is-rSNP: a novel technique for in silico regulatory SNP detection

Genetic Evidence for Possible Involvement of the Calcium Channel Gene CACNA1A in Autism Pathogenesis in Chinese Han Population

Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders. Recent studies suggested that calcium channel genes might be involved in the genetic etiology of ASD. CACNA1A, encoding an alpha-1 subunit of voltage-gated calcium channel, has been reported to play an important role in neural development. Previous study detected that a single nucleotide polymorphism (SNP) in CACNA1A confers risk to ASD in Central European population. However, the genetic relationship between autism and CACNA1A in Chinese Han population remains unclear. To explore the association of CACNA1A with autism, we performed a family-based association study. First, we carried out a family-based association test between twelve tagged SNPs and autism in 239 trios. To further confirm the association, the sample size was expanded to 553 trios by recruiting 314 additional trios. In a total of 553 trios, we identified association of rs7249246 and rs12609735 with autism though this would not survive after Bonferroni correction. Our findings suggest that CACNA1A might play a role in the etiology of autism.

Chromatin remodeling gene EZH2 involved in the genetic etiology of autism in Chinese Han population

Autism spectrum disorder (ASD) is a group of severe neurodevelopmental disorders. Epigenetic factors play a critical role in the etiology of ASD. Enhancer of zest homolog 2 (EZH2), which encodes a histone methyltransferase, plays an important role in the process of chromatin remodeling during neurodevelopment. Further, EZH2 is located in chromosome 7q35-36, which is one of the linkage regions for autism. However, the genetic relationship between autism and EZH2 remains unclear. To investigate the association between EZH2 and autism in Chinese Han population, we performed a family-based association study between autism and three tagged single nucleotide polymorphisms (SNPs) that covered 95.4% of the whole region of EZH2. In the discovery cohort of 239 trios, two SNPs (rs740949 and rs6464926) showed a significant association with autism. To decrease false positive results, we expanded the sample size to 427 trios. A SNP (rs6464926) was significantly associated with autism even after Bonferroni correction (p=0.008). Haplotype G-T (rs740949 and rs6464926) was a risk factor for autism (Z=2.655, p=0.008, Global p=0.024). In silico function prediction for SNPs indicated that these two SNPs might be regulatory SNPs. Expression pattern of EZH2 showed that it is highly expressed in human embryonic brains. In conclusion, our findings demonstrate that EZH2 might contribute to the genetic etiology of autism in Chinese Han population.

GERV: a statistical method for generative evaluation of regulatory variants for transcription factor binding

MOTIVATION

The majority of disease-associated variants identified in genome-wide association studies reside in noncoding regions of the genome with regulatory roles. Thus being able to interpret the functional consequence of a variant is essential for identifying causal variants in the analysis of genome-wide association studies.

RESULTS

We present GERV (generative evaluation of regulatory variants), a novel computational method for predicting regulatory variants that affect transcription factor binding. GERV learns a k-mer-based generative model of transcription factor binding from ChIP-seq and DNase-seq data, and scores variants by computing the change of predicted ChIP-seq reads between the reference and alternate allele. The k-mers learned by GERV capture more sequence determinants of transcription factor binding than a motif-based approach alone, including both a transcription factor's canonical motif and associated co-factor motifs. We show that GERV outperforms existing methods in predicting single-nucleotide polymorphisms associated with allele-specific binding. GERV correctly predicts a validated causal variant among linked single-nucleotide polymorphisms and prioritizes the variants previously reported to modulate the binding of FOXA1 in breast cancer cell lines. Thus, GERV provides a powerful approach for functionally annotating and prioritizing causal variants for experimental follow-up analysis.

AVAILABILITY AND IMPLEMENTATION

The implementation of GERV and related data are available at http://gerv.csail.mit.edu/.

How to Use SNP_TATA_Comparator to Find a Significant Change in Gene Expression Caused by the Regulatory SNP of This Gene's Promoter via a Change in Affinity of the TATA-Binding Protein for This Promoter

The use of biomedical SNP markers of diseases can improve effectiveness of treatment. Genotyping of patients with subsequent searching for SNPs more frequent than in norm is the only commonly accepted method for identification of SNP markers within the framework of translational research. The bioinformatics applications aimed at millions of unannotated SNPs of the "1000 Genomes" can make this search for SNP markers more focused and less expensive. We used our Web service involving Fisher's Z-score for candidate SNP markers to find a significant change in a gene's expression. Here we analyzed the change caused by SNPs in the gene's promoter via a change in affinity of the TATA-binding protein for this promoter. We provide examples and discuss how to use this bioinformatics application in the course of practical analysis of unannotated SNPs from the "1000 Genomes" project. Using known biomedical SNP markers, we identified 17 novel candidate SNP markers nearby: rs549858786 (rheumatoid arthritis); rs72661131 (cardiovascular events in rheumatoid arthritis); rs562962093 (stroke); rs563558831 (cyclophosphamide bioactivation); rs55878706 (malaria resistance, leukopenia), rs572527200 (asthma, systemic sclerosis, and psoriasis), rs371045754 (hemophilia B), rs587745372 (cardiovascular events); rs372329931, rs200209906, rs367732974, and rs549591993 (all four: cancer); rs17231520 and rs569033466 (both: atherosclerosis); rs63750953, rs281864525, and rs34166473 (all three: malaria resistance, thalassemia).

Comprehensive genetic assessment of the ESR1 locus identifies a risk region for endometrial cancer

Excessive exposure to estrogen is a well-established risk factor for endometrial cancer (EC), particularly for cancers of endometrioid histology. The physiological function of estrogen is primarily mediated by estrogen receptor alpha, encoded by ESR1. Consequently, several studies have investigated whether variation at the ESR1 locus is associated with risk of EC, with conflicting results. We performed comprehensive fine-mapping analyses of 3633 genotyped and imputed single nucleotide polymorphisms (SNPs) in 6607 EC cases and 37 925 controls. There was evidence of an EC risk signal located at a potential alternative promoter of the ESR1 gene (lead SNP rs79575945, P=1.86×10(-5)), which was stronger for cancers of endometrioid subtype (P=3.76×10(-6)). Bioinformatic analysis suggests that this risk signal is in a functionally important region targeting ESR1, and eQTL analysis found that rs79575945 was associated with expression of SYNE1, a neighbouring gene. In summary, we have identified a single EC risk signal located at ESR1, at study-wide significance. Given SNPs located at this locus have been associated with risk for breast cancer, also a hormonally driven cancer, this study adds weight to the rationale for performing informed candidate fine-scale genetic studies across cancer types.

