Comprehensive analysis of DNA-methylation in mammalian tissues using MeDIP-chip

Genome-wide mapping of epigenetic changes is essential for understanding the mechanisms involved in gene regulation during cell differentiation and embryonic development. DNA-methylation is one of these key epigenetic marks that is directly linked to gene expression is. Methylated DNA immunoprecipitation (MeDIP) is a recently devised method used to determine the distribution of DNA-methylation within functional regions (e.g., promoters) or in the entire genome robustly and cost-efficiently. This approach is based on the enrichment of methylated DNA with an antibody that specifically binds to 5-methyl-cytosine and can be combined with PCR, microarrays or high-throughput sequencing. This article outlines the experimental procedure of MeDIP-chip and provides a comprehensive summary of quality control strategies and primary data analysis.     

Systematic Genetic Analysis Identifies Cis-eQTL Target Genes Associated with Glioblastoma Patient Survival

Prior expression quantitative trait locus (eQTL) studies have demonstrated heritable variation determining differences in gene expression. The majority of eQTL studies were based on cell lines and normal tissues. We performed cis-eQTL analysis using glioblastoma multiforme (GBM) data sets obtained from The Cancer Genome Atlas (TCGA) to systematically investigate germline variation’s contribution to tumor gene expression levels. We identified 985 significant cis-eQTL associations (FDR<0.05) mapped to 978 SNP loci and 159 unique genes. Approximately 57% of these eQTLs have been previously linked to the gene expression in cell lines and normal tissues; 43% of these share cis associations known to be associated with functional annotations. About 25% of these cis-eQTL associations are also common to those identified in Breast Cancer from a recent study. Further investigation of the relationship between gene expression and patient clinical information identified 13 eQTL genes whose expression level significantly correlates with GBM patient survival (p<0.05). Most of these genes are also differentially expressed in tumor samples and organ-specific controls (p<0.05). Our results demonstrated a significant relationship of germline variation with gene expression levels in GBM. The identification of eQTLs-based expression associated survival might be important to the understanding of genetic contribution to GBM cancer prognosis.     

Comparative genome-wide DNA methylation analysis of colorectal tumor and matched normal tissues

Aberrant DNA methylation often occurs in colorectal cancer (CRC). In our study we applied a genome-wide DNA methylation analysis approach, MethylCap-seq, to map the differentially methylated regions (DMRs) in 24 tumors and matched normal colon samples. In total, 2687 frequently hypermethylated and 468 frequently hypomethylated regions were identified, which include potential biomarkers for CRC diagnosis. Hypermethylation in the tumor samples was enriched at CpG islands and gene promoters, while hypomethylation was distributed throughout the genome. Using epigenetic data from human embryonic stem cells, we show that frequently hypermethylated regions coincide with bivalent loci in human embryonic stem cells. DNA methylation is commonly thought to lead to gene silencing; however, integration of publically available gene expression data indicates that 75% of the frequently hypermethylated genes were most likely already lowly or not expressed in normal tissue. Collectively, our study provides genome-wide DNA methylation maps of CRC, comprehensive lists of DMRs, and gives insights into the role of aberrant DNA methylation in CRC formation.     

Aberrant Gene Expression in Humans

Gene expression as an intermediate molecular phenotype has been a focus of research interest. In particular, studies of expression quantitative trait loci (eQTL) have offered promise for understanding gene regulation through the discovery of genetic variants that explain variation in gene expression levels. Existing eQTL methods are designed for assessing the effects of common variants, but not rare variants. Here, we address the problem by establishing a novel analytical framework for evaluating the effects of rare or private variants on gene expression. Our method starts from the identification of outlier individuals that show markedly different gene expression from the majority of a population, and then reveals the contributions of private SNPs to the aberrant gene expression in these outliers. Using population-scale mRNA sequencing data, we identify outlier individuals using a multivariate approach. We find that outlier individuals are more readily detected with respect to gene sets that include genes involved in cellular regulation and signal transduction, and less likely to be detected with respect to the gene sets with genes involved in metabolic pathways and other fundamental molecular functions. Analysis of polymorphic data suggests that private SNPs of outlier individuals are enriched in the enhancer and promoter regions of corresponding aberrantly-expressed genes, suggesting a specific regulatory role of private SNPs, while the commonly-occurring regulatory genetic variants (i.e., eQTL SNPs) show little evidence of involvement. Additional data suggest that non-genetic factors may also underlie aberrant gene expression. Taken together, our findings advance a novel viewpoint relevant to situations wherein common eQTLs fail to predict gene expression when heritable, rare inter-individual variation exists. The analytical framework we describe, taking into consideration the reality of differential phenotypic robustness, may be valuable for investigating complex traits and conditions.     

