previously associated with dyslexia and related phenotypes were suitable for analysis. Transcripts corresponding to four SNPs were sufficiently expressed in 28 cell lines originating from controls and a family affected by dyslexia. We observed a significant effect of rs600753 on expression levels of DYX1C1 in forward and reverse sequencing approaches. The expression level of the rs600753 risk allele was increased in the respective seven cell lines from members of the dyslexia family which might be due to a disturbed transcription factor binding sites. When considering our results in the context of neuroanatomical dyslexia-specific findings, we speculate that this mechanism may be part of the pathomechanisms underlying the dyslexia-specific brain phenotype. Our results suggest that allele-specific DYX1C1 expression levels depend on genetic variants of rs600753 and contribute to dyslexia. However, these results are preliminary and need replication.

Cis-Regulatory Divergence in Gene Expression between Two Thermally Divergent Yeast Species

Gene regulation is a ubiquitous mechanism by which organisms respond to their environment. While organisms are often found to be adapted to the environments they experience, the role of gene regulation in environmental adaptation is not often known. In this study, we examine divergence in cis-regulatory effects between two Saccharomycesspecies, S. cerevisiaeand S. uvarum, that have substantially diverged in their thermal growth profile. We measured allele specific expression (ASE) in the species’ hybrid at three temperatures, the highest of which is lethal to S. uvarumbut not the hybrid or S. cerevisiae. We find that S. uvarumalleles can be expressed at the same level as S. cerevisiaealleles at high temperature and most cis-acting differences in gene expression are not dependent on temperature. While a small set of 136 genes show temperature-dependent ASE, we find no indication that signatures of directional cis-regulatory evolution are associated with temperature. Within promoter regions we find binding sites enriched upstream of temperature responsive genes, but only weak correlations between binding site and expression divergence. Our results indicate that temperature divergence between S. cerevisiaeand S. uvarumhas not caused widespread divergence in cis-regulatory activity, but point to a small subset of genes where the species’ alleles show differences in magnitude or opposite responses to temperature. The difficulty of explaining divergence in cis-regulatory sequences with models of transcription factor binding sites and nucleosome positioning highlights the importance of identifying mutations that underlie cis-regulatory divergence between species.

Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases

Recently, many new approaches, study designs, and statistical and analytical methods have emerged for studying gene-environment interactions (G×Es) in large-scale studies of human populations. There are opportunities in this field, particularly with respect to the incorporation of -omics and next-generation sequencing data and continual improvement in measures of environmental exposures implicated in complex disease outcomes. In a workshop called "Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases," held October 17-18, 2014, by the National Institute of Environmental Health Sciences and the National Cancer Institute in conjunction with the annual American Society of Human Genetics meeting, participants explored new approaches and tools that have been developed in recent years for G×E discovery. This paper highlights current and critical issues and themes in G×E research that need additional consideration, including the improved data analytical methods, environmental exposure assessment, and incorporation of functional data and annotations.

Genetic basis of mycotoxin susceptibility differences between budding yeast isolates

Micophenolic acid (MPA) is an immunosuppressant mycotoxin which impairs yeast cell growth to variable degrees depending on the genetic background. Such variation could have emerged from several phenomena, including MPA gene resistance mutations and variations in copy number and localisation of resistance genes. To test this, we evaluated MPA susceptibility in four S. cerevisiae isolates and genetically dissected variation through the identification of Quantitative Trait Loci. Via linkage analysis we identified six QTLs, majority of which were located within subtelomeres and co-localised with IMD2, an inosine monophosphate dehydrogenase previously identified underlying MPA drug resistance in yeast cells. From chromosome end disruption and bioinformatics analysis, it was found that the subtelomere localisation of IMD2 within chromosome ends is variable depending on the strain, demonstrating the influence of IMD2 on the natural variation in yeast MPA susceptibility. Furthermore, GxE gene expression analysis of strains exhibiting opposite phenotypes indicated that ribosome biogenesis, RNA transport, and purine biosynthesis were impaired in strains most susceptible to MPA toxicity. Our results demonstrate that natural variation can be exploited to better understand the molecular mechanisms underlying mycotoxin susceptibility in eukaryote cells and demonstrate the role of subtelomeric regions in mediating interactions with the environment.

Differential connectivity of gene regulatory networks distinguishes corticosteroid response in asthma

BACKGROUND

Variations in drug response between individuals have prevented us from achieving high drug efficacy in treating many complex diseases, including asthma. Genetics plays an important role in accounting for such interindividual variations in drug response. However, systematic approaches for addressing how genetic factors and their regulators determine variations in drug response in asthma treatment are lacking.

OBJECTIVE

We sought to identify key transcriptional regulators of corticosteroid response in asthma using a novel systems biology approach.

METHODS

We used Passing Attributes between Networks for Data Assimilations (PANDA) to construct the gene regulatory networks associated with good responders and poor responders to inhaled corticosteroids based on a subset of 145 white children with asthma who participated in the Childhood Asthma Management Cohort. PANDA uses gene expression profiles and published relationships among genes, transcription factors (TFs), and proteins to construct the directed networks of TFs and genes. We assessed the differential connectivity between the gene regulatory network of good responders versus that of poor responders.

RESULTS

When compared with poor responders, the network of good responders has differential connectivity and distinct ontologies (eg, proapoptosis enriched in network of good responders and antiapoptosis enriched in network of poor responders). Many of the key hubs identified in conjunction with clinical response are also cellular response hubs. Functional validation demonstrated abrogation of differences in corticosteroid-treated cell viability following siRNA knockdown of 2 TFs and differential downstream expression between good responders and poor responders.

