Cis-acting regulatory variation in the human genome

Cis-regulatory Variation in Relation to Sex and Sexual Dimorphism in Drosophila melanogaster

Much of sexual dimorphism is likely due to sex-biased gene expression, which results from differential regulation of a genome that is largely shared between males and females. Here, we use allele-specific expression to explore cis-regulatory variation in Drosophila melanogaster in relation to sex. We develop a Bayesian framework to infer the transcriptome-wide joint distribution of cis-regulatory effects across the sexes. We also examine patterns of cis-regulatory variation with respect to two other levels of variation in sexual dimorphism: (i) across genes that vary in their degree of sex-biased expression and (ii) among tissues that vary in their degree of dimorphism (e.g. relatively low dimorphism in heads vs. high dimorphism in gonads). We uncover evidence of widespread cis-regulatory variation in all tissues examined, with female-biased genes being especially enriched for this variation. A sizeable proportion of cis-regulatory variation is inferred to have sex-specific effects, with sex-dependent cis effects being much more frequent in gonads than in heads. Finally, we find some genes where 1 allele contributes to more than 50% of a gene's expression in heterozygous males but <50% of its expression in heterozygous females. Such variants could provide a mechanism for sex-specific dominance reversals, a phenomenon important for sexually antagonistic balancing selection. However, tissue differences in allelic imbalance are approximately as frequent as sex differences, perhaps suggesting that sexual conflict may not be particularly unique in shaping patterns of expression variation.

Identification of candidate causal variants and target genes at 41 breast cancer risk loci through differential allelic expression analysis

Understanding breast cancer genetic risk relies on identifying causal variants and candidate target genes in risk loci identified by genome-wide association studies (GWAS), which remains challenging. Since most loci fall in active gene regulatory regions, we developed a novel approach facilitated by pinpointing the variants with greater regulatory potential in the disease's tissue of origin. Through genome-wide differential allelic expression (DAE) analysis, using microarray data from 64 normal breast tissue samples, we mapped the variants associated with DAE (daeQTLs). Then, we intersected these with GWAS data to reveal candidate risk regulatory variants and analysed their cis-acting regulatory potential. Finally, we validated our approach by extensive functional analysis of the 5q14.1 breast cancer risk locus. We observed widespread gene expression regulation by cis-acting variants in breast tissue, with 65% of coding and noncoding expressed genes displaying DAE (daeGenes). We identified over 54 K daeQTLs for 6761 (26%) daeGenes, including 385 daeGenes harbouring variants previously associated with BC risk. We found 1431 daeQTLs mapped to 93 different loci in strong linkage disequilibrium with risk-associated variants (risk-daeQTLs), suggesting a link between risk-causing variants and cis-regulation. There were 122 risk-daeQTL with stronger cis-acting potential in active regulatory regions with protein binding evidence. These variants mapped to 41 risk loci, of which 29 had no previous report of target genes and were candidates for regulating the expression levels of 65 genes. As validation, we identified and functionally characterised five candidate causal variants at the 5q14.1 risk locus targeting the ATG10 and ATP6AP1L genes, likely acting via modulation of alternative transcription and transcription factor binding. Our study demonstrates the power of DAE analysis and daeQTL mapping to identify causal regulatory variants and target genes at breast cancer risk loci, including those with complex regulatory landscapes. It additionally provides a genome-wide resource of variants associated with DAE for future functional studies.

Mechanisms of transcriptional regulation in Anopheles gambiae revealed by allele-specific expression

Malaria control relies on insecticides targeting the mosquito vector, but this is increasingly compromised by insecticide resistance, which can be achieved by elevated expression of detoxifying enzymes that metabolize the insecticide. In diploid organisms, gene expression is regulated both in cis, by regulatory sequences on the same chromosome, and by trans acting factors, affecting both alleles equally. Differing levels of transcription can be caused by mutations in cis-regulatory modules (CRM), but few of these have been identified in mosquitoes. We crossed bendiocarb-resistant and susceptible Anopheles gambiae strains to identify cis-regulated genes that might be responsible for the resistant phenotype using RNAseq, and CRM sequences controlling gene expression in insecticide resistance relevant tissues were predicted using machine learning. We found 115 genes showing allele-specific expression (ASE) in hybrids of insecticide susceptible and resistant strains, suggesting cis-regulation is an important mechanism of gene expression regulation in A. gambiae. The genes showing ASE included a higher proportion of Anopheles-specific genes on average younger than genes with balanced allelic expression.

Germline allelic expression of genes at 17q22 locus associates with risk of breast cancer

INTRODUCTION

Translation of genome-wide association study (GWAS) findings into preventive approaches is challenged by the identification of the causal risk variants and the understanding of the biological mechanisms by which they act. We present using allelic expression (AE) ratios to perform quantitative case-control analysis as a novel approach to identify risk associations, causal regulatory variants, and target genes.

METHODS

Using the breast cancer (BC) risk locus 17q22 to validate this approach, we measured AE ratios in normal breast tissue samples from controls and cases, as well as from unmatched blood samples. Then we used in-silico and in-vitro analysis to map and functionally characterised candidate causal variants.

RESULTS

We found a significant shift in the AE patterns of STXBP4 (rs2628315) and COX11 (rs17817901) in the normal breast tissue of cases and healthy controls. Preferential expression of the G-rs2628315 and A-rs17817901 alleles, more often observed in cases, was associated with an increased risk for BC. Analysis of blood samples from cases and controls found a similar association. Furthermore, we identified two putative cis-regulatory variants - rs17817901 and rs8066588 - that affect a miRNA and a transcription factor binding site, respectively.

CONCLUSION

We propose causal variants and target genes for the 17q22 BC risk locus and show that using AE ratios in case-control association studies is helpful in identifying risk and mapping causal variants.

Allelic expression imbalance of PIK3CA mutations is frequent in breast cancer and prognostically significant

PIK3CA mutations are the most common in breast cancer, particularly in the estrogen receptor-positive cohort, but the benefit of PI3K inhibitors has had limited success compared with approaches targeting other less common mutations. We found a frequent allelic expression imbalance between the missense mutant and wild-type PIK3CA alleles in breast tumors from the METABRIC (70.2%) and the TCGA (60.1%) projects. When considering the mechanisms controlling allelic expression, 27.7% and 11.8% of tumors showed imbalance due to regulatory variants in cis, in the two studies respectively. Furthermore, preferential expression of the mutant allele due to cis-regulatory variation is associated with poor prognosis in the METABRIC tumors (P = 0.031). Interestingly, ER-, PR-, and HER2+ tumors showed significant preferential expression of the mutated allele in both datasets. Our work provides compelling evidence to support the clinical utility of PIK3CA allelic expression in breast cancer in identifying patients of poorer prognosis, and those with low expression of the mutated allele, who will unlikely benefit from PI3K inhibitors. Furthermore, our work proposes a model of differential regulation of a critical cancer-promoting gene in breast cancer.

Allelic imbalance of HLA-B expression in human lung cells infected with coronavirus and other respiratory viruses

The human leucocyte antigen (HLA) loci have been widely characterized to be associated with viral infectious diseases using either HLA allele frequency-based association or in silico predicted studies. However, there is less experimental evidence to link the HLA alleles with COVID-19 and other respiratory infectious diseases, particularly in the lung cells. To examine the role of HLA alleles in response to coronavirus and other respiratory viral infections in disease-relevant cells, we designed a two-stage study by integrating publicly accessible RNA-seq data sets, and performed allelic expression (AE) analysis on heterozygous HLA genotypes. We discovered an increased AE pattern accompanied with overexpression of HLA-B gene in SARS-CoV-2-infected human lung epithelial cells. Analysis of independent data sets verified the respiratory virus-induced AE of HLA-B gene in lung cells and tissues. The results were further experimentally validated in cultured lung cells infected with SARS-CoV-2. We further uncovered that the antiviral cytokine IFNβ contribute to AE of the HLA-B gene in lung cells. Our analyses provide a new insight into allelic influence on the HLA expression in association with SARS-CoV-2 and other common viral infectious diseases.

