Modeling recurrent DNA copy number alterations in array CGH data

MOTIVATION: Recurrent DNA copy number alterations (CNA) measured with array comparative genomic hybridization (aCGH) reveal important molecular features of human genetics and disease. Studying aCGH profiles from a phenotypic group of individuals can determine important recurrent CNA patterns that suggest a strong correlation to the phenotype. Computational approaches to detecting recurrent CNAs from a set of aCGH experiments have typically relied on discretizing the noisy log ratios and subsequently inferring patterns. We demonstrate that this can have the effect of filtering out important signals present in the raw data. In this article we develop statistical models that jointly infer CNA patterns and the discrete labels by borrowing statistical strength across samples. RESULTS: We propose extending single sample aCGH HMMs to the multiple sample case in order to infer shared CNAs. We model recurrent CNAs as a profile encoded by a master sequence of states that generates the samples. We show how to improve on two basic models by performing joint inference of the discrete labels and providing sparsity in the output. We demonstrate on synthetic ground truth data and real data from lung cancer cell lines how these two important features of our model improve results over baseline models. We include standard quantitative metrics and a qualitative assessment on which to base our conclusions. AVAILABILITY: http://www.cs.ubc.ca/~sshah/acgh.     

Detection of copy number variants in the horse genome and examination of their association with recurrent laryngeal neuropathy

We used the data from a recently performed genome‐wide association study using the Illumina Equine SNP50 beadchip for the detection of copy number variants (CNVs) and examined their association with recurrent laryngeal neuropathy (RLN), an important equine upper airway disease compromising performance. A total of 2797 CNVs were detected for 477 horses, covering 229 kb and seven SNPs on average. Overlapping CNVs were merged to define 478 CNV regions (CNVRs). CNVRs, particularly deletions, were shown to be significantly depleted in genes. Fifty‐two of the 67 common CNVRs (frequency ≥ 1%) were validated by association mapping, Mendelian inheritance, and/or Mendelian inconsistencies. None of the 67 common CNVRs were significantly associated with RLN when accounting for multiple testing. However, a duplication on chromosome 10 was detected in 10 cases (representing three breeds) and two unphenotyped parents but in none of the controls. The duplication was embedded in an 8‐Mb haplotype shared across breeds.     

Detection of DNA copy number alterations using penalized least squares regression

MOTIVATION: Genomic DNA copy number alterations are characteristic of many human diseases including cancer. Various techniques and platforms have been proposed to allow researchers to partition the whole genome into segments where copy numbers change between contiguous segments, and subsequently to quantify DNA copy number alterations. In this paper, we incorporate the spatial dependence of DNA copy number data into a regression model and formalize the detection of DNA copy number alterations as a penalized least squares regression problem. In addition, we use a stationary bootstrap approach to estimate the statistical significance and false discovery rate. RESULTS: The proposed method is studied by simulations and illustrated by an application to an extensively analyzed dataset in the literature. The results show that the proposed method can correctly detect the numbers and locations of the true breakpoints while appropriately controlling the false positives. AVAILABILITY: http://bioinformatics.med.yale.edu/DNACopyNumber CONTACT: hongyu.zhao@yale.edu SUPPLEMENTARY INFORMATION: http://bioinformatics.med.yale.edu/DNACopyNumber.     

Sparse representation and Bayesian detection of genome copy number alterations from microarray data

MOTIVATION: Genomic instability in cancer leads to abnormal genome copy number alterations (CNA) that are associated with the development and behavior of tumors. Advances in microarray technology have allowed for greater resolution in detection of DNA copy number changes (amplifications or deletions) across the genome. However, the increase in number of measured signals and accompanying noise from the array probes present a challenge in accurate and fast identification of breakpoints that define CNA. This article proposes a novel detection technique that exploits the use of piece wise constant (PWC) vectors to represent genome copy number and sparse Bayesian learning (SBL) to detect CNA breakpoints. METHODS: First, a compact linear algebra representation for the genome copy number is developed from normalized probe intensities. Second, SBL is applied and optimized to infer locations where copy number changes occur. Third, a backward elimination (BE) procedure is used to rank the inferred breakpoints; and a cut-off point can be efficiently adjusted in this procedure to control for the false discovery rate (FDR). RESULTS: The performance of our algorithm is evaluated using simulated and real genome datasets and compared to other existing techniques. Our approach achieves the highest accuracy and lowest FDR while improving computational speed by several orders of magnitude. The proposed algorithm has been developed into a free standing software application (GADA, Genome Alteration Detection Algorithm). AVAILABILITY: http://biron.usc.edu/~piquereg/GADA     

