Recent advances in array comparative genomic hybridization technologies and their applications in human genetics

Advancements and Applications of Preimplantation Genetic Testing in In Vitro Fertilization: A Comprehensive Review

Preimplantation genetic testing (PGT) has become an integral component of assisted reproductive technology (ART), offering couples the opportunity to screen embryos for genetic abnormalities before implantation during in vitro fertilization (IVF). This comprehensive review explores the advancements and applications of PGT in IVF, covering its various types, technological developments, clinical applications, efficacy, challenges, regulatory aspects, and future directions. The evolution of PGT techniques, including next-generation sequencing (NGS) and comparative genomic hybridization (CGH), has significantly enhanced the accuracy and reliability of genetic testing in embryos. PGT holds profound implications for the future of ART by improving IVF success rates, reducing the incidence of genetic disorders, and mitigating the emotional and financial burdens associated with failed pregnancies and genetic diseases. Recommendations for clinicians, researchers, and policymakers include staying updated on the latest PGT techniques and guidelines, exploring innovative technologies, establishing clear regulatory frameworks, and fostering collaboration to maximize the potential benefits of PGT in assisted reproduction. Overall, this review provides valuable insights into the current state of PGT and its implications for the field of reproductive medicine.

Combining callers improves the detection of copy number variants from whole-genome sequencing

Copy Number Variants (CNVs) are deletions, duplications or insertions larger than 50 base pairs. They account for a large percentage of the normal genome variation and play major roles in human pathology. While array-based approaches have long been used to detect them in clinical practice, whole-genome sequencing (WGS) bears the promise to allow concomitant exploration of CNVs and smaller variants. However, accurately calling CNVs from WGS remains a difficult computational task, for which a consensus is still lacking. In this paper, we explore practical calling options to reach the best compromise between sensitivity and sensibility. We show that callers based on different signal (paired-end reads, split reads, coverage depth) yield complementary results. We suggest approaches combining four selected callers (Manta, Delly, ERDS, CNVnator) and a regenotyping tool (SV2), and show that this is applicable in everyday practice in terms of computation time and further interpretation. We demonstrate the superiority of these approaches over array-based Comparative Genomic Hybridization (aCGH), specifically regarding the lack of resolution in breakpoint definition and the detection of potentially relevant CNVs. Finally, we confirm our results on the NA12878 benchmark genome, as well as one clinically validated sample. In conclusion, we suggest that WGS constitutes a timely and economically valid alternative to the combination of aCGH and whole-exome sequencing.

Advances in sperm analysis: techniques, discoveries and applications

Infertility affects one in six couples worldwide, and fertility continues to deteriorate globally, partly owing to a decline in semen quality. Sperm analysis has a central role in diagnosing and treating male factor infertility. Many emerging techniques, such as digital holography, super-resolution microscopy and next-generation sequencing, have been developed that enable improved analysis of sperm motility, morphology and genetics to help overcome limitations in accuracy and consistency, and improve sperm selection for infertility treatment. These techniques have also improved our understanding of fundamental sperm physiology by enabling discoveries in sperm behaviour and molecular structures. Further progress in sperm analysis and integrating these techniques into laboratories and clinics requires multidisciplinary collaboration, which will increase discovery and improve clinical outcomes.

Genomic Mosaicism Formed by Somatic Variation in the Aging and Diseased Brain

Over the past 20 years, analyses of single brain cell genomes have revealed that the brain is composed of cells with myriad distinct genomes: the brain is a genomic mosaic, generated by a host of DNA sequence-altering processes that occur somatically and do not affect the germline. As such, these sequence changes are not heritable. Some processes appear to occur during neurogenesis, when cells are mitotic, whereas others may also function in post-mitotic cells. Here, we review multiple forms of DNA sequence alterations that have now been documented: aneuploidies and aneusomies, smaller copy number variations (CNVs), somatic repeat expansions, retrotransposons, genomic cDNAs (gencDNAs) associated with somatic gene recombination (SGR), and single nucleotide variations (SNVs). A catch-all term of DNA content variation (DCV) has also been used to describe the overall phenomenon, which can include multiple forms within a single cell’s genome. A requisite step in the analyses of genomic mosaicism is ongoing technology development, which is also discussed. Genomic mosaicism alters one of the most stable biological molecules, DNA, which may have many repercussions, ranging from normal functions including effects of aging, to creating dysfunction that occurs in neurodegenerative and other brain diseases, most of which show sporadic presentation, unlinked to causal, heritable genes.

A Practical Guide for Structural Variation Detection in the Human Genome

Profiling genetic variants-including single nucleotide variants, small insertions and deletions, copy number variations, and structural variations (SVs)-from both healthy individuals and individuals with disease is a key component of genetic and biomedical research. SVs are large-scale changes in the genome and involve breakage and rejoining of DNA fragments. They may affect thousands to millions of nucleotides and can lead to loss, gain, and reshuffling of genes and regulatory elements. SVs are known to impact gene expression and potentially result in altered phenotypes and diseases. Therefore, identifying SVs from the human genomes is particularly important. In this review, I describe advantages and disadvantages of the available high-throughput assays for the discovery of SVs, which are the most challenging genetic alterations to detect. A practical guide is offered to suggest the most suitable strategies for discovering different types of SVs including common germline, rare, somatic, and complex variants. I also discuss factors to be considered, such as cost and performance, for different strategies when designing experiments. Last, I present several approaches to identify potential SV artifacts caused by samples, experimental procedures, and computational analysis. © 2020 Wiley Periodicals LLC.

A novel interstitial deletion of chromosome 2q21.1-q23.3: Case report and literature review

Background

Interstitial deletions of 2q are rare. Those that have been reported show varying clinical manifestations according to the size of the deletion and the genomic region involved.

Method and Results

We describe a preterm male harboring a novel interstitial deletion encompassing the 2q21.2‐q23.3 region of 2q, a deletion that has not been described previously. The patient had multiple congenital anomalies including agenesis of the corpus callosum, congenital cardiac defects, bilateral hydronephrosis, spontaneous intestinal perforation, hypospadias and cryptorchidism, sacral dimple and rocker‐bottom feet. Array comparative genomic hybridization (aCGH) analysis revealed a de novo >18 Mb deletion at 2q21.1–q23.3, a region that included (605802, 611472 and 604593) OMIM genes.