CONCLUSIONS

We have identified and validated multiple TFs influencing asthma treatment response. Our results show that differential connectivity analysis can provide new insights into the heterogeneity of drug treatment effects.

Genome-wide association study identifies four novel loci associated with Alzheimer's endophenotypes and disease modifiers

More than 20 genetic loci have been associated with risk for Alzheimer's disease (AD), but reported genome-wide significant loci do not account for all the estimated heritability and provide little information about underlying biological mechanisms. Genetic studies using intermediate quantitative traits such as biomarkers, or endophenotypes, benefit from increased statistical power to identify variants that may not pass the stringent multiple test correction in case-control studies. Endophenotypes also contain additional information helpful for identifying variants and genes associated with other aspects of disease, such as rate of progression or onset, and provide context to interpret the results from genome-wide association studies (GWAS). We conducted GWAS of amyloid beta (Aβ42), tau, and phosphorylated tau (ptau181) levels in cerebrospinal fluid (CSF) from 3146 participants across nine studies to identify novel variants associated with AD. Five genome-wide significant loci (two novel) were associated with ptau181, including loci that have also been associated with AD risk or brain-related phenotypes. Two novel loci associated with Aβ42 near GLIS1 on 1p32.3 (β = -0.059, P = 2.08 × 10-8) and within SERPINB1 on 6p25 (β = -0.025, P = 1.72 × 10-8) were also associated with AD risk (GLIS1: OR = 1.105, P = 3.43 × 10-2), disease progression (GLIS1: β = 0.277, P = 1.92 × 10-2), and age at onset (SERPINB1: β = 0.043, P = 4.62 × 10-3). Bioinformatics indicate that the intronic SERPINB1 variant (rs316341) affects expression of SERPINB1 in various tissues, including the hippocampus, suggesting that SERPINB1 influences AD through an Aβ-associated mechanism. Analyses of known AD risk loci suggest CLU and FERMT2 may influence CSF Aβ42 (P = 0.001 and P = 0.009, respectively) and the INPP5D locus may affect ptau181 levels (P = 0.009); larger studies are necessary to verify these results. Together the findings from this study can be used to inform future AD studies.

Time-dependent genetic effects on gene expression implicate aging processes

Gene expression is dependent on genetic and environmental factors. In the last decade, a large body of research has significantly improved our understanding of the genetic architecture of gene expression. However, it remains unclear whether genetic effects on gene expression remain stable over time. Here, we show, using longitudinal whole-blood gene expression data from a twin cohort, that the genetic architecture of a subset of genes is unstable over time. In addition, we identified 2213 genes differentially expressed across time points that we linked with aging within and across studies. Interestingly, we discovered that most differentially expressed genes were affected by a subset of 77 putative causal genes. Finally, we observed that putative causal genes and down-regulated genes were affected by a loss of genetic control between time points. Taken together, our data suggest that instability in the genetic architecture of a subset of genes could lead to widespread effects on the transcriptome with an aging signature.

Using GWAS to identify novel therapeutic targets for osteoporosis

Osteoporosis is a common, increasingly prevalent, global health burden characterized by low bone mineral density (BMD) and increased risk of fracture. Despite its significant impact on human health, there is currently a lack of highly effective treatments free of side effects for osteoporosis. Therefore, a major goal in the field is to identify new drug targets. Genetic discovery has been shown to be effective in the unbiased identification of novel drug targets and genome-wide association studies (GWASs) have begun to provide insight into genetic basis of osteoporosis. Over the last decade, GWASs have led to the identification of ∼100 loci associated with BMD and other bone traits related to risk of fracture. However, there have been limited efforts to identify the causal genes underlying the GWAS loci or the mechanisms by which GWAS loci alter bone physiology. In this review, we summarize the current state of the field and discuss strategies for causal gene discovery and the evidence that the novel genes underlying GWAS loci are likely to be a new source of drug targets.

Association of breast cancer risk in BRCA1 and BRCA2 mutation carriers with genetic variants showing differential allelic expression: identification of a modifier of breast cancer risk at locus 11q22.3

PURPOSE

Cis-acting regulatory SNPs resulting in differential allelic expression (DAE) may, in part, explain the underlying phenotypic variation associated with many complex diseases. To investigate whether common variants associated with DAE were involved in breast cancer susceptibility among BRCA1 and BRCA2 mutation carriers, a list of 175 genes was developed based of their involvement in cancer-related pathways.

METHODS

Using data from a genome-wide map of SNPs associated with allelic expression, we assessed the association of ~320 SNPs located in the vicinity of these genes with breast and ovarian cancer risks in 15,252 BRCA1 and 8211 BRCA2 mutation carriers ascertained from 54 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2.

RESULTS

We identified a region on 11q22.3 that is significantly associated with breast cancer risk in BRCA1 mutation carriers (most significant SNP rs228595 p = 7 × 10-6). This association was absent in BRCA2 carriers (p = 0.57). The 11q22.3 region notably encompasses genes such as ACAT1, NPAT, and ATM. Expression quantitative trait loci associations were observed in both normal breast and tumors across this region, namely for ACAT1, ATM, and other genes. In silico analysis revealed some overlap between top risk-associated SNPs and relevant biological features in mammary cell data, which suggests potential functional significance.