Analysis of copy number variants in the cattle genome

Copy number variation (CNV) is likely to be an important component of heritable variation in livestock. To characterise CNVs in cattle, we performed a genome wide survey to determine the number, location and gene content of these genomic features. A tiling oligonucleotide array with ~385,000 probes was used for comparative genomic hybridisation of both taurine and zebu cattle. Using a conservative set of calling criteria, a total of 51 CNV were detected that collectively spanned approximately half of one percent of the bovine genome. The size of the average CNV within each animal ranged from 213 kb up to 335 kb. Half of the CNV were detected in a single animal only, whilst the remainder was independently identified in multiple individuals. Analysis was performed to determine the gene content for each CNV region. This revealed that the majority of CNV (82%) spanned at least one gene, with a number of CNV containing genes which are known to control aspects of phenotypic variation in cattle. Whilst additional studies are required to determine the impact of individual CNV, this study confirmed them as an important class of genomic variation in cattle.     

The extent of whole‐genome copy number alterations predicts aggressive features in primary melanomas

Recent evidence indicates that melanoma comprises distinct types of tumors and suggests that specific morphological features may help predict its clinical behavior. Using a SNP‐array approach, we quantified chromosomal copy number alterations (CNA) across the whole genome in 41 primary melanomas and found a high degree of heterogeneity in their genomic asset. Association analysis correlating the number and relative length of CNA with clinical, morphological, and dermoscopic attributes of melanoma revealed that features of aggressiveness were strongly linked to the overall amount of genomic damage. Furthermore, we observed that melanoma progression and survival were mainly affected by a low number of large chromosome losses and a high number of small gains. We identified the alterations most frequently associated with aggressive melanoma, and by integrating our data with publicly available gene expression profiles, we identified five genes which expression was found to be necessary for melanoma cells proliferation. In conclusion, this work provides new evidence that the phenotypic heterogeneity of melanoma reflects a parallel genetic diversity and lays the basis to define novel strategies for a more precise prognostic stratification of patients.     

Recurrent chromosomal copy number alterations in sporadic chordomas

The molecular events in chordoma pathogenesis have not been fully delineated, particularly with respect to copy number changes. Understanding copy number alterations in chordoma may reveal critical disease mechanisms that could be exploited for tumor classification and therapy. We report the copy number analysis of 21 sporadic chordomas using array comparative genomic hybridization (CGH). Recurrent copy changes were further evaluated with immunohistochemistry, methylation specific PCR, and quantitative real-time PCR. Similar to previous findings, large copy number losses, involving chromosomes 1p, 3, 4, 9, 10, 13, 14, and 18, were more common than copy number gains. Loss of CDKN2A with or without loss of CDKN2B on 9p21.3 was observed in 16/20 (80%) unique cases of which six (30%) showed homozygous deletions ranging from 76 kilobases to 4.7 megabases. One copy loss of the 10q23.31 region which encodes PTEN was found in 16/20 (80%) cases. Loss of CDKN2A and PTEN expression in the majority of cases was not attributed to promoter methylation. Our sporadic chordoma cases did not show hotspot point mutations in some common cancer gene targets. Moreover, most of these sporadic tumors are not associated with T (brachyury) duplication or amplification. Deficiency of CDKN2A and PTEN expression, although shared across many other different types of tumors, likely represents a key aspect of chordoma pathogenesis. Sporadic chordomas may rely on mechanisms other than copy number gain if they indeed exploit T/brachyury for proliferation.     