STAT3-mediated allelic imbalance of novel genetic variant Rs1047643 and B-cell-specific super-enhancer in association with systemic lupus erythematosus

Mapping of allelic imbalance (AI) at heterozygous loci has the potential to establish links between genetic risk for disease and biological function. Leveraging multi-omics data for AI analysis and functional annotation, we discovered a novel functional risk variant rs1047643 at 8p23 in association with systemic lupus erythematosus (SLE). This variant displays dynamic AI of chromatin accessibility and allelic expression on FDFT1 gene in B cells with SLE. We further found a B-cell restricted super-enhancer (SE) that physically contacts with this SNP-residing locus, an interaction that also appears specifically in B cells. Quantitative analysis of chromatin accessibility and DNA methylation profiles further demonstrated that the SE exhibits aberrant activity in B cell development with SLE. Functional studies identified that STAT3, a master factor associated with autoimmune diseases, directly regulates both the AI of risk variant and the activity of SE in cultured B cells. Our study reveals that STAT3-mediated SE activity and cis-regulatory effects of SNP rs1047643 at 8p23 locus are associated with B cell deregulation in SLE.

Genome-Wide Allele-Specific Expression in Obligately Asexual Daphnia pulex and the Implications for the Genetic Basis of Asexuality

Although obligately asexual lineages are thought to experience selective disadvantages associated with reduced efficiency of fixing beneficial mutations and purging deleterious mutations, such lineages are phylogenetically and geographically widespread. However, despite several genome-wide association studies, little is known about the genetic elements underlying the origin of obligate asexuality and how they spread. Because many obligately asexual lineages have hybrid origins, it has been suggested that asexuality is caused by the unbalanced expression of alleles from the hybridizing species. Here, we investigate this idea by identifying genes with allele-specific expression (ASE) in a Daphnia pulex population, in which obligate parthenogens (OP) and cyclical parthenogens (CP) coexist, with the OP clones having been originally derived from hybridization between CP D. pulex and its sister species, Daphnia pulicaria. OP D. pulex have significantly more ASE genes (ASEGs) than do CP D. pulex. Whole-genomic comparison of OP and CP clones revealed ∼15,000 OP-specific markers and 42 consistent ASEGs enriched in marker-defined regions. Ten of the 42 ASEGs have alleles coding for different protein sequences, suggesting functional differences between the products of the two parental alleles. At least three of these ten genes appear to be directly involved in meiosis-related processes, for example, RanBP2 can cause abnormal chromosome segregation in anaphase I, and the presence of Wee1 in immature oocytes leads to failure to enter meiosis II. These results provide a guide for future molecular resolution of the genetic basis of the transition to ameiotic parthenogenesis.

Optimization of intracellular macromolecule delivery by nanoparticle-mediated photoporation

Nanoparticle-mediated photoporation is a novel delivery platform for intracellular molecule delivery. We studied the dependence of macromolecular delivery on molecular weight and sought to enhance delivery efficiency. DU145 prostate cancer cells were exposed to pulsed laser beam in the presence of carbon-black nanoparticles. Intracellular uptake of molecules decreased with increasing molecular weight. Attributing this dependence to molecular diffusivity, we hypothesized that macromolecular delivery efficiency could be enhanced by increasing either laser fluence or laser exposure duration at low fluence. We observed increased percentages of macromolecule uptake by cells in both cases. However, trade-off between cell uptake and viability loss was most favorable at low laser fluence (25-29 mJ/cm²) and longer exposure durations (4-5 min). We conclude that long exposure at low laser fluence optimizes intracellular macromolecule delivery by nanoparticle-mediated photoporation, which may be explained by longer time for macromolecules to diffuse into cells, during and between laser pulses.

Detecting cell-type-specific allelic expression imbalance by integrative analysis of bulk and single-cell RNA sequencing data

Allelic expression imbalance (AEI), quantified by the relative expression of two alleles of a gene in a diploid organism, can help explain phenotypic variations among individuals. Traditional methods detect AEI using bulk RNA sequencing (RNA-seq) data, a data type that averages out cell-to-cell heterogeneity in gene expression across cell types. Since the patterns of AEI may vary across different cell types, it is desirable to study AEI in a cell-type-specific manner. Although this can be achieved by single-cell RNA sequencing (scRNA-seq), it requires full-length transcript to be sequenced in single cells of a large number of individuals, which are still cost prohibitive to generate. To overcome this limitation and utilize the vast amount of existing disease relevant bulk tissue RNA-seq data, we developed BSCET, which enables the characterization of cell-type-specific AEI in bulk RNA-seq data by integrating cell type composition information inferred from a small set of scRNA-seq samples, possibly obtained from an external dataset. By modeling covariate effect, BSCET can also detect genes whose cell-type-specific AEI are associated with clinical factors. Through extensive benchmark evaluations, we show that BSCET correctly detected genes with cell-type-specific AEI and differential AEI between healthy and diseased samples using bulk RNA-seq data. BSCET also uncovered cell-type-specific AEIs that were missed in bulk data analysis when the directions of AEI are opposite in different cell types. We further applied BSCET to two pancreatic islet bulk RNA-seq datasets, and detected genes showing cell-type-specific AEI that are related to the progression of type 2 diabetes. Since bulk RNA-seq data are easily accessible, BSCET provides a convenient tool to integrate information from scRNA-seq data to gain insight on AEI with cell type resolution. Results from such analysis will advance our understanding of cell type contributions in human diseases.

Detection of allelic expression imbalance (AEI), a phenomenon where the two alleles of a gene differ in their expression magnitude, is a key step towards the understanding of phenotypic variations among individuals. Existing methods detect AEI using bulk RNA sequencing (RNA-seq) data and ignore AEI variations among different cell types. Although single-cell RNA sequencing (scRNA-seq) has enabled the characterization of cell-to-cell heterogeneity in gene expression, the high costs have limited its application in AEI analysis. To overcome this limitation, we developed BSCET to characterize cell-type-specific AEI using the widely available bulk RNA-seq data by integrating cell-type composition information inferred from scRNA-seq samples. Since the degree of AEI may vary with disease phenotypes, we further extended BSCET to detect genes whose cell-type-specific AEIs are associated with clinical factors. Through extensive benchmark evaluations and analyses of two pancreatic islet bulk RNA-seq datasets, we demonstrated BSCET’s ability to refine bulk-level AEI to cell-type resolution, and to identify genes whose cell-type-specific AEIs are associated with the progression of type 2 diabetes. With the vast amount of easily accessible bulk RNA-seq data, we believe BSCET will be a valuable tool for elucidating cell type contributions in human diseases.

Unravelling the complex genetics of common kidney diseases: from variants to mechanisms

Genome-wide association studies (GWAS) have identified hundreds of loci associated with kidney-related traits such as glomerular filtration rate, albuminuria, hypertension, electrolyte and metabolite levels. However, these impressive, large-scale mapping approaches have not always translated into an improved understanding of disease or development of novel therapeutics. GWAS have several important limitations. Nearly all disease-associated risk loci are located in the non-coding region of the genome and therefore, their target genes, affected cell types and regulatory mechanisms remain unknown. Genome-scale approaches can be used to identify associations between DNA sequence variants and changes in gene expression (quantified through bulk and single-cell methods), gene regulation and other molecular quantitative trait studies, such as chromatin accessibility, DNA methylation, protein expression and metabolite levels. Data obtained through these approaches, used in combination with robust computational methods, can deliver robust mechanistic inferences for translational exploitation. Understanding the genetic basis of common kidney diseases means having a comprehensive picture of the genes that have a causal role in disease development and progression, of the cells, tissues and organs in which these genes act to affect the disease, of the cellular pathways and mechanisms that drive disease, and of potential targets for disease prevention, detection and therapy.

Cytomorphologic features of thyroid disease in patients with DICER1 mutations: A report of cytology-histopathology correlation in 7 patients

BACKGROUND

Germline and somatic mutations of DICER1 have been identified in various types of neoplastic lesions, with germline DICER1 mutation being linked to autosomal dominant hereditary pleiotropic tumor syndrome (DICER1 syndrome). Patients with DICER1 syndrome are at increased risk of developing thyroid disease, including thyroid cancer. The goal of this study was to identify diagnostic cytologic features in thyroid fine-needle aspiration (FNA) samples from patients with DICER1 mutation.