CONCLUSION

We identified 11q22.3 as a new modifier locus in BRCA1 carriers. Replication in larger studies using estrogen receptor (ER)-negative or triple-negative (i.e., ER-, progesterone receptor-, and HER2-negative) cases could therefore be helpful to confirm the association of this locus with breast cancer risk.

Systems Genetics as a Tool to Identify Master Genetic Regulators in Complex Disease

Systems genetics stems from systems biology and similarly employs integrative modeling approaches to describe the perturbations and phenotypic effects observed in a complex system. However, in the case of systems genetics the main source of perturbation is naturally occurring genetic variation, which can be analyzed at the systems-level to explain the observed variation in phenotypic traits. In contrast with conventional single-variant association approaches, the success of systems genetics has been in the identification of gene networks and molecular pathways that underlie complex disease. In addition, systems genetics has proven useful in the discovery of master trans-acting genetic regulators of functional networks and pathways, which in many cases revealed unexpected gene targets for disease. Here we detail the central components of a fully integrated systems genetics approach to complex disease, starting from assessment of genetic and gene expression variation, linking DNA sequence variation to mRNA (expression QTL mapping), gene regulatory network analysis and mapping the genetic control of regulatory networks. By summarizing a few illustrative (and successful) examples, we highlight how different data-modeling strategies can be effectively integrated in a systems genetics study.

miR-203 and miR-320 Regulate Bone Morphogenetic Protein-2-Induced Osteoblast Differentiation by Targeting Distal-Less Homeobox 5 (Dlx5)

MicroRNAs (miRNAs) are a family of small, non-coding RNAs (17–24 nucleotides), which regulate gene expression either by the degradation of the target mRNAs or inhibiting the translation of genes. Recent studies have indicated that miRNA plays an important role in regulating osteoblast differentiation. In this study, we identified miR-203 and miR-320b as important miRNAs modulating osteoblast differentiation. We identified Dlx5 as potential common target by prediction algorithms and confirmed this by knock-down and over expression of the miRNAs and assessing Dlx5 at mRNA and protein levels and specificity was verified by luciferase reporter assays. We examined the effect of miR-203 and miR-320b on osteoblast differentiation by transfecting with pre- and anti-miRs. Over-expression of miR-203 and miR-320b inhibited osteoblast differentiation, whereas inhibition of miR-203 and miR-320b stimulated alkaline phosphatase activity and matrix mineralization. We show that miR-203 and miR-320b negatively regulate BMP-2-induced osteoblast differentiation by suppressing Dlx5, which in turn suppresses the downstream osteogenic master transcription factor Runx2 and Osx and together they suppress osteoblast differentiation. Taken together, we propose a role for miR-203 and miR-320b in modulating bone metabolism.

Association of breast cancer risk with genetic variants showing differential allelic expression: Identification of a novel breast cancer susceptibility locus at 4q21

There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, cis-acting variants represent an important source of phenotypic variation. Consequently, cis-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, P = 5.6x10-6). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, HELQ, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, MRPS18C encoding the Mitochondrial Ribosomal Protein S18C and FAM175A (ABRAXAS), encoding a BRCA1 BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with HELQ (P = 8.28x10-14), MRPS18C (P = 1.94x10-27) and FAM175A (P = 3.83x10-3), explaining about 20%, 14% and 1%, respectively of the variance inexpression of these genes in breast carcinomas.

Capture Hi-C identifies a novel causal gene, IL20RA, in the pan-autoimmune genetic susceptibility region 6q23

BACKGROUND

The identification of causal genes from genome-wide association studies (GWAS) is the next important step for the translation of genetic findings into biologically meaningful mechanisms of disease and potential therapeutic targets. Using novel chromatin interaction detection techniques and allele specific assays in T and B cell lines, we provide compelling evidence that redefines causal genes at the 6q23 locus, one of the most important loci that confers autoimmunity risk.

RESULTS

Although the function of disease-associated non-coding single nucleotide polymorphisms (SNPs) at 6q23 is unknown, the association is generally assigned to TNFAIP3, the closest gene. However, the DNA fragment containing the associated SNPs interacts through chromatin looping not only with TNFAIP3, but also with IL20RA, located 680 kb upstream. The risk allele of the most likely causal SNP, rs6927172, is correlated with both a higher frequency of interactions and increased expression of IL20RA, along with a stronger binding of both the NFκB transcription factor and chromatin marks characteristic of active enhancers in T-cells.

CONCLUSIONS

Our results highlight the importance of gene assignment for translating GWAS findings into biologically meaningful mechanisms of disease and potential therapeutic targets; indeed, monoclonal antibody therapy targeting IL-20 is effective in the treatment of rheumatoid arthritis and psoriasis, both with strong GWAS associations to this region.