Comparative genome-wide DNA methylation analysis of colorectal tumor and matched normal tissues

Aberrant DNA methylation often occurs in colorectal cancer (CRC). In our study we applied a genome-wide DNA methylation analysis approach, MethylCap-seq, to map the differentially methylated regions (DMRs) in 24 tumors and matched normal colon samples. In total, 2687 frequently hypermethylated and 468 frequently hypomethylated regions were identified, which include potential biomarkers for CRC diagnosis. Hypermethylation in the tumor samples was enriched at CpG islands and gene promoters, while hypomethylation was distributed throughout the genome. Using epigenetic data from human embryonic stem cells, we show that frequently hypermethylated regions coincide with bivalent loci in human embryonic stem cells. DNA methylation is commonly thought to lead to gene silencing; however, integration of publically available gene expression data indicates that 75% of the frequently hypermethylated genes were most likely already lowly or not expressed in normal tissue. Collectively, our study provides genome-wide DNA methylation maps of CRC, comprehensive lists of DMRs, and gives insights into the role of aberrant DNA methylation in CRC formation.     

Epigenomic profiling reveals DNA-methylation changes associated with major psychosis

Epigenetic misregulation is consistent with various non-Mendelian features of schizophrenia and bipolar disorder. To date, however, few studies have investigated the role of DNA methylation in major psychosis, and none have taken a genome-wide epigenomic approach. In this study we used CpG-island microarrays to identify DNA-methylation changes in the frontal cortex and germline associated with schizophrenia and bipolar disorder. In the frontal cortex we find evidence for psychosis-associated DNA-methylation differences in numerous loci, including several involved in glutamatergic and GABAergic neurotransmission, brain development, and other processes functionally linked to disease etiology. DNA-methylation changes in a significant proportion of these loci correspond to reported changes of steady-state mRNA level associated with psychosis. Gene-ontology analysis highlighted epigenetic disruption to loci involved in mitochondrial function, brain development, and stress response. Methylome network analysis uncovered decreased epigenetic modularity in both the brain and the germline of affected individuals, suggesting that systemic epigenetic dysfunction may be associated with major psychosis. We also report evidence for a strong correlation between DNA methylation in the MEK1 gene promoter region and lifetime antipsychotic use in schizophrenia patients. Finally, we observe that frontal-cortex DNA methylation in the BDNF gene is correlated with genotype at a nearby nonsynonymous SNP that has been previously associated with major psychosis. Our data are consistent with the epigenetic theory of major psychosis and suggest that DNA-methylation changes are important to the etiology of schizophrenia and bipolar disorder.     

Genomic imprinting in mammals

A review of the data on the mechanisms and effects of genomic imprinting, an epigenetic phenomenon regulating the development in placentate mammals, is presented. In contrast to the majority of gene loci with biallelic expression, the expression of imprinted loci is monoallelic. In humans and mice, more than 300 imprinted loci have been identified, in which maternal or paternal alleles may either be expressed or be found in a repressed state during ontogeny. Imprinting is established during gametogenesis, and the repression of an allele of the imprinted locus is determined by methylation of the key regulatory element of this allele. Both the maternal and paternal chromosome sets are required for normal development in mammals. This is why parthenogenesis and androgenesis in these animals are impossible in nature. As a result of differential gene expression of many imprinted loci, the balance of gene activity is established, which is necessary for normal proliferation and differentiation of various cell clones in embryogenesis. Many human developmental abnormalities and syndromes are determined by defective genomic imprinting. In particular, the loss of imprints, which is followed by the occurrence of biallelic expression of some imprinted loci, may cause malignant tumors.     

Parent-of-origin specific QTL--a possibility towards understanding reciprocal effects in chicken and the origin of imprinting