Conclusion

To the best of our knowledge this is the first report of a de novo interstitial deletion at 2q21.1–q23.3 in which haploinsufficiency of dose‐sensitive genes is shown to contribute to the patient's phenotype.

Critical evaluation of copy number variant calling methods using DNA methylation

Recent technological and methodological developments have enabled the use of array-based DNA methylation data to call copy number variants (CNVs). ChAMP, Conumee, and cnAnalysis450k are popular methods currently used to call CNVs using methylation data. However, so far, no studies have analyzed the reliability of these methods using real samples. Data from a cohort of individuals with genotype and DNA methylation data generated using the HumanMethylation450 and MethylationEPIC BeadChips were used to assess the consistency between the CNV calls generated by methylation and genotype data. We also took advantage of repeated measures of methylation data collected from the same individuals to compare the reliability of CNVs called by ChAMP, Conumee, and cnAnalysis450k for both the methylation arrays. ChAMP identified more CNVs than Conumee and cnAnalysis450k for both the arrays and, as a consequence, had a higher overlap (~62%) with the calls from the genotype data. However, all methods had relatively low reliability. For the MethylationEPIC array, Conumee had the highest reliability (57.6%), whereas for the HumanMethylation450 array, cnAnalysis450k had the highest reliability (43.0%). Overall, the MethylationEPIC array provided significant gains in reliability for CNV calling over the HumanMethylation450 array but not for overlap with CNVs called using genotype data.

Cytogenetics and Cytogenomics Evaluation in Cancer

The availability of cytogenetics and cytogenomics technologies improved the detection and identification of tumor molecular signatures as well as the understanding of cancer initiation and progression. The use of large-scale and high-throughput cytogenomics technologies has led to a fast identification of several cancer candidate biomarkers associated with diagnosis, prognosis, and therapeutics. The advent of array comparative genomic hybridization and next-generation sequencing technologies has significantly improved the knowledge about cancer biology, underlining driver genes to guide targeted therapy development, drug-resistance prediction, and pharmacogenetics. However, few of these candidate biomarkers have made the transition to the clinic with a clear benefit for the patients. Technological progress helped to demonstrate that cellular heterogeneity plays a significant role in tumor progression and resistance/sensitivity to cancer therapies, representing the major challenge of precision cancer therapy. A paradigm shift has been introduced in cancer genomics with the recent advent of single-cell sequencing, since it presents a lot of applications with a clear benefit to oncological patients, namely, detection of intra-tumoral heterogeneity, mapping clonal evolution, monitoring the development of therapy resistance, and detection of rare tumor cell populations. It seems now evident that no single biomarker could provide the whole information necessary to early detect and predict the behavior and prognosis of tumors. The promise of precision medicine is based on the molecular profiling of tumors being vital the continuous progress of high-throughput technologies and the multidisciplinary efforts to catalogue chromosomal rearrangements and genomic alterations of human cancers and to do a good interpretation of the relation genotype-phenotype.

Computational Methods for the Analysis of Array Comparative Genomic Hybridization

Array comparative genomic hybridization (array CGH) is a technique for assaying the copy number status of cancer genomes. The widespread use of this technology has lead to a rapid accumulation of high throughput data, which in turn has prompted the development of computational strategies for the analysis of array CGH data. Here we explain the principles behind array image processing, data visualization and genomic profile analysis, review currently available software packages, and raise considerations for future software development.

Functionally-focused algorithmic analysis of high resolution microarray-CGH genomic landscapes demonstrates comparable genomic copy number aberrations in MSI and MSS sporadic colorectal cancer

Array-based comparative genomic hybridization (aCGH) emerged as a powerful technology for studying copy number variations at higher resolution in many cancers including colorectal cancer. However, the lack of standardized systematic protocols including bioinformatic algorithms to obtain and analyze genomic data resulted in significant variation in the reported copy number aberration (CNA) data. Here, we present genomic aCGH data obtained using highly stringent and functionally relevant statistical algorithms from 116 well-defined microsatellites instable (MSI) and microsatellite stable (MSS) colorectal cancers. We utilized aCGH to characterize genomic CNAs in 116 well-defined sets of colorectal cancer (CRC) cases. We further applied the significance testing for aberrant copy number (STAC) and Genomic Identification of Significant Targets in Cancer (GISTIC) algorithms to identify functionally relevant (nonrandom) chromosomal aberrations in the analyzed colorectal cancer samples. Our results produced high resolution genomic landscapes of both, MSI and MSS sporadic CRC. We found that CNAs in MSI and MSS CRCs are heterogeneous in nature but may be divided into 3 distinct genomic patterns. Moreover, we show that although CNAs in MSI and MSS CRCs differ with respect to their size, number and chromosomal distribution, the functional copy number aberrations obtained from MSI and MSS CRCs were in fact comparable but not identical. These unifying CNAs were verified by MLPA tumor-loss gene panel, which spans 15 different chromosomal locations and contains 50 probes for at least 20 tumor suppressor genes. Consistently, deletion/amplification in these frequently cancer altered genes were identical in MSS and MSI CRCs. Our results suggest that MSI and MSS copy number aberrations driving CRC may be functionally comparable.

Coiled-coil domain containing 68 (CCDC68) demonstrates a tumor-suppressive role in pancreatic ductal adenocarcinoma

Using integrative genomics and functional screening, we identified coiled-coil domain containing 68 (CCDC68) as a novel putative tumor suppressor gene (TSG) in pancreatic ductal adenocarcinoma (PDAC). CCDC68 allelic losses were documented in 48% of primary PDAC patient tumors, 50% of PDAC cell lines and 30% of primary patient derived xenografts. We also discovered a single nucleotide polymorphism (SNP) variant (SNP rs1344011) that leads to exon skipping and generation of an unstable protein isoform CCDC68Δ(69-114) in 31% of PDAC patients. Overexpression of full length CCDC68 (CCDC68(wt)) in PANC-1 and Hs.766T PDAC cell lines lacking CDCC68 expression decreased proliferation and tumorigenicity in scid mice. In contrast, the downregulation of endogenous CCDC68 in MIAPaca-2 cells increased tumor growth rate. These effects were not observed with the deletion-containing isoform, CCDC68Δ(69-114).

