Knowledge-based analysis of microarray gene expression data by using support vector machines

We introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. We test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, we use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

Identification of sample-specific sequences in mammalian cDNA and genomic DNA by the novel ligation-mediated subtraction (Limes)

The representational difference analysis (RDA) and other subtraction techniques are used to enrich sample-specific sequences by elimination of ubiquitous sequences existing in both the sample of interest (tester) and the subtraction partner (driver). While applying the RDA to genomic DNA of cutaneous lymphoma cells in order to identify tumor relevant alterations, we predominantly isolated repetitive sequences and artificial repeat-mediated fusion products of otherwise independent PCR fragments (PCR hybrids). Since these products severely interfered with the isolation of tester-specific fragments, we developed a considerably more robust and efficient approach, termed ligation-mediated subtraction (Limes). In first applications of Limes, genomic sequences and/or transcripts of genes involved in the regulation of transcription, such as transforming growth factor β stimulated clone 22 related gene (TSC-22R), cell death and cytokine production (caspase-1) or antigen presentation (HLA class II sequences), were found to be completely absent in a cutaneous lymphoma line. On the assumption that mutations in tumor-relevant genes can affect their transcription pattern, a protocol was developed and successfully applied that allows the identification of such sequences. Due to these results, Limes may substitute/supplement other subtraction/comparison techniques such as RDA or DNA microarray techniques in a variety of different research fields.

Exploring the DNA-binding specificities of zinc fingers with DNA microarrays

A key step in the regulation of networks that control gene expression is the sequence-specific binding of transcription factors to their DNA recognition sites. A more complete understanding of these DNA–protein interactions will permit a more comprehensive and quantitative mapping of the regulatory pathways within cells, as well as a deeper understanding of the potential functions of individual genes regulated by newly identified DNA-binding sites. Here we describe a DNA microarray-based method to characterize sequence-specific DNA recognition by zinc-finger proteins. A phage display library, prepared by randomizing critical amino acid residues in the second of three fingers of the mouse Zif268 domain, provided a rich source of zinc-finger proteins with variant DNA-binding specificities. Microarrays containing all possible 3-bp binding sites for the variable zinc fingers permitted the quantitation of the binding site preferences of the entire library, pools of zinc fingers corresponding to different rounds of selection from this library, as well as individual Zif268 variants that were isolated from the library by using specific DNA sequences. The results demonstrate the feasibility of using DNA microarrays for genome-wide identification of putative transcription factor-binding sites.

Screening insertion libraries for mutations in many genes simultaneously using DNA microarrays

We describe a method to screen pools of DNA from multiple transposon lines for insertions in many genes simultaneously. We use thermal asymmetric interlaced–PCR, a hemispecific PCR amplification protocol that combines nested, insertion-specific primers with degenerate primers, to amplify DNA flanking the transposons. In reconstruction experiments with previously characterized Arabidopsis lines carrying insertions of the maize Dissociation (Ds) transposon, we show that fluorescently labeled, transposon-flanking fragments overlapping ORFs hybridize to cognate expressed sequence tags (ESTs) on a DNA microarray. We further show that insertions can be detected in DNA pools from as many as 100 plants representing different transposon lines and that all of the tested, transposon-disrupted genes whose flanking fragments can be amplified individually also can be detected when amplified from the pool. The ability of a transposon-flanking fragment to hybridize declines rapidly with decreasing homology to the spotted DNA fragment, so that only ESTs with >90% homology to the transposon-disrupted gene exhibit significant cross-hybridization. Because thermal asymmetric interlaced–PCR fragments tend to be short, use of the present method favors recovery of insertions in and near genes. We apply the technique to screening pools of new Ds lines using cDNA microarrays containing ESTs for ≈1,000 stress-induced and -repressed Arabidopsis genes.

