Simultaneous A8344G heteroplasmy and mitochondrial DNA copy number quantification in Myoclonus Epilepsy and Ragged-Red Fibers (MERRF) syndrome by a multiplex Molecular Beacon based real-time fluorescence PCR

The association of a particular mitochondrial DNA (mtDNA) mutation with different clinical phenotypes is a well-known feature of mitochondrial diseases. A simple genotype–phenotype correlation has not been found between mutation load and disease expression. Tissue and intercellular mosaicism as well as mtDNA copy number are thought to be responsible for the different clinical phenotypes. As disease expression of mitochondrial tRNA mutations is mostly in postmitotic tissues, studies to elucidate disease mechanisms need to be performed on patient material. Heteroplasmy quantitation and copy number estimation using small patient biopsy samples has not been reported before, mainly due to technical restrictions. In order to resolve this problem, we have developed a robust assay that utilizes Molecular Beacons to accurately quantify heteroplasmy levels and determine mtDNA copy number in small samples carrying the A8344G tRNALys mutation. It provides the methodological basis to investigate the role of heteroplasmy and mtDNA copy number in determining the clinical phenotypes.

PCR-Based Analysis of Mitochondrial DNA Copy Number, Mitochondrial DNA Damage, and Nuclear DNA Damage.

Because of the role that DNA damage and depletion play in human disease, it is important to develop and improve tools to assess these endpoints. This unit describes PCR-based methods to measure nuclear and mitochondrial DNA damage and copy number. Long amplicon quantitative polymerase chain reaction (LA-QPCR) is used to detect DNA damage by measuring the number of polymerase-inhibiting lesions present based on the amount of PCR amplification; real-time PCR (RT-PCR) is used to calculate genome content. In this unit, we provide step-by-step instructions to perform these assays in Homo sapiens, Mus musculus, Rattus norvegicus, Caenorhabditis elegans, Drosophila melanogaster, Danio rerio, Oryzias latipes, Fundulus grandis, and Fundulus heteroclitus, and discuss the advantages and disadvantages of these assays.

Integration of miRNA and mRNA expression with DNA copy number of Ewing sarcoma cell lines

Ewing sarcoma is an aggressive and poorly differentiated malignancy of bone and soft tissue. It primarily affects children, adolescents, and young adults, with a slight male predominance. It is characterized by a translocation between chromosomes 11 and 22 resulting in the EWSR1-FLI1fusion transcription factor. The aim of this study is to identify putative Ewing sarcoma target genes through an integrative analysis of three microarray data sets. Array comparative genomic hybridization is used to measure changes in DNA copy number, and analyzed to detect common chromosomal aberrations. mRNA and miRNA microarrays are used to measure expression of protein-coding and miRNA genes, and these results integrated with the copy number data. Chromosomal aberrations typically contain also bystanders in addition to the driving tumor suppressor and oncogenes, and integration with expression helps to identify the true targets. Correlation between expression of miRNAs and their predicted target mRNAs is also evaluated to assess the results of post-transcriptional miRNA regulation on mRNA levels. The highest frequencies of copy number gains were identified in chromosome 8, 1q, and X. Losses were most frequent in 9p21.3, which also showed an enrichment of copy number breakpoints relative to the rest of the genome. Copy number losses in 9p21.3 were found have a statistically significant effect on the expression of MTAP, but not on CDKN2A, which is a known tumor-suppressor in the same locus. MTAP was also down-regulated in the Ewing sarcoma cell lines compared to mesenchymal stem cells. Genes exhibiting elevated expression in association with copy number gains and up-regulation compared to the reference samples included DCAF7, ENO2, MTCP1, andSTK40. Differentially expressed miRNAs were detected by comparing Ewing sarcoma cell lines against mesenchymal stem cells. 21 up-regulated and 32 down-regulated miRNAs were identified, includingmiR-145, which has been previously linked to Ewing sarcoma. The EWSR1-FLI1 fusion gene represses miR-145, which in turn targets FLI1 forming a mutually repressive feedback loop. In addition higher expression linked to copy number gains and compared to mesenchymal stem cells, STK40 was also found to be a target of four different miRNAs that were all down-regulated in Ewing sarcoma cell lines compared to the reference samples. SLCO5A1 was identified as the only up-regulated gene within a frequently gained region in chromosome 8. This region was gained in over 90 % of the cell lines, and also with a higher frequency than the neighboring regions. In addition, SLCO5A1 was found to be a target of three miRNAs that were down-regulated compared to the mesenchymal stem cells.