A novel interstitial deletion of 2q22.3 q23.3 in a patient with dysmorphic features, epilepsy, aganglionosis, pure red cell aplasia, and skeletal malformations

Many chromosomal deletions encompassing the 2q23.1 region have been described ranging from small deletions of 38 kb up to >19 Mb. Most phenotypic features of the 2q23.1 deletion syndrome are due to a MBD5 gene loss independent of the size of the deletion. Here, we describe a male patient harboring a novel interstitial deletion encompassing the 2q22.3 q23.3 chromosomal region. Array-CGH revealed a 7.1 Mb deletion causing haploinsufficiency of several genes including MBD5, ACVR2, KIF5C, and EPC2. This patient presents with additional findings to those already described in individuals who have deletions of MBD5 including toes absence of halluces, pure red cell aplasia, and intestinal aganglionosis. Interestingly, in the deleted region there are previously identified regulatory sequences which are located upstream to ZEB2, which is associated with Hirschsprung disease (HSCR). Several genes have been associated with pure red cell aplasia, but to our knowledge, this is the first time that 2q deletion is associated with this phenotype. These additional findings should be added to the list of manifestations associated with 2q deletion, and provide support for the hypothesis that this individual has a true contiguous gene deletion syndrome.

Microarray Technology for the Diagnosis of Fetal Chromosomal Aberrations: Which Platform Should We Use?

The advantage of microarray (array) over conventional karyotype for the diagnosis of fetal pathogenic chromosomal anomalies has prompted the use of microarrays in prenatal diagnostics. In this review we compare the performance of different array platforms (BAC, oligonucleotide CGH, SNP) and designs (targeted, whole genome, whole genome, and targeted, custom) and discuss their advantages and disadvantages in relation to prenatal testing. We also discuss the factors to consider when implementing a microarray testing service for the diagnosis of fetal chromosomal aberrations.

The challenges and importance of structural variation detection in livestock

Recent studies in humans and other model organisms have demonstrated that structural variants (SVs) comprise a substantial proportion of variation among individuals of each species. Many of these variants have been linked to debilitating diseases in humans, thereby cementing the importance of refining methods for their detection. Despite progress in the field, reliable detection of SVs still remains a problem even for human subjects. Many of the underlying problems that make SVs difficult to detect in humans are amplified in livestock species, whose lower quality genome assemblies and incomplete gene annotation can often give rise to false positive SV discoveries. Regardless of the challenges, SV detection is just as important for livestock researchers as it is for human researchers, given that several productive traits and diseases have been linked to copy number variations (CNVs) in cattle, sheep, and pig. Already, there is evidence that many beneficial SVs have been artificially selected in livestock such as a duplication of the agouti signaling protein gene that causes white coat color in sheep. In this review, we will list current SV and CNV discoveries in livestock and discuss the problems that hinder routine discovery and tracking of these polymorphisms. We will also discuss the impacts of selective breeding on CNV and SV frequencies and mention how SV genotyping could be used in the future to improve genetic selection.

Oncogenic function of SCCRO5/DCUN1D5 requires its Neddylation E3 activity and nuclear localization

PURPOSE

To determine mechanisms by which SCCRO5 (aka DCUN1D5) promotes oncogenesis.

EXPERIMENTAL DESIGN

SCCRO5 mRNA and protein expression were assessed in 203 randomly selected primary cancer tissue samples, matched histologically normal tissues, and cell lines by use of real-time PCR and Western blot analysis. SCCRO5 overexpression was correlated with survival. The effect of SCCRO5 knockdown on viability was assessed in selected cancer cell lines. Structure-function studies were performed to determine the SCCRO5 residues required for binding to the neddylation components, for neddylation-promoting activity, and for transformation.

RESULTS

In oral and lung squamous cell carcinomas, SCCRO5 mRNA levels corresponded with protein levels and overexpression correlated with decreased disease-specific survival. Knockdown of SCCRO5 by RNAi resulted in a selective decrease in the viability of cancer cells with high endogenous levels, suggesting the presence of oncogene addiction. SCCRO5 promoted cullin neddylation while maintaining conserved reaction processivity paradigms involved in ubiquitin and ubiquitin-like protein conjugation, establishing it as a component of the neddylation E3. Neddylation activities in vitro required the potentiating of neddylation (PONY) domain but not the nuclear localization sequence (NLS) domain. In contrast, both the NLS domain and the PONY domain were required for transformation of NIH-3T3 cells.

CONCLUSIONS

Our data suggest that SCCRO5 has oncogenic potential that requires its function as a component of the neddylation E3. Neddylation activity and nuclear localization of SCCRO5 are important for its in vivo function.

Array-based comparative genomic hybridization-guided identification of reference genes for normalization of real-time quantitative polymerase chain reaction assay data for lymphomas, histiocytic sarcomas, and osteosarcomas of dogs

OBJECTIVE

To identify suitable reference genes for normalization of real-time quantitative PCR (RT-qPCR) assay data for common tumors of dogs.

SAMPLE

Malignant lymph node (n = 8), appendicular osteosarcoma (9), and histiocytic sarcoma (12) samples and control samples of various nonneoplastic canine tissues.

PROCEDURES

Array-based comparative genomic hybridization (aCGH) data were used to guide selection of 9 candidate reference genes. Expression stability of candidate reference genes and 4 commonly used reference genes was determined for tumor samples with RT-qPCR assays and 3 software programs.

RESULTS

LOC611555 was the candidate reference gene with the highest expression stability among the 3 tumor types. Of the commonly used reference genes, expression stability of HPRT was high in histiocytic sarcoma samples, and expression stability of Ubi and RPL32 was high in osteosarcoma samples. Some of the candidate reference genes had higher expression stability than did the commonly used reference genes.

CONCLUSIONS AND CLINICAL RELEVANCE

Data for constitutively expressed genes with high expression stability are required for normalization of RT-qPCR assay results. Without such data, accurate quantification of gene expression in tumor tissue samples is difficult. Results of the present study indicated LOC611555 may be a useful RT-qPCR assay reference gene for multiple tissue types. Some commonly used reference genes may be suitable for normalization of gene expression data for tumors of dogs, such as lymphomas, osteosarcomas, or histiocytic sarcomas.