Reciprocal effects for sexual maturity, egg production, egg quality traits and viability are well known in poultry crosses. They have been used in an optimal way to form profitable production hybrids. These effects have been hypothesized to originate from sex-linked genes, maternal effects or a combination of both. However, these may not be the only explanations for reciprocal effects. Recent mapping of quantitative trait loci (QTL) has revealed autosomal areas with parent-of-origin specific effects in the chicken. In mammals, parental imprinting, i.e. the specifically regulated expression of either maternal or paternal allele in the offspring, is the main cause of such effects. The most commonly accepted hypothesis for the origin of imprinting, the conflict hypothesis, assumes a genetic conflict of interest between the maternal and paternal genomes regarding the allocation of resources to the offspring. It also intrinsically implies that imprinting should not occur in oviparous taxa. However, new molecular genetic information has raised a need to review the possible involvement of imprinting or some related phenomena as a putative cause of reciprocal effects in poultry. Comparative mapping provides strong evidence for the conservation of orthologous imprinted gene clusters on chicken macrochromosomes. Furthermore, these gene clusters exhibit asynchronous DNA replication, an epigenetic mark specific for all imprinted regions. It has been proposed that these intrinsic chromosomal properties have been important for the evolution of imprinted gene expression in the mammalian lineage. Many of the mapped parent-of-origin specific QTL effects in chicken locate in or close to these conserved regions that show some of the basic features involved in monoallelic expression. If monoallelic expression in these regions would be observed in birds, the actual mechanism and cause may be different from the imprinting that evolved later in the mammalian lineage. In this review we discuss recent molecular genetic results that may provide tools for understanding of reciprocal differences in poultry breeding and the evolution of imprinting.     

Allozyme polymorphisms in tetraploid potato gene pools and the effect on human selection

The need for broadening a crop’s genetic base may be determined by comparing allele frequencies within the gene pools of farmer selections in their centers of diversity with that of modern breeding populations. The genetic structure of Andean and Chilean potato farmer selections was investigated with the aid of nine isozymes, which have been studied in detail and used to characterize North American cultivars and advanced breeding lines. These isozymes are associated with the most-important agronomic or quality characters in the North American gene pool. By comparing these data with previous analyses of the North American gene pool, allozyme frequency changes for nine loci were monitored. Allozyme frequency changes were not always due to genetic drift, but resulted also from directional selection of isozyme marker linked quantitative trait loci (QTLs) affecting agronomic or quality characters. Changes in allozyme frequency can also occur as a consequence of pleiotropy, i.e. the isozyme itself may be involved in the expression of a phenotype. These allozyme frequency changes may reflect the manipulation of the potato genome by breeders. There were allozymes in some North American cultivars that were not observed in the farmer selections from the Andes and Chile. This confirms that breeders have already introgressed exotic genes from wild and other primitive cultivated tuber-bearing Solanum species. On this basis, the need for broadening the genetic base for specific chromosomes (or chromosome regions) should be based on analysis with these and other genetic markers available in potato. Received: 20 November 2000 / Accepted: 27 December 2000     

Altered Gene Expression Associated with microRNA Binding Site Polymorphisms

Allele-specific gene expression associated with genetic variation in regulatory regions can play an important role in the development of complex traits. We hypothesized that polymorphisms in microRNA (miRNA) response elements (MRE-SNPs) that either disrupt a miRNA binding site or create a new miRNA binding site can affect the allele-specific expression of target genes. By integrating public expression quantitative trait locus (eQTL) data, miRNA binding site predictions, small RNA sequencing, and Argonaute crosslinking immunoprecipitation (AGO-CLIP) datasets, we identified genetic variants that can affect gene expression by modulating miRNA binding efficiency. We also identified MRE-SNPs located in regions associated with complex traits, indicating possible causative mechanisms associated with these loci. The results of this study expand the current understanding of gene expression regulation and help to interpret the mechanisms underlying eQTL effects.     

Prediction of human disease genes by human-mouse conserved coexpression analysis

Background

Even in the post-genomic era, the identification of candidate genes within loci associated with human genetic diseases is a very demanding task, because the critical region may typically contain hundreds of positional candidates. Since genes implicated in similar phenotypes tend to share very similar expression profiles, high throughput gene expression data may represent a very important resource to identify the best candidates for sequencing. However, so far, gene coexpression has not been used very successfully to prioritize positional candidates.

Methodology/Principal Findings

We show that it is possible to reliably identify disease-relevant relationships among genes from massive microarray datasets by concentrating only on genes sharing similar expression profiles in both human and mouse. Moreover, we show systematically that the integration of human-mouse conserved coexpression with a phenotype similarity map allows the efficient identification of disease genes in large genomic regions. Finally, using this approach on 850 OMIM loci characterized by an unknown molecular basis, we propose high-probability candidates for 81 genetic diseases.

Conclusion

Our results demonstrate that conserved coexpression, even at the human-mouse phylogenetic distance, represents a very strong criterion to predict disease-relevant relationships among human genes.     