A polymorphism in CCR1/CCR3 is associated with narcolepsy

Etiology of narcolepsy-cataplexy involves multiple genetic and environmental factors. While the human leukocyte antigen (HLA)-DRB1*15:01-DQB1*06:02 haplotype is strongly associated with narcolepsy, it is not sufficient for disease development. To identify additional, non-HLA susceptibility genes, we conducted a genome-wide association study (GWAS) using Japanese samples. An initial sample set comprising 409 cases and 1562 controls was used for the GWAS of 525,196 single nucleotide polymorphisms (SNPs) located outside the HLA region. An independent sample set comprising 240 cases and 869 controls was then genotyped at 37 SNPs identified in the GWAS. We found that narcolepsy was associated with a SNP in the promoter region of chemokine (C-C motif) receptor 1 (CCR1) (rs3181077, P=1.6×10(-5), odds ratio [OR]=1.86). This rs3181077 association was replicated with the independent sample set (P=0.032, OR=1.36). We measured mRNA levels of candidate genes in peripheral blood samples of 38 cases and 37 controls. CCR1 and CCR3 mRNA levels were significantly lower in patients than in healthy controls, and CCR1 mRNA levels were associated with rs3181077 genotypes. In vitro chemotaxis assays were also performed to measure monocyte migration. We observed that monocytes from carriers of the rs3181077 risk allele had lower migration indices with a CCR1 ligand. CCR1 and CCR3 are newly discovered susceptibility genes for narcolepsy. These results highlight the potential role of CCR genes in narcolepsy and support the hypothesis that patients with narcolepsy have impaired immune function.

Predicting functional regulatory SNPs in the human antimicrobial peptide genes DEFB1 and CAMP in tuberculosis and HIV/AIDS

Single nucleotide polymorphisms (SNPs) in transcription factor binding sites (TFBSs) within gene promoter region or enhancers can modify the transcription rate of genes related to complex diseases. These SNPs can be called regulatory SNPs (rSNPs). Data compiled from recent projects, such as the 1000 Genomes Project and ENCODE, has revealed essential information used to perform in silico prediction of the molecular and biological repercussions of SNPs within TFBS. However, most of these studies are very limited, as they only analyze SNPs in coding regions or when applied to promoters, and do not integrate essential biological data like TFBSs, expression profiles, pathway analysis, homotypic redundancy (number of TFBSs for the same TF in a region), chromatin accessibility and others, which could lead to a more accurate prediction. Our aim was to integrate different data in a biologically coherent method to analyze the proximal promoter regions of two antimicrobial peptide genes, DEFB1 and CAMP, that are associated with tuberculosis (TB) and HIV/AIDS. We predicted SNPs within the promoter regions that are more likely to interact with transcription factors (TFs). We also assessed the impact of homotypic redundancy using a novel approach called the homotypic redundancy weight factor (HWF). Our results identified 10 SNPs, which putatively modify the binding affinity of 24 TFs previously identified as related to TB and HIV/AIDS expression profiles (e.g. KLF5, CEBPA and NFKB1 for TB; FOXP2, BRCA1, CEBPB, CREB1, EBF1 and ZNF354C for HIV/AIDS; and RUNX2, HIF1A, JUN/AP-1, NR4A2, EGR1 for both diseases). Validating with the OregAnno database and cell-specific functional/non functional SNPs from additional 13 genes, our algorithm performed 53% sensitivity and 84.6% specificity to detect functional rSNPs using the DNAseI-HUP database. We are proposing our algorithm as a novel in silico method to detect true functional rSNPs in antimicrobial peptide genes. With further improvement, this novel method could be applied to other promoters in order to design probes and to discover new drug targets for complex diseases.

Variants in RBP4 and AR genes modulate age at onset in familial amyloid polyneuropathy (FAP ATTRV30M)

Familial amyloid polyneuropathy (FAP) ATTRV30M is a neurodegenerative disorder due to point mutations in the transthyretin gene, with V30M being the commonest. FAP ATTRV30M shows a wide variation in age at onset (AO) between clusters, families and generations. Portuguese patients also show remarkable AO differences between genders. Genes found to be associated with FAP ATTRV30M pathways may act as AO modifiers. Our aim was to further explore the role of APCS and RBP4 genes and to study for the first time the involvement of sex-linked genetic modifiers - AR and HSD17B1 genes - in AO variation in Portuguese families. We collected DNA from a sample of 318 patients, currently under follow-up. A total of 18 tagging SNPs from APCS, RBP4, AR and HSD17B1 and 5 additional SNPs from APCS and RBP4 previously studied were genotyped. To account for nonindependency of AO between members of the same family, we used generalized estimating equations (GEEs). We found that APCS and RBP4 were associated with late AO. In addition, rs11187545 of the RBP4 was associated with an early AO. For the AR, in the male group three SNPs were associated with an early AO, whereas in the female group four were associated with both an early and later AO. These results strengthened the role of APCS and RBP4 genes and revealed for the first time the contribution of AR genes as an AO modifier in both males and females. These findings may have important implications in genetic counseling and for new therapeutic strategies.

BayesPI-BAR: a new biophysical model for characterization of regulatory sequence variations

Sequence variations in regulatory DNA regions are known to cause functionally important consequences for gene expression. DNA sequence variations may have an essential role in determining phenotypes and may be linked to disease; however, their identification through analysis of massive genome-wide sequencing data is a great challenge. In this work, a new computational pipeline, a Bayesian method for protein–DNA interaction with binding affinity ranking (BayesPI-BAR), is proposed for quantifying the effect of sequence variations on protein binding. BayesPI-BAR uses biophysical modeling of protein–DNA interactions to predict single nucleotide polymorphisms (SNPs) that cause significant changes in the binding affinity of a regulatory region for transcription factors (TFs). The method includes two new parameters (TF chemical potentials or protein concentrations and direct TF binding targets) that are neglected by previous methods. The new method is verified on 67 known human regulatory SNPs, of which 47 (70%) have predicted true TFs ranked in the top 10. Importantly, the performance of BayesPI-BAR, which uses principal component analysis to integrate multiple predictions from various TF chemical potentials, is found to be better than that of existing programs, such as sTRAP and is-rSNP, when evaluated on the same SNPs. BayesPI-BAR is a publicly available tool and is able to carry out parallelized computation, which helps to investigate a large number of TFs or SNPs and to detect disease-associated regulatory sequence variations in the sea of genome-wide noncoding regions.

atSNP: transcription factor binding affinity testing for regulatory SNP detection

MOTIVATION

Genome-wide association studies revealed that most disease-associated single nucleotide polymorphisms (SNPs) are located in regulatory regions within introns or in regions between genes. Regulatory SNPs (rSNPs) are such SNPs that affect gene regulation by changing transcription factor (TF) binding affinities to genomic sequences. Identifying potential rSNPs is crucial for understanding disease mechanisms. In silico methods that evaluate the impact of SNPs on TF binding affinities are not scalable for large-scale analysis.