Discovering subgroups of patients from DNA copy number data using NMF on compacted matrices

In the study of complex genetic diseases, the identification of subgroups of patients sharing similar genetic characteristics represents a challenging task, for example, to improve treatment decision. One type of genetic lesion, frequently investigated in such disorders, is the change of the DNA copy number (CN) at specific genomic traits. Non-negative Matrix Factorization (NMF) is a standard technique to reduce the dimensionality of a data set and to cluster data samples, while keeping its most relevant information in meaningful components. Thus, it can be used to discover subgroups of patients from CN profiles. It is however computationally impractical for very high dimensional data, such as CN microarray data. Deciding the most suitable number of subgroups is also a challenging problem. The aim of this work is to derive a procedure to compact high dimensional data, in order to improve NMF applicability without compromising the quality of the clustering. This is particularly important for analyzing high-resolution microarray data. Many commonly used quality measures, as well as our own measures, are employed to decide the number of subgroups and to assess the quality of the results. Our measures are based on the idea of identifying robust subgroups, inspired by biologically/clinically relevance instead of simply aiming at well-separated clusters. We evaluate our procedure using four real independent data sets. In these data sets, our method was able to find accurate subgroups with individual molecular and clinical features and outperformed the standard NMF in terms of accuracy in the factorization fitness function. Hence, it can be useful for the discovery of subgroups of patients with similar CN profiles in the study of heterogeneous diseases.

Germline DNA copy number variation in familial and early-onset breast cancer

Introduction: Genetic factors predisposing individuals to cancer remain elusive in the majority of patients with a familial or clinical history suggestive of hereditary breast cancer. Germline DNA copy number variation (CNV) has recently been implicated in predisposition to cancers such as neuroblastomas as well as prostate and colorectal cancer. We evaluated the role of germline CNVs in breast cancer susceptibility, in particular those with low population frequencies (rare CNVs), which are more likely to cause disease." Methods: Using whole-genome comparative genomic hybridization on microarrays, we screened a cohort of women fulfilling criteria for hereditary breast cancer who did not carry BRCA1/BRCA2 mutations. Results: The median numbers of total and rare CNVs per genome were not different between controls and patients. A total of 26 rare germline CNVs were identified in 68 cancer patients, however, a proportion that was significantly different (P = 0.0311) from the control group (23 rare CNVs in 100 individuals). Several of the genes affected by CNV in patients and controls had already been implicated in cancer. Conclusions: This study is the first to explore the contribution of germline CNVs to BRCA1/2-negative familial and early-onset breast cancer. The data suggest that rare CNVs may contribute to cancer predisposition in this small cohort of patients, and this trend needs to be confirmed in larger population samples.

CopywriteR: DNA copy number detection from off-target sequence data.

Current methods for detection of copy number variants (CNV) and aberrations (CNA) from targeted sequencing data are based on the depth of coverage of captured exons. Accurate CNA determination is complicated by uneven genomic distribution and non-uniform capture efficiency of targeted exons. Here we present CopywriteR, which eludes these problems by exploiting 'off-target' sequence reads. CopywriteR allows for extracting uniformly distributed copy number information, can be used without reference, and can be applied to sequencing data obtained from various techniques including chromatin immunoprecipitation and target enrichment on small gene panels. CopywriteR outperforms existing methods and constitutes a widely applicable alternative to available tools.

Clinical relevance of polymorphic DNA copy number variation (CNV) in African American women with stage I-II breast cancer

Objectives. The chief goal of this study was to analyze copy number variation (CNV) in breast cancer tumors from 25 African American women with early stage breast cancer (BC) using molecular inversion probes (MIP) in order to: (1) compare the degree of CNV in tumors compared to normal lymph nodes, and (2) determine whether gains and/or losses of genes in specific chromosomes differ between pathologic subtypes of breast cancer defined by known prognostic markers, (3) determine whether gains/losses in CN are associated with known oncogenes or tumor suppressor genes, and (4) determine whether increased gains/losses in CN for specific chromosomes were associated with differences in breast cancer recurrence. ^ Methods. Twenty to 37 nanograms of DNA extracted from 25 formalin-fixed paraffin embedded (FFPE) tumor samples and matched normal lymph nodes were added to individual tubes. Oligonucleotide probes with recognition sequences at each terminus were hybridized with a genomic target sequence to form a circular structure. Probes are released from genomic DNA obtained from FFPE samples, and those which have been correctly "circularized" in the proper allele/nucleotide reaction combination are amplified using polymerase chain reaction (PCR) primers. Amplicons were fluorescently labeled and the tag sequences released from the genome homology regions by treatment with uracil-N-glycosylase to cleave the probe at the site where uracils are present, and detected using a complementary tag array developed by Affymetrix. ^ Results. Analysis of CN gains and losses from tumors and normal tissues showed marked differences in tumors with numerous chromosomes affected. Similar changes were not observed in normal lymph nodes. When tumors were stratified into four groups based on expression or lack of expression of the estrogen receptor and HER2/neu, distinct patterns of CNV for different chromosomes were observed. Gains or losses in CN for specific chromosomes correlated with amplifications/deletions of particular oncogenes or tumor suppressor genes (i.e. such as found on chromosome 17) known to be associated with aggressive tumor phenotype and poor prognosis. There was a trend for increases in CN observed for chromosome 17 to correlate inversely with time to recurrence of BC (p=0.14 for trend). CNV was also observed for chromosomes 5, 8, 10, 11, and 16, which are known sites for several breast cancer susceptibility alleles. ^ Conclusions. This study is the first to validate the MIP technique, to correlate differences in gene expression with known prognostic tumor markers, and to correlate significant increases/decreases in CN with known tumor markers associated with prognosis. The results of this study may have far reaching public health implications towards identifying new high-risk groups based on genomic differences in CNP, both with respect to prognosis and response to therapy, and to eventually identify new therapeutic targets for prevention and treatment of this disease. ^