METHODS

Cytology cases of thyroid FNA from 7 patients with DICER1 mutation were identified. Clinical, imaging, cytomorphologic, and molecular data were analyzed.

RESULTS

Cytologic preparations from reviewed cases showed thyroid lesions of follicular derivation with scant colloid, moderate cellularity, uniform follicular cells with round nuclei and inconspicuous nucleoli arranged in small crowded groups and microfollicles. Follicular neoplasm was diagnosed in 4 cases and follicular lesion of undetermined significance in 3 cases, based on the Bethesda System for Reporting Thyroid Cytopathology. Histopathological analysis of thyroid tissue confirmed neoplastic process in 6 out of 7 cases: follicular carcinoma (FC, 3 cases), papillary thyroid carcinoma (2 cases), poorly differentiated thyroid carcinoma (PDTC, 1 case). Genetic studies identified 3 different somatic variants of DICER1 gene, including transcript consequence c.5428G>T, which was detected in FC and PDTC (and has been described previously in multinodular goiter).

CONCLUSION

DICER1 mutation in all analyzed patients was identified as a result of thyroid FNA evaluation, emphasizing the critical role of FNA in the screening of patients with thyroid nodules, proper diagnosis of thyroid disease, and monitoring of patients with DICER1 mutation.

Epigenetic Regulation of Alternative mRNA Splicing in Dilated Cardiomyopathy

In recent years, the genetic architecture of dilated cardiomyopathy (DCM) has been more thoroughly elucidated. However, there is still insufficient knowledge on the modifiers and regulatory principles that lead to the failure of myocardial function. The current study investigates the association of epigenome-wide DNA methylation and alternative splicing, both of which are important regulatory principles in DCM. We analyzed screening and replication cohorts of cases and controls and identified distinct transcriptomic patterns in the myocardium that differ significantly, and we identified a strong association of intronic DNA methylation and flanking exons usage (p < 2 × 10^-16). By combining differential exon usage (DEU) and differential methylation regions (DMR), we found a significant change of regulation in important sarcomeric and other DCM-associated pathways. Interestingly, inverse regulation of Titin antisense non-coding RNA transcript splicing and DNA methylation of a locus reciprocal to TTN substantiate these findings and indicate an additional role for non-protein-coding transcripts. In summary, this study highlights for the first time the close interrelationship between genetic imprinting by DNA methylation and the transport of this epigenetic information towards the dynamic mRNA splicing landscape. This expands our knowledge of the genome-environment interaction in DCM besides simple gene expression regulation.

Allele-specific miRNA-binding analysis identifies candidate target genes for breast cancer risk

Most breast cancer (BC) risk-associated single-nucleotide polymorphisms (raSNPs) identified in genome-wide association studies (GWAS) are believed to cis-regulate the expression of genes. We hypothesise that cis-regulatory variants contributing to disease risk may be affecting microRNA (miRNA) genes and/or miRNA binding. To test this, we adapted two miRNA-binding prediction algorithms-TargetScan and miRanda-to perform allele-specific queries, and integrated differential allelic expression (DAE) and expression quantitative trait loci (eQTL) data, to query 150 genome-wide significant ( P ≤ 5 × 10 - 8 ) raSNPs, plus proxies. We found that no raSNP mapped to a miRNA gene, suggesting that altered miRNA targeting is an unlikely mechanism involved in BC risk. Also, 11.5% (6 out of 52) raSNPs located in 3'-untranslated regions of putative miRNA target genes were predicted to alter miRNA::mRNA (messenger RNA) pair binding stability in five candidate target genes. Of these, we propose RNF115, at locus 1q21.1, as a strong novel target gene associated with BC risk, and reinforce the role of miRNA-mediated cis-regulation at locus 19p13.11. We believe that integrating allele-specific querying in miRNA-binding prediction, and data supporting cis-regulation of expression, improves the identification of candidate target genes in BC risk, as well as in other common cancers and complex diseases.

Tumor suppressor genes and allele-specific expression: mechanisms and significance

Recent findings indicate that allele-specific expression (ASE) at specific cancer driver gene loci may be of importance in onset/progression of the disease. Of particular interest are loss-of-function (LOF) of tumor suppressor gene (TSGs) alleles. While LOF tumor suppressor mutations are typically considered to be recessive, if these mutant alleles can be significantly differentially expressed relative to wild-type alleles in heterozygotes, the clinical consequences could be significant. LOF TSG alleles are shown to be segregating at high frequencies in world-wide populations of normal/healthy individuals. Matched sets of normal and tumor tissues isolated from 233 cancer patients representing four diverse tumor types demonstrate functionally important changes in patterns of ASE in individuals heterozygous for LOF TSG alleles associated with cancer onset/progression. While a variety of molecular mechanisms were identified as potentially contributing to changes in ASE patterns in cancer, changes in DNA copy number and allele-specific alternative splicing possibly mediated by antisense RNA emerged as predominant factors. In conclusion, LOF TSGs are segregating in human populations at significant frequencies indicating that many otherwise healthy individuals are at elevated risk of developing cancer. Changes in ASE between normal and cancer tissues indicates that LOF TSG alleles may contribute to cancer onset/progression even when heterozygous with wild-type functional alleles.

Resilience in reef-building corals: The ecological and evolutionary importance of the host response to thermal stress

Coral reefs are under extreme threat due to a number of stressors, but temperature increases due to changing climate are the most severe. Rising ocean temperatures coupled with local extremes lead to extensive bleaching, where the coral-algal symbiosis breaks down and corals may die, compromising the structure and function of reefs. Although the symbiotic nature of the coral colony has historically been a focus of research on coral resilience, the host itself is a foundational component in the response to thermal stress. Fixed effects in the coral host set trait baselines through evolutionary processes, acting on many loci of small effect to create mosaics of thermal tolerance across latitudes and individual coral reefs. These genomic differences can be strongly heritable, producing wide variation among clones of different genotypes or families of a specific larval cross. Phenotypic plasticity is overlaid on these baselines and a growing body of knowledge demonstrates the potential for acclimatization of reef-building corals through a variety of mechanisms that promote resilience and stress tolerance. The long-term persistence of coral reefs will require many of these mechanisms to adjust to warmer temperatures within a generation, bridging the gap to reproductive events that allow recombination of standing diversity and adaptive change. Business-as-usual climate scenarios will probably lead to the loss of some coral populations or species in the future, so the interaction between intragenerational effects and evolutionary pressure is critical for the survival of reefs.

Leveraging allelic imbalance to refine fine-mapping for eQTL studies

Many disease risk loci identified in genome-wide association studies are present in non-coding regions of the genome. Previous studies have found enrichment of expression quantitative trait loci (eQTLs) in disease risk loci, indicating that identifying causal variants for gene expression is important for elucidating the genetic basis of not only gene expression but also complex traits. However, detecting causal variants is challenging due to complex genetic correlation among variants known as linkage disequilibrium (LD) and the presence of multiple causal variants within a locus. Although several fine-mapping approaches have been developed to overcome these challenges, they may produce large sets of putative causal variants when true causal variants are in high LD with many non-causal variants. In eQTL studies, there is an additional source of information that can be used to improve fine-mapping called allelic imbalance (AIM) that measures imbalance in gene expression on two chromosomes of a diploid organism. In this work, we develop a novel statistical method that leverages both AIM and total expression data to detect causal variants that regulate gene expression. We illustrate through simulations and application to 10 tissues of the Genotype-Tissue Expression (GTEx) dataset that our method identifies the true causal variants with higher specificity than an approach that uses only eQTL information. Across all tissues and genes, our method achieves a median reduction rate of 11% in the number of putative causal variants. We use chromatin state data from the Roadmap Epigenomics Consortium to show that the putative causal variants identified by our method are enriched for active regions of the genome, providing orthogonal support that our method identifies causal variants with increased specificity.

In recent years, many studies have identified genetic variants that are associated with the expression of genes (eQTLs). While thousands of eQTLs have been identified, not all associated variants cause changes in gene expression. This is in part due to the complex patterns of genetic correlation in the human genome. If a region of the genome contains many genetic variants that are highly correlated with each other, non-causal genetic variants close to a causal variant are also correlated with gene expression. Statistical fine-mapping is the process of identifying true causal variants from a set of candidate variants. In regions with high genetic correlation, previous fine-mapping methods may not be able to differentiate causal variants from nearby variants. We propose a method that utilizes a complementary source of information called allelic imbalance (AIM). We show that by combining eQTL and AIM data, we can identify the true causal variants more efficiently and substantially decrease the number of putative causal variants for downstream analysis.

