Interaction between genetic and epigenetic variation defines gene expression patterns at the asthma-associated locus 17q12-q21 in lymphoblastoid cell lines

Phenotypic variation results from variation in gene expression, which is modulated by genetic and/or epigenetic factors. To understand the molecular basis of human disease, interaction between genetic and epigenetic factors needs to be taken into account. The asthma-associated region 17q12-q21 harbors three genes, the zona pellucida binding protein 2 (ZPBP2), gasdermin B (GSDMB) and ORM1-like 3 (ORMDL3), that show allele-specific differences in expression levels in lymphoblastoid cell lines (LCLs) and CD4+ T cells. Here, we report a molecular dissection of allele-specific transcriptional regulation of the genes within the chromosomal region 17q12-q21 combining in vitro transfection, formaldehyde-assisted isolation of regulatory elements, chromatin immunoprecipitation and DNA methylation assays in LCLs. We found that a single nucleotide polymorphism rs4795397 influences the activity of ZPBP2 promoter in vitro in an allele-dependent fashion, and also leads to nucleosome repositioning on the asthma-associated allele. However, variable methylation of exon 1 of ZPBP2 masks the strong genetic effect on ZPBP2 promoter activity in LCLs. In contrast, the ORMDL3 promoter is fully unmethylated, which allows detection of genetic effects on its transcription. We conclude that the cis-regulatory effects on 17q12-q21 gene expression result from interaction between several regulatory polymorphisms and epigenetic factors within the cis-regulatory haplotype region

Variable expression of cerebral cavernous malformations in carriers of a premature termination codon in exon 17 of the Krit1 gene

BACKGROUND: Cerebral cavernous malformations (CCM) present as either sporadic or autosomal dominant conditions with incomplete penetrance of symptoms. Differences in genetic and environmental factors might be minimized among first-degree relatives. We therefore studied clinical expression in a family with several affected members. METHODS: We studied a three-generation family with the onset of CCM as a cerebral haemorrhage in the younger (four-year-old) sibling. Identification and enumeration of CCMs were performed in T2-weighted or gradient-echo MRIs of the whole brains. Genetic analysis comprised SCCP, sequencing and restriction polymorphism of the Krit1 gene in the proband and at risk relatives. RESULTS: The phenotypes of cerebral cavernous malformations (CCMs) in carriers of Krit1 mutations were very variable. We identified a novel frameshift mutation caused by a 1902A insertion in exon 17 of the Krit1 gene, which leads to a premature TAA triplet and predicts the truncating phenotype Y634X. A very striking finding was the absence of both clinical symptoms and CCMs in the eldest sibling harbouring the 1902insA. CONCLUSIONS: Patients in this family, harbouring the same mutation, illustrate the very variable clinical and radiological expression of a Krit1 mutation. The early and critical onset in the proband contrasts with minor clinical findings in affected relatives. This consideration is important in genetic counselling

A genome-wide screen in human embryonic stem cells reveals novel sites of allele-specific histone modification associated with known disease loci

<p>Abstract</p> <p>Background</p> <p>Chromatin structure at a given site can differ between chromosome copies in a cell, and such imbalances in chromatin structure have been shown to be important in understanding the molecular mechanisms controlling several disease loci. Human genetic variation, DNA methylation, and disease have been intensely studied, uncovering many sites of allele-specific DNA methylation (ASM). However, little is known about the genome-wide occurrence of sites of allele-specific histone modification (ASHM) and their relationship to human disease. The aim of this study was to investigate the extent and characteristics of sites of ASHM in human embryonic stem cells (hESCs).</p> <p>Results</p> <p>Using a statistically rigorous protocol, we investigated the genomic distribution of ASHM in hESCs, and their relationship to sites of allele-specific expression (ASE) and DNA methylation. We found that, although they were rare, sites of ASHM were substantially enriched at loci displaying ASE. Many were also found at known imprinted regions, hence sites of ASHM are likely to be better markers of imprinted regions than sites of ASM. We also found that sites of ASHM and ASE in hESCs colocalize at risk loci for developmental syndromes mediated by deletions, providing insights into the etiology of these disorders.</p> <p>Conclusion</p> <p>These results demonstrate the potential importance of ASHM patterns in the interpretation of disease loci, and the protocol described provides a basis for similar studies of ASHM in other cell types to further our understanding of human disease susceptibility.</p

Genome-wide association reveals genetic effects on human Aβ₄₂and τ protein levels in cerebrospinal fluids: a case control study

