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.

Forensisch relevante SNP-Genotypisierung mittels elektronischer Microarray-Technologie

Die vorliegende Dissertation entstand im Rahmen eines multizentrischen EU-geförderten Projektes, das die Anwendungsmöglichkeiten von Einzelnukleotid-Polymorphismen (SNPs) zur Individualisierung von Personen im Kontext der Zuordnung von biologischen Tatortspuren oder auch bei der Identifizierung unbekannter Toter behandelt. Die übergeordnete Zielsetzung des Projektes bestand darin, hochauflösende Genotypisierungsmethoden zu etablieren und zu validieren, die mit hoher Genauigkeit aber geringen Aufwand SNPs im Multiplexformat simultan analysieren können. Zunächst wurden 29 Y-chromosomale und 52 autosomale SNPs unter der Anforderung ausgewählt, dass sie als Multiplex eine möglichst hohe Individualisierungschance aufweisen. Anschließend folgten die Validierungen beider Multiplex-Systeme und der SNaPshot™-Minisequenzierungsmethode in systematischen Studien unter Beteiligung aller Arbeitsgruppen des Projektes. Die validierte Referenzmethode auf der Basis einer Minisequenzierung diente einerseits für die kontrollierte Zusammenarbeit unterschiedlicher Laboratorien und andererseits als Grundlage für die Entwicklung eines Assays zur SNP-Genotypisierung mittels der elektronischen Microarray-Technologie in dieser Arbeit. Der eigenständige Hauptteil dieser Dissertation beschreibt unter Verwendung der zuvor validierten autosomalen SNPs die Neuentwicklung und Validierung eines Hybridisierungsassays für die elektronische Microarray-Plattform der Firma Nanogen Dazu wurden im Vorfeld drei verschiedene Assays etabliert, die sich im Funktionsprinzip auf dem Microarray unterscheiden. Davon wurde leistungsorientiert das Capture down-Assay zur Weiterentwicklung ausgewählt. Nach zahlreichen Optimierungsmaßnahmen hinsichtlich PCR-Produktbehandlung, gerätespezifischer Abläufe und analysespezifischer Oligonukleotiddesigns stand das Capture down-Assay zur simultanen Typisierung von drei Individuen mit je 32 SNPs auf einem Microarray bereit. Anschließend wurde dieses Verfahren anhand von 40 DNA-Proben mit bekannten Genotypen für die 32 SNPs validiert und durch parallele SNaPshot™-Typisierung die Genauigkeit bestimmt. Das Ergebnis beweist nicht nur die Eignung des validierten Analyseassays und der elektronischen Microarray-Technologie für bestimmte Fragestellungen, sondern zeigt auch deren Vorteile in Bezug auf Schnelligkeit, Flexibilität und Effizienz. Die Automatisierung, welche die räumliche Anordnung der zu untersuchenden Fragmente unmittelbar vor der Analyse ermöglicht, reduziert unnötige Arbeitsschritte und damit die Fehlerhäufigkeit und Kontaminationsgefahr bei verbesserter Zeiteffizienz. Mit einer maximal erreichten Genauigkeit von 94% kann die Zuverlässigkeit der in der forensischen Genetik aktuell eingesetzten STR-Systeme jedoch noch nicht erreicht werden. Die Rolle des neuen Verfahrens wird damit nicht in einer Ablösung der etablierten Methoden, sondern in einer Ergänzung zur Lösung spezieller Probleme wie z.B. der Untersuchung stark degradierter DNA-Spuren zu finden sein.

A microarray-based system for the simultaneous analysis of single nucleotide polymorphisms in human genes involved in the metabolism of anti-malarial drugs

Background: In order to provide a cost-effective tool to analyse pharmacogenetic markers in malaria treatment, DNA microarray technology was compared with sequencing of polymerase chain reaction (PCR) fragments to detect single nucleotide polymorphisms (SNPs) in a larger number of samples. Methods: The microarray was developed to affordably generate SNP data of genes encoding the human cytochrome P450 enzyme family (CYP) and N-acetyltransferase-2 (NAT2) involved in antimalarial drug metabolisms and with known polymorphisms, i.e. CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, and NAT2. Results: For some SNPs, i.e. CYP2A6*2, CYP2B6*5, CYP2C8*3, CYP2C9*3/*5, CYP2C19*3, CYP2D6*4 and NAT2*6/*7/*14, agreement between both techniques ranged from substantial to almost perfect (kappa index between 0.61 and 1.00), whilst for other SNPs a large variability from slight to substantial agreement (kappa index between 0.39 and 1.00) was found, e. g. CYP2D6*17 (2850C>T), CYP3A4*1B and CYP3A5*3. Conclusion: The major limit of the microarray technology for this purpose was lack of robustness and with a large number of missing data or with incorrect specificity.