RESULTS

We describe A: ffinity T: esting for regulatory SNP: s (atSNP), a computationally efficient R package for identifying rSNPs in silico. atSNP implements an importance sampling algorithm coupled with a first-order Markov model for the background nucleotide sequences to test the significance of affinity scores and SNP-driven changes in these scores. Application of atSNP with >20 K SNPs indicates that atSNP is the only available tool for such a large-scale task. atSNP provides user-friendly output in the form of both tables and composite logo plots for visualizing SNP-motif interactions. Evaluations of atSNP with known rSNP-TF interactions indicate that SNP is able to prioritize motifs for a given set of SNPs with high accuracy.

AVAILABILITY AND IMPLEMENTATION

https://github.com/keleslab/atSNP.

CONTACT

keles@stat.wisc.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk

Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression.

Genetic study of complex diseases in the post-GWAS era

Genome-wide association studies (GWASs) have identified thousands of genes and genetic variants (mainly SNPs) that contribute to complex diseases in humans. Functional characterization and mechanistic elucidation of these SNPs and genes action are the next major challenge. It has been well established that SNPs altering the amino acids of protein-coding genes can drastically impact protein function, and play an important role in molecular pathogenesis. Functions of regulatory SNPs can be complex and elusive, and involve gene expression regulation through the effect on RNA splicing, transcription factor binding, DNA methylation and miRNA recruitment. In the present review, we summarize the recent progress in our understanding of functional consequences of GWAS-associated non-coding regulatory SNPs, and discuss the application of systems genetics and network biology in the interpretation of GWAS findings.

In-silico QTL mapping of postpubertal mammary ductal development in the mouse uncovers potential human breast cancer risk loci

Genetic background plays a dominant role in mammary gland development and breast cancer (BrCa). Despite this, the role of genetics is only partially understood. This study used strain-dependent variation in an inbred mouse mapping panel, to identify quantitative trait loci (QTL) underlying structural variation in mammary ductal development, and determined if these QTL correlated with genomic intervals conferring BrCa susceptibility in humans. For about half of the traits, developmental variation among the complete set of strains in this study was greater (P < 0.05) than that of previously studied strains, or strains in current common use for mammary gland biology. Correlations were also detected with previously reported variation in mammary tumor latency and metastasis. In-silico genome-wide association identified 20 mammary development QTL (Mdq). Of these, five were syntenic with previously reported human BrCa loci. The most significant (P = 1 × 10(-11)) association of the study was on MMU6 and contained the genes Plxna4, Plxna4os1, and Chchd3. On MMU5, a QTL was detected (P = 8 × 10(-7)) that was syntenic to a human BrCa locus on h12q24.5 containing the genes Tbx3 and Tbx5. Intersection of linked SNP (r(2) > 0.8) with genomic and epigenomic features, and intersection of candidate genes with gene expression and survival data from human BrCa highlighted several for further study. These results support the conclusion that mammary tumorigenesis and normal ductal development are influenced by common genetic factors and that further studies of genetically diverse mice can improve our understanding of BrCa in humans.

Genetic variation of the transthyretin gene in wild-type transthyretin amyloidosis (ATTRwt)

Wild-type transthyretin amyloidosis (ATTRwt), typically diagnosed as congestive heart failure in elderly Caucasian men, features myocardial amyloid deposits of wild-type plasma protein transthyretin (TTR). ATTRwt is sporadic, its pathogenesis is poorly understood, and currently there are no biomarkers for diagnosis or prognosis. Genetic studies of variant-associated transthyretin amyloidosis have suggested that non-coding TTR gene variants modulate disease. We hypothesized that cis-acting regulatory elements in the TTR gene non-coding regions may modify expression, affecting ATTRwt onset and progression. We studied an ATTRwt cohort consisting of 108 Caucasian males ranging in age from 59 to 87 years with cardiomyopathy due to wild-type TTR deposition; results were compared to 118 anonymous controls matched by age, sex, and race. Four predicted non-coding regulatory regions and all exons in the TTR gene were sequenced using the Sanger method. Eleven common variants were identified; three variants were significantly associated with ATTRwt (p < 0.05), though only one, rs72922940, remained near significance (p corrected = 0.083) after multiple testing correction. Exon analyses demonstrated the occurrence of the p.G26S (G6S) polymorphism in 7 % of ATTRwt subjects and 12 % of controls; this variant was predicted to be a protective factor (p = 0.051). Four variants were significantly associated with age at onset and survival. In this first genetic study of a large, well-characterized cohort of ATTRwt, non-coding and coding variants associated with disease, age at onset, and survival were identified. Further investigation is warranted to determine the prevalence of these variants in ATTRwt, their regulatory function, and potential role in assessing disease risk.

Identified single-nucleotide polymorphisms and haplotypes at 16q22.1 increase diabetic nephropathy risk in Han Chinese population

Background

Diabetic nephropathy (DN) has become one of the most common causes of end-stage renal disease (ESRD) in many countries, such as 44.5% in Taiwan. Previous studies have shown that there is a genetic component to ESRD. Studies attempting to determine which genetic variants are related to DN in Han Chinese are limited. A case–control study was conducted to identify DN susceptibility variants in Han Chinese patients with type 2 diabetes.

Results

We included 574 unrelated type 2 diabetes patients (217 DN cases and 357 controls), who were genotyped using Illumina HumanHap550-Duo BeadChip. In single-SNP association tests, the SNPs rs11647932, rs11645214, and rs6499323 located at 16q22.1 under the additive-effect disease model were significantly associated with an approximately 2-fold increased risk of DN. In haplotype association tests, identified haplotypes located in the chromosome 16q22.1 region (containing ST3GAL2, COG4, SF3B3, and IL34 genes) raised DN risk. The strongest association was found with haplotype rs2288491-rs4985534-rs11645214 (C-C-G) (adjusted odds ratio [AOR] 1.93, 95% confidence interval [CI] 1.83-2.03, p = 6.25 × 10⁻⁷), followed by haplotype rs8052125-rs2288491-rs4985534-rs11645214 (G-C-C-G) (AOR 1.92, 95% CI 1.82-2.02, p = 6.56 × 10⁻⁷), and haplotype rs2303792-rs8052125-rs2288491-rs4985534-rs11645214 (A-G-C-C-G) (AOR 1.91, 95% CI 1.81-2.01, p = 1.15 × 10⁻⁶).

Conclusions

Our results demonstrate that the novel SNPs and haplotypes located at the 16q22.1 region may involve in the biological pathways of DN in Han Chinese patients with type 2 diabetes. This study can provide new insights into the etiology of DN.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-014-0113-8) contains supplementary material, which is available to authorized users.