High-throughput allele-specific expression across 250 environmental conditions

Gene-by-environment (GxE) interactions determine common disease risk factors and biomedically relevant complex traits. However, quantifying how the environment modulates genetic effects on human quantitative phenotypes presents unique challenges. Environmental covariates are complex and difficult to measure and control at the organismal level, as found in GWAS and epidemiological studies. An alternative approach focuses on the cellular environment using in vitro treatments as a proxy for the organismal environment. These cellular environments simplify the organism-level environmental exposures to provide a tractable influence on subcellular phenotypes, such as gene expression. Expression quantitative trait loci (eQTL) mapping studies identified GxE interactions in response to drug treatment and pathogen exposure. However, eQTL mapping approaches are infeasible for large-scale analysis of multiple cellular environments. Recently, allele-specific expression (ASE) analysis emerged as a powerful tool to identify GxE interactions in gene expression patterns by exploiting naturally occurring environmental exposures. Here we characterized genetic effects on the transcriptional response to 50 treatments in five cell types. We discovered 1455 genes with ASE (FDR < 10%) and 215 genes with GxE interactions. We demonstrated a major role for GxE interactions in complex traits. Genes with a transcriptional response to environmental perturbations showed sevenfold higher odds of being found in GWAS. Additionally, 105 genes that indicated GxE interactions (49%) were identified by GWAS as associated with complex traits. Examples include GIPR–caffeine interaction and obesity and include LAMP3–selenium interaction and Parkinson disease. Our results demonstrate that comprehensive catalogs of GxE interactions are indispensable to thoroughly annotate genes and bridge epidemiological and genome-wide association studies.

Genome-wide associations for birth weight and correlations with adult disease

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10-8). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = -0.22, P = 5.5 × 10-13), T2D (Rg = -0.27, P = 1.1 × 10-6) and coronary artery disease (Rg = -0.30, P = 6.5 × 10-9). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10-4). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.

Hypothalamic transcriptomes of 99 mouse strains reveal trans eQTL hotspots, splicing QTLs and novel non-coding genes

Previous studies had shown that the integration of genome wide expression profiles, in metabolic tissues, with genetic and phenotypic variance, provided valuable insight into the underlying molecular mechanisms. We used RNA-Seq to characterize hypothalamic transcriptome in 99 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP), a reference resource population for cardiovascular and metabolic traits. We report numerous novel transcripts supported by proteomic analyses, as well as novel non coding RNAs. High resolution genetic mapping of transcript levels in HMDP, reveals both local and trans expression Quantitative Trait Loci (eQTLs) demonstrating 2 trans eQTL 'hotspots' associated with expression of hundreds of genes. We also report thousands of alternative splicing events regulated by genetic variants. Finally, comparison with about 150 metabolic and cardiovascular traits revealed many highly significant associations. Our data provide a rich resource for understanding the many physiologic functions mediated by the hypothalamus and their genetic regulation.

DOI:http://dx.doi.org/10.7554/eLife.15614.001

Metabolism is a term that describes all the chemical reactions that are involved in keeping a living organism alive. Diseases related to metabolism – such as obesity, heart disease and diabetes – are a major health problem in the Western world. The causes of these diseases are complex and include both environmental factors, such as diet and exercise, and genetics. Indeed, many genetic variants that contribute to obesity have been uncovered in both humans and mice. However, it is only dimly understood how these genetic variants affect the underlying networks of interacting genes that cause metabolic disorders.

Measuring gene activity or expression, and tracing how genetic instructions are carried from DNA into RNA and proteins, can reliably identify groups of genes that correlate with metabolic traits in specific organs. This strategy was successfully used in previous studies to reveal new information about abnormalities linked to obesity in specific tissues such as the liver and fat tissues. It was also shown that this approach might suggest new molecules that could be targeted to treat metabolic disorders.

A brain region called the hypothalamus is key to the control of metabolism, including feeding behavior and obesity. Hasin-Brumshtein et al. set out to explore gene expression in the hypothalamus of 99 different strains of mice, in the hope that the data will help identify new connections between gene expression and metabolism.

This approach showed that thousands of new and known genes are expressed in the mouse hypothalamus, some of which coded for proteins, and some of which did not. Hasin-Brumshtein et al. uncovered two genetic variants that controlled the expression of hundreds of other genes. Further analysis then revealed thousands of genetic variants that regulated the expression of, and type of RNA (so-called "spliceforms") produced from neighboring genes. Also, the expression of many individual genes showed significant similarities with about 150 metabolic measurements that had been evaluated previously in the mice.

This new dataset is a unique resource that can be coupled with different approaches to test existing ideas and develop new ones about the role of particular genes or genetic mechanisms in obesity. Future studies will likely focus on new genes that show strong associations with attributes that are relevant to metabolic disorders, such as insulin levels, weight and fat mass.

DOI:http://dx.doi.org/10.7554/eLife.15614.002

Second generation sequencing of microRNA in Human Bone Cells treated with Parathyroid Hormone or Dexamethasone

We investigated the impact of treatment with parathyroid hormone (PTH) and dexamethasone (DEX) for 2 and 24h by RNA sequencing of miRNAs in primary human bone (HOB) cells. A total of 207 million reads were obtained, and normalized absolute expression retrieved for 373 most abundant miRNAs. In naïve control cells, 7 miRNAs were differentially expressed (FDR<0.05) between the two time points. Ten miRNAs exhibited differential expression (FDR <0.05) across two time points and treatments after adjusting for expression in controls and were selected for downstream analyses. Results show significant effects on miRNA expression when comparing PTH with DEX at 2h with even more pronounced effects at 24h. Interestingly, several miRNAs exhibiting differences in expression are predicted to target genes involved in bone metabolism e.g. miR-30c2, miR-203 and miR-205 targeting RUNX2, and miR-320 targeting β-catenin (CTNNB1) mRNA expression. CTNNB1and RUNX2 levels were decreased after DEX treatment and increased after PTH treatment. Our analysis also identified 2 putative novel miRNAs in PTH and DEX treated cells at 24h. RNA sequencing showed that PTH and DEX treatment affect miRNA expression in HOB cells and that regulated miRNAs in turn are correlated with expression levels of key genes involved in bone metabolism.

