Exon array CGH: detection of copy-number changes at the resolution of individual exons in the human genome

The development of high-throughput screening methods such as array-based comparative genome hybridization (array CGH) allows screening of the human genome for copy-number changes. Current array CGH strategies have limits of resolution that make detection of small (less than a few tens of kilobases) gains or losses of genomic DNA difficult to identify. We report here a significant improvement in the resolution of array CGH, with the development of an array platform that utilizes single-stranded DNA array elements to accurately measure copy-number changes of individual exons in the human genome. Using this technology, we screened 31 patient samples across an array containing a total of 162 exons for five disease genes and detected copy-number changes, ranging from whole-gene deletions and duplications to single-exon deletions and duplications, in 100% of the cases. Our data demonstrate that it is possible to screen the human genome for copy-number changes with array CGH at a resolution that is 2 orders of magnitude higher than that previously reported.     

Reference-unbiased copy number variant analysis using CGH microarrays

Comparative genomic hybridization (CGH) microarrays have been used to determine copy number variations (CNVs) and their effects on complex diseases. Detection of absolute CNVs independent of genomic variants of an arbitrary reference sample has been a critical issue in CGH array experiments. Whole genome analysis using massively parallel sequencing with multiple ultra-high resolution CGH arrays provides an opportunity to catalog highly accurate genomic variants of the reference DNA (NA10851). Using information on variants, we developed a new method, the CGH array reference-free algorithm (CARA), which can determine reference-unbiased absolute CNVs from any CGH array platform. The algorithm enables the removal and rescue of false positive and false negative CNVs, respectively, which appear due to the effects of genomic variants of the reference sample in raw CGH array experiments. We found that the CARA remarkably enhanced the accuracy of CGH array in determining absolute CNVs. Our method thus provides a new approach to interpret CGH array data for personalized medicine.     

Allele-specific disparity in breast cancer

Background

Molecular alterations critical to development of cancer include mutations, copy number alterations (amplifications and deletions) as well as genomic rearrangements resulting in gene fusions. Massively parallel next generation sequencing, which enables the discovery of such changes, uses considerable quantities of genomic DNA (> 5 ug), a serious limitation in ever smaller clinical samples. However, a commonly available microarray platforms such as array comparative genomic hybridization (array CGH) allows the characterization of gene copy number at a single gene resolution using much smaller amounts of genomic DNA. In this study we evaluate the sensitivity of ultra-dense array CGH platforms developed by Agilent, especially that of the 1 million probe array (1 M array), and their application when whole genome amplification is required because of limited sample quantities.

Methods

We performed array CGH on whole genome amplified and not amplified genomic DNA from MCF-7 breast cancer cells, using 244 K and 1 M Agilent arrays. The ADM-2 algorithm was used to identify micro-copy number alterations that measured less than 1 Mb in genomic length.

Results

DNA from MCF-7 breast cancer cells was analyzed for micro-copy number alterations, defined as measuring less than 1 Mb in genomic length. The 4-fold extra resolution of the 1 M array platform relative to the less dense 244 K array platform, led to the improved detection of copy number variations (CNVs) and micro-CNAs. The identification of intra-genic breakpoints in areas of DNA copy number gain signaled the possible presence of gene fusion events. However, the ultra-dense platforms, especially the densest 1 M array, detect artifacts inherent to whole genome amplification and should be used only with non-amplified DNA samples.

Conclusions

This is a first report using 1 M array CGH for the discovery of cancer genes and biomarkers. We show the remarkable capacity of this technology to discover CNVs, micro-copy number alterations and even gene fusions. However, these platforms require excellent genomic DNA quality and do not tolerate relatively small imperfections related to the whole genome amplification.     