Single nucleotide polymorphisms in noncoding regions of Rad51C do not change the risk of unselected breast cancer but they modulate the level of oxidative stress and the DNA damage characteristics: a case-control study

Deleterious and missense mutations of RAD51C have recently been suggested to modulate the individual susceptibility to hereditary breast and ovarian cancer and unselected ovarian cancer, but not unselected breast cancer (BrC). We enrolled 132 unselected BrC females and 189 cancer-free female subjects to investigate whether common single nucleotide polymorphisms (SNPs) in non-coding regions of RAD51C modulate the risk of BrC, and whether they affect the level of oxidative stress and the extent/characteristics of DNA damage. Neither SNPs nor reconstructed haplotypes were found to significantly affect the unselected BrC risk. Contrary to this, carriers of rs12946522, rs16943176, rs12946397 and rs17222691 rare-alleles were found to present significantly increased level of blood plasma TBARS compared to respective wild-type homozygotes (p<0.05). Furthermore, these carriers showed significantly decreased fraction of oxidatively generated DNA damage (34% of total damaged DNA) in favor of DNA strand breakage, with no effect on total DNA damage, unlike respective wild-types, among which more evenly distributed proportions between oxidatively damaged DNA (48% of total DNA damage) and DNA strand breakage was found (p<0.0005 for the difference). Such effects were found among both the BrC cases and healthy subjects, indicating that they cannot be assumed as causal factors contributing to BrC development.

Associating disease-related genetic variants in intergenic regions to the genes they impact

We present a method to assist in interpretation of the functional impact of intergenic disease-associated SNPs that is not limited to search strategies proximal to the SNP. The method builds on two sources of external knowledge: the growing understanding of three-dimensional spatial relationships in the genome, and the substantial repository of information about relationships among genetic variants, genes, and diseases captured in the published biomedical literature. We integrate chromatin conformation capture data (HiC) with literature support to rank putative target genes of intergenic disease-associated SNPs. We demonstrate that this hybrid method outperforms a genomic distance baseline on a small test set of expression quantitative trait loci, as well as either method individually. In addition, we show the potential for this method to uncover relationships between intergenic SNPs and target genes across chromosomes. With more extensive chromatin conformation capture data becoming readily available, this method provides a way forward towards functional interpretation of SNPs in the context of the three dimensional structure of the genome in the nucleus.

Transcriptional regulation of human UDP-glucuronosyltransferase genes

Glucuronidation is an important metabolic pathway for many small endogenous and exogenous lipophilic compounds, including bilirubin, steroid hormones, bile acids, carcinogens and therapeutic drugs. Glucuronidation is primarily catalyzed by the UDP-glucuronosyltransferase (UGT) 1A and two subfamilies, including nine functional UGT1A enzymes (1A1, 1A3-1A10) and 10 functional UGT2 enzymes (2A1, 2A2, 2A3, 2B4, 2B7, 2B10, 2B11, 2B15, 2B17 and 2B28). Most UGTs are expressed in the liver and this expression relates to the major role of hepatic glucuronidation in systemic clearance of toxic lipophilic compounds. Hepatic glucuronidation activity protects the body from chemical insults and governs the therapeutic efficacy of drugs that are inactivated by UGTs. UGT mRNAs have also been detected in over 20 extrahepatic tissues with a unique complement of UGT mRNAs seen in almost every tissue. This extrahepatic glucuronidation activity helps to maintain homeostasis and hence regulates biological activity of endogenous molecules that are primarily inactivated by UGTs. Deciphering the molecular mechanisms underlying tissue-specific UGT expression has been the subject of a large number of studies over the last two decades. These studies have shown that the constitutive and inducible expression of UGTs is primarily regulated by tissue-specific and ligand-activated transcription factors (TFs) via their binding to cis-regulatory elements (CREs) in UGT promoters and enhancers. This review first briefly summarizes published UGT gene transcriptional studies and the experimental models and tools utilized in these studies, and then describes in detail the TFs and their respective CREs that have been identified in the promoters and/or enhancers of individual UGT genes.

Current trend of annotating single nucleotide variation in humans--A case study on SNVrap

As high throughput methods, such as whole genome genotyping arrays, whole exome sequencing (WES) and whole genome sequencing (WGS), have detected huge amounts of genetic variants associated with human diseases, function annotation of these variants is an indispensable step in understanding disease etiology. Large-scale functional genomics projects, such as The ENCODE Project and Roadmap Epigenomics Project, provide genome-wide profiling of functional elements across different human cell types and tissues. With the urgent demands for identification of disease-causal variants, comprehensive and easy-to-use annotation tool is highly in demand. Here we review and discuss current progress and trend of the variant annotation field. Furthermore, we introduce a comprehensive web portal for annotating human genetic variants. We use gene-based features and the latest functional genomics datasets to annotate single nucleotide variation (SNVs) in human, at whole genome scale. We further apply several function prediction algorithms to annotate SNVs that might affect different biological processes, including transcriptional gene regulation, alternative splicing, post-transcriptional regulation, translation and post-translational modifications. The SNVrap web portal is freely available at http://jjwanglab.org/snvrap.

In silico analysis of TTR gene (coding and non-coding regions, and interactive network) and its implications in transthyretin-related amyloidosis

INTRODUCTION

Transthyretin (TTR)-related amyloidosis is a life-threatening disease. Currently, several questions about the pathogenic mechanisms of TTR-related amyloidosis remain unanswered.

METHODS

We have investigated various TTR-related issues using different in silico approaches.

RESULTS

Using an amino acid similarity-based analysis, we have indicated the most relevant TTR secondary structures in determining mutation impact. Our amyloidogenic propensity analysis of TTR missense substitutions has highlighted a similar pattern for wild-type and mutated TTR amino β acid sequences. However, some mutations present differences with respect to the general distribution. We have identified non-coding variants in cis-regulatory elements of the TTR gene, and our analysis on V122I-related haplotypes has indicated differences in non-coding regulatory variants, suggesting differences among V122I carriers. The analysis of methylation status indicated CpG sites that may affect TTR expression. Finally, our interactive network analysis revealed functional partners of TTR that may play a modifier role in the pathogenesis of TTR-related amyloidosis.

DISCUSSION AND CONCLUSION

Our data provided new insights into the pathogenesis of TTR-related amyloidosis that, if they were to be confirmed through experimental investigations, could significantly improve our understanding of the disease.

Exploring the function of genetic variants in the non-coding genomic regions: approaches for identifying human regulatory variants affecting gene expression

Understanding the genetic basis of human traits/diseases and the underlying mechanisms of how these traits/diseases are affected by genetic variations is critical for public health. Current genome-wide functional genomics data uncovered a large number of functional elements in the noncoding regions of human genome, providing new opportunities to study regulatory variants (RVs). RVs play important roles in transcription factor bindings, chromatin states and epigenetic modifications. Here, we systematically review an array of methods currently used to map RVs as well as the computational approaches in annotating and interpreting their regulatory effects, with emphasis on regulatory single-nucleotide polymorphism. We also briefly introduce experimental methods to validate these functional RVs.