Applications of array-CGH for lung cancer

This chapter summarizes the current knowledge on gene copy number changes found in lung tumors, and their application in the diagnosis, prognostication, and prediction of response to chemotherapy. Examples of the identification of specific "driver" oncogenes within amplified DNA segments are described. A model of how array-CGH could be integrated clinically into the routine workup of lung cancers in clinical laboratory is proposed.

The database of chromosome imbalance regions and genes resided in lung cancer from Asian and Caucasian identified by array-comparative genomic hybridization

BACKGROUND

Cancer-related genes show racial differences. Therefore, identification and characterization of DNA copy number alteration regions in different racial groups helps to dissect the mechanism of tumorigenesis.

METHODS

Array-comparative genomic hybridization (array-CGH) was analyzed for DNA copy number profile in 40 Asian and 20 Caucasian lung cancer patients. Three methods including MetaCore analysis for disease and pathway correlations, concordance analysis between array-CGH database and the expression array database, and literature search for copy number variation genes were performed to select novel lung cancer candidate genes. Four candidate oncogenes were validated for DNA copy number and mRNA and protein expression by quantitative polymerase chain reaction (qPCR), chromogenic in situ hybridization (CISH), reverse transcriptase-qPCR (RT-qPCR), and immunohistochemistry (IHC) in more patients.

RESULTS

We identified 20 chromosomal imbalance regions harboring 459 genes for Caucasian and 17 regions containing 476 genes for Asian lung cancer patients. Seven common chromosomal imbalance regions harboring 117 genes, included gain on 3p13-14, 6p22.1, 9q21.13, 13q14.1, and 17p13.3; and loss on 3p22.2-22.3 and 13q13.3 were found both in Asian and Caucasian patients. Gene validation for four genes including ARHGAP19 (10q24.1) functioning in Rho activity control, FRAT2 (10q24.1) involved in Wnt signaling, PAFAH1B1 (17p13.3) functioning in motility control, and ZNF322A (6p22.1) involved in MAPK signaling was performed using qPCR and RT-qPCR. Mean gene dosage and mRNA expression level of the four candidate genes in tumor tissues were significantly higher than the corresponding normal tissues (P<0.001~P=0.06). In addition, CISH analysis of patients indicated that copy number amplification indeed occurred for ARHGAP19 and ZNF322A genes in lung cancer patients. IHC analysis of paraffin blocks from Asian Caucasian patients demonstrated that the frequency of PAFAH1B1 protein overexpression was 68% in Asian and 70% in Caucasian.

CONCLUSIONS

Our study provides an invaluable database revealing common and differential imbalance regions at specific chromosomes among Asian and Caucasian lung cancer patients. Four validation methods confirmed our database, which would help in further studies on the mechanism of lung tumorigenesis.

Genomic alterations in rectal tumors and response to neoadjuvant chemoradiotherapy: an exploratory study

Background

Neoadjuvant chemoradiotherapy is the treatment of choice in advanced rectal cancer, even though there are many patients who will not benefit from it. There are still no effective methods for predicting which patients will respond or not. The present study aimed to define the genomic profile of rectal tumors and to identify alterations that are predictive of response in order to optimize therapeutic strategies.

Methods

Forty-eight candidates for neoadjuvant chemoradiotherapy were recruited and their pretherapy biopsies analyzed by array Comparative Genomic Hybridization (aCGH). Pathologic response was evaluated by tumor regression grade.

Results

Both Hidden Markov Model and Smoothing approaches identified similar alterations, with a prevalence of DNA gains. Non responsive patients had a different alteration profile from responsive ones, with a higher number of genome changes mainly located on 2q21, 3q29, 7p22-21, 7q21, 7q36, 8q23-24, 10p14-13, 13q12, 13q31-34, 16p13, 17p13-12 and 18q23 chromosomal regions.

Conclusions

This exploratory study suggests that an in depth characterization of chromosomal alterations by aCGH would provide useful predictive information on response to neoadjuvant chemoradiotherapy and could help to optimize therapy in rectal cancer patients.

The data discussed in this study are available on the NCBI Gene Expression Omnibus [GEO: GSE25885].

Microarray data analysis and mining tools

Microarrays are one of the latest breakthroughs in experimental molecular biology that allow monitoring the expression levels of tens of thousands of genes simultaneously. Arrays have been applied to studies in gene expression, genome mapping, SNP discrimination, transcription factor activity, toxicity, pathogen identification and many other applications. In this paper we concentrate on discussing various bioinformatics tools used for microarray data mining tasks with its underlying algorithms, web resources and relevant reference. We emphasize this paper mainly for digital biologists to get an aware about the plethora of tools and programs available for microarray data analysis. First, we report the common data mining applications such as selecting differentially expressed genes, clustering, and classification. Next, we focused on gene expression based knowledge discovery studies such as transcription factor binding site analysis, pathway analysis, protein- protein interaction network analysis and gene enrichment analysis.

A survey of analysis software for array-comparative genomic hybridisation studies to detect copy number variation

Copy number variants (CNVs) create a major source of variation among individuals and populations. Array-based comparative genomic hybridisation (aCGH) is a powerful method used to detect and compare the copy numbers of DNA sequences at high resolution along the genome. In recent years, several informatics tools for accurate and efficient CNV detection and assessment have been developed. In this paper, most of the well known algorithms, analysis software and the limitations of that software will be briefly reviewed.

Integrating the multiple dimensions of genomic and epigenomic landscapes of cancer

Advances in high-throughput, genome-wide profiling technologies have allowed for an unprecedented view of the cancer genome landscape. Specifically, high-density microarrays and sequencing-based strategies have been widely utilized to identify genetic (such as gene dosage, allelic status, and mutations in gene sequence) and epigenetic (such as DNA methylation, histone modification, and microRNA) aberrations in cancer. Although the application of these profiling technologies in unidimensional analyses has been instrumental in cancer gene discovery, genes affected by low-frequency events are often overlooked. The integrative approach of analyzing parallel dimensions has enabled the identification of (a) genes that are often disrupted by multiple mechanisms but at low frequencies by any one mechanism and (b) pathways that are often disrupted at multiple components but at low frequencies at individual components. These benefits of using an integrative approach illustrate the concept that the whole is greater than the sum of its parts. As efforts have now turned toward parallel and integrative multidimensional approaches for studying the cancer genome landscape in hopes of obtaining a more insightful understanding of the key genes and pathways driving cancer cells, this review describes key findings disseminating from such high-throughput, integrative analyses, including contributions to our understanding of causative genetic events in cancer cell biology.

