Detection of cryptic pathogenic copy number variations and constitutional loss of heterozygosity using high resolution SNP microarray analysis in 117 patients referred for cytogenetic analysis and impact on clinical practice

BACKGROUND: Microarray genome analysis is realising its promise for improving detection of genetic abnormalities in individuals with mental retardation and congenital abnormality. Copy number variations (CNVs) are now readily detectable using a variety of platforms and a major challenge is the distinction of pathogenic from ubiquitous, benign polymorphic CNVs. The aim of this study was to investigate replacement of time consuming, locus specific testing for specific microdeletion and microduplication syndromes with microarray analysis, which theoretically should detect all known syndromes with CNV aetiologies as well as new ones. METHODS: Genome wide copy number analysis was performed on 117 patients using Affymetrix 250K microarrays. RESULTS: 434 CNVs (195 losses and 239 gains) were found, including 18 pathogenic CNVs and 9 identified as "potentially pathogenic". Almost all pathogenic CNVs were larger than 500 kb, significantly larger than the median size of all CNVs detected. Segmental regions of loss of heterozygosity larger than 5 Mb were found in 5 patients. CONCLUSIONS: Genome microarray analysis has improved diagnostic success in this group of patients. Several examples of recently discovered "new syndromes" were found suggesting they are more common than previously suspected and collectively are likely to be a major cause of mental retardation. The findings have several implications for clinical practice. The study revealed the potential to make genetic diagnoses that were not evident in the clinical presentation, with implications for pretest counselling and the consent process. The importance of contributing novel CNVs to high quality databases for genotype-phenotype analysis and review of guidelines for selection of individuals for microarray analysis is emphasised.

High-resolution microarray analysis of chromosome 20q in human colon cancer metastasis model systems

Amplification of human chromosome 20q DNA is the most frequently occurring chromosomal abnormality detected in sporadic colorectal carcinomas and shows significant correlation with liver metastases. Through comprehensive high-resolution microarray comparative genomic hybridization and microarray gene expression profiling, we have characterized chromosome 20q amplicon genes associated with human colorectal cancer metastasis in two in vitro metastasis model systems. The results revealed increasing complexity of the 20q genomic profile from the primary tumor-derived cell lines to the lymph node and liver metastasis derived cell lines. Expression analysis of chromosome 20q revealed a subset of over expressed genes residing within the regions of genomic copy number gain in all the tumor cell lines, suggesting these are Chromosome 20q copy number responsive genes. Bases on their preferential expression levels in the model system cell lines and known biological function, four of the over expressed genes mapping to the common intervals of genomic copy gain were considered the most promising candidate colorectal metastasis-associated genes. Validation of genomic copy number and expression array data was carried out on these genes, with one gene, DNMT3B, standing out as expressed at a relatively higher levels in the metastasis-derived cell lines compared with their primary-derived counterparts in both the models systems analyzed. The data provide evidence for the role of chromosome 20q genes with low copy gain and elevated expression in the clonal evolution of metastatic cells and suggests that such genes may serve as early biomarkers of metastatic potential. The data also support the utility of the combined microarray comparative genomic hybridization and expression array analysis for identifying copy number responsive genes in areas of low DNA copy gain in cancer cells. ^

Microarray analysis of autoimmune diseases by machine learning procedures

—Microarray-based global gene expression profiling, with the use of sophisticated statistical algorithms is providing new insights into the pathogenesis of autoimmune diseases. We have applied a novel statistical technique for gene selection based on machine learning approaches to analyze microarray expression data gathered from patients with systemic lupus erythematosus (SLE) and primary antiphospholipid syndrome (PAPS), two autoimmune diseases of unknown genetic origin that share many common features. The methodology included a combination of three data discretization policies, a consensus gene selection method, and a multivariate correlation measurement. A set of 150 genes was found to discriminate SLE and PAPS patients from healthy individuals. Statistical validations demonstrate the relevance of this gene set from an univariate and multivariate perspective. Moreover, functional characterization of these genes identified an interferon-regulated gene signature, consistent with previous reports. It also revealed the existence of other regulatory pathways, including those regulated by PTEN, TNF, and BCL-2, which are altered in SLE and PAPS. Remarkably, a significant number of these genes carry E2F binding motifs in their promoters, projecting a role for E2F in the regulation of autoimmunity.

Is Microarray Analysis Really Useful and Sufficient to Diagnose Nut Allergy in the Mediterranean Area?