Análise de expressão gênica de Xylella fastidiosa cultivada em diferentes concentrações de glicose pela técnica de microarrays de DNA

Xylella fastidiosa (Xf) é o agente etiológico causador de doenças em uma grande variedade de cultivos de grande importância econômica, causando a c1orose variegada dos citros, uma das doenças mais danosas à indústria de citros no Brasil. Os genomas de algumas cepas deste fitopatógeno foram completamente seqüenciados promovendo assim estudos funcionais do genoma em larga escala. Neste trabalho nós nos propusemos a investigar o perfil de transcrição de Xf através da técnica microarranjos (no título da dissertação microarrays, mas a partir de agora usaremos microaarranjos) de DNA usando todo o genoma do fitopatógeno e cultivando-a sob meio definido variando a concentração de glicose. O objetivo inicial deste trabalho era observar se Xf comportava-se da mesma forma que Xac, que tem a expressão de goma aumentada devido ao aumento da concentração de glicose do meio. Nossas análises revelaram que enquanto os transcritos relacionados à goma não se mostraram afetados com a concentração de glicose, genes que codificam para análogos a Colicina-V e precursores de fimbria foram induzidos em alta concentração de glicose. Baseados nestes resultados, nós propusemos um modelo de mecanismo de produção e defesa contra a Colicina em Xf.

MILVA:An interactive tool for the exploration of multidimensional microarray data

Clustering techniques such as k-means and hierarchical clustering are commonly used to analyze DNA microarray derived gene expression data. However, the interactions between processes underlying the cell activity suggest that the complexity of the microarray data structure may not be fully represented with discrete clustering methods.

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.

mRNA-Seq and microarray development for the Grooved carpet shell clam, Ruditapes decussatus: a functional approach to unravel host -parasite interaction

Background The Grooved Carpet shell clam Ruditapes decussatus is the autochthonous European clam and the most appreciated from a gastronomic and economic point of view. The production is in decline due to several factors such as Perkinsiosis and habitat invasion and competition by the introduced exotic species, the manila clam Ruditapes philippinarum. After we sequenced R. decussatus transcriptome we have designed an oligo microarray capable of contributing to provide some clues on molecular response of the clam to Perkinsiosis. Results A database consisting of 41,119 unique transcripts was constructed, of which 12,479 (30.3%) were annotated by similarity. An oligo-DNA microarray platform was then designed and applied to profile gene expression in R. decussatus heavily infected by Perkinsus olseni. Functional annotation of differentially expressed genes between those two conditionswas performed by gene set enrichment analysis. As expected, microarrays unveil genes related with stress/infectious agents such as hydrolases, proteases and others. The extensive role of innate immune system was also analyzed and effect of parasitosis upon expression of important molecules such as lectins reviewed. Conclusions This study represents a first attempt to characterize Ruditapes decussatus transcriptome, an important marine resource for the European aquaculture. The trancriptome sequencing and consequent annotation will increase the available tools and resources for this specie, introducing the possibility of high throughput experiments such as microarrays analysis. In this specific case microarray approach was used to unveil some important aspects of host-parasite interaction between the Carpet shell clam and Perkinsus, two non-model species, highlighting some genes associated with this interaction. Ample information was obtained to identify biological processes significantly enriched among differentially expressed genes in Perkinsus infected versus non-infected gills. An overview on the genes related with the immune system on R. decussatus transcriptome is also reported.

Utility of a panviral microarray for detection of swine respiratory viruses in clinical samples

Several factors have recently converged, elevating the need for highly parallel diagnostic platforms that have the ability to detect many known, novel, and emerging pathogenic agents simultaneously. Panviral DNA microarrays represent the most robust approach for massively parallel viral surveillance and detection. The Virochip is a panviral DNA microarray that is capable of detecting all known viruses, as well as novel viruses related to known viral families, in a single assay and has been used to successfully identify known and novel viral agents in clinical human specimens. However, the usefulness and the sensitivity of the Virochip platform have not been tested on a set of clinical veterinary specimens with the high degree of genetic variance that is frequently observed with swine virus field isolates. In this report, we investigate the utility and sensitivity of the Virochip to positively detect swine viruses in both cell culture-derived samples and clinical swine samples. The Virochip successfully detected porcine reproductive and respiratory syndrome virus (PRRSV) in serum containing 6.10 × 10(2) viral copies per microliter and influenza A virus in lung lavage fluid containing 2.08 × 10(6) viral copies per microliter. The Virochip also successfully detected porcine circovirus type 2 (PCV2) in serum containing 2.50 × 10(8) viral copies per microliter and porcine respiratory coronavirus (PRCV) in turbinate tissue homogenate. Collectively, the data in this report demonstrate that the Virochip can successfully detect pathogenic viruses frequently found in swine in a variety of solid and liquid specimens, such as turbinate tissue homogenate and lung lavage fluid, as well as antemortem samples, such as serum.