Methylation analysis by DNA immunoprecipitation

DNA methylation regulates gene expression primarily through modification of chromatin structure. Global methylation studies have revealed biologically relevant patterns of DNA methylation in the human genome affecting sequences such as gene promoters, gene bodies, and repetitive elements. Disruption of normal methylation patterns and subsequent gene expression changes have been observed in several diseases especially in human cancers. Immunoprecipitation (IP)-based methods to evaluate methylation status of DNA have been instrumental in such genome-wide methylation studies. This review describes techniques commonly used to identify and quantify methylated DNA with emphasis on IP based platforms. In an effort to consolidate the wealth of information and highlight critical aspects of methylated DNA analysis, sample considerations, experimental and bioinformatic approaches for analyzing genome-wide methylation profiles, and the benefit of integrating DNA methylation data with complementary dimensions of genomic data are discussed.

CHESS (CgHExpreSS): a comprehensive analysis tool for the analysis of genomic alterations and their effects on the expression profile of the genome

Background

Genomic alterations frequently occur in many cancer patients and play important mechanistic roles in the pathogenesis of cancer. Furthermore, they can modify the expression level of genes due to altered copy number in the corresponding region of the chromosome. An accumulating body of evidence supports the possibility that strong genome-wide correlation exists between DNA content and gene expression. Therefore, more comprehensive analysis is needed to quantify the relationship between genomic alteration and gene expression. A well-designed bioinformatics tool is essential to perform this kind of integrative analysis. A few programs have already been introduced for integrative analysis. However, there are many limitations in their performance of comprehensive integrated analysis using published software because of limitations in implemented algorithms and visualization modules.

Results

To address this issue, we have implemented the Java-based program CHESS to allow integrative analysis of two experimental data sets: genomic alteration and genome-wide expression profile. CHESS is composed of a genomic alteration analysis module and an integrative analysis module. The genomic alteration analysis module detects genomic alteration by applying a threshold based method or SW-ARRAY algorithm and investigates whether the detected alteration is phenotype specific or not. On the other hand, the integrative analysis module measures the genomic alteration's influence on gene expression. It is divided into two separate parts. The first part calculates overall correlation between comparative genomic hybridization ratio and gene expression level by applying following three statistical methods: simple linear regression, Spearman rank correlation and Pearson's correlation. In the second part, CHESS detects the genes that are differentially expressed according to the genomic alteration pattern with three alternative statistical approaches: Student's t-test, Fisher's exact test and Chi square test. By successive operations of two modules, users can clarify how gene expression levels are affected by the phenotype specific genomic alterations. As CHESS was developed in both Java application and web environments, it can be run on a web browser or a local machine. It also supports all experimental platforms if a properly formatted text file is provided to include the chromosomal position of probes and their gene identifiers.

Conclusions

CHESS is a user-friendly tool for investigating disease specific genomic alterations and quantitative relationships between those genomic alterations and genome-wide gene expression profiling.

CGHnormaliter: an iterative strategy to enhance normalization of array CGH data with imbalanced aberrations

BACKGROUND

Array comparative genomic hybridization (aCGH) is a popular technique for detection of genomic copy number imbalances. These play a critical role in the onset of various types of cancer. In the analysis of aCGH data, normalization is deemed a critical pre-processing step. In general, aCGH normalization approaches are similar to those used for gene expression data, albeit both data-types differ inherently. A particular problem with aCGH data is that imbalanced copy numbers lead to improper normalization using conventional methods.

RESULTS

In this study we present a novel method, called CGHnormaliter, which addresses this issue by means of an iterative normalization procedure. First, provisory balanced copy numbers are identified and subsequently used for normalization. These two steps are then iterated to refine the normalization. We tested our method on three well-studied tumor-related aCGH datasets with experimentally confirmed copy numbers. Results were compared to a conventional normalization approach and two more recent state-of-the-art aCGH normalization strategies. Our findings show that, compared to these three methods, CGHnormaliter yields a higher specificity and precision in terms of identifying the 'true' copy numbers.

CONCLUSION

We demonstrate that the normalization of aCGH data can be significantly enhanced using an iterative procedure that effectively eliminates the effect of imbalanced copy numbers. This also leads to a more reliable assessment of aberrations. An R-package containing the implementation of CGHnormaliter is available at http://www.ibi.vu.nl/programs/cghnormaliterwww.

Analysis of array-CGH data using the R and Bioconductor software suite

Background. Array-based comparative genomic hybridization (array-CGH) is an emerging high-resolution and high-throughput molecular genetic technique that allows genome-wide screening for chromosome alterations. DNA copy number alterations (CNAs) are a hallmark of somatic mutations in tumor genomes and congenital abnormalities that lead to diseases such as mental retardation. However, accurate identification of amplified or deleted regions requires a sequence of different computational analysis steps of the microarray data. Results. We have developed a user-friendly and versatile tool for the normalization, visualization, breakpoint detection, and comparative analysis of array-CGH data which allows the accurate and sensitive detection of CNAs. Conclusion. The implemented option for the determination of minimal altered regions (MARs) from a series of tumor samples is a step forward in the identification of new tumor suppressor genes or oncogenes.

RJaCGH: Bayesian analysis of aCGH arrays for detecting copy number changes and recurrent regions

SUMMARY

Several methods have been proposed to detect copy number changes and recurrent regions of copy number variation from aCGH, but few methods return probabilities of alteration explicitly, which are the direct answer to the question 'is this probe/region altered?' RJaCGH fits a Non-Homogeneous Hidden Markov model to the aCGH data using Markov Chain Monte Carlo with Reversible Jump, and returns the probability that each probe is gained or lost. Using these probabilites, recurrent regions (over sets of individuals) of copy number alteration can be found.

AVAILABILITY

RJaCGH is available as an R package from CRAN repositories (e.g. http://cran.r-project.org/web/packages).