HaploReg v4: systematic mining of putative causal variants, cell types, regulators and target genes for human complex traits and disease

More than 90% of common variants associated with complex traits do not affect proteins directly, but instead the circuits that control gene expression. This has increased the urgency of understanding the regulatory genome as a key component for translating genetic results into mechanistic insights and ultimately therapeutics. To address this challenge, we developed HaploReg (http://compbio.mit.edu/HaploReg) to aid the functional dissection of genome-wide association study (GWAS) results, the prediction of putative causal variants in haplotype blocks, the prediction of likely cell types of action, and the prediction of candidate target genes by systematic mining of comparative, epigenomic and regulatory annotations. Since first launching the website in 2011, we have greatly expanded HaploReg, increasing the number of chromatin state maps to 127 reference epigenomes from ENCODE 2012 and Roadmap Epigenomics, incorporating regulator binding data, expanding regulatory motif disruption annotations, and integrating expression quantitative trait locus (eQTL) variants and their tissue-specific target genes from GTEx, Geuvadis, and other recent studies. We present these updates as HaploReg v4, and illustrate a use case of HaploReg for attention deficit hyperactivity disorder (ADHD)-associated SNPs with putative brain regulatory mechanisms.

Genetic risk factors for decreased bone mineral accretion in children with asthma receiving multiple oral corticosteroid bursts

BACKGROUND

Long-term intermittent oral corticosteroid (OCS) use in children with asthma leads to significant decreases in bone mineral accretion (BMA).

OBJECTIVE

We aimed to identify genetic factors influencing OCS dose effects on BMA in children with asthma.

METHODS

We first performed a gene-by-OCS interaction genome-wide association study (GWAS) of BMA in 489 white participants in the Childhood Asthma Management Program trial who took short-term oral prednisone bursts when they experienced acute asthma exacerbations. We selected the top-ranked 2000 single nucleotide polymorphisms (SNPs) in the GWAS and determined whether these SNPs also had cis-regulatory effects on dexamethasone-induced gene expression in osteoblasts.

RESULTS

We identified 2 SNPs (rs9896933 and rs2074439) associated with decreased BMA and related to the tubulin γ pathway. The rs9896933 variant met the criteria for genome-wide significance (P = 3.15 × 10(-8) in the GWAS) and is located on the intron of tubulin folding cofactor D (TBCD) gene. The rs2074439 variant (P = 2.74 × 10(-4) in the GWAS) showed strong cis-regulatory effects on dexamethasone-induced tubulin γ gene expression in osteoblasts (P = 8.64 × 10(-4)). Interestingly, we found that BMA worsened with increasing prednisone dose as the number of mutant alleles of the 2 SNPs increased.

CONCLUSIONS

We have identified 2 novel tubulin γ pathway SNPs, rs9896933 and rs2074439, showing independent interactive effects with cumulative corticosteroid dose on BMA in children with asthma receiving multiple OCS bursts.

Asthma Pharmacogenomics: 2015 Update

There is evidence that genetic factors are implicated in the observed differences in therapeutic responses to the common classes of asthma therapy such as β2-agonists, corticosteroids, and leukotriene modifiers. Pharmacogenomics explores the roles of genetic variation in drug response and continues to be a field of great interest in asthma therapy. Prior studies have focused on candidate genes and recently emphasized genome-wide association analyses. Newer integrative omics and system-level approaches have recently revealed novel understanding of drug response pathways. However, the current known genetic loci only account for a fraction of variability in drug response and ongoing research is needed. While the field of asthma pharmacogenomics is not yet fully translatable to clinical practice, ongoing research should hopefully achieve this goal in the near future buttressed by the recent precision medicine efforts in the USA and worldwide.

Combining genetic and nongenetic biomarkers to realize the promise of pharmacogenomics for inflammatory diseases

Many drugs used to treat inflammatory diseases are ineffective in a substantial proportion of patients. Identifying patients that are likely to respond to specific therapies would facilitate personalized treatment strategies that could improve outcomes while reducing costs and risks of adverse events. Despite these clear benefits, there are limited examples of predictive biomarkers of drug efficacy currently implemented into clinical practice for inflammatory diseases. We review efforts to identify genetic and nongenetic biomarkers of drug response in these diseases and consider potential benefits from combining multiple sources of biological data into multifeature predictive models.

Global miRNA expression and correlation with mRNA levels in primary human bone cells

MicroRNAs (miRNAs) are important post-transcriptional regulators that have recently introduced an additional level of intricacy to our understanding of gene regulation. The aim of this study was to investigate miRNA-mRNA interactions that may be relevant for bone metabolism by assessing correlations and interindividual variability in miRNA levels as well as global correlations between miRNA and mRNA levels in a large cohort of primary human osteoblasts (HOBs) obtained during orthopedic surgery in otherwise healthy individuals. We identified differential expression (DE) of 24 miRNAs, and found 9 miRNAs exhibiting DE between males and females. We identified hsa-miR-29b, hsa-miR-30c2, and hsa-miR-125b and their target genes as important modulators of bone metabolism. Further, we used an integrated analysis of global miRNA-mRNA correlations, mRNA-expression profiling, DE, bioinformatics analysis, and functional studies to identify novel target genes for miRNAs with the potential to regulate osteoblast differentiation and extracellular matrix production. Functional studies by overexpression and knockdown of miRNAs showed that, the differentially expressed miRNAs hsa-miR-29b, hsa-miR-30c2, and hsa-miR-125b target genes highly relevant to bone metabolism, e.g., collagen, type I, α1 (COL1A1), osteonectin (SPARC), Runt-related transcription factor 2 (RUNX2), osteocalcin (BGLAP), and frizzled-related protein (FRZB). These miRNAs orchestrate the activities of key regulators of osteoblast differentiation and extracellular matrix proteins by their convergent action on target genes and pathways to control the skeletal gene expression.