Virus-derived variation in diverse human genomes

Acquisition of genetic material from viruses by their hosts can generate inter-host structural genome variation. We developed computational tools enabling us to study virus-derived structural variants (SVs) in population-scale whole genome sequencing (WGS) datasets and applied them to 3,332 humans. Although SVs had already been cataloged in these subjects, we found previously-overlooked virus-derived SVs. We detected non-germline SVs derived from squirrel monkey retrovirus (SMRV), human immunodeficiency virus 1 (HIV-1), and human T lymphotropic virus (HTLV-1); these variants are attributable to infection of the sequenced lymphoblastoid cell lines (LCLs) or their progenitor cells and may impact gene expression results and the biosafety of experiments using these cells. In addition, we detected new heritable SVs derived from human herpesvirus 6 (HHV-6) and human endogenous retrovirus-K (HERV-K). We report the first solo-direct repeat (DR) HHV-6 likely to reflect DR rearrangement of a known full-length endogenous HHV-6. We used linkage disequilibrium between single nucleotide variants (SNVs) and variants in reads that align to HERV-K, which often cannot be mapped uniquely using conventional short-read sequencing analysis methods, to locate previously-unknown polymorphic HERV-K loci. Some of these loci are tightly linked to trait-associated SNVs, some are in complex genome regions inaccessible by prior methods, and some contain novel HERV-K haplotypes likely derived from gene conversion from an unknown source or introgression. These tools and results broaden our perspective on the coevolution between viruses and humans, including ongoing virus-to-human gene transfer contributing to genetic variation between humans.     

Congruent population structure across paralogous and nonparalogous loci in Salish Sea chum salmon (Oncorhynchus keta)

Whole‐genome duplications are major evolutionary events with a lasting impact on genome structure. Duplication events complicate genetic analyses as paralogous sequences are difficult to distinguish; consequently, paralogs are often excluded from studies. The effects of an ancient whole‐genome duplication (approximately 88 MYA) are still evident in salmonids through the persistence of numerous paralogous gene sequences and partial tetrasomic inheritance. We use restriction site‐associated DNA sequencing on 10 collections of chum salmon from the Salish Sea in the USA and Canada to investigate genetic diversity and population structure in both tetrasomic and rediploidized regions of the genome. We use a pedigree and high‐density linkage map to identify paralogous loci and to investigate genetic variation across the genome. By applying multivariate statistical methods, we show that it is possible to characterize paralogous loci and that they display similar patterns of population structure as the diploidized portion of the genome. We find genetic associations with the adaptively important trait of run‐timing in both sets of loci. By including paralogous loci in genome scans, we can observe evolutionary signals in genomic regions that have routinely been excluded from population genetic studies in other polyploid‐derived species.     

Genetic susceptibility to autoimmune disorders: clues from gene association and gene expression studies

Susceptibility to autoimmune disorders results from the interaction of multiple genetic factors that regulate the threshold of autoreactivity. Genome-wide microsatellite screens and large-scale single nucleotide polymorphism (SNP) association studies have identified chromosomal loci that are associated with specific disorders including systemic lupus erythematosus, rheumatoid arthritis, juvenile arthritis, multiple sclerosis, and diabetes. Numerous candidate gene association studies have in turn investigated the association of specific genes within these chromosomal regions, with susceptibility to autoimmune diseases (e.g. FcgammaReceptors, TYK2 and systemic lupus). More recently, large-scale differential gene expression studies performed on selected tissues from patients with autoimmune disorders, have led to the identification of gene signatures associated with the activation of specific pathways in these diseases (e.g. interferon signature in lupus). In the future, integrated analyses of gene (and protein) expression together with SNP data will allow us to sketch an intelligible picture of the genesis of autoimmunity in humans. This review sets out to illustrate how the most recent advances in the field of systemic lupus erythematosus, rheumatoid arthritis and juvenile arthritis have led to a better understanding of these disorders.     

Biallelic polymorphism in the intron region of beta-tubulin gene of Cryptosporidium parasites

Nucleotide sequencing of polymerase chain reaction amplified intron region of the Cryptosporidium parvum beta-tubulin gene in 26 human and 15 animal isolates revealed distinct genetic polymorphism between the human and bovine genotypes. The separation of 2 genotypes of C. parvum is in agreement with our previous genotyping data based on the thrombospondin-related adhesion protein (TRAP-C2) gene, indicating these genotype characteristics are linked at 2 genetic loci. Characterization of Cryptosporidium muris and Cryptosporidium serpentis has further shown that non-parvum Cryptosporidium parasites have beta-tubulin intron sequences identical to bovine genotype of C. parvum. Thus, results of this study confirm the lineage of 2 genotypes of C. parvum at 2 genetic loci and suggest a need for extensive characterization of various Cryptosporidium spp.