Gene expression down-regulation in CD90(+) prostate tumor-associated stromal cells involves potential organ-specific genes

Background: The prostate stroma is a key mediator of epithelial differentiation and development, and potentially plays a role in the initiation and progression of prostate cancer. The tumor-associated stroma is marked by increased expression of CD90/THYI. Isolation and characterization of these stromal cells could provide valuable insight into the biology of the tumor microenvironment. Methods: Prostate CD90(+) stromal fibromuscular cells from tumor specimens were isolated by cell-sorting and analyzed by DNA microarray. Dataset analysis was used to compare gene expression between histologically normal and tumor-associated stromal cells. For comparison, stromal cells were also isolated and analyzed from the urinary bladder. Results: The tumor-associated stromal cells were found to have decreased expression of genes involved in smooth muscle differentiation, and those detected in prostate but not bladder. Other differential expression between the stromal cell types included that of the CXC-chemokine genes. Conclusion: CD90(+) prostate tumor-associated stromal cells differed from their normal counterpart in expression of multiple genes, some of which are potentially involved in organ development.

Differential gene expression between the biotrophic-like and saprotrophic mycelia of the witches` broom pathogen Moniliophthora perniciosa

Moniliophthora perniciosa is a hemibiotrophic fungus that causes witches` broom disease (WBD) in cacao. Marked dimorphism characterizes this fungus, showing a monokaryotic or biotrophic phase that causes disease symptoms and a later dikaryotic or saprotrophic phase. A combined strategy of DNA microarray, expressed sequence tag, and real-time reverse-transcriptase polymerase chain reaction analyses was employed to analyze differences between these two fungal stages in vitro. In all, 1,131 putative genes were hybridized with cDNA from different phases, resulting in 189 differentially expressed genes, and 4,595 reads were clusterized, producing 1,534 unigenes. The analysis of these genes, which represent approximately 21% of the total genes, indicates that the biotrophic-like phase undergoes carbon and nitrogen catabollite repression that correlates to the expression of phytopathogenicity genes. Moreover, downregulation of mitochondrial oxidative phosphorylation and the presence of a putative ngr1 of Saccharomyces cerevisiae could help explain its lower growth rate. In contrast, the saprotrophic mycelium expresses genes related to the metabolism of hexoses, ammonia, and oxidative phosphorylation, which could explain its faster growth. Antifungal toxins were upregulated and could prevent the colonization by competing fungi. This work significantly contributes to our understanding of the molecular mechanisms of WBD and, to our knowledge, is the first to analyze differential gene expression of the different phases of a hemibiotrophic fungus.

Decreased AIRE Expression and Global Thymic Hypofunction in Down Syndrome

The Down syndrome (DS) immune phenotype is characterized by thymus hypotrophy, higher propensity to organ-specific autoimmune disorders, and higher susceptibility to infections, among other features. Considering that AIRE (autoimmune regulator) is located on 21q22.3, we analyzed protein and gene expression in surgically removed thymuses from 14 DS patients with congenital heart defects, who were compared with 42 age-matched controls with heart anomaly as an isolated malformation. Immunohistochemistry revealed 70.48 +/- 49.59 AIRE-positive cells/mm(2) in DS versus 154.70 +/- 61.16 AIRE-positive cells/mm(2) in controls (p < 0.0001), and quantitative PCR as well as DNA microarray data confirmed those results. The number of FOXP3-positive cells/mm(2) was equivalent in both groups. Thymus transcriptome analysis showed 407 genes significantly hypoexpressed in DS, most of which were related, according to network transcriptional analysis (FunNet), to cell division and to immunity. Immune response-related genes included those involved in 1) Ag processing and presentation (HLA-DQB1, HLA-DRB3, CD1A, CD1B, CD1C, ERAP) and 2) thymic T cell differentiation (IL2RG, RAG2, CD3D, CD3E, PRDX2, CDK6) and selection (SH2D1A, CD74). It is noteworthy that relevant AIRE-partner genes, such as TOP2A, LAMNB1, and NUP93, were found hypoexpressed in DNA microarrays and quantitative real-time PCR analyses. These findings on global thymic hypofunction in DS revealed molecular mechanisms underlying DS immune phenotype and strongly suggest that DS immune abnormalities are present since early development, rather than being a consequence of precocious aging, as widely hypothesized. Thus, DS should be considered as a non-monogenic primary immunodeficiency. The Journal of Immunology, 2011, 187: 3422-3430.

