High-resolution analysis of cytosine methylation in ancient DNA

Epigenetic changes to gene expression can result in heritable phenotypic characteristics that are not encoded in the DNA itself, but rather by biochemical modifications to the DNA or associated chromatin proteins. Interposed between genes and environment, these epigenetic modifications can be influenced by environmental factors to affect phenotype for multiple generations. This raises the possibility that epigenetic states provide a substrate for natural selection, with the potential to participate in the rapid adaptation of species to changes in environment. Any direct test of this hypothesis would require the ability to measure epigenetic states over evolutionary timescales. Here we describe the first single-base resolution of cytosine methylation patterns in an ancient mammalian genome, by bisulphite allelic sequencing of loci from late Pleistocene Bison priscus remains. Retrotransposons and the differentially methylated regions of imprinted loci displayed methylation patterns identical to those derived from fresh bovine tissue, indicating that methylation patterns are preserved in the ancient DNA. Our findings establish the biochemical stability of methylated cytosines over extensive time frames, and provide the first direct evidence that cytosine methylation patterns are retained in DNA from ancient specimens. The ability to resolve cytosine methylation in ancient DNA provides a powerful means to study the role of epigenetics in evolution.     

A segmental maximum a posteriori approach to genome-wide copy number profiling

MOTIVATION: Copy number profiling methods aim at assigning DNA copy numbers to chromosomal regions using measurements from microarray-based comparative genomic hybridizations. Among the proposed methods to this end, Hidden Markov Model (HMM)-based approaches seem promising since DNA copy number transitions are naturally captured in the model. Current discrete-index HMM-based approaches do not, however, take into account heterogeneous information regarding the genomic overlap between clones. Moreover, the majority of existing methods are restricted to chromosome-wise analysis. RESULTS: We introduce a novel Segmental Maximum A Posteriori approach, SMAP, for DNA copy number profiling. Our method is based on discrete-index Hidden Markov Modeling and incorporates genomic distance and overlap between clones. We exploit a priori information through user-controllable parameterization that enables the identification of copy number deviations of various lengths and amplitudes. The model parameters may be inferred at a genome-wide scale to avoid overfitting of model parameters often resulting from chromosome-wise model inference. We report superior performances of SMAP on synthetic data when compared with two recent methods. When applied on our new experimental data, SMAP readily recognizes already known genetic aberrations including both large-scale regions with aberrant DNA copy number and changes affecting only single features on the array. We highlight the differences between the prediction of SMAP and the compared methods and show that SMAP accurately determines copy number changes and benefits from overlap consideration.     

Discovering tumor suppressor genes through genome-wide copy number analysis

Classical tumor suppressor gene discovery has largely involved linkage analysis and loss-of-heterozygosity (LOH) screens, followed by detailed mapping of relatively large chromosomal regions. Subsequent efforts made use of genome-wide PCR-based methods to detect rare homozygous deletions. More recently, high-resolution genomic arrays have been applied to cancer gene discovery. However, accurate characterization of regions of genomic loss is particularly challenging due to sample heterogeneity, the small size of deleted regions and the high frequency of germline copy number polymorphisms. Here, we review the application of genome-wide copy number analysis to the specific problem of identifying tumor suppressor genes.     

CONAN: copy number variation analysis software for genome-wide association studies

Background  

Genome-wide association studies (GWAS) based on single nucleotide polymorphisms (SNPs) revolutionized our perception of the genetic regulation of complex traits and diseases. Copy number variations (CNVs) promise to shed additional light on the genetic basis of monogenic as well as complex diseases and phenotypes. Indeed, the number of detected associations between CNVs and certain phenotypes are constantly increasing. However, while several software packages support the determination of CNVs from SNP chip data, the downstream statistical inference of CNV-phenotype associations is still subject to complicated and inefficient in-house solutions, thus strongly limiting the performance of GWAS based on CNVs.     

Optimizing copy number variation analysis using genome-wide short sequence oligonucleotide arrays

The detection of copy number variants (CNV) by array-based platforms provides valuable insight into understanding human diversity. However, suboptimal study design and data processing negatively affect CNV assessment. We quantitatively evaluate their impact when short-sequence oligonucleotide arrays are applied (Affymetrix Genome-Wide Human SNP Array 6.0) by evaluating 42 HapMap samples for CNV detection. Several processing and segmentation strategies are implemented, and results are compared to CNV assessment obtained using an oligonucleotide array CGH platform designed to query CNVs at high resolution (Agilent). We quantitatively demonstrate that different reference models (e.g. single versus pooled sample reference) used to detect CNVs are a major source of inter-platform discrepancy (up to 30%) and that CNVs residing within segmental duplication regions (higher reference copy number) are significantly harder to detect (P < 0.0001). After adjusting Affymetrix data to mimic the Agilent experimental design (reference sample effect), we applied several common segmentation approaches and evaluated differential sensitivity and specificity for CNV detection, ranging 39–77% and 86–100% for non-segmental duplication regions, respectively, and 18–55% and 39–77% for segmental duplications. Our results are relevant to any array-based CNV study and provide guidelines to optimize performance based on study-specific objectives.     