Novel origins of copy number variation in the dog genome

ABSTRACT: BACKGROUND: Copy number variants (CNVs) account for substantial variation between genomes and are a major source of normal and pathogenic phenotypic differences. The dog is an ideal model to investigate mutational mechanisms that generate CNVs as its genome lacks a functional ortholog of the PRDM9 gene implicated in recombination and CNV formation in humans. Here we comprehensively assay CNVs using high-density array comparative genomic hybridization in 50 dogs from 17 dog breeds and 3 gray wolves. RESULTS: We use a stringent new method to identify a total of 430 high-confidence CNV loci, that range in size from 9 kb to 1.6 Mb and span 26.4 Mb, or 1.08%, of the assayed dog genome, overlapping 413 annotated genes. 98% of CNVs observed in each breed are also observed in multiple breeds. CNVs predicted to disrupt gene function are significantly less common than expected by chance. We identify a significant overrepresentation of peaks of GC content, previously shown to be enriched in dog recombination hotspots, in the vicinity of CNV breakpoints. CONCLUSIONS: A number of the CNVs identified by this study are candidates for generating breed-specific phenotypes. Purifying selection seems to be a major factor shaping structural variation in the dog genome, suggesting that many CNVs are deleterious. Localized peaks of GC content appear to be novel sites of CNV formation in the dog genome by non-allelic homologous recombination, potentially activated by the loss of PRDM9. These sequence features may have driven genome instability and chromosomal rearrangements throughout canid evolution.     

Clinical interpretation of copy number variants in the human genome

Molecular methods, by which copy number variants (CNVs) detection is available, have been gradually introduced into routine diagnostics over the last 15 years. Despite this, some CNVs continue to be a huge challenge when it comes to clinical interpretation. CNVs are an important source of normal and pathogenic variants, but, in many cases, their impact on human health depends on factors that are not yet known. Therefore, perception of their clinical consequences can change over time, as our knowledge grows. This review summarises guidelines that facilitate correct classification of identified changes and discusses difficulties with the interpretation of rare, small CNVs.     

rSW-seq: Algorithm for detection of copy number alterations in deep sequencing data

Background  

Recent advances in sequencing technologies have enabled generation of large-scale genome sequencing data. These data can be used to characterize a variety of genomic features, including the DNA copy number profile of a cancer genome. A robust and reliable method for screening chromosomal alterations would allow a detailed characterization of the cancer genome with unprecedented accuracy.     

A first comparative map of copy number variations in the sheep genome

We carried out a cross species cattle-sheep array comparative genome hybridization experiment to identify copy number variations (CNVs) in the sheep genome analysing ewes of Italian dairy or dual-purpose breeds (Bagnolese, Comisana, Laticauda, Massese, Sarda, and Valle del Belice) using a tiling oligonucleotide array with ~385,000 probes designed on the bovine genome. We identified 135 CNV regions (CNVRs; 24 reported in more than one animal) covering ~10.5 Mb of the virtual sheep genome referred to the bovine genome (0.398%) with a mean and a median equal to 77.6 and 55.9 kb, respectively. A comparative analysis between the identified sheep CNVRs and those reported in cattle and goat genomes indicated that overlaps between sheep and both other species CNVRs are highly significant (P<0.0001), suggesting that several chromosome regions might contain recurrent interspecies CNVRs. Many sheep CNVRs include genes with important biological functions. Further studies are needed to evaluate their functional relevance.     

Detecting copy number variation in the human genome using comparative genomic hybridization

Among human beings, it was once estimated that our genomes were 99.9% genetically identical. While this high level of genetic similarity helps to define us as a species, it is our genetic variation that contributes to our phenotypic diversity. As genomic technologies evolve to provide genome-wide analyses at higher resolution, we are beginning to appreciate that the human genome has a lot more variation than was once thought. Array-based comparative genomic hybridization (CGH) is one of these technologies that has recently revealed a newly appreciated type of genetic variation: copy number variation, in which thousands of regions of the human genome are now known to be variable in number between individuals. Some of these copy number variable regions have already been shown to predispose to certain common diseases, and others may ultimately have a significant impact on how each of us reacts to certain foods (e.g., allergic reactions), medications (e.g., pharmacogenomics), microscopic infections (i.e., immunity), and other aspects of our ever-changing environment.     