QuASAR: quantitative allele-specific analysis of reads

MOTIVATION

Expression quantitative trait loci (eQTL) studies have discovered thousands of genetic variants that regulate gene expression, enabling a better understanding of the functional role of non-coding sequences. However, eQTL studies are costly, requiring large sample sizes and genome-wide genotyping of each sample. In contrast, analysis of allele-specific expression (ASE) is becoming a popular approach to detect the effect of genetic variation on gene expression, even within a single individual. This is typically achieved by counting the number of RNA-seq reads matching each allele at heterozygous sites and testing the null hypothesis of a 1:1 allelic ratio. In principle, when genotype information is not readily available, it could be inferred from the RNA-seq reads directly. However, there are currently no existing methods that jointly infer genotypes and conduct ASE inference, while considering uncertainty in the genotype calls.

RESULTS

We present QuASAR, quantitative allele-specific analysis of reads, a novel statistical learning method for jointly detecting heterozygous genotypes and inferring ASE. The proposed ASE inference step takes into consideration the uncertainty in the genotype calls, while including parameters that model base-call errors in sequencing and allelic over-dispersion. We validated our method with experimental data for which high-quality genotypes are available. Results for an additional dataset with multiple replicates at different sequencing depths demonstrate that QuASAR is a powerful tool for ASE analysis when genotypes are not available.

AVAILABILITY AND IMPLEMENTATION

http://github.com/piquelab/QuASAR.

CONTACT

fluca@wayne.edu or rpique@wayne.edu

SUPPLEMENTARY INFORMATION

Supplementary Material is available at Bioinformatics online.

Extensive cis-regulatory variation robust to environmental perturbation in Arabidopsis

cis- and trans-acting factors affect gene expression and responses to environmental conditions. However, for most plant systems, we lack a comprehensive map of these factors and their interaction with environmental variation. Here, we examined allele-specific expression (ASE) in an F1 hybrid to study how alleles from two Arabidopsis thaliana accessions affect gene expression. To investigate the effect of the environment, we used drought stress and developed a variance component model to estimate the combined genetic contributions of cis- and trans-regulatory polymorphisms, environmental factors, and their interactions. We quantified ASE for 11,003 genes, identifying 3318 genes with consistent ASE in control and stress conditions, demonstrating that cis-acting genetic effects are essentially robust to changes in the environment. Moreover, we found 1618 genes with genotype x environment (GxE) interactions, mostly cis x E interactions with magnitude changes in ASE. We found fewer trans x E interactions, but these effects were relatively less robust across conditions, showing more changes in the direction of the effect between environments; this confirms that trans-regulation plays an important role in the response to environmental conditions. Our data provide a detailed map of cis- and trans-regulation and GxE interactions in A. thaliana, laying the ground for mechanistic investigations and studies in other plants and environments.

Allelic expression mapping across cellular lineages to establish impact of non-coding SNPs

Most complex disease-associated genetic variants are located in non-coding regions and are therefore thought to be regulatory in nature. Association mapping of differential allelic expression (AE) is a powerful method to identify SNPs with direct cis-regulatory impact (cis-rSNPs). We used AE mapping to identify cis-rSNPs regulating gene expression in 55 and 63 HapMap lymphoblastoid cell lines from a Caucasian and an African population, respectively, 70 fibroblast cell lines, and 188 purified monocyte samples and found 40–60% of these cis-rSNPs to be shared across cell types. We uncover a new class of cis-rSNPs, which disrupt footprint-derived de novo motifs that are predominantly bound by repressive factors and are implicated in disease susceptibility through overlaps with GWAS SNPs. Finally, we provide the proof-of-principle for a new approach for genome-wide functional validation of transcription factor–SNP interactions. By perturbing NFκB action in lymphoblasts, we identified 489 cis-regulated transcripts with altered AE after NFκB perturbation. Altogether, we perform a comprehensive analysis of cis-variation in four cell populations and provide new tools for the identification of functional variants associated to complex diseases.

Pharmacogenomics in asthma therapy: where are we and where do we go?

The response to drug treatment in asthma is a complex trait and is markedly variable even in patients with apparently similar clinical features. Pharmaco-genomics, which is the study of variations of human genome characteristics as related to drug response, can play a role in asthma therapy. Both a traditional candidate-gene approach to conducting genetic association studies and genome-wide association studies have provided an increasing list of genes and variants associated with the three major classes of asthma medications: β2-agonists, inhaled corticosteroids, and leukotriene modifiers. Moreover, a recent integrative, systems-level approach has offered a promising opportunity to identify important pharmacogenomics loci in asthma treatment. However, we are still a long way away from making this discipline directly relevant to patients. The combination of network modeling, functional validation, and integrative omics technologies will likely be needed to move asthma pharmacogenomics closer to clinical relevance.