EXPLORATION, NORMALIZATION, AND GENOTYPE CALLS OF HIGH DENSITY OLIGONUCLEOTIDE SNP ARRAY DATA

In most microarray technologies, a number of critical steps are required to convert raw intensity measurements into the data relied upon by data analysts, biologists and clinicians. These data manipulations, referred to as preprocessing, can influence the quality of the ultimate measurements. In the last few years, the high-throughput measurement of gene expression is the most popular application of microarray technology. For this application, various groups have demonstrated that the use of modern statistical methodology can substantially improve accuracy and precision of gene expression measurements, relative to ad-hoc procedures introduced by designers and manufacturers of the technology. Currently, other applications of microarrays are becoming more and more popular. In this paper we describe a preprocessing methodology for a technology designed for the identification of DNA sequence variants in specific genes or regions of the human genome that are associated with phenotypes of interest such as disease. In particular we describe methodology useful for preprocessing Affymetrix SNP chips and obtaining genotype calls with the preprocessed data. We demonstrate how our procedure improves existing approaches using data from three relatively large studies including one in which large number independent calls are available. Software implementing these ideas are avialble from the Bioconductor oligo package.

De Novo Assembly And Transcriptome Analysis Of The Rubber Tree (hevea Brasiliensis) And Snp Markers Development For Rubber Biosynthesis Pathways.

Hevea brasiliensis (Willd. Ex Adr. Juss.) Muell.-Arg. is the primary source of natural rubber that is native to the Amazon rainforest. The singular properties of natural rubber make it superior to and competitive with synthetic rubber for use in several applications. Here, we performed RNA sequencing (RNA-seq) of H. brasiliensis bark on the Illumina GAIIx platform, which generated 179,326,804 raw reads on the Illumina GAIIx platform. A total of 50,384 contigs that were over 400 bp in size were obtained and subjected to further analyses. A similarity search against the non-redundant (nr) protein database returned 32,018 (63%) positive BLASTx hits. The transcriptome analysis was annotated using the clusters of orthologous groups (COG), gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Pfam databases. A search for putative molecular marker was performed to identify simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). In total, 17,927 SSRs and 404,114 SNPs were detected. Finally, we selected sequences that were identified as belonging to the mevalonate (MVA) and 2-C-methyl-D-erythritol 4-phosphate (MEP) pathways, which are involved in rubber biosynthesis, to validate the SNP markers. A total of 78 SNPs were validated in 36 genotypes of H. brasiliensis. This new dataset represents a powerful information source for rubber tree bark genes and will be an important tool for the development of microsatellites and SNP markers for use in future genetic analyses such as genetic linkage mapping, quantitative trait loci identification, investigations of linkage disequilibrium and marker-assisted selection.

Tissue Microarray Is A Reliable Method For Immunohistochemical Analysis Of Pleomorphic Adenoma.

To determine the most adequate number and size of tissue microarray (TMA) cores for pleomorphic adenoma immunohistochemical studies. Eighty-two pleomorphic adenoma cases were distributed in 3 TMA blocks assembled in triplicate containing 1.0-, 2.0-, and 3.0-mm cores. Immunohistochemical analysis against cytokeratin 7, Ki67, p63, and CD34 were performed and subsequently evaluated with PixelCount, nuclear, and microvessel software applications. The 1.0-mm TMA presented lower results than 2.0- and 3.0-mm TMAs versus conventional whole section slides. Possibly because of an increased amount of stromal tissue, 3.0-mm cores presented a higher microvessel density. Comparing the results obtained with one, two, and three 2.0-mm cores, there was no difference between triplicate or duplicate TMAs and a single-core TMA. Considering the possible loss of cylinders during immunohistochemical reactions, 2.0-mm TMAs in duplicate are a more reliable approach for pleomorphic adenoma immunohistochemical study.