Genetics and Extracellular Vesicles of Pediatrics Sleep Disordered Breathing and Epilepsy

Sleep remains one of the least understood phenomena in biology, and sleep disturbances are one of the most common behavioral problems in childhood. The etiology of sleep disorders is complex and involves both genetic and environmental factors. Epilepsy is the most popular childhood neurological condition and is characterized by an enduring predisposition to generate epileptic seizures, and the neurobiological, cognitive, psychological, and social consequences of this condition. Sleep and epilepsy are interrelated, and the importance of sleep in epilepsy is less known. The state of sleep also influences whether a seizure will occur at a given time, and this differs considerably for various epilepsy syndromes. The development of epilepsy has been associated with single or multiple gene variants. The genetics of epilepsy is complex and disorders exhibit significant genetic heterogeneity and variability in the expressivity of seizures. Phenobarbital (PhB) is the most widely used antiepileptic drug. With its principal mechanism of action to prolong the opening time of the γ-aminobutyric acid (GABA)-A receptor-associated chloride channel, it enhances chloride anion influx into neurons, with subsequent hyperpolarization, thereby reducing excitability. Enzymes that metabolize pharmaceuticals including PhB are well known for having genetic polymorphisms that contribute to adverse drug–drug interactions. PhB metabolism is highly dependent upon the cytochrome P450 (CYP450) and genetic polymorphisms can lead to variability in active drug levels. The highly polymorphic CYP2C19 isozymes are responsible for metabolizing a large portion of routinely prescribed drugs and variants contribute significantly to adverse drug reactions and therapeutic failures. A limited number of CYP2C19 single nucleotide polymorphisms (SNPs) are involved in drug metabolism. Extracellular vesicles (EVs) are circular membrane fragments released from the endosomal compartment as exosomes are shed from the surfaces of the membranes of most cell types. Increasing evidence indicated that EVs play a pivotal role in cell-to-cell communication. Theses EVs may play an important role between sleep, epilepsy, and treatments. The discovery of exosomes provides potential strategies for the diagnosis and treatment of many diseases including neurocognitive deficit. The aim of this study is to better understand and provide further knowledge about the metabolism and interactions between phenobarbital and CYP2C19 polymorphisms in children with epilepsy, interplay between sleep, and EVs. Understanding this interplay between epilepsy and sleep is helpful in the optimal treatment of all patients with epileptic seizures. The use of genetics and extracellular vesicles as precision medicine for the diagnosis and treatment of children with sleep disorder will improve the prognosis and the quality of life in patients with epilepsy.

Advances of Molecular Markers and Their Application for Body Variables and Carcass Traits in Qinchuan Cattle

This review considers the unique characteristics of Chinese cattle and intramuscular fat content (IMF) as factors influencing meat quality, including tenderness, flavor, and juiciness of meat. Due to its nutritional qualities, meat contributes to a healthy and balanced diet. The intramuscular fat content and eating quality of beef are influenced by many factors, which can generally be divided into on-farm and pre-slaughter factors (breed, sex of cattle, age at slaughter, housing system, diet, and pre-slaughter handling) and postmortem factors (post-slaughter processing, chilling temperature, and packaging). Meat quality traits can also be influenced by the individual genetic background of the animal. Worldwide, the function of genes and genetic polymorphisms that have potential effects on fattening of cattle and beef quality have been investigated. The use of DNA markers is recognized as a powerful and efficient approach to achieve genetic gain for desirable phenotypic characteristics, which is helpful for economic growth. The polymorphisms of the SIRT4, SIRT6, SIRT7, CRTC3, ABHD5, KLF6, H-FABP, and ELOVL6 genes for body and growth characteristics of cattle, and also for beef quality, are considered with the aim of highlighting the significance of beef intramuscular fat content, and that growth, body, and meat quality characteristics are polygenically regulated.

Sex-specific effects of a microsatellite polymorphism on human growth hormone receptor gene expression

Growth hormone (GH) binds to its specific receptor (GHR) at the surface of target cells activating multiple signaling pathways implicated in growth and metabolism. Dysregulation of GHRs leads to pathophysiological states that most commonly affect stature. We previously showed the association of a polymorphic (n = 15-37) GT microsatellite in the human GHR gene promoter with short stature in a sex-specific manner. In the present study we evaluated the functional relevance of this polymorphism in regulating GHR expression. Using luciferase reporter assays, we found that the GT repeat had a significant cis regulatory effect in response to HIF1α and a potential repressor role following C/EBPβ stimulation. Using a digital PCR application to measure allelic imbalance (AI), we showed a high prevalence of AI (∼76%) at the GHR locus in lymphoblastoid cell lines (LCLs), with a significantly higher degree of imbalance in LCLs derived from males. Examination of expression of GHR as well as other members of the GH-IGF1 axis in the LCLs revealed significant associations of GHR, IGF1 and BCL2 expression with GT genotype in a sex-specific manner. Our results suggest that this GT microsatellite exerts both cis and trans effects in a sex-specific context, revealing a new mechanism by which GHR gene expression is regulated.

Genetic variants in the SIRT6 transcriptional regulatory region affect gene activity and carcass quality traits in indigenous Chinese beef cattle (Bos taurus)

Background

The aim of this study was to analyze potential influences of polymorphisms within the regulatory region of the bovine SIRT6 gene on carcass quality traits. Expression analyses suggested that SIRT6 gene is predominately expressed in kidney, compared with other tissues. In 535 indigenous Chinese beef cattle, two novel single nucleotide polymorphisms (SNPs) were identified within the promoter region of the SIRT6 gene.

Results

Association analysis indicated that G allele of the c.-1100 A > G had a positive effect on fat deposition, and the Hap4/4 diplotype had more favourable results than other dipoltypes with respect to the evaluation of carcass quality traits. Furthermore, promoter activity associated with the Hap3 haplotype was measured at higher levels than the Hap1 haplotype, which would be in agreement with the previously described association analysis.

Conclusion

The SIRT6 promoter variants significantly affect transcriptional levels and subsequently significantly influence bovine intramscular fat content.

NRF1 and ZSCAN10 bind to the promoter region of the SIX1 gene and their effects body measurements in Qinchuan cattle

The SIX1 homeobox gene belongs to the six homeodomain family and is widely thought to play a principal role in mediating of skeletal muscle development. In the present study, we determined that the bovine SIX1 gene was highly expressed in the longissimus thoracis and physiologically immature individuals. DNA sequencing of 428 individual Qinchuan cattle identified nine single nucleotide polymorphisms (SNPs) in the promoter region of the SIX1 gene. Using a series of 5′ deletion promoter plasmid luciferase reporter assays and 5′-rapid amplification of cDNA end analysis (RACE), two of these SNPs were found to be located in the proximal minimal promoter region −216/−28 relative to the transcriptional start site (TSS). Correlation analysis showed the combined haplotypes H₁-H₂ (-GG-GA-) was significantly greater in the body measurement traits (BMTs) than the others, which was consistent with the results showing that the transcriptional activity of Hap2 was higher than the others in Qinchuan cattle myoblast cells. Furthermore, the electrophoretic mobility shift assays (EMSA) and chromatin immunoprecipitation assay (ChIP) demonstrated that NRF1 and ZSCAN10 binding occurred in the promoter region of diplotypes H₁-H₂ to regulate SIX1 transcriptional activity. This information may be useful for molecular marker-assisted selection (MAS) in cattle breeding.

Novel risk genes for systemic lupus erythematosus predicted by random forest classification

Genome-wide association studies have identified risk loci for SLE, but a large proportion of the genetic contribution to SLE still remains unexplained. To detect novel risk genes, and to predict an individual's SLE risk we designed a random forest classifier using SNP genotype data generated on the "Immunochip" from 1,160 patients with SLE and 2,711 controls. Using gene importance scores defined by the random forest classifier, we identified 15 potential novel risk genes for SLE. Of them 12 are associated with other autoimmune diseases than SLE, whereas three genes (ZNF804A, CDK1, and MANF) have not previously been associated with autoimmunity. Random forest classification also allowed prediction of patients at risk for lupus nephritis with an area under the curve of 0.94. By allele-specific gene expression analysis we detected cis-regulatory SNPs that affect the expression levels of six of the top 40 genes designed by the random forest analysis, indicating a regulatory role for the identified risk variants. The 40 top genes from the prediction were overrepresented for differential expression in B and T cells according to RNA-sequencing of samples from five healthy donors, with more frequent over-expression in B cells compared to T cells.