Interrogation of allelic chromatin states in human cells by high-density ChIP-genotyping

Allele-specific (AS) assessment of chromatin has the potential to elucidate specific cis-regulatory mechanisms, which are predicted to underlie the majority of the known genetic associations to complex disease. However, development of chromatin landscapes at allelic resolution has been challenging since sites of variable signal strength require substantial read depths not commonly applied in sequencing based approaches. In this study, we addressed this by performing parallel analyses of input DNA and chromatin immunoprecipitates (ChIP) on high-density Illumina genotyping arrays. Allele-specificity for the histone modifications H3K4me1, H3K4me3, H3K27ac, H3K27me3, and H3K36me3 was assessed using ChIP samples generated from 14 lymphoblast and 6 fibroblast cell lines. AS-ChIP SNPs were combined into domains and validated using high-confidence ChIP-seq sites. We observed characteristic patterns of allelic-imbalance for each histone-modification around allele-specifically expressed transcripts. Notably, we found H3K4me1 to be significantly anti-correlated with allelic expression (AE) at transcription start sites, indicating H3K4me1 allelic imbalance as a marker of AE. We also found that allelic chromatin domains exhibit population and cell-type specificity as well as heritability within trios. Finally, we observed that a subset of allelic chromatin domains is regulated by DNase I-sensitive quantitative trait loci and that these domains are significantly enriched for genome-wide association studies hits, with autoimmune disease associated SNPs specifically enriched in lymphoblasts. This study provides the first genome-wide maps of allelic-imbalance for five histone marks. Our results provide new insights into the role of chromatin in cis-regulation and highlight the need for high-depth sequencing in ChIP-seq studies along with the need to improve allele-specificity of ChIP-enrichment.

Allele-specific expression and eQTL analysis in mouse adipose tissue

Background

The 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.

Results

In 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.

Conclusions

We 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.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-471) contains supplementary material, which is available to authorized users.

Phenotypic dissection of bone mineral density reveals skeletal site specificity and facilitates the identification of novel loci in the genetic regulation of bone mass attainment

Heritability of bone mineral density (BMD) varies across skeletal sites, reflecting different relative contributions of genetic and environmental influences. To quantify the degree to which common genetic variants tag and environmental factors influence BMD, at different sites, we estimated the genetic (rg) and residual (re) correlations between BMD measured at the upper limbs (UL-BMD), lower limbs (LL-BMD) and skull (SK-BMD), using total-body DXA scans of ∼ 4,890 participants recruited by the Avon Longitudinal Study of Parents and their Children (ALSPAC). Point estimates of rg indicated that appendicular sites have a greater proportion of shared genetic architecture (LL-/UL-BMD rg = 0.78) between them, than with the skull (UL-/SK-BMD rg = 0.58 and LL-/SK-BMD rg = 0.43). Likewise, the residual correlation between BMD at appendicular sites (r(e) = 0.55) was higher than the residual correlation between SK-BMD and BMD at appendicular sites (r(e) = 0.20-0.24). To explore the basis for the observed differences in rg and re, genome-wide association meta-analyses were performed (n ∼ 9,395), combining data from ALSPAC and the Generation R Study identifying 15 independent signals from 13 loci associated at genome-wide significant level across different skeletal regions. Results suggested that previously identified BMD-associated variants may exert site-specific effects (i.e. differ in the strength of their association and magnitude of effect across different skeletal sites). In particular, variants at CPED1 exerted a larger influence on SK-BMD and UL-BMD when compared to LL-BMD (P = 2.01 × 10(-37)), whilst variants at WNT16 influenced UL-BMD to a greater degree when compared to SK- and LL-BMD (P = 2.31 × 10(-14)). In addition, we report a novel association between RIN3 (previously associated with Paget's disease) and LL-BMD (rs754388: β = 0.13, SE = 0.02, P = 1.4 × 10(-10)). Our results suggest that BMD at different skeletal sites is under a mixture of shared and specific genetic and environmental influences. Allowing for these differences by performing genome-wide association at different skeletal sites may help uncover new genetic influences on BMD.

Determining causality and consequence of expression quantitative trait loci

Expression quantitative trait loci (eQTLs) are currently the most abundant and systematically-surveyed class of functional consequence for genetic variation. Recent genetic studies of gene expression have identified thousands of eQTLs in diverse tissue types for the majority of human genes. Application of this large eQTL catalog provides an important resource for understanding the molecular basis of common genetic diseases. However, only now has both the availability of individuals with full genomes and corresponding advances in functional genomics provided the opportunity to dissect eQTLs to identify causal regulatory variants. Resolving the properties of such causal regulatory variants is improving understanding of the molecular mechanisms that influence traits and guiding the development of new genome-scale approaches to variant interpretation. In this review, we provide an overview of current computational and experimental methods for identifying causal regulatory variants and predicting their phenotypic consequences.