High-resolution array-CGH profiling of germline and tumor-specific copy number alterations on chromosome 22 in patients affected with schwannomas

Schwannomas may develop sporadically or in association with NF2 and schwannomatosis. The fundamental aberration in schwannomas is the bi-allelic inactivation of the NF2 gene. However, clinical and molecular data suggest that these tumors share a common pathogenetic mechanism related to as yet undefined 22q-loci. Linkage studies in schwannomatosis, a condition related to NF2, have defined a candidate 22q-locus and excluded the NF2 gene as the causative germline mutation. Thus, analysis of aberrations in schwannomas may lead to the identification of putative gene(s) involved in the development of schwannoma/schwannomatosis. We profiled a series of 88 schwannomas and constitutional DNA using a tiling path chromosome 22 array. Array-CGH is a suitable method for high-resolution discrimination between germline and tumor-specific aberrations. Previously reported frequencies of 22q-associated deletions in schwannomas display large discrepancies, ranging from 30% to 80%. We detected heterozygous deletions in 53% of schwannomas and the predominant pattern was monosomy 22. In addition, three tumors displayed terminal deletions and four harbored overlapping interstitial deletions of various sizes encompassing the NF2 gene. When profiling constitutional DNA, we identified eight loci that were affected by copy number variation (CNV). Some of the identified CNVs may not be phenotypically neutral and the possible role of these CNVs in the pathogenesis of schwannomas should be studied further. We observed a correlation between the breakpoint position, present in tumor and/or constitutional DNA and the location of segmental duplications. This association implicates these unstable regions in rearrangements occurring both in meiosis and mitosis.     

Functional profiling and gene expression analysis of chromosomal copy number alterations

Contrarily to the traditional view in which only one or a few key genes were supposed to be the causative factors of diseases, we discuss the importance of considering groups of functionally related genes in the study of pathologies characterised by chromosomal copy number alterations. Recent observations have reported the existence of regions in higher eukaryotic chromosomes (including humans) containing genes of related function that show a high degree of coregulation. Copy number alterations will consequently affect to clusters of functionally related genes, which will be the final causative agents of the diseased phenotype, in many cases. Therefore, we propose that the functional profiling of the regions affected by copy number alterations must be an important aspect to take into account in the understanding of this type of pathologies. To illustrate this, we present an integrated study of DNA copy number variations, gene expression along with the functional profiling of chromosomal regions in a case of multiple myeloma.     

Genome-wide combination profiling of copy number and methylation offers an approach for deciphering misregulation and development in cancer cells

Copy number changes and DNA methylation alterations are crucial to gene regulation in mammals. Recently, a number of microarray studies have been based on copy number and DNA methylation alterations in order to find clinical biomarkers of carcinogenesis. In this study, we attempted to combine profiles of copy number and methylation patterns in four human cancer cell lines using BAC microarray-based approaches and we detected several clinically important genes which showed genetic and epigenetic relationships. Within the clones analyzed, many contained cancer-related genes involved in cell cycle regulation, cell division, signal transduction, tumor necrosis, cell differentiation, and cell proliferation. One clone included the FHIT gene, a well-known tumor suppressor gene involved in various human cancers. Our combined profiling techniques may provide a method by which to find new clinicopathologic cancer biomarkers, and support the idea that systematic characterization of the genetic and epigenetic events in cancers may rapidly become a reality.     

Common methods for cytosine methylation analysis in DNA

The review considers the methods most commonly used to detect DNA methylation, their advantages, potential limitations, and selection for various purposes. A detailed protocol is described for bisulfite treatment, which is used as a preliminary step in the majority of DNA methylation assays.     

Accurate and objective copy number profiling using real-time quantitative PCR

Copy number changes are known to be involved in numerous human genetic disorders. In this context, qPCR-based copy number screening may serve as the method of choice for targeted screening of the relevant disease genes and their surrounding regulatory landscapes. qPCR has many advantages over alternative methods, such as its low consumable and instrumentation costs, fast turnaround and assay development time, high sensitivity and open format (independent of a single supplier). In this chapter we provide all relevant information for a successfully implement of qPCR-based copy number analysis. We emphasize the significance of thorough in silico and empirical validation of the primers, the need for a well thought-out experiment design, and the importance of quality controls along the entire workflow. Furthermore, we suggest an appropriate and practical way to calculate copy numbers and to objectively interpret the results.The provided guidelines will most certainly improve the quality and reliability of your qPCR-based copy number screening.     