Genetic-epigenetic interactions in cis: a major focus in the post-GWAS era

Studies on genetic-epigenetic interactions, including the mapping of methylation quantitative trait loci (mQTLs) and haplotype-dependent allele-specific DNA methylation (hap-ASM), have become a major focus in the post-genome-wide-association-study (GWAS) era. Such maps can nominate regulatory sequence variants that underlie GWAS signals for common diseases, ranging from neuropsychiatric disorders to cancers. Conversely, mQTLs need to be filtered out when searching for non-genetic effects in epigenome-wide association studies (EWAS). Sequence variants in CCCTC-binding factor (CTCF) and transcription factor binding sites have been mechanistically linked to mQTLs and hap-ASM. Identifying these sites can point to disease-associated transcriptional pathways, with implications for targeted treatment and prevention.

Regulatory Single-Nucleotide Variant Predictor Increases Predictive Performance of Functional Regulatory Variants

In silico methods for detecting functionally relevant genetic variants are important for identifying genetic markers of human inherited disease. Much research has focused on protein-coding variants since coding regions have well-defined physicochemical and functional properties. However, many bioinformatics tools are not applicable to variants outside coding regions. Here, we increase the classification performance of our regulatory single-nucleotide variant predictor (RSVP) for variants that cause regulatory abnormalities from an AUC of 0.90-0.97 by incorporating genomic regions identified by the ENCODE project into RSVP. RSVP is comparable to a recently published tool, Genome-Wide Annotation of Variants (GWAVA); both RSVP and GWAVA perform better on regulatory variants than a traditional variant predictor, combined annotation-dependent depletion (CADD). However, our method outperforms GWAVA on variants located at similar distances to the transcription start site as the positive set (AUC: 0.96) as compared with GWAVA (AUC: 0.71). Much of this disparity is due to RSVP's incorporation of features pertaining to the nearest gene (expression, GO terms, etc.), which are not included in GWAVA. Our findings hold out the promise of a framework for the assessment of all functional regulatory variants, providing a means to predict which rare or de novo variants are of pathogenic significance.

The abundance of cis-acting loci leading to differential allele expression in F1 mice and their relationship to loci harboring genes affecting complex traits

Background

Genome-wide surveys have detected cis-acting quantitative trait loci altering levels of RNA transcripts (RNA-eQTLs) by associating SNV alleles to transcript levels. However, the sensitivity and specificity of detection of cis- expression quantitative trait loci (eQTLs) by genetic approaches, reliant as it is on measurements of transcript levels in recombinant inbred strains or offspring from arranged crosses, is unknown, as is their relationship to QTL’s for complex phenotypes.

Results

We used transcriptome-wide differential allele expression (DAE) to detect cis-eQTLs in forebrain and kidney from reciprocal crosses between three mouse inbred strains, 129S1/SvlmJ, DBA/2J, and CAST/EiJ and C57BL/6 J. Two of these crosses were previously characterized for cis-eQTLs and QTLs for various complex phenotypes by genetic analysis of recombinant inbred (RI) strains. 5.4 %, 1.9 % and 1.5 % of genes assayed in forebrain of B6/129SF1, B6/DBAF1, and B6/CASTF1 mice, respectively, showed differential allelic expression, indicative of cis-acting alleles at these genes. Moreover, the majority of DAE QTLs were observed to be tissue-specific with only a small fraction showing cis-effects in both tissues. Comparing DAE QTLs in F1 mice to cis-eQTLs previously mapped in RI strains we observed that many of the cis-eQTLs were not confirmed by DAE. Additionally several novel DAE-QTLs not identified as cis-eQTLs were identified suggesting that there are differences in sensitivity and specificity for QTL detection between the two methodologies. Strain specific DAE QTLs in B6/DBAF1 mice were located in excess at candidate genes for alcohol use disorders, seizures, and angiogenesis previously implicated by genetic linkage in C57BL/6J × DBA/2JF2 mice or BXD RI strains.

Conclusions

Via a survey for differential allele expression in F1 mice, a substantial proportion of genes were found to have alleles altering expression in cis-acting fashion. Comparing forebrain and kidney, many or most of these alleles were tissue-specific in action. The identification of strain specific DAE QTLs, can assist in assessment of candidate genes located within the large intervals associated with trait QTLs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2922-9) contains supplementary material, which is available to authorized users.

Allele-Specific Transcriptome and Methylome Analysis Reveals Stable Inheritance and Cis-Regulation of DNA Methylation in Nasonia

Gene expression divergence between closely related species could be attributed to both cis- and trans- DNA sequence changes during evolution, but it is unclear how the evolutionary dynamics of epigenetic marks are regulated. In eutherian mammals, biparental DNA methylation marks are erased and reset during gametogenesis, resulting in paternal or maternal imprints, which lead to genomic imprinting. Whether DNA methylation reprogramming exists in insects is not known. Wasps of the genus Nasonia are non-social parasitoids that are emerging as a model for studies of epigenetic processes in insects. In this study, we quantified allele-specific expression and methylation genome-wide in Nasonia vitripennis and Nasonia giraulti and their reciprocal F1 hybrids. No parent-of-origin effect in allelic expression was found for >8,000 covered genes, suggesting a lack of genomic imprinting in adult Nasonia. As we expected, both significant cis- and trans- effects are responsible for the expression divergence between N. vitripennis and N. giraulti. Surprisingly, all 178 differentially methylated genes are also differentially methylated between the two alleles in F1 hybrid offspring, recapitulating the parental methylation status with nearly 100% fidelity, indicating the presence of strong cis-elements driving the target of gene body methylation. In addition, we discovered that total and allele-specific expression are positively correlated with allele-specific methylation in a subset of the differentially methylated genes. The 100% cis-regulation in F1 hybrids suggests the methylation machinery is conserved and DNA methylation is targeted by cis features in Nasonia. The lack of genomic imprinting and parent-of-origin differentially methylated regions in Nasonia, together with the stable inheritance of methylation status between generations, suggests either a cis-regulatory motif for methylation at the DNA level or highly stable inheritance of an epigenetic signal in Nasonia.

RNA-sequencing and whole-genome bisulfite sequencing in the hybrid offspring of two Nasonia parasitoid wasp species revealed strong cis-regulation of methylation and allele-specific expression. No gene was found to display genomic imprinting.

The relationship between methylation of genomic DNA and expression of the genes that it encodes—and how this relationship changes during evolution—has been widely studied in mammals, but remains less well understood for insects. Here we analyze the expressed mRNA transcripts and genomic DNA methylation of the hybrid offspring of a pair of Nasonia parasitoid wasp species, producing a wealth of information about the regulation of gene expression. We find that variation in DNA sequence impacts expression on the same strand (called “cis-regulation”), and that cytosine methylation state is also associated in cis with the regulatory consequences of this base alteration. We show that these wasp species lack differential expression dependent on parent-of-origin (called “genomic imprinting”), and that in the hybrids the alleles retain the methylation status of the parental species in a strong cis-regulated fashion. Transcript abundances were also largely driven in a cis-regulated manner, consistent with a correlation between methylation status and expression levels. Despite the many differences between Nasonia and mammals in the impact of genomic DNA methylation, in both groups the use of methylated cytosine has been co-opted in ways that help tune gene expression.