COL18A1 is highly expressed during human adipocyte differentiation and the SNP c.1136C > T in its "frizzled" motif is associated with obesity in diabetes type 2 patients

Collagen XVIII can generate two fragments, NC11-728 containing a frizzled motif which possibly acts in Wnt signaling and Endostatin, which is cleaved from the NC1 and is a potent inhibitor of angiogenesis. Collagen XVIII and Wnt signaling have recently been associated with adipogenic differentiation and obesity in some animal models, but not in humans. In the present report, we have shown that COL18A1 expression increases during human adipogenic differentiation. We also tested if polymorphisms in the Frizzled (c.1136C>T; Thr379Met) and Endostatin (c.4349G>A; Asp1437Asn) regions contribute towards susceptibility to obesity in patients with type 2 diabetes (113 obese, BMI =30; 232 non-obese, BMI < 30) of European ancestry. No evidence of association was observed between the allele c.4349G>A and obesity, but we observed a significantly higher frequency of homozygotes c.1136TT in obese (19.5%) than in non-obese individuals (10.9%) [P = 0.02; OR = 2.0 (95%CI: 1.07-3.73)], suggesting that the allele c.1136T is associated to obesity in a recessive model. This genotype, after controlling for cholesterol, LDL cholesterol, and triglycerides, was independently associated with obesity (P = 0.048), and increases the chance of obesity in 2.8 times. Therefore, our data suggest the involvement of collagen XVIII in human adipogenesis and susceptibility to obesity.

Production of DNA microarray and expression analysis of genes from Xylella fastidiosa in different culture media

DNA Microarray was developed to monitor the expression of many genes from Xylella fastidiosa, allowing the side by-side comparison of two situations in a single experiment. The experiments were performed using X. fastidiosa cells grown in two culture media: BCYE and XDM2. The primers were synthesized, spotted onto glass slides and the array was hybridized against fluorescently labeled cDNAs. The emitted signals were quantified, normalized and the data were statistically analyzed to verify the differentially expressed genes. According to the data, 104 genes were differentially expressed in XDM2 and 30 genes in BCYE media. The present study showed that DNA microarray technique efficiently differentiate the expressed genes under different conditions.

High-throughput SNP genotyping in the highly heterozygous genome of Eucalyptus: assay success, polymorphism and transferability across species

Background: High-throughput SNP genotyping has become an essential requirement for molecular breeding and population genomics studies in plant species. Large scale SNP developments have been reported for several mainstream crops. A growing interest now exists to expand the speed and resolution of genetic analysis to outbred species with highly heterozygous genomes. When nucleotide diversity is high, a refined diagnosis of the target SNP sequence context is needed to convert queried SNPs into high-quality genotypes using the Golden Gate Genotyping Technology (GGGT). This issue becomes exacerbated when attempting to transfer SNPs across species, a scarcely explored topic in plants, and likely to become significant for population genomics and inter specific breeding applications in less domesticated and less funded plant genera. Results: We have successfully developed the first set of 768 SNPs assayed by the GGGT for the highly heterozygous genome of Eucalyptus from a mixed Sanger/454 database with 1,164,695 ESTs and the preliminary 4.5X draft genome sequence for E. grandis. A systematic assessment of in silico SNP filtering requirements showed that stringent constraints on the SNP surrounding sequences have a significant impact on SNP genotyping performance and polymorphism. SNP assay success was high for the 288 SNPs selected with more rigorous in silico constraints; 93% of them provided high quality genotype calls and 71% of them were polymorphic in a diverse panel of 96 individuals of five different species. SNP reliability was high across nine Eucalyptus species belonging to three sections within subgenus Symphomyrtus and still satisfactory across species of two additional subgenera, although polymorphism declined as phylogenetic distance increased. Conclusions: This study indicates that the GGGT performs well both within and across species of Eucalyptus notwithstanding its nucleotide diversity >= 2%. The development of a much larger array of informative SNPs across multiple Eucalyptus species is feasible, although strongly dependent on having a representative and sufficiently deep collection of sequences from many individuals of each target species. A higher density SNP platform will be instrumental to undertake genome-wide phylogenetic and population genomics studies and to implement molecular breeding by Genomic Selection in Eucalyptus.

