Istepanian, Robert S H; Sungoor, Ala; Nebel, Jean-Christophe
Genomic signal processing is a new area of research that combines advanced digital signal processing methodologies for enhanced genetic data analysis. It has many promising applications in bioinformatics and next generation of healthcare systems, in particular, in the field of microarray data clustering. In this paper we present a comparative performance analysis of enhanced digital spectral analysis methods for robust clustering of gene expression across multiple microarray data samples. Three digital signal processing methods: linear predictive coding, wavelet decomposition, and fractal dimension are studied to provide a comparative evaluation of the clustering performance of these methods on several microarray datasets. The results of this study show that the fractal approach provides the best clustering accuracy compared to other digital signal processing and well known statistical methods.
Smith Andrew M
Full Text Available Abstract Background Microarrays are an invaluable tool in many modern genomic studies. It is generally perceived that decreasing the size of microarray features leads to arrays with higher resolution (due to greater feature density, but this increase in resolution can compromise sensitivity. Results We demonstrate that barcode microarrays with smaller features are equally capable of detecting variation in DNA barcode intensity when compared to larger feature sizes within a specific microarray platform. The barcodes used in this study are the well-characterized set derived from the Yeast KnockOut (YKO collection used for screens of pooled yeast (Saccharomyces cerevisiae deletion mutants. We treated these pools with the glycosylation inhibitor tunicamycin as a test compound. Three generations of barcode microarrays at 30, 8 and 5 μm features sizes independently identified the primary target of tunicamycin to be ALG7. Conclusion We show that the data obtained with 5 μm feature size is of comparable quality to the 30 μm size and propose that further shrinking of features could yield barcode microarrays with equal or greater resolving power and, more importantly, higher density.
Carvalho, B; Ouwerkerk, E; Meijer, G.A.; Ylstra, B.
BACKGROUND: Currently, comparative genomic hybridisation array (array CGH) is the method of choice for studying genome wide DNA copy number changes. To date, either amplified representations of bacterial artificial chromosomes (BACs)/phage artificial chromosomes (PACs) or cDNAs have been spotted as
Woodward Martin J
Full Text Available Abstract Background Microarray based comparative genomic hybridisation (CGH experiments have been used to study numerous biological problems including understanding genome plasticity in pathogenic bacteria. Typically such experiments produce large data sets that are difficult for biologists to handle. Although there are some programmes available for interpretation of bacterial transcriptomics data and CGH microarray data for looking at genetic stability in oncogenes, there are none specifically to understand the mosaic nature of bacterial genomes. Consequently a bottle neck still persists in accurate processing and mathematical analysis of these data. To address this shortfall we have produced a simple and robust CGH microarray data analysis process that may be automated in the future to understand bacterial genomic diversity. Results The process involves five steps: cleaning, normalisation, estimating gene presence and absence or divergence, validation, and analysis of data from test against three reference strains simultaneously. Each stage of the process is described and we have compared a number of methods available for characterising bacterial genomic diversity, for calculating the cut-off between gene presence and absence or divergence, and shown that a simple dynamic approach using a kernel density estimator performed better than both established, as well as a more sophisticated mixture modelling technique. We have also shown that current methods commonly used for CGH microarray analysis in tumour and cancer cell lines are not appropriate for analysing our data. Conclusion After carrying out the analysis and validation for three sequenced Escherichia coli strains, CGH microarray data from 19 E. coli O157 pathogenic test strains were used to demonstrate the benefits of applying this simple and robust process to CGH microarray studies using bacterial genomes.
Ruth B Lathi
Full Text Available PURPOSE: The metaphase karyotype is often used as a diagnostic tool in the setting of early miscarriage; however this technique has several limitations. We evaluate a new technique for karyotyping that uses single nucleotide polymorphism microarrays (SNP. This technique was compared in a blinded, prospective fashion, to the traditional metaphase karyotype. METHODS: Patients undergoing dilation and curettage for first trimester miscarriage between February and August 2010 were enrolled. Samples of chorionic villi were equally divided and sent for microarray testing in parallel with routine cytogenetic testing. RESULTS: Thirty samples were analyzed, with only four discordant results. Discordant results occurred when the entire genome was duplicated or when a balanced rearrangement was present. Cytogenetic karyotyping took an average of 29 days while microarray-based karytoyping took an average of 12 days. CONCLUSIONS: Molecular karyotyping of POC after missed abortion using SNP microarray analysis allows for the ability to detect maternal cell contamination and provides rapid results with good concordance to standard cytogenetic analysis.
Song Joon J
Full Text Available Abstract Background With the growing abundance of microarray data, statistical methods are increasingly needed to integrate results across studies. Two common approaches for meta-analysis of microarrays include either combining gene expression measures across studies or combining summaries such as p-values, probabilities or ranks. Here, we compare two Bayesian meta-analysis models that are analogous to these methods. Results Two Bayesian meta-analysis models for microarray data have recently been introduced. The first model combines standardized gene expression measures across studies into an overall mean, accounting for inter-study variability, while the second combines probabilities of differential expression without combining expression values. Both models produce the gene-specific posterior probability of differential expression, which is the basis for inference. Since the standardized expression integration model includes inter-study variability, it may improve accuracy of results versus the probability integration model. However, due to the small number of studies typical in microarray meta-analyses, the variability between studies is challenging to estimate. The probability integration model eliminates the need to model variability between studies, and thus its implementation is more straightforward. We found in simulations of two and five studies that combining probabilities outperformed combining standardized gene expression measures for three comparison values: the percent of true discovered genes in meta-analysis versus individual studies; the percent of true genes omitted in meta-analysis versus separate studies, and the number of true discovered genes for fixed levels of Bayesian false discovery. We identified similar results when pooling two independent studies of Bacillus subtilis. We assumed that each study was produced from the same microarray platform with only two conditions: a treatment and control, and that the data sets
Full Text Available Abstract Background The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH. One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment. Results We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser. Conclusion ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.
Full Text Available Microarray comparative genomic hybridisation (aCGH provides an estimate of the relative abundance of genomic DNA (gDNA taken from comparator and reference organisms by hybridisation to a microarray containing probes that represent sequences from the reference organism. The experimental method is used in a number of biological applications, including the detection of human chromosomal aberrations, and in comparative genomic analysis of bacterial strains, but optimisation of the analysis is desirable in each problem domain.We present a method for analysis of bacterial aCGH data that encodes spatial information from the reference genome in a hidden Markov model. This technique is the first such method to be validated in comparisons of sequenced bacteria that diverge at the strain and at the genus level: Pectobacterium atrosepticum SCRI1043 (Pba1043 and Dickeya dadantii 3937 (Dda3937; and Lactococcus lactis subsp. lactis IL1403 and L. lactis subsp. cremoris MG1363. In all cases our method is found to outperform common and widely used aCGH analysis methods that do not incorporate spatial information. This analysis is applied to comparisons between commercially important plant pathogenic soft-rotting enterobacteria (SRE Pba1043, P. atrosepticum SCRI1039, P. carotovorum 193, and Dda3937.Our analysis indicates that it should not be assumed that hybridisation strength is a reliable proxy for sequence identity in aCGH experiments, and robustly extends the applicability of aCGH to bacterial comparisons at the genus level. Our results in the SRE further provide evidence for a dynamic, plastic 'accessory' genome, revealing major genomic islands encoding gene products that provide insight into, and may play a direct role in determining, variation amongst the SRE in terms of their environmental survival, host range and aetiology, such as phytotoxin synthesis, multidrug resistance, and nitrogen fixation.
Moerman Donald G
Full Text Available Abstract Background Microarray comparative genomic hybridization (CGH is currently one of the most powerful techniques to measure DNA copy number in large genomes. In humans, microarray CGH is widely used to assess copy number variants in healthy individuals and copy number aberrations associated with various diseases, syndromes and disease susceptibility. In model organisms such as Caenorhabditis elegans (C. elegans the technique has been applied to detect mutations, primarily deletions, in strains of interest. Although various constraints on oligonucleotide properties have been suggested to minimize non-specific hybridization and improve the data quality, there have been few experimental validations for CGH experiments. For genomic regions where strict design filters would limit the coverage it would also be useful to quantify the expected loss in data quality associated with relaxed design criteria. Results We have quantified the effects of filtering various oligonucleotide properties by measuring the resolving power for detecting deletions in the human and C. elegans genomes using NimbleGen microarrays. Approximately twice as many oligonucleotides are typically required to be affected by a deletion in human DNA samples in order to achieve the same statistical confidence as one would observe for a deletion in C. elegans. Surprisingly, the ability to detect deletions strongly depends on the oligonucleotide 15-mer count, which is defined as the sum of the genomic frequency of all the constituent 15-mers within the oligonucleotide. A similarity level above 80% to non-target sequences over the length of the probe produces significant cross-hybridization. We recommend the use of a fairly large melting temperature window of up to 10°C, the elimination of repeat sequences, the elimination of homopolymers longer than 5 nucleotides, and a threshold of -1 kcal/mol on the oligonucleotide self-folding energy. We observed very little difference in data
Gao, Wu-Jun; Li, Shu-Fen; Zhang, Guo-Jun; Wang, Ning-Na; Deng, Chuan-Liang; Lu, Long-Dou
To identify rapidly a number of genes probably involved in sex determination and differentiation of the dioecious plant Asparagus officinalis, gene expression profiles in early flower development for male and female plants were investigated by microarray assay with 8,665 probes. In total, 638 male-biased and 543 female-biased genes were identified. These genes with biased-expression for male and female were involved in a variety of processes associated with molecular functions, cellular components, and biological processes, suggesting that a complex mechanism underlies the sex development of asparagus. Among the differentially expressed genes involved in the reproductive process, a number of genes associated with floral development were identified. Reverse transcription-PCR was performed for validation, and the results were largely consistent with those obtained by microarray analysis. The findings of this study might contribute to understanding of the molecular mechanisms of sex determination and differentiation in dioecious asparagus and provide a foundation for further studies of this plant.
Willenbrock, Hanni; Salomon, Jesper; Søkilde, Rolf
Recently, next-generation sequencing has been introduced as a promising, new platform for assessing the copy number of transcripts, while the existing microarray technology is considered less reliable for absolute, quantitative expression measurements. Nonetheless, so far, results from the two...... technologies have only been compared based on biological data, leading to the conclusion that, although they are somewhat correlated, expression values differ significantly. Here, we use synthetic RNA samples, resembling human microRNA samples, to find that microarray expression measures actually correlate...... better with sample RNA content than expression measures obtained from sequencing data. In addition, microarrays appear highly sensitive and perform equivalently to next-generation sequencing in terms of reproducibility and relative ratio quantification....
Leimena, M.M.; Wels, M.; Bongers, R.; Smid, E.J.; Zoetendal, E.G.; Kleerebezem, M.
RNA sequencing is starting to compete with the use of DNA microarrays for transcription analysis in eukaryotes as well as in prokaryotes. Application of RNA sequencing in prokaryotes requires additional steps in the RNA preparation procedure to increase the relative abundance of mRNA and cannot
Skinner, M.; Robertson, L.B.; Tempest, H.G.; Langley, E.J.; Ioannou, D.; Fowler, K.E.; Crooijmans, R.P.M.A.
Background: The availability of the complete chicken (Gallus gallus) genome sequence as well as a large number of chicken probes for fluorescent in-situ hybridization (FISH) and microarray resources facilitate comparative genomic studies between chicken and other bird species. In a previous study, w
Bhawe, Kaumudi M.; Aghi, Manish K.
Microarray analysis in glioblastomas is done using either cell lines or patient samples as starting material. A survey of the current literature points to transcript-based microarrays and immunohistochemistry (IHC)-based tissue microarrays as being the preferred methods of choice in cancers of neurological origin. Microarray analysis may be carried out for various purposes including the following: To correlate gene expression signatures of glioblastoma cell lines or tumors with response to chemotherapy (DeLay et al., Clin Cancer Res 18(10):2930–2942, 2012)To correlate gene expression patterns with biological features like proliferation or invasiveness of the glioblastoma cells (Jiang et al., PLoS One 8(6):e66008, 2013)To discover new tumor classificatory systems based on gene expression signature, and to correlate therapeutic response and prognosis with these signatures (Huse et al., Annu Rev Med 64(1):59–70, 2013; Verhaak et al., Cancer Cell 17(1):98–110, 2010) While investigators can sometimes use archived tumor gene expression data available from repositories such as the NCBI Gene Expression Omnibus to answer their questions, new arrays must often be run to adequately answer specific questions. Here, we provide a detailed description of microarray methodologies, how to select the appropriate methodology for a given question, and analytical strategies that can be used. Experimental methodology for protein microarrays is outside the scope of this chapter, but basic sample preparation techniques for transcript-based microarrays are included here. PMID:26113463
Fowler Katie E
Full Text Available Abstract Background The availability of the complete chicken (Gallus gallus genome sequence as well as a large number of chicken probes for fluorescent in-situ hybridization (FISH and microarray resources facilitate comparative genomic studies between chicken and other bird species. In a previous study, we provided a comprehensive cytogenetic map for the turkey (Meleagris gallopavo and the first analysis of copy number variants (CNVs in birds. Here, we extend this approach to the Pekin duck (Anas platyrhynchos, an obvious target for comparative genomic studies due to its agricultural importance and resistance to avian flu. Results We provide a detailed molecular cytogenetic map of the duck genome through FISH assignment of 155 chicken clones. We identified one inter- and six intrachromosomal rearrangements between chicken and duck macrochromosomes and demonstrated conserved synteny among all microchromosomes analysed. Array comparative genomic hybridisation revealed 32 CNVs, of which 5 overlap previously designated "hotspot" regions between chicken and turkey. Conclusion Our results suggest extensive conservation of avian genomes across 90 million years of evolution in both macro- and microchromosomes. The data on CNVs between chicken and duck extends previous analyses in chicken and turkey and supports the hypotheses that avian genomes contain fewer CNVs than mammalian genomes and that genomes of evolutionarily distant species share regions of copy number variation ("CNV hotspots". Our results will expedite duck genomics, assist marker development and highlight areas of interest for future evolutionary and functional studies.
Jason H. Moore
Full Text Available The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a fl exible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occurring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profi les of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specifi c gene expression patterns having both statistical and biological signifi cance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the fl exibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org.
Stewart J McD
Full Text Available Abstract Background Semigamy in cotton is a type of facultative apomixis controlled by an incompletely dominant autosomal gene (Se. During semigamy, the sperm and egg cells undergo cellular fusion, but the sperm and egg nucleus fail to fuse in the embryo sac, giving rise to diploid, haploid, or chimeric embryos composed of sectors of paternal and maternal origin. In this study we sought to identify differentially expressed genes related to the semigamy genotype by implementing a comparative microarray analysis of anthers and ovules between a non-semigametic Pima S-1 cotton and its doubled haploid natural isogenic mutant semigametic 57-4. Selected differentially expressed genes identified by the microarray results were then confirmed using quantitative reverse transcription PCR (qRT-PCR. Results The comparative analysis between isogenic 57-4 and Pima S-1 identified 284 genes in anthers and 1,864 genes in ovules as being differentially expressed in the semigametic genotype 57-4. Based on gene functions, 127 differentially expressed genes were common to both semigametic anthers and ovules, with 115 being consistently differentially expressed in both tissues. Nine of those genes were selected for qRT-PCR analysis, seven of which were confirmed. Furthermore, several well characterized metabolic pathways including glycolysis/gluconeogenesis, carbon fixation in photosynthetic organisms, sesquiterpenoid biosynthesis, and the biosynthesis of and response to plant hormones were shown to be affected by differentially expressed genes in the semigametic tissues. Conclusion As the first report using microarray analysis, several important metabolic pathways affected by differentially expressed genes in the semigametic cotton genotype have been identified and described in detail. While these genes are unlikely to be the semigamy gene itself, the effects associated with expression changes in those genes do mimic phenotypic traits observed in semigametic plants
Kyndi, Marianne; Sørensen, Flemming Brandt; Knudsen, H
INTRODUCTION: The tissue microarray (TMA) technique comprises the potential of significantly reducing time and tissue spent on slicing and performing immunohistochemical (IHC) stainings of paraffin-embedded tumor tissue. Tissue heterogeneity is an argument against using TMAs, which has been dealt...
Kyndi, M.; Sorensen, F.B.; Overgaard, M.
Introduction. The tissue microarray (TMA) technique comprises the potential of significantly reducing time and tissue spent on slicing and performing immunohistochemical (IHC) stainings of paraffin-embedded tumor tissue. Tissue heterogeneity is an argument against using TMAs, which has been dealt...
Im, Jong-Hyuk; Kim, Myung-Gun; Kim, Eung-Soo
Avermectin and its analogs are major commercial antiparasitic agents in the fields of animal health, agriculture, and human infections. To increase our understanding about the genetic mechanism underlying avermectin overproduction, comparative transcriptomes were analyzed between the low producer S. avermitilis ATCC31267 and the high producer S. avermitilis ATCC31780 via a S. avermitilis whole genome chip. The comparative transcriptome analysis revealed that fifty S. avermitilis genes were expressed at least two-fold higher in S. avermitilis ATCC31780. In particular, all the avermectin biosynthetic genes, including polyketide synthase (PKS) genes and an avermectin pathway-specific regulatory gene, were less expressed in the%low producer S. avermitilis ATCC31267. The present results imply that avermectin overproduction in S. avermitilis ATCC31780 could be attributed to the previously unidentified fifty genes reported here and increased transcription levels of avermectin PKS genes.
Leimena, M.M.; Wels, M.W.; Bongers, R.S.; Smid, E.J.; Zoetendal, E.G.; Kleerebezem, M.
RNA sequencing is starting to compete with the use of DNA microarrays for transcription analysis in eukaryotes as well as in prokaryotes. The application of RNA sequencing in prokaryotes requires additional steps in the RNA preparation procedure to increase the relative abundance of mRNA and cannot
Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z-score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z-score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z-score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications.
Oikawa, Masahiro; Yoshiura, Koh-ichiro; Kondo, Hisayoshi; Miura, Shiro; Nagayasu, Takeshi; Nakashima, Masahiro
It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide aCGH analysis. Our results suggested that A
Full Text Available Abstract Background It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN, which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH. Methods Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. Results The mean of the derivative log ratio spread (DLRSpread, which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05. The concordance of results between aCGH and fluorescence in situ hybridization (FISH for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively. The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15. Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40. Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005 independent factor which was associated with larger total length of CNA of breast cancers. Conclusions Thus, archival FFPE tissues from A-bomb survivors are useful for
Kyndi, Marianne; Sørensen, Flemming Brandt; Knudsen, H;
&c trials, were IHC stained for ER, PgR and HER2. In addition, ER and PgR were measured in the DBCG82 b&c trials by a biochemical analysis. Statistical analyses included Kappa statistics, Kaplan-Meier survival curves, Log-rank tests, and Cox regression hazards analyses. RESULTS AND CONCLUSION: IHC stainings...... stainings of TMA cores and biochemical analyses. Divergence between IHC and biochemical analyses was predominantly due to the chosen thresholds. IHC staining of one 1mm core from each tumor revealed a significant independent prognostic value of PgR and HER2 on overall survival. In conclusion, IHC stainings...... cores and biochemical analyses. PATIENTS AND METHODS: A central and a peripheral 1mm core and a whole section from each of 54 paraffin blocks from 27 breast cancers included in a one-institution cohort, and a single 1mm central TMA core, from each breast tumor from 1000 patients included in the DBCG82 b...
Frédéric J J Chain
Full Text Available BACKGROUND: Prefabricated expression microarrays are currently available for only a few species but methods have been proposed to extend their application to comparisons between divergent genomes. METHODOLOGY/PRINCIPAL FINDINGS: Here we demonstrate that the hybridization intensity of genomic DNA is a poor basis on which to select unbiased probes on Affymetrix expression arrays for studies of comparative transcriptomics, and that doing so produces spurious results. We used the Affymetrix Xenopus laevis microarray to evaluate expression divergence between X. laevis, X. borealis, and their F1 hybrids. When data are analyzed with probes that interrogate only sequences with confirmed identity in both species, we recover results that differ substantially analyses that use genomic DNA hybridizations to select probes. CONCLUSIONS/SIGNIFICANCE: Our findings have implications for the experimental design of comparative expression studies that use single-species microarrays, and for our understanding of divergent expression in hybrid clawed frogs. These findings also highlight important limitations of single-species microarrays for studies of comparative transcriptomics of polyploid species.
Marcel von der Haar
Full Text Available DNA-Microarrays have become a potent technology for high-throughput analysis of genetic regulation. However, the wide dynamic range of signal intensities of fluorophore-based microarrays exceeds the dynamic range of a single array scan by far, thus limiting the key benefit of microarray technology: parallelization. The implementation of multi-scan techniques represents a promising approach to overcome these limitations. These techniques are, in turn, limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner’s laser light. In this paper the photobleaching characteristics of cyanine-3 and cyanine-5 as part of solid state DNA microarrays are studied. The effects of initial fluorophore intensity as well as laser scanner dependent variables such as the photomultiplier tube’s voltage on bleaching and imaging are investigated. The resulting data is used to develop a model capable of simulating the expected degree of signal intensity reduction caused by photobleaching for each fluorophore individually, allowing for the removal of photobleaching-induced, systematic bias in multi-scan procedures. Single-scan applications also benefit as they rely on pre-scans to determine the optimal scanner settings. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the lab-to-lab comparability of microarray experiment results.
Duk Kyung Kim
Full Text Available Relative expression levels of immune- and non-immune-related mRNAs in chicken intestinal intraepithelial lymphocytes experimentally infected with Eimeria acervulina, E. maxima, or E. tenella were measured using a 10K cDNA microarray. Based on a cutoff of >2.0-fold differential expression compared with uninfected controls, relatively equal numbers of transcripts were altered by the three Eimeria infections at 1, 2, and 3 days post-primary infection. By contrast, E. tenella elicited the greatest number of altered transcripts at 4, 5, and 6 days post-primary infection, and at all time points following secondary infection. When analyzed on the basis of up- or down-regulated transcript levels over the entire 6 day infection periods, approximately equal numbers of up-regulated transcripts were detected following E. tenella primary (1,469 and secondary (1,459 infections, with a greater number of down-regulated mRNAs following secondary (1,063 vs. primary (890 infection. On the contrary, relatively few mRNA were modulated following primary infection with E. acervulina (35 up, 160 down or E. maxima (65 up, 148 down compared with secondary infection (E. acervulina, 1,142 up, 1,289 down; E. maxima, 368 up, 1,349 down. With all three coccidia, biological pathway analysis identified the altered transcripts as belonging to the categories of "Disease and Disorder" and "Physiological System Development and Function". Sixteen intracellular signaling pathways were identified from the differentially expressed transcripts following Eimeria infection, with the greatest significance observed following E. acervulina infection. Taken together, this new information will expand our understanding of host-pathogen interactions in avian coccidiosis and contribute to the development of novel disease control strategies.
Alberts, Rudi; Fu, Jingyuan; Swertz, Morris A.; Lubbers, L. Alrik; Albers, Casper J.; Jansen, Ritsert C.
Gene expression can be studied at a genome-wide scale with the aid of modern microarray technologies. Expression profiling of tens to hundreds of individuals in a genetic population can reveal the consequences of genetic variation. In this paper it is argued that the design and analysis of such a
Alberts, Rudi; Fu, Jingyuan; Swertz, Morris A.; Lubbers, L. Alrik; Albers, Casper J.; Jansen, Ritsert C.
Gene expression can be studied at a genome-wide scale with the aid of modern microarray technologies. Expression profiling of tens to hundreds of individuals in a genetic population can reveal the consequences of genetic variation. In this paper it is argued that the design and analysis of such a st
A meta-analysis of public microarray data identifies gene regulatory pathways deregulated in peripheral blood mononuclear cells from individuals with Systemic Lupus Erythematosus compared to those without.
Kröger, Wendy; Mapiye, Darlington; Entfellner, Jean-Baka Domelevo; Tiffin, Nicki
Systemic Lupus Erythematosus (SLE) is a complex, multi-systemic, autoimmune disease for which the underlying aetiological mechanisms are poorly understood. The genetic and molecular processes underlying lupus have been extensively investigated using a variety of -omics approaches, including genome-wide association studies, candidate gene studies and microarray experiments of differential gene expression in lupus samples compared to controls. This study analyses a combination of existing microarray data sets to identify differentially regulated genetic pathways that are dysregulated in human peripheral blood mononuclear cells from SLE patients compared to unaffected controls. Two statistical approaches, quantile discretisation and scaling, are used to combine publicly available expression microarray datasets and perform a meta-analysis of differentially expressed genes. Differentially expressed genes implicated in interferon signaling were identified by the meta-analysis, in agreement with the findings of the individual studies that generated the datasets used. In contrast to the individual studies, however, the meta-analysis and subsequent pathway analysis additionally highlighted TLR signaling, oxidative phosphorylation and diapedesis and adhesion regulatory networks as being differentially regulated in peripheral blood mononuclear cells (PBMCs) from SLE patients compared to controls. Our analysis demonstrates that it is possible to derive additional information from publicly available expression data using meta-analysis techniques, which is particularly relevant to research into rare diseases where sample numbers can be limiting.
Nakao, Kenjiro; Oikawa, Masahiro; Arai, Junichi; Mussazhanova, Zhanna; Kondo, Hisayoshi; Shichijo, Kazuko; Nakashima, Masahiro; Hayashi, Tomayoshi; Yoshiura, Koh-Ichiro; Hatachi, Toshiko; Nagayasu, Takeshi
Utilizing formalin-fixed paraffin-embedded (FFPE) archival tissue, the most common form of tissue preservation in routine practice, for cytogenetic analysis using microarray comparative genomic hybridization (aCGH) remains challenging. We searched for a predictive factor of the performance of FFPE DNA in aCGH analysis. DNA was extracted from 63 FFPE archival tissue samples of various tissue types (31 breast cancers, 24 lung cancers, and 8 thyroid tumors), followed by aCGH analysis using high-density oligonucleotide microarrays. Tumor DNA from matched frozen samples and from FFPE samples after whole-genome amplification were also analyzed in 2 and 4 case, respectively. The derivative log ratio spread (DLRSpread) was used to assess the overall quality of each aCGH result. The DLRSpread correlated significantly with the double-stranded DNA ratio of tumor DNA, storage time, and the degree of labeling with Cy5 (Parchival tissue samples can be utilized for aCGH analysis.
Luo, Hailang; Shen, Li; Yin, Huaqun; Li, Qian; Chen, Qijiong; Luo, Yanjie; Liao, Liqin; Qiu, Guanzhou; Liu, Xueduan
Acidithiobacillus ferrooxidans is an important microorganism used in biomining operations for metal recovery. Whole-genomic diversity analysis based on the oligonucleotide microarray was used to analyze the gene content of 12 strains of A. ferrooxidans purified from various mining areas in China. Among the 3100 open reading frames (ORFs) on the slides, 1235 ORFs were absent in at least 1 strain of bacteria and 1385 ORFs were conserved in all strains. The hybridization results showed that these strains were highly diverse from a genomic perspective. The hybridization results of 4 major functional gene categories, namely electron transport, carbon metabolism, extracellular polysaccharides, and detoxification, were analyzed. Based on the hybridization signals obtained, a phylogenetic tree was built to analyze the evolution of the 12 tested strains, which indicated that the geographic distribution was the main factor influencing the strain diversity of these strains. Based on the hybridization signals of genes associated with bioleaching, another phylogenetic tree showed an evolutionary relationship from which the co-relation between the clustering of specific genes and geochemistry could be observed. The results revealed that the main factor was geochemistry, among which the following 6 factors were the most important: pH, Mg, Cu, S, Fe, and Al.
Full Text Available Abstract Background Rhipicephalus (Boophilus microplus is an obligate blood feeder which is host specific to cattle. Existing knowledge pertaining to the host or host breed effects on tick transcript expression profiles during the tick - host interaction is poor. Results Global analysis of gene expression changes in whole R. microplus ticks during larval, pre-attachment and early adult stages feeding on Bos indicus and Bos taurus cattle were compared using gene expression microarray analysis. Among the 13,601 R. microplus transcripts from BmiGI Version 2 we identified 297 high and 17 low expressed transcripts that were significantly differentially expressed between R. microplus feeding on tick resistant cattle [Bos indicus (Brahman] compared to R. microplus feeding on tick susceptible cattle [Bos taurus (Holstein-Friesian] (p ≤ 0.001. These include genes encoding enzymes involved in primary metabolism, and genes related to stress, defence, cell wall modification, cellular signaling, receptor, and cuticle formation. Microarrays were validated by qRT-PCR analysis of selected transcripts using three housekeeping genes as normalization controls. Conclusion The analysis of all tick stages under survey suggested a coordinated regulation of defence proteins, proteases and protease inhibitors to achieve successful attachment and survival of R. microplus on different host breeds, particularly Bos indicus cattle. R. microplus ticks demonstrate different transcript expression patterns when they encounter tick resistant and susceptible breeds of cattle. In this study we provide the first transcriptome evidence demonstrating the influence of tick resistant and susceptible cattle breeds on transcript expression patterns and the molecular physiology of ticks during host attachment and feeding. The microarray data used in this analysis have been submitted to NCBI GEO database under accession number GSE20605 http://www.ncbi
Toyota, Kenji; Williams, Timothy D; Sato, Tomomi; Tatarazako, Norihisa; Iguchi, Taisen
The freshwater zooplankton Daphnia magna has been extensively employed in chemical toxicity tests such as OECD Test Guidelines 202 and 211. Previously, it has been demonstrated that the treatment of juvenile hormones (JHs) or their analogues to female daphnids can induce male offspring production. Based on this finding, a rapid screening method for detection of chemicals with JH-activity was recently developed using adult D. magna. This screening system determines whether a chemical has JH-activity by investigating the male offspring inducibility. Although this is an efficient high-throughput short-term screening system, much remains to be discovered about JH-responsive pathways in the ovary, and whether different JH-activators act via the same mechanism. JH-responsive genes in the ovary including developing oocytes are still largely undescribed. Here, we conducted comparative microarray analyses using ovaries from Daphnia magna treated with fenoxycarb (Fx; artificial JH agonist) or methyl farnesoate (MF; a putative innate JH in daphnids) to elucidate responses to JH agonists in the ovary, including developing oocytes, at a JH-sensitive period for male sex determination. We demonstrate that induction of hemoglobin genes is a well-conserved response to JH even in the ovary, and a potential adverse effect of JH agonist is suppression of vitellogenin gene expression, that might cause reduction of offspring number. This is the first report demonstrating different transcriptomics profiles from MF and an artificial JH agonist in D. magna ovary, improving understanding the tissue-specific mode-of-action of JH. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Klein, David C; Bailey, Michael J; Carter, David A
Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-h schedule. This effort has highlighted surprising similarity...... foundation that microarray analysis has provided will broadly support future research on pineal function....
Koning, de D.J.; Jaffrezic, F.; Lund, M.S.; Watson, M.; Channing, C.; Hulsegge, B.; Pool, M.H.; Buitenhuis, B.; Hedegaard, J.; Hornshoj, H.; Sorensen, P.; Marot, G.; Delmas, C.; Lê Cao, K.A.; San Cristobal, M.; Baron, M.D.; Malinverni, R.; Stella, A.; Brunner, R.M.; Seyfert, H.M.; Jensen, K.; Mouzaki, D.; Waddington, D.; Jiménez-Marín, A.; Perez-Alegre, M.; Perez-Reinado, E.; Closset, R.; Detilleux, J.C.; Dovc, P.; Lavric, M.; Nie, H.; Janss, L.
Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10
Full Text Available Abstract Background Microarray analysis has become a widely used technique for the study of gene-expression patterns on a genomic scale. As more and more laboratories are adopting microarray technology, there is a need for powerful and easy to use microarray databases facilitating array fabrication, labeling, hybridization, and data analysis. The wealth of data generated by this high throughput approach renders adequate database and analysis tools crucial for the pursuit of insights into the transcriptomic behavior of cells. Results MARS (Microarray Analysis and Retrieval System provides a comprehensive MIAME supportive suite for storing, retrieving, and analyzing multi color microarray data. The system comprises a laboratory information management system (LIMS, a quality control management, as well as a sophisticated user management system. MARS is fully integrated into an analytical pipeline of microarray image analysis, normalization, gene expression clustering, and mapping of gene expression data onto biological pathways. The incorporation of ontologies and the use of MAGE-ML enables an export of studies stored in MARS to public repositories and other databases accepting these documents. Conclusion We have developed an integrated system tailored to serve the specific needs of microarray based research projects using a unique fusion of Web based and standalone applications connected to the latest J2EE application server technology. The presented system is freely available for academic and non-profit institutions. More information can be found at http://genome.tugraz.at.
de Koning, Dirk-Jan; Jaffrézic, Florence; Lund, Mogens Sandø
Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from...... 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays...... statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful...
Logotheti, Marianthi; Papadodima, Olga; Venizelos, Nikolaos; Chatziioannou, Aristotelis; Kolisis, Fragiskos
Schizophrenia affecting almost 1% and bipolar disorder affecting almost 3%-5% of the global population constitute two severe mental disorders. The catecholaminergic and the serotonergic pathways have been proved to play an important role in the development of schizophrenia, bipolar disorder, and other related psychiatric disorders. The aim of the study was to perform and interpret the results of a comparative genomic profiling study in schizophrenic patients as well as in healthy controls and in patients with bipolar disorder and try to relate and integrate our results with an aberrant amino acid transport through cell membranes. In particular we have focused on genes and mechanisms involved in amino acid transport through cell membranes from whole genome expression profiling data. We performed bioinformatic analysis on raw data derived from four different published studies. In two studies postmortem samples from prefrontal cortices, derived from patients with bipolar disorder, schizophrenia, and control subjects, have been used. In another study we used samples from postmortem orbitofrontal cortex of bipolar subjects while the final study was performed based on raw data from a gene expression profiling dataset in the postmortem superior temporal cortex of schizophrenics. The data were downloaded from NCBI's GEO datasets.
Full Text Available Schizophrenia affecting almost 1% and bipolar disorder affecting almost 3%–5% of the global population constitute two severe mental disorders. The catecholaminergic and the serotonergic pathways have been proved to play an important role in the development of schizophrenia, bipolar disorder, and other related psychiatric disorders. The aim of the study was to perform and interpret the results of a comparative genomic profiling study in schizophrenic patients as well as in healthy controls and in patients with bipolar disorder and try to relate and integrate our results with an aberrant amino acid transport through cell membranes. In particular we have focused on genes and mechanisms involved in amino acid transport through cell membranes from whole genome expression profiling data. We performed bioinformatic analysis on raw data derived from four different published studies. In two studies postmortem samples from prefrontal cortices, derived from patients with bipolar disorder, schizophrenia, and control subjects, have been used. In another study we used samples from postmortem orbitofrontal cortex of bipolar subjects while the final study was performed based on raw data from a gene expression profiling dataset in the postmortem superior temporal cortex of schizophrenics. The data were downloaded from NCBI's GEO datasets.
Comparative microarray analysis of Arabidopsis thaliana and Arabidopsis halleri roots identifies nicotianamine synthase, a ZIP transporter and other genes as potential metal hyperaccumulation factors.
Weber, Michael; Harada, Emiko; Vess, Christoph; Roepenack-Lahaye, Edda v; Clemens, Stephan
The hyperaccumulation of zinc (Zn) and cadmium (Cd) is a constitutive property of the metallophyte Arabidopsis halleri. We therefore used Arabidopsis GeneChips to identify genes more active in roots of A. halleri as compared to A. thaliana under control conditions. The two genes showing highest expression in A. halleri roots relative to A. thaliana roots out of more than 8000 genes present on the chip encode a nicotianamine (NA) synthase and a putative Zn2+ uptake system. The significantly higher activity of these and other genes involved in metal homeostasis under various growth conditions was confirmed by Northern and RT-PCR analyses. A. halleri roots also show higher NA synthase protein levels. Furthermore, we developed a capillary liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (CapLC-ESI-QTOF-MS)-based NA analysis procedure and consistently found higher NA levels in roots of A. halleri. Expression of a NA synthase in Zn2+-hypersensitive Schizosaccharomyces pombe cells demonstrated that formation of NA can confer Zn2+ tolerance. Taken together, these observations implicate NA in plant Zn homeostasis and NA synthase in the hyperaccumulation of Zn by A. halleri. Furthermore, the results show that comparative microarray analysis of closely related species can be a valuable tool for the elucidation of phenotypic differences between such species.
Claesson, M.J.; O'Sullivan, O.; Wang, Q.; Nikkilä, J.; Marchesi, J.R.; Smidt, H.; Vos, de W.M.; Ross, R.P.; O'Toole, P.W.
BACKGROUND: Variations in the composition of the human intestinal microbiota are linked to diverse health conditions. High-throughput molecular technologies have recently elucidated microbial community structure at much higher resolution than was previously possible. Here we compare two such methods
Matthew A Care
Full Text Available Cell of origin classification of diffuse large B-cell lymphoma (DLBCL identifies subsets with biological and clinical significance. Despite the established nature of the classification existing studies display variability in classifier implementation, and a comparative analysis across multiple data sets is lacking. Here we describe the validation of a cell of origin classifier for DLBCL, based on balanced voting between 4 machine-learning tools: the DLBCL automatic classifier (DAC. This shows superior survival separation for assigned Activated B-cell (ABC and Germinal Center B-cell (GCB DLBCL classes relative to a range of other classifiers. DAC is effective on data derived from multiple microarray platforms and formalin fixed paraffin embedded samples and is parsimonious, using 20 classifier genes. We use DAC to perform a comparative analysis of gene expression in 10 data sets (2030 cases. We generate ranked meta-profiles of genes showing consistent class-association using ≥6 data sets as a cut-off: ABC (414 genes and GCB (415 genes. The transcription factor ZBTB32 emerges as the most consistent and differentially expressed gene in ABC-DLBCL while other transcription factors such as ARID3A, BATF, and TCF4 are also amongst the 24 genes associated with this class in all datasets. Analysis of enrichment of 12323 gene signatures against meta-profiles and all data sets individually confirms consistent associations with signatures of molecular pathways, chromosomal cytobands, and transcription factor binding sites. We provide DAC as an open access Windows application, and the accompanying meta-analyses as a resource.
Thomas, R; Duke, S E; Karlsson, E K; Evans, A; Ellis, P; Lindblad-Toh, K; Langford, C F; Breen, M
Molecular cytogenetic studies have been instrumental in defining the nature of numerical and structural chromosome changes in human cancers, but their significance remains to be fully understood. The emergence of high quality genome assemblies for several model organisms provides exciting opportunities to develop novel genome-integrated molecular cytogenetic resources that now permit a comparative approach to evaluating the relevance of tumor-associated chromosome aberrations, both within and between species. We have used the dog genome sequence assembly to identify a framework panel of 2,097 bacterial artificial chromosome (BAC) clones, selected at intervals of approximately one megabase. Each clone has been evaluated by multicolor fluorescence in situ hybridization (FISH) to confirm its unique cytogenetic location in concordance with its reported position in the genome assembly, providing new information on the organization of the dog genome. This panel of BAC clones also represents a powerful cytogenetic resource with numerous potential applications. We have used the clone set to develop a genome-wide microarray for comparative genomic hybridization (aCGH) analysis, and demonstrate its application in detection of tumor-associated DNA copy number aberrations (CNAs) including single copy deletions and amplifications, regional aneuploidy and whole chromosome aneuploidy. We also show how individual clones selected from the BAC panel can be used as FISH probes in direct evaluation of tumor karyotypes, to verify and explore CNAs detected using aCGH analysis. This cytogenetically validated, genome integrated BAC clone panel has enormous potential for aiding gene discovery through a comparative approach to molecular oncology.
Cecilia W S Chan
Full Text Available Retinal neovascularization is a critical component in the pathogenesis of common ocular disorders that cause blindness, and treatment options are limited. We evaluated the therapeutic effect of a DNA enzyme targeting c-jun mRNA in mice with pre-existing retinal neovascularization. A single injection of Dz13 in a lipid formulation containing N-[1-(2,3-dioleoyloxypropyl]-N,N,N-trimethylammonium methyl-sulfate and 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine inhibited c-Jun expression and reduced retinal microvascular density. The DNAzyme inhibited retinal microvascular density as effectively as VEGF-A antibodies. Comparative microarray and gene expression analysis determined that Dz13 suppressed not only c-jun but a range of growth factors and matrix-degrading enzymes. Dz13 in this formulation inhibited microvascular endothelial cell proliferation, migration and tubule formation in vitro. Moreover, animals treated with Dz13 sensed the top of the cage in a modified forepaw reach model, unlike mice given a DNAzyme with scrambled RNA-binding arms that did not affect c-Jun expression. These findings demonstrate reduction of microvascular density and improvement in forepaw reach in mice administered catalytic DNA.
Full Text Available Abstract Background Image analysis of microarrays and, in particular, spot quantification and spot quality control, is one of the most important steps in statistical analysis of microarray data. Recent methods of spot quality control are still in early age of development, often leading to underestimation of true positive microarray features and, consequently, to loss of important biological information. Therefore, improving and standardizing the statistical approaches of spot quality control are essential to facilitate the overall analysis of microarray data and subsequent extraction of biological information. Findings We evaluated the performance of two image analysis packages MAIA and GenePix (GP using two complementary experimental approaches with a focus on the statistical analysis of spot quality factors. First, we developed control microarrays with a priori known fluorescence ratios to verify the accuracy and precision of the ratio estimation of signal intensities. Next, we developed advanced semi-automatic protocols of spot quality evaluation in MAIA and GP and compared their performance with available facilities of spot quantitative filtering in GP. We evaluated these algorithms for standardised spot quality analysis in a whole-genome microarray experiment assessing well-characterised transcriptional modifications induced by the transcription regulator SNAI1. Using a set of RT-PCR or qRT-PCR validated microarray data, we found that the semi-automatic protocol of spot quality control we developed with MAIA allowed recovering approximately 13% more spots and 38% more differentially expressed genes (at FDR = 5% than GP with default spot filtering conditions. Conclusion Careful control of spot quality characteristics with advanced spot quality evaluation can significantly increase the amount of confident and accurate data resulting in more meaningful biological conclusions.
Klein, David C.; Bailey, Michael J.; Carter, David A.; Kim, Jong-so; Shi, Qiong; Ho, Anthony K.; Chik, Constance L.; Gaildrat, Pascaline; Morin, Fabrice; Ganguly, Surajit; Rath, Martin F.; Moller, Morten; Sugden, David; Rangel, Zoila G.; Munson, Peter J.; Weller, Joan L.; Coon, Steven L.
Microarray analysis has provided a new understanding of pineal function by identifying genes that are highly expressed in this tissue relative to other tissues and also by identifying over 600 genes that are expressed on a 24-h schedule. This effort has highlighted surprising similarity to the retin
Full Text Available Abstract Background Microarray technologies are widely used to quantify the abundance of transcripts corresponding to thousands of genes. To maximise the robustness of transcriptome results, we have tested the performance and reproducibility of rat and mouse gene expression data obtained with Affymetrix, Illumina and Operon platforms. Results We present a thorough analysis of the degree of reproducibility provided by analysing the transcriptomic profile of the same animals of several experimental groups under different popular microarray technologies in different tissues. Concordant results from inter- and intra-platform comparisons were maximised by testing many popular computational methods for generating fold changes and significances and by only considering oligonucleotides giving high expression levels. The choice of Affymetrix signal extraction technique was shown to have the greatest effect on the concordance across platforms. In both species, when choosing optimal methods, the agreement between data generated on the Affymetrix and Illumina was excellent; this was verified using qRT-PCR on a selection of genes present on all platforms. Conclusion This study provides an extensive assessment of analytical methods best suited for processing data from different microarray technologies and can assist integration of technologically different gene expression datasets in biological systems.
of each method’s ability to analyze DNA copy number data. Moreover, our study shows that analysis methods developed for cancer research may also successfully be applied to DNA copy number profiles from bacterial genomes. However, here the purpose is to characterize variations in the gene content...... to verify predictions of highly expressed genes. Moreover, the codon bias of microbial genomes was found to constitute an environmental signature. For example, soil bacteria have very similar codon bias....
Wang, Min; Senger, Ryan S; Paredes, Carlos; Banik, Gautam G; Lin, Andy; Papoutsakis, Eleftherios T
Whole-cell immunotherapies and other cellular therapies have shown promising results in clinical trials. Due to the complex nature of the whole cell product and of the sometimes limited correlation of clinical potency with the proposed mechanism of action, these cellular immunotherapy products are generally not considered well characterized. Therefore, one major challenge in the product development of whole cell therapies is the ability to demonstrate comparability of product after changes in the manufacturing process. Such changes are nearly inevitable with increase in manufacturing experience leading to improved and robust processes that may have higher commercial feasibility. In order to comprehensively assess the impact of the process changes on the final product, and thus establish comparability, a matrix of characterization assays (in addition to lot release assays) assessing the various aspects of the cellular product are required. In this study, we assessed the capability of DNA-microarray-based, gene-expression analysis as a characterization tool using GVAX cancer immunotherapy cells manufactured by Cell Genesys, Inc. The GVAX immunotherapy product consists two prostate cancer cell lines (CG1940 and CG8711) engineered to secrete human GM-CSF. To demonstrate the capability of the assay, we assessed the transcriptional changes in the product when produced in the presence or absence of fetal bovine serum, and under normal and hypoxic conditions, both changes intended to stress the cell lines. We then assessed the impact of an approximately 10-fold process scale-up on the final product at the transcriptional level. These data were used to develop comparisons and statistical analyses suitable for characterizing culture reproducibility and cellular product similarity. Use of gene-expression data for process characterization proved to be a reproducible and sensitive method for detecting differences due to small or large changes in culture conditions as might be
FANG Zhuo; LUO Qingming; ZHANG Guoqing; LI Yixue
Microarray technology, which permits rapid and large-scale screening for patterns of gene expressions, usually generates a large amount of data. How to mine the biological meanings under these data is one of the main challenges in bioinformatics. Compared to the pure mathematical techniques, those methods incorporated with some prior biological knowledge generally bring better interpretations.Recently, a new analysis, in which the knowledge of biological networks such as metabolic network and protein interaction network is introduced, is widely applied to microarray data analysis. The microarray data analysis based on biological networks contains two main research aspects: identification of active components in biological networks and assessment of gene sets significance. In this paper, we briefly review the progress of these two categories of analyses, especially some representative methods.