Promoter methylation and transgene copy numbers predict unstable protein production in recombinant Chinese hamster ovary cell lines

Mammalian cell lines for recombinant protein production need to maintain productivity over extended cultivation times. Long-term stability studies are time and resource intensive, but are widely performed to identify and eliminate unstable candidates during cell line development. Production instability of manufacturing cell lines can be associated with methylation and silencing of the heterologous promoter. We have identified CpG dinucleotides within the human cytomegalovirus major immediate early promoter/enhancer (hCMV-MIE) that are frequently methylated in unstable antibody-producing Chinese hamster ovary (CHO) cell lines. We have established methylation-specific real-time qPCR for the rapid and sensitive measurement of hCMV-MIE methylation in multiple cell lines and provide evidence that hCMV-MIE methylation and transgene copy numbers can be used as early markers to predict production instability of recombinant CHO cell lines. These markers should provide the opportunity to enrich stable producers early in cell line development and allow developers to put more emphasis on other criteria, such as product quality and bioprocess robustness.     

Gene copy number and cell cycle arrest

The cell cycle is an orderly sequence of events which ultimately lead to the division of a single cell into two daughter cells. In the case of DNA damage by radiation or chemicals, the damage checkpoints in the G1 and G2 phases of the cell cycle are activated. This results in an arrest of the cell cycle so that the DNA damage can be repaired. Once this is done, the cell continues with its usual cycle of activity. We study a mathematical model of the DNA damage checkpoint in the G2 phase which arrests the transition from the G2 to the M (mitotic) phase of the cell cycle. The tumor suppressor protein p53 plays a key role in activating the pathways leading to cell cycle arrest in mammalian systems. If the DNA damage is severe, the p53 proteins activate other pathways which bring about apoptosis, i.e., programmed cell death. Loss of the p53 gene results in the proliferation of cells containing damaged DNA, i.e., in the growth of tumors which may ultimately become cancerous. There is some recent experimental evidence which suggests that the mutation of a single copy of the p53 gene (in the normal cell each gene has two identical copies) is sufficient to trigger the formation of tumors. We study the effect of reducing the gene copy number of the p53 and two other genes on cell cycle arrest and obtain results consistent with experimental observations.     

Methylation-specific MLPA (MS-MLPA): simultaneous detection of CpG methylation and copy number changes of up to 40 sequences

Copy number changes and CpG methylation of various genes are hallmarks of tumor development but are not yet widely used in diagnostic settings. The recently developed multiplex ligation-dependent probe amplification (MLPA) method has increased the possibilities for multiplex detection of gene copy number aberrations in a routine laboratory. Here we describe a novel robust method: the methylation-specific MLPA (MS-MLPA) that can detect changes in both CpG methylation as well as copy number of up to 40 chromosomal sequences in a simple reaction. In MS-MLPA, the ligation of MLPA probe oligonucleotides is combined with digestion of the genomic DNA–probe hybrid complexes with methylation-sensitive endonucleases. Digestion of the genomic DNA–probe complex, rather than double-stranded genomic DNA, allowed the use of DNA derived from the formalin treated paraffin-embedded tissue samples, enabling retrospective studies. To validate this novel method, we used MS-MLPA to detect aberrant methylation in DNA samples of patients with Prader–Willy syndrome, Angelman syndrome or acute myeloid leukemia.     

CNAmet: an R package for integrating copy number, methylation and expression data

SUMMARY: Gene copy number and DNA methylation alterations are key regulators of gene expression in cancer. Accordingly, genes that show simultaneous methylation, copy number and expression alterations are likely to have a key role in tumor progression. We have implemented a novel software package (CNAmet) for integrative analysis of high-throughput copy number, DNA methylation and gene expression data. To demonstrate the utility of CNAmet, we use copy number, DNA methylation and gene expression data from 50 glioblastoma multiforme and 188 ovarian cancer primary tumor samples. Our results reveal a synergistic effect of DNA methylation and copy number alterations on gene expression for several known oncogenes as well as novel candidate oncogenes. AVAILABILITY: CNAmet R-package and user guide are freely available under GNU General Public License at http://csbi.ltdk.helsinki.fi/CNAmet.     