A Novel Hepatitis C Virus Genotyping Method Based on Liquid Microarray

The strategy used to treat HCV infection depends on the genotype involved. An accurate and reliable genotyping method is therefore of paramount importance. We describe here, for the first time, the use of a liquid microarray for HCV genotyping. This liquid microarray is based on the 5'UTR - the most highly conserved region of HCV - and the variable region NS5B sequence. The simultaneous genotyping of two regions can be used to confirm findings and should detect inter-genotypic recombination. Plasma samples from 78 patients infected with viruses with genotypes and subtypes determined in the Versant (TM) HCV Genotype Assay LiPA (version I; Siemens Medical Solutions, Diagnostics Division, Fernwald, Germany) were tested with our new liquid microarray method. This method successfully determined the genotypes of 74 of the 78 samples previously genotyped in the Versant (TM) HCV Genotype Assay LiPA (74/78, 95%). The concordance between the two methods was 100% for genotype determination (74/74). At the subtype level, all 3a and 2b samples gave identical results with both methods (17/17 and 7/7, respectively). Two 2c samples were correctly identified by microarray, but could only be determined to the genotype level with the Versant (TM) HCV assay. Genotype ""1'' subtypes (1a and 1b) were correctly identified by the Versant (TM) HCV assay and the microarray in 68% and 40% of cases, respectively. No genotype discordance was found for any sample. HCV was successfully genotyped with both methods, and this is of prime importance for treatment planning. Liquid microarray assays may therefore be added to the list of methods suitable for HCV genotyping. It provides comparable results and may readily be adapted for the detection of other viruses frequently co-infecting HCV patients. Liquid array technology is thus a reliable and promising platform for HCV genotyping.

An assessment of population structure in eight breeds of cattle using a whole genome SNP panel

Background: Analyses of population structure and breed diversity have provided insight into the origin and evolution of cattle. Previously, these studies have used a low density of microsatellite markers, however, with the large number of single nucleotide polymorphism markers that are now available, it is possible to perform genome wide population genetic analyses in cattle. In this study, we used a high-density panel of SNP markers to examine population structure and diversity among eight cattle breeds sampled from Bos indicus and Bos taurus. Results: Two thousand six hundred and forty one single nucleotide polymorphisms ( SNPs) spanning all of the bovine autosomal genome were genotyped in Angus, Brahman, Charolais, Dutch Black and White Dairy, Holstein, Japanese Black, Limousin and Nelore cattle. Population structure was examined using the linkage model in the program STRUCTURE and Fst estimates were used to construct a neighbor-joining tree to represent the phylogenetic relationship among these breeds. Conclusion: The whole-genome SNP panel identified several levels of population substructure in the set of examined cattle breeds. The greatest level of genetic differentiation was detected between the Bos taurus and Bos indicus breeds. When the Bos indicus breeds were excluded from the analysis, genetic differences among beef versus dairy and European versus Asian breeds were detected among the Bos taurus breeds. Exploration of the number of SNP loci required to differentiate between breeds showed that for 100 SNP loci, individuals could only be correctly clustered into breeds 50% of the time, thus a large number of SNP markers are required to replace the 30 microsatellite markers that are currently commonly used in genetic diversity studies.

Genes up- and down-regulated by dermcidin in breast cancer: a microarray analysis