A novel 5q11.2 deletion detected by microarray comparative genomic hybridisation in a child referred as a case of suspected 22q11 deletion syndrome

The 22q11 deletion syndrome (22q11DS) is a developmental syndrome comprising of heart, palate, thymus and parathyroid glands defects. Individuals with 22q11DS usually carry a 1.5- to 3-Mb heterozygous deletion on chromosome 22q11.2. However, there are many patients with features of 22q11DS without a known cause from conventional karyotype and FISH analysis. Six patients with features of 22q11DS, a normal chromosomal and FISH 22q11 analysis, were selected for investigation by microarray genomic comparative hybridisation (array CGH). Array-CGH is a powerful technology enabling detection of submicroscopic chromosome duplications and deletions by comparing a differentially labelled test sample to a control. The samples are co-hybridised to a microarray containing genomic clones and the resulting ratio of fluorescence intensities on each array element is proportional to the DNA copy number difference. No chromosomal changes were detected by hybridisation to a high resolution array representing chromosome 22q. However, one patient was found to have a 6-Mb deletion on 5q11.2 detected by a whole genome 1-Mb array. This deletion was confirmed with fluorescence in-situ hybridisation (FISH) and microsatellite marker analysis. It is the first deletion described in this region. The patient had tetralogy of Fallot, a bifid uvula and velopharyngeal insufficiency, short stature, learning and behavioural difficulties. This case shows the increased sensitivity of array CGH over detailed karyotype analysis for detection of chromosomal changes. It is anticipated that array CGH will improve the clinicians capacity to diagnose congenital syndromes with an unknown aetiology.     

寡核苷酸阵列比较基因组杂交技术及其应用

阵列-比较基因组杂交技术（array comparative genomic hybridization, array CGH）能在全基因组水平和/或高分辨率基础上检测染色体拷贝数的变化,主要应用于遗传学和肿瘤学研究。Array CGH中微阵列探针通常是PCR扩增的BAC克隆或cDNA分子。最近几年,寡核苷酸阵列比较基因组杂交（oligonucleotide array CGH, oaCGH）逐渐开始应用。oaCGH与BAC array CGH比较,具有操作更简便、探针设计更灵活、分辨率更高等多项优点,预计oaCGH将逐步取代利用BAC克隆片段或cDNA分子的array CGH。oaCGH的应用及其与其它高通量检测技术的结合将促进新的癌症相关基因、肿瘤耐药基因的发现。本文综述了现有主要oaCGH平台在空间分辨率、探针长度、灵敏度、特异性等方面的特点及其应用,概括了oaCGH近年来的进展。     

Human and mouse oligonucleotide-based array CGH

Array-based comparative genomic hybridization is a high resolution method for measuring chromosomal copy number changes. Here we present a validated protocol using in-house spotted oligonucleotide libraries for array comparative genomic hybridization (CGH). This oligo array CGH platform yields reproducible results and is capable of detecting single copy gains, multi-copy amplifications as well as homozygous and heterozygous deletions as small as 100 kb with high resolution. A human oligonucleotide library was printed on amine binding slides. Arrays were hybridized using a hybstation and analysed using BlueFuse feature extraction software, with >95% of spots passing quality control. The protocol allows as little as 300 ng of input DNA and a 90% reduction of Cot-1 DNA without compromising quality. High quality results have also been obtained with DNA from archival tissue. Finally, in addition to human oligo arrays, we have applied the protocol successfully to mouse oligo arrays. We believe that this oligo-based platform using ‘off-the-shelf’ oligo libraries provides an easy accessible alternative to BAC arrays for CGH, which is cost-effective, available at high resolution and easily implemented for any sequenced organism without compromising the quality of the results.     

High-resolution array CGH increases heterogeneity tolerance in the analysis of clinical samples

Recent advances in array comparative genomic hybridization (array CGH) technology are revolutionizing our understanding of tumor genomes. Marker-based arrays enable rapid survey at megabase intervals, while tiling path arrays examine the entire genome in unprecedented detail. Tumor biopsies are typically small and contain infiltrating stromal cells, requiring tedious microdissection. Tissue heterogeneity is a major barrier to high-throughput profiling of tumor genomes and is also an important consideration for the introduction of array CGH to clinical settings. We propose that increasing array resolution will enhance detection sensitivity in mixed tissues and as a result significantly reduce microdissection requirements. In this study, we first simulated normal cell contamination to determine the heterogeneity tolerance of array CGH and then validated this detection sensitivity model on cancer specimens using the newly developed submegabase resolution tiling-set (SMRT) array, which spans the human genome with 32,433 overlapping BAC clones.     