Genetic signatures of HPV-related and unrelated oropharyngeal carcinoma and their prognostic implications

PURPOSE

Patients with human papillomavirus (HPV)-containing oropharyngeal squamous cell carcinomas (OSCC) have a better prognosis than patients with HPV-negative OSCC. This may be attributed to different genetic pathways promoting cancer.

EXPERIMENTAL DESIGN

We used comparative genomic hybridization to identify critical genetic changes in 60 selected OSCC, 28 of which were associated with HPV-16 as determined by HPV-specific PCR and fluorescence in situ hybridization analysis and positive p16(INK4A) immunostaining. The results were correlated with HPV status and clinical data from patients.

RESULTS

Two thirds of OSCC harbored gain at 3q26.3-qter irrespective of HPV status. In HPV-negative tumors this alteration was associated with advanced tumor stage (P=0.013). In comparison with HPV-related OSCC, the HPV-negative tumors harbored: (a) a higher number of chromosomal alterations and amplifications (P=0.03 and 0.039, respectively); (b) significantly more losses at 3p, 5q, 9p, 15q, and 18q, and gains/amplifications at 11q13 (P=0.002, 0.03; <0.001, 0.02, 0.004, and 0.001, respectively); and (c) less often 16q losses and Xp gains (P=0.02 and 0.03). Survival analysis revealed a significantly better disease-free survival for HPV-related OSCC (P=0.02), whereas chromosome amplification was an unfavorable prognostic indicator for disease-free and overall survival (P=0.01 and 0.05, respectively). Interestingly, 16q loss, predominantly identified in HPV-related OSCC, was a strong indicator of favorable outcome (overall survival, P=0.008; disease-free survival, P=0.01) and none of these patients had a tumor recurrence.

CONCLUSIONS

Genetic signatures of HPV-related and HPV-unrelated OSCC are different and most likely underlie differences in tumor development and progression. In addition, distinct chromosomal alterations have prognostic significance.

A new classification method using array Comparative Genome Hybridization data, based on the concept of Limited Jumping Emerging Patterns

Background

Classification using aCGH data is an important and insufficiently investigated problem in bioinformatics. In this paper we propose a new classification method of DNA copy number data based on the concept of limited Jumping Emerging Patterns. We present the comparison of our limJEPClassifier to SVM which is considered the most successful classifier in the case of high-throughput data.

Results

Our results revealed that the classification performance using limJEPClassifier is significantly higher than other methods. Furthermore, we show that application of the limited JEP's can significantly improve classification, when strongly unbalanced data are given.

Conclusion

Nowadays, aCGH has become a very important tool, used in research of cancer or genomic disorders. Therefore, improving classification of aCGH data can have a great impact on many medical issues such as the process of diagnosis and finding disease-related genes. The performed experiment shows that the application of Jumping Emerging Patterns can be effective in the classification of high-dimensional data, including these from aCGH experiments.

Comparative genomic hybridization on BAC arrays

Alterations in genomic DNA are a key feature of many constitutional disorders and cancer. The discovery of the underlying regions of gene dosage has thus been essential in dissecting complex disease phenotypes and identifying targets for therapeutic intervention and diagnostic testing. The development of array comparative genomic hybridization (aCGH) using bacterial artificial chromosomes (BACs) as hybridization targets has facilitated the discovery and fine mapping of novel genomic alterations allowing rapid identification of target genes. In BAC aCGH, DNA samples are first labeled with fluorescent dyes through a random priming reaction with 100-400 ng of genomic DNA. This probe is then co-hybridized to an array consisting of BAC clones, either tiling the genome (approximately 50 kbp resolution) or spaced at intervals (e.g., 1 Mbp resolution). The resulting arrays are then imaged and the signal at each locus is compared between a reference and test sample to determine the copy number status. The DNA samples to be analyzed may be derived from either fresh, frozen, or formalin-fixed paraffin-embedded material, and sample requirements are currently significantly lower than those for oligonucleotide platforms due to the high probe-binding capacity of BAC clone targets (approximately 150 kbp) compared to oligonucleotides (25-80 bp). In this chapter, we describe in detail the technical procedure required to perform copy number analysis of genomes with BAC aCGH.

Application of oligonucleotides arrays for coincident comparative genomic hybridization, ploidy status and loss of heterozygosity studies in human cancers

Many oligonucleotide arrays comprise of spotted short oligonucleotides from throughout the genome under study. Hybridization of tumor DNA samples to these arrays will provide copy number estimates at each reference point with varying degrees of accuracy. In addition to copy number changes, however, tumors often undergo loss of heterozygosity for specific regions of the genome without copy number changes and these genetic changes can only be identified using arrays that identify polymorphic alleles at each reference point. In addition, because the hybridization intensity can be measured at each of the allelic variants, allelic ratios can be established which give indications of ploidy status in the tumor which is not generally possible using most other oligonucleotide array designs. The only arrays currently available that simultaneously report copy number, ploidy, and loss of heterozygosity are the Affymetrix SNP mapping arrays. In this review, the features of the SNP mapping arrays are described and computational tools explored which allow the maximum genetic information to be extracted from the experiment. Although the methodologies to generate the SNP data are now well established, approaches to interpret the data are only just being developed. From our experience using these arrays, we provide insights into how to evaluate the SNP data to report copy number changes, loss of heterozygosity, and ploidy in the same tumor samples using a single array.

SIGMA2: a system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes

Background

High throughput microarray technologies have afforded the investigation of genomes, epigenomes, and transcriptomes at unprecedented resolution. However, software packages to handle, analyze, and visualize data from these multiple 'omics disciplines have not been adequately developed.

Results

Here, we present SIGMA², a system for the integrative genomic multi-dimensional analysis of cancer genomes, epigenomes, and transcriptomes. Multi-dimensional datasets can be simultaneously visualized and analyzed with respect to each dimension, allowing combinatorial integration of the different assays belonging to the different 'omics.

Conclusion

The identification of genes altered at multiple levels such as copy number, loss of heterozygosity (LOH), DNA methylation and the detection of consequential changes in gene expression can be concertedly performed, establishing SIGMA² as a novel tool to facilitate the high throughput systems biology analysis of cancer.