Eichler, Gabriel S
The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational interpretation techniques. It is for this reason that bioinformatic analysis of complex molecular profiling data has become a fundamental technology in the development of personalized medicine. This chapter provides a high-level overview of the field of bioinformatics and outlines several, classic bioinformatic approaches. The highlighted approaches can be aptly applied to nearly any sort of high-dimensional genomic, proteomic, or metabolomic experiments. Reviewed technologies in this chapter include traditional clustering analysis, the Gene Expression Dynamics Inspector (GEDI), GoMiner (GoMiner), Gene Set Enrichment Analysis (GSEA), and the Learner of Functional Enrichment (LeFE).
The prognostic implications of microvascular density and lymphatic vessel density in esophageal squamous cell carcinoma: Comparative analysis between the traditional whole sections and the tissue microarray.
Chen, Bo; Fang, Wang-Kai; Wu, Zhi-Yong; Xu, Xiu-E; Wu, Jian-Yi; Fu, Jun-Hui; Yao, Xiao-Dong; Huang, Jian-Hao; Chen, Jie-Xin; Shen, Jin-Hui; Zheng, Chun-Peng; Wang, Shao-Hong; Li, En-Min; Xu, Li-Yan
Focal distribution of microvascular and lymphatic vessels is a critical issue in cancer, and is measured by tissue microarray (TMA) construction from paraffin-embedded surgically obtained tissues, a process that may not accurately reflect true focal distribution. The aim of this study was to assess the concordance of microvascular density (MVD) and lymphatic vessel density (LVD) in TMAs with corresponding whole sections, and to correlate the MVD or LVD with clinicopathological parameters in 124 cases of esophageal squamous cell carcinoma (ESCC). MVD, determined by CD105 immunohistochemistry of whole sections, was strongly associated with lymph node metastasis (p=0.000) and pTNM stage (p=0.001). Kaplan-Meier survival analysis showed that increasing CD105 microvessel count correlated with decreasing survival (ptissue microarrays. Analysis of continuous data showed a highly significant correlation between whole sections and TMA data (Pearson r=0.522, p<0.001). Increasing LVD, as determined by D2-40 immunohistochemistry of whole sections, correlated with decreasing survival, but this relationship was undetectable using TMAs. In conclusion, we demonstrate that for the selected endothelial markers, TMAs can provide a realistic and reliable estimate of the extent of MVD, but not LVD in ESCC samples. Copyright © 2013 Elsevier GmbH. All rights reserved.
Singh, R P; Shafeeque, C M; Sharma, S K; Singh, R; Mohan, J; Sastry, K V H; Saxena, V K; Azeez, P A
It has been confirmed that mammalian sperm contain thousands of functional RNAs, and some of them have vital roles in fertilization and early embryonic development. Therefore, we attempted to characterize transcriptome of the sperm of fertile chickens using microarray analysis. Spermatozoal RNA was pooled from 10 fertile males and used for RNA preparation. Prior to performing the microarray, RNA quality was assessed using a bioanalyzer, and gDNA and somatic cell RNA contamination was assessed by CD4 and PTPRC gene amplification. The chicken sperm transcriptome was cross-examined by analysing sperm and testes RNA on a 4 × 44K chicken array, and results were verified by RT-PCR. Microarray analysis identified 21,639 predominantly nuclear-encoded transcripts in chicken sperm. The majority (66.55%) of the sperm transcripts were shared with the testes, while surprisingly, 33.45% transcripts were detected (raw signal intensity greater than 50) only in the sperm and not in the testes. The greatest proportion of up-regulated transcripts were responsible for signal transduction (63.20%) followed by embryonic development (56.76%) and cell structure (56.25%). Of the 20 most abundant transcripts, 18 remain uncharacterized, whereas the least abundant genes were mostly associated with the ribosome. These findings lay a foundation for more detailed investigations on sperm RNAs in chickens to identify sperm-based biomarkers for fertility.
Identification of an IMPDH1 mutation in autosomal dominant retinitis pigmentosa (RP10) revealed following comparative microarray analysis of transcripts derived from retinas of wild-type and Rho(-/-) mice
Kennan, Avril; Aherne, Aileen; Palfi, Arpad
Comparative analysis of the transcriptional profiles of approximately 6000 genes in the retinas of wild-type mice with those carrying a targeted disruption of the rhodopsin gene was undertaken by microarray analysis. This revealed a series of transcripts, of which some were derived from genes known...... is not present in healthy, unrelated individuals of European origin. These data provide strong evidence that mutations within the IMPDH1 gene cause adRP, and validate approaches to mutation detection involving comparative analysis of global transcription profiles in normal and degenerating retinal tissues. Other...
Full Text Available Abstract Background Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. Findings We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Conclusion Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.
Full Text Available Abstract Background In DNA microarray experiments, measurements from different biological samples are often assumed to be independent and to have identical variance. For many datasets these assumptions have been shown to be invalid and typically lead to too optimistic p-values. A method called WAME has been proposed where a variance is estimated for each sample and a covariance is estimated for each pair of samples. The current version of WAME is, however, limited to experiments with paired design, e.g. two-channel microarrays. Results The WAME procedure is extended to general microarray experiments, making it capable of handling both one- and two-channel datasets. Two public one-channel datasets are analysed and WAME detects both unequal variances and correlations. WAME is compared to other common methods: fold-change ranking, ordinary linear model with t-tests, LIMMA and weighted LIMMA. The p-value distributions are shown to differ greatly between the examined methods. In a resampling-based simulation study, the p-values generated by WAME are found to be substantially more correct than the alternatives when a relatively small proportion of the genes is regulated. WAME is also shown to have higher power than the other methods. WAME is available as an R-package. Conclusion The WAME procedure is generalized and the limitation to paired-design microarray datasets is removed. The examined other methods produce invalid p-values in many cases, while WAME is shown to produce essentially valid p-values when a relatively small proportion of genes is regulated. WAME is also shown to have higher power than the examined alternative methods.
Jaenisch, Holger; Handley, James; Williams, Deborah
We implement a Spatial Voting (SV) based analogy of microarray analysis for digital gene marker identification in malware code sections. We examine a famous set of malware formally analyzed by Mandiant and code named Advanced Persistent Threat (APT1). APT1 is a Chinese organization formed with specific intent to infiltrate and exploit US resources. Manidant provided a detailed behavior and sting analysis report for the 288 malware samples available. We performed an independent analysis using a new alternative to the traditional dynamic analysis and static analysis we call Spatial Analysis (SA). We perform unsupervised SA on the APT1 originating malware code sections and report our findings. We also show the results of SA performed on some members of the families associated by Manidant. We conclude that SV based SA is a practical fast alternative to dynamics analysis and static analysis.
Full Text Available BACKGROUND: Phototrophy of the extremely halophilic archaeon Halobacterium salinarum was explored for decades. The research was mainly focused on the expression of bacteriorhodopsin and its functional properties. In contrast, less is known about genome wide transcriptional changes and their impact on the physiological adaptation to phototrophy. The tool of choice to record transcriptional profiles is the DNA microarray technique. However, the technique is still rarely used for transcriptome analysis in archaea. METHODOLOGY/PRINCIPAL FINDINGS: We developed a whole-genome DNA microarray based on our sequence data of the Hbt. salinarum strain R1 genome. The potential of our tool is exemplified by the comparison of cells growing under aerobic and phototrophic conditions, respectively. We processed the raw fluorescence data by several stringent filtering steps and a subsequent MAANOVA analysis. The study revealed a lot of transcriptional differences between the two cell states. We found that the transcriptional changes were relatively weak, though significant. Finally, the DNA microarray data were independently verified by a real-time PCR analysis. CONCLUSION/SIGNIFICANCE: This is the first DNA microarray analysis of Hbt. salinarum cells that were actually grown under phototrophic conditions. By comparing the transcriptomics data with current knowledge we could show that our DNA microarray tool is well applicable for transcriptome analysis in the extremely halophilic archaeon Hbt. salinarum. The reliability of our tool is based on both the high-quality array of DNA probes and the stringent data handling including MAANOVA analysis. Among the regulated genes more than 50% had unknown functions. This underlines the fact that haloarchaeal phototrophy is still far away from being completely understood. Hence, the data recorded in this study will be subject to future systems biology analysis.
von der Haar, Marcel; Heuer, Christopher; Pähler, Martin; von der Haar, Kathrin; Lindner, Patrick; Scheper, Thomas; Stahl, Frank
The application of DNA microarrays for high throughput analysis of genetic regulation is often limited by the fluorophores used as markers. The implementation of multi-scan techniques is limited by the fluorophores' susceptibility to photobleaching when exposed to the scanner laser light. This paper presents combined mechanical and chemical strategies which enhance the photostability of cyanine 3 and cyanine 5 as part of solid state DNA microarrays. These strategies are based on scanning the microarrays while the hybridized DNA is still in an aqueous solution with the presence of a reductive/oxidative system (ROXS). Furthermore, the experimental setup allows for the analysis and eventual normalization of Förster-resonance-energy-transfer (FRET) interaction of cyanine-3/cyanine-5 dye combinations on the microarray. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the comparability of microarray experiment results between labs.
Marcel von der Haar
Full Text Available The application of DNA microarrays for high throughput analysis of genetic regulation is often limited by the fluorophores used as markers. The implementation of multi-scan techniques is limited by the fluorophores’ susceptibility to photobleaching when exposed to the scanner laser light. This paper presents combined mechanical and chemical strategies which enhance the photostability of cyanine 3 and cyanine 5 as part of solid state DNA microarrays. These strategies are based on scanning the microarrays while the hybridized DNA is still in an aqueous solution with the presence of a reductive/oxidative system (ROXS. Furthermore, the experimental setup allows for the analysis and eventual normalization of Förster-resonance-energy-transfer (FRET interaction of cyanine-3/cyanine-5 dye combinations on the microarray. These findings constitute a step towards standardization of microarray experiments and analysis and may help to increase the comparability of microarray experiment results between labs.
Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and
Full Text Available Microarray study enables us to obtain hundreds of thousands of expressions of genes or genotypes at once, and it is an indispensable technology for genome research. The first step is the analysis of scanned microarray images. This is the most important procedure for obtaining biologically reliable data. Currently most microarray image processing systems require burdensome manual block/spot indexing work. Since the amount of experimental data is increasing very quickly, automated microarray image analysis software becomes important. In this paper, we propose two automated methods for analyzing microarray images. First, we propose the extended -regular sequence to index blocks and spots, which enables a novel automatic gridding procedure. Second, we provide a methodology, hierarchical metagrid alignment, to allow reliable and efficient batch processing for a set of microarray images. Experimental results show that the proposed methods are more reliable and convenient than the commercial tools.
Li, J J; Wang, B. Q.; Fei, Q.; Yang, Y; Li, D.
Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed...
Nylund, L.; Satokari, R.; Nikkilä, J.; Rajilic-Stojanovic, M.; Kalliomäki, M.; Isolauri, E.; Salminen, S.; Vos, de W.M.
BACKGROUND: Deviations in composition and diversity of intestinal microbiota in infancy have been associated with both the development and recurrence of atopic eczema. Thus, we decided to use a deep and global microarray-based method to characterize the diversity and temporal changes of the intestin
HER2/neu Expression and Gene Alterations in Pancreatic Ductal Adenocarcinoma: A Comparative mmunohistochemistry and Chromogenic in Situ Hybridization Study Based on Tissue Microarrays and Computerized Image Analysis
Full Text Available Context: HER2/neu overexpression is observed in many cancers including pancreatic ductal adenocarcinoma. Although immunohistochemistry remains the basic method for evaluating HER2/neu protein expression, significant information regarding gene status cannot be assessed. Design: Using tissue microarray technology, fifty histologically confirmed pancreatic ductal adenocarcinomas were cored twice and re-embedded in one paraffin block. Immunohistochemistry (clone TAB 250 and chromogenic (HER2/neu amplification Spot Light kit in situ hybridization protocols were performed. The immunostained slides were evaluated by conventional eye microscopy and digital image analysis. The chi square test and the kappa statistic were applied by running the SPSS package. Main outcome measures :The levels of staining intensity were estimated by the performance of a semi automated image analysis system. Results :HER2/neu gene amplification was detected in 8/50 cases (16%. Chromosome 17 aneuploidy was detected in 19 cases (38%. Significant improvement in interobserver agreement (kappa=0.76 vs. 0.94 was achieved correlating the immunohistochemical results obtained by conventional eye and digital microscopy, especially in the cases of overexpression (2+, 3+. Finally, 29 (58%, 11 (22%, 6 (12% and 4 (8% cases were characterized as 0, 1+, 2+ and 3+, respectively. HER2/neu protein expression was significantly associated with grade (P=0.019, but not with stage (P=0.466. in addition, chromosome 17 and gene status were not correlated with stage and grade.. Conclusion :Our results indicate that a subset of pancreatic ductal adenocarcinomas is characterized by HER2/neu gene amplification. In contrast to breast cancer, protein overexpression does not predict this specific gene deregulation mechanism. This event may reflect the different biological role of the molecule in those two solid tumours, affecting the response to novel targeted agents, such as monoclonal anti-HER2/neu
Giuseppe, Agapito; Milano, Marianna
The importance of semantic-based methods and algorithms for the analysis and management of biological data is growing for two main reasons. From a biological side, knowledge contained in ontologies is more and more accurate and complete, from a computational side, recent algorithms are using in a valuable way such knowledge. Here we focus on semantic-based management and analysis of protein interaction networks referring to all the approaches of analysis of protein-protein interaction data that uses knowledge encoded into biological ontologies. Semantic approaches for studying high-throughput data have been largely used in the past to mine genomic and expression data. Recently, the emergence of network approaches for investigating molecular machineries has stimulated in a parallel way the introduction of semantic-based techniques for analysis and management of network data. The application of these computational approaches to the study of microarray data can broad the application scenario of them and simultaneously can help the understanding of disease development and progress.
Full Text Available This paper presents microarray BASICA: an integrated image processing tool for background adjustment, segmentation, image compression, and analysis of cDNA microarray images. BASICA uses a fast Mann-Whitney test-based algorithm to segment cDNA microarray images, and performs postprocessing to eliminate the segmentation irregularities. The segmentation results, along with the foreground and background intensities obtained with the background adjustment, are then used for independent compression of the foreground and background. We introduce a new distortion measurement for cDNA microarray image compression and devise a coding scheme by modifying the embedded block coding with optimized truncation (EBCOT algorithm (Taubman, 2000 to achieve optimal rate-distortion performance in lossy coding while still maintaining outstanding lossless compression performance. Experimental results show that the bit rate required to ensure sufficiently accurate gene expression measurement varies and depends on the quality of cDNA microarray images. For homogeneously hybridized cDNA microarray images, BASICA is able to provide from a bit rate as low as 5 bpp the gene expression data that are 99% in agreement with those of the original 32 bpp images.
Ramachandran, Anassuya; Black, Michael A; Shelling, Andrew N; Love, Donald R
Microarrays provide a powerful means of analyzing the expression level of multiple transcripts in two sample populations. In this study, we have used microarray technology to identify genes that are differentially regulated in response to activin-treated ovarian cancer cells. We find a number of biologically relevant genes that are involved in regulating activin signaling and genes potentially contributing to activin-mediated growth arrest appear to be differentially regulated. Thus, microarrays are an important tool for dissecting gene expression changes in normal physiological processes and disease.
Full Text Available Zebrafish (Danio rerio is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html.
Full Text Available Zebrafish (Danio rerio is a well-recognized model for the study of vertebrate developmental genetics, yet at the same time little is known about the transcriptional events that underlie zebrafish embryogenesis. Here we have employed microarray analysis to study the temporal activity of developmentally regulated genes during zebrafish embryogenesis. Transcriptome analysis at 12 different embryonic time points covering five different developmental stages (maternal, blastula, gastrula, segmentation, and pharyngula revealed a highly dynamic transcriptional profile. Hierarchical clustering, stage-specific clustering, and algorithms to detect onset and peak of gene expression revealed clearly demarcated transcript clusters with maximum gene activity at distinct developmental stages as well as co-regulated expression of gene groups involved in dedicated functions such as organogenesis. Our study also revealed a previously unidentified cohort of genes that are transcribed prior to the mid-blastula transition, a time point earlier than when the zygotic genome was traditionally thought to become active. Here we provide, for the first time to our knowledge, a comprehensive list of developmentally regulated zebrafish genes and their expression profiles during embryogenesis, including novel information on the temporal expression of several thousand previously uncharacterized genes. The expression data generated from this study are accessible to all interested scientists from our institute resource database (http://giscompute.gis.a-star.edu.sg/~govind/zebrafish/data_download.html.
Full Text Available Conventional comparative genomic hybridization (CGH profiling of neuroblastomas has identified many genomic aberrations, although the limited resolution has precluded a precise localization of sequences of interest within amplicons. To map high copy number genomic gains in clinically matched stage IV neuroblastomas, CGH analysis using a 19,200-feature cDNA microarray was used. A dedicated (freely available algorithm was developed for rapid in silico determination of chromosomal localizations of microarray cDNA targets, and for generation of an ideogram-type profile of copy number changes. Using these methodologies, novel gene amplifications undetectable by chromosome CGH were identified, and larger MYCN amplicon sizes (in one tumor up to 6 Mb than those previously reported in neuroblastoma were identified. The genes HPCAL1, LPIN1/KIAA0188, NAG, and NSE1/LOC151354 were found to be coamplified with MYCN. To determine whether stage IV primary tumors could be further subclassified based on their genomic copy number profiles, hierarchical clustering was performed. Cluster analysis of microarray CGH data identified three groups: 1 no amplifications evident, 2 a small MYCN amplicon as the only detectable imbalance, and 3 a large MYCN amplicon with additional gene amplifications. Application of CGH to cDNA microarray targets will help to determine both the variation of amplicon size and help better define amplification-dependent and independent pathways of progression in neuroblastoma.
Wu, Eunice; Su, Yan A.; Billings, Eric; Brooks, Bernard R.; Wu, Xiongwu
High throughput microarray analysis has great potential in scientific research, disease diagnosis, and drug discovery. A major hurdle toward high throughput microarray analysis is the time and effort needed to accurately locate gene spots in microarray images. An automatic microarray image processor will allow accurate and efficient determination of spot locations and sizes so that gene expression information can be reliably extracted in a high throughput manner. Current microarray image processing tools require intensive manual operations in addition to the input of grid parameters to correctly and accurately identify gene spots. This work developed a method, herein called auto-spot, to automate the spot identification process. Through a series of correlation and convolution operations, as well as pixel manipulations, this method makes spot identification an automatic and accurate process. Testing with real microarray images has demonstrated that this method is capable of automatically extracting subgrids from microarray images and determining spot locations and sizes within each subgrid, regardless of variations in array patterns and background noises. With this method, we are one step closer to the goal of high throughput microarray analysis. PMID:24298393
Full Text Available Abstract Background Deviations in composition and diversity of intestinal microbiota in infancy have been associated with both the development and recurrence of atopic eczema. Thus, we decided to use a deep and global microarray-based method to characterize the diversity and temporal changes of the intestinal microbiota in infancy and to define specific bacterial signatures associated with eczema. Faecal microbiota at 6 and 18 months of age were analysed from 34 infants (15 with eczema and 19 healthy controls selected from a prospective follow-up study based on the availability of faecal samples. The infants were originally randomized to receive either Lactobacillus rhamnosus GG or placebo. Results Children with eczema harboured a more diverse total microbiota than control subjects as assessed by the Simpson’s reciprocal diversity index of the microarray profiles. Composition of the microbiota did not differ between study groups at age of 6 months, but was significantly different at age of 18 months as assessed by MCPP (p=0.01. At this age healthy children harboured 3 -fold greater amount of members of the Bacteroidetes (p=0.01. Microbiota of children suffering from eczema had increased abundance of the Clostridium clusters IV and XIVa, which are typically abundant in adults. Probiotic Lactobacillus rhamnosus GG supplementation in early infancy was observed to have minor long-term effects on the microbiota composition. Conclusion A diverse and adult-type microbiota in early childhood is associated with eczema and it may contribute to the perpetuation of eczema.
Sekhon, Rajandeep S.; Briskine, Roman; Hirsch, Candice N.; Myers, Chad L.; Springer, Nathan M.; Buell, C. Robin; de Leon, Natalia; Kaeppler, Shawn M.
Transcriptome analysis is a valuable tool for identification and characterization of genes and pathways underlying plant growth and development. We previously published a microarray-based maize gene atlas from the analysis of 60 unique spatially and temporally separated tissues from 11 maize organs . To enhance the coverage and resolution of the maize gene atlas, we have analyzed 18 selected tissues representing five organs using RNA sequencing (RNA-Seq). For a direct comparison of the two methodologies, the same RNA samples originally used for our microarray-based atlas were evaluated using RNA-Seq. Both technologies produced similar transcriptome profiles as evident from high Pearson's correlation statistics ranging from 0.70 to 0.83, and from nearly identical clustering of the tissues. RNA-Seq provided enhanced coverage of the transcriptome, with 82.1% of the filtered maize genes detected as expressed in at least one tissue by RNA-Seq compared to only 56.5% detected by microarrays. Further, from the set of 465 maize genes that have been historically well characterized by mutant analysis, 427 show significant expression in at least one tissue by RNA-Seq compared to 390 by microarray analysis. RNA-Seq provided higher resolution for identifying tissue-specific expression as well as for distinguishing the expression profiles of closely related paralogs as compared to microarray-derived profiles. Co-expression analysis derived from the microarray and RNA-Seq data revealed that broadly similar networks result from both platforms, and that co-expression estimates are stable even when constructed from mixed data including both RNA-Seq and microarray expression data. The RNA-Seq information provides a useful complement to the microarray-based maize gene atlas and helps to further understand the dynamics of transcription during maize development. PMID:23637782
Zupancic, Margaret L; Frieman, Matthew; Smith, David; Alvarez, Richard A; Cummings, Richard D; Cormack, Brendan P
...) family responsible for mediating adherence to host cells. To better understand the mechanism by which the Epa proteins contribute to pathogenesis, we have used glycan microarray analysis to characterize their carbohydrate...
HUANG; Yi; LI; Lihua; CHEN; Ying; LI; Xianghua; XU; Caiguo; WANG; Shiping; ZHANG; Qifa
Using a cDNA microarray consisting of 9198 expressed sequence tags, we surveyed the gene expression profiles in shoots and roots of a rice hybrid, Liangyoupei 9 and its parents Peiai 64s and 93-11 at 72 h after germination. A total of 8587 sequences had detectable signals in both shoots and roots of the three genotypes. A total of 1571 sequences exhibited significant (P＜0.01) expression differences in shoots or roots among the three genotypes, of which 121 showed expression polymorphisms in both shoots and roots, and 870 revealed significant expression differences between the hybrid and one of the parents. The expression polymorphism of the sequences was associated with the functional categories of the sequences. They occurred more frequently in categories of carbohydrate, energy and lipid metabolisms and stress response than expected, while less frequently in categories of amino acid metabolism, transcription and translation regulation, and signal transduction. A total of 214 sequences exhibited significant (P＜0.05) mid-parent heterosis in expression, of which 117 had homology to genes with known functions, assigned in the categories of basic metabolism, genetic information processing, cell growth and death, signal transduction, transportation and stress response. The results may provide useful information for exploring the relationship between gene expression polymorphism and phenotypic variation, and for characterizing the molecular mechanism of seedling development and heterosis in rice.
Full Text Available Abstract Background Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are used to discretize microarray data. Selection of the discretization method is often arbitrary and no systematic comparison of different discretization has been conducted, in the context of gene regulatory network inference from time series gene expression data. Results In this study, we propose a new discretization method "bikmeans", and compare its performance with four other widely-used discretization methods using different datasets, modeling algorithms and number of intervals. Sensitivities, specificities and total accuracies were calculated and statistical analysis was carried out. Bikmeans method always gave high total accuracies. Conclusions Our results indicate that proper discretization methods can consistently improve gene regulatory network inference independent of network modeling algorithms and datasets. Our new method, bikmeans, resulted in significant better total accuracies than other methods.
Full Text Available Abstract Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced. While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses.
Bruun, G. M.; Wernersson, Rasmus; Juncker, Agnieszka
different probes. It is therefore of great interest to correct for the variation between probes. Much of this variation is sequence dependent. We demonstrate that a thermodynamic model for hybridization of either DNA or RNA to a DNA microarray, which takes the sequence-dependent probe affinities...
Rice(Oryza sativa) feeds over half of the global population.A web-based integrated platform for rice microarray annotation and data analysis in various biological contexts is presented,which provides a convenient query for comprehensive annotation compared with similar databases.Coupled with existing rice microarray data,it provides online analysis methods from the perspective of bioinformatics.This comprehensive bioinformatics analysis platform is composed of five modules,including data retrieval,microarray annotation,sequence analysis,results visualization and data analysis.The BioChip module facilitates the retrieval of microarray data information via identifiers of "Probe Set ID","Locus ID" and "Analysis Name".The BioAnno module is used to annotate the gene or probe set based on the gene function,the domain information,the KEGG biochemical and regulatory pathways and the potential microRNA which regulates the genes.The BioSeq module lists all of the related sequence information by a microarray probe set.The BioView module provides various visual results for the microarray data.The BioAnaly module is used to analyze the rice microarray’s data set.
. Conclusion CGHScan is an effective tool for analyzing comparative genomic hybridization data from high-density microarrays. The algorithm is capable of accurately identifying known variable regions and is tolerant of high noise and varying methods of data preprocessing. Statistical analysis is used to define each variable region providing a robust and reliable method for rapid identification of genomic differences independent of annotated gene boundaries.
Full Text Available Abstract Background Acute lymphoblastic leukemia (ALL is the most common pediatric malignancy and has been the poster-child for improved therapeutics in cancer, with life time disease-free survival (LTDFS rates improving from 80% today. There are numerous known genetic prognostic variables in ALL, which include T cell ALL, the hyperdiploid karyotype and the translocations: t(12;21[TEL-AML1], t(4;11[MLL-AF4], t(9;22[BCR-ABL], and t(1;19[E2A-PBX]. ALL has been studied at the molecular level through expression profiling resulting in un-validated expression correlates of these prognostic indices. To date, the great wealth of expression data, which has been generated in disparate institutions, representing an extremely large cohort of samples has not been combined to validate any of these analyses. The majority of this data has been generated on the Affymetrix platform, potentially making data integration and validation on independent sample sets a possibility. Unfortunately, because the array platform has been evolving over the past several years the arrays themselves have different probe sets, making direct comparisons difficult. To test the comparability between different array platforms, we have accumulated all Affymetrix ALL array data that is available in the public domain, as well as two sets of cDNA array data. In addition, we have supplemented this data pool by profiling additional diagnostic pediatric ALL samples in our lab. Lists of genes that are differentially expressed in the six major subclasses of ALL have previously been reported in the literature as possible predictors of the subclass. Results We validated the predictability of these gene lists on all of the independent datasets accumulated from various labs and generated on various array platforms, by blindly distinguishing the prognostic genetic variables of ALL. Cross-generation array validation was used successfully with high sensitivity and high specificity of gene predictors
Yolken Robert H
Full Text Available Abstract Background Recent studies have shown similarities between schizophrenia and bipolar disorder in phenotypes and in genotypes, and those studies have contributed to an ongoing re-evaluation of the traditional dichotomy between schizophrenia and bipolar disorder. Bipolar disorder with psychotic features may be closely related to schizophrenia and therefore, psychosis may be an alternative phenotype compared to the traditional diagnosis categories. Methods We performed a cross-study analysis of 7 gene expression microarrays that include both psychosis and non-psychosis subjects. These studies include over 400 microarray samples (163 individual subjects on 3 different Affymetrix microarray platforms. Results We found that 110 transcripts are differentially regulated (p Conclusion This study demonstrates the advantages of cross-study analysis in detecting consensus changes in gene expression across multiple microarray studies. Differential gene expression between individuals with and without psychosis suggests that psychosis may be a useful phenotypic variable to complement the traditional diagnosis categories.
Semeralul, Mawahib O; Boutros, Paul C; Likhodi, Olga; Okey, Allan B; Van Tol, Hubert H M; Wong, Albert H C
Abnormal development of the prefrontal cortex (PFC) is associated with a number of neuropsychiatric disorders that have an onset in childhood or adolescence. Although the basic laminar structure of the PFC is established in utero, extensive remodeling continues into adolescence. To map the overall pattern of changes in cortical gene transcripts during postnatal development, we made serial measurements of mRNA levels in mouse PFC using oligonucleotide microarrays. We observed changes in mRNA transcripts consistent with known postnatal morphological and biochemical events. Overall, most transcripts that changed significantly showed a progressive decrease in abundance after birth, with the majority of change between postnatal weeks 2 and 4. Genes with cell proliferative, cytoskeletal, extracellular matrix, plasma membrane lipid/transport, protein folding, and regulatory functions had decreases in mRNA levels. Quantitative PCR verified the microarray results for six selected genes: DNA methyltransferase 3A (Dnmt3a), procollagen, type III, alpha 1 (Col3a1), solute carrier family 16 (monocarboxylic acid transporters), member 1 (Slc16a1), MARCKS-like 1 (Marcksl1), nidogen 1 (Nid1) and 3-hydroxybutyrate dehydrogenase (heart, mitochondrial) (Bdh).
We propose statistical methods for comparing phenomics data generated by the Biolog Phenotype Microarray (PM) platform for high-throughput phenotyping. Instead of the routinely used visual inspection of data with no sound inferential basis, we develop two approaches. The first approach is based on quantifying the distance between mean or median curves from two treatments and then applying a permutation test; we also consider a permutation test applied to areas under mean curves. The second approach employs functional principal component analysis. Properties of the proposed methods are investigated on both simulated data and data sets from the PM platform.
Sturino, Joseph; Zorych, Ivan; Mallick, Bani; Pokusaeva, Karina; Chang, Ying-Ying; Carroll, Raymond J; Bliznuyk, Nikolay
We propose statistical methods for comparing phenomics data generated by the Biolog Phenotype Microarray (PM) platform for high-throughput phenotyping. Instead of the routinely used visual inspection of data with no sound inferential basis, we develop two approaches. The first approach is based on quantifying the distance between mean or median curves from two treatments and then applying a permutation test; we also consider a permutation test applied to areas under mean curves. The second approach employs functional principal component analysis. Properties of the proposed methods are investigated on both simulated data and data sets from the PM platform.
Sturino, Joseph; Zorych, Ivan; Mallick, Bani; Pokusaeva, Karina; Chang, Ying-Ying; Carroll, Raymond J; Bliznuyk, Nikolay
We propose statistical methods for comparing phenomics data generated by the Biolog Phenotype Microarray (PM) platform for high-throughput phenotyping. Instead of the routinely used visual inspection of data with no sound inferential basis, we develop two approaches. The first approach is based on quantifying the distance between mean or median curves from two treatments and then applying a permutation test; we also consider a permutation test applied to areas under mean curves. The second approach employs functional principal component analysis. Properties of the proposed methods are investigated on both simulated data and data sets from the PM platform. PMID:20865133
Salonen, A.; Nikkilä, J.; Jalanka-Tuovinen, J.; Immonen, O.; Rajilic-Stojanovic, M.; Kekkonen, R.A.; Palva, A.; Vos, de W.M.
Several different protocols are used for fecal DNA extraction, which is an integral step in all phylogenetic and metagenomic approaches to characterize the highly diverse intestinal ecosystem. We compared four widely used methods, and found their DNA yields to vary up to 35-fold. Bacterial, archaeal
Salonen, A.; Nikkilä, J.; Jalanka-Tuovinen, J.; Immonen, O.; Rajilic-Stojanovic, M.; Kekkonen, R.A.; Palva, A.; Vos, de W.M.
Several different protocols are used for fecal DNA extraction, which is an integral step in all phylogenetic and metagenomic approaches to characterize the highly diverse intestinal ecosystem. We compared four widely used methods, and found their DNA yields to vary up to 35-fold. Bacterial, archaeal
Bernau, C; Boulesteix, A-L; Knaus, J
Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.
Full Text Available Abstract Background Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users. Results We have developed a tool, LACK, for calculating the statistical significance of apparent lexical bias in microarray datasets. The frequency of a user-specified list of search terms in a list of genes which are differentially regulated is assessed for statistical significance by comparison to randomly generated datasets. The simplicity of the input files and user interface targets the average microarray user who wishes to have a statistical measure of apparent lexical trends in analyzed datasets without the need for bioinformatics skills. The software is available as Perl source or a Windows executable. Conclusion We have used LACK in our laboratory to generate biological hypotheses based on our microarray data. We demonstrate the program's utility using an example in which we confirm significant upregulation of SPI-2 pathogenicity island of Salmonella enterica serovar Typhimurium by the cation chelator dipyridyl.
Hui-Ying Jin; Kai-Hua Tao; Yue-Xi Li; Fa-Qing Li; Su-Qin Li
AIM: To establish the rapid, specific, and sensitive method for detecting O157:H7 with DNA microchips.METHODS: Specific oligonucleotide probes (26-28 nt) of bacterial antigenic and virulent genes of E. coli O157:H7 and other related pathogen genes were pre-synthesized and immobilized on a solid support to make microchips. The four genes encoding O157 somatic antigen (rfbE), H7 fiagellar antigen (fliC) and toxins (SLT1, SLT2) were monitored by multiplex PCR with four pairs of specific primers. Fluorescence-Cy3 labeled samples for hybridization were generated by PCR with Cy3-labeled single prime. Hybridization was performed for 60 min at 45 ℃. Microchip images were taken using a confocal fluorescent scanner.RESULTS: Twelve different bacterial strains were detected with various combinations of four virulent genes. All the O157:H7 strains yielded positive results by multiplex PCR.The size of the PCR products generated with these primers varied from 210 to 678 bp. All the rfbE/fliC/SLT1/SLT2 probes specifically recognized Cy3-labeled fluorescent samples from O157:H7 strains, or strains containing O157 and H7 genes. No cross hybridization of O157:H7 fluorescent samples occurred in other probes. Non-O157:H7 pathogens failed to yield any signal under comparable conditions. If the Cy3-labeled fluorescent product of O157 single PCR was diluted 50-fold, no signal was found in agarose gel electrophoresis, but a positive signal was found in microarray hybridization.CONCLUSION: Microarray analysis of O157:H7 is a rapid,specific, and efficient method for identification and detection of bacterial pathogens.
Vanderburg Charles R
Full Text Available Abstract Background Gene microarray technology is an effective tool to investigate the simultaneous activity of multiple cellular pathways from hundreds to thousands of genes. However, because data in the colossal amounts generated by DNA microarray technology are usually complex, noisy, high-dimensional, and often hindered by low statistical power, their exploitation is difficult. To overcome these problems, two kinds of unsupervised analysis methods for microarray data: principal component analysis (PCA and independent component analysis (ICA have been developed to accomplish the task. PCA projects the data into a new space spanned by the principal components that are mutually orthonormal to each other. The constraint of mutual orthogonality and second-order statistics technique within PCA algorithms, however, may not be applied to the biological systems studied. Extracting and characterizing the most informative features of the biological signals, however, require higher-order statistics. Results ICA is one of the unsupervised algorithms that can extract higher-order statistical structures from data and has been applied to DNA microarray gene expression data analysis. We performed FastICA method on DNA microarray gene expression data from Alzheimer's disease (AD hippocampal tissue samples and consequential gene clustering. Experimental results showed that the ICA method can improve the clustering results of AD samples and identify significant genes. More than 50 significant genes with high expression levels in severe AD were extracted, representing immunity-related protein, metal-related protein, membrane protein, lipoprotein, neuropeptide, cytoskeleton protein, cellular binding protein, and ribosomal protein. Within the aforementioned categories, our method also found 37 significant genes with low expression levels. Moreover, it is worth noting that some oncogenes and phosphorylation-related proteins are expressed in low levels. In
Urushibara, Tomoko; Akasaka, Shizu; Ito, Makiko; Suzuki, Tomonori; Miyazaki, Satoru
Recently after human genome sequence has been determined almost perfectly, more and more researchers have been studying genes in detail. Therefore, we are sure that accumulated gene information for human will be getting more important in the near future to develop customized medicine and to make gene interactions clear. Among plenty of information, micro array might be one of the most important analysis method for genes because it is the technique that can get big amount of the gene expressions data from one time experiment and also can be used for DNA isolation. To get the novel knowledge from micro array data, we need to enrich statistical tools for its data analysis. So far, many mathematical theories and definition have been proposing. However, many of those proposals are tested with strict conditions or customized to data for specific species. In this paper, we reviewed existing typical statistical methods for micro array analysis and discussed the repeatability of the analysis, construction the guideline with more general procedure. First we analyzed the micro array data for TG rats, with statistical methods of family-wise error rate (FWER) control approach and False Discovery Rate (FDR) control approach. As existing report, no significantly different gene could be detected with FWER control approach. On the other hand, we could find several genes significantly with FDR control approach even q=0.5. To find out the reliability of FDR control approach with micro array conditions, we have analyzed 2 more pieces of data from Gene Expression Omnibus (GEO) public database on the web site with SAM in addition to FWER and FDR control approaches. We could find a certain number of significantly different genes with BH method and SAM in the case of q=0.05. However, we have to note that the number and kinds of detected genes are different when we compare our result with the one from the published paper. Even if the same approach is used to analyze the same micro array
Kuklin A. V.
Full Text Available The changes induced in transcriptome of rat hepatocytes treated with interferon alpha (IFN during three and six hours were analyzed by DNA microarray. Aim. To conduct a stepwise analysis of the results of microarray experiment and to determine whether they meet/fail to the conventional requirements. Methods. The files obtained after scanning microarrays were subjected to the analysis in statistical environment R by Bioconductor’s packages «affy», «simpleaffy», «affyPLM» and BRB Array Tools software for paired T-test. Results. All microarrays had quality metrics lying within recommended ranges, passed quality control, were normalized and are comparable with each other. The T-test revealed 28 and 124 differentially expressed genes after three and six hours of cells cultivation with IFNα , respectively. Conclusions. The obtained data meet the conventional criteria of quality and are applicable for further evaluation of their biological significance. The R-codes used in this study can be used for the analysis of the microarrays data.
Brask, Julie Benedicte; Talman, Maj-Lis Møller; Wielenga, Vera Timmermans
by investigating the usefulness of tissue microarray (TMA) analysis as a screening tool. We present our findings with regard to sensitivity and specificity compared with whole-mount sections. The material consists of 240 cases of breast cancer divided into 20 TMA blocks that were all immunohistochemically stained...
Beaudet, Arthur L.
Chromosomal microarray analysis (CMA) has emerged as a powerful new tool to identify genomic abnormalities associated with a wide range of developmental disabilities including congenital malformations, cognitive impairment, and behavioral abnormalities. CMA includes array comparative genomic hybridization (CGH) and single nucleotide polymorphism…
LI Guo-qi; SHENG Huan-ye
Background knowledge is important for data mining, especially in complicated situation. Ontological engineering is the successor of knowledge engineering. The sharable knowledge bases built on ontology can be used to provide background knowledge to direct the process of data mining. This paper gives a common introduction to the method and presents a practical analysis example using SVM (support vector machine) as the classifier. Gene Ontology and the accompanying annotations compose a big knowledge base, on which many researches have been carried out. Microarray dataset is the output of DNA chip.With the help of Gene Ontology we present a more elaborate analysis on microarray data than former researchers. The method can also be used in other fields with similar scenario.
Ak, Handan; Zeybek, Burak; Atay, Sevcan; Askar, Niyazi; Akdemir, Ali; Aydin, Hikmet Hakan
Pelvic organ prolapse (POP) is a major health problem that impairs the quality of life with a wide clinical spectrum. Since the uterosacral ligaments provide primary support for the uterus and the upper vagina, we hypothesize that the disruption of these ligaments may lead to a loss of support and eventually contribute to POP. In this study, we therefore investigated whether there are any differences in the transcription profile of uterosacral ligaments in patients with POP when compared to those of the control samples. Seventeen women with POP and 8 non-POP controls undergoing hysterectomy for benign conditions were included in the study. Affymetrix® Gene Chip microarrays (Human Hu 133 plus 2.0) were used for whole genome gene expression profiling analysis. There was 1 significantly down-regulated gene, NKX2-3 in patients with POP compared to the controls (p=4.28464e-013). KIF11 gene was found to be significantly down-regulated in patients with ≥3 deliveries compared to patients with <3 deliveries (p=0.0156237). UGT1A1 (p=2.43388e-005), SCARB1 (p=1.19001e-006) and NKX2-3 (p=2.17966e-013) genes were found to be significantly down-regulated in the premenopausal patients compared to the premenopausal controls. UGT1A1 gene was also found to be significantly down-regulated in the post menopausal patients compared to the postmenopausal controls (p=0.0005). This study provides evidence for a significant down-regulation of the genes that take role in cell cycle, proliferation and embryonic development along with cell adhesion process on the development of POP for the first time. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
To identify gene expression profiling in epithelial ovarian cancer and to explore its correlation with histopathology characterization and prognosis. Gene expression profiles were generated from 10 human ovarian frozen tissue specimens using Agilent Human 1A microarrays. Strikingly, clear differences of gene expression patterns were observed in ovarian cancer as compared to normal tissues. Unique gene profiles were observed in moderately and poorly differentiated epithelial ovarian cancer. It is concluded that different histopathology characterization likely exists extensive molecular heterogeneity.
Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.
Mans, Jeffrey J; Lamont, Richard J; Handfield, Martin
Host-pathogen interactions are inherently complex and dynamic. The recent use of human microarrays has been invaluable to monitor the effects of various bacterial and viral pathogens upon host cell gene expression programs. This methodology has allowed the host response transcriptome of several cell lines to be studied on a global scale. To this point, the great majority of reports have focused on the response of immune cells, including macrophages and dendritic cells. These studies revealed that the immune response to microbial pathogens is tailored to different microbial challenges. Conversely, the paradigm for epithelial cells has--until recently--held that the epithelium mostly served as a relatively passive physical barrier to infection. It is now generally accepted that the epithelial barrier contributes more actively to signaling events in the immune response. In light of this shift, this review will compare transcriptional profiling data from studies that involved host-pathogen interactions occurring with epithelial cells. Experiments that defined both a common core response, as well as pathogen-specific host responses will be discussed. This review will also summarize the contributions that transcriptional profiling analysis has made to our understanding of bacterial physio-pathogensis of infection. This will include a discussion of how host transcriptional responses can be used to infer the function of virulence determinants from bacterial pathogens interacting with epithelial mucosa. In particular, we will expand upon the lessons that have been learned from gastro-intestinal and oral pathogens, as well as from members of the commensal flora.
Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph
The web application MAGMA provides a simple and intuitive interface to identify differentially expressed genes from two-channel microarray data. While the underlying algorithms are not superior to those of similar web applications, MAGMA is particularly user friendly and can be used without prior training. The user interface guides the novice user through the most typical microarray analysis workflow consisting of data upload, annotation, normalization and statistical analysis. It automatically generates R-scripts that document MAGMA's entire data processing steps, thereby allowing the user to regenerate all results in his local R installation. The implementation of MAGMA follows the model-view-controller design pattern that strictly separates the R-based statistical data processing, the web-representation and the application logic. This modular design makes the application flexible and easily extendible by experts in one of the fields: statistical microarray analysis, web design or software development. State-of-the-art Java Server Faces technology was used to generate the web interface and to perform user input processing. MAGMA's object-oriented modular framework makes it easily extendible and applicable to other fields and demonstrates that modern Java technology is also suitable for rather small and concise academic projects. MAGMA is freely available at www.magma-fgcz.uzh.ch.
Getz, G; Domany, E
We present a novel coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task: we present an algorithm, based on iterative clustering, which performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.
Getz, Gad; Levine, Erel; Domany, Eytan
We present a coupled two-way clustering approach to gene microarray data analysis. The main idea is to identify subsets of the genes and samples, such that when one of these is used to cluster the other, stable and significant partitions emerge. The search for such subsets is a computationally complex task. We present an algorithm, based on iterative clustering, that performs such a search. This analysis is especially suitable for gene microarray data, where the contributions of a variety of biological mechanisms to the gene expression levels are entangled in a large body of experimental data. The method was applied to two gene microarray data sets, on colon cancer and leukemia. By identifying relevant subsets of the data and focusing on them we were able to discover partitions and correlations that were masked and hidden when the full dataset was used in the analysis. Some of these partitions have clear biological interpretation; others can serve to identify possible directions for future research.
Hideo KABURAGI; Naoyuki SUGANO; Maiko OSHIKAWA; Ryosuke KOSHI; Naoki SENDA; Kazuhiro KAWAMOTO; Koichi ITO
To analyze the molecular events that occur in the developing mandible, we examined the expression of 8803 genes from samples taken at different time points during rat postnatal mandible development.Total RNA was extracted from the mandibles of 1-day-old, 1-week-old, and 2-week-old rats. Complementary RNA (cRNA) was synthesized from cDNA and biotinylated. Fragmented cRNA was hybridized to RGU34A GeneChip arrays. Among the 8803 genes tested, 4344 were detectable. We identified 148 genes with significantly increased expression, and 19 genes with significantly decreased expression. A comprehensive analysis appears to be an effective method of studying the complex process of development.
Li, J. J.; Wang, B. Q.; Yang, Y.; Li, D.
Objectives In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. Methods We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. Results A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be signiﬁcantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Conclusion Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and
Knudsen, Steen; Workman, Christopher; Sicheritz-Ponten, T.
GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with aspecification of the data. The server performs normalization......, statistical analysis and visualization of the data. The results are run against databases of signal transduction pathways, metabolic pathways and promoter sequences in order to extract more information. The results of the entire analysis are summarized in report form and returned to the user....
Moon, Eun-Kyung; Xuan, Ying-Hua; Kong, Hyun-Hee
Long-term cultivation in a laboratory could reduce the virulence of Acanthamoeba. To identify virulence factors of Acanthamoeba, the authors compared the transcription profiles of long-term cultivated Acanthamoeba healyi (OLD) and three times mouse-brain passaged A. healyi (MBP) using microarray analysis and eukaryotic orthologous group (KOG) assignments. Microarray analysis revealed that 601 genes were up-regulated by mouse-brain passage. The results of real-time PCR of 8 randomly selected genes up-regulated in the MBP strain confirmed microarray analysis findings. KOG assignments showed relatively higher percentages of the MBP strain up-regulated genes in T article (signal transduction mechanism), O article (posttranslational modification, protein turnover, chaperones), C article (energy production and conversion), and J article (translation, ribosomal structure and biogenesis). In particular, the MBP strain showed higher expressions of cysteine protease and metalloprotease. A comparison of KOG assignments by microarray analysis and previous EST (expressed sequence tags) analysis showed similar populations of up-regulated genes. These results provide important information regarding the identification of virulence factors of pathogenic Acanthamoeba.
Andersen, Mikael Rørdam; Vongsangnak, Wanwipa; Panagiotou, Gianni
The full-genome sequencing of the filamentous fungi Aspergillus nidulans, Aspergillus niger, and Aspergillus oryzae has opened possibilities for studying the cellular physiology of these fungi on a systemic level. As a tool to explore this, we are making available an Affymetrix GeneChip developed...... data identified 23 genes to be a conserved response across Aspergillus sp., including the xylose transcriptional activator XlnR. A promoter analysis of the up-regulated genes in all three species indicates the conserved XInR-binding site to be 5'-GGNTAAA-3'. The composition of the conserved gene......-set suggests that xylose acts as a molecule, indicating the presence of complex carbohydrates such as hemicellulose, and triggers an array of degrading enzymes. With this case example, we present a validated tool for transcriptome analysis of three Aspergillus species and a methodology for conducting cross...
Bozinov, Oliver; Köhler, Sylvia; Samans, Birgit; Benes, Ludwig; Miller, Dorothea; Ritter, Markus; Sure, Ulrich; Bertalanffy, Helmut
Malignant astrocytomas of World Health Organization (WHO) grade III or IV have a reduced median survival time, and possible pathways have been described for the progression of anaplastic astrocytomas and glioblastomas, but the molecular basis of malignant astrocytoma progression is still poorly understood. Microarray analysis provides the chance to accelerate studies by comparison of the expression of thousands of genes in these tumours and consequently identify targeting genes. We compared the transcriptional profile of 4,608 genes in tumours of 15 patients including 6 anaplastic astrocytomas (WHO grade III) and 9 glioblastomas (WHO grade IV) using microarray analysis. The microarray data were corroborated by real-time reverse transcription-polymerase chain reaction analysis of two selected genes. We identified 166 gene alterations with a fold change of 2 and higher whose mRNA levels differed (absolute value of the t statistic of 1.96) between the two malignant glioma groups. Further analyses confirmed same transcription directions for Olig2 and IL-13Ralpha2 in anaplastic astrocytomas as compared to glioblastomas. Microarray analyses with a close binary question reveal numerous interesting candidate genes, which need further histochemical testing after selection for confirmation. IL-13Ralpha2 and Olig2 have been identified and confirmed to be interesting candidate genes whose differential expression likely plays a role in malignant progression of astrocytomas.
Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N
The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a
Marcelo F. Carazzolle
Full Text Available The web application D-Maps provides a user-friendly interface to researchers performing studies based on microarrays. The program was developed to manage and process one- or two-color microarray data obtained from several platforms (currently, GeneTAC, ScanArray, CodeLink, NimbleGen and Affymetrix. Despite the availability of many algorithms and many software programs designed to perform microarray analysis on the internet, these usually require sophisticated knowledge of mathematics, statistics and computation. D-maps was developed to overcome the requirement of high performance computers or programming experience. D-Maps performs raw data processing, normalization and statistical analysis, allowing access to the analyzed data in text or graphical format. An original feature presented by D-Maps is GEO (Gene Expression Omnibus submission format service. The D-MaPs application was already used for analysis of oligonucleotide microarrays and PCR-spotted arrays (one- and two-color, laser and light scanner. In conclusion, D-Maps is a valuable tool for microarray research community, especially in the case of groups without a bioinformatic core.
Full Text Available Abstract Background The origin of novel traits and their subsequent diversification represent central themes in evo-devo and evolutionary ecology. Here we explore the genetic and genomic basis of a class of traits that is both novel and highly diverse, in a group of organisms that is ecologically complex and experimentally tractable: horned beetles. Results We developed two high quality, normalized cDNA libraries for larval and pupal Onthophagus taurus and sequenced 3,488 ESTs that assembled into 451 contigs and 2,330 singletons. We present the annotation and a comparative analysis of the conservation of the sequences. Microarrays developed from the combined libraries were then used to contrast the transcriptome of developing primordia of head horns, prothoracic horns, and legs. Our experiments identify a first comprehensive list of candidate genes for the evolution and diversification of beetle horns. We find that developing horns and legs show many similarities as well as important differences in their transcription profiles, suggesting that the origin of horns was mediated partly, but not entirely, by the recruitment of genes involved in the formation of more traditional appendages such as legs. Furthermore, we find that horns developing from the head and prothorax differ in their transcription profiles to a degree that suggests that head and prothoracic horns are not serial homologs, but instead may have evolved independently from each other. Conclusion We have laid the foundation for a systematic analysis of the genetic basis of horned beetle development and diversification with the potential to contribute significantly to several major frontiers in evolutionary developmental biology.
Cronobacter is a recently defined genus synonymous with Enterobacter sakazakii. This new genus currently comprises 6 genomospecies. To extend our understanding of the genetic relationship between Cronobacter sakazakii BAA-894 and the other species of this genus, microarray-based comparative genomi...
Full Text Available Abstract Background The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determine which clustering algorithm is most appropriate to apply, and it is difficult to verify the results of any algorithm due to the lack of a gold-standard. Appropriate data visualization tools can aid this analysis process, but existing visualization methods do not specifically address this issue. Results We present several visualization techniques that incorporate meaningful statistics that are noise-robust for the purpose of analyzing the results of clustering algorithms on microarray data. This includes a rank-based visualization method that is more robust to noise, a difference display method to aid assessments of cluster quality and detection of outliers, and a projection of high dimensional data into a three dimensional space in order to examine relationships between clusters. Our methods are interactive and are dynamically linked together for comprehensive analysis. Further, our approach applies to both protein and gene expression microarrays, and our architecture is scalable for use on both desktop/laptop screens and large-scale display devices. This methodology is implemented in GeneVAnD (Genomic Visual ANalysis of Datasets and is available at http://function.princeton.edu/GeneVAnD. Conclusion Incorporating relevant statistical information into data visualizations is key for analysis of large biological datasets, particularly because of high levels of noise and the lack of a gold-standard for comparisons. We developed several new visualization techniques and demonstrated their effectiveness for evaluating cluster quality and relationships between clusters.
Loots, G G; Chain, P G; Mabery, S; Rasley, A; Garcia, E; Ovcharenko, I
We have developed an integrative and automated toolkit for the analysis of Affymetrix microarray data, named Array2BIO. It identifies groups of coexpressed genes using two complementary approaches--comparative analysis of signal versus control microarrays and clustering analysis of gene expression across different conditions. The identified genes are assigned to functional categories based on the Gene Ontology classification, and a detection of corresponding KEGG protein interaction pathways. Array2BIO reliably handles low-expressor genes and provides a set of statistical methods to quantify the odds of observations, including the Benjamini-Hochberg and Bonferroni multiple testing corrections. Automated interface with the ECR Browser provides evolutionary conservation analysis of identified gene loci while the interconnection with Creme allows high-throughput analysis of human promoter regions and prediction of gene regulatory elements that underlie the observed expression patterns. Array2BIO is publicly available at http://array2bio.dcode.org.
DNA microarrays can be used for large number of application where high-throughput is needed. The ability to probe a sample for hundred to million different molecules at once has made DNA microarray one of the fastest growing techniques since its introduction about 15 years ago. Microarray technology can be used for large scale genotyping, gene expression profiling, comparative genomic hybridization and resequencing among other applications. Microarray technology is a complex mixture of numerous technology and research fields such as mechanics, microfabrication, chemistry, DNA behaviour, microfluidics, enzymology, optics and bioinformatics. This chapter will give an introduction to each five basic steps in microarray technology that includes fabrication, target preparation, hybridization, detection and data analysis. Basic concepts and nomenclature used in the field of microarray technology and their relationships will also be explained.
Qi, Xin; Cukierski, William; Foran, David J.
The lack of clear consensus over the utility of multispectral imaging (MSI) for bright-field imaging prompted our team to investigate the benefit of using MSI on breast tissue microarrays (TMA). We have conducted performance studies to compare MSI with standard bright-field imaging in hematoxylin stained breast tissue. The methodology has three components. The first extracts a region of interest using adaptive thresholding and morphological processing. The second performs texture feature extraction from a local binary pattern within each spectral channel and compared to features of co-occurrence matrix and texture feature coding in third component. The third component performs feature selection and classification. For each spectrum, exhaustive feature selection was used to search for the combination of features that yields the best classification accuracy. AdaBoost with a linear perceptron least-square classifier was applied. The spectra carrying the greatest discriminatory power were automatically chosen and a majority vote was used to make the final classification. 92 breast TMA discs were included in the study. Sensitivity of 0.96 and specificity of 0.89 were achieved on the multispectral data, compared with sensitivity of 0.83 and specificity of 0.85 on RGB data. MSI consistently achieved better classification results than those obtained using standard RGB images. While the benefits of MSI for unmixing multi-stained specimens are well documented, this study demonstrated statistically significant improvements in the automated analysis of single stained bright-field images.
Sarkar, Anasua; Maulik, Ujjwal
Identification of co-expressed genes is the central goal in microarray gene expression analysis. Point-symmetry-based clustering is an important unsupervised learning technique for recognising symmetrical convex- or non-convex-shaped clusters. To enable fast clustering of large microarray data, we propose a distributed time-efficient scalable approach for point-symmetry-based K-Means algorithm. A natural basis for analysing gene expression data using symmetry-based algorithm is to group together genes with similar symmetrical expression patterns. This new parallel implementation also satisfies linear speedup in timing without sacrificing the quality of clustering solution on large microarray data sets. The parallel point-symmetry-based K-Means algorithm is compared with another new parallel symmetry-based K-Means and existing parallel K-Means over eight artificial and benchmark microarray data sets, to demonstrate its superiority, in both timing and validity. The statistical analysis is also performed to establish the significance of this message-passing-interface based point-symmetry K-Means implementation. We also analysed the biological relevance of clustering solutions.
Full Text Available Gene mutations play a critical role in cancer development and progression, and their identification offers possibilities for accurate diagnostics and therapeutic targeting. Finding genes undergoing mutations is challenging and slow, even in the post-genomic era. A new approach was recently developed by Noensie and Dietz to prioritize and focus the search, making use of nonsense-mediated mRNA decay (NMD inhibition and microarray analysis (NMD microarrays in the identification of transcripts containing nonsense mutations. We combined NMD microarrays with array-based CGH (comparative genomic hybridization in order to identify inactivation of tumor suppressor genes in cancer. Such a “mutatomics” screening of prostate cancer cell lines led to the identification of inactivating mutations in the EPHB2 gene. Up to 8% of metastatic uncultured prostate cancers also showed mutations of this gene whose loss of function may confer loss of tissue architecture. NMD microarray analysis could turn out to be a powerful research method to identify novel mutated genes in cancer cell lines, providing targets that could then be further investigated for their clinical relevance and therapeutic potential.
Yang, Kyeong Eun; Kwon, Joseph; Rhim, Ji-Heon; Choi, Jong Soon; Kim, Seung Il; Lee, Seung-Hoon; Park, Junsoo; Jang, Ik-Soon
The extracellular matrix (ECM) provides an essential structural framework for cell attachment, proliferation, and differentiation, and undergoes progressive changes during senescence. To investigate changes in protein expression in the extracellular matrix between young and senescent fibroblasts, we compared proteomic data (LTQ-FT) with cDNA microarray results. The peptide counts from the proteomics analysis were used to evaluate the level of ECM protein expression by young cells and senescent cells, and ECM protein expression data were compared with the microarray data. After completing the comparative analysis, we grouped the genes into four categories. Class I included genes with increased expression levels in both analyses, while class IV contained genes with reduced expression in both analyses. Class II and Class III contained genes with an inconsistent expression pattern. Finally, we validated the comparative analysis results by examining the expression level of the specific gene from each category using Western blot analysis and semiquantitative RT-PCR. Our results demonstrate that comparative analysis can be used to identify differentially expressed genes.
Archer Kellie J
Full Text Available Abstract Background With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN to those with normal functioning allograft. Results The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. Conclusion We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been
Kong, Xiangrong; Mas, Valeria; Archer, Kellie J
With the popularity of DNA microarray technology, multiple groups of researchers have studied the gene expression of similar biological conditions. Different methods have been developed to integrate the results from various microarray studies, though most of them rely on distributional assumptions, such as the t-statistic based, mixed-effects model, or Bayesian model methods. However, often the sample size for each individual microarray experiment is small. Therefore, in this paper we present a non-parametric meta-analysis approach for combining data from independent microarray studies, and illustrate its application on two independent Affymetrix GeneChip studies that compared the gene expression of biopsies from kidney transplant recipients with chronic allograft nephropathy (CAN) to those with normal functioning allograft. The simulation study comparing the non-parametric meta-analysis approach to a commonly used t-statistic based approach shows that the non-parametric approach has better sensitivity and specificity. For the application on the two CAN studies, we identified 309 distinct genes that expressed differently in CAN. By applying Fisher's exact test to identify enriched KEGG pathways among those genes called differentially expressed, we found 6 KEGG pathways to be over-represented among the identified genes. We used the expression measurements of the identified genes as predictors to predict the class labels for 6 additional biopsy samples, and the predicted results all conformed to their pathologist diagnosed class labels. We present a new approach for combining data from multiple independent microarray studies. This approach is non-parametric and does not rely on any distributional assumptions. The rationale behind the approach is logically intuitive and can be easily understood by researchers not having advanced training in statistics. Some of the identified genes and pathways have been reported to be relevant to renal diseases. Further study on the
Tchagang, Alain B.; Tewfik, Ahmed H.
Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.
Tewfik Ahmed H
Full Text Available Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.
Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.
Lu, Xin-Yan; Phung, Mai T.; Shaw, Chad A.; Pham, Kim; Neil, Sarah E.; Patel, Ankita; Sahoo, Trilochan; Bacino, Carlos A.; Stankiewicz, Pawel; Lee Kang, Sung-Hae; Lalani, Seema; Chinault, A. Craig; Lupski, James R.; Cheung, Sau W.; Beaudet, Arthur L.
OBJECTIVES Our aim was to determine the frequency of genomic imbalances in neonates with birth defects by using targeted array-based comparative genomic hybridization, also known as chromosomal microarray analysis. METHODS Between March 2006 and September 2007, 638 neonates with various birth defects were referred for chromosomal microarray analysis. Three consecutive chromosomal microarray analysis versions were used: bacterial artificial chromosome-based versions V5 and V6 and bacterial artificial chromosome emulated oligonucleotide-based version V6 Oligo. Each version had targeted but increasingly extensive genomic coverage and interrogated >150 disease loci with enhanced coverage in genomic rearrangement-prone pericentromeric and subtelomeric regions. RESULTS Overall, 109 (17.1%) patients were identified with clinically significant abnormalities with detection rates of 13.7%, 16.6%, and 19.9% on V5, V6, and V6 Oligo, respectively. The majority of these abnormalities would not be defined by using karyotype analysis. The clinically significant detection rates by use of chromosomal microarray analysis for various clinical indications were 66.7% for “possible chromosomal abnormality” ± “others” (other clinical indications), 33.3% for ambiguous genitalia ± others, 27.1% for dysmorphic features + multiple congenital anomalies ± others, 24.6% for dysmorphic features ± others, 21.8% for congenital heart disease ± others, 17.9% for multiple congenital anomalies ± others, and 9.5% for the patients referred for others that were different from the groups defined. In all, 16 (2.5%) patients had chromosomal aneuploidies, and 81 (12.7%) patients had segmental aneusomies including common microdeletion or microduplication syndromes and other genomic disorders. Chromosomal mosaicism was found in 12 (1.9%) neonates. CONCLUSIONS Chromosomal microarray analysis is a valuable clinical diagnostic tool that allows precise and rapid identification of genomic imbalances
Sturino, Joseph; Zorych, Ivan; Mallick, Bani; Pokusaeva, Karina; Chang, Ying-Ying; Carroll, Raymond J.; Bliznuyk, Nikolay
We propose statistical methods for comparing phenomics data generated by the Biolog Phenotype Microarray (PM) platform for high-throughput phenotyping. Instead of the routinely used visual inspection of data with no sound inferential basis, we develop two approaches. The first approach is based on quantifying the distance between mean or median curves from two treatments and then applying a permutation test; we also consider a permutation test applied to areas under mean curves. The second ap...
蒋学锋; 朱涛; 杨洁; 李双; 叶双梅; 廖书杰; 孟力; 卢运萍; 马丁
The purpose of this study was to pool information in epithelial ovarian cancer by combining studies using Affymetrix expression microarray datasets made at different laboratories to identify novel biomarkers.Epithelial microarray expression information across laboratories was screened and combined after preprocessing raw microarray data,then ANOVA and unpaired T test statistical analysis was performed for identifying differentially expressed genes(DEGs),followed by clustering and pathway analysis for these ...
Hess Ann M
Full Text Available Abstract Background Due to the large number of hypothesis tests performed during the process of routine analysis of microarray data, a multiple testing adjustment is certainly warranted. However, when the number of tests is very large and the proportion of differentially expressed genes is relatively low, the use of a multiple testing adjustment can result in very low power to detect those genes which are truly differentially expressed. Filtering allows for a reduction in the number of tests and a corresponding increase in power. Common filtering methods include filtering by variance, average signal or MAS detection call (for Affymetrix arrays. We study the effects of filtering in combination with the Benjamini-Hochberg method for false discovery rate control and q-value for false discovery rate estimation. Results Three case studies are used to compare three different filtering methods in combination with the two false discovery rate methods and three different preprocessing methods. For the case studies considered, filtering by detection call and variance (on the original scale consistently led to an increase in the number of differentially expressed genes identified. On the other hand, filtering by variance on the log2 scale had a detrimental effect when paired with MAS5 or PLIER preprocessing methods, even when the testing was done on the log2 scale. A simulation study was done to further examine the effect of filtering by variance. We find that filtering by variance leads to higher power, often with a decrease in false discovery rate, when paired with either of the false discovery rate methods considered. This holds regardless of the proportion of genes which are differentially expressed or whether we assume dependence or independence among genes. Conclusion The case studies show that both detection call and variance filtering are viable methods of filtering which can increase the number of differentially expressed genes identified. The
Keramas, Georgios; Bang, Dang Duong; Lund, Marianne
A DNA microarray for detection of Campylobacter spp. was recently developed and applied to detect Campylobacter spp. directly from chicken feces. Sixty-five pooled chicken cloacal swab samples from 650 individual broiler chickens were included in the study. The results of Campylobacter sp....... detection obtained with DNA microarrays were compared to those obtained by conventional culture and gel electrophoresis. By conventional culture, 60% of the samples were positive for either Campylobacter jejuni or Campylobacter coli. By PCR and capillary electrophoresis, 95% of the samples were positive...... for Campylobacter spp., whereas with DNA microarrays all samples were positive for Campylobacter spp. By application of DNA microarray analysis, the isolates in 4 samples (6%) could not be identified to the species level, whereas by PCR-capillary electrophoresis, the isolates in 12 samples (19%) remained...
Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar
Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. Copyright © 2016 Elsevier Inc. All rights reserved.
Full Text Available Abstract Background It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of genes are dependent on each other. Experimental techniques to detect such interacting pairs of genes have been in place for quite some time. With the advent of microarray technology, newer computational techniques to detect such interaction or association between gene expressions are being proposed which lead to an association network. While most microarray analyses look for genes that are differentially expressed, it is of potentially greater significance to identify how entire association network structures change between two or more biological settings, say normal versus diseased cell types. Results We provide a recipe for conducting a differential analysis of networks constructed from microarray data under two experimental settings. At the core of our approach lies a connectivity score that represents the strength of genetic association or interaction between two genes. We use this score to propose formal statistical tests for each of following queries: (i whether the overall modular structures of the two networks are different, (ii whether the connectivity of a particular set of "interesting genes" has changed between the two networks, and (iii whether the connectivity of a given single gene has changed between the two networks. A number of examples of this score is provided. We carried out our method on two types of simulated data: Gaussian networks and networks based on differential equations. We show that, for appropriate choices of the connectivity scores and tuning parameters, our method works well on simulated data. We also analyze a real data set involving normal versus heavy mice and identify an interesting set of genes that may play key roles in obesity. Conclusions Examining changes in network structure can provide valuable information about the
Pérez-Amador, M A; Lidder, P; Johnson, M A; Landgraf, J; Wisman, E; Green, P J
In this study, DNA microarray analysis was used to expand our understanding of the dst1 mutant of Arabidopsis. The dst (downstream) mutants were isolated originally as specifically increasing the steady state level and the half-life of DST-containing transcripts. As such, txhey offer a unique opportunity to study rapid sequence-specific mRNA decay pathways in eukaryotes. These mutants show a threefold to fourfold increase in mRNA abundance for two transgenes and an endogenous gene, all containing DST elements, when examined by RNA gel blot analysis; however, they show no visible aberrant phenotype. Here, we use DNA microarrays to identify genes with altered expression levels in dst1 compared with the parental plants. In addition to verifying the increase in the transgene mRNA levels, which were used to isolate these mutants, we were able to identify new genes with altered mRNA abundance in dst1. RNA gel blot analysis confirmed the microarray data for all genes tested and also was used to catalog the first molecular differences in gene expression between the dst1 and dst2 mutants. These differences revealed previously unknown molecular phenotypes for the dst mutants that will be helpful in future analyses. Cluster analysis of genes altered in dst1 revealed new coexpression patterns that prompt new hypotheses regarding the nature of the dst1 mutation and a possible role of the DST-mediated mRNA decay pathway in plants.
Moon, Eun-Kyung; Xuan, Ying-Hua; Chung, Dong-Il; Hong, Yeonchul; Kong, Hyun-Hee
Acanthamoeba infection is difficult to treat because of the resistance property of Acanthamoeba cyst against the host immune system, diverse antibiotics, and therapeutic agents. To identify encystation mediating factors of Acanthamoeba, we compared the transcription profile between cysts and trophozoites using microarray analysis. The DNA chip was composed of 12,544 genes based on expressed sequence tag (EST) from an Acanthamoeba ESTs database (DB) constructed in our laboratory, genetic information of Acanthamoeba from TBest DB, and all of Acanthamoeba related genes registered in the NCBI. Microarray analysis indicated that 701 genes showed higher expression than 2 folds in cysts than in trophozoites, and 859 genes were less expressed in cysts than in trophozoites. The results of real-time PCR analysis of randomly selected 9 genes of which expression was increased during cyst formation were coincided well with the microarray results. Eukaryotic orthologous groups (KOG) analysis showed an increment in T article (signal transduction mechanisms) and O article (posttranslational modification, protein turnover, and chaperones) whereas significant decrement of C article (energy production and conversion) during cyst formation. Especially, cystein proteinases showed high expression changes (282 folds) with significant increases in real-time PCR, suggesting a pivotal role of this proteinase in the cyst formation of Acanthamoeba. The present study provides important clues for the identification and characterization of encystation mediating factors of Acanthamoeba.
Hogan Michael E
Full Text Available Abstract Background Neonatal blood, obtained from a heel stick and stored dry on paper cards, has been the standard for birth defects screening for 50 years. Such dried blood samples are used, primarily, for analysis of small-molecule analytes. More recently, the DNA complement of such dried blood cards has been used for targeted genetic testing, such as for single nucleotide polymorphism in cystic fibrosis. Expansion of such testing to include polygenic traits, and perhaps whole genome scanning, has been discussed as a formal possibility. However, until now the amount of DNA that might be obtained from such dried blood cards has been limiting, due to inefficient DNA recovery technology. Results A new technology is employed for efficient DNA release from a standard neonatal blood card. Using standard Guthrie cards, stored an average of ten years post-collection, about 1/40th of the air-dried neonatal blood specimen (two 3 mm punches was processed to obtain DNA that was sufficient in mass and quality for direct use in microarray-based whole genome scanning. Using that same DNA release technology, it is also shown that approximately 1/250th of the original purified DNA (about 1 ng could be subjected to whole genome amplification, thus yielding an additional microgram of amplified DNA product. That amplified DNA product was then used in microarray analysis and yielded statistical concordance of 99% or greater to the primary, unamplified DNA sample. Conclusion Together, these data suggest that DNA obtained from less than 10% of a standard neonatal blood specimen, stored dry for several years on a Guthrie card, can support a program of genome-wide neonatal genetic testing.
Bogert, van den B.; Vos, de W.M.; Zoetendal, E.G.; Kleerebezem, M.
Large-scale and in-depth characterization of the intestinal microbiota necessitates application of high-throughput 16S rRNA gene-based technologies, such as barcoded pyrosequencing and phylogenetic microarray analysis. In this study, the two techniques were compared and contrasted for analysis of th
Greetham, Darren; Lappin, David F; Rajendran, Ranjith; O'Donnell, Lindsay; Sherry, Leighann; Ramage, Gordon; Nile, Christopher
Candida albicans metabolic activity in the presence and absence of acetylcholine was measured using phenotypic microarray analysis. Acetylcholine inhibited C. albicans biofilm formation by slowing metabolism independent of biofilm forming capabilities. Phenotypic microarray analysis can therefore be used for screening compound libraries for novel anti-fungal drugs and measuring antifungal resistance.
Furge, Laura Lowe; Winter, Michael B.; Meyers, Jacob I.; Furge, Kyle A.
Comprehensive measurement of gene expression using high-density nucleic acid arrays (i.e. microarrays) has become an important tool for investigating the molecular differences in clinical and research samples. Consequently, inclusion of discussion in biochemistry, molecular biology, or other appropriate courses of microarray technologies has…
Full Text Available BACKGROUND: The use of resequencing microarrays for screening multiple, candidate disease loci is a promising alternative to conventional capillary sequencing. We describe the performance of a custom resequencing microarray for mutational analysis of Congenital Myasthenic Syndromes (CMSs, a group of disorders in which the normal process of neuromuscular transmission is impaired. METHODOLOGY/PRINCIPAL FINDINGS: Our microarray was designed to assay the exons and flanking intronic regions of 8 genes linked to CMSs. A total of 31 microarrays were hybridized with genomic DNA from either individuals with known CMS mutations or from healthy controls. We estimated an overall microarray call rate of 93.61%, and we found the percentage agreement between the microarray and capillary sequencing techniques to be 99.95%. In addition, our microarray exhibited 100% specificity and 99.99% reproducibility. Finally, the microarray detected 22 out of the 23 known missense mutations, but it failed to detect all 7 known insertion and deletion (indels mutations, indicating an overall sensitivity of 73.33% and a sensitivity with respect to missense mutations of 95.65%. CONCLUSIONS/SIGNIFICANCE: Overall, our microarray prototype exhibited strong performance and proved highly efficient for screening genes associated with CMSs. Until indels can be efficiently assayed with this technology, however, we recommend using resequencing microarrays for screening CMS mutations after common indels have been first assayed by capillary sequencing.
Polycystic ovary syndrome (PCOS) affects 5-10 % of women during their reproductive age and the incidence of the disease is increasing worldwide. More than 50 % of women with PCOS are insulin resistant leading to an increased risk of type 2 diabetes (T2D) and cardiovascular diseases. However...... 1 and 2, the application of gene expression microarrays from Affymetrix was combined with global pathway analysis using GenMAPP and GSEA and subsequent validation by quantitative real-time PCR (q-RT-PCR). Impaired insulin-stimulated glucose metabolism in women with PCOS was associated with reduced...... comparable to other commercial and custom made microarrays and is a cost-effective alternative especially in larger epidemiological studies....
Full Text Available Bulk segregant analysis (BSA using microarrays, and extreme array mapping (XAM have recently been used to rapidly identify genomic regions associated with phenotypes in multiple species. These experiments, however, require the identification of single feature polymorphisms (SFP between the cross parents for each new combination of genotypes, which raises the cost of experiments. The availability of the genomic polymorphism data in Arabidopsis thaliana, coupled with the efficient designs of Single Nucleotide Polymorphism (SNP genotyping arrays removes the requirement for SFP detection and lowers the per array cost, thereby lowering the overall cost per experiment. To demonstrate that these approaches would be functional on SNP arrays and determine confidence intervals, we analyzed hybridizations of natural accessions to the Arabidopsis ATSNPTILE array and simulated BSA or XAM given a variety of gene models, populations, and bulk selection parameters. Our results show a striking degree of correlation between the genotyping output of both methods, which suggests that the benefit of SFP genotyping in context of BSA can be had with the cheaper, more efficient SNP arrays. As a final proof of concept, we hybridized the DNA from bulks of an F2 mapping population of a Sulfur and Selenium ionomics mutant to both the Arabidopsis ATTILE1R and ATSNPTILE arrays, which produced almost identical results. We have produced R scripts that prompt the user for the required parameters and perform the BSA analysis using the ATSNPTILE1 array and have provided them as supplemental data files.
van Gent Marjolein
Full Text Available Abstract Background Whooping cough caused by Bordetella pertussis in humans, is re-emerging in many countries despite vaccination. Several studies have shown that significant shifts have occurred in the B. pertussis population resulting in antigenic divergence between vaccine strains and circulating strains and suggesting pathogen adaptation. In the Netherlands, the resurgence of pertussis is associated with the rise of B. pertussis strains with an altered promoter region for pertussis toxin (ptxP3. Results We used Multi-Locus Sequence Typing (MLST, Multiple-Locus Variable Number of Tandem Repeat Analysis (MLVA and microarray-based comparative genomic hybridization (CGH to characterize the ptxP3 strains associated with the Dutch epidemic. For CGH analysis, we developed an oligonucleotide (70-mers microarray consisting of 3,581 oligonucleotides representing 94% of the gene repertoire of the B. pertussis strain Tohama I. Nine different MLST profiles and 38 different MLVA types were found in the period 1993 to 2004. Forty-three Dutch clinical isolates were analyzed with CGH, 98 genes were found to be absent in at least one of the B. pertussis strains tested, these genes were clustered in 8 distinct regions of difference. Conclusion The presented MLST, MLVA and CGH-analysis identified distinctive characteristics of ptxP3 B. pertussis strains -the most prominent of which was a genomic deletion removing about 23,000 bp. We propose a model for the emergence of ptxP3 strains.
Deng, Ye; He, Zhili; Van Nostrand, Joy D.; Zhou, Jizhong
Nonspecific hybridization is currently a major concern with microarray technology. One of most effective approaches to estimating nonspecific hybridizations in oligonucleotide microarrays is the utilization of mismatch probes; however, this approach has not been used for longer oligonucleotide probes. Here, an oligonucleotide microarray was constructed to evaluate and optimize parameters for 50-mer mismatch probe design. A perfect match (PM) and 28 mismatch (MM) probes were designed for each of ten target genes selected from three microorganisms. The microarrays were hybridized with synthesized complementary oligonucleotide targets at different temperatures (e.g., 42, 45 and 50 C). In general, the probes with evenly distributed mismatches were more distinguishable than those with randomly distributed mismatches. MM probes with 3, 4 and 5 mismatched nucleotides were differentiated for 50-mer oligonucleotide probes hybridized at 50, 45 and 42 C, respectively. Based on the experimental data generated from this study, a modified positional dependent nearest neighbor (MPDNN) model was constructed to adjust the thermodynamic parameters of matched and mismatched dimer nucleotides in the microarray environment. The MM probes with four flexible positional mismatches were designed using the newly established MPDNN model and the experimental results demonstrated that the redesigned MM probes could yield more consistent hybridizations. Conclusions: This study provides guidance on the design of MM probes for long oligonucleotides (e.g., 50 mers). The novel MPDNN model has improved the consistency for long MM probes, and this modeling method can potentially be used for the prediction of oligonucleotide microarray hybridizations.
Deng, Ye; He, Zhili; Van Nostrand, Joy D.; Zhou, Jizhong
Nonspecific hybridization is currently a major concern with microarray technology. One of most effective approaches to estimating nonspecific hybridizations in oligonucleotide microarrays is the utilization of mismatch probes; however, this approach has not been used for longer oligonucleotide probes. Here, an oligonucleotide microarray was constructed to evaluate and optimize parameters for 50-mer mismatch probe design. A perfect match (PM) and 28 mismatch (MM) probes were designed for each of ten target genes selected from three microorganisms. The microarrays were hybridized with synthesized complementary oligonucleotide targets at different temperatures (e.g., 42, 45 and 50 C). In general, the probes with evenly distributed mismatches were more distinguishable than those with randomly distributed mismatches. MM probes with 3, 4 and 5 mismatched nucleotides were differentiated for 50-mer oligonucleotide probes hybridized at 50, 45 and 42 C, respectively. Based on the experimental data generated from this study, a modified positional dependent nearest neighbor (MPDNN) model was constructed to adjust the thermodynamic parameters of matched and mismatched dimer nucleotides in the microarray environment. The MM probes with four flexible positional mismatches were designed using the newly established MPDNN model and the experimental results demonstrated that the redesigned MM probes could yield more consistent hybridizations. Conclusions: This study provides guidance on the design of MM probes for long oligonucleotides (e.g., 50 mers). The novel MPDNN model has improved the consistency for long MM probes, and this modeling method can potentially be used for the prediction of oligonucleotide microarray hybridizations.
Daniel L Roden
Full Text Available Complex human diseases can show significant heterogeneity between patients with the same phenotypic disorder. An outlier detection strategy was developed to identify variants at the level of gene transcription that are of potential biological and phenotypic importance. Here we describe a graphical software package (z-score outlier detection (ZODET that enables identification and visualisation of gross abnormalities in gene expression (outliers in individuals, using whole genome microarray data. Mean and standard deviation of expression in a healthy control cohort is used to detect both over and under-expressed probes in individual test subjects. We compared the potential of ZODET to detect outlier genes in gene expression datasets with a previously described statistical method, gene tissue index (GTI, using a simulated expression dataset and a publicly available monocyte-derived macrophage microarray dataset. Taken together, these results support ZODET as a novel approach to identify outlier genes of potential pathogenic relevance in complex human diseases. The algorithm is implemented using R packages and Java.The software is freely available from http://www.ucl.ac.uk/medicine/molecular-medicine/publications/microarray-outlier-analysis.
Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B
Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools.
Zupancic, Margaret L; Frieman, Matthew; Smith, David; Alvarez, Richard A; Cummings, Richard D; Cormack, Brendan P
The Candida glabrata genome encodes at least 23 members of the EPA (epithelial adhesin) family responsible for mediating adherence to host cells. To better understand the mechanism by which the Epa proteins contribute to pathogenesis, we have used glycan microarray analysis to characterize their carbohydrate-binding specificities. Using Saccharomyces cerevisiae strains surface-expressing the N-terminal ligand-binding domain of the Epa proteins, we found that the three Epa family members functionally identified as adhesins in Candida glabrata (Epa1, Epa6 and Epa7) bind to ligands containing a terminal galactose residue. However, the specificity of the three proteins for glycans within this class varies, with Epa6 having a broader specificity range than Epa1 or Epa7. This result is intriguing given the close homology between Epa6 and Epa7, which are 92% identical at the amino acid level. We have mapped a five-amino-acid region within the N-terminal ligand-binding domain that accounts for the difference in specificity of Epa6 and Epa7 and show that these residues contribute to adherence to both epithelial and endothelial cell lines in vitro.
Full Text Available Noma (cancrum oris is a gangrenous disease of unknown etiology affecting the maxillo-facial region of young children in extremely limited resource countries. In an attempt to better understand the microbiological events occurring during this disease, we used phylogenetic and low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis (ANG lesions, and compared them to healthy control subjects of the same geographical and social background. Our observations raise doubts about Fusobacterium necrophorum, a previously suspected causative agent of noma, as this species was not associated with noma lesions. Various oral pathogens were more abundant in noma lesions, notably Atopobium spp., Prevotella intermedia, Peptostreptococcus spp., Streptococcus pyogenes and Streptococcus anginosus. On the other hand, pathogens associated with periodontal diseases such as Aggregatibacter actinomycetemcomitans, Capnocytophaga spp., Porphyromonas spp. and Fusobacteriales were more abundant in healthy controls. Importantly, the overall loss of bacterial diversity observed in noma samples as well as its homology to that of ANG microbiota supports the hypothesis that ANG might be the immediate step preceding noma.
Chunyan Yin; Yanfeng Xiao; Wei Zhang; Erdi Xu; Weihua Liu; Xiaoqing Yi; Ming Chang
In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes exhibited a ≥ 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RT-PCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.
Preza, Dorita; Olsen, Ingar; Willumsen, Tiril; Boches, Susan K.; Cotton, Sean L.; Grinde, Bjørn; Paster, Bruce J.
Purpose The present study used a new 16S rRNA-based microarray with probes for over 300 bacterial species better define the bacterial profiles of healthy root surfaces and root caries (RC) in the elderly. Materials Supragingival plaque was collected from 20 healthy subjects (Controls) and from healthy and carious roots and carious dentin from 21 RC subjects (Patients). Results Collectively, 179 bacterial species and species groups were detected. A higher bacterial diversity was observed in the Controls as compared to Patients. Lactobacillus casei/paracasei/rhamnosus and Pseudoramibacter alactolyticus were notably associated with most root caries samples. Streptococcus mutans was detected more frequently in the infected dentin than in the other samples, but the difference was not significant. Actinomyces were found more frequently in Controls. Conclusion Actinomyces and S. mutans may play a limited role as pathogens of RC. The results from this study were in agreement with those of our previous study based on 16S rRNA gene sequencing with 72% of the species being detected with both methods. PMID:19039610
Yin, Chunyan; Xiao, Yanfeng; Zhang, Wei; Xu, Erdi; Liu, Weihua; Yi, Xiaoqing; Chang, Ming
In the present study, the human liposarcoma cell line SW872 was used to identify global changes in gene expression profiles occurring during adipogenesis. We further explored some of the genes expressed during the late phase of adipocyte differentiation. These genes may play a major role in promoting excessive proliferation and accumulation of lipid droplets, which contribute to the development of obesity. By using microarray-based technology, we examined differential gene expression in early differentiated adipocytes and late differentiated adipocytes. Validated genes exhibited a greater than or equal to 10-fold increase in the late phase of adipocyte differentiation by polymerase chain reaction (RT-PCR). Compared with undifferentiated preadipocytes, we found that 763 genes were increased in early differentiated adipocytes, and 667 genes were increased in later differentiated adipocytes. Furthermore, 21 genes were found being expressed 10-fold higher in the late phase of adipocyte differentiation. The results were in accordance with the RTPCR test, which validated 11 genes, namely, CIDEC, PID1, LYRM1, ADD1, PPAR?2, ANGPTL4, ADIPOQ, ACOX1, FIP1L1, MAP3K2 and PEX14. Most of these genes were found being expressed in the later phase of adipocyte differentiation involved in obesity-related diseases. The findings may help to better understand the mechanism of obesity and related diseases.
Huyghe, Antoine; François, Patrice; Mombelli, Andrea; Tangomo, Manuela; Girard, Myriam; Baratti-Mayer, Denise; Bolivar, Ignacio; Pittet, Didier; Schrenzel, Jacques
Noma (cancrum oris) is a gangrenous disease of unknown etiology affecting the maxillo-facial region of young children in extremely limited resource countries. In an attempt to better understand the microbiological events occurring during this disease, we used phylogenetic and low-density microarrays targeting the 16S rRNA gene to characterize the gingival flora of acute noma and acute necrotizing gingivitis (ANG) lesions, and compared them to healthy control subjects of the same geographical and social background. Our observations raise doubts about Fusobacterium necrophorum, a previously suspected causative agent of noma, as this species was not associated with noma lesions. Various oral pathogens were more abundant in noma lesions, notably Atopobium spp., Prevotella intermedia, Peptostreptococcus spp., Streptococcus pyogenes and Streptococcus anginosus. On the other hand, pathogens associated with periodontal diseases such as Aggregatibacter actinomycetemcomitans, Capnocytophaga spp., Porphyromonas spp. and Fusobacteriales were more abundant in healthy controls. Importantly, the overall loss of bacterial diversity observed in noma samples as well as its homology to that of ANG microbiota supports the hypothesis that ANG might be the immediate step preceding noma.
Richardson Andrea L
Full Text Available Abstract Background Na+/I- symporter (NIS-mediated iodide uptake allows radioiodine therapy for thyroid cancer. NIS is also expressed in breast tumors, raising potential for radionuclide therapy of breast cancer. However, NIS expression in most breast cancers is low and may not be sufficient for radionuclide therapy. We aimed to identify biomarkers associated with NIS expression such that mechanisms underlying NIS modulation in human breast tumors may be elucidated. Methods Published oligonucleotide microarray data within the National Center for Biotechnology Information Gene Expression Omnibus database were analyzed to identify gene expression tightly correlated with NIS mRNA level among human breast tumors. NIS immunostaining was performed in a tissue microarray composed of 28 human breast tumors which had corresponding oligonucleotide microarray data available for each tumor such that gene expression associated with cell surface NIS protein level could be identified. Results and Discussion NIS mRNA levels do not vary among breast tumors or when compared to normal breast tissues when detected by Affymetrix oligonucleotide microarray platforms. Cell surface NIS protein levels are much more variable than their corresponding NIS mRNA levels. Despite a limited number of breast tumors examined, our analysis identified cysteinyl-tRNA synthetase as a biomarker that is highly associated with cell surface NIS protein levels in the ER-positive breast cancer subtype. Conclusions Further investigation on genes associated with cell surface NIS protein levels within each breast cancer molecular subtype may lead to novel targets for selectively increasing NIS expression/function in a subset of breast cancers patients.
Deising Holger B
Full Text Available Abstract Background The toxigenic fungal plant pathogen Fusarium graminearum compromises wheat production worldwide. Azole fungicides play a prominent role in controlling this pathogen. Sequencing of its genome stimulated the development of high-throughput technologies to study mechanisms of coping with fungicide stress and adaptation to fungicides at a previously unprecedented precision. DNA-microarrays have been used to analyze genome-wide gene expression patterns and uncovered complex transcriptional responses. A recently developed one-color multiplex array format allowed flexible, effective, and parallel examinations of eight RNA samples. Results We took advantage of the 8 × 15 k Agilent format to design, evaluate, and apply a novel microarray covering the whole F. graminearum genome to analyze transcriptional responses to azole fungicide treatment. Comparative statistical analysis of expression profiles uncovered 1058 genes that were significantly differentially expressed after azole-treatment. Quantitative RT-PCR analysis for 31 selected genes indicated high conformity to results from the microarray hybridization. Among the 596 genes with significantly increased transcript levels, analyses using GeneOntology and FunCat annotations detected the ergosterol-biosynthesis pathway genes as the category most significantly responding, confirming the mode-of-action of azole fungicides. Cyp51A, which is one of the three F. graminearum paralogs of Cyp51 encoding the target of azoles, was the most consistently differentially expressed gene of the entire study. A molecular phylogeny analyzing the relationships of the three CYP51 proteins in the context of 38 fungal genomes belonging to the Pezizomycotina indicated that CYP51C (FGSG_11024 groups with a new clade of CYP51 proteins. The transcriptional profiles for genes encoding ABC transporters and transcription factors suggested several involved in mechanisms alleviating the impact of the fungicide
Yu-Juan Xiang; Zhi-Gang Yu; Ming-Ming Guo; Qin-Ye Fu; Zhong-Bing Ma; De-Zong Gao; Qiang Zhang; Yu-Yang Li; Liang Li; Lu Liu; Chun-Miao Ye
Objective: The aim of this study was to reveal the exact changes during the occurrence of breast cancer to explore significant new and promising genes or factors related to this disease. Methods: We compared the gene expression profiles of breast cancer tissues with its uninvolved normal breast tissues as controls using the cDNA microarray analysis in seven breast cancer patients. Further, one representative gene, named IFI30, was quanti-tatively analyzed by real-time PCR to confirm the result of the cDNA microarray analysis. Results: A total of 427 genes were identified with significantly differential expression, 221 genes were up-regulated and 206 genes were down-regulated. And the result of cDNA microarray analysis was validated by detection of IFI30 mRNA level changes by real-time PCR. Genes for cell proliferation, cell cycle, cell division, mitosis, apoptosis, and immune response were enriched in the up-regulated genes, while genes for cell adhesion, proteolysis, and transport were significantly enriched in the down-regulated genes in breast cancer tissues compared with normal breast tissues by a gene ontology analysis. Conclusion: Our present study revealed a range of differentially expressed genes between breast cancer tissues and normal breast tissues, and provide candidate genes for further study focusing on the pathogenesis and new biomarkers for breast cancer. Copyright © 2015, Chinese Medical Association Production. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Mammary glands undergo functional and metabolic changes during virgin,lactation and dry periods.A total of 122 genes were identified as differentially expressed,including 79 up-regulated and 43 down-regulated genes during lactation compared with virgin and dry periods.Gene ontology analysis showed the functional classification of the up-regulated genes in lactation,including transport,biosynthetic process,signal transduction,catalytic activity,immune system process,cell death,and positive regulation of the developmental process.Microarray data clarified molecular events in bovine mammary gland lactation.