Rearrangements of chromosome 18 illustrate the utility of array-based comparative genomic hybridization

Comprehensive and reliable testing is an important component of counseling and management in clinical genetics. Identification of imbalances of chromosomal segments has uncovered new genes and has established phenotype/genotype correlations for many syndromes with previously unidentified causes. Conventional cytogenetics has proven to be useful for the detection of large aberrations, but its resolution limits the identification of submicroscopic alterations. Comparative genomic hybridization (CGH) on a microarray-based platform has the potential to detect and characterize both microscopic and submicroscopic chromosomal abnormalities. Nine cases of aberrations involving chromosome 18 are used to illustrate the use and clinical potential of array CGH.     

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

Array comparative genomic hybridization (array CGH) is a method for detecting gains and losses of DNA segments or gene dosage in the genome ¹. Recent advances in this technology have enabled high resolution comparison of whole genomes for the identification of genetic alterations in cancer and other genetic diseases ². The Sub-Megabase Resolution Tiling-set array (or SMRT) array is comprised of a set of approximately thirty thousand overlapping bacterial artificial chromosome (BAC) clones that span the human genome in ~100 kilobase pair (kb) segments ². These BAC targets are individually synthesized and spotted in duplicate on a single glass slide ^2-4. Array CGH is based on the principle of competitive hybridization. Sample and reference DNA are differentially labeled with Cyanine-3 and Cyanine-5 fluorescent dyes, and co-hybridized to the array. After an incubation period the unbound samples are washed from the slide and the array is imaged. A freely available custom software package called SeeGH (www.flintbox.ca) is used to process the large volume of data collected - a single experiment generates 53,892 data points. SeeGH visualizes the log2 signal intensity ratio between the 2 samples at each BAC target which is vertically aligned with chromosomal position ^5,6. The SMRT array can detect alterations as small as 50 kb in size ⁷. The SMRT array can detect a variety of DNA rearrangement events including DNA gains, losses, amplifications and homozygous deletions. A unique advantage of the SMRT array is that one can use DNA isolated from formalin fixed paraffin embedded samples. When combined with the low input requirements of unamplified DNA (25-100ng) this allows profiling of precious samples such as those produced by microdissection ^7,8. This is attributed to the large size of each BAC hybridization target that allows the binding of sufficient labeled samples to produce signals for detection. Another advantage of this platform is the tolerance of tissue heterogeneity, decreasing the need for tedious tissue microdissection ⁸. This video protocol is a step-by-step tutorial from labeling the input DNA through to signal acquisition for the whole genome tiling path SMRT array.Download video file.^{(62M, mov)}     

Array CGH data modeling and smoothing in Stationary Wavelet Packet Transform domain

Background

Array-based comparative genomic hybridization (array CGH) is a highly efficient technique, allowing the simultaneous measurement of genomic DNA copy number at hundreds or thousands of loci and the reliable detection of local one-copy-level variations. Characterization of these DNA copy number changes is important for both the basic understanding of cancer and its diagnosis. In order to develop effective methods to identify aberration regions from array CGH data, many recent research work focus on both smoothing-based and segmentation-based data processing. In this paper, we propose stationary packet wavelet transform based approach to smooth array CGH data. Our purpose is to remove CGH noise in whole frequency while keeping true signal by using bivariate model.

Results

In both synthetic and real CGH data, Stationary Wavelet Packet Transform (SWPT) is the best wavelet transform to analyze CGH signal in whole frequency. We also introduce a new bivariate shrinkage model which shows the relationship of CGH noisy coefficients of two scales in SWPT. Before smoothing, the symmetric extension is considered as a preprocessing step to save information at the border.