Application of metaphase HR-CGH and targeted Chromosomal Microarray Analyses to genomic characterization of 116 patients with mental retardation and dysmorphic features

Recent advances in molecular cytogenetics enable identification of small chromosomal aberrations that are undetectable by routine chromosome banding in 5-20% of patients with mental retardation/developmental delay (MR/DD) and dysmorphism. The aim of this study was to compare the clinical usefulness of two molecular cytogenetic techniques, metaphase high-resolution comparative genomic hybridization (HR-CGH) and targeted array CGH, also known as Chromosomal Microarray Analysis (CMA). A total of 116 patients with unexplained mild to severe MR and other features suggestive of a chromosomal abnormality with apparently normal or balanced karyotypes were analyzed using HR-CGH (43 patients) and/or CMA (91 patients). Metaphase HR-CGH detected seven interstitial deletions (16.3%). Rare deletions of chromosomes 16 (16p11.2p12.1) and 8 (8q21.11q21.2) were identified. Targeted CMA revealed copy-number changes in 19 of 91 patients (20.8%), among which 11 (11.8%) were clinically relevant, 6 (6.5%) were interpreted as polymorphic variants and 2 (2.1%) were of uncertain significance. The changes varied in size from 0.5 to 12.9 Mb. In summary, our results show that metaphase HR-CGH and array CGH techniques have become important components in cytogenetic diagnostics, particularly for detecting cryptic constitutional chromosome imbalances in patients with MR, in whom the underlying genetic defect is unknown. Additionally, application of both methods together increased the detection rates of genomic imbalances in the tested groups.

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. 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. 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 approximately 100 kilobase pair (kb) segments. These BAC targets are individually synthesized and spotted in duplicate on a single glass slide. 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. The SMRT array can detect alterations as small as 50 kb in size. 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 (25-100 ng) this allows profiling of precious samples such as those produced by microdissection. 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. 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.

MD-SeeGH: a platform for integrative analysis of multi-dimensional genomic data

Background

Recent advances in global genomic profiling methodologies have enabled multi-dimensional characterization of biological systems. Complete analysis of these genomic profiles require an in depth look at parallel profiles of segmental DNA copy number status, DNA methylation state, single nucleotide polymorphisms, as well as gene expression profiles. Due to the differences in data types it is difficult to conduct parallel analysis of multiple datasets from diverse platforms.

Results

To address this issue, we have developed an integrative genomic analysis platform MD-SeeGH, a software tool that allows users to rapidly and directly analyze genomic datasets spanning multiple genomic experiments. With MD-SeeGH, users have the flexibility to easily update datasets in accordance with new genomic builds, make a quality assessment of data using the filtering features, and identify genetic alterations within single or across multiple experiments. Multiple sample analysis in MD-SeeGH allows users to compare profiles from many experiments alongside tracks containing detailed localized gene information, microRNA, CpG islands, and copy number variations.

Conclusion

MD-SeeGH is a new platform for the integrative analysis of diverse microarray data, facilitating multiple profile analyses and group comparisons.

Nonrecurrent MECP2 duplications mediated by genomic architecture-driven DNA breaks and break-induced replication repair

Recurrent submicroscopic genomic copy number changes are the result of nonallelic homologous recombination (NAHR). Nonrecurrent aberrations, however, can result from different nonexclusive recombination-repair mechanisms. We previously described small microduplications at Xq28 containing MECP2 in four male patients with a severe neurological phenotype. Here, we report on the fine-mapping and breakpoint analysis of 16 unique microduplications. The size of the overlapping copy number changes varies between 0.3 and 2.3 Mb, and FISH analysis on three patients demonstrated a tandem orientation. Although eight of the 32 breakpoint regions coincide with low-copy repeats, none of the duplications are the result of NAHR. Bioinformatics analysis of the breakpoint regions demonstrated a 2.5-fold higher frequency of Alu interspersed repeats as compared with control regions, as well as a very high GC content (53%). Unexpectedly, we obtained the junction in only one patient by long-range PCR, which revealed nonhomologous end joining as the mechanism. Breakpoint analysis in two other patients by inverse PCR and subsequent array comparative genomic hybridization analysis demonstrated the presence of a second duplicated region more telomeric at Xq28, of which one copy was inserted in between the duplicated MECP2 regions. These data suggest a two-step mechanism in which part of Xq28 is first inserted near the MECP2 locus, followed by breakage-induced replication with strand invasion of the normal sister chromatid. Our results indicate that the mechanism by which copy number changes occur in regions with a complex genomic architecture can yield complex rearrangements.

Epidermal growth factor receptor (EGFR) is transcriptionally induced by the Y-box binding protein-1 (YB-1) and can be inhibited with Iressa in basal-like breast cancer, providing a potential target for therapy

Introduction

Basal-like breast cancers (BLBCs) are very aggressive, and present serious clinical challenges as there are currently no targeted therapies available. We determined the regulatory role of Y-box binding protein-1 (YB-1) on epidermal growth factor receptor (EGFR) overexpression in BLBC, and the therapeutic potential of inhibiting EGFR. We pursued this in light of our recent work showing that YB-1 induces the expression of EGFR, a new BLBC marker.

Methods

Primary tumour tissues were evaluated for YB1 protein expression by immunostaining tissue microarrays, while copy number changes were assessed by comparative genomic hybridization (CGH). The ability of YB-1 to regulate EGFR was evaluated using luciferase reporter, chromatin immunoprecipitation (ChIP) and gel shift assays. The impact of Iressa on monolayer cell growth was measured using an ArrayScan VTI high-throughput analyser to count cell number, and colony formation in soft agar was used to measure anchorage-independent growth.

Results

YB-1 (27/37 or 73% of cases, P = 3.899 × 10^-4) and EGFR (20/37 or 57.1% of cases, P = 9.206 × 10^-12) are expressed in most cases of BLBC. However, they are not typically amplified in primary BLBC, suggesting overexpression owing to transcriptional activation. In support of this, we demonstrate that YB-1 promotes EGFR reporter activity. YB-1 specifically binds the EGFR promoter at two different YB-1-responsive elements (YREs) located at -940 and -968 using ChIP and gel shift assays in a manner that is dependent on the phosphorylation of S102 on YB-1. Inhibiting EGFR with Iressa suppressed the growth of SUM149 cells by ~40% in monolayer, independent of mutations in the receptor. More importantly anchorage-independent growth of BLBC cell lines was inhibited with combinations of Iressa and YB-1 suppression.