Almeida, L M; Basu, U; Williams, J L; Moore, S S; Guan, L L
Bovine spongiform encephalopathy (BSE) is a fatal disorder in cattle characterized by progressive neurodegeneration of the central nervous system. We investigated the molecular mechanisms involved in neurodegeneration during prion infection through the identification of genes that are differentially expressed (DE) between experimentally infected and non-challenged cattle. Gene expression of caudal medulla from control and orally infected animals was compared by microarray analysis using 24,000 bovine oligonucleotides representing 16,846 different genes to identify DE genes associated with BSE disease. In total, 182 DE genes were identified between normal and BSE-infected tissues (>2.0-fold change, P bovine species.
Zhou, Jing; Wu, Yu; Lee, Sang-Kwon; Fan, Rong
High-content cellomic analysis is a powerful tool for rapid screening of cellular responses to extracellular cues and examination of intracellular signal transduction pathways at the single-cell level. In conjunction with microfluidics technology that provides unique advantages in sample processing and precise control of fluid delivery, it holds great potential to transform lab-on-a-chip systems for high-throughput cellular analysis. However, high-content imaging instruments are expensive, sophisticated, and not readily accessible. Herein, we report on a laser scanning cytometry approach that exploits a bench-top microarray scanner as an end-point reader to perform rapid and automated fluorescence imaging of cells cultured on a chip. Using high-content imaging analysis algorithms, we demonstrated multiplexed measurements of morphometric and proteomic parameters from all single cells. Our approach shows the improvement of both sensitivity and dynamic range by two orders of magnitude as compared to conventional epifluorescence microscopy. We applied this technology to high-throughput analysis of mesenchymal stem cells on an extracellular matrix protein array and characterization of heterotypic cell populations. This work demonstrates the feasibility of a laser microarray scanner for high-content cellomic analysis and opens up new opportunities to conduct informative cellular analysis and cell-based screening in the lab-on-a-chip systems.
Hsiao, Nai-Hua; Kirby, Ralph
DNA/DNA microarray hybridization was used to compare the genome content of Streptomyces avermitilis, Streptomyces cattleya, Streptomyces maritimus and Kitasatospora aureofaciens with that of Streptomyces coelicolor A3(2). The array data showed an about 93% agreement with the genome sequence data available for S. avermitilis and also showed a number of trends in the genome structure for Streptomyces and closely related Kitasatospora. A core central region was well conserved, which might be predicted from previous research and this was linked to a low degree of gene conservation in the terminal regions of the linear chromosome across all four species. Between these regions there are two areas of intermediate gene conservation by microarray analysis where gene synteny is still detectable in S. avermitilis. Nonetheless, a range of conserved genes could be identified within the terminal regions. Variation in the genes involved in differentiation, transcription, DNA replication, etc. provides interesting insights into which genes in these categories are generally conserved and which are not. The results also provide target priorities for possible gene knockouts in a group of bacteria with a very large numbers of genes with unknown functions compared to most bacterial species.
Park, Sungjin; Gildersleeve, Jeffrey C; Blixt, Klas Ola
-based technology has been widely employed for rapid analysis of the glycan binding properties of lectins and antibodies, the quantitative measurements of glycan-protein interactions, detection of cells and pathogens, identification of disease-related anti-glycan antibodies for diagnosis, and fast assessment...... of substrate specificities of glycosyltransferases. This review covers the construction of carbohydrate microarrays, detection methods of carbohydrate microarrays and their applications in biological and biomedical research.......In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray...
Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose
Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database 1 was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in
Full Text Available Abstract Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database 1 was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global
Siegmund, Kimberly D
Following the rapid development and adoption in DNA methylation microarray assays, we are now experiencing a growth in the number of statistical tools to analyze the resulting large-scale data sets. As is the case for other microarray applications, biases caused by technical issues are of concern. Some of these issues are old (e.g., two-color dye bias and probe- and array-specific effects), while others are new (e.g., fragment length bias and bisulfite conversion efficiency). Here, I highlight characteristics of DNA methylation that suggest standard statistical tools developed for other data types may not be directly suitable. I then describe the microarray technologies most commonly in use, along with the methods used for preprocessing and obtaining a summary measure. I finish with a section describing downstream analyses of the data, focusing on methods that model percentage DNA methylation as the outcome, and methods for integrating DNA methylation with gene expression or genotype data.
Full Text Available Abstract Background High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. Results We have proposed a novel approach, based on a piece-wise function – to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. Conclusion The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value -13. The prototype R code has been made available as supplementary material [see Additional file 1]. Additional file 1 gsam_prototypercode.zip. File archive comprising of prototype R code for gSAM implementation including readme and examples. Click here for file
Ghosh, Srinka; Hirsch, Heather A; Sekinger, Edward A; Kapranov, Philipp; Struhl, Kevin; Gingeras, Thomas R
High density oligonucleotide tiling arrays are an effective and powerful platform for conducting unbiased genome-wide studies. The ab initio probe selection method employed in tiling arrays is unbiased, and thus ensures consistent sampling across coding and non-coding regions of the genome. These arrays are being increasingly used to study the associated processes of transcription, transcription factor binding, chromatin structure and their association. Studies of differential expression and/or regulation provide critical insight into the mechanics of transcription and regulation that occurs during the developmental program of a cell. The time-course experiment, which comprises an in-vivo system and the proposed analyses, is used to determine if annotated and un-annotated portions of genome manifest coordinated differential response to the induced developmental program. We have proposed a novel approach, based on a piece-wise function - to analyze genome-wide differential response. This enables segmentation of the response based on protein-coding and non-coding regions; for genes the methodology also partitions differential response with a 5' versus 3' versus intra-genic bias. The algorithm built upon the framework of Significance Analysis of Microarrays, uses a generalized logic to define regions/patterns of coordinated differential change. By not adhering to the gene-centric paradigm, discordant differential expression patterns between exons and introns have been identified at a FDR of less than 12 percent. A co-localization of differential binding between RNA Polymerase II and tetra-acetylated histone has been quantified at a p-value < 0.003; it is most significant at the 5' end of genes, at a p-value < 10-13. The prototype R code has been made available as supplementary material [see Additional file 1].
Microarray analysis of genes affected by salt stress in tomato. ... African Journal of Environmental Science and Technology ... key enzyme genes in the metabolic pathways of carbohydrates, amino acids, and fatty acids, were also affected by ...
GAO Jian; KANG Jian
In order to explore the bioleaching mechanism and improve the bioleaching efficiency,the microbial community in the bioleaching solution was compared with that on the surface of minerals based on the microarray analysis.Meanwhile,the elements composition in the bioleaching solution was analyzed using the ICP-AES method.Results showed that there was a high concentration of S and Cu in the leaching solution which up to 2380 mg/L and 1378 mg/L,respectively,after continuously bioleaching of copper-ore concentrate for 30 days by a mixed culture associated with 12 species of bioleaching microorganisms.Based on the data of microarray,the total of cell number in the surface of minerals was far higher than that in the bioleaching solution.Furthermore,the dominant communities on the surface of minerals,such as Acidithiobacillus ferrooxidans,Acidithiobacillus thiooxidans and Acidithiobacillus caldus,were similar to that in the bioleaching solution.However,the relative level of some bacteria,such as Sulfobacillus acidophilus and Sulfobacillus thermosulfidooxidans,showed great discrepancy with lower presence in the bioleaching solution with respect to the mineral surface.
Belder, Nevin; Coskun, Öznur; Doganay Erdogan, Beyza; Ilk, Ozlem; Savas, Berna; Ensari, Arzu; Özdağ, Hilal
Genome-wide gene expression profiling analysis of FFPE tissue samples is indispensable for cancer research and provides the opportunity to evaluate links between molecular and clinical information, however, working with FFPE samples is challenging due to extensive cross-linking, fragmentation and limited quantities of nucleic acid. Thus, processing of FFPE tissue samples from RNA extraction to microarray analysis still needs optimization. In this study, a modified deparaffinization protocol was conducted prior to RNA isolation. Trizol, Qiagen RNeasy FFPE and Arcturus PicoPure RNA Isolation kits were used in parallel to compare their impact on RNA isolation. We also evaluated the effect of two different cRNA/cDNA preparation and labeling protocols with two different array platforms (Affymetrix Human Genome U133 Plus 2.0 and U133_X3P) on the percentage of present calls. Our optimization study shows that the Qiagen RNeasy FFPE kit with modified deparaffinization step gives better results (RNA quantity and quality) than the other two isolation kits. The Ribo-SPIA protocol gave a significantly higher percentage of present calls than the 3' IVT cDNA amplification and labeling system. However, no significant differences were found between the two array platforms. Our study paves the way for future high-throughput transcriptional analysis by optimizing FFPE tissue sample processing from RNA isolation to microarray analysis. Copyright © 2016 Elsevier GmbH. All rights reserved.
Asunción Salmeán, Armando
to concept proof that is possible to use the Comprehensive Microarray Polymer Profiling (CoMPP) as a tool for other extracellular matrixes such as marine animals and not only for algal or plant cell walls. Thus, we discovered fucoidan and cellulose epitopes in several tissues of various marine animals from...
Cheng-Bo Han; Xiao-Yun Mao; Yan Xin; Shao-Cheng Wang; Jia-Ming Ma; Yu-Jie Zhao
AIM: To design a novel method to rapidly detect the quantitative alteration of mtRNA in patients with tumors.METHODS: Oligo 6.22 and Primer Premier 5.0 bio-soft were used to design 15 pairs of primers of mtRNA cDNA probes in light of the functional and structural property of mtDNA, and then RT-PCR amplification was used to produce 15 probes of mtRNA from one normal gastric mucosal tissue. Total RNA extracted from 9 gastric cancers and corresponding normal gastric mucosal tissues was reverse transcribed into cDNA labeled with fluorescein. The spotted mtDNA microarrays were made and hybridized. Finally,the microarrays were scanned with a GeneTACTM laser scanner to get the hybridized results. Northern blot was used to confirm the microarray results.RESULTS: The hybridized spots were distinct with clear and consistent backgrounds. After data was standardized according to the housekeeping genes, the results showed that the expression levels of some mitochondrial genes in gastric carcinoma were different from those in the corresponding non-cancerous regions.CONCLUSION: The mtDNA expression microarray can rapidly, massively and exactly detect the quantity of mtRNA in tissues and cells. In addition, the whole expressive information of mtRNA from a tumor patient on just one slide can be obtained using this method, providing an effective method to investigate the relationship between mtDNA expression and tumorigenesis.
Holbrook Michael R
Full Text Available Abstract Background All infectious disease oriented clinical diagnostic assays in use today focus on detecting the presence of a single, well defined target agent or a set of agents. In recent years, microarray-based diagnostics have been developed that greatly facilitate the highly parallel detection of multiple microbes that may be present in a given clinical specimen. While several algorithms have been described for interpretation of diagnostic microarrays, none of the existing approaches is capable of incorporating training data generated from positive control samples to improve performance. Results To specifically address this issue we have developed a novel interpretive algorithm, VIPR (Viral Identification using a PRobabilistic algorithm, which uses Bayesian inference to capitalize on empirical training data to optimize detection sensitivity. To illustrate this approach, we have focused on the detection of viruses that cause hemorrhagic fever (HF using a custom HF-virus microarray. VIPR was used to analyze 110 empirical microarray hybridizations generated from 33 distinct virus species. An accuracy of 94% was achieved as measured by leave-one-out cross validation. Conclusions VIPR outperformed previously described algorithms for this dataset. The VIPR algorithm has potential to be broadly applicable to clinical diagnostic settings, wherein positive controls are typically readily available for generation of training data.
Full Text Available Abstract Background DNA microarray technology allows the analysis of genome structure and dynamics at genome-wide scale. Expression microarrays (EMA contain probes for annotated open reading frames (ORF and are widely used for the analysis of differential gene expression. By contrast, tiling microarrays (TMA have a much higher probe density and provide unbiased genome-wide coverage. The purpose of this study was to develop a protocol to exploit the high resolution of TMAs for quantitative measurement of DNA strand-specific differential expression of annotated and non-annotated transcripts. Results We extensively filtered probes present in Affymetrix Genechip Yeast Genome 2.0 expression and GeneChip S. pombe 1.0FR tiling microarrays to generate custom Chip Description Files (CDF in order to compare their efficiency. We experimentally tested the potential of our approach by measuring the differential expression of 4904 genes in the yeast Schizosaccharomyces pombe growing under conditions of oxidative stress. The results showed a Pearson correlation coefficient of 0.943 between both platforms, indicating that TMAs are as reliable as EMAs for quantitative expression analysis. A significant advantage of TMAs over EMAs is the possibility of detecting non-annotated transcripts generated only under specific physiological conditions. To take full advantage of this property, we have used a target-labelling protocol that preserves the original polarity of the transcripts and, therefore, allows the strand-specific differential expression of non-annotated transcripts to be determined. By using a segmentation algorithm prior to generating the corresponding custom CDFs, we identified and quantitatively measured the expression of 510 transcripts longer than 180 nucleotides and not overlapping previously annotated ORFs that were differentially expressed at least 2-fold under oxidative stress. Conclusions We show that the information derived from TMA
Full Text Available Microarray-based comparative genomic hybridization (array CGH is a newly emerged molecular cytogenetic technique for rapid evaluation of the entire genome with sub-megabase resolution. It allows for the comprehensive investigation of thousands and millions of genomic loci at once and therefore enables the efficient detection of DNA copy number variations (a.k.a, cryptic genomic imbalances. The development and the clinical application of array CGH have revolutionized the diagnostic process in patients and has provided a clue to many unidentified or unexplained diseases which are suspected to have a genetic cause. In this paper, we present three clinical cases in both prenatal and postnatal settings. Among all, array CGH played a major discovery role to reveal the cryptic and/or complex nature of chromosome arrangements. By identifying the genetic causes responsible for the clinical observation in patients, array CGH has provided accurate diagnosis and appropriate clinical management in a timely and efficient manner.
Sumantran, Venil N; Mishra, Pratik; Sudhakar, N
A new hallmark of cancer involves acquisition of a lipogenic phenotype which promotes tumorigenesis. Little is known about lipid metabolism in melanomas. Therefore, we used BRB (Biometrics Research Branch) class comparison tool with multivariate analysis to identify differentially expressed genes in human cutaneous melanomas, compared with benign nevi and normal skin derived from the microarray dataset (GDS1375). The methods were validated by identifying known melanoma biomarkers (CITED1, FGFR2, PTPRF, LICAM, SPP1 and PHACTR1) in our results. Eighteen genes regulating metabolism of fatty acids, lipid second messengers and gangliosides were 2-9 fold upregulated in melanomas of GDS-1375. Out of the 18 genes, 13 were confirmed by KEGG pathway analysis and 10 were also significantly upregulated in human melanoma cell lines of NCI-60 Cell Miner database. Results showed that melanomas upregulated PPARGC1A transcription factor and its target genes regulating synthesis of fatty acids (SCD) and complex lipids (FABP3 and ACSL3). Melanoma also upregulated genes which prevented lipotoxicity (CPT2 and ACOT7) and regulated lipid second messengers, such as phosphatidic acid (AGPAT-4, PLD3) and inositol triphosphate (ITPKB, ITPR3). Genes for synthesis of pro-tumorigenic GM3 and GD3 gangliosides (UGCG, HEXA, ST3GAL5 and ST8SIA1) were also upregulated in melanoma. Overall, the microarray analysis of GDS-1375 dataset indicated that melanomas can become lipogenic by upregulating genes, leading to increase in fatty acid metabolism, metabolism of specific lipid second messengers, and ganglioside synthesis.
Parry, R M; Jones, W; Stokes, T H; Phan, J H; Moffitt, R A; Fang, H; Shi, L; Oberthuer, A; Fischer, M; Tong, W; Wang, M D
In the clinical application of genomic data analysis and modeling, a number of factors contribute to the performance of disease classification and clinical outcome prediction. This study focuses on the k-nearest neighbor (KNN) modeling strategy and its clinical use. Although KNN is simple and clinically appealing, large performance variations were found among experienced data analysis teams in the MicroArray Quality Control Phase II (MAQC-II) project. For clinical end points and controls from breast cancer, neuroblastoma and multiple myeloma, we systematically generated 463,320 KNN models by varying feature ranking method, number of features, distance metric, number of neighbors, vote weighting and decision threshold. We identified factors that contribute to the MAQC-II project performance variation, and validated a KNN data analysis protocol using a newly generated clinical data set with 478 neuroblastoma patients. We interpreted the biological and practical significance of the derived KNN models, and compared their performance with existing clinical factors.
Full Text Available Abstract Background In individually dye-balanced microarray designs, each biological sample is hybridized on two different slides, once with Cy3 and once with Cy5. While this strategy ensures an automatic correction of the gene-specific labelling bias, it also induces dependencies between log-ratio measurements that must be taken into account in the statistical analysis. Results We present two original statistical procedures for the statistical analysis of individually balanced designs. These procedures are compared with the usual ML and REML mixed model procedures proposed in most statistical toolboxes, on both simulated and real data. Conclusion The UP procedure we propose as an alternative to usual mixed model procedures is more efficient and significantly faster to compute. This result provides some useful guidelines for the analysis of complex designs.
Baboota, Ritesh K; Sarma, Siddhartha M; Boparai, Ravneet K; Kondepudi, Kanthi Kiran; Mantri, Shrikant; Bishnoi, Mahendra
Two types of adipose tissues, white (WAT) and brown (BAT) are found in mammals. Increasingly novel strategies are being proposed for the treatment of obesity and its associated complications by altering amount and/or activity of BAT using mouse models. The present study was designed to: (a) investigate the differential expression of genes in LACA mice subcutaneous WAT (sWAT) and BAT using mouse DNA microarray, (b) to compare mouse differential gene expression with previously published human data; to understand any inter- species differences between the two and (c) to make a comparative assessment with C57BL/6 mouse strain. In mouse microarray studies, over 7003, 1176 and 401 probe sets showed more than two-fold, five-fold and ten-fold change respectively in differential expression between murine BAT and WAT. Microarray data was validated using quantitative RT-PCR of key genes showing high expression in BAT (Fabp3, Ucp1, Slc27a1) and sWAT (Ms4a1, H2-Ob, Bank1) or showing relatively low expression in BAT (Pgk1, Cox6b1) and sWAT (Slc20a1, Cd74). Multi-omic pathway analysis was employed to understand possible links between the organisms. When murine two fold data was compared with published human BAT and sWAT data, 90 genes showed parallel differential expression in both mouse and human. Out of these 90 genes, 46 showed same pattern of differential expression whereas the pattern was opposite for the remaining 44 genes. Based on our microarray results and its comparison with human data, we were able to identify genes (targets) (a) which can be studied in mouse model systems to extrapolate results to human (b) where caution should be exercised before extrapolation of murine data to human. Our study provides evidence for inter species (mouse vs human) differences in differential gene expression between sWAT and BAT. Critical understanding of this data may help in development of novel ways to engineer one form of adipose tissue to another using murine model with focus on
Full Text Available Abstract Background Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management. Results EMAAS (Extensible MicroArray Analysis System is a multi-user rich internet application (RIA providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms. Conclusion EMAAS enables users to track and perform microarray data
Lüke, Claudia; Bodrossy, Levente; Lupotto, Elisabetta; Frenzel, Peter
Rice plants play a key role in regulating methane emissions from paddy fields by affecting both underlying processes: methane production and oxidation. Specific differences were reported for methane oxidation rates; however, studies on the bacterial communities involved are rare. Here, we analysed the methanotrophic community on the roots of 18 different rice cultivars by pmoA-based terminal restriction fragment length polymorphism (T-RFLP) and microarray analysis. Both techniques showed comparable and consistent results revealing a high diversity dominated by type II and type Ib methanotrophs. pmoA microarrays have been successfully used to study methane-oxidizing bacteria in various environments. However, the microarray's full potential resolving community structure has not been exploited yet. Here, we provide an example on how to include this information into multivariate statistics. The analysis revealed a rice cultivar effect on the methanotroph community composition that could be affiliated to the plant genotype. This effect became only significant by including the specific phylogenetic resolution provided by the microarray into the statistical analysis.
Yang, Jianji; Cohen, Aaron; Hersh, William
Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS) is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html.
Turbitt, E; Halliday, J L; Amor, D J; Metcalfe, S A
Chromosomal microarray (CMA) testing is now performed frequently in paediatric care. Although CMAs improve diagnostic yields, they increase detection of variants of unknown and uncertain clinical significance (VUS). Understanding parents', paediatricians' and genetic health professionals' (GHPs) views regarding variant disclosure may reduce the potential for communication of unwanted information. A questionnaire was designed to compare disclosure preferences of these three groups in Australia. One hundred and forty-seven parents, 159 paediatricians and 69 GHPs hold similar views with at least 89% of respondents certainly or probably favouring disclosure of all categories of variants. However, some differences were observed between health care providers (HCPs: paediatricians and GHPs) and parents, who were less sure of their disclosure preferences. There was consensus among respondent groups that knowledge of a variant of certain clinical significance would provide more practical and emotional utility compared to VUS. Compared to HCPs, parents placed more emphasis on using knowledge of a VUS when considering future pregnancies (p exome/genome sequencing is integrated into clinical practice, the potential for differing views of parents and HCPs should be considered when developing guidelines for result disclosure.
Polen, Tino; Wendisch, Volker F
DNA microarray technology has become an important research tool for biotechnology and microbiology. It is now possible to characterize genetic diversity and gene expression in a genomewide manner. DNA microarrays have been applied extensively to study the biology of many bacteria including Escherichia coli, but only recently have they been developed for the Gram-positive Corynebacterium glutamicum. Both bacteria are widely used for biotechnological amino acid production. In this article, in addition to the design and generation of microarrays as well as their use in hybridization experiments and subsequent data analysis, we describe recent applications of DNA microarray technology regarding amino acid production in C. glutamicum and E. coli. We also discuss the impact of functional genomics studies on fundamental as well as applied aspects of amino acid production with C. glutamicum and E. coli.
Yu, Lu; Guo, Na; Yang, Yi; Wu, Xiuping; Meng, Rizeng; Fan, Junwen; Ge, Fa; Wang, Xuelin; Liu, Jingbo; Deng, Xuming
p-Anisaldehyde (4-methoxybenzaldehyde), an extract from Pimpinella anisum L. seeds, is a potential novel preservative. To reveal the possible action mechanism of p-anisaldehyde against microorganisms, yeast-based commercial oligonucleotide microarrays were used to analyze the genome-wide transcriptional changes in response to p-anisaldehyde. Quantitative real-time RT-PCR was performed for selected genes to verify the microarray results. We interpreted our microarray data with the clustering tool, T-profiler. Analysis of microarray data revealed that p-anisaldehyde induced the expression of genes related to sulphur assimilation, aromatic aldehydes metabolism, and secondary metabolism, which demonstrated that the addition of p-anisaldehyde may influence the normal metabolism of aromatic aldehydes. This genome-wide transcriptomics approach revealed first insights into the response of Saccharomyces cerevisiae (S. cerevisiae) to p-anisaldehyde challenge.
Botao Zhao; Shuo Ding; Wei Li; Youxin Jin
MicroRNA (miRNA) microarrays have been successfully used for profiling miRNA expression in many physiological processes such as development, differentiation, oncogenesis,and other disease processes. Detecting miRNA by miRNA microarray is actually based on nucleic acid hybridization between target molecules and their corresponding complementary probes. Due to the small size and high degree of similarity among miRNA sequences, the hybridization condition must be carefully optimized to get specific and reliable signals. Previously, we reported a microarray platform to detect miRNA expression. In this study, we evaluated the sensitivity and specificity of our microarray platform. After systematic analysis, we determined an optimized hybridization condition with high sensitivity and specificity for miRNA detection. Our results would be helpful for other hybridization-based miRNA detection methods, such as northern blot and nuclease protection assay.
Torata, Nobuhiro; Ohuchida, Kenoki; Akagawa, Shin; Cui, Lin; Kozono, Shingo; Mizumoto, Kazuhiro; Aishima, Shinichi; Oda, Yoshinao; Tanaka, Masao
Frozen human tissues are necessary for research purposes, but tissue banking methods have not changed for more than a decade. Many institutions use cryovial tubes or plastic molds with an optimal cutting temperature compound. However, these methods are associated with several problems, such as samples sticking to one another and the need for a larger storing space. We established an efficient tissue freezing and storing procedure ("tissue tablet method") applicable to both molecular analysis and frozen tissue microarray. Tissue samples were chopped into tiny fragments and embedded into tablet-shaped frozen optimal cutting temperature compound using our original tissue-freezing plate. These tablets can be sectioned and stored in cryovial tubes. We compared the tissue quality of tablet-shaped samples with that of conventional optimal cutting temperature blocks and found no significant difference between them. Tissue microarray is a key method to utilize tissue-banking specimens. However, most tissue microarrays require the coring out of cylindrically shaped tissues from formalin-fixed, paraffin-embedded tissue blocks. Antigenic changes and mRNA degradation are frequently observed with formalin-fixed, paraffin-embedded samples. Therefore, we have applied tablet-shaped samples to construct frozen tissue microarrays with our original mounting base. Constructed tissue microarray sections showed good morphology without obvious artifact and good immunohistochemistry and in situ hybridization results. These results suggest that the quality of arrayed samples was sufficiently appropriate for research purposes. In conclusion, the tissue tablet method and frozen tissue microarray procedure can save time, provides easy tissue handling and processing, and satisfies the demands of research methodologies and tissue banking. © 2013.
Vallon-Christersson, Johan; Nordborg, Nicklas; Svensson, Martin; Häkkinen, Jari
Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.
Full Text Available Abstract Background Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. Results The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. Conclusion BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.
Kostić, Tanja; Stessl, Beatrix; Wagner, Martin; Sessitsch, Angela
Microbial diagnostic microarrays are tools for simultaneous detection and identification of microorganisms in food, clinical, and environmental samples. In comparison to classic methods, microarray-based systems have the potential for high throughput, parallelism, and miniaturization. High specificity and high sensitivity of detection have been demonstrated. A microbial diagnostic microarray for the detection of the most relevant bacterial food- and waterborne pathogens and indicator organisms was developed and thoroughly validated. The microarray platform based on sequence-specific end labeling of oligonucleotides and the phylogenetically robust gyrB marker gene allowed a highly specific (resolution on genus and/or species level) and sensitive (0.1% relative and 10(4) CFU absolute sensitivity) detection of the target pathogens. In initial challenge studies of the applicability of microarray-based food analysis, we obtained results demonstrating the questionable specificity of standardized culture-dependent microbiological detection methods. Taking into consideration the importance of reliable food safety assessment methods, comprehensive performance assessment is essential. Results demonstrate the potential of this new pathogen diagnostic microarray to evaluate culture-based standard methods in microbiological food analysis.
Full Text Available Demand for high quality gene expression data has driven the development of revolutionary microarray technologies. The quality of the data is affected by the performance of the microarray platform as well as how the nucleic acid targets are prepared. The most common method for target nucleic acid preparation includes in vitro transcription amplification of the sample RNA. Although this method requires a small amount of starting material and is reported to have high reproducibility, there are also technical disadvantages such as amplification bias and the long, laborious protocol. Using RNA derived from human brain, breast and colon, we demonstrate that a non-amplification method, which was previously shown to be inferior, could be transformed to a highly quantitative method with a dynamic range of five orders of magnitude. Furthermore, the correlation coefficient calculated by comparing microarray assays using non-amplified samples with qRT-PCR assays was approximately 0.9, a value much higher than when samples were prepared using amplification methods. Our results were also compared with data from various microarray platforms studied in the MicroArray Quality Control (MAQC project. In combination with micro-columnar 3D-Gene™ microarray, this non-amplification method is applicable to a variety of genetic analyses, including biomarker screening and diagnostic tests for cancer.
Full Text Available Abstract Background Several preprocessing methods are available for the analysis of Affymetrix Genechips arrays. The most popular algorithms analyze the measured fluorescence intensities with statistical methods. Here we focus on a novel algorithm, AffyILM, available from Bioconductor, which relies on inputs from hybridization thermodynamics and uses an extended Langmuir isotherm model to compute transcript concentrations. These concentrations are then employed in the statistical analysis. We compared the performance of AffyILM and other traditional methods both in the old and in the newest generation of GeneChips. Results Tissue mixture and Latin Square datasets (provided by Affymetrix were used to assess the performances of the differential expression analysis depending on the preprocessing strategy. A correlation analysis conducted on the tissue mixture data reveals that the median-polish algorithm allows to best summarize AffyILM concentrations computed at the probe-level. Those correlation results are equivalent to the best correlations observed using popular preprocessing methods relying on intensity values. The performances of each tested preprocessing algorithm were quantified using the Latin Square HG-U133A dataset, thanks to the comparison of differential analysis results with the list of spiked genes. The figures of merit generated illustrates that the performances associated to AffyILM(medianpolish, inferred from the present statistical analysis, are comparable to the best performing strategies previously reported. Conclusions Converting probe intensities to estimates of target concentrations prior to the statistical analysis, AffyILM(medianpolish is one of the best performing strategy currently available. Using hybridization theory, probe-level estimates of target concentrations should be identically distributed. In the future, a probe-level multivariate analysis of the concentrations should be compared to the univariate analysis of
Full Text Available Abstract Background In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases. Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets. Results We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes. Conclusions Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.
Podpečan, Vid; Lavrač, Nada; Mozetič, Igor; Novak, Petra Kralj; Trajkovski, Igor; Langohr, Laura; Kulovesi, Kimmo; Toivonen, Hannu; Petek, Marko; Motaln, Helena; Gruden, Kristina
In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility of current bioinformatics workflow environments can be significantly increased by offering advanced data mining services as workflow components. Such services can support, for instance, knowledge discovery from diverse distributed data and knowledge sources (such as GO, KEGG, PubMed, and experimental databases). Specifically, cutting-edge data analysis approaches, such as semantic data mining, link discovery, and visualization, have not yet been made available to researchers investigating complex biological datasets. We present a new methodology, SegMine, for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment, Orange4WS, with integrated support for web services in which the SegMine methodology is implemented. The SegMine methodology consists of two main steps. First, the semantic subgroup discovery algorithm is used to construct elaborate rules that identify enriched gene sets. Then, a link discovery service is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that could improve understanding of the underlying mechanisms of senescence and identification of candidate marker genes. Compared to the available data analysis systems, SegMine offers improved hypothesis generation and data interpretation for bioinformatics in an easy-to-use integrated workflow environment.
Full Text Available We have recently identified lymphatic endothelial cells (LECs to form two morphologically different populations, exhibiting significantly different surface protein expression levels of podoplanin, a major surface marker for this cell type. In vitro shockwave treatment (IVSWT of LECs resulted in enrichment of the podoplaninhigh cell population and was accompanied by markedly increased cell proliferation, as well as 2D and 3D migration. Gene expression profiles of these distinct populations were established using Affymetrix microarray analyses. Here we provide additional details about our dataset (NCBI GEO accession number GSE62510 and describe how we analyzed the data to identify differently expressed genes in these two LEC populations.
Chen, Chaang-Ray; Shu, Wun-Yi; Tsai, Min-Lung; Cheng, Wei-Chung; Hsu, Ian C
A number of recent studies have shown that loop-design is more efficient than reference control design. Data analysis for loop-design microarray experiments is commonly undertaken using linear models and statistical tests. These techniques require specialized knowledge in statistical programming. However, limited loop-design web-based tools are available. We have developed the THEME (Tsing Hua Engine of Microarray Experiment) that exploits all necessary data analysis tools for loop-design microarray studies. THEME allows users to construct linear models and to apply multiple user-defined statistical tests of hypotheses for detection of DEG (differentially expressed genes). Users can modify entries of design matrix for experimental design as well as that of contrast matrix for statistical tests of hypotheses. The output of multiple user-defined statistical tests of hypotheses, DEG lists, can be cross-validated. The web platform provides data assessment and visualization tools that significantly assist users when evaluating the performance of microarray experimental procedures. THEME is also a MIAME (Minimal Information About a Microarray Experiment) compliant system, which enables users to export formatted files for GEO (Gene Expression Omnibus) submission. THEME offers comprehensive web services to biologists for data analysis of loop-design microarray experiments. This web-based resource is especially useful for core facility service as well as collaboration projects when researchers are not at the same site. Data analysis procedures, starting from uploading raw data files to retrieving DEG lists, can be flexibly operated with natural workflows. These features make THEME a reliable and powerful on-line system for data analysis of loop-design microarrays. The THEME server is available at http://metadb.bmes.nthu.edu.tw/theme/.
Chen Wei; Li Xu; Wang Xiang
Objective To examine the differentially expressed invasion-related genes in two anchorage-independent uterine cervical carcinoma cell lines derived from the same patient using a cDNA array. Methods Two human uterine cervical carcinoma subclonal cell lines CS03 and CS07 derived from a single donor line CS1213 were established by limited dilution procedure. The two cDNA samples retro-transcribed from total RNA derived from CS03 and CS07 cells were screened by a cDNA microarray carrying 234 human cell-cycle related genes and 1011 human signal transduction and membrane receptor -associated genes, scanned with a ScanArray 3000 laser scanner. Results The cDNA microarray analysis showed that 12 genes in CS03 were up-regulated compared to CS07, and 24 genes in CS07 were up-regulated. The function of a number of differentially expressed genes was consistently associated with cell-cycle, cell proliferation, migration, apoptosis, signal transduction and tumor metastasis, including p34cdc2, TSC22, plasminogen activator inhibitor I (PAI-1)and desmosome associated protein(Pinin). Conclusion Multiple genes are differentially expressed in uterine cervical carcinoma cell lines even came from the same patient. It is suggested that these genes are involved in the different phenotypic characteristics and development of cervical carcinoma.
Fabi João Paulo
Full Text Available Abstract Background Papaya (Carica papaya L. is a commercially important crop that produces climacteric fruits with a soft and sweet pulp that contain a wide range of health promoting phytochemicals. Despite its importance, little is known about transcriptional modifications during papaya fruit ripening and their control. In this study we report the analysis of ripe papaya transcriptome by using a cross-species (XSpecies microarray technique based on the phylogenetic proximity between papaya and Arabidopsis thaliana. Results Papaya transcriptome analyses resulted in the identification of 414 ripening-related genes with some having their expression validated by qPCR. The transcription profile was compared with that from ripening tomato and grape. There were many similarities between papaya and tomato especially with respect to the expression of genes encoding proteins involved in primary metabolism, regulation of transcription, biotic and abiotic stress and cell wall metabolism. XSpecies microarray data indicated that transcription factors (TFs of the MADS-box, NAC and AP2/ERF gene families were involved in the control of papaya ripening and revealed that cell wall-related gene expression in papaya had similarities to the expression profiles seen in Arabidopsis during hypocotyl development. Conclusion The cross-species array experiment identified a ripening-related set of genes in papaya allowing the comparison of transcription control between papaya and other fruit bearing taxa during the ripening process.
E. V. Thomas
Full Text Available Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.
Ma, K; Lian, Y; Zhou, S; Hu, R; Xiong, Y; Ting, P; Xiong, Y; Li, X; Wang, X
To detect the candidate genes for preeclampsia (PE). The gene expression profiles in preeclamptic and normal placental tissues were analyzed using cDNA microarray approach and the altered expression of important genes were further confirmed by real-time RT-PCR (reverse transcription polymerase chain reaction) technique. Total RNA was extracted from placental tissues of three cases with severe PE and from three cases with normal pregnancy. After scanning, differentially expressed genes were detected by software. In two experiments (the fluorescent labels were exchanged), a total of 111 differentially expressed genes were detected. In placental tissue ofpreeclamptic pregnancy, 68 differentially expressed genes were up-regulated, and 44 differentially expressed genes were down-regulated. Of these genes, 16 highly differentially expressed genes were confirmed by real-time fluorescent quantitative RT-PCR, and the result showed that the ratio of gene expression differences was comparable to that detected by cDNA microarray. The results of bioinformatic analysis showed that encoding products of differentially expressed genes were correlated to infiltration of placenta trophoblastic cells, immunomodulatory factors, pregnancy-associated plasma protein, signal transduction pathway, and cell adhesion. Further studies on the biological function and regulating mechanism of these genes will provide new clues for better understanding of etiology and pathogenesis of PE.
Full Text Available The biological function of human ovaries declines with age. To identify the potential molecular changes in ovarian aging, we performed genome-wide gene expression analysis by microarray of ovaries from young, middle-aged, and old rhesus monkeys. Microarray data was validated by quantitative real-time PCR. Results showed that a total of 503 (60 upregulated, 443 downregulated and 84 (downregulated genes were differentially expressed in old ovaries compared to young and middle-aged groups, respectively. No difference in gene expression was found between middle-aged and young groups. Differentially expressed genes were mainly enriched in cell and organelle, cellular and physiological process, binding, and catalytic activity. These genes were primarily associated with KEGG pathways of cell cycle, DNA replication and repair, oocyte meiosis and maturation, MAPK, TGF-beta, and p53 signaling pathway. Genes upregulated were involved in aging, defense response, oxidation reduction, and negative regulation of cellular process; genes downregulated have functions in reproduction, cell cycle, DNA and RNA process, macromolecular complex assembly, and positive regulation of macromolecule metabolic process. These findings show that monkey ovary undergoes substantial change in global transcription with age. Gene expression profiles are useful in understanding the mechanisms underlying ovarian aging and age-associated infertility in primates.
Jonathan P Butchar
Full Text Available Francisella tularensis is a gram-negative facultative bacterium that causes the disease tularemia, even upon exposure to low numbers of bacteria. One critical characteristic of Francisella is its ability to dampen or subvert the host immune response. In order to help understand the mechanisms by which this occurs, we performed Affymetrix microarray analysis on transcripts from blood monocytes infected with the virulent Type A Schu S4 strain. Results showed that expression of several host response genes were reduced such as those associated with interferon signaling, Toll-like receptor signaling, autophagy and phagocytosis. When compared to microarrays from monocytes infected with the less virulent F. tularensis subsp. novicida, we found qualitative differences and also a general pattern of quantitatively reduced pro-inflammatory signaling pathway genes in the Schu S4 strain. Notably, the PI3K/Akt1 pathway appeared specifically down-regulated following Schu S4 infection and a concomitantly lower cytokine response was observed. This study identifies several new factors potentially important in host cell subversion by the virulent Type A F. tularensis that may serve as novel targets for drug discovery.
Makabe, Yasushi; Sasaki, Hodaka; Mori, Gentaro; Sekine, Hideshi; Yoshinari, Masao; Yajima, Yasutomo
Implant placement entails disruption of the epithelial continuity, which can lead to various complications. Therefore, the area of mucosal penetration is of particular interest clinically. The goal of the present study was to compare gene expression in peri-implant soft tissue (PIST) with that in oral mucosal tissue (OMT) using microarray analysis, and to investigate which genes were specifically expressed in PIST. The bilateral upper first molars were extracted from 4-week-old rats and titanium alloy implants placed only in the left-side extraction sockets. Four weeks after surgery, samples were harvested from the left-side PIST and right-side OMT and total RNA samples isolated. Microarray analysis was used to compare gene expression in PIST and OMT, which was then confirmed using quantitative real-time polymerase chain reaction. Immunohistochemical staining was also performed to confirm protein level expression. The number of genes expressed with more than a twofold change in PIST compared with OMT was 1,102, of which 750 genes were upregulated and 352 genes were downregulated. The messenger RNA (mRNA) expression of three selected genes-Ceacam1, Ifitm1, and MUC4-were more significantly expressed in PIST than in OMT(P microarray analysis showed that, because of implant placement, 750 genes were upregulated in PIST compared with OMT. CEACAM1, IFITM1, and MUC4 were specifically upregulated in PIST.
Hsiao, Nai-hua; Kirby, Ralph
DNA/DNA microarray hybridization was used to compare the genome content of Streptomyces avermitilis, Streptomyces cattleya, Streptomyces maritimus and Kitasatospora aureofaciens with that of Streptomyces coelicolor A3(2). The array data showed an about 93% agreement with the genome sequence data ava
Barth Jeremy L
Full Text Available Abstract Background Numerous microarray analysis programs have been created through the efforts of Open Source software development projects. Providing browser-based interfaces that allow these programs to be executed over the Internet enhances the applicability and utility of these analytic software tools. Results Here we present ArrayQuest, a web-based DNA microarray analysis process controller. Key features of ArrayQuest are that (1 it is capable of executing numerous analysis programs such as those written in R, BioPerl and C++; (2 new analysis programs can be added to ArrayQuest Methods Library at the request of users or developers; (3 input DNA microarray data can be selected from public databases (i.e., the Medical University of South Carolina (MUSC DNA Microarray Database or Gene Expression Omnibus (GEO or it can be uploaded to the ArrayQuest center-point web server into a password-protected area; and (4 analysis jobs are distributed across computers configured in a backend cluster. To demonstrate the utility of ArrayQuest we have populated the methods library with methods for analysis of Affymetrix DNA microarray data. Conclusion ArrayQuest enables browser-based implementation of DNA microarray data analysis programs that can be executed on a Linux-based platform. Importantly, ArrayQuest is a platform that will facilitate the distribution and implementation of new analysis algorithms and is therefore of use to both developers of analysis applications as well as users. ArrayQuest is freely available for use at http://proteogenomics.musc.edu/arrayquest.html.
van Zyl, Willem A; Stutzer, Christian; Olivier, Nicholas A; Maritz-Olivier, Christine
The cattle tick, Rhipicephalus microplus, has a debilitating effect on the livestock industry worldwide, owing to its being a vector of the causative agents of bovine babesiosis and anaplasmosis. In South Africa, co-infestation with R. microplus and R. decoloratus, a common vector species on local livestock, occurs widely in the northern and eastern parts of the country. An alternative to chemical control methods is sought in the form of a tick vaccine to control these tick species. However, sequence information and transcriptional data for R. decoloratus is currently lacking. Therefore, this study aimed at identifying genes that are shared between midgut tissues of feeding adult female R. microplus and R. decoloratus ticks. In this regard, a custom oligonucleotide microarray comprising of 13,477 R. microplus sequences was used for transcriptional profiling and 2476 genes were found to be shared between these Rhipicephalus species. In addition, 136 transcripts were found to be more abundantly expressed in R. decoloratus and 1084 in R. microplus. Chi-square analysis revealed that genes involved in lipid transport and metabolism are significantly overrepresented in R. microplus and R. decoloratus. This study is the first transcriptional profiling of R. decoloratus and is an additional resource that can be evaluated further in future studies for possible tick control. Copyright © 2014 Elsevier GmbH. All rights reserved.
Hing Anne V
Full Text Available Abstract Background Supernumerary marker chromosomes (SMCs are structurally abnormal extra chromosomes that cannot be unambiguously identified by conventional banding techniques. In the past, SMCs have been characterized using a variety of different molecular cytogenetic techniques. Although these techniques can sometimes identify the chromosome of origin of SMCs, they are cumbersome to perform and are not available in many clinical cytogenetic laboratories. Furthermore, they cannot precisely determine the region or breakpoints of the chromosome(s involved. In this study, we describe four patients who possess one or more SMCs (a total of eight SMCs in all four patients that were characterized by microarray comparative genomic hybridization (array CGH. Results In at least one SMC from all four patients, array CGH uncovered unexpected complexity, in the form of complex rearrangements, that could have gone undetected using other molecular cytogenetic techniques. Although array CGH accurately defined the chromosome content of all but two minute SMCs, fluorescence in situ hybridization was necessary to determine the structure of the markers. Conclusion The increasing use of array CGH in clinical cytogenetic laboratories will provide an efficient method for more comprehensive characterization of SMCs. Improved SMC characterization, facilitated by array CGH, will allow for more accurate SMC/phenotype correlation.
Tra, Yolande V; Evans, Irene M
BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.
Evans, Irene M.
BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. PMID:20810954
Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J
Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson
Full Text Available Abstract Background Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. Results In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC, that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. Conclusion
Full Text Available Abstract Background DNA microarray is an invaluable tool for gene expression explorations. In the two-dye microarray, fluorescence intensities of two samples, each labeled with a different dye, are compared after hybridization. To compare a large number of samples, the 'reference design' is widely used, in which all RNA samples are hybridized to a common reference. Genomic DNA is an attractive candidate for use as a universal reference, especially for bacterial systems with a low percentage of non-coding sequences. However, genomic DNA, comprising of both the sense and anti-sense strands, is unlike the single stranded cDNA usually used in microarray hybridizations. The presence of the antisense strand in the 'reference' leads to reactions between complementary labeled strands in solution and may cause the assay result to deviate from true values. Results We have developed a mathematical model to predict the validity of using genomic DNA as a reference in the microarray assay. The model predicts that the assay can accurately estimate relative concentrations for a wide range of initial cDNA concentrations. Experimental results of DNA microarray assay using genomic DNA as a reference correlated well to those obtained by a direct hybridization between two cDNA samples. The model predicts that the initial concentrations of labeled genomic DNA strands and immobilized strands, and the hybridization time do not significantly affect the assay performance. At low values of the rate constant for hybridization between immobilized and mobile strands, the assay performance varies with the hybridization time and initial cDNA concentrations. For the case where a microarray with immobilized single strands is used, results from hybridizations using genomic DNA as a reference will correspond to true ratios under all conditions. Conclusion Simulation using the mathematical model, and the experimental study presented here show the potential utility of microarray
Full Text Available Abstract Background Microarrays for the analysis of gene expression are of three different types: short oligonucleotide (25–30 base, long oligonucleotide (50–80 base, and cDNA (highly variable in length. The short oligonucleotide and cDNA arrays have been the mainstay of expression analysis to date, but long oligonucleotide platforms are gaining in popularity and will probably replace cDNA arrays. As part of a validation study for the long oligonucleotide arrays, we compared and contrasted expression profiles from the three formats, testing RNA from six different cell lines against a universal reference standard. Results The three platforms had 6430 genes in common. In general, correlation of gene expression levels across the platforms was good when defined by concordance in the direction of expression difference (upregulation or downregulation, scatter plot analysis, principal component analysis, cell line correlation or quantitative RT-PCR. The overall correlations (r values between platforms were in the range 0.7 to 0.8, as determined by analysis of scatter plots. When concordance was measured for expression ratios significant at p-values of Conclusion Our results indicate that the long oligonucleotide platform is highly suitable for expression analysis and compares favorably with the cDNA and short oligonucleotide varieties. All three platforms can give similar and reproducible results if the criterion is the direction of change in gene expression and minimal emphasis is placed on the magnitude of change.