Allelic Imbalance in Regulation of ANRIL through Chromatin Interaction at 9p21 Endometriosis Risk Locus

Genome-wide association studies (GWASs) have discovered numerous single nucleotide polymorphisms (SNPs) associated with human complex disorders. However, functional characterization of the disease-associated SNPs remains a formidable challenge. Here we explored regulatory mechanism of a SNP on chromosome 9p21 associated with endometriosis by leveraging “allele-specific” functional genomic approaches. By re-sequencing 1.29 Mb of 9p21 region and scrutinizing DNase-seq data from the ENCODE project, we prioritized rs17761446 as a candidate functional variant that was in perfect linkage disequilibrium with the original GWAS SNP (rs10965235) and located on DNase I hypersensitive site. Chromosome conformation capture followed by high-throughput sequencing revealed that the protective G allele of rs17761446 exerted stronger chromatin interaction with ANRIL promoter. We demonstrated that the protective allele exhibited preferential binding affinities to TCF7L2 and EP300 by bioinformatics and chromatin immunoprecipitation (ChIP) analyses. ChIP assays for histone H3 lysine 27 acetylation and RNA polymerase II reinforced the enhancer activity of the SNP site. The allele specific expression analysis for eutopic endometrial tissues and endometrial carcinoma cell lines showed that rs17761446 was a cis-regulatory variant where G allele was associated with increased ANRIL expression. Our work illuminates the allelic imbalances in a series of transcriptional regulation from factor binding to gene expression mediated by chromatin interaction underlie the molecular mechanism of 9p21 endometriosis risk locus. Functional genomics on common disease will unlock functional aspect of genotype-phenotype correlations in the post-GWAS stage.

A large number of variants associated with human complex diseases have been discovered by genome-wide association studies (GWASs). These discoveries have been anticipated to be translated into the definitive understanding of disease pathogeneses; however, functional characterization of the disease-associated SNPs remains a formidable challenge. Here we explored regulatory mechanism of a variant on chromosome 9p21 associated with endometriosis, a common gynecological disorder. By scrutinizing linkage disequilibrium structure and DNase I hypersensitive sites across the risk locus, we prioritized rs17761446 as a candidate causal variant. The results of our “allele-specific” functional genomic approaches sheds light on regulatory mechanisms underlying 9p21 endometriosis risk locus, in which preferential bindings of TCF7L2 and its coactivator EP300 to the protective G allele of rs17761446 lead to stronger chromatin interaction with the promoter of ANRIL, which in turn activate transcription of the non-coding RNA. Motivated by the fact that TCF7L2 was a key transcription factor of Wnt signaling pathway, we postulated that the induction of Wnt signaling activated expression levels of ANRIL and cell cycle inhibitors, CDKN2A/2B. Functional genomics on common disease will unlock functional aspect of genotype-phenotype correlations in the post-GWAS stage.

The role of CD40 and CD40L in bone mineral density and in osteoporosis risk: A genetic and functional study

Compelling data are revealing that the CD40/CD40L system is involved in bone metabolism. Furthermore, we have previously demonstrated that polymorphisms in both genes are associated with bone phenotypes. The aim of this study is to further characterize this association and to identify the causal functional mechanism. We conducted an association study of BMD with 15 SNPs in CD40/CD40L genes in a population of 779 women. In addition, we assessed the functionality of this association through the study of the allele-dependent expression of CD40 and CD40L in peripheral blood leukocytes (PBLs) and in human osteoblasts (OBs) obtained from bone explants by qPCR and by sequencing. When an allelic imbalance (AI) was detected, studies on allele-dependent in vitro transcription rate and on CpG methylation in the gene promoter were also performed. Our results confirm the genetic association between SNP rs116535 (T>C) of CD40L gene with LS-BMD. Regarding CD40 gene, two SNPs showed nominal P-values<0.05 for FN- and LS-BMD (Z-scores), although the association was not significant after correcting for multiple testing. Homozygous TT women for SNP rs1883832 (C>T) of CD40 gene showed a trend to have lower levels of OPG (Q-value=0.059), especially when women of BMD-quartile ends were selected (P<0.05). Regarding functionality, we detected an AI for rs1883832 with the C allele the most expressed in OBs and in PBLs. Since the rs116535 of CD40L gene did not show AI, it was not further analyzed. Finally, we described a differential methylation of CpGs in the CD40 promoter among women of high in comparison to low BMD. Our results suggest that the CD40/CD40L system plays a role in regulating BMD. Effectively, our data suggest that a decreased production of OPG could be the cause of the lower BMD observed in TT women for rs1883832 of the CD40 gene and that the degree of methylation of CpGs in the CD40 promoter could contribute to the acquisition of BMD. One possibility that deserves further study is whether the degree of methylation of the CD40 gene affects the level of CD40 expression and, consequently, the level of OPG.

Novel Association of WNK4 Gene, Ala589Ser Polymorphism in Essential Hypertension, and Type 2 Diabetes Mellitus in Malaysia

With-no-lysine (K) Kinase-4 (WNK4) consisted of unique serine and threonine protein kinases, genetically associated with an autosomal dominant form of hypertension. Argumentative consequences have lately arisen on the association of specific single nucleotide polymorphisms of WNK4 gene and essential hypertension (EHT). The aim of this study was to determine the association of Ala589Ser polymorphism of WNK4 gene with essential hypertensive patients in Malaysia. WNK4 gene polymorphism was specified utilizing mutagenically separated polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP) method in 320 subjects including 163 cases and 157 controls. Close relation between Ala589Ser polymorphism and elevated systolic and diastolic blood pressure (SBP and DBP) was recognized. Sociodemographic factors including body mass index (BMI), age, the level of fasting blood sugar (FBS), low density lipoprotein (LDL), and triglyceride (TG) in the cases and healthy subjects exhibited strong differences (p < 0.05). The distribution of allele frequency and genotype of WNK4 gene Ala589Ser polymorphism showed significant differences (p < 0.05) between EHT subjects with or without type 2 diabetes mellitus (T2DM) and normotensive subjects, statistically. The WNK4 gene variation influences significantly blood pressure increase. Ala589Ser probably has effects on the enzymic activity leading to enhanced predisposition to the disorder.

Enhancer Runaway and the Evolution of Diploid Gene Expression

Evidence is mounting that the evolution of gene expression plays a major role in adaptation and speciation. Understanding the evolution of gene regulatory regions is indeed an essential step in linking genotypes and phenotypes and in understanding the molecular mechanisms underlying evolutionary change. The common view is that expression traits (protein folding, expression timing, tissue localization and concentration) are under natural selection at the individual level. Here, we use a theoretical approach to show that, in addition, in diploid organisms, enhancer strength (i.e., the ability of enhancers to activate transcription) may increase in a runaway process due to competition for expression between homologous enhancer alleles. These alleles may be viewed as self-promoting genetic elements, as they spread without conferring a benefit at the individual level. They gain a selective advantage by getting associated to better genetic backgrounds: deleterious mutations are more efficiently purged when linked to stronger enhancers. This process, which has been entirely overlooked so far, may help understand the observed overrepresentation of cis-acting regulatory changes in between-species phenotypic differences, and sheds a new light on investigating the contribution of gene expression evolution to adaptation.

With the advent of new sequencing technologies, the evolution of gene expression regulation is becoming a subject of intensive research. In this paper, we report an entirely new phenomenon acting on the evolution of gene regulatory sequences. We show that in a small genomic region around genes there is a selection pressure to increase expression, such that stronger enhancers are favored. This leads to an open-ended escalation of enhancer strength. This outcome is not a particular case and we expect it to occur for all genes in nearly all eukaryotic diploid organisms. We also show that this escalation is not stopped by stabilizing selection on expression profiles. Indeed, regulators may coevolve to maintain optimal phenotypes despite the enhancer strength escalation. This widespread phenomenon can significantly shift our understanding of gene regulatory regions and opens a wide array of possible tests.

Using next-generation RNA sequencing to identify imprinted genes

Genomic imprinting is manifested as differential allelic expression (DAE) depending on the parent-of-origin. The most direct way to identify imprinted genes is to directly score the DAE in a context where one can identify which parent transmitted each allele. Because many genes display DAE, simply scoring DAE in an individual is not sufficient to identify imprinted genes. In this paper, we outline many technical aspects of a scheme for identification of imprinted genes that makes use of RNA sequencing (RNA-seq) from tissues isolated from F1 offspring derived from the pair of reciprocal crosses. Ideally, the parental lines are from two inbred strains that are not closely related to each other. Aspects of tissue purity, RNA extraction, library preparation and bioinformatic inference of imprinting are all covered. These methods have already been applied in a number of organisms, and one of the most striking results is the evolutionary fluidity with which novel imprinted genes are gained and lost within genomes. The general methodology is also applicable to a wide range of other biological problems that require quantification of allele-specific expression using RNA-seq, such as cis-regulation of gene expression, X chromosome inactivation and random monoallelic expression.