Conclusion

We have designed the SWTP and the SWPT-Bi which are using the stationary wavelet packet transform with the hard thresholding and the new bivariate shrinkage estimator respectively to smooth the array CGH data. We demonstrate the effectiveness of our approach through theoretical and experimental exploration of a set of array CGH data, including both synthetic data and real data. The comparison results show that our method outperforms the previous approaches.

     

Der Stellenwert der ?array comparative genomic hybridization“ in der Pr?nataldiagnostik

Array comparative genomic hybridization (CGH) enables, without the need for cell culture, the detection of changes in copy numbers with high accuracy below the resolution of standard chromosome analysis. The implementation of array?CGH in prenatal diagnosis has been hesitant in spite of these obvious advantages. This has been predominantly due to the likelihood of finding copy number variations (CNVs) of uncertain clinical significance. In prenatal diagnosis array?CGH should not be offered as a first tier but as an adjunct to standard diagnostic procedures in order to minimize uncertainty. Indications for the use of array?CGH will be defined and substantiated in the present article. Guidelines should be established at each laboratory regarding the minimum size of CNVs to be assessed and the genomic regions considered clinically significant.     

A method for calling gains and losses in array CGH data

Array CGH is a powerful technique for genomic studies of cancer. It enables one to carry out genome-wide screening for regions of genetic alterations, such as chromosome gains and losses, or localized amplifications and deletions. In this paper, we propose a new algorithm 'Cluster along chromosomes' (CLAC) for the analysis of array CGH data. CLAC builds hierarchical clustering-style trees along each chromosome arm (or chromosome), and then selects the 'interesting' clusters by controlling the False Discovery Rate (FDR) at a certain level. In addition, it provides a consensus summary across a set of arrays, as well as an estimate of the corresponding FDR. We illustrate the method using an application of CLAC on a lung cancer microarray CGH data set as well as a BAC array CGH data set of aneuploid cell strains.     

FACADE: a fast and sensitive algorithm for the segmentation and calling of high resolution array CGH data

The availability of high resolution array comparative genomic hybridization (CGH) platforms has led to increasing complexities in data analysis. Specifically, defining contiguous regions of alterations or segmentation can be computationally intensive and popular algorithms can take hours to days for the processing of arrays comprised of hundreds of thousands to millions of elements. Additionally, tumors tend to demonstrate subtle copy number alterations due to heterogeneity, ploidy and hybridization effects. Thus, there is a need for fast, sensitive array CGH segmentation and alteration calling algorithms. Here, we describe Fast Algorithm for Calling After Detection of Edges (FACADE), a highly sensitive and easy to use algorithm designed to rapidly segment and call high resolution array data.     

SW-ARRAY: a dynamic programming solution for the identification of copy-number changes in genomic DNA using array comparative genome hybridization data

Comparative genome hybridization (CGH) to DNA microarrays (array CGH) is a technique capable of detecting deletions and duplications in genomes at high resolution. However, array CGH studies of the human genome noting false negative and false positive results using large insert clones as probes have raised important concerns regarding the suitability of this approach for clinical diagnostic applications. Here, we adapt the Smith–Waterman dynamic-programming algorithm to provide a sensitive and robust analytic approach (SW-ARRAY) for detecting copy-number changes in array CGH data. In a blind series of hybridizations to arrays consisting of the entire tiling path for the terminal 2 Mb of human chromosome 16p, the method identified all monosomies between 267 and 1567 kb with a high degree of statistical significance and accurately located the boundaries of deletions in the range 267–1052 kb. The approach is unique in offering both a nonparametric segmentation procedure and a nonparametric test of significance. It is scalable and well-suited to high resolution whole genome array CGH studies that use array probes derived from large insert clones as well as PCR products and oligonucleotides.     