JK1 (FAM134B) gene and colorectal cancer : a pilot study on the gene copy number alterations and correlations with clinicopathological parameters

AIMS The aims of the study are to characterize changes in JK-1 (FAM134B) at the DNA level in colorectal adenocarcinoma and adenoma and exploring the possible correlations with clinical and pathological features. METHOD JK-1 gene DNA copy number changes were studied in 211 colorectal carcinomas, 32 colorectal adenoma and 20 colorectal non-cancer colorectal tissue samples by real-time quantitative polymerase chain reaction. The results were correlated with clinical and pathological parameters. RESULTS Colorectal adenomas were more likely to be amplified than deleted with regard to JK-1 (FAM134B) DNA copy number change. The copy number level of JK-1 (FAM134B) DNA in colorectal adenocarcinomas was significantly lower in comparison to colorectal adenomas. Changes in JK-1 (FAM134B) DNA copy number were associated with histological subtypes, and cancer stage. Lower copy numbers were associated with higher tumor stage, lymph node stage and overall pathological stage of cancer. Conversely, higher DNA copy numbers were detected more often in the mucinous adenocarcinoma. CONCLUSIONS This is the first study showing significant correlations of the JK-1 (FAM134B) gene copy number alterations with clinical and pathological features in a large cohort of pre-invasive and invasive colorectal malignancies. The changes in DNA copy number associated with progression of colorectal malignancies reflect that JK-1 (FAM134B) gene could play a role in controlling some steps in development of the invasive phenotypes.

High-resolution SNP microarray investigation of copy number variations on chromosome 18 in a control cohort

Copy number variations (CNVs) as described in the healthy population are purported to contribute significantly to genetic heterogeneity. Recent studies have described CNVs using lymphoblastoid cell lines or by application of specifically developed algorithms to interrogate previously described data. However, the full extent of CNVs remains unclear. Using high-density SNP array, we have undertaken a comprehensive investigation of chromosome 18 for CNV discovery and characterisation of distribution and association with chromosome architecture. We identified 399 CNVs, of which loss represents 98%, 58% are less than 2.5 kb in size and 71% are intergenic. Intronic deletions account for the majority of copy number changes with gene involvement. Furthermore, one-third of CNVs do not have putative breakpoints within repetitive sequences. We conclude that replicative processes, mediated either by repetitive elements or microhomology, account for the majority of CNVs in the healthy population. Genomic instability involving the formation of a non-B structure is demonstrated in one region.

Genome-wide scan of copy number variation in late-onset Alzheimer's disease.

Alzheimer's disease is a complex and progressive neurodegenerative disease leading to loss of memory, cognitive impairment, and ultimately death. To date, six large-scale genome-wide association studies have been conducted to identify SNPs that influence disease predisposition. These studies have confirmed the well-known APOE epsilon4 risk allele, identified a novel variant that influences disease risk within the APOE epsilon4 population, found a SNP that modifies the age of disease onset, as well as reported the first sex-linked susceptibility variant. Here we report a genome-wide scan of Alzheimer's disease in a set of 331 cases and 368 controls, extending analyses for the first time to include assessments of copy number variation. In this analysis, no new SNPs show genome-wide significance. We also screened for effects of copy number variation, and while nothing was significant, a duplication in CHRNA7 appears interesting enough to warrant further investigation.

Comparative analyses of seven algorithms for copy number variant identification from single nucleotide polymorphism arrays.