Full Text Available Recently emerged deep sequencing technologies offer new high-throughput methods to quantify gene expression, epigenetic modifications and DNA-protein binding. From a computational point of view, the data is very different from that produced by the already established microarray technology, providing a new perspective on the samples under study and complementing microarray gene expression data. Software offering the integrated analysis of data from different technologies is of growing importance as new data emerge in systems biology studies. Mayday is an extensible platform for visual data exploration and interactive analysis and provides many methods for dissecting complex transcriptome datasets. We present Mayday SeaSight, an extension that allows to integrate data from different platforms such as deep sequencing and microarrays. It offers methods for computing expression values from mapped reads and raw microarray data, background correction and normalization and linking microarray probes to genomic coordinates. It is now possible to use Mayday's wealth of methods to analyze sequencing data and to combine data from different technologies in one analysis.
Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu
Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.
Full Text Available Abstract Background During the past decade, many software packages have been developed for analysis and visualization of various types of microarrays. We have developed and maintained the widely used dChip as a microarray analysis software package accessible to both biologist and data analysts. However, challenges arise when dChip users want to analyze large number of arrays automatically and share data analysis procedures and parameters. Improvement is also needed when the dChip user support team tries to identify the causes of reported analysis errors or bugs from users. Results We report here implementation and application of the dChip automation module. Through this module, dChip automation files can be created to include menu steps, parameters, and data viewpoints to run automatically. A data-packaging function allows convenient transfer from one user to another of the dChip software, microarray data, and analysis procedures, so that the second user can reproduce the entire analysis session of the first user. An analysis report file can also be generated during an automated run, including analysis logs, user comments, and viewpoint screenshots. Conclusion The dChip automation module is a step toward reproducible research, and it can prompt a more convenient and reproducible mechanism for sharing microarray software, data, and analysis procedures and results. Automation data packages can also be used as publication supplements. Similar automation mechanisms could be valuable to the research community if implemented in other genomics and bioinformatics software packages.
Full Text Available Abstract Background Hepatitis C virus (HCV RNA synthesis and protein expression affect cell homeostasis by modulation of gene expression. The impact of HCV replication on global cell transcription has not been fully evaluated. Thus, we analysed the expression profiles of different clones of human hepatoma-derived Huh-7 cells carrying a self-replicating HCV RNA which express all viral proteins (HCV replicon system. Results First, we compared the expression profile of HCV replicon clone 21-5 with both the Huh-7 parental cells and the 21-5 cured (21-5c cells. In these latter, the HCV RNA has been eliminated by IFN-α treatment. To confirm data, we also analyzed microarray results from both the 21-5 and two other HCV replicon clones, 22-6 and 21-7, compared to the Huh-7 cells. The study was carried out by using the Applied Biosystems (AB Human Genome Survey Microarray v1.0 which provides 31,700 probes that correspond to 27,868 human genes. Microarray analysis revealed a specific transcriptional program induced by HCV in replicon cells respect to both IFN-α-cured and Huh-7 cells. From the original datasets of differentially expressed genes, we selected by Venn diagrams a final list of 38 genes modulated by HCV in all clones. Most of the 38 genes have never been described before and showed high fold-change associated with significant p-value, strongly supporting data reliability. Classification of the 38 genes by Panther System identified functional categories that were significantly enriched in this gene set, such as histones and ribosomal proteins as well as extracellular matrix and intracellular protein traffic. The dataset also included new genes involved in lipid metabolism, extracellular matrix and cytoskeletal network, which may be critical for HCV replication and pathogenesis. Conclusion Our data provide a comprehensive analysis of alterations in gene expression induced by HCV replication and reveal modulation of new genes potentially useful
Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben
Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.
Tan, Qihua; Thomassen, Mads; Burton, Mark
Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering...... the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...... time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health....
Tan, Qihua; Thomassen, Mads; Burton, Mark
Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering...... the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray...
Maslow, Bat-Sheva L; Budinetz, Tara; Sueldo, Carolina; Anspach, Erica; Engmann, Lawrence; Benadiva, Claudio; Nulsen, John C
To compare the analysis of chromosome number from paraffin-embedded products of conception using single-nucleotide polymorphism (SNP) microarray with the recommended screening for the evaluation of couples presenting with recurrent pregnancy loss who do not have previous fetal cytogenetic data. We performed a retrospective cohort study including all women who presented for a new evaluation of recurrent pregnancy loss over a 2-year period (January 1, 2012, to December 31, 2013). All participants had at least two documented first-trimester losses and both the recommended screening tests and SNP microarray performed on at least one paraffin-embedded products of conception sample. Single-nucleotide polymorphism microarray identifies all 24 chromosomes (22 autosomes, X, and Y). Forty-two women with a total of 178 losses were included in the study. Paraffin-embedded products of conception from 62 losses were sent for SNP microarray. Single-nucleotide polymorphism microarray successfully diagnosed fetal chromosome number in 71% (44/62) of samples, of which 43% (19/44) were euploid and 57% (25/44) were noneuploid. Seven of 42 (17%) participants had abnormalities on recurrent pregnancy loss screening. The per-person detection rate for a cause of pregnancy loss was significantly higher in the SNP microarray (0.50; 95% confidence interval [CI] 0.36-0.64) compared with recurrent pregnancy loss evaluation (0.17; 95% CI 0.08-0.31) (P=.002). Participants with one or more euploid loss identified on paraffin-embedded products of conception were significantly more likely to have an abnormality on recurrent pregnancy loss screening than those with only noneuploid results (P=.028). The significance remained when controlling for age, number of losses, number of samples, and total pregnancies. These results suggest that SNP microarray testing of paraffin-embedded products of conception is a valuable tool for the evaluation of recurrent pregnancy loss in patients without prior fetal
Fiegler, Heike; Carr, Philippa; Douglas, Eleanor J; Burford, Deborah C; Hunt, Sarah; Scott, Carol E; Smith, James; Vetrie, David; Gorman, Patricia; Tomlinson, Ian P M; Carter, Nigel P
We have designed DOP-PCR primers specifically for the amplification of large insert clones for use in the construction of DNA microarrays. A bioinformatic approach was used to construct primers that were efficient in the general amplification of human DNA but were poor at amplifying E. coli DNA, a common contaminant of DNA preparations from large insert clones. We chose the three most selective primers for use in printing DNA microarrays. DNA combined from the amplification of large insert clones by use of these three primers and spotted onto glass slides showed more than a sixfold increase in the human to E. coli hybridization ratio when compared to the standard DOP-PCR primer, 6MW. The microarrays reproducibly delineated previously characterized gains and deletions in a cancer cell line and identified a small gain not detected by use of conventional CGH. We also describe a method for the bulk testing of the hybridization characteristics of chromosome-specific clones spotted on microarrays by use of DNA amplified from flow-sorted chromosomes. Finally, we describe a set of clones selected from the publicly available Golden Path of the human genome at 1-Mb intervals and a view in the Ensembl genome browser from which data required for the use of these clones in array CGH and other experiments can be downloaded across the Internet.
Danielle E Green
Full Text Available BackgroundThe value of immunohistochemistry (IHC-microarray analysis of pathological specimens in the management of patients is controversial although preliminary data suggests potential benefit. We describe the characteristics of patients undergoing a commercially available IHC-microarray method in patients with peritoneal metastases (PM and the feasibility of this technique in this population.MethodsWe retrospectively analyzed consecutive patients with pathologically confirmed PM from appendiceal or colorectal primary who underwent Caris Molecular IntelligenceTM testing. IHC, microarray, FISH and mutational analysis were included and stratified by PCI score, histology and treatment characteristics. Statistical analysis was performed using non-parametric tests.ResultsOur study included 5 patients with appendiceal and 11 with colorectal PM. The median age of patients was 51 (IQR 39-65 years, with 11(68% female. The median PCI score of the patients was 17(IQR 10-25. Hyperthermic intra-peritoneal chemoperfusion (HIPEC was performed in 4 (80% patients with appendiceal primary tumors and 4 (36% with colorectal primary. KRAS mutations were encountered in 40% of appendiceal vs. 30% colorectal tumors, while BRAF mutations were seen in 40% of colorectal PM and none of the patients with appendiceal PM (p=0.06. IHC biomarker expression was not significantly different between the two primaries. Sufficient tumor for microarray analysis was found in 44% (n=7 patients, which was not associated with previous use of chemotherapy (p>0.20 for 5-FU/LV, Irinotecan and Oxaliplatin.ConclusionsIn a small sample of patients with peritoneal metastases, the feasibility and results of IHC-microarray staining based on a commercially available test is reported. The apparent high incidence of the BRAF mutation in patients with PM may potentially offer opportunities for novel therapeutics and suggest that IHC-microarray is a method that can be used in this population.
Full Text Available Abstract Background Chromosomal Comparative Genomic Hybridization (CGH has been applied to all stages of cervical carcinoma progression, defining a specific pattern of chromosomal imbalances in this tumor. However, given its limited spatial resolution, chromosomal CGH has offered only general information regarding the possible genetic targets of DNA copy number changes. Methods In order to further define specific DNA copy number changes in cervical cancer, we analyzed 20 cervical samples (3 pre-malignant lesions, 10 invasive tumors, and 7 cell lines, using the GenoSensor microarray CGH system to define particular genetic targets that suffer copy number changes. Results The most common DNA gains detected by array CGH in the invasive samples were located at the RBP1-RBP2 (3q21-q22 genes, the sub-telomeric clone C84C11/T3 (5ptel, D5S23 (5p15.2 and the DAB2 gene (5p13 in 58.8% of the samples. The most common losses were found at the FHIT gene (3p14.2 in 47% of the samples, followed by deletions at D8S504 (8p23.3, CTDP1-SHGC- 145820 (18qtel, KIT (4q11-q12, D1S427-FAF1 (1p32.3, D9S325 (9qtel, EIF4E (eukaryotic translation initiation factor 4E, 4q24, RB1 (13q14, and DXS7132 (Xq12 present in 5/17 (29.4% of the samples. Conclusion Our results confirm the presence of a specific pattern of chromosomal imbalances in cervical carcinoma and define specific targets that are suffering DNA copy number changes in this neoplasm.
Hidalgo, Alfredo; Baudis, Michael; Petersen, Iver; Arreola, Hugo; Piña, Patricia; Vázquez-Ortiz, Guelaguetza; Hernández, Dulce; González, José; Lazos, Minerva; López, Ricardo; Pérez, Carlos; García, José; Vázquez, Karla; Alatorre, Brenda; Salcedo, Mauricio
Background Chromosomal Comparative Genomic Hybridization (CGH) has been applied to all stages of cervical carcinoma progression, defining a specific pattern of chromosomal imbalances in this tumor. However, given its limited spatial resolution, chromosomal CGH has offered only general information regarding the possible genetic targets of DNA copy number changes. Methods In order to further define specific DNA copy number changes in cervical cancer, we analyzed 20 cervical samples (3 pre-malignant lesions, 10 invasive tumors, and 7 cell lines), using the GenoSensor microarray CGH system to define particular genetic targets that suffer copy number changes. Results The most common DNA gains detected by array CGH in the invasive samples were located at the RBP1-RBP2 (3q21-q22) genes, the sub-telomeric clone C84C11/T3 (5ptel), D5S23 (5p15.2) and the DAB2 gene (5p13) in 58.8% of the samples. The most common losses were found at the FHIT gene (3p14.2) in 47% of the samples, followed by deletions at D8S504 (8p23.3), CTDP1-SHGC- 145820 (18qtel), KIT (4q11-q12), D1S427-FAF1 (1p32.3), D9S325 (9qtel), EIF4E (eukaryotic translation initiation factor 4E, 4q24), RB1 (13q14), and DXS7132 (Xq12) present in 5/17 (29.4%) of the samples. Conclusion Our results confirm the presence of a specific pattern of chromosomal imbalances in cervical carcinoma and define specific targets that are suffering DNA copy number changes in this neoplasm. PMID:16004614
Full Text Available Plants have evolved with intricate mechanisms to cope with multiple environmental stresses. To adapt with biotic and abiotic stresses, plant responses involve changes at the cellular and molecular levels. The current study was designed to investigate the effects of combinations of different environmental stresses on the transcriptome level of Arabidopsis genome using public microarray databases. We investigated the role of cyclopentenones in mediating plant responses to environmental stress through TGA (TGACG motif-binding factor transcription factor, independently from jasmonic acid. Candidate genes were identified by comparing plants inoculated with Botrytis cinerea or treated with heat, salt or osmotic stress with non-inoculated or non-treated tissues. About 2.5% heat-, 19% salinity- and 41% osmotic stress-induced genes were commonly upregulated by B. cinerea-treatment; and 7.6%, 19% and 48% of genes were commonly downregulated by B. cinerea-treatment, respectively. Our results indicate that plant responses to biotic and abiotic stresses are mediated by several common regulatory genes. Comparisons between transcriptome data from Arabidopsis stressed-plants support our hypothesis that some molecular and biological processes involved in biotic and abiotic stress response are conserved. Thirteen of the common regulated genes to abiotic and biotic stresses were studied in detail to determine their role in plant resistance to B. cinerea. Moreover, a T-DNA insertion mutant of the Responsive to Dehydration gene (rd20, encoding for a member of the caleosin (lipid surface protein family, showed an enhanced sensitivity to B. cinerea infection and drought. Overall, the overlapping of plant responses to abiotic and biotic stresses, coupled with the sensitivity of the rd20 mutant, may provide new interesting programs for increased plant resistance to multiple environmental stresses, and ultimately increases its chances to survive. Future research
Albers, Casper J.; Jansen, Ritsert C.; Kok, Jan; Kuipers, Oscar P.; Hijum, Sacha A.F.T. van
Simulation of DNA-microarray data serves at least three purposes: (i) optimizing the design of an intended DNA microarray experiment, (ii) comparing existing pre-processing and processing methods for best analysis of a given DNA microarray experiment, (iii) educating students, lab-workers and other
ZhiJun Tan; Xian-Gui Hu; Gui-Song Cao; Yan Tang
AIM: To identify new diagnostic markers and drug targets,the gene expression profiles of pancreatic cancer were compared with that of adjacent normal tissues utilizing cDNA microarray analysis.METHODS: cDNA probes were prepared by labeling mRNA from samples of six pancreatic carcinoma tissues with Cy5dUTP and mRNA from adjacent normal tissues with Cy3dUTP respectively through reverse transcription. The mixed probes of each sample were then hybridized with 12 800cDNA arrays (12 648 unique human cDNA sequences), and the fluorescent signals were scanned by ScanArray 3 000scanner (General Scanning, Inc.). The values of CyS-dUTP and Cy3-dUTP on each spot were analyzed and calculated by ImaGene 3.0 software (BioDiscovery, Inc.). Differentially expressed genes were screened according to the criterion that the absolute value of natural logarithm of the ratio of Cy5-dUTP to Cy3-dUTP was greater-than 0.69.RESETS: Among 6 samples investigated, 301 genes, which accounted for 2.38% of genes on the microarry slides,exhibited differentially expression at least in 5. There were 166 over-expressed genes including 136 having been registered in Genebank, and 135 under-expressed genes including 79 in Genebank in cancerous tissues.CONCLUSION: Microarray analysis may provide invaluable information on disease pathology, progression, resistance to treatment, and response to cellular microenvironments of pancreatic carcinoma and ultimately may lead to improving early diagnosis and discovering innovative therapeutic approaches for cancer.
Full Text Available Abstract Background Summarization of gene information in the literature has the potential to help genomics researchers translate basic research into clinical benefits. Gene expression microarrays have been used to study biomarkers for disease and discover novel types of therapeutics and the task of finding information in journal articles on sets of genes is common for translational researchers working with microarray data. However, manually searching and scanning the literature references returned from PubMed is a time-consuming task for scientists. We built and evaluated an automatic summarizer of information on genes studied in microarray experiments. The Gene Information Clustering and Summarization System (GICSS is a system that integrates two related steps of the microarray data analysis process: functional gene clustering and gene information gathering. The system evaluation was conducted during the process of genomic researchers analyzing their own experimental microarray datasets. Results The clusters generated by GICSS were validated by scientists during their microarray analysis process. In addition, presenting sentences in the abstract provided significantly more important information to the users than just showing the title in the default PubMed format. Conclusion The evaluation results suggest that GICSS can be useful for researchers in genomic area. In addition, the hybrid evaluation method, partway between intrinsic and extrinsic system evaluation, may enable researchers to gauge the true usefulness of the tool for the scientists in their natural analysis workflow and also elicit suggestions for future enhancements. Availability GICSS can be accessed online at: http://ir.ohsu.edu/jianji/index.html
Ogunnaike, Babatunde A; Gelmi, Claudio A; Edwards, Jeremy S
Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays.
Yutaka Midorikawa; Masatoshi Makuuchi; Wei Tang; Hiroyuki Aburatani
Accumulation of mutations and alterations in the expression of various genes result in carcinogenesis, and the development of microarray technology has enabled us to identify the comprehensive gene expression alterations in oncogenesis. Many studies have applied this technology for hepatocellular carcinoma (HCC), and identified a number of candidate genes useful as biomarkers in cancer staging, prediction of recurrence and prognosis, and treatment selection. Some of these target molecules have been used to develop new serum diagnostic markers and therapeutic targets against HCC to benefit patients. Previously, we compared gene expression profiling data with classification based on clinicopathological features, such as hepatitis viral infection or liver cancer progression. The next era of gene expression analysis will require systematic integration of expression profiles with other types of biological information, such as genomic locus, gene function, and sequence information. We have reported integration between expression profiles and locus information, which is effective in detecting structural genomic abnormalities, such as chromosomal gains and losses, in which we showed that gene expression profiles are subject to chromosomal bias. Furthermore, array-based comparative genomic hybridization analysis and allelic dosage analysis using genotyping arrays for HCC were also reviewed, with comparison of conventional methods.
Neerincx, P.B.T.; Casel, P.; Prickett, D.; Nie, H.; Watson, M.; Leunissen, J.A.M.; Groenen, M.A.M.; Klopp, C.
Background - Reliable annotation linking oligonucleotide probes to target genes is essential for functional biological analysis of microarray experiments. We used the IMAD, OligoRAP and sigReannot pipelines to update the annotation for the ARK-Genomics Chicken 20 K array as part of a joined EADGENE/
Pas, te M.F.W.; Hulsegge, B.; Pool, M.H.
Microarray experiments investigate the changes in the expression of the transcriptome of a tissue during biological processes such as development of the tissue. Analysis usually produces a list of up and down regulated genes. While this in itself mayhighlight important biological processes taking
Evans, Helen; Mello, Luciane V.; Fang, Yongxiang; Wit, Ernst; Thompson, Fiona J.; Viney, Mark E.; Paterson, Steve
The molecular mechanisms by which parasitic nematodes reproduce and have adapted to life within a host are unclear. In the present study, microarray analysis was used to explore differential transcription among the different stages and sexes of Strongyloides ratti, a parasitic nematode of brown rats
Aharoni, A.; O'Connell, A.P.
Large-scale, single pass sequencing and parallel gene expression analysis using DNA microarrays were employed for the comprehensive investigation of ripening in strawberry fruit. A total of 1701 cDNA clones (comprising 1100 strawberry ESTs and 601 unsequenced cDNAs) obtained from a strawberry (Fraga
Cho, Hyunmin; Jung, Juyeon; Chung, Bong Hyun
We introduce a scanometric detection method for the analysis of DNA microarrays using DNA intercalator-conjugated gold nanoparticles that can be analyzed with the naked eye or with an optical scanner after the enhancement of the AuNPs. Moreover, we successfully detected a hemagglutinin-subtyping DNA array using this method.
Biehl, Michael; Breitling, Rainer; Li, Yang; Yin, H; Tino, P; Corchado, E; Byrne, W; Yao,
We apply learning vector quantization to the analysis of tiling microarray data. As an example we consider the classification of C. elegans genomic probes as intronic or exonic. Training is based on the current annotation of the genome. Relevance learning techniques are used to weight and select fea
Elferink, Marieke; Olinga, Peter; Draaisma, Annelies; Merema, M.T.; Bauerschmidt, Susanne; Polman, Jan; Schoonen, Willem; Groothuis, Geny
In the process of drug discovery it is of great importance to develop methods to determine early markers for druginduced toxicity. The microarray technology, developed for the simultaneous analysis of a large number of genes, may be useful for the detection of toxicity in an early stage of the devel
McGrew, Susan G.; Peters, Brittany R.; Crittendon, Julie A.; Veenstra-VanderWeele, Jeremy
Genetic testing is recommended for patients with ASD; however specific recommendations vary by specialty. American Academy of Pediatrics and American Academy of Neurology guidelines recommend G-banded karyotype and Fragile X DNA. The American College of Medical Genetics recommends Chromosomal Microarray Analysis (CMA). We determined the yield of…
Neerincx, P.B.T.; Casel, P.; Prickett, D.; Nie, H.; Watson, M.; Leunissen, J.A.M.; Groenen, M.A.M.; Klopp, C.
Background - Reliable annotation linking oligonucleotide probes to target genes is essential for functional biological analysis of microarray experiments. We used the IMAD, OligoRAP and sigReannot pipelines to update the annotation for the ARK-Genomics Chicken 20 K array as part of a joined EADGENE/
DNA/DNA microarray hybridization was used to compare the genome content of Streptomyces avermitilis, Streptomyces cattleya, Streptomyces maritimus and Kitasatospora aureofaciens with that of Streptomyces coelicolor A3(2). The array data showed an about 93% agreement with the genome sequence data available for S. avermitilis and also showed a number of trends in the genome structure for Streptomyces and closely related Kitasatospora. A core central region was well conserved, which might be pre...
Full Text Available Desert locusts (Schistocerca gregaria show an extreme form of phenotypic plasticity and can transform between a cryptic solitarious phase and a swarming gregarious phase. The two phases differ extensively in behavior, morphology and physiology but very little is known about the molecular basis of these differences. We used our recently generated Expressed Sequence Tag (EST database derived from S. gregaria central nervous system (CNS to design oligonucleotide microarrays and compare the expression of thousands of genes in the CNS of long-term gregarious and solitarious adult desert locusts. This identified 214 differentially expressed genes, of which 40% have been annotated to date. These include genes encoding proteins that are associated with CNS development and modeling, sensory perception, stress response and resistance, and fundamental cellular processes. Our microarray analysis has identified genes whose altered expression may enable locusts of either phase to deal with the different challenges they face. Genes for heat shock proteins and proteins which confer protection from infection were upregulated in gregarious locusts, which may allow them to respond to acute physiological challenges. By contrast the longer-lived solitarious locusts appear to be more strongly protected from the slowly accumulating effects of ageing by an upregulation of genes related to anti-oxidant systems, detoxification and anabolic renewal. Gregarious locusts also had a greater abundance of transcripts for proteins involved in sensory processing and in nervous system development and plasticity. Gregarious locusts live in a more complex sensory environment than solitarious locusts and may require a greater turnover of proteins involved in sensory transduction, and possibly greater neuronal plasticity.
Lubbock, Alexander L R; Katz, Elad; Harrison, David J; Overton, Ian M
Tissue microarrays (TMAs) allow multiplexed analysis of tissue samples and are frequently used to estimate biomarker protein expression in tumour biopsies. TMA Navigator (www.tmanavigator.org) is an open access web application for analysis of TMA data and related information, accommodating categorical, semi-continuous and continuous expression scores. Non-biological variation, or batch effects, can hinder data analysis and may be mitigated using the ComBat algorithm, which is incorporated with enhancements for automated application to TMA data. Unsupervised grouping of samples (patients) is provided according to Gaussian mixture modelling of marker scores, with cardinality selected by Bayesian information criterion regularization. Kaplan-Meier survival analysis is available, including comparison of groups identified by mixture modelling using the Mantel-Cox log-rank test. TMA Navigator also supports network inference approaches useful for TMA datasets, which often constitute comparatively few markers. Tissue and cell-type specific networks derived from TMA expression data offer insights into the molecular logic underlying pathophenotypes, towards more effective and personalized medicine. Output is interactive, and results may be exported for use with external programs. Private anonymous access is available, and user accounts may be generated for easier data management.
Topcuoglu, Nursen; Kulekci, Guven
DNA microarray analysis is a computer based technology, that a reverse capture, which targets 10 periodontal bacteria (ParoCheck) is available for rapid semi-quantitative determination. The aim of this three-year retrospective study was to display the microarray analysis results for the subgingival biofilm samples taken from patient cases diagnosed with different forms of periodontitis. A total of 84 patients with generalized aggressive periodontitis (GAP,n:29), generalized chronic periodontitis (GCP, n:25), peri-implantitis (PI,n:14), localized aggressive periodontitis (LAP,n:8) and refractory chronic periodontitis (RP,n:8) were consecutively selected from the archives of the Oral Microbiological Diagnostic Laboratory. The subgingival biofilm samples were analyzed by the microarray-based identification of 10 selected species. All the tested species were detected in the samples. The red complex bacteria were the most prevalent with very high levels in all groups. Fusobacterium nucleatum was detected in all samples at high levels. The green and blue complex bacteria were less prevalent compared with red and orange complex, except Aggregatibacter actinomycetemcomitas was detected in all LAP group. Positive correlations were found within all the red complex bacteria and between red and orange complex bacteria especially in GCP and GAP groups. Parocheck enables to monitoring of periodontal pathogens in all forms of periodontal disease and can be alternative to other guiding and reliable microbiologic tests.
Liebner, David A; Huang, Kun; Parvin, Jeffrey D
One of the significant obstacles in the development of clinically relevant microarray-derived biomarkers and classifiers is tissue heterogeneity. Physical cell separation techniques, such as cell sorting and laser-capture microdissection, can enrich samples for cell types of interest, but are costly, labor intensive and can limit investigation of important interactions between different cell types. We developed a new computational approach, called microarray microdissection with analysis of differences (MMAD), which performs microdissection in silico. Notably, MMAD (i) allows for simultaneous estimation of cell fractions and gene expression profiles of contributing cell types, (ii) adjusts for microarray normalization bias, (iii) uses the corrected Akaike information criterion during model optimization to minimize overfitting and (iv) provides mechanisms for comparing gene expression and cell fractions between samples in different classes. Computational microdissection of simulated and experimental tissue mixture datasets showed tight correlations between predicted and measured gene expression of pure tissues as well as tight correlations between reported and estimated cell fraction for each of the individual cell types. In simulation studies, MMAD showed superior ability to detect differentially expressed genes in mixed tissue samples when compared with standard metrics, including both significance analysis of microarrays and cell type-specific significance analysis of microarrays. We have developed a new computational tool called MMAD, which is capable of performing robust tissue microdissection in silico, and which can improve the detection of differentially expressed genes. MMAD software as implemented in MATLAB is publically available for download at http://sourceforge.net/projects/mmad/.
Ben Abdallah, Inesse; Hannachi, Hanene; Soyah, Najla; Saad, Ali; Elghezal, Hatem
Chromosomal imbalances comprise a major cause of mental retardation, particularly in association with congenital malformations and dysmorphic features. Chromosomal analysis using banded karyotyping is limited by the low resolution of this technique, and cryptic chromosomal rearrangements cannot be detected. We describe a 6-year-old girl with mental retardation, mild growth, congenital malformation, and facial anomalies. Chromosomal analysis with karyotyping produced normal results. Because the phenotype suggested chromosomal abnormality, microarray comparative genomic hybridization was used to search for a possible cryptic anomaly. A subtelomeric chromosomal imbalance, consisting of partial trisomy 2q35 and partial monosomy 3p26, was detected and confirmed using fluorescence in situ hybridization. This rearrangement was inherited from an equilibrated maternal t(2;3) reciprocal translocation. Comparative genomic hybridization array in similar situations is useful in detecting cryptic chromosomal rearrangements, identifying genes contained in deleted or duplicated regions, establishing a precise phenotype-genotype correlation, and offering unambiguous genetic counseling. Copyright © 2011 Elsevier Inc. All rights reserved.
Kang, Suyeon; Song, Jongwoo
A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.
Full Text Available Abstract Background Over the past decade, gene expression microarray studies have greatly expanded our knowledge of genetic mechanisms of human diseases. Meta-analysis of substantial amounts of accumulated data, by integrating valuable information from multiple studies, is becoming more important in microarray research. However, collecting data of special interest from public microarray repositories often present major practical problems. Moreover, including low-quality data may significantly reduce meta-analysis efficiency. Results M2DB is a human curated microarray database designed for easy querying, based on clinical information and for interactive retrieval of either raw or uniformly pre-processed data, along with a set of quality-control metrics. The database contains more than 10,000 previously published Affymetrix GeneChip arrays, performed using human clinical specimens. M2DB allows online querying according to a flexible combination of five clinical annotations describing disease state and sampling location. These annotations were manually curated by controlled vocabularies, based on information obtained from GEO, ArrayExpress, and published papers. For array-based assessment control, the online query provides sets of QC metrics, generated using three available QC algorithms. Arrays with poor data quality can easily be excluded from the query interface. The query provides values from two algorithms for gene-based filtering, and raw data and three kinds of pre-processed data for downloading. Conclusion M2DB utilizes a user-friendly interface for QC parameters, sample clinical annotations, and data formats to help users obtain clinical metadata. This database provides a lower entry threshold and an integrated process of meta-analysis. We hope that this research will promote further evolution of microarray meta-analysis.
Roberts, Jennifer L; Hovanes, Karine; Dasouki, Majed; Manzardo, Ann M; Butler, Merlin G
Chromosomal microarray analysis is now commonly used in clinical practice to identify copy number variants (CNVs) in the human genome. We report our experience with the use of the 105 K and 180K oligonucleotide microarrays in 215 consecutive patients referred with either autism or autism spectrum disorders (ASD) or developmental delay/learning disability for genetic services at the University of Kansas Medical Center during the past 4 years (2009-2012). Of the 215 patients [140 males and 75 females (male/female ratio=1.87); 65 with ASD and 150 with learning disability], abnormal microarray results were seen in 45 individuals (21%) with a total of 49 CNVs. Of these findings, 32 represented a known diagnostic CNV contributing to the clinical presentation and 17 represented non-diagnostic CNVs (variants of unknown significance). Thirteen patients with ASD had a total of 14 CNVs, 6 CNVs recognized as diagnostic and 8 as non-diagnostic. The most common chromosome involved in the ASD group was chromosome 15. For those with a learning disability, 32 patients had a total of 35 CNVs. Twenty-six of the 35 CNVs were classified as a known diagnostic CNV, usually a deletion (n=20). Nine CNVs were classified as an unknown non-diagnostic CNV, usually a duplication (n=8). For the learning disability subgroup, chromosomes 2 and 22 were most involved. Thirteen out of 65 patients (20%) with ASD had a CNV compared with 32 out of 150 patients (21%) with a learning disability. The frequency of chromosomal microarray abnormalities compared by subject group or gender was not statistically different. A higher percentage of individuals with a learning disability had clinical findings of seizures, dysmorphic features and microcephaly, but not statistically significant. While both groups contained more males than females, a significantly higher percentage of males were present in the ASD group.
Luo, Wen; Gudipati, Murali; Jung, Kevin; Chen, Mao; Marschke, Keith B
Despite the large number of software tools developed to address different areas of microarray data analysis, very few offer an all-in-one solution with little learning curve. For microarray core labs, there are even fewer software packages available to help with their routine but critical tasks, such as data quality control (QC) and inventory management. We have developed a simple-to-use web portal to allow bench biologists to analyze and query complicated microarray data and related biological pathways without prior training. Both experiment-based and gene-based analysis can be easily performed, even for the first-time user, through the intuitive multi-layer design and interactive graphic links. While being friendly to inexperienced users, most parameters in Goober can be easily adjusted via drop-down menus to allow advanced users to tailor their needs and perform more complicated analysis. Moreover, we have integrated graphic pathway analysis into the website to help users examine microarray data within the relevant biological content. Goober also contains features that cover most of the common tasks in microarray core labs, such as real time array QC, data loading, array usage and inventory tracking. Overall, Goober is a complete microarray solution to help biologists instantly discover valuable information from a microarray experiment and enhance the quality and productivity of microarray core labs. The whole package is freely available at http://sourceforge.net/projects/goober. A demo web server is available at http://www.goober-array.org.
Gang Jin; Xian-Gui Hu; Kang Ying; Yan Tang; Rui Liu; Yi-Jie Zhang; Zai-Ping Jing; Yi Xie; Yu-Min Mao
AIM: To study the pathogenetic processes and the role of gene expression by microarray analyses in expediting our understanding of the molecular pathophysiology of pancreatic adenocarcinoma, and to identify the novel cancer-associated genes.METHODS: Nine histologically defined pancreatic head adenocarcinoma specimens associated with clinical data were studied. Total RNA and mRNA were isolated and labeled by reverse transcription reaction with Cy5 and Cy3 for cDNA probe. The cDNA microarrays that represent a set of 4 096 human genes were hybridized with labeled cDNA probe and screened for molecular profiling analyses.RESULTS: Using this methodology, 184 genes were screened out for differences in gene expression level after nine couples of hybridizations. Of the 184 genes,87 were upregulated and 97 downregulated, including 11 novel human genes. In pancreatic adenocarcinoma tissue, several invasion and metastasis related genes showed their high expression levels, suggesting that poor prognosis of pancreatic adenocarcinoma might have a solid molecular biological basis.CONCLUSION: The application of cDNA microarray technique for analysis of gene expression patterns is a powerful strategy to identify novel cancer-associated genes, and to rapidly explore their role in clinical pancreatic adenocarcinoma. Microarray profiles provide us new insights into the carcinogenesis and invasive process of pancreatic adenocarcinoma. Our results suggest that a highly organized and structured process of tumor invasion exists in the pancreas.
Paraboschi, Elvezia Maria; Cardamone, Giulia; Rimoldi, Valeria; Gemmati, Donato; Spreafico, Marta; Duga, Stefano; Soldà, Giulia; Asselta, Rosanna
Abnormalities in RNA metabolism and alternative splicing (AS) are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS) and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls), followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p=0.0015) by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.
Luque-Baena, Rafael Marcos; Urda, Daniel; Subirats, Jose Luis; Franco, Leonardo; Jerez, Jose M
Extracting relevant information from microarray data is a very complex task due to the characteristics of the data sets, as they comprise a large number of features while few samples are generally available. In this sense, feature selection is a very important aspect of the analysis helping in the tasks of identifying relevant genes and also for maximizing predictive information. Due to its simplicity and speed, Stepwise Forward Selection (SFS) is a widely used feature selection technique. In this work, we carry a comparative study of SFS and Genetic Algorithms (GA) as general frameworks for the analysis of microarray data with the aim of identifying group of genes with high predictive capability and biological relevance. Six standard and machine learning-based techniques (Linear Discriminant Analysis (LDA), Support Vector Machines (SVM), Naive Bayes (NB), C-MANTEC Constructive Neural Network, K-Nearest Neighbors (kNN) and Multilayer perceptron (MLP)) are used within both frameworks using six free-public datasets for the task of predicting cancer outcome. Better cancer outcome prediction results were obtained using the GA framework noting that this approach, in comparison to the SFS one, leads to a larger selection set, uses a large number of comparison between genetic profiles and thus it is computationally more intensive. Also the GA framework permitted to obtain a set of genes that can be considered to be more biologically relevant. Regarding the different classifiers used standard feedforward neural networks (MLP), LDA and SVM lead to similar and best results, while C-MANTEC and k-NN followed closely but with a lower accuracy. Further, C-MANTEC, MLP and LDA permitted to obtain a more limited set of genes in comparison to SVM, NB and kNN, and in particular C-MANTEC resulted in the most robust classifier in terms of changes in the parameter settings. This study shows that if prediction accuracy is the objective, the GA-based approach lead to better results
Tárraga, Joaquín; Medina, Ignacio; Carbonell, José; Huerta-Cepas, Jaime; Minguez, Pablo; Alloza, Eva; Al-Shahrour, Fátima; Vegas-Azcárate, Susana; Goetz, Stefan; Escobar, Pablo; Garcia-Garcia, Francisco; Conesa, Ana; Montaner, David; Dopazo, Joaquín
Gene Expression Profile Analysis Suite (GEPAS) is one of the most complete and extensively used web-based packages for microarray data analysis. During its more than 5 years of activity it has continuously been updated to keep pace with the state-of-the-art in the changing microarray data analysis arena. GEPAS offers diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and functional profiling of the experiment. New options for time-course (or dose-response) experiments, microarray-based class prediction, new clustering methods and new tests for differential expression have been included. The new pipeliner module allows automating the execution of sequential analysis steps by means of a simple but powerful graphic interface. An extensive re-engineering of GEPAS has been carried out which includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. GEPAS is nowadays the most quoted web tool in its field and it is extensively used by researchers of many countries and its records indicate an average usage rate of 500 experiments per day. GEPAS, is available at http://www.gepas.org. PMID:18508806
Smith Maria W
Full Text Available Abstract Background Many model systems of human viral disease involve human-mouse chimeric tissue. One such system is the recently developed SCID-beige/Alb-uPA mouse model of hepatitis C virus (HCV infection which involves a human-mouse chimeric liver. The use of functional genomics to study HCV infection in these chimeric tissues is complicated by the potential cross-hybridization of mouse mRNA on human oligonucleotide microarrays. To identify genes affected by mouse liver mRNA hybridization, mRNA from identical human liver samples labeled with either Cy3 or Cy5 was compared in the presence and absence of known amounts of mouse liver mRNA labeled in only one dye. Results The results indicate that hybridization of mouse mRNA to the corresponding human gene probe on Agilent Human 22 K oligonucleotide microarray does occur. The number of genes affected by such cross-hybridization was subsequently reduced to approximately 300 genes both by increasing the hybridization temperature and using liver samples which contain at least 80% human tissue. In addition, Real Time quantitative RT-PCR using human specific probes was shown to be a valid method to verify the expression level in human cells of known cross-hybridizing genes. Conclusion The identification of genes affected by cross-hybridization of mouse liver RNA on human oligonucleotide microarrays makes it feasible to use functional genomics approaches to study the chimeric SCID-beige/Alb-uPA mouse model of HCV infection. This approach used to study cross-species hybridization on oligonucleotide microarrays can be adapted to other chimeric systems of viral disease to facilitate selective analysis of human gene expression.
van Ommen Gert-Jan B
Full Text Available Abstract Background Comparative analysis of expression microarray studies is difficult due to the large influence of technical factors on experimental outcome. Still, the identified differentially expressed genes may hint at the same biological processes. However, manually curated assignment of genes to biological processes, such as pursued by the Gene Ontology (GO consortium, is incomplete and limited. We hypothesised that automatic association of genes with biological processes through thesaurus-controlled mining of Medline abstracts would be more effective. Therefore, we developed a novel algorithm (LAMA: Literature-Aided Meta-Analysis to quantify the similarity between transcriptomics studies. We evaluated our algorithm on a large compendium of 102 microarray studies published in the field of muscle development and disease, and compared it to similarity measures based on gene overlap and over-representation of biological processes assigned by GO. Results While the overlap in both genes and overrepresented GO-terms was poor, LAMA retrieved many more biologically meaningful links between studies, with substantially lower influence of technical factors. LAMA correctly grouped muscular dystrophy, regeneration and myositis studies, and linked patient and corresponding mouse model studies. LAMA also retrieves the connecting biological concepts. Among other new discoveries, we associated cullin proteins, a class of ubiquitinylation proteins, with genes down-regulated during muscle regeneration, whereas ubiquitinylation was previously reported to be activated during the inverse process: muscle atrophy. Conclusion Our literature-based association analysis is capable of finding hidden common biological denominators in microarray studies, and circumvents the need for raw data analysis or curated gene annotation databases.
Full Text Available Abstract Background In order to understand microarray data reasonably in the context of other existing biological knowledge, it is necessary to conduct a thorough examination of the data utilizing every aspect of available omic knowledge libraries. So far, a number of bioinformatics tools have been developed. However, each of them is restricted to deal with one type of omic knowledge, e.g., pathways, interactions or gene ontology. Now that the varieties of omic knowledge are expanding, analysis tools need a way to deal with any type of omic knowledge. Hence, we have designed the Omic Space Markup Language (OSML that can represent a wide range of omic knowledge, and also, we have developed a tool named GSCope3, which can statistically analyze microarray data in comparison with the OSML-formatted omic knowledge data. Results In order to test the applicability of OSML to represent a variety of omic knowledge specifically useful for analysis of Arabidopsis thaliana microarray data, we have constructed a Biological Knowledge Library (BiKLi by converting eight different types of omic knowledge into OSML-formatted datasets. We applied GSCope3 and BiKLi to previously reported A. thaliana microarray data, so as to extract any additional insights from the data. As a result, we have discovered a new insight that lignin formation resists drought stress and activates transcription of many water channel genes to oppose drought stress; and most of the 20S proteasome subunit genes show similar expression profiles under drought stress. In addition to this novel discovery, similar findings previously reported were also quickly confirmed using GSCope3 and BiKLi. Conclusion GSCope3 can statistically analyze microarray data in the context of any OSML-represented omic knowledge. OSML is not restricted to a specific data type structure, but it can represent a wide range of omic knowledge. It allows us to convert new types of omic knowledge into datasets that can be
This article is available through the Brunel Open Access Publishing Fund. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the inte...
Rasooly, Avraham; Herold, Keith E.
Culture-based methods used for microbial detection and identification are simple to use, relatively inexpensive, and sensitive. However, culture-based methods are too time-consuming for high-throughput testing and too tedious for analysis of samples with multiple organisms and provide little clinical information regarding the pathogen (e.g., antibiotic resistance genes, virulence factors, or strain subtype). DNA-based methods, such as polymerase chain reaction (PCR), overcome some these limit...
Tempelman, Robert J
Experimental designs that efficiently embed a fixed effects treatment structure within a random effects design structure typically require a mixed-model approach to data analyses. Although mixed model software tailored for the analysis of two-color microarray data is increasingly available, much of this software is generally not capable of correctly analyzing the elaborate incomplete block designs that are being increasingly proposed and used for factorial treatment structures. That is, optimized designs are generally unbalanced as it pertains to various treatment comparisons, with different specifications of experimental variability often required for different treatment factors. This paper uses a publicly available microarray dataset, as based upon an efficient experimental design, to demonstrate a proper mixed model analysis of a typical unbalanced factorial design characterized by incomplete blocks and hierarchical levels of variability.
MacInnes Janet I
Full Text Available Abstract Background Actinobacillus pleuropneumoniae, the causative agent of porcine pleuropneumonia, is a highly contagious respiratory pathogen that causes severe losses to the swine industry worldwide. Current commercially-available vaccines are of limited value because they do not induce cross-serovar immunity and do not prevent development of the carrier state. Microarray-based comparative genomic hybridizations (M-CGH were used to estimate whole genomic diversity of representative Actinobacillus pleuropneumoniae strains. Our goal was to identify conserved genes, especially those predicted to encode outer membrane proteins and lipoproteins because of their potential for the development of more effective vaccines. Results Using hierarchical clustering, our M-CGH results showed that the majority of the genes in the genome of the serovar 5 A. pleuropneumoniae L20 strain were conserved in the reference strains of all 15 serovars and in representative field isolates. Fifty-eight conserved genes predicted to encode for outer membrane proteins or lipoproteins were identified. As well, there were several clusters of diverged or absent genes including those associated with capsule biosynthesis, toxin production as well as genes typically associated with mobile elements. Conclusion Although A. pleuropneumoniae strains are essentially clonal, M-CGH analysis of the reference strains of the fifteen serovars and representative field isolates revealed several classes of genes that were divergent or absent. Not surprisingly, these included genes associated with capsule biosynthesis as the capsule is associated with sero-specificity. Several of the conserved genes were identified as candidates for vaccine development, and we conclude that M-CGH is a valuable tool for reverse vaccinology.
Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew
Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed
Lubbock, A. L. R.; Katz, E; Harrison, D J; Overton, I M
Scottish Funding Council (SFC) and the Chief Scientist’s Office (CSO) (to D.H.); Royal Society of Edinburgh Scottish Government Fellowship co-funded by Marie Curie Actions and the UK Medical Research Council (MRC) (to I.O.). Funding for open access charge: Royal Society of Edinburgh. Tissue microarrays (TMAs) allow multiplexed analysis of tissue samples and are frequently used to estimate biomarker protein expression in tumour biopsies. TMA Navigator (www.tmanavigator.org) is an open acces...
The potential of expression analysis using cDNA microarrays to address complex problems in a wide variety of biological contexts is now being realised. A limiting factor in such analyses is often the amount of RNA required, usually tens of micrograms. To address this problem researchers have turned to methods of improving detection sensitivity, either through increasing fluorescent signal output per mRNA molecule or increasing the amount of target available for labelling by use of an amplific...
Gadea Jose; Forment Javier; Santiago Julia; Marques M Carmen; Juarez Jose; Mauri Nuria; Martinez-Godoy M Angeles
Abstract Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-...
Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose
Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA...
Martínez-Godoy, M. Ángeles; Mauri, Nuria; Juárez, José; Marqués, M. Carmen; Santiago, Julia; Forment, Javier; Gadea Vacas, José
Background: Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genomewide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results: We have designed and constructed a publicly available ...
Khatri, Bhagwati; Fielder, Mark; Jones, Gareth; Newell, William; Abu-Oun, Manal; Wheeler, Paul R.