Maternal embryonic leucine zipper kinase transcript abundance correlates with malignancy grade in human astrocytomas

We have performed cDNA microarray analyses to identify gene expression differences between highly invasive glioblastoma multiforme (GBM) and typically benign pilocytic astrocytomas (PA). Despite the significant clinical and pathological differences between the 2 tumor types, only 63 genes were found to exhibit 2-fold or greater overexpression in GBM as compared to PA. Forty percent of these genes are related to the regulation of the cell cycle and mitosis. QT-PCR validation of 6 overexpressed genes: MELK, AUKB, ASPM, PRC1, IL13RA2 and KIAA0101 confirmed at least a 5-fold increase in the average expression levels in GBM. Maternal embryonic leucine zipper kinase (MELK) exhibited the most statistically significant difference. A more detailed investigation of MELK expression was undertaken to study its oncogenic relevance. In the examination of more than 100 tumors of the central nervous system, we found progressively higher expression of MELK with astrocytoma grade and a noteworthy uniformity of high level expression in GBM. Similar level of overexpression was also observed in medulloblastoma. We found neither gene promoter hypomethylation nor amplification to be a factor in MELK expression, but were able to demonstrate that MELK knockdown in malignant astrocytoma cell lines caused a reduction in proliferation and anchorage-independent growth in in vitro assays. Our results indicate that GBM and PA differ by the expression of surprisingly few genes. Among them, MELK correlated with malignancy grade in astrocytomas and represents a therapeutic target for the management of the most frequent brain tumors in adult and children. (C) 2007 Wiley-Liss, Inc.

Gene Expression in Brain: A Window on Ethanol Dependence, Neuroadaptation, and Preference

This article represents the proceedings of a symposium at the 2002 joint RSA/ISBRA Conference in San Francisco, California. The organizer was Paula L. Hoffman and the co-chairs were Paula L. Hoffman and Michael Miles. The presentations were (1) Introduction and overview of the use of DNA microarrays, by Michael Miles; (2) DNA microarray analysis of gene expression in brains of P and NP rats, by Howard J. Edenberg; (3) Gene expression patterns in brain regions of AA and ANA rats, by Wolfgang Sommer; (4) Patterns of gene expression in brains of selected lines of mice that differ in ethanol tolerance, by Boris Tabakoff; (5) Gene expression profiling related to initial sensitivity and tolerance in gamma-protein kinase C mutants, by Jeanne Wehner; and (6) Gene expression patterns in human alcoholic brain: from microarrays to protein profiles, by Joanne Lewohl.

Gene expression databases and data mining.

The DNA microarray technology has arguably caught the attention of the worldwide life science community and is now systematically supporting major discoveries in many fields of study. The majority of the initial technical challenges of conducting experiments are being resolved, only to be replaced with new informatics hurdles, including statistical analysis, data visualization, interpretation, and storage. Two systems of databases, one containing expression data and one containing annotation data are quickly becoming essential knowledge repositories of the research community. This present paper surveys several databases, which are considered "pillars" of research and important nodes in the network. This paper focuses on a generalized workflow scheme typical for microarray experiments using two examples related to cancer research. The workflow is used to reference appropriate databases and tools for each step in the process of array experimentation. Additionally, benefits and drawbacks of current array databases are addressed, and suggestions are made for their improvement.