Using high-density DNA methylation arrays to profile copy number alterations

The integration of genomic and epigenomic data is an increasingly popular approach for studying the complex mechanisms driving cancer development. We have developed a method for evaluating both methylation and copy number from high-density DNA methylation arrays. Comparing copy number data from Infinium HumanMethylation450 BeadChips and SNP arrays, we demonstrate that Infinium arrays detect copy number alterations with the sensitivity of SNP platforms. These results show that high-density methylation arrays provide a robust and economic platform for detecting copy number and methylation changes in a single experiment. Our method is available in the ChAMP Bioconductor package: http://www.bioconductor.org/packages/2.13/bioc/html/ChAMP.html.     

Cytogenetically balanced translocations are associated with focal copy number alterations

Current cytogenetic methods (e.g., G-banding and multicolor chromosomal painting) allow detection of translocation events but lack the resolution to (a) locate the breakpoints precisely at the chromosome band level or (b) discriminate balanced translocations from translocations with copy number alterations not previously reported, or imperfectly balanced translocations. In this study, we demonstrate that cytogenetically balanced translocations are in fact frequently associated with segmental gain or loss of DNA. The recent development of a whole genome tiling path BAC array has enabled tiling resolution analysis of genomic segmental copy number status. Combining tiling resolution BAC array comparative genomic hybridization (array CGH) with G-Banding analysis and multicolor chromosomal painting approaches such as spectral karyotyping (SKY) facilitates high-resolution mapping of genomic alterations associated with imperfectly balanced translocations. Using a refined version of our CGH array we have deduced the copy number status throughout the genomes of three cytogenetically well-characterized prostate cancer cell lines (PC3, DU145, LNCaP) to determine whether translocations are associated with focal gains and losses of DNA. At 78 kb tiling resolution we identified the boundaries of 170, 80, and 34 known and novel copy number alterations (CNA) in these cell line genomes, respectively. Thirty-three of the 36 known translocations (92%, P < 0.001) in DU145 were associated with segmental CNA. Likewise, 80% (P < 0.001) of the known translocations showed association in LNCaP. Although many translocation breakpoints exhibit segmental alteration in PC3, the pattern of chromosomal rearrangements is too complex for use in comprehensive association with CNA boundaries. Our results reveal that imperfectly balanced translocations in tumor genomes are a phenomenon that occurs at frequencies much higher than previously demonstrated. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

A high-resolution map of segmental DNA copy number variation in the mouse genome

Submicroscopic (less than 2 Mb) segmental DNA copy number changes are a recently recognized source of genetic variability between individuals. The biological consequences of copy number variants (CNVs) are largely undefined. In some cases, CNVs that cause gene dosage effects have been implicated in phenotypic variation. CNVs have been detected in diverse species, including mice and humans. Published studies in mice have been limited by resolution and strain selection. We chose to study 21 well-characterized inbred mouse strains that are the focus of an international effort to measure, catalog, and disseminate phenotype data. We performed comparative genomic hybridization using long oligomer arrays to characterize CNVs in these strains. This technique increased the resolution of CNV detection by more than an order of magnitude over previous methodologies. The CNVs range in size from 21 to 2,002 kb. Clustering strains by CNV profile recapitulates aspects of the known ancestry of these strains. Most of the CNVs (77.5%) contain annotated genes, and many (47.5%) colocalize with previously mapped segmental duplications in the mouse genome. We demonstrate that this technique can identify copy number differences associated with known polymorphic traits. The phenotype of previously uncharacterized strains can be predicted based on their copy number at these loci. Annotation of CNVs in the mouse genome combined with sequence-based analysis provides an important resource that will help define the genetic basis of complex traits.     

Control-free calling of copy number alterations in deep-sequencing data using GC-content normalization

SUMMARY: We present a tool for control-free copy number alteration (CNA) detection using deep-sequencing data, particularly useful for cancer studies. The tool deals with two frequent problems in the analysis of cancer deep-sequencing data: absence of control sample and possible polyploidy of cancer cells. FREEC (control-FREE Copy number caller) automatically normalizes and segments copy number profiles (CNPs) and calls CNAs. If ploidy is known, FREEC assigns absolute copy number to each predicted CNA. To normalize raw CNPs, the user can provide a control dataset if available; otherwise GC content is used. We demonstrate that for Illumina single-end, mate-pair or paired-end sequencing, GC-contentr normalization provides smooth profiles that can be further segmented and analyzed in order to predict CNAs. AVAILABILITY: Source code and sample data are available at http://bioinfo-out.curie.fr/projects/freec/.