We have observed extensive interindividual differences in DNA methylation of 8590 CpG sites of 6229 genes in 153 human adult cerebellum samples, enriched in CpG island "shores" and at further distances from CpG islands. To search for genetic factors that regulate this variation, we performed a genome-wide association study (GWAS) mapping of methylation quantitative trait loci (mQTLs) for the 8590 testable CpG sites. cis association refers to correlation of methylation with SNPs within 1 Mb of a CpG site. 736 CpG sites showed phenotype-wide significant cis association with 2878 SNPs (after permutation correction for all tested markers and methylation phenotypes). In trans analysis of methylation, which tests for distant regulation effects, associations of 12 CpG sites and 38 SNPs remained significant after phenotype-wide correction. To examine the functional effects of mQTLs, we analyzed 85 genes that were with genetically regulated methylation we observed and for which we had quality gene expression data. Ten genes showed SNP-methylation-expression three-way associations-the same SNP simultaneously showed significant association with both DNA methylation and gene expression, while DNA methylation was significantly correlated with gene expression. Thus, we demonstrated that DNA methylation is frequently a heritable continuous quantitatively variable trait in human brain. Unlike allele-specific methylation, genetic polymorphisms mark both cis- and trans-regulatory genetic sites at measurable distances from their CpG sites. Some of the genetically regulated DNA methylation is directly connected with genetically regulated gene expression variation.

BackgroundProper cell models for breast cancer primary tumors have long been the focal point in the cancer’s research. The genomic comparison between cell lines and tumors can investigate the similarity and dissimilarity and help to select right cell model to mimic tumor tissues to properly evaluate the drug reaction in vitro. In this paper, a comprehensive comparison in copy number variation (CNV), mutation, mRNA expression and protein expression between 68 breast cancer cell lines and 1375 primary breast tumors is conducted and presented.ResultsUsing whole genome expression arrays, strong correlations were observed between cells and tumors. PAM50 gene expression differentiated them into four major breast cancer subtypes: Luminal A and B, HER2amp, and Basal-like in both cells and tumors partially. Genomic CNVs patterns were observed between tumors and cells across chromosomes in general. High C > T and C > G trans-version rates were observed in both cells and tumors, while the cells had slightly higher somatic mutation rates than tumors. Clustering analysis on protein expression data can reasonably recover the breast cancer subtypes in cell lines and tumors. Although the drug-targeted proteins ER/PR and interesting mTOR/GSK3/TS2/PDK1/ER_P118 cluster had shown the consistent patterns between cells and tumor, low protein-based correlations were observed between cells and tumors. The expression consistency of mRNA verse protein between cell line and tumors reaches 0.7076. These important drug targets in breast cancer, ESR1, PGR, HER2, EGFR and AR have a high similarity in mRNA and protein variation in both tumors and cell lines. GATA3 and RP56KB1 are two promising drug targets for breast cancer. A total score developed from the four correlations among four molecular profiles suggests that cell lines, BT483, T47D and MDAMB453 have the highest similarity with tumors.ConclusionsThe integrated data from across these multiple platforms demonstrates the existence of the similarity and dissimilarity of molecular features between breast cancer tumors and cell lines. The cell lines only mirror some but not all of the molecular properties of primary tumors. The study results add more evidence in selecting cell line models for breast cancer research.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2911-z) contains supplementary material, which is available to authorized users.

We conducted a systematic study of top susceptibility variants from a genome-wide association (GWA) study of Bipolar Disorder to gain insight into the functional consequences of genetic variation influencing disease risk. We report here the results of experiments to explore the effects of these susceptibility variants on DNA methylation and mRNA expression in human cerebellum samples. Among the top susceptibility variants, we identified an enrichment of cis regulatory loci on mRNA expression (eQTLs), and a significant excess of quantitative trait loci for DNA CpG methylation, hereafter referred to as mQTLs. Bipolar Disorder susceptibility variants that cis-regulate both cerebellar expression and methylation of the same gene are a very small proportion of Bipolar Disorder susceptibility variants. This finding suggests that mQTLs and eQTLs provide orthogonal ways of functionally annotating genetic variation within the context of studies of pathophysiology in brain. No lymphocyte mQTL enrichment was found, suggesting that mQTL enrichment was specific to the cerebellum, in contrast to eQTLs. Separately, we found that using mQTL information to restrict the number of SNPs studied enhances our ability to detect a significant association. With this restriction a priori informed by the observed functional enrichment, we identified a significant association (rs12618769, Pbonferroni<0.05) from two other GWA studies (TGen+GAIN; 2,191 cases and 1,434 controls) of Bipolar Disorder, which we replicated in an independent GWA study (WTCCC). Collectively, our findings highlight the importance of integrating functional annotation of genetic variants for gene expression and DNA methylation to advance biological understanding of Bipolar Disorder.

An overall burden of rare structural genomic variants has not been reported in bipolar disorder (BD), although there have been reports of cases with microduplication and microdeletion. Here, we present a genome-wide copy number variant (CNV) survey of 1001 cases and 1034 controls using the Affymetrix single nucleotide polymorphism (SNP) 6.0 SNP and CNV platform. Singleton deletions (deletions that appear only once in the dataset) more than 100 kb in length are present in 16.2% of BD cases in contrast to 12.3% of controls (permutation P = 0.007). This effect was more pronounced for age at onset of mania p18 years old. Our results strongly suggest that BD can result from the effects of multiple rare structural variants.

Schizophrenia and bipolar disorder are highly heritable psychiatric disorders. Associated genetic and gene expression changes have been identified, but many have not been replicated and have unknown functions. We identified groups of genes whose expressions varied together, i.e. co-expression modules, then tested them for association with schizophrenia. Using Weighted Gene Co-expression Network Analysis, we show that two modules were differentially expressed in patients versus controls. One, up-regulated in cerebral cortex, was enriched with neuron differentiation and neuron development genes, as well as disease GWAS genetic signals; the second, altered in cerebral cortex and cerebellum, was enriched with genes involved in neuron protection functions. The findings were preserved in five expression data sets, including sets from three brain regions, from a different microarray platform, and from bipolar disorder patients. From those observations, we propose neuron differentiation and development pathways may be involved in etiologies of both schizophrenia and bipolar disorder, and neuron protection function participates in pathological process of the diseases.