Rad51C: a novel suppressor gene modulates the risk of head and neck cancer

We conducted a case-control study to investigate the possible association between the head and neck cancer (HNC) and genetic variability of Rad51C tumor suppressor gene. Eight polymorphic sites spanning over non-coding regions of Rad51C promoter, exon 1 and intron 1 were genotyped in 81 HNC cases and 156 healthy controls using the real-time PCR technique. One investigated site turned out to be not polymorphic, while among the remaining seven sites a significant HNC risk-increasing effect was found for rs16943176 (c.-118G>A), rs12946397 (c.-26C>T) and rs17222691 (c.145+947C>T) on both allelic (OR=1.8; p<0.05) and genotypic (OR=2.0; p<0.05) level. Furthermore, our data seem to provide marginal evidence, that this effect might possibly be confined to women only (OR=2.8; p=0.05 for allelic and OR=3.7; p=0.05 for genotypic comparisons). These SNPs were found to co-segregate together forming two distinct, HNC risk-modulating haplotypes. The genetic variability of Rad51C might thus be of relevance with respect to HNC risk.

rSNPBase: a database for curated regulatory SNPs

In recent years, human regulatory SNPs (rSNPs) have been widely studied. Here, we present database rSNPBase, freely available at http://rsnp.psych.ac.cn/, to provide curated rSNPs that analyses the regulatory features of all SNPs in the human genome with reference to experimentally supported regulatory elements. In contrast with previous SNP functional annotation databases, rSNPBase is characterized by several unique features. (i) To improve reliability, all SNPs in rSNPBase are annotated with reference to experimentally supported regulatory elements. (ii) rSNPBase focuses on rSNPs involved in a wide range of regulation types, including proximal and distal transcriptional regulation and post-transcriptional regulation, and identifies their potentially regulated genes. (iii) Linkage disequilibrium (LD) correlations between SNPs were analysed so that the regulatory feature is annotated to SNP-set rather than a single SNP. (iv) rSNPBase provides the spatio-temporal labels and experimental eQTL labels for SNPs. In summary, rSNPBase provides more reliable, comprehensive and user-friendly regulatory annotations on rSNPs and will assist researchers in selecting candidate SNPs for further genetic studies and in exploring causal SNPs for in-depth molecular mechanisms of complex phenotypes.

Functional variation of the transthyretin gene among human populations and its correlation with amyloidosis phenotypes

INTRODUCTION

Heterogeneity in the genotype-phenotype correlation of transthyretin (TTR)-related amyloidosis has been reported, suggesting that other factors may interact with disease-causing mutations. Additional genetic variants in the TTR gene and its surrounding regions may influence disease phenotype. To explore this hypothesis, we analyzed the TTR variation among human populations to identify functional inter-ethnic differences that could influence the TTR-related amyloidosis.

METHODS

Using the 1000 Genomes Project database, we analyzed a 20 kb region in 1092 apparently healthy individuals who belonged to 14 human populations. In silico analyses were performed to determine the functional impact of genetic variants.

RESULTS

These analyses showed that significant ethnic differences are present in the TTR gene, and some differences may affect TTR gene function. Specifically, the non-coding variants potentially associated with regulatory function showed a significant diversity between African and non-African individuals.

DISCUSSION AND CONCLUSIONS

Our results highlighted that cis-regulatory variants may contribute to the cardiac TTR-related amyloidosis observed in patients carrier of Val122Ile mutation, the most common in population with African origin. Indeed, non-coding variants differentiated in Africans are, in some cases, located in binding sites of transcription factors involved in cardiac development and function (i.e. E2F3_2, REST, and TEAD).

Fulvestrant up regulates UGT1A4 and MRPs through ERα and c-Myb pathways: a possible primary drug disposition mechanism

Fulvestrant (Faslodex™) is a pure antiestrogen that is effective in treating estrogen receptor-(ER) positive breast cancer tumors that are resistant to selective estrogen receptor modulators such as tamoxifen. Clinical trials investigating the utility of adding fulvestrant to other therapeutics have not been shown to affect cytochrome P450-mediated metabolism. Effects on phase II metabolism and drug resistance have not been explored. This study demonstrates that fulvestrant up regulates the expression of UDP glucuronosyltransferase 1A4 (UGT1A4) >2.5- and >3.5-fold in MCF7 and HepG2 cells, respectively. Up regulation occurred in a time- and concentration-dependent manner, and was inhibited by siRNA silencing of ERα. Fulvestrant also up regulates multidrug resistance-associated proteins (MRPs). There was an up regulation of MRP2 (1.5- and 3.5-fold), and MRP3 (5.5- and 4.5-fold) in MCF7 and HepG2 cell lines, respectively, and an up regulation of MRP1 (4-fold) in MCF7 cells. UGT1A4 mRNA up regulation was significantly correlated with UGT1A4 protein expression, anastrozole glucuronidation, ERα mRNA expression and MRP mRNA expression, but not with ERα protein expression. Genetic variants in the UGT1A4 promoter (-163A, -217G and -219T) reduced the basal activity of UGT1A4 by 40-60%. In silico analysis indicated that transcription factor c-Myb binding capacity may be affected by these variations. Luciferase activity assays demonstrate that silencing c-Myb abolished UGT1A4 up regulation by fulvestrant in promoters with the common genotype (-163G, -217 T and -219C) in MCF7 cells. These data indicate that fulvestrant can influence the disposition of other UGT1A4 substrates. These findings suggest a clinically significant role for UGT1A4 and MRPs in drug efficacy.

Genome-wide analysis of blood pressure variability and ischemic stroke

BACKGROUND AND PURPOSE

Visit-to-visit variability in blood pressure (vBP) is associated with ischemic stroke. We sought to determine whether such variability has genetic causes and whether genetic variants associated with BP variability are also associated with ischemic stroke.

METHODS

A Genome Wide Association Study (GWAS) for loci influencing BP variability was undertaken in 3802 individuals from the Anglo-Scandinavian Cardiac Outcome Trial (ASCOT) study, in which long-term visit-to-visit and within-visit BP measures were available. Because BP variability is strongly associated with ischemic stroke, we genotyped the sentinel single nucleotide polymorphism in an independent ischemic stroke population comprising 8624 cases and 12 722 controls and in 3900 additional (Scandinavian) participants from the ASCOT study to replicate our findings.

RESULTS

The ASCOT discovery GWAS identified a cluster of 17 correlated single nucleotide polymorphisms within the NLGN1 gene (3q26.31) associated with BP variability. The strongest association was with rs976683 (P=1.4×10(-8)). Conditional analysis of rs976683 provided no evidence of additional independent associations at the locus. Analysis of rs976683 in patients with ischemic stroke found no association for overall stroke (odds ratio, 1.02; 95% CI, 0.97-1.07; P=0.52) or its subtypes: cardioembolic (odds ratio, 1.07; 95% CI, 0.97-1.16; P=0.17), large vessel disease (odds ratio, 0.98; 95% CI, 0.89-1.07; P=0.60), and small vessel disease (odds ratio, 1.07; 95% CI, 0.97-1.17; P=0.19). No evidence for association was found between rs976683 and BP variability in the additional (Scandinavian) ASCOT participants (P=0.18).