<p>Abstract</p> <p>Background</p> <p>Alzheimer's disease (AD) is common and highly heritable with many genes and gene variants associated with AD in one or more studies, including APOE ε2/ε3/ε4. However, the genetic backgrounds for normal cognition, mild cognitive impairment (MCI) and AD in terms of changes in cerebrospinal fluid (CSF) levels of Aβ_1-42, T-tau, and P-tau_181P, have not been clearly delineated. We carried out a genome-wide association study (GWAS) in order to better define the genetic backgrounds to these three states in relation to CSF levels.</p> <p>Methods</p> <p>Subjects were participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI). The GWAS dataset consisted of 818 participants (mainly Caucasian) genotyped using the Illumina Human Genome 610 Quad BeadChips. This sample included 410 subjects (119 Normal, 115 MCI and 176 AD) with measurements of CSF Aβ_1-42, T-tau, and P-tau_181PLevels. We used PLINK to find genetic associations with the three CSF biomarker levels. Association of each of the 498,205 SNPs was tested using additive, dominant, and general association models while considering APOE genotype and age. Finally, an effort was made to better identify relevant biochemical pathways for associated genes using the ALIGATOR software.</p> <p>Results</p> <p>We found that there were some associations with APOE genotype although CSF levels were about the same for each subject group; CSF Aβ_1-42levels decreased with APOE gene dose for each subject group. T-tau levels tended to be higher among AD cases than among normal subjects. From adjusted result using APOE genotype and age as covariates, no SNP was associated with CSF levels among AD subjects. <it>CYP19A1 </it>'aromatase' (rs2899472), <it>NCAM2</it>, and multiple SNPs located on chromosome 10 near the <it>ARL5B </it>gene demonstrated the strongest associations with Aβ_1-42in normal subjects. Two genes found to be near the top SNPs, <it>CYP19A1 </it>(rs2899472, p = 1.90 × 10^-7) and <it>NCAM2 </it>(rs1022442, p = 2.75 × 10^-7) have been reported as genetic factors related to the progression of AD from previous studies. In AD subjects, APOE ε2/ε3 and ε2/ε4 genotypes were associated with elevated T-tau levels and ε4/ε4 genotype was associated with elevated T-tau and P-tau_181Plevels. Pathway analysis detected several biological pathways implicated in Normal with CSF β-amyloid peptide (Aβ_1-42).</p> <p>Conclusions</p> <p>Our genome-wide association analysis identified several SNPs as important factors for CSF biomarker. We also provide new evidence for additional candidate genetic risk factors from pathway analysis that can be tested in further studies.</p

Genome screen in familial intracranial aneurysm

Research articl

Computational Analysis of Whole-Genome Differential Allelic Expression Data in Human

Allelic imbalance (AI) is a phenomenon where the two alleles of a given gene are expressed at different levels in a given cell, either because of epigenetic inactivation of one of the two alleles, or because of genetic variation in regulatory regions. Recently, Bing et al. have described the use of genotyping arrays to assay AI at a high resolution (∼750,000 SNPs across the autosomes). In this paper, we investigate computational approaches to analyze this data and identify genomic regions with AI in an unbiased and robust statistical manner. We propose two families of approaches: (i) a statistical approach based on z-score computations, and (ii) a family of machine learning approaches based on Hidden Markov Models. Each method is evaluated using previously published experimental data sets as well as with permutation testing. When applied to whole genome data from 53 HapMap samples, our approaches reveal that allelic imbalance is widespread (most expressed genes show evidence of AI in at least one of our 53 samples) and that most AI regions in a given individual are also found in at least a few other individuals. While many AI regions identified in the genome correspond to known protein-coding transcripts, others overlap with recently discovered long non-coding RNAs. We also observe that genomic regions with AI not only include complete transcripts with consistent differential expression levels, but also more complex patterns of allelic expression such as alternative promoters and alternative 3′ end. The approaches developed not only shed light on the incidence and mechanisms of allelic expression, but will also help towards mapping the genetic causes of allelic expression and identify cases where this variation may be linked to diseases

Asthma-susceptibility variants identified using probands in case-control and family-based analyses

<p>Abstract</p> <p>Background</p> <p>Asthma is a chronic respiratory disease whose genetic basis has been explored for over two decades, most recently via genome-wide association studies. We sought to find asthma-susceptibility variants by using probands from a single population in both family-based and case-control association designs.</p> <p>Methods</p> <p>We used probands from the Childhood Asthma Management Program (CAMP) in two primary genome-wide association study designs: (1) probands were combined with publicly available population controls in a case-control design, and (2) probands and their parents were used in a family-based design. We followed a two-stage replication process utilizing three independent populations to validate our primary findings.</p> <p>Results</p> <p>We found that single nucleotide polymorphisms with similar case-control and family-based association results were more likely to replicate in the independent populations, than those with the smallest p-values in either the case-control or family-based design alone. The single nucleotide polymorphism that showed the strongest evidence for association to asthma was rs17572584, which replicated in 2/3 independent populations with an overall p-value among replication populations of 3.5E-05. This variant is near a gene that encodes an enzyme that has been implicated to act coordinately with modulators of Th2 cell differentiation and is expressed in human lung.</p> <p>Conclusions</p> <p>Our results suggest that using probands from family-based studies in case-control designs, and combining results of both family-based and case-control approaches, may be a way to augment our ability to find SNPs associated with asthma and other complex diseases.</p