Array-basierter Nachweis chromosomaler Aberrationen bei malignen Neoplasien

Over the last decade, array-based methods for the detection of genomic imbalances have gained increasing importance in the field of cancer genetics. With their particular platform-specific advantages and disadvantages, different array comparative genomic hybridization (CGH) and single nucleotide polymorphism (SNP) array-based technologies can be utilized according to the question addressed, the material to be analyzed and the resolution targeted. In contrast to array CGH-based technologies, SNP-based arrays allow the simultaneous detection of copy-neutral loss of heterozygosity in addition to the diagnosis of chromosomal imbalances. In all array-based approaches it should be borne in mind that tumors are usually a mixture of clonal neoplastic and normal cells and that some aberrations might be subclonal. Applications of array-based imbalance mapping in cancer include the characterization of pathogenetically relevant imbalances, the definition of molecular or clinical subgroups of tumors or the identification of targets for individualized therapy.     

Studying copy number variations using a nanofluidic platform

Copy number variations (CNVs) in the human genome are conventionally detected using high-throughput scanning technologies, such as comparative genomic hybridization and high-density single nucleotide polymorphism (SNP) microarrays, or relatively low-throughput techniques, such as quantitative polymerase chain reaction (PCR). All these approaches are limited in resolution and can at best distinguish a twofold (or 50%) difference in copy number. We have developed a new technology to study copy numbers using a platform known as the digital array, a nanofluidic biochip capable of accurately quantitating genes of interest in DNA samples. We have evaluated the digital array's performance using a model system, to show that this technology is exquisitely sensitive, capable of differentiating as little as a 15% difference in gene copy number (or between 6 and 7 copies of a target gene). We have also analyzed commercial DNA samples for their CYP2D6 copy numbers and confirmed that our results were consistent with those obtained independently using conventional techniques. In a screening experiment with breast cancer and normal DNA samples, the ERBB2 gene was found to be amplified in about 35% of breast cancer samples. The use of the digital array enables accurate measurement of gene copy numbers and is of significant value in CNV studies.     

High-resolution molecular characterization of 15q11-q13 rearrangements by array comparative genomic hybridization (array CGH) with detection of gene dosage

Maternally derived duplication of the imprinted region of chromosome 15q11-q14 leads to a complex neurobehavioral phenotype that often includes autism, cognitive deficits, and seizures. Multiple repeat elements within the region mediate a variety of rearrangements, including interstitial duplications, interstitial triplications, and supernumerary isodicentric marker chromosomes, as well as the deletions that cause Prader-Willi and Angelman syndromes. To elucidate the molecular structure of these duplication chromosomes, we designed a high-resolution array comparative genomic hybridization (array CGH) platform. The array contains 79 clones that form a gapped contig across the critical region on chromosome 15q11-q14 and 21 control clones from other autosomes and the sex chromosomes. We used this array to examine a set of 48 samples from patients with segmental aneuploidy of chromosome 15q. Using the array, we were able to determine accurately the dosage, which ranged from 1 to 6 copies, and also to detect atypical and asymmetric rearrangements. In addition, the increased resolution of the array allowed us to position two previously reported breakpoints within the contig. These results indicate that array CGH is a powerful technique to study rearrangements of proximal chromosome 15q.     

Array-CGH für die Analyse von Tumorgenomen

Array comparative genomic hybridization (array CGH) allows the genome-wide analysis of copy number changes at a high resolution. In the last decade, such copy number aberrations have been found frequently and in large quantities in tumor genomes. Alterations in the array CGH profile of tumor DNA indicate the location of tumor suppressor or proto-oncogenes, thereby enabling identification of cancer-relevant genes. In addition, patterns of aberrations have been detected that allow the molecular subclassification of certain tumor types with diagnostic significance. Array CGH analyses have also been instrumental in identifying new prognostic markers. In the future, data evaluation by integrated approaches, including other molecular levels and the selective use of chromosome and tumor-specific microarrays, will be of particular importance.     

SeeGH – A software tool for visualization of whole genome array comparative genomic hybridization data

Background  

Array comparative genomic hybridization (CGH) is a technique which detects copy number differences in DNA segments. Complete sequencing of the human genome and the development of an array representing a tiling set of tens of thousands of DNA segments spanning the entire human genome has made high resolution copy number analysis throughout the genome possible. Since array CGH provides signal ratio for each DNA segment, visualization would require the reassembly of individual data points into chromosome profiles.