Single nucleotide polymorphisms with cis-regulatory effects on long non-coding transcripts in human primary monocytes

We applied genome-wide allele-specific expression analysis of monocytes from 188 samples. Monocytes were purified from white blood cells of healthy blood donors to detect cis-acting genetic variation that regulates the expression of long non-coding RNAs. We analysed 8929 regions harboring genes for potential long non-coding RNA that were retrieved from data from the ENCODE project. Of these regions, 60% were annotated as intergenic, which implies that they do not overlap with protein-coding genes. Focusing on the intergenic regions, and using stringent analysis of the allele-specific expression data, we detected robust cis-regulatory SNPs in 258 out of 489 informative intergenic regions included in the analysis. The cis-regulatory SNPs that were significantly associated with allele-specific expression of long non-coding RNAs were enriched to enhancer regions marked for active or bivalent, poised chromatin by histone modifications. Out of the lncRNA regions regulated by cis-acting regulatory SNPs, 20% (n = 52) were co-regulated with the closest protein coding gene. We compared the identified cis-regulatory SNPs with those in the catalog of SNPs identified by genome-wide association studies of human diseases and traits. This comparison identified 32 SNPs in loci from genome-wide association studies that displayed a strong association signal with allele-specific expression of non-coding RNAs in monocytes, with p-values ranging from 6.7×10(-7) to 9.5×10(-89). The identified cis-regulatory SNPs are associated with diseases of the immune system, like multiple sclerosis and rheumatoid arthritis.

Evidence of allelic imbalance in the schizophrenia susceptibility gene ZNF804A in human dorsolateral prefrontal cortex

The rs1344706, an intronic SNP within the zinc-finger protein 804A gene (ZNF804A), was identified as one of the most compelling risk SNPs for schizophrenia (SZ) and bipolar disorder (BD). It is however not clear by which molecular mechanisms ZNF804A increases disease risk. We evaluated the role of ZNF804A in SZ and BD by genotyping the originally associated rs1344706 SNP and an exonic SNP (rs12476147) located in exon four of ZNF804A in a sample of 422 SZ, 382 BD, and 507 controls from the isolated population of the Costa Rica Central Valley. We also investigated the rs1344706 SNP for allelic specific expression (ASE) imbalance in the dorsolateral prefrontal cortex (DLPFC) of 46 heterozygous postmortem brains. While no significant association between rs1344706 and SZ or BD was observed in the Costa Rica sample, we observed an increased risk of SZ for the minor allele (A) of the exonic rs12476147 SNP (p=0.026). Our ASE assay detected a significant over-expression of the rs12476147 A allele in DLPFC of rs1344706 heterozygous subjects. Interestingly, cDNA allele ratios were significantly different according to the intronic rs1344706 genotypes (p-value=0.03), with the rs1344706 A allele associated with increased ZNF804A rs12476147 A allele expression (average 1.06, p-value=0.02, for heterozygous subjects vs. genomic DNA). In conclusion, we have demonstrated a significant association of rs12476147 with SZ, and using a powerful within-subject design, an allelic expression imbalance of ZNF804A exonic SNP rs12476147 in the DLPFC. Although this data does not preclude the possibility of other functional variants in ZNF804A, it provides evidence that the rs1344706 SZ risk allele is the cis-regulatory variant directly responsible for this allelic expression imbalance in adult cortex.

Natural variation in the histone demethylase, KDM4C, influences expression levels of specific genes including those that affect cell growth

DNA sequence variants influence gene expression and cellular phenotypes. In this study, we focused on natural variation in the gene encoding the histone demethylase, KDM4C, which promotes transcriptional activation by removing the repressive histone mark, H3K9me3, from its target genes. We uncovered cis-acting variants that contribute to extensive individual differences in KDM4C expression. We also identified the target genes of KDM4C and demonstrated that variation in KDM4C expression leads to differences in the growth of normal and some cancer cells. Together, our results from genetic mapping and molecular analysis provide an example of how genetic variation affects epigenetic regulation of gene expression and cellular phenotype.

Quantifying RNA allelic ratios by microfluidic multiplex PCR and sequencing

We developed a targeted RNA sequencing method that couples microfluidics-based multiplex PCR and deep sequencing (mmPCR-seq) to uniformly and simultaneously amplify up to 960 loci in 48 samples independently of their gene expression levels, and accurately and cost-effectively measure allelic ratios even for low-quantity or low-quality RNA samples. We applied mmPCR-seq to RNA editing and allele-specific expression studies. mmPCR-seq complements RNA-seq and provides a highly desirable solution for future applications.

Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals

Understanding the consequences of regulatory variation in the human genome remains a major challenge, with important implications for understanding gene regulation and interpreting the many disease-risk variants that fall outside of protein-coding regions. Here, we provide a direct window into the regulatory consequences of genetic variation by sequencing RNA from 922 genotyped individuals. We present a comprehensive description of the distribution of regulatory variation--by the specific expression phenotypes altered, the properties of affected genes, and the genomic characteristics of regulatory variants. We detect variants influencing expression of over ten thousand genes, and through the enhanced resolution offered by RNA-sequencing, for the first time we identify thousands of variants associated with specific phenotypes including splicing and allelic expression. Evaluating the effects of both long-range intra-chromosomal and trans (cross-chromosomal) regulation, we observe modularity in the regulatory network, with three-dimensional chromosomal configuration playing a particular role in regulatory modules within each chromosome. We also observe a significant depletion of regulatory variants affecting central and critical genes, along with a trend of reduced effect sizes as variant frequency increases, providing evidence that purifying selection and buffering have limited the deleterious impact of regulatory variation on the cell. Further, generalizing beyond observed variants, we have analyzed the genomic properties of variants associated with expression and splicing and developed a Bayesian model to predict regulatory consequences of genetic variants, applicable to the interpretation of individual genomes and disease studies. Together, these results represent a critical step toward characterizing the complete landscape of human regulatory variation.

Characterizing the genetic basis of transcriptome diversity through RNA-sequencing of 922 individuals

Understanding the consequences of regulatory variation in the human genome remains a major challenge, with important implications for understanding gene regulation and interpreting the many disease-risk variants that fall outside of protein-coding regions. Here, we provide a direct window into the regulatory consequences of genetic variation by sequencing RNA from 922 genotyped individuals. We present a comprehensive description of the distribution of regulatory variation—by the specific expression phenotypes altered, the properties of affected genes, and the genomic characteristics of regulatory variants. We detect variants influencing expression of over ten thousand genes, and through the enhanced resolution offered by RNA-sequencing, for the first time we identify thousands of variants associated with specific phenotypes including splicing and allelic expression. Evaluating the effects of both long-range intra-chromosomal and trans (cross-chromosomal) regulation, we observe modularity in the regulatory network, with three-dimensional chromosomal configuration playing a particular role in regulatory modules within each chromosome. We also observe a significant depletion of regulatory variants affecting central and critical genes, along with a trend of reduced effect sizes as variant frequency increases, providing evidence that purifying selection and buffering have limited the deleterious impact of regulatory variation on the cell. Further, generalizing beyond observed variants, we have analyzed the genomic properties of variants associated with expression and splicing and developed a Bayesian model to predict regulatory consequences of genetic variants, applicable to the interpretation of individual genomes and disease studies. Together, these results represent a critical step toward characterizing the complete landscape of human regulatory variation.

Efficient site-specific transgenesis and enhancer activity tests in medaka using PhiC31 integrase

Established transgenesis methods for fish model systems allow efficient genomic integration of transgenes. However, thus far a way of controlling copy number and integration sites has not been available, leading to variable transgene expression caused by position effects. The integration of transgenes at predefined genomic positions enables the direct comparison of different transgenes, thereby improving time and cost efficiency. Here, we report an efficient PhiC31-based site-specific transgenesis system for medaka. This system includes features that allow the pre-selection of successfully targeted integrations early on in the injected generation. Pre-selected embryos transmit the correctly integrated transgene through the germline with high efficiency. The landing site design enables a variety of applications, such as reporter and enhancer switch, in addition to the integration of any insert. Importantly, this allows assaying of enhancer activity in a site-specific manner without requiring germline transmission, thus speeding up large-scale analyses of regulatory elements.