Determination of copy number variants (CNVs) inferred in genome wide single nucleotide polymorphism arrays has shown increasing utility in genetic variant disease associations. Several CNV detection methods are available, but differences in CNV call thresholds and characteristics exist. We evaluated the relative performance of seven methods: circular binary segmentation, CNVFinder, cnvPartition, gain and loss of DNA, Nexus algorithms, PennCNV and QuantiSNP. Tested data included real and simulated Illumina HumHap 550 data from the Singapore cohort study of the risk factors for Myopia (SCORM) and simulated data from Affymetrix 6.0 and platform-independent distributions. The normalized singleton ratio (NSR) is proposed as a metric for parameter optimization before enacting full analysis. We used 10 SCORM samples for optimizing parameter settings for each method and then evaluated method performance at optimal parameters using 100 SCORM samples. The statistical power, false positive rates, and receiver operating characteristic (ROC) curve residuals were evaluated by simulation studies. Optimal parameters, as determined by NSR and ROC curve residuals, were consistent across datasets. QuantiSNP outperformed other methods based on ROC curve residuals over most datasets. Nexus Rank and SNPRank have low specificity and high power. Nexus Rank calls oversized CNVs. PennCNV detects one of the fewest numbers of CNVs.

HIF1α regulates Mitochondrial biogenesis and Cellular senescence induced by Gamma Radiation

Cellular response to γ-rays is mediated by ATM-p53 axis. When p53 is phosphorylated, it can transactivate several genes to induce permanent cell cycle arrest (senescence) or apoptosis. Epithelial and mesenchymal cells are more resistant to radiation-induced apoptosis and respond mainly by activating senescence. Hence, tumor cells in a senescent state might remain as “dormant” malignant in fact through disruption of p53 function, cells may overcome growth arrest. Oncocytic features were acquired in the recurring neoplasia after radiation therapy in patient with colonrectal cancer. Oncocytic tumors are characterized by aberrant biogenesis and are mainly non-aggressive neoplasms. Their low proliferation degree can be explained by chronic destabilization of HIF1α, which presides to adaptation to hypoxia and also plays a pivotal role in hypoxia-related radio-resistance. The aim of the present thesis was to verify whether mitochondrial biogenesis can be induced following radiation treatment, in relation of HIF1α status and whether is predictive of a senescence response. In this study was demonstrate that mitochondrial biogenesis parameters like mitochondrial DNA copy number could be used for the prediction of hypoxic status of tissue after radiation treatment. γ-rays induce an increase of mitochondrial mass and function, in response to a genotoxic stress that pushes cells into senescence. Mitochondrial biogenesis is only indirectly regulated by p53, whose activation triggers a MDM2-mediated HIF1α degradation, leading to the release of PGC-1β inhibition by HIF1α. On the other hand, this protein blunts the mitochondrial response to γ-rays as well as the induction of p21-mediated cell senescence, indicating prevalence of the hypoxic over the genotoxic response. Finally in vivo, post-radiotherapy mtDNA copy number increase well correlates with lack of HIF1α increase in the tissue, concluding this may be a useful molecular tool to infer the trigger of a hypoxic response during radiotherapy, which may lead to failure of activation of senescence.

A MULTILEVEL MODEL TO ADDRESS BATCH EFFECTS IN COPY NUMBER ESTIMATION USING SNP ARRAYS

Submicroscopic changes in chromosomal DNA copy number dosage are common and have been implicated in many heritable diseases and cancers. Recent high-throughput technologies have a resolution that permits the detection of segmental changes in DNA copy number that span thousands of basepairs across the genome. Genome-wide association studies (GWAS) may simultaneously screen for copy number-phenotype and SNP-phenotype associations as part of the analytic strategy. However, genome-wide array analyses are particularly susceptible to batch effects as the logistics of preparing DNA and processing thousands of arrays often involves multiple laboratories and technicians, or changes over calendar time to the reagents and laboratory equipment. Failure to adjust for batch effects can lead to incorrect inference and requires inefficient post-hoc quality control procedures that exclude regions that are associated with batch. Our work extends previous model-based approaches for copy number estimation by explicitly modeling batch effects and using shrinkage to improve locus-specific estimates of copy number uncertainty. Key features of this approach include the use of diallelic genotype calls from experimental data to estimate batch- and locus-specific parameters of background and signal without the requirement of training data. We illustrate these ideas using a study of bipolar disease and a study of chromosome 21 trisomy. The former has batch effects that dominate much of the observed variation in quantile-normalized intensities, while the latter illustrates the robustness of our approach to datasets where as many as 25% of the samples have altered copy number. Locus-specific estimates of copy number can be plotted on the copy-number scale to investigate mosaicism and guide the choice of appropriate downstream approaches for smoothing the copy number as a function of physical position. The software is open source and implemented in the R package CRLMM available at Bioconductor (http:www.bioconductor.org).