Background: Component-based diagnosis on multiplex platforms is widely used in food allergy but its clinical performance has not been evaluated in nut allergy. Objective: To assess the diagnostic performance of a commercial protein microarray in the determination of specific IgE (sIgE) in peanut, hazelnut, and walnut allergy. Methods: sIgE was measured in 36 peanut-allergic, 36 hazelnut-allergic, and 44 walnut-allergic patients by ISAC 112, and subsequently, sIgE against available components was determined by ImmunoCAP in patients with negative ISAC results. ImmunoCAP was also used to measure sIgE to Ara h 9, Cor a 8, and Jug r 3 in a subgroup of lipid transfer protein (LTP)-sensitized nut-allergic patients (positive skin prick test to LTP-enriched extract). sIgE levels by ImmunoCAP were compared with ISAC ranges. Results: Most peanut-, hazelnut-, and walnut-allergic patients were sensitized to the corresponding nut LTP (Ara h 9, 66.7%; Cor a 8, 80.5%; Jug r 3, 84% respectively). However, ISAC did not detect sIgE in 33.3% of peanut-allergic patients, 13.9% of hazelnut-allergic patients, or 13.6% of walnut-allergic patients. sIgE determination by ImmunoCAP detected sensitization to Ara h 9, Cor a 8, and Jug r 3 in, respectively, 61.5% of peanut-allergic patients, 60% of hazelnut-allergic patients, and 88.3% of walnut-allergic patients with negative ISAC results. In the subgroup of peach LTP?sensitized patients, Ara h 9 sIgE was detected in more cases by ImmunoCAP than by ISAC (94.4% vs 72.2%, P<.05). Similar rates of Cor a 8 and Jug r 3 sensitization were detected by both techniques. Conclusions: The diagnostic performance of ISAC was adequate for hazelnut and walnut allergy but not for peanut allergy. sIgE sensitivity against Ara h 9 in ISAC needs to be improved.

Host microarray analysis reveals a role for the Salmonella response regulator phoP in human macrophage cell death

Bacterial pathogens manipulate host cells to promote pathogen survival and dissemination. We used a 22,571 human cDNA microarray to identify host pathways that are affected by the Salmonella enterica subspecies typhimurium phoP gene, a transcription factor required for virulence, by comparing the expression profiles of human monocytic tissue culture cells infected with either the wild-type bacteria or a phoP∷Tn10 mutant strain. Both wild-type and phoP∷Tn10 bacteria induced a common set of genes, many of which are proinflammatory. Differentially expressed genes included those that affect host cell death, suggesting that the phoP regulatory system controls bacterial genes that alter macrophage survival. Subsequent experiments showed that the phoP∷Tn10 mutant strain is defective for killing both cultured and primary human macrophages but is able to replicate intracellularly. These experiments indicate that phoP plays a role in Salmonella-induced human macrophage cell death.

Tissue-specific gene expression in soybean (Glycine max) detected by cDNA microarray analysis

We have constructed cDNA microarrays for soybean (Glycine max L. Merrill), containing approximately 4,100 Unigene ESTs derived from axenic roots, to evaluate their application and utility for functional genomics of organ differentiation in legumes. We assessed microarray technology by conducting studies to evaluate the accuracy of microarray data and have found them to be both reliable and reproducible in repeat hybridisations. Several ESTs showed high levels (>50 fold) of differential expression in either root or shoot tissue of soybean. A small number of physiologically interesting, and differentially expressed sequences found by microarray analysis were verified by both quantitative real-time RT-PCR and Northern blot analysis. There was a linear correlation (r(2) = 0.99, over 5 orders of magnitude) between microarray and quantitative real-time RT-PCR data. Microarray analysis of soybean has enormous potential not only for the discovery of new genes involved in tissue differentiation and function, but also to study the expression of previously characterised genes, gene networks and gene interactions in wild-type, mutant or transgenic; plants.

Gene expression in human alcoholism: Microarray analysis of frontal cortex

Background: Changes in brain gene expression are thought to be responsible for the tolerance, dependence, and neurotoxicity produced by chronic alcohol abuse, but there has been no large scale study of gene expression in human alcoholism. Methods: RNA was extracted from postmortem samples of superior frontal cortex of alcoholics and nonalcoholics. Relative levels of RNA were determined by array techniques. We used both cDNA and oligonucleotide microarrays to provide coverage of a large number of genes and to allow cross-validation for those genes represented on both types of arrays. Results: Expression levels were determined for over 4000 genes and 163 of these were found to differ by 40% or more between alcoholics and nonalcoholics. Analysis of these changes revealed a selective reprogramming of gene expression in this brain region, particularly for myelin-related genes which were downregulated in the alcoholic samples. In addition, cell cycle genes and several neuronal genes were changed in expression. Conclusions: These gene expression changes suggest a mechanism for the loss of cerebral white matter in alcoholics as well as alterations that may lead to the neurotoxic actions of ethanol.