Dermcidin (DCD) is a human gene mapped to chromosome 12q13 region, which is co-amplified with multiple oncogenes with a well-established role in the growth, survival and progression of breast cancers. Here, we present a summary of a DNA microarray-based study that identified the genes that are up- and down-regulated in a human MDA-361 pLKO control clone and three clones expressing short hairpin RNA against three different regions of DCD mRNA. A list of 235 genes was differentially expressed among independent clones (> 3-fold change and P < 0.005). The gene expression of 208 was reduced and of 27 was increased in the three DCD-RNAi clones compared to pLKO control clone. The expression of 77 genes (37%) encoding for enzymes involved in amino acid metabolism, glucose metabolism and oxidoreductase activity and several genes required for cell survival and DNA repair were decreased. The expression of EGFR/ErbB-1 gene, an important predictor of outcome in breast cancer, was reduced together with the genes for betacellulin and amphiregulin, two known ligands of EGFR/ErbB receptors. Many of the 27 genes up-regulated by DCD-RNAi expression have not yet been fully characterized; among those with known function, we identified the calcium-calmodulin-dependent protein kinase-II delta and calcineurin A alpha. We compared 132 up-regulated and 12 down-regulated genes in our dataset with those genes up- and down-regulated by inhibitors targeting various signaling pathway components. The analysis showed that the genes in the DCD pathway are aligned with those functionally influenced by the drugs sirolimus, LY-294002 and wortmannin. Therefore, DCD may exert its function by activating the PI3K/AKT/mTOR signaling pathway. Together, these bioinformatic approaches suggest the involvement of DCD in the regulation of genes for breast cancer cell metabolism, proliferation and survival.

Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence

Background: The malaria parasite Plasmodium falciparum exhibits abundant genetic diversity, and this diversity is key to its success as a pathogen. Previous efforts to study genetic diversity in P. falciparum have begun to elucidate the demographic history of the species, as well as patterns of population structure and patterns of linkage disequilibrium within its genome. Such studies will be greatly enhanced by new genomic tools and recent large-scale efforts to map genomic variation. To that end, we have developed a high throughput single nucleotide polymorphism (SNP) genotyping platform for P. falciparum. Results: Using an Affymetrix 3,000 SNP assay array, we found roughly half the assays (1,638) yielded high quality, 100% accurate genotyping calls for both major and minor SNP alleles. Genotype data from 76 global isolates confirm significant genetic differentiation among continental populations and varying levels of SNP diversity and linkage disequilibrium according to geographic location and local epidemiological factors. We further discovered that nonsynonymous and silent (synonymous or noncoding) SNPs differ with respect to within-population diversity, interpopulation differentiation, and the degree to which allele frequencies are correlated between populations. Conclusions: The distinct population profile of nonsynonymous variants indicates that natural selection has a significant influence on genomic diversity in P. falciparum, and that many of these changes may reflect functional variants deserving of follow-up study. Our analysis demonstrates the potential for new high-throughput genotyping technologies to enhance studies of population structure, natural selection, and ultimately enable genome-wide association studies in P. falciparum to find genes underlying key phenotypic traits.

Functional microarray analysis suggests repressed cell-cell signaling and cell survival-related modules inhibit progression of head and neck squamous cell carcinoma

Background: Cancer shows a great diversity in its clinical behavior which cannot be easily predicted using the currently available clinical or pathological markers. The identification of pathways associated with lymph node metastasis (N+) and recurrent head and neck squamous cell carcinoma (HNSCC) may increase our understanding of the complex biology of this disease. Methods: Tumor samples were obtained from untreated HNSCC patients undergoing surgery. Patients were classified according to pathologic lymph node status (positive or negative) or tumor recurrence (recurrent or non-recurrent tumor) after treatment (surgery with neck dissection followed by radiotherapy). Using microarray gene expression, we screened tumor samples according to modules comprised by genes in the same pathway or functional category. Results: The most frequent alterations were the repression of modules in negative lymph node (N0) and in non-recurrent tumors rather than induction of modules in N+ or in recurrent tumors. N0 tumors showed repression of modules that contain cell survival genes and in non-recurrent tumors cell-cell signaling and extracellular region modules were repressed. Conclusions: The repression of modules that contain cell survival genes in N0 tumors reinforces the important role that apoptosis plays in the regulation of metastasis. In addition, because tumor samples used here were not microdissected, tumor gene expression data are represented together with the stroma, which may reveal signaling between the microenvironment and tumor cells. For instance, in non-recurrent tumors, extracellular region module was repressed, indicating that the stroma and tumor cells may have fewer interactions, which disable metastasis development. Finally, the genes highlighted in our analysis can be implicated in more than one pathway or characteristic, suggesting that therapeutic approaches to prevent tumor progression should target more than one gene or pathway, specially apoptosis and interactions between tumor cells and the stroma.

Selection bias in gene extraction on the basis of microarray gene-expression data

In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.