CONCLUSIONS

We identified a cluster of single nucleotide polymorphisms at the NLGN1 locus showing significant association with BP variability. Follow-up analyses did not support an association with risk of ischemic stroke and its subtypes.

GWAS3D: Detecting human regulatory variants by integrative analysis of genome-wide associations, chromosome interactions and histone modifications

Interpreting the genetic variants located in the regulatory regions, such as enhancers and promoters, is an indispensable step to understand molecular mechanism of complex traits. Recent studies show that genetic variants detected by genome-wide association study (GWAS) are significantly enriched in the regulatory regions. Therefore, detecting, annotating and prioritizing of genetic variants affecting gene regulation are critical to our understanding of genotype-phenotype relationships. Here, we developed a web server GWAS3D to systematically analyze the genetic variants that could affect regulatory elements, by integrating annotations from cell type-specific chromatin states, epigenetic modifications, sequence motifs and cross-species conservation. The regulatory elements are inferred from the genome-wide chromosome interaction data, chromatin marks in 16 different cell types and 73 regulatory factors motifs from the Encyclopedia of DNA Element project. Furthermore, we used these function elements, as well as risk haplotype, binding affinity, conservation and P-values reported from the original GWAS to reprioritize the genetic variants. Using studies from low-density lipoprotein cholesterol, we demonstrated that our reprioritizing approach was effective and cell type specific. In conclusion, GWAS3D provides a comprehensive annotation and visualization tool to help users interpreting their results. The web server is freely available at http://jjwanglab.org/gwas3d.

Candidate gene association studies: a comprehensive guide to useful in silico tools

The candidate gene approach has been a pioneer in the field of genetic epidemiology, identifying risk alleles and their association with clinical traits. With the advent of rapidly changing technology, there has been an explosion of in silico tools available to researchers, giving them fast, efficient resources and reliable strategies important to find casual gene variants for candidate or genome wide association studies (GWAS). In this review, following a description of candidate gene prioritisation, we summarise the approaches to single nucleotide polymorphism (SNP) prioritisation and discuss the tools available to assess functional relevance of the risk variant with consideration to its genomic location. The strategy and the tools discussed are applicable to any study investigating genetic risk factors associated with a particular disease. Some of the tools are also applicable for the functional validation of variants relevant to the era of GWAS and next generation sequencing (NGS).

Non-homologous end-joining pathway associated with occurrence of myocardial infarction: gene set analysis of genome-wide association study data

PURPOSE

DNA repair deficiencies have been postulated to play a role in the development and progression of cardiovascular disease (CVD). The hypothesis is that DNA damage accumulating with age may induce cell death, which promotes formation of unstable plaques. Defects in DNA repair mechanisms may therefore increase the risk of CVD events. We examined whether the joints effect of common genetic variants in 5 DNA repair pathways may influence the risk of CVD events.

METHODS

The PLINK set-based test was used to examine the association to myocardial infarction (MI) of the DNA repair pathway in GWAS data of 866 subjects of the GENetic DEterminants of Restenosis (GENDER) study and 5,244 subjects of the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER) study. We included the main DNA repair pathways (base excision repair, nucleotide excision repair, mismatch repair, homologous recombination and non-homologous end-joining (NHEJ)) in the analysis.

RESULTS

The NHEJ pathway was associated with the occurrence of MI in both GENDER (P = 0.0083) and PROSPER (P = 0.014). This association was mainly driven by genetic variation in the MRE11A gene (PGENDER = 0.0001 and PPROSPER = 0.002). The homologous recombination pathway was associated with MI in GENDER only (P = 0.011), for the other pathways no associations were observed.

CONCLUSION

This is the first study analyzing the joint effect of common genetic variation in DNA repair pathways and the risk of CVD events, demonstrating an association between the NHEJ pathway and MI in 2 different cohorts.

Linking disease associations with regulatory information in the human genome

Genome-wide association studies have been successful in identifying single nucleotide polymorphisms (SNPs) associated with a large number of phenotypes. However, an associated SNP is likely part of a larger region of linkage disequilibrium. This makes it difficult to precisely identify the SNPs that have a biological link with the phenotype. We have systematically investigated the association of multiple types of ENCODE data with disease-associated SNPs and show that there is significant enrichment for functional SNPs among the currently identified associations. This enrichment is strongest when integrating multiple sources of functional information and when highest confidence disease-associated SNPs are used. We propose an approach that integrates multiple types of functional data generated by the ENCODE Consortium to help identify “functional SNPs” that may be associated with the disease phenotype. Our approach generates putative functional annotations for up to 80% of all previously reported associations. We show that for most associations, the functional SNP most strongly supported by experimental evidence is a SNP in linkage disequilibrium with the reported association rather than the reported SNP itself. Our results show that the experimental data sets generated by the ENCODE Consortium can be successfully used to suggest functional hypotheses for variants associated with diseases and other phenotypes.

Network graph analysis of gene-gene interactions in genome-wide association study data

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

HOCOMOCO: a comprehensive collection of human transcription factor binding sites models

Transcription factor (TF) binding site (TFBS) models are crucial for computational reconstruction of transcription regulatory networks. In existing repositories, a TF often has several models (also called binding profiles or motifs), obtained from different experimental data. Having a single TFBS model for a TF is more pragmatic for practical applications. We show that integration of TFBS data from various types of experiments into a single model typically results in the improved model quality probably due to partial correction of source specific technique bias.

We present the Homo sapiens comprehensive model collection (HOCOMOCO, http://autosome.ru/HOCOMOCO/, http://cbrc.kaust.edu.sa/hocomoco/) containing carefully hand-curated TFBS models constructed by integration of binding sequences obtained by both low- and high-throughput methods. To construct position weight matrices to represent these TFBS models, we used ChIPMunk software in four computational modes, including newly developed periodic positional prior mode associated with DNA helix pitch. We selected only one TFBS model per TF, unless there was a clear experimental evidence for two rather distinct TFBS models. We assigned a quality rating to each model. HOCOMOCO contains 426 systematically curated TFBS models for 401 human TFs, where 172 models are based on more than one data source.

Bioinformatics for personal genome interpretation

An international consortium released the first draft sequence of the human genome 10 years ago. Although the analysis of this data has suggested the genetic underpinnings of many diseases, we have not yet been able to fully quantify the relationship between genotype and phenotype. Thus, a major current effort of the scientific community focuses on evaluating individual predispositions to specific phenotypic traits given their genetic backgrounds. Many resources aim to identify and annotate the specific genes responsible for the observed phenotypes. Some of these use intra-species genetic variability as a means for better understanding this relationship. In addition, several online resources are now dedicated to collecting single nucleotide variants and other types of variants, and annotating their functional effects and associations with phenotypic traits. This information has enabled researchers to develop bioinformatics tools to analyze the rapidly increasing amount of newly extracted variation data and to predict the effect of uncharacterized variants. In this work, we review the most important developments in the field--the databases and bioinformatics tools that will be of utmost importance in our concerted effort to interpret the human variome.