Latest developments in the microarray analysis of human brain mRNA

Microarrays are used to monitor the expression of thousands of gene transcripts. This technique requires high-quality RNA, which can be extracted from a variety sources, including autopsy brain tissue. Most nucleic acids and proteins are reasonably stable post mortem. However, their abundance and integrity can exhibit marked intraand inter-subject variability, so care must be taken when comparisons between case-groups are made. We will review issues associated with the sampling of RNA from autopsy brain tissue in relation to various ante- and post-mortem factors.

Microarray analysis of expression of cell death-associated genes in rat spinal cord cells exposed to cyclic tensile stresses in vitro

The application of mechanical insults to the spinal cord results in profound cellular and molecular changes, including the induction of neuronal cell death and altered gene expression profiles. Previous studies have described alterations in gene expression following spinal cord injury, but the specificity of this response to mechanical stimuli is difficult to investigate in vivo. Therefore, we have investigated the effect of cyclic tensile stresses on cultured spinal cord cells from E15 Sprague-Dawley rats, using the FX3000 Flexercell Strain Unit. We examined cell morphology and viability over a 72 hour time course. Microarray analysis of gene expression was performed using the Affymetrix GeneChip System, where categorization of identified genes was performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) systems. Changes in expression of 12 genes were validated with quantitative real-time reverse transcription polymerase chain reaction (RT-PCR).

Microarray analysis of expression of cell death-associated genes in spinal cord cells with cyclic tensile strain

Previous studies have described alterations in gene expression following spinal cord injury, but this response to mechanical stimuli is difficult to investigate in vivo. Therefore, we have investigated the effect of cyclic tensile strain on cultured spinal cord cells from E15 Sprague-Dawley rats. Microarray analysis of gene expression and categorization of identified genes were performed using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) systems. The application of cyclic tensile strain reduced the viability of cultured spinal cord cells significantly in a dose- and time-dependent manner. GO analysis identified candidate genes related to apoptosis (44) and to response to stimulus (17). KEGG analysis identified changes in the expression levels of 12 genes of the mitogen-activated protein kinase (MAPK) signaling pathway, which were confirmed to be upregulated and validated by RT-PCR analysis. Spinal cord cells undergo cell death in response to cyclic tensile strain, which were dose- and time-dependent, with upregulation of various genes, in particular of the MAPK pathway.

ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization

Background: Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. Results: We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. Conclusion: ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.

Discovery of stable and variable differences in the Mycobacterium avium subsp. paratuberculosis type I, II, and III genomes by pan-genome microarray analysis

Mycobacterium avium subsp. paratuberculosis is an important animal pathogen widely disseminated in the environment that has also been associated with Crohn's disease in humans. Three M. avium subsp. paratuberculosis genomotypes are recognized, but genomic differences have not been fully described. To further investigate these potential differences, a 60-mer oligonucleotide microarray (designated the MAPAC array), based on the combined genomes of M. avium subsp. paratuberculosis (strain K-10) and Mycobacterium avium subsp. hominissuis (strain 104), was designed and validated. By use of a test panel of defined M. avium subsp. paratuberculosis strains, the MAPAC array was able to identify a set of large sequence polymorphisms (LSPs) diagnostic for each of the three major M. avium subsp. paratuberculosis types. M. avium subsp. paratuberculosis type II strains contained a smaller genomic complement than M. avium subsp. paratuberculosis type I and M. avium subsp. paratuberculosis type III genomotypes, which included a set of genomic regions also found in M. avium subsp. hominissuis 104. Specific PCRs for genes within LSPs that differentiated M. avium subsp. paratuberculosis types were devised and shown to accurately screen a panel (n = 78) of M. avium subsp. paratuberculosis strains. Analysis of insertion/deletion region INDEL12 showed deletion events causing a reduction in the complement of mycobacterial cell entry genes in M. avium subsp. paratuberculosis type II strains and significantly altering the coding of a major immunologic protein (MPT64) associated with persistence and granuloma formation. Analysis of MAPAC data also identified signal variations in several genomic regions, termed variable genomic islands (vGIs), suggestive of transient duplication/deletion events. vGIs contained significantly low GC% and were immediately flanked by insertion sequences, integrases, or short inverted repeat sequences. Quantitative PCR demonstrated that variation in vGI signals could be associated with colony growth rate and morphology.