MethylRAD: a simple and scalable method for genome-wide DNA methylation profiling using methylation-dependent restriction enzymes

Characterization of dynamic DNA methylomes in diverse phylogenetic groups has attracted growing interest for a better understanding of the evolution of DNA methylation as well as its function and biological significance in eukaryotes. Sequencing-based methods are promising in fulfilling this task. However, none of the currently available methods offers the ‘perfect solution’, and they have limitations that prevent their application in the less studied phylogenetic groups. The recently discovered Mrr-like enzymes are appealing for new method development, owing to their ability to collect 32-bp methylated DNA fragments from the whole genome for high-throughput sequencing. Here, we have developed a simple and scalable DNA methylation profiling method (called MethylRAD) using Mrr-like enzymes. MethylRAD allows for de novo (reference-free) methylation analysis, extremely low DNA input (e.g. 1 ng) and adjustment of tag density, all of which are still unattainable for most widely used methylation profiling methods such as RRBS and MeDIP. We performed extensive analyses to validate the power and accuracy of our method in both model (plant Arabidopsis thaliana) and non-model (scallop Patinopecten yessoensis) species. We further demonstrated its great utility in identification of a gene (LPCAT1) that is potentially crucial for carotenoid accumulation in scallop adductor muscle. MethylRAD has several advantages over existing tools and fills a void in the current epigenomic toolkit by providing a universal tool that can be used for diverse research applications, e.g. from model to non-model species, from ordinary to precious samples and from small to large genomes, but at an affordable cost.     

Minimum error calibration and normalization for genomic copy number analysis

BackgroundCopy number variations (CNV) are regional deviations from the normal autosomal bi-allelic DNA content. While germline CNVs are a major contributor to genomic syndromes and inherited diseases, the majority of cancers accumulate extensive “somatic” CNV (sCNV or CNA) during the process of oncogenetic transformation and progression. While specific sCNV have closely been associated with tumorigenesis, intriguingly many neoplasias exhibit recurrent sCNV patterns beyond the involvement of a few cancer driver genes. Currently, CNV profiles of tumor samples are generated using genomic micro-arrays or high-throughput DNA sequencing. Regardless of the underlying technology, genomic copy number data is derived from the relative assessment and integration of multiple signals, with the data generation process being prone to contamination from several sources. Estimated copy number values have no absolute or strictly linear correlation to their corresponding DNA levels, and the extent of deviation differs between sample profiles, which poses a great challenge for data integration and comparison in large scale genome analysis.ResultsIn this study, we present a novel method named “Minimum Error Calibration and Normalization for Copy Numbers Analysis” (Mecan4CNA). It only requires CNV segmentation files as input, is platform independent, and has a high performance with limited hardware requirements. For a given multi-sample copy number dataset, Mecan4CNA can batch-normalize all samples to the corresponding true copy number levels of the main tumor clones. Experiments of Mecan4CNA on simulated data showed an overall accuracy of 93% and 91% in determining the normal level and single copy alteration (i.e. duplication or loss of one allele), respectively. Comparison of estimated normal levels and single copy alternations with existing methods and karyotyping data on the NCI-60 tumor cell line produced coherent results. To estimate the method's impact on downstream analyses, we performed GISTIC analyses on the original and Mecan4CNA normalized data from the Cancer Genome Atlas (TCGA) where the normalized data showed prominent improvements of both sensitivity and specificity in detecting focal regions.ConclusionsMecan4CNA provides an advanced method for CNA data normalization, especially in meta-analyses involving large profile numbers and heterogeneous source data quality. With its informative output and visualization options, Mecan4CNA also can improve the interpretation of individual CNA profiles. Mecan4CNA is freely available as a Python package and through its code repository on Github.     

Dissecting the genotype in syndromic intellectual disability using whole exome sequencing in addition to genome-wide copy number analysis

When a known microimbalance affecting multiple genes is detected in a patient with syndromic intellectual disability, it is usually presumed causative for all observed features. Whole exome sequencing (WES) allows questioning this assumption. In this study of three families with children affected by unexplained syndromic intellectual disability, genome-wide copy number and subsequent analyses revealed a de novo maternal 1.1 Mb microdeletion in the 14q32 imprinted region causing a paternal UPD(14)-like phenotype, and two inherited 22q11.21 microduplications of 2.5 or 2.8 Mb. In patient 1 carrying the 14q32 microdeletion, tall stature and renal malformation were unexplained by paternal UPD(14), and there was no altered DLK1 expression or unexpected methylation status. By WES and filtering with a mining tool, a novel FBN1 missense variant was found in patient 1 and his mother, who both showed clinical features of Marfan syndrome by thorough anthropometric assessment, and a novel EYA1 missense variant as a probable cause of the renal malformation in the patient. In patient 2 with the 22q11.21 microduplication syndrome, skin hypo- and hyperpigmentation and two malignancies were only partially explained. By WES, compound heterozygous BLM stop founder mutations were detected causing Bloom syndrome. In male patient 3 carrying a 22q11.21 microduplication inherited from his unaffected father, WES identified a novel missense variant in the OPHN1 X-linked intellectual disability gene inherited from the unaffected mother as a possible additional cause for developmental delay. Thus, WES seems warranted in patients carrying microdeletions or microduplications, who have unexplained clinical features or microimbalances inherited from an unaffected parent.