Global Analysis of the Impact of Environmental Perturbation on cis-Regulation of Gene Expression

Genetic variants altering cis-regulation of normal gene expression (cis-eQTLs) have been extensively mapped in human cells and tissues, but the extent by which controlled, environmental perturbation influences cis-eQTLs is unclear. We carried out large-scale induction experiments using primary human bone cells derived from unrelated donors of Swedish origin treated with 18 different stimuli (7 treatments and 2 controls, each assessed at 2 time points). The treatments with the largest impact on the transcriptome, verified on two independent expression arrays, included BMP-2 (t = 2h), dexamethasone (DEX) (t = 24h), and PGE2 (t = 24h). Using these treatments and control, we performed expression profiling for 18,144 RefSeq transcripts on biological replicates of the complete study cohort of 113 individuals (ntotal = 782) and combined it with genome-wide SNP-genotyping data in order to map treatment-specific cis-eQTLs (defined as SNPs located within the gene ±250 kb). We found that 93% of cis-eQTLs at 1% FDR were observed in at least one additional treatment, and in fact, on average, only 1.4% of the cis-eQTLs were considered as treatment-specific at high confidence. The relative invariability of cis-regulation following perturbation was reiterated independently by genome-wide allelic expression tests where only a small proportion of variance could be attributed to treatment. Treatment-specific cis-regulatory effects were, however, 2- to 6-fold more abundant among differently expressed genes upon treatment. We further followed-up and validated the DEX–specific cis-regulation of the MYO6 and TNC loci and found top cis-regulatory variants located 180 kb and 250 kb upstream of the transcription start sites, respectively. Our results suggest that, as opposed to tissue-specificity of cis-eQTLs, the interactions between cellular environment and cis-variants are relatively rare (∼1.5%), but that detection of such specific interactions can be achieved by a combination of functional genomic approaches as described here

Maps of Open Chromatin Guide the Functional Follow-Up of Genome-Wide Association Signals: Application to Hematological Traits

Turning genetic discoveries identified in genome-wide association (GWA) studies into biological mechanisms is an important challenge in human genetics. Many GWA signals map outside exons, suggesting that the associated variants may lie within regulatory regions. We applied the formaldehyde-assisted isolation of regulatory elements (FAIRE) method in a megakaryocytic and an erythroblastoid cell line to map active regulatory elements at known loci associated with hematological quantitative traits, coronary artery disease, and myocardial infarction. We showed that the two cell types exhibit distinct patterns of open chromatin and that cell-specific open chromatin can guide the finding of functional variants. We identified an open chromatin region at chromosome 7q22.3 in megakaryocytes but not erythroblasts, which harbors the common non-coding sequence variant rs342293 known to be associated with platelet volume and function. Resequencing of this open chromatin region in 643 individuals provided strong evidence that rs342293 is the only putative causative variant in this region. We demonstrated that the C- and G-alleles differentially bind the transcription factor EVI1 affecting PIK3CG gene expression in platelets and macrophages. A protein–protein interaction network including up- and down-regulated genes in Pik3cg knockout mice indicated that PIK3CG is associated with gene pathways with an established role in platelet membrane biogenesis and thrombus formation. Thus, rs342293 is the functional common variant at this locus; to the best of our knowledge this is the first such variant to be elucidated among the known platelet quantitative trait loci (QTLs). Our data suggested a molecular mechanism by which a non-coding GWA index SNP modulates platelet phenotype

Unraveling the Regulatory Mechanisms Underlying Tissue-Dependent Genetic Variation of Gene Expression

It is known that genetic variants can affect gene expression, but it is not yet completely clear through what mechanisms genetic variation mediate this expression. We therefore compared the cis-effect of single nucleotide polymorphisms (SNPs) on gene expression between blood samples from 1,240 human subjects and four primary non-blood tissues (liver, subcutaneous, and visceral adipose tissue and skeletal muscle) from 85 subjects. We characterized four different mechanisms for 2,072 probes that show tissue-dependent genetic regulation between blood and non-blood tissues: on average 33.2% only showed cis-regulation in non-blood tissues; 14.5% of the eQTL probes were regulated by different, independent SNPs depending on the tissue of investigation. 47.9% showed a different effect size although they were regulated by the same SNPs. Surprisingly, we observed that 4.4% were regulated by the same SNP but with opposite allelic direction. We show here that SNPs that are located in transcriptional regulatory elements are enriched for tissue-dependent regulation, including SNPs at 3′ and 5′ untranslated regions (P = 1.84×10−5 and 4.7×10−4, respectively) and SNPs that are synonymous-coding (P = 9.9×10−4). SNPs that are associated with complex traits more often exert a tissue-dependent effect on gene expression (P = 2.6×10−10). Our study yields new insights into the genetic basis of tissue-dependent expression and suggests that complex trait associated genetic variants have even more complex regulatory effects than previously anticipated