Tuberculosis is a major human and animal disease of major importance worldwide. Genetically, the closely related strains within the Mycobacterium tuberculosis complex which cause disease are well-characterized but there is an urgent need better to understand their phenotypes. To search rapidly for metabolic differences, a working method using Biolog Phenotype MicroArray analysis was developed. Of 380 substrates surveyed, 71 permitted tetrazolium dye reduction, the readout over 7 days in the m...
Kuttapitiya, Anasuya; Assi, Lena; Laing, Ken; Hing, Caroline; Mitchell, Philip; Whitley, Guy; Harrison, Abiola; Howe, Franklyn A; Ejindu, Vivian; Heron, Christine; Sofat, Nidhi
Bone marrow lesions (BMLs) are well described in osteoarthritis (OA) using MRI and are associated with pain, but little is known about their pathological characteristics and gene expression. We evaluated BMLs using novel tissue analysis tools to gain a deeper understanding of their cellular and molecular expression. We recruited 98 participants, 72 with advanced OA requiring total knee replacement (TKR), 12 with mild OA and 14 non-OA controls. Participants were assessed for pain (using Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)) and with a knee MRI (using MOAKS). Tissue was then harvested at TKR for BML analysis using histology and tissue microarray. The mean (SD) WOMAC pain scores were significantly increased in advanced OA 59.4 (21.3) and mild OA 30.9 (20.3) compared with controls 0.5 (1.28) (plesions, bone marrow volume was starkly reduced being replaced by dense fibrous connective tissue, new blood vessels, hyaline cartilage and fibrocartilage. Microarray comparing OA BML and normal bone found a significant difference in expression of 218 genes (p<0.05). The most upregulated genes included stathmin 2, thrombospondin 4, matrix metalloproteinase 13 and Wnt/Notch/catenin/chemokine signalling molecules that are known to constitute neuronal, osteogenic and chondrogenic pathways. Our study is the first to employ detailed histological analysis and microarray techniques to investigate knee OA BMLs. BMLs demonstrated areas of high metabolic activity expressing pain sensitisation, neuronal, extracellular matrix and proinflammatory signalling genes that may explain their strong association with pain. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Full Text Available Abscisic acid (ABA plays a crucial role in plant responses to abiotic stress. To investigate differences in plant responses to salt and ABA stimulus, differences in gene expression in Arabidopsis in response to salt and ABA were compared using an Agilent oligo microarray. A total of 144 and 139 genes were significantly up- and downregulated, respectively, under NaCl stress, while 406 and 381 genes were significantly up- and downregulated, respectively, under ABA stress conditions. In addition, 31 genes were upregulated by both NaCl and ABA stresses, and 23 genes were downregulated by these stressors, suggesting that these genes may play similar roles in plant responses to salt and ABA stress. Gene ontology (GO analysis revealed four subgroups of genes, including genes in the GO categories “Molecular transducer activity”, “Growth”, “Biological adhesion” and “Pigmentation”, which were expressed in response to ABA stress but not NaCl stress. In addition, genes that play specific roles during salt or ABA stress were identified. Our results may help elucidate differences in the response of plants to salt and ABA stress.
Full Text Available High-resolution image guidance for resection of residual tumor cells would enable more precise and complete excision for more effective treatment of cancers, such as medulloblastoma, the most common pediatric brain cancer. Numerous studies have shown that brain tumor patient outcomes correlate with the precision of resection. To enable guided resection with molecular specificity and cellular resolution, molecular probes that effectively delineate brain tumor boundaries are essential. Therefore, we developed a bioinformatics approach to analyze micro-array datasets for the identification of transcripts that encode candidate cell surface biomarkers that are highly enriched in medulloblastoma. The results identified 380 genes with greater than a two-fold increase in the expression in the medulloblastoma compared with that in the normal cerebellum. To enrich for targets with accessibility for extracellular molecular probes, we further refined this list by filtering it with gene ontology to identify genes with protein localization on, or within, the plasma membrane. To validate this meta-analysis, the top 10 candidates were evaluated with immunohistochemistry. We identified two targets, fibrillin 2 and EphA3, which specifically stain medulloblastoma. These results demonstrate a novel bioinformatics approach that successfully identified cell surface and extracellular candidate markers enriched in medulloblastoma versus adjacent cerebellum. These two proteins are high-value targets for the development of tumor-specific probes in medulloblastoma. This bioinformatics method has broad utility for the identification of accessible molecular targets in a variety of cancers and will enable probe development for guided resection.
Full Text Available Over the past decades, gene expression microarrays have been used extensively in biomedical research. However, these high-throughput experiments are affected by technical variation and biases introduced at different levels, such as mRNA processing, labeling, hybridization, scanning and/or imaging. Therefore, data preprocessing is important to minimize these systematic errors in order to identify actual biological changes. The aim of this study was to compare all possible combinations of two normalization, four summarization, and two background correction options, using two different foreground estimates. The results shows that the background correction of the raw median signal and summarization methods used here have no impact in downstream analysis. In contrast, the choice of the normalization method influences the results; the quantile normalization leading to a better biological sensitivity of the data. When Agilent processed signal was considered, regardless of the summarization and normalization options, there were consistently identified more differentially expressed genes (DEG than when raw median signal was used. Nevertheless, the greater number of DEG didn’t result in an improvement of the biological relevance.
Merlin G. Butler
Full Text Available We report our experience with high resolution microarray analysis in infants and young children with developmental disability and/or aberrant behavior enrolled at the Centro Ann Sullivan del Peru in Lima, Peru, a low income country. Buccal cells were collected with cotton swabs from 233 participants for later DNA isolation and identification of copy number variation (deletions/duplications and regions of homozygosity (ROH for estimating consanguinity status in 15 infants and young children (12 males, 3 females; mean age ± SD = 28.1 m ± 7.9 m; age range 14 m–41 m randomly selected for microarray analysis. An adequate DNA yield was found in about one-half of the enrolled participants. Ten participants showed deletions or duplications containing candidate genes reported to impact behavior or cognitive development. Five children had ROHs which could have harbored recessive gene alleles contributing to their clinical presentation. The coefficient of inbreeding was calculated and three participants showed first-second cousin relationships, indicating consanguinity. Our preliminary study showed that DNA isolated from buccal cells using cotton swabs was suboptimal, but yet in a subset of participants the yield was adequate for high resolution microarray analysis and several genes were found that impact development and behavior and ROHs identified to determine consanguinity status.
Brinch, Marie; Hatt, Lotte; Singh, Ripudaman
identified by XY fluorescence in situ hybridization and confirmed by reverse-color fluorescence in situ hybridization were shot off microscope slides by laser capture microdissection. The expression pattern of a subset of expressed genes was compared between fetal cells and maternal blood cells using stem......OBJECTIVE: Different fetal cell types have been found in the maternal blood during pregnancy in the past, but fetal cells are scarce, and the proportions of the different cell types are unclear. The objective of the present study was to identify specific fetal cell markers from fetal cells found...... in the maternal blood circulation at the end of the first trimester. METHOD: Twenty-three fetal cells were isolated from maternal blood by removing the red blood cells by lysis or combining this with removal of large proportions of maternal white blood cells by magnetic-activated cell sorting. Fetal cells...
Full Text Available Abstract Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2 regulated by RUNX1 and STAT3 is correlated to the pathological stage
Full Text Available Abstract Background Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, production and manipulations are limiting factors, affecting data quality. The use of customized DNA microarrays improves overall data quality in many situations, however, only if for these specifically designed microarrays analysis tools are available. Results The IronChip Evaluation Package (ICEP is a collection of Perl utilities and an easy to use data evaluation pipeline for the analysis of microarray data with a focus on data quality of custom-designed microarrays. The package has been developed for the statistical and bioinformatical analysis of the custom cDNA microarray IronChip but can be easily adapted for other cDNA or oligonucleotide-based designed microarray platforms. ICEP uses decision tree-based algorithms to assign quality flags and performs robust analysis based on chip design properties regarding multiple repetitions, ratio cut-off, background and negative controls. Conclusions ICEP is a stand-alone Windows application to obtain optimal data quality from custom-designed microarrays and is freely available here (see "Additional Files" section and at: http://www.alice-dsl.net/evgeniy.vainshtein/ICEP/
Jessie J Hsu
Full Text Available One goal of cluster analysis is to sort characteristics into groups (clusters so that those in the same group are more highly correlated to each other than they are to those in other groups. An example is the search for groups of genes whose expression of RNA is correlated in a population of patients. These genes would be of greater interest if their common level of RNA expression were additionally predictive of the clinical outcome. This issue arose in the context of a study of trauma patients on whom RNA samples were available. The question of interest was whether there were groups of genes that were behaving similarly, and whether each gene in the cluster would have a similar effect on who would recover. For this, we develop an algorithm to simultaneously assign characteristics (genes into groups of highly correlated genes that have the same effect on the outcome (recovery. We propose a random effects model where the genes within each group (cluster equal the sum of a random effect, specific to the observation and cluster, and an independent error term. The outcome variable is a linear combination of the random effects of each cluster. To fit the model, we implement a Markov chain Monte Carlo algorithm based on the likelihood of the observed data. We evaluate the effect of including outcome in the model through simulation studies and describe a strategy for prediction. These methods are applied to trauma data from the Inflammation and Host Response to Injury research program, revealing a clustering of the genes that are informed by the recovery outcome.
Full Text Available Abstract Background Renal cell carcinoma (RCC is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. Methods Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. Results Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR. Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. Conclusions This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most
Zhang, Yijuan; Akintola, Oluwafemi S; Liu, Ken J A; Sun, Bingyun
Microarray (MA) and high-throughput sequencing are two commonly used detection systems for global gene expression profiling. Although these two systems are frequently used in parallel, the differences in their final results have not been examined thoroughly. Transcriptomic analysis of housekeeping (HK) genes provides a unique opportunity to reliably examine the technical difference between these two systems. We investigated here the structure, genome location, expression quantity, microarray probe coverage, as well as biological functions of differentially identified human HK genes by 9 MA and 6 sequencing studies. These in-depth analyses allowed us to discover, for the first time, a subset of transcripts encoding membrane, cell surface and nuclear proteins that were prone to differential identification by the two platforms. We hope that the discovery can aid the future development of these technologies for comprehensive transcriptomic studies. Copyright © 2015 Elsevier B.V. All rights reserved.
Alfred O. Hero
Full Text Available This paper introduces a statistical methodology for the identification of differentially expressed genes in DNA microarray experiments based on multiple criteria. These criteria are false discovery rate (FDR, variance-normalized differential expression levels (paired t statistics, and minimum acceptable difference (MAD. The methodology also provides a set of simultaneous FDR confidence intervals on the true expression differences. The analysis can be implemented as a two-stage algorithm in which there is an initial screen that controls only FDR, which is then followed by a second screen which controls both FDR and MAD. It can also be implemented by computing and thresholding the set of FDR P values for each gene that satisfies the MAD criterion. We illustrate the procedure to identify differentially expressed genes from a wild type versus knockout comparison of microarray data.
Yin, Aihua; Zhang, Xiangzhong; Wu, Jing; Du, Li; He, Tianwen; Zhang, Xiaozhuang
The noninvasive prenatal diagnosis procedures that are currently used to detect genetic diseases do not achieve desirable levels of sensitivity and specificity. Recently, fetal methylated DNA biomarkers in maternal peripheral blood have been explored for the noninvasive prenatal detection of genetic disorders. However, such efforts have covered only chromosomal aneuploidy, and fetal methylated DNA biomarkers in maternal whole blood for detecting single-gene diseases remain to be discovered. To address this issue, we systematically screened significantly hypermethylated genes in fetal tissues and compared them with maternal peripheral blood potential in an attempt to detect fetal genes in maternal peripheral blood. First, the methylated-CpG island recovery assay combined with a CpG island array was performed for four fetus-toward placental tissues and the corresponding maternal peripheral bloods. Subsequently, direct bisulfite sequencing and combined bisulfite restriction analysis (COBRA) were carried out to validate the methylation status of the hypermethylated genes that were identified by the microarray analysis. Three hundred and ten significantly hypermethylated genes in the placental tissues were detected by microarray. From the top 15 hypermethylated genes detected by microarray, two were selected for sequencing validation in placental tissue and chorionic villus samples and four were selected for COBRA validation in four placental tissues, ten amniotic fluids and five chorionic villus samples. The six selected genes were confirmed to be hypermethylated in placental tissue and chorionic villus samples, but methylation of the genes could not be detected in the amniotic fluids. Of the many hypermethylated genes and methylation sites that were found in the fetal tissues, some have great potential to be developed into molecular markers for noninvasive prenatal diagnosis of monogenic disorders. Further clinical studies are warranted to confirm these findings.
Ricke, Steven C; Khatiwara, Anita; Kwon, Young Min
Salmonellosis in the United States is one of the most costly foodborne diseases. Given that Salmonella can originate from a wide variety of environments, reduction of this organism at all stages of poultry production is critical. Salmonella species can encounter various environmental stress conditions that can dramatically influence their survival and virulence. Previous knowledge of Salmonella species genomic regulation of metabolism and physiology in relation to poultry is based on limited information of a few well-characterized genes. Consequently, although there is some information about environmental signals that control Salmonella growth and pathogenesis, much still remains unknown. Advancements in DNA sequencing technologies revolutionized the way bacteria were studied and molecular tools such as microarrays have subsequently been used for comprehensive transcriptomic analysis of Salmonella. With microarray analysis, the expression levels of each single gene in the Salmonella genome can be directly assessed and previously unknown genetic systems that are required for Salmonella growth and survival in the poultry production cycle can be elucidated. This represents an opportunity for development of novel approaches for limiting Salmonella establishment in all phases of poultry production. In this review, recent advances in transcriptome-microarray technologies that are facilitating a better understanding of Salmonella biology in poultry production and processing are discussed.
Song, Yan; Ahn, Jinsoo; Suh, Yeunsu; Davis, Michael E; Lee, Kichoon
Understanding the tissue-specific pattern of gene expression is critical in elucidating the molecular mechanisms of tissue development, gene function, and transcriptional regulations of biological processes. Although tissue-specific gene expression information is available in several databases, follow-up strategies to integrate and use these data are limited. The objective of the current study was to identify and evaluate novel tissue-specific genes in human and mouse tissues by performing comparative microarray database analysis and semi-quantitative PCR analysis. We developed a powerful approach to predict tissue-specific genes by analyzing existing microarray data from the NCBI's Gene Expression Omnibus (GEO) public repository. We investigated and confirmed tissue-specific gene expression in the human and mouse kidney, liver, lung, heart, muscle, and adipose tissue. Applying our novel comparative microarray approach, we confirmed 10 kidney, 11 liver, 11 lung, 11 heart, 8 muscle, and 8 adipose specific genes. The accuracy of this approach was further verified by employing semi-quantitative PCR reaction and by searching for gene function information in existing publications. Three novel tissue-specific genes were discovered by this approach including AMDHD1 (amidohydrolase domain containing 1) in the liver, PRUNE2 (prune homolog 2) in the heart, and ACVR1C (activin A receptor, type IC) in adipose tissue. We further confirmed the tissue-specific expression of these 3 novel genes by real-time PCR. Among them, ACVR1C is adipose tissue-specific and adipocyte-specific in adipose tissue, and can be used as an adipocyte developmental marker. From GEO profiles, we predicted the processes in which AMDHD1 and PRUNE2 may participate. Our approach provides a novel way to identify new sets of tissue-specific genes and to predict functions in which they may be involved.
Full Text Available Abstract Background Microarray chips are being rapidly deployed as a major tool in genomic research. To date most of the analysis of the enormous amount of information provided on these chips has relied on clustering techniques and other standard statistical procedures. These methods, particularly with regard to cancer patient prognosis, have generally been inadequate in providing the reduced gene subsets required for perfect classification. Results Networks trained on microarray data from DLBCL lymphoma patients have, for the first time, been able to predict the long-term survival of individual patients with 100% accuracy. Other networks were able to distinguish DLBCL lymphoma donors from other donors, including donors with other lymphomas, with 99% accuracy. Differentiating the trained network can narrow the gene profile to less than three dozen genes for each classification. Conclusions Here we show that artificial neural networks are a superior tool for digesting microarray data both with regard to making distinctions based on the data and with regard to providing very specific reference as to which genes were most important in making the correct distinction in each case.
Venu, R C; Jia, Yulin; Gowda, Malali; Jia, Melissa H; Jantasuriyarat, Chatchawan; Stahlberg, Eric; Li, Huameng; Rhineheart, Andrew; Boddhireddy, Prashanth; Singh, Pratibha; Rutger, Neil; Kudrna, David; Wing, Rod; Nelson, James C; Wang, Guo-Liang
Sheath blight caused by the fungal pathogen Rhizoctonia solani is an emerging problem in rice production worldwide. To elucidate the molecular basis of rice defense to the pathogen, RNA isolated from R. solani-infected leaves of Jasmine 85 was used for both RL-SAGE library construction and microarray hybridization. RL-SAGE sequence analysis identified 20,233 and 24,049 distinct tags from the control and inoculated libraries, respectively. Nearly half of the significant tags (> or =2 copies) from both libraries matched TIGR annotated genes and KOME full-length cDNAs. Among them, 42% represented sense and 7% antisense transcripts, respectively. Interestingly, 60% of the library-specific (> or =10 copies) and differentially expressed (>4.0-fold change) tags were novel transcripts matching genomic sequence but not annotated genes. About 70% of the genes identified in the SAGE libraries showed similar expression patterns (up or down-regulated) in the microarray data obtained from three biological replications. Some candidate RL-SAGE tags and microarray genes were located in known sheath blight QTL regions. The expression of ten differentially expressed RL-SAGE tags was confirmed with RT-PCR. The defense genes associated with resistance to R. solani identified in this study are useful genomic materials for further elucidation of the molecular basis of the defense response to R. solani and fine mapping of target sheath blight QTLs.
McDaniel Lisa D
Full Text Available Abstract Background Chronic lymphocytic leukemia (CLL is a highly variable disease with life expectancies ranging from months to decades. Cytogenetic findings play an integral role in defining the prognostic significance and treatment for individual patients. Results We have evaluated 25 clinical cases from a tertiary cancer center that have an established diagnosis of CLL and for which there was prior cytogenetic and/or fluorescence in situ hybridization (FISH data. We performed microarray-based comparative genomic hybridization (aCGH using a bacterial artificial chromosome (BAC-based microarray designed for the detection of known constitutional genetic syndromes. In 15 of the 25 cases, aCGH detected all copy number imbalances identified by prior cytogenetic and/or FISH studies. For the majority of those not detected, the aberrations were present at low levels of mosaicism. Furthermore, for 15 of the 25 cases, additional abnormalities were detected. Four of those cases had deletions that mapped to intervals implicated in inherited predisposition to CLL. For most cases, aCGH was able to detect abnormalities present in as few as 10% of cells. Although changes in ploidy are not easily discernable by aCGH, results for two cases illustrate the detection of additional copy gains and losses present within a mosaic tetraploid cell population. Conclusions Our results illustrate the successful evaluation of CLL using a microarray optimized for the interrogation of inherited disorders and the identification of alterations with possible relevance to CLL susceptibility.
Steffen Maak, Diana Boettcher, Jens Tetens, Monika Wensch-Dorendorf, Gerd Nürnberg, Klaus Wimmers, Hermann H. Swalve, Georg Thaller
Full Text Available The congenital splay leg syndrome in piglets is characterized by a temporarily impaired functionality of the hind leg muscles immediately after birth. Etiology and pathogenetic mechanisms for the disease are still not well understood. We compared genome wide gene expression of three hind leg muscles (M. adductores, M. gracilis and M. sartorius between affected piglets and their healthy littermates with the GeneChip® Porcine Genome Array (Affymetrix in order to identify candidate genes for the disease. Data analysis with standard algorithms revealed no significant differences between both groups. By application of an alternative approach, we identified 63 transcripts with differences in two muscles and 5 genes differing between the groups in three muscles. The expression of six selected genes (SQSTM1, SSRP1, DDIT4, ENAH, MAF, and PDK4 was investigated with SYBRGreen RT - Real time PCR. The differences obtained with the microarray analysis could be confirmed and demonstrate the validity of the alternative approach to microarray data analysis. Four genes with different expression levels in at least two muscles (SQSTM1, SSRP1, DDIT4, and MAF are assigned to transcriptional cascades related to cell death and may thus indicate pathways for further investigations on congenital splay leg in piglets.
ZENG Yue-bin; QIAN Yuan-shu; MA Lian; GU Hong-ni
Background Candida albicans is the most frequently seen opportunistic human fungal pathogen. Terbinafine is an allylamine antifungal agent that has been proven to have high clinical efficacy in the therapy of fungal infections, the mechanism of action of terbinafine involves the specific inhibition of fungal squalene epoxidase, resulting in ergosterol deficiency and accumulation of intracellular squalene. We used cDNA microarray analysis technology to monitor global expression profile changes of Candida albicans genes in response to terbinafine treatment, and we anticipated a panoramic view of the responses of Candida albicans cells to the representatives of allylamine antifungal agents at the molecular level in an effort to identify drug class-specific and mechanism-independent changes in gene expression.Methods Candida albicans strain ATCC 90028 was exposed to either medium alone or terbinafine at a concentration equivalent to the 1/2 minimal inhibitory concentrations (MICs, 4 mg/L) for 90 minutes. RNA was isolated and gene expression profiles were compared to identify the changes in the gene expression profile using a cDNA microarray analysis. Differential expression of 10 select genes detected by cDNA microarray analysis was confirmed by semi-quantitative reverse transcription-polymerase chain reaction (RT-PCR).Results A total of 222 genes were found to be responsive to terbinafine, including 121 up-regulated genes and 101 down-regulated genes. These included genes encoding membrane transport proteins belonging to the members of the ATP-binding cassette (ABC) or major facilitator superfamily (MFS; CDR1, AGP2, GAP6, PHO84, HOL3, FCY23, VCX1),genes involved in stress response and detoxification (CDR1, AGP2, HOL3), and gene involved in the ergosterol biosynthesis pathway (ERG12). The results of semi-quantitative RT-PCR were consistent with that of the cDNA microarray analysis.Conclusions The up-regulation of the gene encoding the multidrug resistance efflux pump
Full Text Available Pituitary adenomas, monoclonal in origin, are the most common intracranial neoplasms. Altered gene expression as well as somatic mutations is detected frequently in pituitary adenomas. The purpose of this study was to detect differentially expressed genes (DEGs and biological processes during tumor formation of pituitary adenomas. We performed an integrated analysis of publicly available GEO datasets of pituitary adenomas to identify DEGs between pituitary adenomas and normal control (NC tissues. Gene function analysis including Gene Ontology (GO, Kyoto Encyclopedia of Genes and Genomes (KEGG pathway enrichment analysis, and protein-protein interaction (PPI networks analysis was conducted to interpret the biological role of those DEGs. In this study we detected 3994 DEGs (2043 upregulated and 1951 downregulated in pituitary adenoma through an integrated analysis of 5 different microarray datasets. Gene function analysis revealed that the functions of those DEGs were highly correlated with the development of pituitary adenoma. This integrated analysis of microarray data identified some genes and pathways associated with pituitary adenoma, which may help to understand the pathology underlying pituitary adenoma and contribute to the successful identification of therapeutic targets for pituitary adenoma.
Full Text Available BACKGROUND: Array Comparative Genomic Hybridization (a-CGH is a powerful molecular cytogenetic tool to detect genomic imbalances and study disease mechanism and pathogenesis. We report our experience with the clinical implementation of this high resolution human genome analysis, referred to as Chromosomal Microarray Analysis (CMA. METHODS AND FINDINGS: CMA was performed clinically on 2513 postnatal samples from patients referred with a variety of clinical phenotypes. The initial 775 samples were studied using CMA array version 4 and the remaining 1738 samples were analyzed with CMA version 5 containing expanded genomic coverage. Overall, CMA identified clinically relevant genomic imbalances in 8.5% of patients: 7.6% using V4 and 8.9% using V5. Among 117 cases referred for additional investigation of a known cytogenetically detectable rearrangement, CMA identified the majority (92.5% of the genomic imbalances. Importantly, abnormal CMA findings were observed in 5.2% of patients (98/1872 with normal karyotypes/FISH results, and V5, with expanded genomic coverage, enabled a higher detection rate in this category than V4. For cases without cytogenetic results available, 8.0% (42/524 abnormal CMA results were detected; again, V5 demonstrated an increased ability to detect abnormality. Improved diagnostic potential of CMA is illustrated by 90 cases identified with 51 cryptic microdeletions and 39 predicted apparent reciprocal microduplications in 13 specific chromosomal regions associated with 11 known genomic disorders. In addition, CMA identified copy number variations (CNVs of uncertain significance in 262 probands; however, parental studies usually facilitated clinical interpretation. Of these, 217 were interpreted as familial variants and 11 were determined to be de novo; the remaining 34 await parental studies to resolve the clinical significance. CONCLUSIONS: This large set of clinical results demonstrates the significantly improved sensitivity
Several mechanisms are responsible for the acquired fluconazole (FLC) resistance in Candida albicans. In this study, we developed a FLC-resistant C. albicans strain through serial cultures of a FLC-susceptible C. albicans strain with inhibitory concentrations of FLC. Complimen-tary DNA microarray analysis and real-time reverse tran-scription-polymerase chain reaction were used to investi-gate gene expression changes during the acquisition of azole resistance in the susceptible parental strain and the resis-tant daughter strain. The differentially expressed genes rep-resented functions as diverse as transporters (e.g. CDRI, PDR17), ergosterol biosynthesis (e.g. ERG2, ERG9), sterol metabolism (e.g. ARE2, IPF6464), energy metabolism (e.g. ADH3, AOX2) and transcription factors (e.g. FCR1, ECM22). Functional analysis revealed that energy-depen-dent efflux activity of membrane transporters increased and that ergosterol content decreased with the accumulation of sterol intermediates in the resistant strain as compared with the susceptible strain. We found that a point mutation (N977K) in transcription factor TAC1 that resulted in hy-peractivity of Tac1 could be the reason for overexpression of CDR1, CDR2, and PDR17 in the resistant strain.Furthermore, a single amino acid difference (DI9E) in ERG3 that led to the inactivation of Erg3 could account for both sterol precursor accumulation and the changes in the ex-pression of ergosterol biosynthesis genes in this resistant strain. These findings expand the understanding of poten-tial novel molecular targets of FLC resistance in clinical C.albicans isolates.
Li, Meng; Zhi, Liqiang; Zhang, Zhi; Bian, Weiguo; Qiu, Yusheng
The aim of the present study was to investigate the molecular circuitry of osteoarthritis (OA) and identify more potential target genes for OA treatment. Microarray data of GSE32317 was downloaded from the National Center for Biotechnology Information Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified in samples of synovial membrane from patients with early stage of knee OA (OA_Early) and late stage of knee OA (OA_End) that were compared with healthy specimens. Bioinformatics analysis was applied to analyze the significant functions and pathways that were enriched by the common DEGs identified in OA_Early and OA_End samples. Furthermore, a protein‑protein interaction (PPI) network was constructed and significant modules were extracted. Transcription factors (TFs) that could regulate genes in the significant modules were identified. A total of 1,207 and 1,575 DEGs were identified in OA_Early and OA_End samples compared with healthy samples, respectively. A total of 740 genes were upregulated and 308 genes were downregulated across the OA_Early and OA_End samples. These common DEGs were enriched in different gene ontology terms and pathways, such as immune response. Angiotensinogen (AGT) and C‑X‑C motif chemokine ligand 12 (CXCL12) were identified to be hub proteins in the PPI network or in the selected module 1. In addition, the DEG lysine demethylase 2B (KDM2B) was identified as a TF that can regulate genes in the significant modules 2 and 3. In conclusion, the present study has identified AGT, CXCL12 and KDM2B as potentially essential genes associated with the pathogenesis of knee OA.
Hai-Tao Wang; Jian-Ping Kong; Fang Ding; Xiu-Qin Wang; Ming-Rong Wang; Lian-Xin Liu; Min Wu; Zhi-Hua Liu
AIM: To obtain human esophageal cancer cell EC9706 stably expressed epithelial membrane protein-1 (EMP-1) with integrated eukaryotic plasmid harboring the open reading frame (ORF) of human EMP-1, and then to study the mechanism by which EMP-1 exerts its diverse cellular action on cell proliferation and altered gene profile by exploring the effect of EMP-1.METHODS: The authors first constructed pcDNA3.1/mychis expression vector harboring the ORF of EMP-1 and then transfected it into human esophageal carcinoma cell line EC9706. The positive clones were analyzed by Western blot and RT-PCR. Moreover, the cell growth curve was observed and the cell cycle was checked by FACS technique. Using cDNA microarray technology, the authors compared the gene expression pattern in positive clones with control. To confirm the gene expression profile, semi-quantitative RT-PCR was carried out for 4 of the randomly picked differentially expressed genes. For those differentially expressed genes,classification was performed according to their function and cellular component.RESULTS: Human EMP-1 gene can be stably expressed in ECg706 cell line transfected with human EMP-1. The authors found the cell growth decreased, among which S phase was arrested and G1 phase was prolonged in the transfected positive clones. By cDNA microarray analysis, 35 genes showed an over 2.0 fold change in expression level after transfection, with 28 genes being consistently up-regulated and 7 genes being down-regulated. Among the classified genes, almost half of the induced genes (13 out of 28 genes) were related to cell signaling, cell communication and particularly to adhesion.CONCLUSION: Overexpression of human EMP-1 gene can inhibit the proliferation of EC9706 cell with S phase arrested and G1 phase prolonged. The cDNA microarray analysis suggested that EMP-1 may be one of regulators involved incell signaling, cell communication and adhesion regulators.
Full Text Available Abstract Background Recent transcriptomic analyses in mammals have uncovered the widespread occurrence of endogenous antisense transcripts, termed natural antisense transcripts (NATs. NATs are transcribed from the opposite strand of the gene locus and are thought to control sense gene expression, but the mechanism of such regulation is as yet unknown. Although several thousand potential sense-antisense pairs have been identified in mammals, examples of functionally characterized NATs remain limited. To identify NAT candidates suitable for further functional analyses, we performed DNA microarray-based NAT screening using mouse adult normal tissues and mammary tumors to target not only the sense orientation but also the complementary strand of the annotated genes. Results First, we designed microarray probes to target the complementary strand of genes for which an antisense counterpart had been identified only in human public cDNA sources, but not in the mouse. We observed a prominent expression signal from 66.1% of 635 target genes, and 58 genes of these showed tissue-specific expression. Expression analyses of selected examples (Acaa1b and Aard confirmed their dynamic transcription in vivo. Although interspecies conservation of NAT expression was previously investigated by the presence of cDNA sources in both species, our results suggest that there are more examples of human-mouse conserved NATs that could not be identified by cDNA sources. We also designed probes to target the complementary strand of well-characterized genes, including oncogenes, and compared the expression of these genes between mammary cancerous tissues and non-pathological tissues. We found that antisense expression of 95 genes of 404 well-annotated genes was markedly altered in tumor tissue compared with that in normal tissue and that 19 of these genes also exhibited changes in sense gene expression. These results highlight the importance of NAT expression in the regulation
Cianzio Silvia R
Full Text Available Abstract Background Iron is one of fourteen mineral elements required for proper plant growth and development of soybean (Glycine max L. Merr.. Soybeans grown on calcareous soils, which are prevalent in the upper Midwest of the United States, often exhibit symptoms indicative of iron deficiency chlorosis (IDC. Yield loss has a positive linear correlation with increasing severity of chlorotic symptoms. As soybean is an important agronomic crop, it is essential to understand the genetics and physiology of traits affecting plant yield. Soybean cultivars vary greatly in their ability to respond successfully to iron deficiency stress. Microarray analyses permit the identification of genes and physiological processes involved in soybean's response to iron stress. Results RNA isolated from the roots of two near isogenic lines, which differ in iron efficiency, PI 548533 (Clark; iron efficient and PI 547430 (IsoClark; iron inefficient, were compared on a spotted microarray slide containing 9,728 cDNAs from root specific EST libraries. A comparison of RNA transcripts isolated from plants grown under iron limiting hydroponic conditions for two weeks revealed 43 genes as differentially expressed. A single linkage clustering analysis of these 43 genes showed 57% of them possessed high sequence similarity to known stress induced genes. A control experiment comparing plants grown under adequate iron hydroponic conditions showed no differences in gene expression between the two near isogenic lines. Expression levels of a subset of the differentially expressed genes were also compared by real time reverse transcriptase PCR (RT-PCR. The RT-PCR experiments confirmed differential expression between the iron efficient and iron inefficient plants for 9 of 10 randomly chosen genes examined. To gain further insight into the iron physiological status of the plants, the root iron reductase activity was measured in both iron efficient and inefficient genotypes for plants
Chatziioannou, Aristotelis; Moulos, Panagiotis
Microarray technology allows the survey of gene expression at a global level by measuring mRNA abundance. However, the grand complexity characterizing a microarray experiment entails the development of computationally powerful tools apt for probing the biological problem studied. Here we propose a suite for flexible, adaptable to a wide range of possible needs of the biological end-user, data-driven interpretation of microarray experiments. The suite is implemented in MATLAB and is making use of two modules, able to perform all steps of typical microarray data analysis starting from data standardization and normalization up to statistical selection and pathway analysis utilizing Gene Ontology Term annotations for the species genomes interrogated, whereas due to its modular structure it is scalable thus enabling the incorporation or its seamless assembly with other existing tools.
Kim, Il-Jin; Kang, Hio Chung
DNA microarray technology permits simultaneous analysis of thousands of DNA sequences for genomic research and diagnostics applications. Microarray technology represents the most recent and exciting advance in the application of hybridization-based technology for biological sciences analysis. This review focuses on the classification (oligonucleotide vs. cDNA) and application (mutation-genotyping vs. gene expression) of microarrays. Oligonucleotide microarrays can be used both in mutation-genotyping and gene expression analysis, while cDNA microarrays can only be used in gene expression analysis. We review microarray mutation analysis, including examining the use of three oligonucleotide microarrays developed in our laboratory to determine mutations in RET, β-catenin and K-ras genes. We also discuss the use of the Affymetrix GeneChip in mutation analysis. We review microarray gene expression analysis, including the classifying of such studies into four categories: class comparison, class prediction, class discovery and identification of biomarkers. PMID:20368836
Raddatz, Barbara B; Spitzbarth, Ingo; Matheis, Katja A; Kalkuhl, Arno; Deschl, Ulrich; Baumgärtner, Wolfgang; Ulrich, Reiner
High-throughput, genome-wide transcriptome analysis is now commonly used in all fields of life science research and is on the cusp of medical and veterinary diagnostic application. Transcriptomic methods such as microarrays and next-generation sequencing generate enormous amounts of data. The pathogenetic expertise acquired from understanding of general pathology provides veterinary pathologists with a profound background, which is essential in translating transcriptomic data into meaningful biological knowledge, thereby leading to a better understanding of underlying disease mechanisms. The scientific literature concerning high-throughput data-mining techniques usually addresses mathematicians or computer scientists as the target audience. In contrast, the present review provides the reader with a clear and systematic basis from a veterinary pathologist's perspective. Therefore, the aims are (1) to introduce the reader to the necessary methodological background; (2) to introduce the sequential steps commonly performed in a microarray analysis including quality control, annotation, normalization, selection of differentially expressed genes, clustering, gene ontology and pathway analysis, analysis of manually selected genes, and biomarker discovery; and (3) to provide references to publically available and user-friendly software suites. In summary, the data analysis methods presented within this review will enable veterinary pathologists to analyze high-throughput transcriptome data obtained from their own experiments, supplemental data that accompany scientific publications, or public repositories in order to obtain a more in-depth insight into underlying disease mechanisms.
Dondorp Arjen M
Full Text Available Abstract Background A number of molecular tools have been developed to monitor the emergence and spread of anti-malarial drug resistance to Plasmodium falciparum. One of the major obstacles to the wider implementation of these tools is the absence of practical methods enabling high throughput analysis. Here a new Zip-code array is described, called FlexiChip, linked to a dedicated software program, which largely overcomes this problem. Methods Previously published microarray probes detecting single-nucleotide polymorphisms (SNP associated with parasite resistance to anti-malarial drugs (ResMalChip were adapted for a universal microarray FlexiChip format. To evaluate the overall sensitivity of the FlexiChip package (microarray + software, the results of FlexiChip were compared to ResMalChip microarray, using the same extension probes and with the same PCR products. In both cases, sequence results were used as gold standard to calculate sensitivity and specificity. FlexiChip results obtained with a set of field isolates were then compared to those assessed in an independent reference laboratory. Results The FlexiChip package gave results identical to the ResMalChip results in 92.7% of samples (kappa coefficient 0.8491, with a standard error 0.021 and had a sensitivity of 95.88% and a specificity of 97.68% compared to the sequencing as the reference method. Moreover the method performed well compared to the results obtained in the reference laboratories, with 99.7% of identical results (kappa coefficient 0.9923, S.E. 0.0523. Conclusion Microarrays could be employed to monitor P. falciparum drug resistance markers with greater cost effectiveness and the possibility for high throughput analysis. The FlexiChip package is a promising tool for use in poor resource settings of malaria endemic countries.
Hedjazi, Lyamine; Le Lann, Marie-Veronique; Kempowsky, Tatiana; Dalenc, Florence; Aguilar-Martin, Joseph; Favre, Gilles
Microarray profiling has recently generated the hope to gain new insights into breast cancer biology and thereby improve the performance of current prognostic tools. However, it also poses several serious challenges to classical data analysis techniques related to the characteristics of resulting data, mainly high dimensionality and low signal-to-noise ratio. Despite the tremendous research work performed to handle the first challenge in the feature selection framework, very little attention has been directed to address the second one. We propose in this article to address both issues simultaneously based on symbolic data analysis capabilities in order to derive more accurate genetic marker-based prognostic models. In particular, interval data representation is employed to model various uncertainties in microarray measurements. A recent feature selection algorithm that handles symbolic interval data is used then to derive a genetic signature. The predictive value of the derived signature is then assessed by following a rigorous experimental setup and compared with existing prognostic approaches in terms of predictive performance and estimated survival probability. It is shown that the derived signature (GenSym) performs significantly better than other prognostic models, including the 70-gene signature, St. Gallen, and National Institutes of Health criteria.
Hanène Ayari; Giampiero Bricca
Classic characteristics are poor predictors of the risk of thromboembolism. Thus, better markers for the carotid atheroma plaque formation and symptom causing are needed. Our objective was to study by microarray analysis gene expression of genes involved in homeostasis of iron and heme in carotid atheroma plaque from the same patient. mRNA gene expression was measured by an Affymetrix GeneChip Human Gene 1.0 ST arrays (Affymetrix, Santa Clara, CA, USA) using RNA prepared from 68 specimens of endarteriectomy from 34 patients. Two genes involved in iron-heme homeostasis, CD163 and heme oxygenase (HO-1), were analysed in 34 plaques. CD163 (2.18, =1.45E−08) and HO-1 (fold-change 2.67, =2.07E−09) mRNAs were induced. We suggest that atheroma plaques show a more pronounced induction of CD163 and HO-1. Although further evidence is needed, our results support previous data. To our knowledge, this is the first report comparing gene expression between intact arterial tissue and carotid plaque using microarray analysis.
Kruse, Jacqueline J C M; te Poele, Johannes A M; Velds, Arno; Kerkhoven, Ron M; Boersma, Liesbeth J; Russell, Nicola S; Stewart, Fiona A
Irradiation of the kidney induces dose-dependent, progressive renal functional impairment, which is partly mediated by vascular damage. The molecular mechanisms underlying the development of radiation-induced nephropathy are unclear. Given the complexity of radiation-induced responses, microarrays may offer new opportunities to identify a wider range of genes involved in the development of radiation injury. The aim of the present study was to determine whether microarrays are a useful tool for identifying time-related changes in gene expression and potential mechanisms of radiation-induced nephropathy. Microarray experiments were performed using amplified RNA from irradiated mouse kidneys (1 x 16 Gy) and from sham-irradiated control tissue at different intervals (1-30 weeks) after irradiation. After normalization procedures (using information from straight-color, color-reverse and self-self experiments), the differentially expressed genes were identified. Control and repeat experiments were done to confirm that the observations were not artifacts of the array procedure (RNA amplification, probe synthesis, hybridizations and data analysis). To provide independent confirmation of microarray data, semi-quantitative PCR was performed on a selection of genes. At 1 week after irradiation (before the onset of vascular and functional damage), 16 genes were significantly up-regulated and 9 genes were down-regulated. During the period of developing nephropathy (10 to 20 weeks), 31 and 42 genes were up-regulated and 9 and 4 genes were down-regulated. At the later time of 30 weeks, the vast majority of differentially expressed genes (191 out of 203) were down-regulated. Potential genes of interest included TSA-1 (also known as Ly6e) and Jagged 1 (Jag1). Increased expression of TSA-1, a member of the Ly-6 family, has previously been reported in response to proteinuria. Jagged 1, a ligand for the Notch receptor, is known to play a role in angiogenesis, and is particularly
Gopalan, Banu; Posse, Christian; Sanfilippo, Antonio P.; Stenzel-Poore, Mary; Stevens, S.L.; Castano, Jose; Beagley, Nathaniel; Riensche, Roderick M.; Baddeley, Bob; Simon, R.P.; Pustejovsky, James
Expression arrays are introducing a paradigmatic change in biology by shifting experimental approaches from single gene studies to genome-level analysis, monitoring the ex-pression levels of several thousands of genes in parallel. The massive amounts of data obtained from the microarray data needs to be integrated and interpreted to infer biological meaning within the context of information-rich pathways. In this paper, we present a methodology that integrates textual information with annotations from cross-referenced ontolo-gies to map genes to pathways in a semi-automated way. We illustrate this approach and compare it favorably to other tools by analyzing the gene expression changes underlying the biological phenomena related to stroke. Stroke is the third leading cause of death and a major disabler in the United States. Through years of study, researchers have amassed a significant knowledge base about stroke, and this knowledge, coupled with new technologies, is providing a wealth of new scientific opportunities. The potential for neu-roprotective stroke therapy is enormous. However, the roles of neurogenesis, angiogenesis, and other proliferative re-sponses in the recovery process following ischemia and the molecular mechanisms that lead to these processes still need to be uncovered. Improved annotation of genomic and pro-teomic data, including annotation of pathways in which genes and proteins are involved, is required to facilitate their interpretation and clinical application. While our approach is not aimed at replacing existing curated pathway databases, it reveals multiple hidden relationships that are not evident with the way these databases analyze functional groupings of genes from the Gene Ontology.
Full Text Available It is generally believed that the infant's microbiota is established during the first 1-2 years of life. However, there is scarce data on its characterization and its comparison to the adult-like microbiota in consecutive years.To characterize and compare the intestinal microbiota in healthy young children (1-4 years and healthy adults from the North Carolina region in the U.S. using high-throughput bacterial phylogenetic microarray analysis.Detailed characterization and comparison of the intestinal microbiota of healthy children aged 1-4 years old (n = 28 and healthy adults of 21-60 years (n = 23 was carried out using the Human Intestinal Tract Chip (HITChip phylogenetic microarray targeting the V1 and V6 regions of 16S rRNA and quantitative PCR.The HITChip microarray data indicate that Actinobacteria, Bacilli, Clostridium cluster IV and Bacteroidetes are the predominant phylum-like groups that exhibit differences between young children and adults. The phylum-like group Clostridium cluster XIVa was equally predominant in young children and adults and is thus considered to be established at an early age. The genus-like level show significant 3.6 fold (higher or lower differences in the abundance of 26 genera between young children and adults. Young U.S. children have a significantly 3.5-fold higher abundance of Bifidobacterium species than the adults from the same location. However, the microbiota of young children is less diverse than that of adults.We show that the establishment of an adult-like intestinal microbiota occurs at a later age than previously reported. Characterizing the microbiota and its development in the early years of life may help identify 'windows of opportunity' for interventional strategies that may promote health and prevent or mitigate disease processes.
Adorján, Péter; Distler, Jürgen; Lipscher, Evelyne; Model, Fabian; Müller, Jürgen; Pelet, Cécile; Braun, Aron; Florl, Andrea R.; Gütig, David; Grabs, Gabi; Howe, André; Kursar, Mischo; Lesche, Ralf; Leu, Erik; Lewin, André
Aberrant DNA methylation of CpG sites is among the earliest and most frequent alterations in cancer. Several studies suggest that aberrant methylation occurs in a tumour type-specific manner. However, large-scale analysis of candidate genes has so far been hampered by the lack of high throughput assays for methylation detection. We have developed the first microarray-based technique which allows genome-wide assessment of selected CpG dinucleotides as well as quantification of methylation at e...
C.D. Rogers; N. Fukushima; N. Sato; C. Shi; N. Prasad; S.R. Hustinx; H. Matsubayashi; M. Canto; J.R. Eshleman; R.H. Hruban; M. Goggins
Background: The gene expression profile of pancreatic cancer is significantly different from that of normal pancreas. Differences in gene expression are detectable using microarrays, but microarrays have traditionally been applied to pancreatic cancer tissue obtained from surgical resection. We hypo
Park, Sungjin; Gildersleeve, Jeffrey C; Blixt, Klas Ola;
In the last decade, carbohydrate microarrays have been core technologies for analyzing carbohydrate-mediated recognition events in a high-throughput fashion. A number of methods have been exploited for immobilizing glycans on the solid surface in a microarray format. This microarray-based technol...
Full Text Available DNA Microarray is the emerging technique in Biotechnology. The many varieties of DNA microarray or DNA chip devices and systems are described along with their methods for fabrication and their use. It also includes screening and diagnostic applications. The DNA microarray hybridization applications include the important areas of gene expression analysis and genotyping for point mutations, single nucleotide polymorphisms (SNPs, and short tandem repeats (STRs. In addition to the many molecular biological and genomic research uses, this review covers applications of microarray devices and systems for pharmacogenomic research and drug discovery, infectious and genetic disease and cancer diagnostics, and forensic and genetic identification purposes.