Large-scale computational identification of regulatory SNPs with rSNP-MAPPER

Background

The computational analysis of regulatory SNPs (rSNPs) is an essential step in the elucidation of the structure and function of regulatory networks at the cellular level. In this work we focus in particular on SNPs that potentially affect a Transcription Factor Binding Site (TFBS) to a significant extent, possibly resulting in changes to gene expression patterns or alternative splicing. The application described here is based on the MAPPER platform, a previously developed web-based system for the computational detection of TFBSs in DNA sequences.

Methods

rSNP-MAPPER is a computational tool that analyzes SNPs lying within predicted TFBSs and determines whether the allele substitution results in a significant change in the TFBS predictive score. The application's simple and intuitive interface supports several usage modes. For example, the user may search for potential rSNPs in the promoters of one or more genes, specified as a list of identifiers or chosen among the members of a pathway. Alternatively, the user may specify a set of SNPs to be analyzed by uploading a list of SNP identifiers or providing the coordinates of a genomic region. Finally, the user can provide two alternative sequences (wildtype and mutant), and the system will determine the location of variants to be analyzed by comparing them.

Results

In this paper we outline the architecture of rSNP-MAPPER, describing its intuitive and powerful user interface in detail. We then present several examples of the use of rSNP-MAPPER to reproduce and confirm experimental studies aimed at identifying regulatory SNPs in human genes, that show how rSNP-MAPPER is able to detect and characterize rSNPs with high accuracy. Results are richly annotated and can be displayed online or downloaded in a number of different formats.

Conclusions

rSNP-MAPPER is optimized for large scale work, allowing for the efficient annotation of thousands of SNPs, and is designed to assist in the genome-wide investigation of transcriptional regulatory networks, prioritizing potential rSNPs for subsequent experimental validation. rSNP-MAPPER is freely available at http://genome.ufl.edu/mapper/.

Toll-like receptor 9 polymorphisms are associated with severity variables in a cohort of meningococcal meningitis survivors

BACKGROUND

Genetic variation in immune response genes is associated with susceptibility and severity of infectious diseases. Toll-like receptor (TLR) 9 polymorphisms are associated with susceptibility to develop meningococcal meningitis (MM). The aim of this study is to compare genotype distributions of two TLR9 polymorphisms between clinical severity variables in MM survivors.

METHODS

We used DNA samples of a cohort of 390 children who survived MM. Next, we determined the genotype frequencies of TLR9 -1237 and TLR9 +2848 polymorphisms and compared these between thirteen clinical variables associated with prognostic factors predicting adverse outcome of bacterial meningitis in children.

RESULTS

The TLR9 -1237 TC and CC genotypes were associated with a decreased incidence of a positive blood culture for Neisseria (N.) meningitidis (p = 0.014, odds ratio (OR) 0.5. 95% confidence interval (CI) 0.3 - 0.9). The TLR9 +2848 AA mutant was associated with a decreased incidence of a positive blood culture for N. meningitidis (p = 0.017, OR 0.6, 95% CI 0.3 - 0.9). Cerebrospinal fluid (CSF) leukocytes per μL were higher in patients carrying the TLR9 -1237 TC or CC genotypes compared to carriers of the TT wild type (WT) (p = 0.024, medians: 2117, interquartile range (IQR) 4987 versus 955, IQR 3938). CSF blood/glucose ratios were lower in TLR9 -1237 TC or CC carriers than in carriers of the TT WT (p = 0.017, medians: 0.20, IQR 0.4 versus 0.35, IQR 0.5). CSF leukocytes/μL were higher in patients carrying the TLR9 +2848 AA mutant compared to carriers of GG or GA (p = 0.0067, medians: 1907, IQR 5221 versus 891, IQR 3952).

CONCLUSIONS

We identified TLR9 genotypes associated with protection against meningococcemia and enhanced local inflammatory responses inside the central nervous system, important steps in MM pathogenesis and defense.

Searching for new genetic variations in expression databases for the GABAergic and glutamatergic systems

Changes in gene expression and genetic variations in coding regions have likely functional impact, potentially associated with complex diseases, such as neuropsychiatric conditions. A current need for high throughput analysis of genomic data is leading to the development and improvement of sophisticated bioinformatics approaches, which allows the processing of large amounts of sequence and gene expression data. In this study, we identified new potential genetic variations prioritizing genes related to glutamatergic and GABAergic systems, using different bioinformatics resources. The CLCbio Workbench Combined platform was initially used to build expressed sequence tags and mRNA files retrieved, respectively, from the Goldenpath and National Center for Biotechnology Information databases and latter to perform multiple batches of Smith-Waterman alignments. The PMUT software was used to increase an accurate association between potential variations and pathogenic predictions. The annotation revealed various classes of variations and most of them are deletions ranging from 1 to 7 bp. Bioinformatic pipelines seem to be useful approaches to help screening for genetic variations with potential impact in gene expression. Further analysis will foster this aim to provide celerity at the massive analysis of data currently generated in large scale high throughput experiments.

Unveiling combinatorial regulation through the combination of ChIP information and in silico cis-regulatory module detection

Computationally retrieving biologically relevant cis-regulatory modules (CRMs) is not straightforward. Because of the large number of candidates and the imperfection of the screening methods, many spurious CRMs are detected that are as high scoring as the biologically true ones. Using ChIP-information allows not only to reduce the regions in which the binding sites of the assayed transcription factor (TF) should be located, but also allows restricting the valid CRMs to those that contain the assayed TF (here referred to as applying CRM detection in a query-based mode). In this study, we show that exploiting ChIP-information in a query-based way makes in silico CRM detection a much more feasible endeavor. To be able to handle the large datasets, the query-based setting and other specificities proper to CRM detection on ChIP-Seq based data, we developed a novel powerful CRM detection method 'CPModule'. By applying it on a well-studied ChIP-Seq data set involved in self-renewal of mouse embryonic stem cells, we demonstrate how our tool can recover combinatorial regulation of five known TFs that are key in the self-renewal of mouse embryonic stem cells. Additionally, we make a number of new predictions on combinatorial regulation of these five key TFs with other TFs documented in TRANSFAC.

Post-GWAS functional characterization of susceptibility variants for chronic lymphocytic leukemia

Recent genome-wide association studies (GWAS) have identified several gene variants associated with sporadic chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL). Many of these CLL/SLL susceptibility loci are located in non-coding or intergenic regions, posing a significant challenge to determine their potential functional relevance. Here, we review the literature of all CLL/SLL GWAS and validation studies, and apply eQTL analysis to identify putatively functional SNPs that affect gene expression that may be causal in the pathogenesis of CLL/SLL. We tested 12 independent risk loci for their potential to alter gene expression through cis-acting mechanisms, using publicly available gene expression profiles with matching genotype information. Sixteen SNPs were identified that are linked to differential expression of SP140, a putative tumor suppressor gene previously associated with CLL/SLL. Three additional SNPs were associated with differential expression of DACT3 and GNG8, which are involved in the WNT/β-catenin- and G protein-coupled receptor signaling pathways, respectively, that have been previously implicated in CLL/SLL pathogenesis. Using in silico functional prediction tools, we found that 14 of the 19 significant eQTL SNPs lie in multiple putative regulatory elements, several of which have prior implications in CLL/SLL or other hematological malignancies. Although experimental validation is needed, our study shows that the use of existing GWAS data in combination with eQTL analysis and in silico methods represents a useful starting point to screen for putatively causal SNPs that may be involved in the etiology of CLL/SLL.