Conclusion

We have identified for the first time a causal link for the expression of EGFR in BLBC through the induction by YB-1 where it binds specifically to two distinguished YREs. Finally, inhibition of EGFR in combination with suppression of YB-1 presents a potential opportunity for therapy in BLBC.

Estrogen receptor status could modulate the genomic pattern in familial and sporadic breast cancer

PURPOSE

Familial breast cancer represents 5% to 10% of all breast tumors. Mutations in the two known major breast cancer susceptibility genes, BRCA1 and BRCA2, account for a minority of familial breast cancer, whereas families without mutations in these genes (BRCAX group) account for 70% of familial breast cancer cases.

EXPERIMENTAL DESIGN

To better characterize and define the genomic differences between the three classes of familial tumors and sporadic malignancies, we have analyzed 19 BRCA1, 24 BRCA2, and 31 BRCAX samples from familial breast cancer patients and 19 sporadic breast tumors using a 1-Mb resolution bacterial artificial chromosome array-based comparative genomic hybridization.

RESULTS

We found that BRCA1/2 tumors showed a higher genomic instability than BRCAX and sporadic cancers. There were common genomic alterations present in all breast cancer groups, such as gains of 1q and 16p or losses of 8ptel-p12 and 16q. We found that the presence/absence of the estrogen receptor (ER) may play a crucial role in driving tumor development through distinct genomic pathways independently of the tumor type (sporadic or familial) and mutation status (BRCA1 or BRCA2). ER(-) tumors presented higher genomic instability and different altered regions than ER+ ones.

CONCLUSIONS

According to our results, the BRCA gene mutation status (mainly BRCA1) would contribute to the genomic profile of abnormalities by increasing or modulating the genome instability.

Gene discovery in cervical cancer : towards diagnostic and therapeutic biomarkers

Cervical cancer is a potentially preventable disease; however, it remains the second most common malignancy in women worldwide. The human papillomavirus (HPV) is the single most important etiological agent in cervical cancer. HPV contributes to neoplastic progression through the action of two viral oncoproteins E6 and E7, which interfere with critical cell cycle pathways, tumor protein p53, and retinoblastoma protein. However, evidence suggests that HPV infection alone is insufficient to induce malignant changes, and other host genetic variations are important in the development of cervical cancer. Advances in molecular biology and high throughput technologies have heralded a new era in biomarker discovery and identification of molecular targets related to carcinogenesis. These advancements have improved our understanding of carcinogenesis and will facilitate screening, early detection, management, and personalized targeted therapy. A number of these developments and molecular targets associated with cervical cancer will be addressed in this review.

CGH microarrays and cancer

Genetic alterations are a key feature of cancer cells and typically target biological processes and pathways that contribute to cancer pathogenesis. Array-based comparative genomic hybridization (aCGH) has provided a wealth of new information on copy number changes in cancer on a genome-wide level and aCGH data have also been utilized in cancer classification. More importantly, aCGH analyses have allowed highly accurate localization of specific genetic alterations that, for example, are associated with tumor progression, therapy response, or patient outcome. The genes involved in these aberrations are likely to contribute to cancer pathogenesis, and the high-resolution mapping by aCGH greatly facilitates the subsequent identification of these cancer-associated genes.

A response to Yu et al. "A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array", BMC Bioinformatics 2007, 8: 145

Background

Yu et al. (BMC Bioinformatics 2007,8: 145+) have recently compared the performance of several methods for the detection of genomic amplification and deletion breakpoints using data from high-density single nucleotide polymorphism arrays. One of the methods compared is our non-homogenous Hidden Markov Model approach. Our approach uses Markov Chain Monte Carlo for inference, but Yu et al. ran the sampler for a severely insufficient number of iterations for a Markov Chain Monte Carlo-based method. Moreover, they did not use the appropriate reference level for the non-altered state.

Methods

We rerun the analysis in Yu et al. using appropriate settings for both the Markov Chain Monte Carlo iterations and the reference level. Additionally, to show how easy it is to obtain answers to additional specific questions, we have added a new analysis targeted specifically to the detection of breakpoints.

Results

The reanalysis shows that the performance of our method is comparable to that of the other methods analyzed. In addition, we can provide probabilities of a given spot being a breakpoint, something unique among the methods examined.

Conclusion

Markov Chain Monte Carlo methods require using a sufficient number of iterations before they can be assumed to yield samples from the distribution of interest. Running our method with too small a number of iterations cannot be representative of its performance. Moreover, our analysis shows how our original approach can be easily adapted to answer specific additional questions (e.g., identify edges).

Detection of DNA copy number alterations in cancer by array comparative genomic hybridization

Over the past few years, various reliable platforms for high-resolution detection of DNA copy number changes have become widely available. Together with optimized protocols for labeling and hybridization and algorithms for data analysis and representation, this has lead to a rapid increase in the application of this technology in the study of copy number variation in the human genome in normal cells and copy number imbalances in genetic diseases, including cancer. In this review, we briefly discuss specific technical issues relevant for array comparative genomic hybridization analysis in cancer tissues. We specifically focus on recent successes of array comparative genomic hybridization technology in the progress of our understanding of oncogenesis in a variety of cancer types. A third section highlights the potential of sensitive genome-wide detection of patterns of DNA imbalances or molecular portraits for class discovery and therapeutic stratification.

The impact of array genomic hybridization on mental retardation research: a review of current technologies and their clinical utility

Our understanding of the causes of mental retardation is benefiting greatly from whole-genome scans to detect submicroscopic pathogenic copy number variants (CNVs) that are undetectable by conventional cytogenetic analysis. The current method of choice for performing whole-genome scans for CNVs is array genomic hybridization (AGH). Several platforms are available for AGH, each with its own strengths and limitations. This review discusses considerations that are relevant to the clinical use of whole-genome AGH platforms for the diagnosis of pathogenic CNVs in children with mental retardation. Whole-genome AGH studies are a maturing technology, but their high diagnostic utility assures their increasing use in clinical genetics.