Wang, Liangjiang; Srivastava, Anand K; Schwartz, Charles E
Background Microarray gene expression data are accumulating in public databases. The expression profiles contain valuable information for understanding human gene expression patterns. However, the effective use of public microarray data requires integrating the expression profiles from heterogeneous sources. Results In this study, we have compiled a compendium of microarray expression profiles of various human tissue samples. The microarray raw data generated in different research laboratorie...
Full Text Available Abstract Background Soybeans grown in the upper Midwestern United States often suffer from iron deficiency chlorosis, which results in yield loss at the end of the season. To better understand the effect of iron availability on soybean yield, we identified genes in two near isogenic lines with changes in expression patterns when plants were grown in iron sufficient and iron deficient conditions. Results Transcriptional profiles of soybean (Glycine max, L. Merr near isogenic lines Clark (PI548553, iron efficient and IsoClark (PI547430, iron inefficient grown under Fe-sufficient and Fe-limited conditions were analyzed and compared using the Affymetrix® GeneChip® Soybean Genome Array. There were 835 candidate genes in the Clark (PI548553 genotype and 200 candidate genes in the IsoClark (PI547430 genotype putatively involved in soybean's iron stress response. Of these candidate genes, fifty-eight genes in the Clark genotype were identified with a genetic location within known iron efficiency QTL and 21 in the IsoClark genotype. The arrays also identified 170 single feature polymorphisms (SFPs specific to either Clark or IsoClark. A sliding window analysis of the microarray data and the 7X genome assembly coupled with an iterative model of the data showed the candidate genes are clustered in the genome. An analysis of 5' untranslated regions in the promoter of candidate genes identified 11 conserved motifs in 248 differentially expressed genes, all from the Clark genotype, representing 129 clusters identified earlier, confirming the cluster analysis results. Conclusion These analyses have identified the first genes with expression patterns that are affected by iron stress and are located within QTL specific to iron deficiency stress. The genetic location and promoter motif analysis results support the hypothesis that the differentially expressed genes are co-regulated. The combined results of all analyses lead us to postulate iron inefficiency in
Full Text Available The microflora in environmental water consists of a high density and diversity of bacterial species that form the foundation of the water ecosystem. Because the majority of these species cannot be cultured in vitro, a different approach is needed to identify prokaryotes in environmental water. A novel DNA microarray was developed as a simplified detection protocol. Multiple DNA probes were designed against each of the 97,927 sequences in the DNA Data Bank of Japan and mounted on a glass chip in duplicate. Evaluation of the microarray was performed using the DNA extracted from one liter of environmental water samples collected from seven sites in Japan. The extracted DNA was uniformly amplified using whole genome amplification (WGA, labeled with Cy3-conjugated 16S rRNA specific primers and hybridized to the microarray. The microarray successfully identified soil bacteria and environment-specific bacteria clusters. The DNA microarray described herein can be a useful tool in evaluating the diversity of prokaryotes and assessing environmental changes such as global warming.
Faure, Andre J
Abstract Background In order to interpret the results obtained from a microarray experiment, researchers often shift focus from analysis of individual differentially expressed genes to analyses of sets of genes. These gene-set analysis (GSA) methods use previously accumulated biological knowledge to group genes into sets and then aim to rank these gene sets in a way that reflects their relative importance in the experimental situation in question. We suspect that the presence of paralogs affects the ability of GSA methods to accurately identify the most important sets of genes for subsequent research. Results We show that paralogs, which typically have high sequence identity and similar molecular functions, also exhibit high correlation in their expression patterns. We investigate this correlation as a potential confounding factor common to current GSA methods using Indygene http:\\/\\/www.cbio.uct.ac.za\\/indygene, a web tool that reduces a supplied list of genes so that it includes no pairwise paralogy relationships above a specified sequence similarity threshold. We use the tool to reanalyse previously published microarray datasets and determine the potential utility of accounting for the presence of paralogs. Conclusions The Indygene tool efficiently removes paralogy relationships from a given dataset and we found that such a reduction, performed prior to GSA, has the ability to generate significantly different results that often represent novel and plausible biological hypotheses. This was demonstrated for three different GSA approaches when applied to the reanalysis of previously published microarray datasets and suggests that the redundancy and non-independence of paralogs is an important consideration when dealing with GSA methodologies.
Ruozhuo Liu; Shengyuan Yu; Fengpeng Li; Enchao Qiu
Cortical spreading depression can trigger migraine with aura and activate the trigeminal vascular system. To examine gene expression profiles in the spinal trigeminal nucleus in rats following cortical spreading depression-induced migraine with aura, a rat model was established by injection of 1 M potassium chloride, which induced cortical spreading depression. DNA microarray analysis revealed that, compared with the control group, the cortical spreading depression group showed seven upregulated genes-myosin heavy chain 1/2, myosin light chain 1, myosin light chain (phosphorylatable, fast skeletal muscle), actin alpha 1, homeobox B8, carbonic anhydrase 3 and an unknown gene. Two genes were downregulated-RGD1563441 and an unknown gene. Real-time quantitative reverse transcription-PCR and bioinformatics analysis indicated that these genes are involved in motility, cell migration, CO2 /nitric oxide homeostasis and signal transduction.
Kunze, A; Dilcher, M; Abd El Wahed, A; Hufert, F; Niessner, R; Seidel, M
This work presents an on-chip isothermal nucleic acid amplification test (iNAAT) for the multiplex amplification and detection of viral and bacterial DNA by a flow-based chemiluminescence microarray. In a principle study, on-chip recombinase polymerase amplification (RPA) on defined spots of a DNA microarray was used to spatially separate the amplification reaction of DNA from two viruses (Human adenovirus 41, Phi X 174) and the bacterium Enterococcus faecalis, which are relevant for water hygiene. By establishing the developed assay on the microarray analysis platform MCR 3, the automation of isothermal multiplex-amplification (39 °C, 40 min) and subsequent detection by chemiluminescence imaging was realized. Within 48 min, the microbes could be identified by the spot position on the microarray while the generated chemiluminescence signal correlated with the amount of applied microbe DNA. The limit of detection (LOD) determined for HAdV 41, Phi X 174, and E. faecalis was 35 GU/μL, 1 GU/μL, and 5 × 10(3) GU/μL (genomic units), which is comparable to the sensitivity reported for qPCR analysis, respectively. Moreover the simultaneous amplification and detection of DNA from all three microbes was possible. The presented assay shows that complex enzymatic reactions like an isothermal amplification can be performed in an easy-to-use experimental setup. Furthermore, iNAATs can be potent candidates for multipathogen detection in clinical, food, or environmental samples in routine or field monitoring approaches.
Shao, Lina; Shaw, Chad A.; Lu, Xin-Yan; Sahoo, Trilochan; Bacino, Carlos A.; Lalani, Seema R.; Stankiewicz, Pawel; Yatsenko, Svetlana A.; Li, Yinfeng; Neill, Sarah; Pursley, Amber N.; Chinault, A. Craig; Patel, Ankita; Beaudet, Arthur L.; Lupski, James R.; Cheung, Sau W.
Subtelomeric imbalances are a significant cause of congenital disorders. Screening for these abnormalities has traditionally utilized GTG-banding analysis, fluorescence in situ hybridization (FISH) assays, and multiplex ligation-dependent probe amplification. Microarray-based comparative genomic hybridization (array-CGH) is a relatively new technology that can identify microscopic and submicroscopic chromosomal imbalances. It has been proposed that an array with extended coverage at subtelomeric regions could characterize subtelomeric aberrations more efficiently in a single experiment. The targeted arrays for chromosome microarray analysis (CMA), developed by Baylor College of Medicine, have on average 12 BAC/PAC clones covering 10 Mb of each of the 41 subtelomeric regions. We screened 5,380 consecutive clinical patients using CMA. The most common reasons for referral included developmental delay (DD), and/or mental retardation (MR), dysmorphic features (DF), multiple congenital anomalies (MCA), seizure disorders (SD), and autistic, or other behavioral abnormalities. We found pathogenic rearrangements at subtelomeric regions in 236 patients (4.4%). Among these patients, 103 had a deletion, 58 had a duplication, 44 had an unbalanced translocation, and 31 had a complex rearrangement. The detection rates varied among patients with a normal karyotype analysis (2.98%), with an abnormal karyotype analysis (43.4%), and with an unavailable or no karyotype analysis (3.16%). Six patients out of 278 with a prior normal subtelomere-FISH analysis showed an abnormality including an interstitial deletion, two terminal deletions, two interstitial duplications, and a terminal duplication. In conclusion, genomic imbalances at subtelomeric regions contribute significantly to congenital disorders. Targeted array-CGH with extended coverage (up to 10 Mb) of subtelomeric regions will enhance the detection of subtelomeric imbalances, especially for submicroscopic imbalances. PMID
Background The Mexican axolotl (Ambystoma mexicanum) is considered a hopeful monster because it exhibits an adaptive and derived mode of development - paedomorphosis - that has evolved rapidly and independently among tiger salamanders. Unlike related tiger salamanders that undergo metamorphosis, axolotls retain larval morphological traits into adulthood and thus present an adult body plan that differs dramatically from the ancestral (metamorphic) form. The basis of paedomorphic development was investigated by comparing temporal patterns of gene transcription between axolotl and tiger salamander larvae (Ambystoma tigrinum tigrinum) that typically undergo a metamorphosis. Results Transcript abundances from whole brain and pituitary were estimated via microarray analysis on four different days post hatching (42, 56, 70, 84 dph) and regression modeling was used to independently identify genes that were differentially expressed as a function of time in both species. Collectively, more differentially expressed genes (DEGs) were identified as unique to the axolotl (n = 76) and tiger salamander (n = 292) than were identified as shared (n = 108). All but two of the shared DEGs exhibited the same temporal pattern of expression and the unique genes tended to show greater changes later in the larval period when tiger salamander larvae were undergoing anatomical metamorphosis. A second, complementary analysis that directly compared the expression of 1320 genes between the species identified 409 genes that differed as a function of species or the interaction between time and species. Of these 409 DEGs, 84% exhibited higher abundances in tiger salamander larvae at all sampling times. Conclusions Many of the unique tiger salamander transcriptional responses are probably associated with metamorphic biological processes. However, the axolotl also showed unique patterns of transcription early in development. In particular, the axolotl showed a genome-wide reduction in mRNA abundance
Full Text Available Abstract Background The Mexican axolotl (Ambystoma mexicanum is considered a hopeful monster because it exhibits an adaptive and derived mode of development - paedomorphosis - that has evolved rapidly and independently among tiger salamanders. Unlike related tiger salamanders that undergo metamorphosis, axolotls retain larval morphological traits into adulthood and thus present an adult body plan that differs dramatically from the ancestral (metamorphic form. The basis of paedomorphic development was investigated by comparing temporal patterns of gene transcription between axolotl and tiger salamander larvae (Ambystoma tigrinum tigrinum that typically undergo a metamorphosis. Results Transcript abundances from whole brain and pituitary were estimated via microarray analysis on four different days post hatching (42, 56, 70, 84 dph and regression modeling was used to independently identify genes that were differentially expressed as a function of time in both species. Collectively, more differentially expressed genes (DEGs were identified as unique to the axolotl (n = 76 and tiger salamander (n = 292 than were identified as shared (n = 108. All but two of the shared DEGs exhibited the same temporal pattern of expression and the unique genes tended to show greater changes later in the larval period when tiger salamander larvae were undergoing anatomical metamorphosis. A second, complementary analysis that directly compared the expression of 1320 genes between the species identified 409 genes that differed as a function of species or the interaction between time and species. Of these 409 DEGs, 84% exhibited higher abundances in tiger salamander larvae at all sampling times. Conclusions Many of the unique tiger salamander transcriptional responses are probably associated with metamorphic biological processes. However, the axolotl also showed unique patterns of transcription early in development. In particular, the axolotl showed a genome
Antunes, Heliton S; Wajnberg, Gabriel; Pinho, Marcos B; Jorge, Natasha Andressa Nogueira; de Moraes, Joyce Luana Melo; Stefanoff, Claudio Gustavo; Herchenhorn, Daniel; Araújo, Carlos M M; Viégas, Celia Maria Pais; Rampini, Mariana P; Dias, Fernando L; de Araujo-Souza, Patricia Savio; Passetti, Fabio; Ferreira, Carlos G
Oral mucositis is an acute toxicity that occurs in patients submitted to chemoradiotherapy to treat head and neck squamous cell carcinoma. In this study, we evaluated differences in gene expression in the keratinocytes of the oral mucosa of patients treated with photobiomodulation therapy and tried to associate the molecular mechanisms with clinical findings. From June 2009 to December 2010, 27 patients were included in a randomized double-blind pilot study. Buccal smears from 13 patients were obtained at days 1 and 10 of chemoradiotherapy, and overall gene expression of samples from both dates were analyzed by complementary DNA (cDNA) microarray. In addition, samples from other 14 patients were also collected at D1 and D10 of chemoradiotherapy for subsequent validation of cDNA microarray findings by qPCR. The expression array analysis identified 105 upregulated and 60 downregulated genes in our post-treatment samples when compared with controls. Among the upregulated genes with the highest fold change, it was interesting to observe the presence of genes related to keratinocyte differentiation. Among downregulated genes were observed genes related to cytotoxicity and immune response. The results indicate that genes known to be induced during differentiation of human epidermal keratinocytes were upregulated while genes associated with cytotoxicity and immune response were downregulated in the laser group. These results support previous clinical findings indicating that the lower incidence of oral mucositis associated with photobiomodulation therapy might be correlated to the activation of genes involved in keratinocyte differentiation.
LIU; Moqing; LIU; Hong; SUN; Lilian; DONG; Jie; XUE; Ying; C
In order to overcome the defects of difficult gene operations in Iow-copy suicide plasmid pCVD442, Gateway technology was applied in the construction process of recombinant plasmid for gene knockout in this study. With this improved knockout system, we inactivated sitC gene, which is associated with iron transport in Shigella flexneri2a strain 301, to yield the mutant,MTS. The functional detection of the mutant was performed at the level of culture medium, cell and animal experiment, respectively. The gene expression profiles were compared with DNA microarray between the mutant and the wild type under iron-restricted conditions. The results showed that MTS grew obviously less well than the wild-type strains in L broth containing 150μmol/L iron chelator DIP (2,2'-dipyridyl). Addition of iron or manganese to the cultures stimulated the growth of MTS to wild-type levels in rich culture medium. In either the experiment on the ability of intracellular multiplication and cell-to-cell spread in HeLa and U937 cell lines, or the experiment on keratoconjunctivitis in guinea pigs, MTS showed no obvious changes in virulence compared with the parental strain Sf301. When 65 μmol/L DIP was added to the cultured HeLa cells, the ability of intracellular multiplication of MTS reduced about 51.6% as compared with that of Sf301. The analysis of expression profiles under iron-limited condition showed that MTS was more sensitive for the change of iron deficiency than Sf301. There are 106 more up-regulated genes in MTS than in wild-type strains, which are involved in membrane transportation, amino acid metabolism and uncategorized function genes, while down-regulated genes are mainly involved in energy and carbohydrate metabolism. Under Iow iron conditions, the expression levels of known iron-transport associated genes generally increased. Additionally, the number of these genes and their increase amplitude in MTS are more than those in Sf301. Together, these results confirmed that Sit
Lee, Chu-I; Chou, An-Kuo; Lin, Ching-Chih; Chou, Chia-Hua; Loh, Joon-Khim; Lieu, Ann-Shung; Wang, Chih-Jen; Huang, Chi-Ying F; Howng, Shen-Long; Hong, Yi-Ren
Cerebral vasospasm following subarachnoid hemorrhage (SAH) has been studied in terms of a contraction of the major cerebral arteries, but the effect of cerebrum tissue in SAH is not yet well understood. To gain insight into the biology of SAH-expressing cerebrum, we employed oligonucleotide microarrays to characterize the gene expression profiles of cerebrum tissue at the early stage of SAH. Functional gene expression in the cerebrum was analyzed 2 h following stage 1-hemorrhage in Sprague-Dawley rats. mRNA was investigated by performing microarray and quantitative real-time PCR analyses, and protein expression was determined by Western blot analysis. In this study, 18 upregulated and 18 downregulated genes displayed at least a 1.5-fold change. Five genes were verified by real-time PCR, including three upregulated genes [prostaglandin E synthase (PGES), CD14 antigen, and tissue inhibitor of metalloproteinase 1 (TIMP1)] as well as two downregulated genes [KRAB-zinc finger protein-2 (KZF-2) and γ-aminobutyric acid B receptor 1 (GABA B receptor)]. Notably, there were functional implications for the three upregulated genes involved in the inflammatory SAH process. However, the mechanisms leading to decreased KZF-2 and GABA B receptor expression in SAH have never been characterized. We conclude that oligonucleotide microarrays have the potential for use as a method to identify candidate genes associated with SAH and to provide novel investigational targets, including genes involved in the immune and inflammatory response. Furthermore, understanding the regulation of MMP9/TIMP1 during the early stages of SAH may elucidate the pathophysiological mechanisms in SAH rats.
Nishida, Naohiro; Nagahara, Makoto; Sato, Tetsuya; Mimori, Koshi; Sudo, Tomoya; Tanaka, Fumiaki; Shibata, Kohei; Ishii, Hideshi; Sugihara, Kenichi; Doki, Yuichiro; Mori, Masaki
Cancer stroma plays an important role in the progression of cancer. Although alterations in miRNA expression have been explored in various kinds of cancers, the expression of miRNAs in cancer stroma has not been explored in detail. Using a laser microdissection technique, we collected RNA samples specific for epithelium or stroma from 13 colorectal cancer tissues and four normal tissues, and miRNA microarray and gene expression microarray were carried out. The expression status of miRNAs was confirmed by reverse transcriptase PCR. Furthermore, we investigated whether miRNA expression status in stromal tissue could influence the clinicopathologic factors. Oncogenic miRNAs, including two miRNA clusters, miR-17-92a and miR-106b-25 cluster, were upregulated in cancer stromal tissues compared with normal stroma. Gene expression profiles from cDNA microarray analyses of the same stromal tissue samples revealed that putative targets of these miRNA clusters, predicted by Target Scan, such as TGFBR2, SMAD2, and BMP family genes, were significantly downregulated in cancer stromal tissue. Downregulated putative targets were also found to be involved in cytokine interaction and cellular adhesion. Importantly, expression of miR-25 and miR-92a in stromal tissues was associated with a variety of clinicopathologic factors. Oncogenic miRNAs were highly expressed in cancer stroma. Although further validation is required, the finding that stromal miRNA expression levels were associated with clinicopathologic factors suggests the possibility that miRNAs in cancer stroma are crucially involved in cancer progression.
Karolin Trautmann; Christine Steudel; Dana Grossmann; Daniela Aust; Gerhard Ehninger; Stephan Miehlke; Christian Thiede
AIM: Gene expression profiling provides an unique opportunity to gain insight into the development of different types of gastric cancer. Tumor sample heterogeneity is thought to decrease the sensitivity and tumor specificity of microarray analysis. Thus, microdissection and preamplification of RNA is frequently performed. However, this technique may also induce considerable changes to the expression profile. To assess the effect of gastric tumor heterogeneity on expression profiling results, we measured the variation in gene expression within the same gastric cancer sample by performing a gene chip analysis with two RNA preparations extracted from the same tumor specimen.METHODS: Tumor samples from six intestinal T2 gastric tumors were dissected under liquid nitrogen and RNA was prepared from two separate tumor fragments. Each extraction was individually processed and hybridized to an Affymetrix U133A gene chip covering approximately 18 000 human gene transcripts. Expression profiles were analyzed using Microarray Suite 5.0 (Affymetrix) and GeneSpring 6.0 (Silicon Genetics).RESULTS: All gastric cancers showed little variance in expression profiles between different regions of the same tumor sample. In this case, gene chips displayed mean pair wise correlation coefficients of 0.94±0.02 (mean±SD),compared to values of 0.61±0.1 for different tumor samples. Expression of the variance between the two expression profiles as a percentage of "total change"(Affymetrix) revealed a remarkably low average value of 1.18±0.78 for comparing fragments of the same tumor sample.In contrast, comparison of fragments from different tumors revealed a percentage of 24.4±4.5.CONCLUSION: Our study indicates a low degree of expression profile variability within gastric tumor samples isolated from one patient. These data suggest that tumor tissue heterogeneity is not a dominant source of error for microarray analysis of larger tumor samples, making total RNA extraction an appropriate
El-Ashker, Maged; Hotzel, Helmut; Gwida, Mayada; El-Beskawy, Mohamed; Silaghi, Cornelia; Tomaso, Herbert
In this preliminary study, a novel DNA microarray system was tested for the diagnosis of bovine piroplasmosis and anaplasmosis in comparison with microscopy and PCR assay results. In the Dakahlia Governorate, Egypt, 164 cattle were investigated for the presence of piroplasms and Anaplasma species. All investigated cattle were clinically examined. Blood samples were screened for the presence of blood parasites using microscopy and PCR assays. Seventy-one animals were acutely ill, whereas 93 were apparently healthy. In acutely ill cattle, Babesia/Theileria species (n=11) and Anaplasma marginale (n=10) were detected. Mixed infections with Babesia/Theileria spp. and A. marginale were present in two further cases. A. marginale infections were also detected in apparently healthy subjects (n=23). The results of PCR assays were confirmed by DNA sequencing. All samples that were positive by PCR for Babesia/Theileria spp. gave also positive results in the microarray analysis. The microarray chips identified Babesia bovis (n=12) and Babesia bigemina (n=2). Cattle with babesiosis were likely to have hemoglobinuria and nervous signs when compared to those with anaplasmosis that frequently had bloody feces. We conclude that clinical examination in combination with microscopy are still very useful in diagnosing acute cases of babesiosis and anaplasmosis, but a combination of molecular biological diagnostic assays will detect even asymptomatic carriers. In perspective, parallel detection of Babesia/Theileria spp. and A. marginale infections using a single microarray system will be a valuable improvement.
Full Text Available Abstract Background The Smyth line (SL of chicken is an excellent avian model for human autoimmune vitiligo. The etiology of vitiligo is complicated and far from clear. In order to better understand critical components leading to vitiligo development, cDNA microarray technology was used to compare gene expression profiles in the target tissue (the growing feather of SL chickens at different vitiligo (SLV states. Results Compared to the reference sample, which was from Brown line chickens (the parental control, 395, 522, 524 and 526 out of the 44 k genes were differentially expressed (DE (P ≤ 0.05 in feather samples collected from SL chickens that never developed SLV (NV, from SLV chickens prior to SLV onset (EV, during active loss of pigmentation (AV, and after complete loss of melanocytes (CV. Comparisons of gene expression levels within SL samples (NV, EV, AV and CV revealed 206 DE genes, which could be categorized into immune system-, melanocyte-, stress-, and apoptosis-related genes based on the biological functions of their corresponding proteins. The autoimmune nature of SLV was supported by predominant presence of immune system related DE genes and their remarkably elevated expression in AV samples compared to NV, EV and/or CV samples. Melanocyte loss was confirmed by decreased expression of genes for melanocyte related proteins in AV and CV samples compared to NV and EV samples. In addition, SLV development was also accompanied by altered expression of genes associated with disturbed redox status and apoptosis. Ingenuity Pathway Analysis of DE genes provided functional interpretations involving but not limited to innate and adaptive immune response, oxidative stress and cell death. Conclusions The microarray results provided comprehensive information at the transcriptome level supporting the multifactorial etiology of vitiligo, where together with apparent inflammatory/innate immune activity and oxidative stress, the adaptive immune
Full Text Available A high phosphorus (HP diet causes disorders of renal function, bone metabolism, and vascular function. We previously demonstrated that DNA microarray analysis is an appropriate method to comprehensively evaluate the effects of a HP diet on kidney dysfunction such as calcification, fibrillization, and inflammation. We reported that type IIb sodium-dependent phosphate transporter is significantly up-regulated in this context. In the present study, we performed DNA microarray analysis to investigate the effects of a HP diet on the liver, which plays a pivotal role in energy metabolism. DNA microarray analysis was performed with total RNA isolated from the livers of rats fed a control diet (containing 0.3% phosphorus or a HP diet (containing 1.2% phosphorus. Gene Ontology analysis of differentially expressed genes (DEGs revealed that the HP diet induced down-regulation of genes involved in hepatic amino acid catabolism and lipogenesis, while genes related to fatty acid β-oxidation process were up-regulated. Although genes related to fatty acid biosynthesis were down-regulated in HP diet-fed rats, genes important for the elongation and desaturation reactions of omega-3 and -6 fatty acids were up-regulated. Concentrations of hepatic arachidonic acid and eicosapentaenoic acid were increased in HP diet-fed rats. These essential fatty acids activate peroxisome proliferator-activated receptor alpha (PPARα, a transcription factor for fatty acid β-oxidation. Evaluation of the upstream regulators of DEGs using Ingenuity Pathway Analysis indicated that PPARα was activated in the livers of HP diet-fed rats. Furthermore, the serum concentration of fibroblast growth factor 21, a hormone secreted from the liver that promotes fatty acid utilization in adipose tissue as a PPARα target gene, was higher (p = 0.054 in HP diet-fed rats than in control diet-fed rats. These data suggest that a HP diet enhances energy expenditure through the utilization of free fatty
Raftery Adrian E
Full Text Available Abstract Background Microarray technology is increasingly used to identify potential biomarkers for cancer prognostics and diagnostics. Previously, we have developed the iterative Bayesian Model Averaging (BMA algorithm for use in classification. Here, we extend the iterative BMA algorithm for application to survival analysis on high-dimensional microarray data. The main goal in applying survival analysis to microarray data is to determine a highly predictive model of patients' time to event (such as death, relapse, or metastasis using a small number of selected genes. Our multivariate procedure combines the effectiveness of multiple contending models by calculating the weighted average of their posterior probability distributions. Our results demonstrate that our iterative BMA algorithm for survival analysis achieves high prediction accuracy while consistently selecting a small and cost-effective number of predictor genes. Results We applied the iterative BMA algorithm to two cancer datasets: breast cancer and diffuse large B-cell lymphoma (DLBCL data. On the breast cancer data, the algorithm selected a total of 15 predictor genes across 84 contending models from the training data. The maximum likelihood estimates of the selected genes and the posterior probabilities of the selected models from the training data were used to divide patients in the test (or validation dataset into high- and low-risk categories. Using the genes and models determined from the training data, we assigned patients from the test data into highly distinct risk groups (as indicated by a p-value of 7.26e-05 from the log-rank test. Moreover, we achieved comparable results using only the 5 top selected genes with 100% posterior probabilities. On the DLBCL data, our iterative BMA procedure selected a total of 25 genes across 3 contending models from the training data. Once again, we assigned the patients in the validation set to significantly distinct risk groups (p
Sharma, Ashok; Zhao, Jieping; Podolsky, Robert; McIndoe, Richard A
Significance analysis of microarrays (SAM) is a widely used permutation-based approach to identifying differentially expressed genes in microarray datasets. While SAM is freely available as an Excel plug-in and as an R-package, analyses are often limited for large datasets due to very high memory requirements. We have developed a parallelized version of the SAM algorithm called ParaSAM to overcome the memory limitations. This high performance multithreaded application provides the scientific community with an easy and manageable client-server Windows application with graphical user interface and does not require programming experience to run. The parallel nature of the application comes from the use of web services to perform the permutations. Our results indicate that ParaSAM is not only faster than the serial version, but also can analyze extremely large datasets that cannot be performed using existing implementations. A web version open to the public is available at http://bioanalysis.genomics.mcg.edu/parasam. For local installations, both the windows and web implementations of ParaSAM are available for free at http://www.amdcc.org/bioinformatics/software/parasam.aspx.
Full Text Available Biohydrogen is a clean and renewable form of hydrogen, which can be produced by photosynthetic bacteria in outdoor large-scale photobioreactors using sunlight. In this study, the transcriptional response of Rhodobacter capsulatus to cold (4 °C and heat (42 °C stress was studied using microarrays. Bacteria were grown in 30/2 acetate/glutamate medium at 30 °C for 48 h under continuous illumination. Then, cold and heat stresses were applied for two and six hours. Growth and hydrogen production were impaired under both stress conditions. Microarray chips for R. capsulatus were custom designed by Affymetrix (GeneChip®. TR_RCH2a520699F. The numbers of significantly changed genes were 328 and 293 out of 3685 genes under cold and heat stress, respectively. Our results indicate that temperature stress greatly affects the hydrogen production metabolisms of R. capsulatus. Specifically, the expression of genes that participate in nitrogen metabolism, photosynthesis and the electron transport system were induced by cold stress, while decreased by heat stress. Heat stress also resulted in down regulation of genes related to cell envelope, transporter and binding proteins. Transcriptome analysis and physiological results were consistent with each other. The results presented here may aid clarification of the genetic mechanisms for hydrogen production in purple non-sulfur (PNS bacteria under temperature stress.
Full Text Available Abstract Background Epidermal Growth Factor (EGF is a key regulatory growth factor activating many processes relevant to normal development and disease, affecting cell proliferation and survival. Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina in combination with digital gene expression profiling (DGE with the Illumina Genome Analyzer. Results By applying a procedure for cross-platform data meta-analysis based on RankProd and GlobalAncova tests, we establish a well validated gene set with transcript levels altered after EGF treatment. We use this robust gene list to build higher order networks of gene interaction by interconnecting associated networks, supporting and extending the important role of the EGF signaling pathway in cancer. In addition, we find an entirely new set of genes previously unrelated to the currently accepted EGF associated cellular functions. Conclusions We propose that the use of global genomic cross-validation derived from high content technologies (microarrays or deep sequencing can be used to generate more reliable datasets. This approach should help to improve the confidence of downstream in silico functional inference analyses based on high content data.
In this study, microarray technique was employed to analyze the gene expression at the RNA level between haploids and corresponding diploids derived from a rice twin-seedling line SARII-628. Differ- ent degrees of expression variations were observed in the plant after haploidization. The main results are as follows: (1) after haploidization, the ratio of the sensitive loci was 2.47% of the total loci designed on chip. Those loci were randomly distributed on the 12 pairs of rice chromosomes and the activated loci were more than the silenced ones. (2) Gene clusters on chromosome were observed for 33 se- quences. (3) GoPipe function classification for 575 sensitive loci revealed an involvement in the bio- logical process, cell component and molecular function. (4) RT-PCR generally validated the result from microarray with a coincidence rate of 83.78%. And for the randomly-selected activated or silenced loci in chip analysis, the coincidence rate was up to 91.86%.
Severgnini, Marco; Pattini, Linda; Consolandi, Clarissa; Rizzi, Ermanno; Battaglia, Cristina; De Bellis, Gianluca; Cerutti, Sergio
Every microarray experiment is affected by many possible sources of variability that may even corrupt biological evidence on analyzed sequences. We applied a "Taguchi method" strategy, based on the use of orthogonal arrays to optimize the deposition step of oligonucleotide sequences on glass slides. We chose three critical deposition parameters (humidity, surface, and buffer) at two levels each, in order to establish optimum settings. A L8 orthogonal array was used in order to monitor both the main effects and interactions on the deposition of a 25 mer oligonucleotide hybridized to its fluorescent-labeled complementary. Signal-background ratio and deposition homogeneity in terms of mean intensity and spot diameter were considered as significant outputs. An analysis of variance (ANOVA) was applied to raw data and to mean results for each slide and experimental run. Finally we calculated an overall evaluation coefficient to group together important outputs in one number. Environmental humidity and surface-buffer interaction were recognized as the most critical factors, for which a 50% humidity, associated to a chitosan-covered slide and a sodium phosphate + 25% dimethyl sulfoxide (DMSO) buffer gave best performances. Our results also suggested that Taguchi methods can be efficiently applied in optimization of microarray procedures.
Full Text Available Abstract Breast cancer tumours among African Americans are usually more aggressive than those found in Caucasian populations. African-American patients with breast cancer also have higher mortality rates than Caucasian women. A better understanding of the disease aetiology of these breast cancers can help to improve and develop new methods for cancer prevention, diagnosis and treatment. The main goal of this project was to identify genes that help differentiate between oestrogen receptor-positive and -negative samples among a small group of African-American patients with breast cancer. Breast cancer microarrays from one of the largest genomic consortiums were analysed using 13 African-American and 201 Caucasian samples with oestrogen receptor status. We used a shrinkage-based classification method to identify genes that were informative in discriminating between oestrogen receptor-positive and -negative samples. Subset analysis and permutation were performed to obtain a set of genes unique to the African-American population. We identified a set of 156 probe sets, which gave a misclassification rate of 0.16 in distinguishing between oestrogen receptor-positive and -negative patients. The biological relevance of our findings was explored through literature-mining techniques and pathway mapping. An independent dataset was used to validate our findings and we found that the top ten genes mapped onto this dataset gave a misclassification rate of 0.15. The described method allows us best to utilise the information available from small sample size microarray data in the context of ethnic minorities.
KONG Bo; LIU Ying-long; L(U) Xiao-dong
Background The physiological differences between fetal and postnatal heart have been well characterized at the cellular level. However, the genetic mechanisms governing and regulating these differences have only been partially elucidated. Elucidation of the differentially expressed genes profile before and after birth has never been systematically proposed and analyzed.Methods The human oligonuclectide microarray and bioinformatics analysis approaches were applied to isolate and classify the differentially expressed genes between fetal and infant cardiac tissue samples. Quantitative real-time PCR was used to confirm the results from the microarray.Results Two hundred and forty-two differentially expressed genes were discovered and classified into 13 categories, including genes related to energy metabolism, myocyte hyperplasia, development, muscle contraction, protein synthesis and degradation, extraceUular matrix components, transcription factors, apoptosis, signal pathway molecules, organelle organization and several other biological processes. Moreover, 95 genes were identified which had not previously been reported to be expressed in the heart.Conclusions The study systematically analyzed the alteration of the gene expression profile between the human fetal and infant myocardium. A number of genes were discovered which had not been reported to be expressed in the heart. The data provided insight into the physical development mechanisms of the heart before and after birth.KONG Bo and LU Xiao-dong contributed equally to this study.
Zhou, Baiyu; Xu, Weihong; Herndon, David; Tompkins, Ronald; Davis, Ronald; Xiao, Wenzhong; Wong, Wing Hung; Toner, Mehmet; Warren, H Shaw; Schoenfeld, David A; Rahme, Laurence; McDonald-Smith, Grace P; Hayden, Douglas; Mason, Philip; Fagan, Shawn; Yu, Yong-Ming; Cobb, J Perren; Remick, Daniel G; Mannick, John A; Lederer, James A; Gamelli, Richard L; Silver, Geoffrey M; West, Michael A; Shapiro, Michael B; Smith, Richard; Camp, David G; Qian, Weijun; Storey, John; Mindrinos, Michael; Tibshirani, Rob; Lowry, Stephen; Calvano, Steven; Chaudry, Irshad; West, Michael A; Cohen, Mitchell; Moore, Ernest E; Johnson, Jeffrey; Moldawer, Lyle L; Baker, Henry V; Efron, Philip A; Balis, Ulysses G J; Billiar, Timothy R; Ochoa, Juan B; Sperry, Jason L; Miller-Graziano, Carol L; De, Asit K; Bankey, Paul E; Finnerty, Celeste C; Jeschke, Marc G; Minei, Joseph P; Arnoldo, Brett D; Hunt, John L; Horton, Jureta; Cobb, J Perren; Brownstein, Bernard; Freeman, Bradley; Maier, Ronald V; Nathens, Avery B; Cuschieri, Joseph; Gibran, Nicole; Klein, Matthew; O'Keefe, Grant
Time-course microarray experiments are capable of capturing dynamic gene expression profiles. It is important to study how these dynamic profiles depend on the multiple factors that characterize the experimental condition under which the time course is observed. Analytic methods are needed to simultaneously handle the time course and factorial structure in the data. We developed a method to evaluate factor effects by pooling information across the time course while accounting for multiple testing and nonnormality of the microarray data. The method effectively extracts gene-specific response features and models their dependency on the experimental factors. Both longitudinal and cross-sectional time-course data can be handled by our approach. The method was used to analyze the impact of age on the temporal gene response to burn injury in a large-scale clinical study. Our analysis reveals that 21% of the genes responsive to burn are age-specific, among which expressions of mitochondria and immunoglobulin genes are differentially perturbed in pediatric and adult patients by burn injury. These new findings in the body's response to burn injury between children and adults support further investigations of therapeutic options targeting specific age groups. The methodology proposed here has been implemented in R package "TANOVA" and submitted to the Comprehensive R Archive Network at http://www.r-project.org/. It is also available for download at http://gluegrant1.stanford.edu/TANOVA/.
Chinnaiyan Arul M
Full Text Available Abstract Background With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across multiple studies. Results In this article, we describe a general probabilistic framework for combining high-throughput genomic data from several related microarray experiments using mixture models. A key feature of the model is the use of latent variables that represent quantities that can be combined across diverse platforms. We consider two methods for estimation of an index termed the probability of expression (POE. The first, reported in previous work by the authors, involves Markov Chain Monte Carlo (MCMC techniques. The second method is a faster algorithm based on the expectation-maximization (EM algorithm. The methods are illustrated with application to a meta-analysis of datasets for metastatic cancer. Conclusion The statistical methods described in the paper are available as an R package, metaArray 1.8.1, which is at Bioconductor, whose URL is http://www.bioconductor.org/.
Navolotskiĭ, D V; Perchik, A V; Mark'ianov, I A; Ganeev, A A; Sliadnev, M N
A microarray analytic system that uses a silicon chip with immobilized in microreactor test-system for multiplex analysis of DNA by real-time polymerase chain reaction (RT-PCR) was developed and optimized. We suggested the method of immobilization of PCR-components of a test-system, chose the stabilizer, and conducted the optimization of the composition of reaction mixture to achieve permanent stability of a microarray. We conducted optimization of preparation of samples using magnetic sorbent and indicated that, with 2.6 x 10(4) copies/ml, 60 min are necessary to obtain positive identification including time for preparation of model probes. The abilities of the created system were demonstrated on the example of microarray analysis of samples with different content of DNA, low absolute limits of identification (20 DNA copies in microreactor), and high reproducibility of the analysis.
Han, G-M; Chen, S-L; Shen, N; Ye, S; Bao, C-D; Gu, Y-Y
Epidemiologic studies suggest a strong genetic component for susceptibility to systemic lupus erythematosus (SLE). To investigate the genetic mechanism of pathogenesis of SLE, we studied the difference in gene expression of peripheral blood cells between 10 SLE patients and 18 healthy controls using oligonucleotide microarray. When gene expression for patients was compared to the mean of normal controls, among the 3002 target genes, 61 genes were identified with greater than a two-fold change difference in expression level. Of these genes, 24 were upregulated and 37 downregulated in at least half of the patients. By the Welch's ANOVA/Welch's t-test, all these 61 genes were significantly different (PTSA-1/Sca-2) may play an important role in the mechanism of SLE pathogenesis. TSA-1 antigens may represent an important alternative pathway for T-cell activation that may be involved in IFN-mediated immunomodulation. Hierarchical clustering showed that patient samples were clearly separated from controls based on their gene expression profile. These results demonstrate that high-density oligonucleotide microarray has the potential to explore the mechanism of pathogenesis of systemic lupus erythematosus.
Full Text Available Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification. In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN, naive Bayes, and support vector machine (SVM. Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT and moving window technique (MWT is used. The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes. Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers. This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community. This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.
Karen S. Ho
Full Text Available Copy number variants (CNVs detected by chromosomal microarray analysis (CMA significantly contribute to understanding the etiology of autism spectrum disorder (ASD and other related conditions. In recognition of the value of CMA testing and its impact on medical management, CMA is in medical guidelines as a first-tier test in the evaluation of children with these disorders. As CMA becomes adopted into routine care for these patients, it becomes increasingly important to report these clinical findings. This study summarizes the results of over 4 years of CMA testing by a CLIA-certified clinical testing laboratory. Using a 2.8 million probe microarray optimized for the detection of CNVs associated with neurodevelopmental disorders, we report an overall CNV detection rate of 28.1% in 10,351 consecutive patients, which rises to nearly 33% in cases without ASD, with only developmental delay/intellectual disability (DD/ID and/or multiple congenital anomalies (MCA. The overall detection rate for individuals with ASD is also significant at 24.4%. The detection rate and pathogenic yield of CMA vary significantly with the indications for testing, age, and gender, as well as the specialty of the ordering doctor. We note discrete differences in the most common recurrent CNVs found in individuals with or without a diagnosis of ASD.
Coessens, Bert; Thijs, Gert; Aerts, Stein; Marchal, Kathleen; De Smet, Frank; Engelen, Kristof; Glenisson, Patrick; Moreau, Yves; Mathys, Janick; De Moor, Bart
INCLUSive is a suite of algorithms and tools for the analysis of gene expression data and the discovery of cis-regulatory sequence elements. The tools allow normalization, filtering and clustering of microarray data, functional scoring of gene clusters, sequence retrieval, and detection of known and unknown regulatory elements using probabilistic sequence models and Gibbs sampling. All tools are available via different web pages and as web services. The web pages are connected and integrated to reflect a methodology and facilitate complex analysis using different tools. The web services can be invoked using standard SOAP messaging. Example clients are available for download to invoke the services from a remote computer or to be integrated with other applications. All services are catalogued and described in a web service registry. The INCLUSive web portal is available for academic purposes at http://www.esat.kuleuven.ac.be/inclusive.
Hernández-López, Edna L.; Ramírez-Puebla, Shamayim T.; Vazquez-Duhalt, Rafael
Asphaltenes are considered as the most recalcitrant petroleum fraction and represent a big problem for the recovery, separation and processing of heavy oils and bitumens. Neosartorya fischeri is a saprophytic fungus that is able to grow using asphaltenes as the sole carbon source . We performed transcription profiling using a custom designed microarray with the complete genome from N. fischeri NRRL 181 in order to identify genes related to the transformation of asphaltenes . Data analysis was performed using the genArise software. Results showed that 287 genes were up-regulated and 118 were down-regulated. Here we describe experimental procedures and methods about our dataset (NCBI GEO accession number GSE68146) and describe the data analysis to identify different expression levels in N. fischeri using this recalcitrant carbon source. PMID:26484261
Gao, Jian-Jie; Peng, Ri-He; Zhu, Bo; Wang, Bo; Wang, Li-Juan; Xu, Jing; Sun, Miao; Yao, Quan-Hong
Acrylamide (ACR) is a widely used industrial chemical. However, it is a dangerous compound because it showed neurotoxic effects in humans and act as reproductive toxicant and carcinogen in many animal species. In the environment, acrylamide has high soil mobility and may travel via groundwater. Phytoremediation is an effective method to remove the environmental pollutants, but the mechanism of plant response to acrylamide remains unknown. With the purpose of assessing remediation potentials of plants for acrylamide, we have examined acrylamide uptake by the model plant Arabidopsis grown on contaminated substrates with high performance liquid chromatography (HPLC) analysis. The result revealed that acrylamide could be absorbed and degraded by Arabidopsis. Further microarray analysis showed that 527 transcripts were up-regulated within 2-days under acrylamide exposure condition. We have found many potential acrylamide-induced genes playing a major role in plant metabolism and phytoremediation. Copyright © 2015 Elsevier Inc. All rights reserved.
Full Text Available Abstract Background A nearly complete collection of gene-deletion mutants (96% of annotated open reading frames of the yeast Saccharomyces cerevisiae has been systematically constructed. Tag microarrays are widely used to measure the fitness of each mutant in a mutant mixture. The tag array experiments can have a complex experimental design, such as time course measurements and drug treatment with multiple dosages. Results TagSmart is a web application for analysis and visualization of Saccharomyces cerevisiae mutant fitness data measured by tag microarrays. It implements a robust statistical approach to assess the concentration differences among S. cerevisiae mutant strains. It also provides an interactive environment for data analysis and visualization. TagSmart has the following advantages over previously described analysis procedures: 1 it is user-friendly software rather than merely a description of analytical procedure; 2 It can handle complicated experimental designs, such as multiple time points and treatment with multiple dosages; 3 it has higher sensitivity and specificity; 4 It allows users to mask out "bad" tags in the analysis. Two biological tests were performed to illustrate the performance of TagSmart. First, we generated titration mixtures of mutant strains, in which the relative concentration of each strain was controlled. We used tag microarrays to measure the numbers of tag copies in each titration mixture. The data was analyzed with TagSmart and the result showed high precision and recall. Second, TagSmart was applied to a dataset in which heterozygous deletion strain mixture pools were treated with a new drug, Cincreasin. TagSmart identified 53 mutant strains as sensitive to Cincreasin treatment. We individually tested each identified mutant, and found 52 out of the 53 predicted mutants were indeed sensitive to Cincreasin. Conclusion TagSmart is provided "as is" to analyze tag array data produced by Affymetrix and Agilent
Lina Yang; Shujuan Guo; Yang Li; Shumin Zhou; Shengce Tao
Systems biology holds the key for understanding biological systems on a system level. It eventually holds the key for the treatment and cure of complex diseases such as cancer,diabetes, obesity, mental disorders, and many others. The '-omics' technologies, such as genomics, transcriptomics,proteomics, and metabonomics, are among the major driving forces of systems biology. Featured as highthroughput, miniaturized, and capable of parallel analysis,protein microarrays have already become an important technology platform for systems biology, In this review, we will focus on the system level or global analysis of biological systems using protein microarrays. Four major types of protein microarrays will be discussed: proteome microarrays, antibody microarrays, reverse-phase protein arrays,and lectin microarrays. We will also discuss the challenges and future directions of protein microarray technologies and their applications for systems biology. We strongly believe that protein microarrays will soon become an indispensable and invaluable tool for systems biology.