HaploReg: a resource for exploring chromatin states, conservation, and regulatory motif alterations within sets of genetically linked variants

The resolution of genome-wide association studies (GWAS) is limited by the linkage disequilibrium (LD) structure of the population being studied. Selecting the most likely causal variants within an LD block is relatively straightforward within coding sequence, but is more difficult when all variants are intergenic. Predicting functional non-coding sequence has been recently facilitated by the availability of conservation and epigenomic information. We present HaploReg, a tool for exploring annotations of the non-coding genome among the results of published GWAS or novel sets of variants. Using LD information from the 1000 Genomes Project, linked SNPs and small indels can be visualized along with their predicted chromatin state in nine cell types, conservation across mammals and their effect on regulatory motifs. Sets of SNPs, such as those resulting from GWAS, are analyzed for an enrichment of cell type-specific enhancers. HaploReg will be useful to researchers developing mechanistic hypotheses of the impact of non-coding variants on clinical phenotypes and normal variation. The HaploReg database is available at http://compbio.mit.edu/HaploReg.

A genome-wide association study identifies a region at chromosome 12 as a potential susceptibility locus for restenosis after percutaneous coronary intervention

Percutaneous coronary intervention (PCI) has become an effective therapy to treat obstructive coronary artery diseases (CAD). However, one of the major drawbacks of PCI is the occurrence of restenosis in 5-25% of all initially treated patients. Restenosis is defined as the re-narrowing of the lumen of the blood vessel, resulting in renewed symptoms and the need for repeated intervention. To identify genetic variants that are associated with restenosis, a genome-wide association study (GWAS) was conducted in 295 patients who developed restenosis (cases) and 571 who did not (controls) from the GENetic Determinants of Restenosis (GENDER) study. Analysis of ~550 000 single nucleotide polymorphisms (SNPs) in GENDER was followed by a replication phase in three independent case-control populations (533 cases and 3067 controls). A potential susceptibility locus for restenosis at chromosome 12, including rs10861032 (P(combined) = 1.11 × 10(-7)) and rs9804922 (P(combined) = 1.45 × 10(-6)), was identified in the GWAS and replication phase. In addition, both SNPs were also associated with coronary events (rs10861032, P(additive) = 0.005; rs9804922, P(additive) = 0.023) in a trial based cohort set of elderly patients with (enhanced risk of) CAD (PROSPER) and all-cause mortality in PROSPER (rs10861032, P(additive) = 0.007; rs9804922, P(additive) = 0.013) and GENDER (rs10861032, P(additive) = 0.005; rs9804922, P(additive) = 0.023). Further analysis suggests that this locus could be involved in regulatory functions.

Identification of cis-regulatory sequence variations in individual genome sequences

Functional contributions of cis-regulatory sequence variations to human genetic disease are numerous. For instance, disrupting variations in a HNF4A transcription factor binding site upstream of the Factor IX gene contributes causally to hemophilia B Leyden. Although clinical genome sequence analysis currently focuses on the identification of protein-altering variation, the impact of cis-regulatory mutations can be similarly strong. New technologies are now enabling genome sequencing beyond exomes, revealing variation across the non-coding 98% of the genome responsible for developmental and physiological patterns of gene activity. The capacity to identify causal regulatory mutations is improving, but predicting functional changes in regulatory DNA sequences remains a great challenge. Here we explore the existing methods and software for prediction of functional variation situated in the cis-regulatory sequences governing gene transcription and RNA processing.

Genome-wide analysis distinguishes hyperglycemia regulated epigenetic signatures of primary vascular cells

Emerging evidence suggests that poor glycemic control mediates post-translational modifications to the H3 histone tail. We are only beginning to understand the dynamic role of some of the diverse epigenetic changes mediated by hyperglycemia at single loci, yet elevated glucose levels are thought to regulate genome-wide changes, and this still remains poorly understood. In this article we describe genome-wide histone H3K9/K14 hyperacetylation and DNA methylation maps conferred by hyperglycemia in primary human vascular cells. Chromatin immunoprecipitation (ChIP) as well as CpG methylation (CpG) assays, followed by massive parallel sequencing (ChIP-seq and CpG-seq) identified unique hyperacetylation and CpG methylation signatures with proximal and distal patterns of regionalization associative with gene expression. Ingenuity knowledge-based pathway and gene ontology analyses indicate that hyperglycemia significantly affects human vascular chromatin with the transcriptional up-regulation of genes involved in metabolic and cardiovascular disease. We have generated the first installment of a reference collection of hyperglycemia-induced chromatin modifications using robust and reproducible platforms that allow parallel sequencing-by-synthesis of immunopurified content. We uncover that hyperglycemia-mediated induction of genes and pathways associated with endothelial dysfunction occur through modulation of acetylated H3K9/K14 inversely correlated with methyl-CpG content.

Identifying functional single nucleotide polymorphisms in the human CArGome

Regulatory SNPs (rSNPs) reside primarily within the nonprotein coding genome and are thought to disturb normal patterns of gene expression by altering DNA binding of transcription factors. Nevertheless, despite the explosive rise in SNP association studies, there is little information as to the function of rSNPs in human disease. Serum response factor (SRF) is a widely expressed DNA-binding transcription factor that has variable affinity to at least 1,216 permutations of a 10 bp transcription factor binding site (TFBS) known as the CArG box. We developed a robust in silico bioinformatics screening method to evaluate sequences around RefSeq genes for conserved CArG boxes. Utilizing a predetermined phastCons threshold score, we identified 8,252 strand-specific CArGs within an 8 kb window around the transcription start site of 5,213 genes, including all previously defined SRF target genes. We then interrogated this CArG dataset for the presence of previously annotated common polymorphisms. We found a total of 118 unique CArG boxes harboring a SNP within the 10 bp CArG sequence and 1,130 CArG boxes with SNPs located just outside the CArG element. Gel shift and luciferase reporter assays validated SRF binding and functional activity of several new CArG boxes. Importantly, SNPs within or just outside the CArG box often resulted in altered SRF binding and activity. Collectively, these findings demonstrate a powerful approach to computationally define rSNPs in the human CArGome and provide a foundation for similar analyses of other TFBS. Such information may find utility in genetic association studies of human disease where little insight is known regarding the functionality of rSNPs.