RNA-seq analysis of allele-specific expression, hybrid effects, and regulatory divergence in hybrids compared with their parents from natural populations

Hybridization is a prominent process among natural plant populations that can result in phenotypic novelty, heterosis, and changes in gene expression. The effects of intraspecific hybridization on F1 hybrid gene expression were investigated using parents from divergent, natural populations of Cirsium arvense, an invasive Compositae weed. Using an RNA-seq approach, the expression of 68,746 unigenes was quantified in parents and hybrids. The expression levels of 51% of transcripts differed between parents, a majority of which had less than 1.25× fold-changes. More unigenes had higher expression in the invasive parent (P1) than the noninvasive parent (P2). Of those that were divergently expressed between parents, 10% showed additive and 81% showed nonadditive (transgressive or dominant) modes of gene action in the hybrids. A majority of the dominant cases had P2-like expression patterns in the hybrids. Comparisons of allele-specific expression also enabled a survey of cis- and trans-regulatory effects. Cis- and trans-regulatory divergence was found at 70% and 68% of 62,281 informative single-nucleotide polymorphism sites, respectively. Of the 17% of sites exhibiting both cis- and trans-effects, a majority (70%) had antagonistic regulatory interactions (cis x trans); trans-divergence tended to drive higher expression of the P1 allele, whereas cis-divergence tended to increase P2 transcript abundance. Trans-effects correlated more highly than cis with parental expression divergence and accounted for a greater proportion of the regulatory divergence at sites with additive compared with nonadditive inheritance patterns. This study explores the nature of, and types of mechanisms underlying, expression changes that occur in upon intraspecific hybridization in natural populations.

Allelic gene expression imbalance of bovine IGF2, LEP and CCL2 genes in liver, kidney and pituitary

Allelic expression imbalance (AEI) is an important genetic factor being the cause of differences in phenotypic traits that can be heritable. Studying AEI can be useful in searching for factors that modulate gene expression and help to understand molecular mechanisms underlying phenotypic changes. Although it was commonly recognized in many species and we know many genes show allelic expression imbalance, this phenomena was not studied on a larger scale in cattle. Using the pyrosequencing method we analyzed a set of 29 bovine genes in order to find those that have preferential allelic expression. The study was conducted in three tissues: liver, pituitary and kindey. Out of the studied group of genes 3 of them—LEP (leptin), IGF2 (insulin-like growth factor 2), CCL2 (chemokine C–C motif ligand 2) showed allelic expression imbalance.

dsPIG: a tool to predict imprinted genes from the deep sequencing of whole transcriptomes

Background

Dysregulation of imprinted genes, which are expressed in a parent-of-origin-specific manner, plays an important role in various human diseases, such as cancer and behavioral disorder. To date, however, fewer than 100 imprinted genes have been identified in the human genome. The recent availability of high-throughput technology makes it possible to have large-scale prediction of imprinted genes. Here we propose a Bayesian model (dsPIG) to predict imprinted genes on the basis of allelic expression observed in mRNA-Seq data of independent human tissues.

Results

Our model (dsPIG) was capable of identifying imprinted genes with high sensitivity and specificity and a low false discovery rate when the number of sequenced tissue samples was fairly large, according to simulations. By applying dsPIG to the mRNA-Seq data, we predicted 94 imprinted genes in 20 cerebellum samples and 57 imprinted genes in 9 diverse tissue samples with expected low false discovery rates. We also assessed dsPIG using previously validated imprinted and non-imprinted genes. With simulations, we further analyzed how imbalanced allelic expression of non-imprinted genes or different minor allele frequencies affected the predictions of dsPIG. Interestingly, we found that, among biallelically expressed genes, at least 18 genes expressed significantly more transcripts from one allele than the other among different individuals and tissues.

Conclusion

With the prevalence of the mRNA-Seq technology, dsPIG has become a useful tool for analysis of allelic expression and large-scale prediction of imprinted genes. For ease of use, we have set up a web service and also provided an R package for dsPIG at http://www.shoudanliang.com/dsPIG/.

Gene-gene interaction and functional impact of polymorphisms on innate immune genes in controlling Plasmodium falciparum blood infection level

Genetic variations in toll-like receptors and cytokine genes of the innate immune pathways have been implicated in controlling parasite growth and the pathogenesis of Plasmodium falciparum mediated malaria. We previously published genetic association of TLR4 non-synonymous and TNF-α promoter polymorphisms with P.falciparum blood infection level and here we extend the study considerably by (i) investigating genetic dependence of parasite-load on interleukin-12B polymorphisms, (ii) reconstructing gene-gene interactions among candidate TLRs and cytokine loci, (iii) exploring genetic and functional impact of epistatic models and (iv) providing mechanistic insights into functionality of disease-associated regulatory polymorphisms. Our data revealed that carriage of AA (P = 0.0001) and AC (P = 0.01) genotypes of IL12B 3′UTR polymorphism was associated with a significant increase of mean log-parasitemia relative to rare homozygous genotype CC. Presence of IL12B+1188 polymorphism in five of six multifactor models reinforced its strong genetic impact on malaria phenotype. Elevation of genetic risk in two-component models compared to the corresponding single locus and reduction of IL12B (2.2 fold) and lymphotoxin-α (1.7 fold) expressions in patients'peripheral-blood-mononuclear-cells under TLR4Thr399Ile risk genotype background substantiated the role of Multifactor Dimensionality Reduction derived models. Marked reduction of promoter activity of TNF-α risk haplotype (C-C-G-G) compared to wild-type haplotype (T-C-G-G) with (84%) and without (78%) LPS stimulation and the loss of binding of transcription factors detected in-silico supported a causal role of TNF-1031. Significantly lower expression of IL12B+1188 AA (5 fold) and AC (9 fold) genotypes compared to CC and under-representation (P = 0.0048) of allele A in transcripts of patients' PBMCs suggested an Allele-Expression-Imbalance. Allele (A+1188C) dependent differential stability (2 fold) of IL12B-transcripts upon actinomycin-D treatment and observed structural modulation (P = 0.013) of RNA-ensemble were the plausible explanations for AEI. In conclusion, our data provides functional support to the hypothesis that de-regulated receptor-cytokine axis of innate immune pathway influences blood infection level in P. falciparum malaria.

Gene-wide characterization of common quantitative trait loci for ABCB1 mRNA expression in normal liver tissues in the Chinese population

In order to comprehensively screen genetic variants leading to differential expression of the important human ABCB1 gene in the primary drug-metabolizing organ, ABCB1 mRNA expression levels were measured in 73 normal liver tissue samples from Chinese subjects. A set of Tag SNPs. were genotyped. In addition, imputation was performed within a 500 kb region around the ABCB1 gene using the reference panels of 1,000 Genome project and HapMap III. Bayesian regression was used to assess the strength of associations by compute Bayes Factors for imputed SNPs. Through imputation and linkage disequilibrium analysis, the imputed loci rs28373093, rs1002205, rs1029421, rs2285647, and rs10235835, may represent independent and strong association signals. rs28373093, a polymorphism 1.5 kb upstream from the ABCB1 transcription start site, has the strongest association. 2677 G>A/T and 3435C>T confer a clear gene-dosage effect on ABCB1 mRNA expression. The systematic characterization of gene-wide common quantitative trait loci associated with ABCB1 mRNA expression in normal liver tissues would provide the candidate markers to ABCB1-relevant clinical phenotypes in Chinese population.

SNPing cancer in the bud: microRNA and microRNA-target site polymorphisms as diagnostic and prognostic biomarkers in cancer

MicroRNAs are master regulators of gene expression and control many biological pathways such as cell growth, differentiation and apoptosis. Deregulation of microRNA expression and activity results in a myriad of diseases including cancer. Recently, several reports have indicated that single nucleotide polymorphisms (SNPs) in microRNAs and microRNA-target sites impact microRNA biology and associate with cancer risk, treatment response and outcome. In this review we will describe these findings and discuss the possible future of utilizing these SNPs as diagnostic and prognostic markers in the clinic.