Pharmacogenomics: novel loci identification via integrating gene differential analysis and eQTL analysis

Nearly one-half of asthmatic patients do not respond to the most commonly prescribed controller therapy, inhaled corticosteroids (ICS). We conducted an expression quantitative trait loci (eQTL) analysis using >300 expression microarrays (from 117 lymphoblastoid cell lines) in corticosteroid (dexamethasone) treated and untreated cells derived from asthmatic subjects in the Childhood Asthma Management Program (CAMP) clinical trial. We then tested the associations of eQTL with longitudinal change in airway responsiveness to methacholine (LnPC20) on ICS. We identified 2484 cis-eQTL affecting 767 genes following dexamethasone treatment. A significant over-representation of lnPC20-associated cis-eQTL [190 single-nucleotide polymorphisms (SNPs)] among differentially expressed genes (odds ratio = 1.76, 95% confidence interval: 1.35-2.29) was noted in CAMP Caucasians. Forty-six of these 190 clinical associations were replicated in CAMP African Americans, including seven SNPs near six genes meeting criteria for genome-wide significance (P < 2 × 10(-7)). Notably, the majority of genome-wide findings would not have been uncovered via analysis of untreated samples. These results indicate that identifying eQTL after relevant environmental perturbation enables identification of true pharmacogenetic variants.

Expression quantitative trait analyses to identify causal genetic variants for type 2 diabetes susceptibility

Type 2 diabetes (T2D) is a common metabolic disorder which is caused by multiple genetic perturbations affecting different biological pathways. Identifying genetic factors modulating the susceptibility of this complex heterogeneous metabolic phenotype in different ethnic and racial groups remains challenging. Despite recent success, the functional role of the T2D susceptibility variants implicated by genome-wide association studies (GWAS) remains largely unknown. Genetic dissection of transcript abundance or expression quantitative trait (eQTL) analysis unravels the genomic architecture of regulatory variants. Availability of eQTL information from tissues relevant for glucose homeostasis in humans opens a new avenue to prioritize GWAS-implicated variants that may be involved in triggering a causal chain of events leading to T2D. In this article, we review the progress made in the field of eQTL research and knowledge gained from those studies in understanding transcription regulatory mechanisms in human subjects. We highlight several novel approaches that can integrate eQTL analysis with multiple layers of biological information to identify ethnic-specific causal variants and gene-environment interactions relevant to T2D pathogenesis. Finally, we discuss how the eQTL analysis mediated search for “missing heritability” may lead us to novel biological and molecular mechanisms involved in susceptibility to T2D.

Vitamin D and gene networks in human osteoblasts

Bone formation is indirectly influenced by 1,25-dihydroxyvitamin D3 (1,25D3) through the stimulation of calcium uptake in the intestine and re-absorption in the kidneys. Direct effects on osteoblasts and bone formation have also been established. The vitamin D receptor (VDR) is expressed in osteoblasts and 1,25D3 modifies gene expression of various osteoblast differentiation and mineralization-related genes, such as alkaline phosphatase (ALPL), osteocalcin (BGLAP), and osteopontin (SPP1). 1,25D3 is known to stimulate mineralization of human osteoblasts in vitro, and recently it was shown that 1,25D3 induces mineralization via effects in the period preceding mineralization during the pre-mineralization period. For a full understanding of the action of 1,25D3 in osteoblasts it is important to get an integrated network view of the 1,25D3-regulated genes during osteoblast differentiation and mineralization. The current data will be presented and discussed alluding to future studies to fully delineate the 1,25D3 action in osteoblast. Describing and understanding the vitamin D regulatory networks and identifying the dominant players in these networks may help develop novel (personalized) vitamin D-based treatments. The following topics will be discussed in this overview: (1) Bone metabolism and osteoblasts, (2) Vitamin D, bone metabolism and osteoblast function, (3) Vitamin D induced transcriptional networks in the context of osteoblast differentiation and bone formation.

Genetic implication of a novel thiamine transporter in human hypertension

OBJECTIVES

This study coupled 2 strategies-trait extremes and genome-wide pooling-to discover a novel blood pressure (BP) locus that encodes a previously uncharacterized thiamine transporter.

BACKGROUND

Hypertension is a heritable trait that remains the most potent and widespread cardiovascular risk factor, although details of its genetic determination are poorly understood.

METHODS

Representative genomic deoxyribonucleic acid (DNA) pools were created from male and female subjects in the highest- and lowest-fifth percentiles of BP in a primary care population of >50,000 patients. The peak associated single-nucleotide polymorphisms were typed in individual DNA samples, as well as in twins/siblings phenotyped for cardiovascular and autonomic traits. Biochemical properties of the associated transporter were evaluated in cellular assays.

RESULTS

After chip hybridization and calculation of relative allele scores, the peak associations were typed in individual samples, revealing an association between hypertension, systolic BP, and diastolic BP and the previously uncharacterized solute carrier SLC35F3. The BP genetic association at SLC35F3 was validated by meta-analysis in an independent sample from the original source population, as well as the International Consortium for Blood Pressure Genome-Wide Association Studies (across North America and western Europe). Sequence homology to a putative yeast thiamine (vitamin B1) transporter prompted us to express human SLC35F3 in Escherichia coli, which catalyzed [(3)H]-thiamine uptake. SLC35F3 risk-allele homozygotes (T/T) displayed decreased erythrocyte thiamine content on microbiological assay. In twin pairs, the SLC35F3 risk allele predicted heritable cardiovascular traits previously associated with thiamine deficiency, including elevated cardiac stroke volume with decreased vascular resistance, and elevated pressor responses to environmental (cold) stress. Allelic expression imbalance confirmed that cis variation at the human SLC35F3 locus influenced expression of that gene, and the allelic expression imbalance peak coincided with the hypertension peak.

CONCLUSIONS

Novel strategies were coupled to position a new hypertension-susceptibility locus, uncovering a previously unsuspected thiamine transporter whose genetic variants predicted several disturbances in cardiac and autonomic function. The results have implications for the pathogenesis and treatment of systemic hypertension.