Full Text Available Neuroblastoma has a very diverse clinical behaviour: from spontaneous regression to a very aggressive malignant progression and resistance to chemotherapy. This heterogeneous clinical behaviour might be due to the existence of Cancer Stem Cells (CSC, a subpopulation within the tumor with stem-like cell properties: a significant proliferation capacity, a unique self-renewal capacity, and therefore, a higher ability to form new tumors. We enriched the CSC-like cell population content of two commercial neuroblastoma cell lines by the use of conditioned cell culture media for neurospheres, and compared genomic gains and losses and genome expression by array-CGH and microarray analysis, respectively (in CSC-like versus standard tumor cells culture. Despite the array-CGH did not show significant differences between standard and CSC-like in both analyzed cell lines, the microarray expression analysis highlighted some of the most relevant biological processes and molecular functions that might be responsible for the CSC-like phenotype. Some signalling pathways detected seem to be involved in self-renewal of normal tissues (Wnt, Notch, Hh and TGF-β and contribute to CSC phenotype. We focused on the aberrant activation of TGF-β and Hh signalling pathways, confirming the inhibition of repressors of TGF-β pathway, as SMAD6 and SMAD7 by RT-qPCR. The analysis of the Sonic Hedgehog pathway showed overexpression of PTCH1, GLI1 and SMO. We found overexpression of CD133 and CD15 in SIMA neurospheres, confirming that this cell line was particularly enriched in stem-like cells. This work shows a cross-talk among different pathways in neuroblastoma and its importance in CSC-like cells.
Dheilly, Nolwenn M.; Lelong, Christophe; Huvet, Arnaud; Kellner, Kristell; Dubos, Marie-Pierre; Riviere, Guillaume; Boudry, Pierre; Favrel, Pascal
Background The Pacific oyster Crassostrea gigas (Mollusca, Lophotrochozoa) is an alternative and irregular protandrous hermaphrodite: most individuals mature first as males and then change sex several times. Little is known about genetic and phenotypic basis of sex differentiation in oysters, and little more about the molecular pathways regulating reproduction. We have recently developed and validated a microarray containing 31,918 oligomers (Dheilly et al., 2011) representing the oyster transcriptome. The application of this microarray to the study of mollusk gametogenesis should provide a better understanding of the key factors involved in sex differentiation and the regulation of oyster reproduction. Methodology/Principal Findings Gene expression was studied in gonads of oysters cultured over a yearly reproductive cycle. Principal component analysis and hierarchical clustering showed a significant divergence in gene expression patterns of males and females coinciding with the start of gonial mitosis. ANOVA analysis of the data revealed 2,482 genes differentially expressed during the course of males and/or females gametogenesis. The expression of 434 genes could be localized in either germ cells or somatic cells of the gonad by comparing the transcriptome of female gonads to the transcriptome of stripped oocytes and somatic tissues. Analysis of the annotated genes revealed conserved molecular mechanisms between mollusks and mammals: genes involved in chromatin condensation, DNA replication and repair, mitosis and meiosis regulation, transcription, translation and apoptosis were expressed in both male and female gonads. Most interestingly, early expressed male-specific genes included bindin and a dpy-30 homolog and female-specific genes included foxL2, nanos homolog 3, a pancreatic lipase related protein, cd63 and vitellogenin. Further functional analyses are now required in order to investigate their role in sex differentiation in oysters. Conclusions
Musser, Richard O; Hum-Musser, Sue M; Gallucci, Matthew; DesRochers, Brittany; Brown, Judith K
Plants are routinely exposed to biotic and abiotic stresses to which they have evolved by synthesizing constitutive and induced defense compounds. Induced defense compounds are usually made, initially, at low levels; however, following further stimulation by specific kinds of biotic and abiotic stresses, they can be synthesized in relatively large amounts to abate the particular stress. cDNA microarray hybridization was used to identify an array of genes that were differentially expressed in tomato plants 15 d after they were exposed to feeding by nonviruliferous whiteflies or by viruliferous whiteflies carrying Pepper golden mosaic virus (PepGMV) (Begomovirus, Geminiviridae). Tomato plants inoculated by viruliferous whiteflies developed symptoms characteristic of PepGMV, whereas plants exposed to nonviruliferous whitefly feeding or nonwounded (negative) control plants exhibited no disease symptoms. The microarray analysis yielded over 290 spotted probes, with significantly altered expression of 161 putative annotated gene targets, and 129 spotted probes of unknown identities. The majority of the differentially regulated "known" genes were associated with the plants exposed to viruliferous compared with nonviruliferous whitefly feeding. Overall, significant differences in gene expression were represented by major physiological functions including defense-, pathogen-, photosynthesis-, and signaling-related responses and were similar to genes identified for other insect-plant systems. Viruliferous whitefly-stimulated gene expression was validated by real-time quantitative polymerase chain reaction of selected, representative candidate genes (messenger RNA): arginase, dehydrin, pathogenesis-related proteins 1 and -4, polyphenol oxidase, and several protease inhibitors. This is the first comparative profiling of the expression of tomato plants portraying different responses to biotic stress induced by viruliferous whitefly feeding (with resultant virus infection
Full Text Available This paper presents a reconfigurable architecture of a lab-on-chip (LoC microarray device capable to process data either in genotyping or in gene expression applications in a fraction of the time that is required by the usual software methods running on a standard computer. The entire LoC consists of a microfluidics part for the sample preparation and hybridization, a microsystem part including the application specific array of sensors for the electronic detection, and finally a reconfigurable processing part for the data analysis. The proposed data processing and analysis electronic module are an embedded multicore reconfigurable system-on-chip designed to analyze data from the forthcoming high-density oligonucleotide microarrays. The proposed architecture employs reconfigurable technology and has the capacity to process data from microarrays of various sizes from small size ones used in genotyping up to large-scale gene expression arrays. Additionally, the embedded processing cores feature reconfigurable circuitry for implementing the intense part of the processing, supplementing the various computational needs of the diverse applications for microarray real-time data processing and for a scalable reconfigurable architecture to handle also the future high-density microarrays.
杨雪莲; 贝学军; 朱友娟
cDNA microarray and oligonucleotide microarray are currently used for analysing citrus gene expression profile.The data analysis of genome microarray include data preprocessing,screening differential expression genes,and further analysing the differential expression genes.Through data analysis and integration of biological information,this paper studies the plant physiological changes.%指出了cDNA芯片和寡核苷酸芯片是目前用于柑橘基因表达谱分析的方法,基因组芯片数据分析主要包括数据预处理,筛选差异基因,差异基因再进一步分析。通过数据分析及整合样点的生物学信息,研究了植物生理变化。
Full Text Available Abstract Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web
Full Text Available Abstract Background Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue. However, standard procedures for sampling tissue for molecular profiling have not yet been established. Methods This study presents a high throughput analysis of texture heterogeneity on breast tissue images for the purpose of identifying regions of interest in the tissue for molecular profiling via tissue microarray technology. Image texture of breast histology slides was described in terms of three parameters: the percentage of area occupied in an image block by chromatin (B, percentage occupied by stroma-like regions (P, and a statistical heterogeneity index H commonly used in image analysis. Texture parameters were defined and computed for each of the thousands of image blocks in our dataset using both the gray scale and color segmentation. The image blocks were then classified into three categories using the texture feature parameters in a novel statistical learning algorithm. These categories are as follows: image blocks specific to normal breast tissue, blocks specific to cancerous tissue, and those image blocks that are non-specific to normal and disease states. Results Gray scale and color segmentation techniques led to identification of same regions in histology slides as cancer-specific. Moreover the image blocks identified as cancer-specific belonged to those cell crowded regions in whole section image slides that were marked by two pathologists as regions of interest for further histological studies. Conclusion These results indicate the high efficiency of our automated method for identifying pathologic regions of interest on histology slides. Automation of critical region identification will help minimize the inter-rater variability among different raters (pathologists as hundreds of tumors that are used to develop an array have typically been evaluated
Full Text Available BACKGROUND: Differences between noninfective first-stage (L1 and infective third-stage (L3i larvae of parasitic nematode Strongyloides stercoralis at the molecular level are relatively uncharacterized. DNA microarrays were developed and utilized for this purpose. METHODS AND FINDINGS: Oligonucleotide hybridization probes for the array were designed to bind 3,571 putative mRNA transcripts predicted by analysis of 11,335 expressed sequence tags (ESTs obtained as part of the Nematode EST project. RNA obtained from S. stercoralis L3i and L1 was co-hybridized to each array after labeling the individual samples with different fluorescent tags. Bioinformatic predictions of gene function were developed using a novel cDNA Annotation System software. We identified 935 differentially expressed genes (469 L3i-biased; 466 L1-biased having two-fold expression differences or greater and microarray signals with a p value<0.01. Based on a functional analysis, L1 larvae have a larger number of genes putatively involved in transcription (p = 0.004, and L3i larvae have biased expression of putative heat shock proteins (such as hsp-90. Genes with products known to be immunoreactive in S. stercoralis-infected humans (such as SsIR and NIE had L3i biased expression. Abundantly expressed L3i contigs of interest included S. stercoralis orthologs of cytochrome oxidase ucr 2.1 and hsp-90, which may be potential chemotherapeutic targets. The S. stercoralis ortholog of fatty acid and retinol binding protein-1, successfully used in a vaccine against Ancylostoma ceylanicum, was identified among the 25 most highly expressed L3i genes. The sperm-containing glycoprotein domain, utilized in a vaccine against the nematode Cooperia punctata, was exclusively found in L3i biased genes and may be a valuable S. stercoralis target of interest. CONCLUSIONS: A new DNA microarray tool for the examination of S. stercoralis biology has been developed and provides new and valuable insights
Brock, Guy N; Mukhopadhyay, Partha; Pihur, Vasyl; Webb, Cynthia; Greene, Robert M; Pisano, M Michele
MicroRNAs (miRNAs) constitute the largest family of noncoding RNAs involved in gene silencing and represent critical regulators of cell and tissue differentiation. Microarray expression profiling of miRNAs is an effective means of acquiring genome-level information of miRNA activation and inhibition, as well as the potential regulatory role that these genes play within a biological system. As with mRNA expression profiling arrays, miRNA microarrays come in a variety of platforms from numerous manufacturers, and there are a multitude of techniques available for reducing and analyzing these data. In this paper, we present an analysis of a typical two-color miRNA microarray experiment using publicly available packages from R and Bioconductor, the open-source software project for the analysis of genomic data. Covered topics include visualization, normalization, quality checking, differential expression, cluster analysis, miRNA target identification, and gene set enrichment analysis. Many of these tools carry-over from the analysis of mRNA microarrays, but with some notable differences that require special attention. The paper is presented as a "compendium" which, along with the accompanying R package MmPalateMiRNA, contains all of the experimental data and source code to reproduce the analyses contained in the paper. The compendium presented in this paper will provide investigators with an access point for applying the methods available in R and Bioconductor for analysis of their own miRNA array data.
Lazar, Cosmin; Taminau, Jonatan; Meganck, Stijn; Steenhoff, David; Coletta, Alain; Molter, Colin; de Schaetzen, Virginie; Duque, Robin; Bersini, Hugues; Nowé, Ann
A plenitude of feature selection (FS) methods is available in the literature, most of them rising as a need to analyze data of very high dimension, usually hundreds or thousands of variables. Such data sets are now available in various application areas like combinatorial chemistry, text mining, multivariate imaging, or bioinformatics. As a general accepted rule, these methods are grouped in filters, wrappers, and embedded methods. More recently, a new group of methods has been added in the general framework of FS: ensemble techniques. The focus in this survey is on filter feature selection methods for informative feature discovery in gene expression microarray (GEM) analysis, which is also known as differentially expressed genes (DEGs) discovery, gene prioritization, or biomarker discovery. We present them in a unified framework, using standardized notations in order to reveal their technical details and to highlight their common characteristics as well as their particularities.
Taitt, Chris Rowe; Leski, Tomasz; Stenger, David; Vora, Gary J.; House, Brent; Nicklasson, Matilda; Pimentel, Guillermo; Zurawski, Daniel V.; Kirkup, Benjamin C.; Craft, David; Waterman, Paige E.; Lesho, Emil P.; Bangurae, Umaru; Ansumana, Rashid
The prevalence of multidrug-resistant infections in personnel wounded in Iraq and Afghanistan has made it challenging for physicians to choose effective therapeutics in a timely fashion. To address the challenge of identifying the potential for drug resistance, we have developed the Antimicrobial Resistance Determinant Microarray (ARDM) to provide DNAbased analysis for over 250 resistance genes covering 12 classes of antibiotics. Over 70 drug-resistant bacteria from different geographic regions have been analyzed on ARDM, with significant differences in patterns of resistance identified: genes for resistance to sulfonamides, trimethoprim, chloramphenicol, rifampin, and macrolide-lincosamidesulfonamide drugs were more frequently identified in isolates from sources in Iraq/Afghanistan. Of particular concern was the presence of genes responsible for resistance to many of the last-resort antibiotics used to treat war traumaassociated infections.
Full Text Available Epithelial stromal cells represent a major cellular component of human uterine endometrium that is subject to tight hormonal regulation. Through cell-cell contacts and/or paracrine mechanisms, stromal cells play a significant role in the malignant transformation of epithelial cells. We isolated stromal cells from normal human endometrium and investigated the morphological and transcriptional changes induced by estrogen, progesterone and tamoxifen. We demonstrated that stromal cells express appreciable levels of estrogen and progesterone receptors and undergo different morphological changes upon hormonal stimulation. Microarray analysis indicated that both estrogen and progesterone induced dramatic alterations in a variety of genes associated with cell structure, transcription, cell cycle, and signaling. However, divergent patterns of changes, and in some genes opposite effects, were observed for the two hormones. A large number of genes are identified as novel targets for hormonal regulation. These hormone-responsive genes may be involved in normal uterine function and the development of endometrial malignancies.
Ren, Chun-E; Zhu, Xueqiong; Li, Jinping; Lyle, Christian; Dowdy, Sean; Podratz, Karl C.; Byck, David; Chen, Hai-Bin; Jiang, Shi-Wen
Epithelial stromal cells represent a major cellular component of human uterine endometrium that is subject to tight hormonal regulation. Through cell-cell contacts and/or paracrine mechanisms, stromal cells play a significant role in the malignant transformation of epithelial cells. We isolated stromal cells from normal human endometrium and investigated the morphological and transcriptional changes induced by estrogen, progesterone and tamoxifen. We demonstrated that stromal cells express appreciable levels of estrogen and progesterone receptors and undergo different morphological changes upon hormonal stimulation. Microarray analysis indicated that both estrogen and progesterone induced dramatic alterations in a variety of genes associated with cell structure, transcription, cell cycle, and signaling. However, divergent patterns of changes, and in some genes opposite effects, were observed for the two hormones. A large number of genes are identified as novel targets for hormonal regulation. These hormone-responsive genes may be involved in normal uterine function and the development of endometrial malignancies. PMID:25782154
, the molecular mechanisms of insulin resistance in skeletal muscle of women with PCOS are largely unknown. The aims of the Ph.D. thesis were: to identify biological pathways of importance for insulin resistance in skeletal muscle in a group of insulin resistant obese PCOS patients using global pathway analysis...... (study 1), to investigate whether pioglitazone therapy could reverse abnormalities in the transcriptional profile of muscle associated with insulin resistance in skeletal muscle of obese PCOS patients (study 2), and to develop a microarray platform for global gene expression profiling (study 3). In study...... expression of nuclear-encoded genes involved in mitochondrial oxidative phosphorylation (OXPHOS) in skeletal muscle, and q-RT-PCR showed that downregulation of OXPHOS genes may be mediated by reduced levels of PGC-1a. Treatment with pioglitazone partially restored insulin sensitivity in obese women with PCOS...
Bryant Susan V
Full Text Available Abstract Background Microarray analysis and 454 cDNA sequencing were used to investigate a centuries-old problem in regenerative biology: the basis of nerve-dependent limb regeneration in salamanders. Innervated (NR and denervated (DL forelimbs of Mexican axolotls were amputated and transcripts were sampled after 0, 5, and 14 days of regeneration. Results Considerable similarity was observed between NR and DL transcriptional programs at 5 and 14 days post amputation (dpa. Genes with extracellular functions that are critical to wound healing were upregulated while muscle-specific genes were downregulated. Thus, many processes that are regulated during early limb regeneration do not depend upon nerve-derived factors. The majority of the transcriptional differences between NR and DL limbs were correlated with blastema formation; cell numbers increased in NR limbs after 5 dpa and this yielded distinct transcriptional signatures of cell proliferation in NR limbs at 14 dpa. These transcriptional signatures were not observed in DL limbs. Instead, gene expression changes within DL limbs suggest more diverse and protracted wound-healing responses. 454 cDNA sequencing complemented the microarray analysis by providing deeper sampling of transcriptional programs and associated biological processes. Assembly of new 454 cDNA sequences with existing expressed sequence tag (EST contigs from the Ambystoma EST database more than doubled (3935 to 9411 the number of non-redundant human-A. mexicanum orthologous sequences. Conclusion Many new candidate gene sequences were discovered for the first time and these will greatly enable future studies of wound healing, epigenetics, genome stability, and nerve-dependent blastema formation and outgrowth using the axolotl model.
Full Text Available Tuberculosis is a major human and animal disease of major importance worldwide. Genetically, the closely related strains within the Mycobacterium tuberculosis complex which cause disease are well-characterized but there is an urgent need better to understand their phenotypes. To search rapidly for metabolic differences, a working method using Biolog Phenotype MicroArray analysis was developed. Of 380 substrates surveyed, 71 permitted tetrazolium dye reduction, the readout over 7 days in the method. By looking for ≥5-fold differences in dye reduction, 12 substrates differentiated M. tuberculosis H37Rv and Mycobacterium bovis AF2122/97. H37Rv and a Beijing strain of M. tuberculosis could also be distinguished in this way, as could field strains of M. bovis; even pairs of strains within one spoligotype could be distinguished by 2 to 3 substrates. Cluster analysis gave three clear groups: H37Rv, Beijing, and all the M. bovis strains. The substrates used agreed well with prior knowledge, though an unexpected finding that AF2122/97 gave greater dye reduction than H37Rv with hexoses was investigated further, in culture flasks, revealing that hexoses and Tween 80 were synergistic for growth and used simultaneously rather than in a diauxic fashion. Potential new substrates for growth media were revealed, too, most promisingly N-acetyl glucosamine. Osmotic and pH arrays divided the mycobacteria into two groups with different salt tolerance, though in contrast to the substrate arrays the groups did not entirely correlate with taxonomic differences. More interestingly, these arrays suggested differences between the amines used by the M. tuberculosis complex and enteric bacteria in acid tolerance, with some hydrophobic amino acids being highly effective. In contrast, γ-aminobutyrate, used in the enteric bacteria, had no effect in the mycobacteria. This study proved principle that Phenotype MicroArrays can be used with slow-growing pathogenic mycobacteria
Braicu, Cornelia; Cojocneanu-Petric, Roxana; Jurj, Ancuta; Gulei, Diana; Taranu, Ionelia; Gras, Alexandru Mihail; Marin, Daniela Eliza; Berindan-Neagoe, Ioana
Zearalenone (ZEA) is a secondary metabolite produced by Fusarium species. ZEA was proved to exert a wide range of unwanted side effects, but its mechanism of action, particularly at duodenum levels, remains unclear. In our study based on the microarray technology we assessed the alteration of gene expression pattern Sus scrofa duodenum which has been previously exposed to ZEA. Gene expression data was validated by qRT-PCR and ELISA. The gene expression data were further extrapolated the results to their human orthologues and analyzed the data in the context of human health using IPA (Ingenuity Pathways Analysis). Using Agilent microarray technology, we found that gene expression pattern was significantly affected by ZEA exposure, considering a 2-fold expression difference as a cut-off level and a p-value < 0.05. In total, we found 1576 upregulated and 2446 downregulated transcripts. About 1084 genes (764 downregulated and 751 overexpressed) were extrapolated to their human orthologues. IPA analysis showed various altered key cellular and molecular pathways. As expected, we observed a significant alteration of immune response related genes, MAPK (mitogen activate protein kinases) pathways or Toll-Like Receptors (TLRs). What captured our attention was the modulation of pathways related to the activation of early carcinogenesis. Our data demonstrate that ZEA has a complex effect at duodenum level. ZEA is able to activate not only the immune response related genes, but also those relate to colorectal carcinogenesis. The effects can be more dramatic when connected with the exposure to other environmental toxic agents or co-occurrence with different microorganisms.
谭志军; 胡先贵; 曹贵松; 唐岩
Objective: To identify new markers for prediction of lymph node metastasis. Methods: cDNA probes were prepared by labeling mRNA from samples of four pancreatic carcinoma tissues with Cy5-dUTP and mRNA from adjacent normal tissues with Cy3-dUTP respectively through reverse transcription. The mixed probes of each sample were then hybridized with 4,096 cDNA arrays (4,000 unique human cDNA sequences), and the fluorescent signals were scanned by ScanArray 3000 scanner (General Scanning, Inc.). The values of Cy5-dUTP and Cy3-dUTP on each spot were analyzed and calculated by ImaGene 3.0 software (BioDiscovery, Inc.). Genes that differentially expresses in each cancerous tissue were sought out according to the standard that the absolute value of natural logarithm of the ratio of Cy5 to Cy3 is greater than 0.69, i. e., more than 2 times change of gene expression, and the signal value of either Cy3 and Cy5 need to be greater than 600. Then, the genes differently expressed in cancer with and without lymphatic metastasis were screened out for further analysis. Results: Among 2 samples with lymphatic metastasis and 2 samples without metastasis, 56 genes, which accounted for 1.40% of genes on the microarray slides, exhibited differentially expression in cancerous tissues with lymphatic metastasis. There were 32 over-expressed genes including 11 having been registered in Genebank, and 24 under-expressed genes including 3 in Genebank. Conclusion: Microarray analysis may provide invaluable information to identify specific gene expression profile of lymphatic metastasis in pancreatic cancer.
Khatri, Bhagwati; Fielder, Mark; Jones, Gareth; Newell, William; Abu-Oun, Manal; Wheeler, Paul R
Tuberculosis is a major human and animal disease of major importance worldwide. Genetically, the closely related strains within the Mycobacterium tuberculosis complex which cause disease are well-characterized but there is an urgent need better to understand their phenotypes. To search rapidly for metabolic differences, a working method using Biolog Phenotype MicroArray analysis was developed. Of 380 substrates surveyed, 71 permitted tetrazolium dye reduction, the readout over 7 days in the method. By looking for ≥5-fold differences in dye reduction, 12 substrates differentiated M. tuberculosis H37Rv and Mycobacterium bovis AF2122/97. H37Rv and a Beijing strain of M. tuberculosis could also be distinguished in this way, as could field strains of M. bovis; even pairs of strains within one spoligotype could be distinguished by 2 to 3 substrates. Cluster analysis gave three clear groups: H37Rv, Beijing, and all the M. bovis strains. The substrates used agreed well with prior knowledge, though an unexpected finding that AF2122/97 gave greater dye reduction than H37Rv with hexoses was investigated further, in culture flasks, revealing that hexoses and Tween 80 were synergistic for growth and used simultaneously rather than in a diauxic fashion. Potential new substrates for growth media were revealed, too, most promisingly N-acetyl glucosamine. Osmotic and pH arrays divided the mycobacteria into two groups with different salt tolerance, though in contrast to the substrate arrays the groups did not entirely correlate with taxonomic differences. More interestingly, these arrays suggested differences between the amines used by the M. tuberculosis complex and enteric bacteria in acid tolerance, with some hydrophobic amino acids being highly effective. In contrast, γ-aminobutyrate, used in the enteric bacteria, had no effect in the mycobacteria. This study proved principle that Phenotype MicroArrays can be used with slow-growing pathogenic mycobacteria and already has
Robert T Gaeta
. Furthermore, our microarray analysis did not provide strong evidence that homoeologous rearrangements were a determinant of genome-wide nonadditive gene expression. In light of the inherent limitations of the Arabidopsis microarray to measure gene expression in polyploid Brassicas, further studies are warranted.
Trask, Heidi W.; Cowper-Sal-lari, Richard; Sartor, Maureen A.; Gui, Jiang; Heath, Catherine V.; Renuka, Janhavi; Higgins, Azara-Jane; Andrews,Peter; Korc, Murray; Moore, Jason H; Craig R Tomlinson
With no known exceptions, every published microarray study to determine differential mRNA levels in eukaryotes used RNA extracted from whole cells. It is assumed that the use of whole cell RNA in microarray gene expression analysis provides a legitimate profile of steady-state mRNA. Standard labeling methods and the prevailing dogma that mRNA resides almost exclusively in the cytoplasm has led to the long-standing belief that the nuclear RNA contribution is negligible. We report that unadulte...
Chen Wei; Fu Xiaobing; Sun Xiaoqing; Sun Tongzhu; Zhao Zhili; Yang Yinhui; Sheng Zhiyong
Background: Microarray analysis is a popular tool to investigate the function of genes that are responsible for the phenotype of the disease. Keloid is a intricate lesion which is probably modulated by interplay of many genes. We ventured to study the differences of gene expressions between keloids and normal skins with the aid of cDNA microarray in order to explore the molecular mechanism underlying keloid formation. Methods: The PCR products of 8400 human genes were spotted on a chip in array. The DNAs were then fixed on the glass plate by a series of treatments. Total RNAs was isolated from freshly excised human keloids and normal skin, and then was purified to mRNA by Oligotex. Both the mRNA from keloids and normal skin was reversely transcribed to cDNAs with the incorporations of fluorescent dUTP, for preparing the hybridization probes. The mixed probes were then hybridized to the cDNA microarray. After highly stringent washing, the cDNA microarray was scanned for the fluorescent signals to display the differences between two kinds of tissues. Results: Among 8400 human genes, there were 402 genes (4.79%) with different expression levels between the keloids and normal skins in all cases, 250were up-regulated (2.98%) and 152 down-regulated (1.81%). Analyses of collagen, fibronectin, proteoglycan,growth factors and apoptosis related molecule gene expression confirmed that our molecular data obtained by cDNA microarray were consistent with published biochemical and clinical observations of keloids. Conclusions: DNA microarray technology is an effective technique in screening for differences in gene expression between keloid and normal skin. Many genes are involved in the formation of keloids. Further analysis of the obtained genes will help understand the molecular mechanism of keloid formation.
Watson, M.; Perez-Alegre, M.; Denis Baron, M.; Delmas, C.; Dovc, P.; Duval, M.; Foulley, J.L.; Garrido-Pavon, J.J.; Hulsegge, B.; Jafrezic, F.; Jiménez-Marín, A.; Lavric, M.; Lê Cao, K.A.; Marot, G.; Mouzaki, D.; Pool, M.H.; Robert-Granié, C.; San Cristobal, M.; Tosser-Klop, G.; Waddington, D.; Koning, de D.J.
Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised
Full Text Available We recently identified 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA reductase, the rate-limiting enzyme of the mevalonate pathway, as a potential therapeutic target of the head and neck squamous cell carcinomas (HNSCC and cervical carcinomas (CC. The products of this complex biochemical pathway, including de novo cholesterol, are vital for a variety of key cellular functions affecting membrane integrity, cell signaling, protein synthesis, and cell cycle progression. Lovastatin, a specific inhibitor of HMG-CoA reductase, induces a pronounced apoptotic response in a specific subset of tumor types, including HNSCC and CC. The mediators of this response are not well established. Identification of differentially expressed genes represents a feasible approach to delineate these mediators as lovastatin has the potential to modulate transcription indirectly by perturbing levels of sterols and other mevalonate metabolites. Expression analysis following treatment of the HNSCC cell lines SCC9 or SCC25 with 10 μM lovastatin for 1 day showed that less than 2% (9 cDNAs of the 588 cDNAs on this microarray were affected in both cell lines. These included diazepam-binding inhibitor/acyl-CoA-binding protein, the activated transcription factor 4 and rhoA. Because the biosynthesis of mevalonate leads to its incorporation into more than a dozen classes of end products, their role in lovastatin-induced apoptosis was also evaluated. Addition of the metabolites of all the major branches of the mevalonate pathway indicated that only the nonsterol moiety, geranylgeranyl pyrophosphate (GGPP, significantly inhibited the apoptotic effects of lovastatin in HNSCC and CC cells. Because rhoA requires GGPP for its function, this links the microarray and biochemical data and identifies rhoA as a potential mediator of the anticancer properties of lovastatin. Our data suggest that the depletion of nonsterol mevalonate metabolites, particularly GGPP, can be potential mediators of
Full Text Available The alkaliphilic hemicellulolytic bacterium Bacillus sp. N16-5 has a broad substrate spectrum and exhibits the capacity to utilize complex carbohydrates such as galactomannan, xylan, and pectin. In the monosaccharide mixture, sequential utilization by Bacillus sp. N16-5 was observed. Glucose appeared to be its preferential monosaccharide, followed by fructose, mannose, arabinose, xylose, and galactose. Global transcription profiles of the strain were determined separately for growth on six monosaccharides (glucose, fructose, mannose, galactose, arabinose, and xylose and four polysaccharides (galactomannan, xylan, pectin, and sodium carboxymethylcellulose using one-color microarrays. Numerous genes potentially related to polysaccharide degradation, sugar transport, and monosaccharide metabolism were found to respond to a specific substrate. Putative gene clusters for different carbohydrates were identified according to transcriptional patterns and genome annotation. Identification and analysis of these gene clusters contributed to pathway reconstruction for carbohydrate utilization in Bacillus sp. N16-5. Several genes encoding putative sugar transporters were highly expressed during growth on specific sugars, suggesting their functional roles. Two phosphoenolpyruvate-dependent phosphotransferase systems were identified as candidate transporters for mannose and fructose, and a major facilitator superfamily transporter was identified as a candidate transporter for arabinose and xylose. Five carbohydrate uptake transporter 1 family ATP-binding cassette transporters were predicted to participate in the uptake of hemicellulose and pectin degradation products. Collectively, microarray data improved the pathway reconstruction involved in carbohydrate utilization of Bacillus sp. N16-5 and revealed that the organism precisely regulates gene transcription in response to fluctuations in energy resources.
Full Text Available Ralstonia solanacearum causes one of the most common soil-borne vascular diseases of diverse plant species, including many solanaceous crops such as tomato and pepper. The resulting disease, bacterial wilt (BW, is devastating and difficult to control using conventional approaches. The aim of this study was to investigate the differentially expressed genes in pepper root systems in response to infection by R. solanacearum. DNA microarray (Capsicum annuum 135K Microarray v3.0 Gene Expression platform analyses were performed using a susceptible genotype, ‘Chilbok’, and a resistant genotype, ‘KC350’, at 3 time points (1, 3, and 6 days post inoculation. It has been identified 115 resistance-specific genes (R-response genes and 109 susceptibility-specific genes (S-response gene, which were up-regulated in 1 genotype, but down-regulated in the other genotype. Gene Ontology (GO analysis for functional categorization indicated that many R-response genes were related to genes that function in xyloglucan biosynthesis and cell wall organization, while S-response genes were involved in the response to stress and cell death. The expression of genes encoding xyloglucan endotransglycosylase/hydrolase (XTH and β-galactosidase were verified by real-time RT-PCR at an early time point of R. solanacearum infection. The results supported the idea that rapidly induced XTH expression in ‘KC350’ may play an important role in the restructuring and reinforcement of the cell wall and restrict bacterial movement in xylem vessels. In addition, induced expression of β-galactosidase in R. solanacearum-infected ‘Chilbok’ implied that degradation of the cell wall structure in vascular tissues by β-galactosidase might be an important factor facilitating R. solanacearum invasion of and movement in susceptible host plants.
Sahoo, T; Peters, S U; Madduri, N S; Glaze, D G; German, J R; Bird, L M; Barbieri-Welge, R; Bichell, T J; Beaudet, A L; Bacino, C A
Angelman syndrome (AS) is a neurodevelopmental disorder characterised by severe mental retardation, dysmorphic features, ataxia, seizures, and typical behavioural characteristics, including a happy sociable disposition. AS is caused by maternal deficiency of UBE3A (E6 associated protein ubiquitin protein ligase 3A gene), located in an imprinted region on chromosome 15q11-q13. Although there are four different molecular types of AS, deletions of the 15q11-q13 region account for approximately 70% of the AS patients. These deletions are usually detected by fluorescence in situ hybridisation studies. The deletions can also be subclassified based on their size into class I and class II, with the former being larger and encompassing the latter. We studied 22 patients with AS due to microdeletions using a microarray based comparative genomic hybridisation (array CGH) assay to define the deletions and analysed their phenotypic severity, especially expression of the autism phenotype, in order to establish clinical correlations. Overall, children with larger, class I deletions were significantly more likely to meet criteria for autism, had lower cognitive scores, and lower expressive language scores compared with children with smaller, class II deletions. Children with class I deletions also required more medications to control their seizures than did those in the class II group. There are four known genes (NIPA1, NIPA2, CYFIP1, & GCP5) that are affected by class I but not class II deletions, thus raising the possibility of a role for these genes in autism as well as the development of expressive language skills.
Full Text Available BACKGROUND: Emerging evidence implicates altered gene expression within skeletal muscle in the pathogenesis of Kennedy disease/spinal bulbar muscular atrophy (KD/SBMA. We therefore broadly characterized gene expression in skeletal muscle of three independently generated mouse models of this disease. The mouse models included a polyglutamine expanded (polyQ AR knock-in model (AR113Q, a polyQ AR transgenic model (AR97Q, and a transgenic mouse that overexpresses wild type AR solely in skeletal muscle (HSA-AR. HSA-AR mice were included because they substantially reproduce the KD/SBMA phenotype despite the absence of polyQ AR. METHODOLOGY/PRINCIPAL FINDINGS: We performed microarray analysis of lower hindlimb muscles taken from these three models relative to wild type controls using high density oligonucleotide arrays. All microarray comparisons were made with at least 3 animals in each condition, and only those genes having at least 2-fold difference and whose coefficient of variance was less than 100% were considered to be differentially expressed. When considered globally, there was a similar overlap in gene changes between the 3 models: 19% between HSA-AR and AR97Q, 21% between AR97Q and AR113Q, and 17% between HSA-AR and AR113Q, with 8% shared by all models. Several patterns of gene expression relevant to the disease process were observed. Notably, patterns of gene expression typical of loss of AR function were observed in all three models, as were alterations in genes involved in cell adhesion, energy balance, muscle atrophy and myogenesis. We additionally measured changes similar to those observed in skeletal muscle of a mouse model of Huntington's Disease, and to those common to muscle atrophy from diverse causes. CONCLUSIONS/SIGNIFICANCE: By comparing patterns of gene expression in three independent models of KD/SBMA, we have been able to identify candidate genes that might mediate the core myogenic features of KD/SBMA.
Wu Thomas D
Full Text Available Abstract Background Gene expression profiling of formalin-fixed, paraffin-embedded (FFPE samples represents a valuable approach for advancing oncology diagnostics and enhancing retrospective clinical studies; however, at present, this methodology still requires optimization and thus has not been extensively used. Here, we utilized thorough quality control methods to assess RNA extracted from FFPE samples and then compared it to RNA extracted from matched fresh-frozen (FF counterparts. We preformed genome-wide expression profiling of FF and FFPE ovarian serous adenocarcinoma sample pairs and compared their gene signatures to normal ovary samples. Methods RNA from FFPE samples was extracted using two different methods, Ambion and Agencourt, and its quality was determined by profiling starting total RNA on Bioanalyzer and by amplifying increasing size fragments of beta actin (ACTB and claudin 3 (CLDN3 by reverse-transcriptase polymerase chain reaction. Five matched FF and FFPE ovarian serous adenocarcinoma samples, as well as a set of normal ovary samples, were profiled using whole genome Agilent microarrays. Reproducibility of the FF and FFPE replicates was measured using Pearson correlation, whereas comparison between the FF and FFPE samples was done using a Z-score analysis. Results Data analysis showed high reproducibility of expression within each FF and FFPE method, whereas matched FF and FFPE pairs demonstrated lower similarity, emphasizing an inherent difference between the two sample types. Z-score analysis of matched FF and FFPE samples revealed good concordance of top 100 differentially expressed genes with the highest correlation of 0.84. Genes characteristic of ovarian serous adenocarcinoma, including a well known marker CLDN3, as well as potentially some novel markers, were identified by comparing gene expression profiles of ovarian adenocarcinoma to those of normal ovary. Conclusion Conclusively, we showed that systematic assessment
Davies Jonathan J
Full Text Available Abstract Background The prevalence of high resolution profiling of genomes has created a need for the integrative analysis of information generated from multiple methodologies and platforms. Although the majority of data in the public domain are gene expression profiles, and expression analysis software are available, the increase of array CGH studies has enabled integration of high throughput genomic and gene expression datasets. However, tools for direct mining and analysis of array CGH data are limited. Hence, there is a great need for analytical and display software tailored to cross platform integrative analysis of cancer genomes. Results We have created a user-friendly java application to facilitate sophisticated visualization and analysis such as cross-tumor and cross-platform comparisons. To demonstrate the utility of this software, we assembled array CGH data representing Affymetrix SNP chip, Stanford cDNA arrays and whole genome tiling path array platforms for cross comparison. This cancer genome database contains 267 profiles from commonly used cancer cell lines representing 14 different tissue types. Conclusion In this study we have developed an application for the visualization and analysis of data from high resolution array CGH platforms that can be adapted for analysis of multiple types of high throughput genomic datasets. Furthermore, we invite researchers using array CGH technology to deposit both their raw and processed data, as this will be a continually expanding database of cancer genomes. This publicly available resource, the System for Integrative Genomic Microarray Analysis (SIGMA of cancer genomes, can be accessed at http://sigma.bccrc.ca.
Wapner, Ronald J; Martin, Christa Lese; Levy, Brynn; Ballif, Blake C; Eng, Christine M; Zachary, Julia M; Savage, Melissa; Platt, Lawrence D; Saltzman, Daniel; Grobman, William A; Klugman, Susan; Scholl, Thomas; Simpson, Joe Leigh; McCall, Kimberly; Aggarwal, Vimla S; Bunke, Brian; Nahum, Odelia; Patel, Ankita; Lamb, Allen N; Thom, Elizabeth A; Beaudet, Arthur L; Ledbetter, David H; Shaffer, Lisa G; Jackson, Laird
Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. We aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. We enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down's syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733.).
Lo, Ken C; Shankar, Ganesh; Turpaz, Yaron; Bailey, Dione; Rossi, Michael R; Burkhardt, Tania; Liang, Ping; Cowell, John K
The Overlay Tool has been developed to combine high throughput data derived from various microarray platforms. This tool analyzes high-resolution correlations between gene expression changes and either copy number abnormalities (CNAs) or loss of heterozygosity events detected using array comparative genomic hybridization (aCGH). Using an overlay analysis which is designed to be performed using data from multiple microarray platforms on a single biological sample, the Overlay Tool identifies potentially important genes whose expression profiles are changed as a result of losses, gains and amplifications in the cancer genome. In addition, the Overlay Tool will incorporate loss of heterozygosity (LOH) probability data into this overlay procedure. To facilitate this analysis, we developed an application which computationally combines two or more high throughput datasets (e.g. aCGH/expression) into a single categorized dataset for visualization and interrogation using a gene-centric approach. As such, data from virtually any microarray platform can be incorporated without the need to remap entire datasets individually. The resultant categorized (overlay) data set can be conveniently viewed using our in-house visualization tool, aCGHViewer (Shankar et al. 2006), which serves as a conduit to public databases such as UCSC and NCBI, to rapidly investigate genes of interest.
Tea, Melinda; Fogarty, Rhys; Brereton, Helen M; Michael, Michael Z; Van der Hoek, Mark B; Tsykin, Anna; Coster, Douglas J; Williams, Keryn A
Different inbred strains of rat differ in their susceptibility to oxygen-induced retinopathy (OIR), an animal model of human retinopathy of prematurity. We examined gene expression in Sprague-Dawley (susceptible) and Fischer 344 (resistant) neonatal rats after 3 days exposure to cyclic hyperoxia or room air, using Affymetrix rat Genearrays. False discovery rate analysis was used to identify differentially regulated genes. Such genes were then ranked by fold change and submitted to the online database, DAVID. The Sprague-Dawley list returned the term "response to hypoxia," absent from the Fischer 344 output. Manual analysis indicated that many genes known to be upregulated by hypoxia-inducible factor-1alpha were downregulated by cyclic hyperoxia. Quantitative real-time RT-PCR analysis of Egln3, Bnip3, Slc16a3, and Hk2 confirmed the microarray results. We conclude that combined methodologies are required for adequate dissection of the pathophysiology of strain susceptibility to OIR in the rat. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s12177-009-9041-7) contains supplementary material, which is available to authorized users.
Full Text Available Among non-small cell lung cancer (NSCLC, adenocarcinoma (AC, and squamous cell carcinoma (SCC are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR, can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed.
Zhang, Lei; Wang, Linlin; Du, Bochuan; Wang, Tianjiao; Tian, Pu; Tian, Suyan
Among non-small cell lung cancer (NSCLC), adenocarcinoma (AC), and squamous cell carcinoma (SCC) are two major histology subtypes, accounting for roughly 40% and 30% of all lung cancer cases, respectively. Since AC and SCC differ in their cell of origin, location within the lung, and growth pattern, they are considered as distinct diseases. Gene expression signatures have been demonstrated to be an effective tool for distinguishing AC and SCC. Gene set analysis is regarded as irrelevant to the identification of gene expression signatures. Nevertheless, we found that one specific gene set analysis method, significance analysis of microarray-gene set reduction (SAMGSR), can be adopted directly to select relevant features and to construct gene expression signatures. In this study, we applied SAMGSR to a NSCLC gene expression dataset. When compared with several novel feature selection algorithms, for example, LASSO, SAMGSR has equivalent or better performance in terms of predictive ability and model parsimony. Therefore, SAMGSR is a feature selection algorithm, indeed. Additionally, we applied SAMGSR to AC and SCC subtypes separately to discriminate their respective stages, that is, stage II versus stage I. Few overlaps between these two resulting gene signatures illustrate that AC and SCC are technically distinct diseases. Therefore, stratified analyses on subtypes are recommended when diagnostic or prognostic signatures of these two NSCLC subtypes are constructed.
M J Pont
Full Text Available Cellular immunotherapy has proven to be effective in the treatment of hematological cancers by donor lymphocyte infusion after allogeneic hematopoietic stem cell transplantation and more recently by targeted therapy with chimeric antigen or T-cell receptor-engineered T cells. However, dependent on the tissue distribution of the antigens that are targeted, anti-tumor responses can be accompanied by undesired side effects. Therefore, detailed tissue distribution analysis is essential to estimate potential efficacy and toxicity of candidate targets for immunotherapy of hematological malignancies. We performed microarray gene expression analysis of hematological malignancies of different origins, healthy hematopoietic cells and various non-hematopoietic cell types from organs that are often targeted in detrimental immune responses after allogeneic stem cell transplantation leading to graft-versus-host disease. Non-hematopoietic cells were also cultured in the presence of IFN-γ to analyze gene expression under inflammatory circumstances. Gene expression was investigated by Illumina HT12.0 microarrays and quality control analysis was performed to confirm the cell-type origin and exclude contamination of non-hematopoietic cell samples with peripheral blood cells. Microarray data were validated by quantitative RT-PCR showing strong correlations between both platforms. Detailed gene expression profiles were generated for various minor histocompatibility antigens and B-cell surface antigens to illustrate the value of the microarray dataset to estimate efficacy and toxicity of candidate targets for immunotherapy. In conclusion, our microarray database provides a relevant platform to analyze and select candidate antigens with hematopoietic (lineage-restricted expression as potential targets for immunotherapy of hematological cancers.
Pont, M J; Honders, M W; Kremer, A N; van Kooten, C; Out, C; Hiemstra, P S; de Boer, H C; Jager, M J; Schmelzer, E; Vries, R G; Al Hinai, A S; Kroes, W G; Monajemi, R; Goeman, J J; Böhringer, S; Marijt, W A F; Falkenburg, J H F; Griffioen, M
Cellular immunotherapy has proven to be effective in the treatment of hematological cancers by donor lymphocyte infusion after allogeneic hematopoietic stem cell transplantation and more recently by targeted therapy with chimeric antigen or T-cell receptor-engineered T cells. However, dependent on the tissue distribution of the antigens that are targeted, anti-tumor responses can be accompanied by undesired side effects. Therefore, detailed tissue distribution analysis is essential to estimate potential efficacy and toxicity of candidate targets for immunotherapy of hematological malignancies. We performed microarray gene expression analysis of hematological malignancies of different origins, healthy hematopoietic cells and various non-hematopoietic cell types from organs that are often targeted in detrimental immune responses after allogeneic stem cell transplantation leading to graft-versus-host disease. Non-hematopoietic cells were also cultured in the presence of IFN-γ to analyze gene expression under inflammatory circumstances. Gene expression was investigated by Illumina HT12.0 microarrays and quality control analysis was performed to confirm the cell-type origin and exclude contamination of non-hematopoietic cell samples with peripheral blood cells. Microarray data were validated by quantitative RT-PCR showing strong correlations between both platforms. Detailed gene expression profiles were generated for various minor histocompatibility antigens and B-cell surface antigens to illustrate the value of the microarray dataset to estimate efficacy and toxicity of candidate targets for immunotherapy. In conclusion, our microarray database provides a relevant platform to analyze and select candidate antigens with hematopoietic (lineage)-restricted expression as potential targets for immunotherapy of hematological cancers.
Maggioni, Mauro; Davis, Gustave L.; Warner, Frederick J.; Geshwind, Frank B.; Coppi, Andreas C.; DeVerse, Richard A.; Coifman, Ronald R.
We apply a unique micro-optoelectromechanical tuned light source and new algorithms to the hyper-spectral microscopic analysis of human colon biopsies. The tuned light prototype (Plain Sight Systems Inc.) transmits any combination of light frequencies, range 440nm 700nm, trans-illuminating H and E stained tissue sections of normal (N), benign adenoma (B) and malignant carcinoma (M) colon biopsies, through a Nikon Biophot microscope. Hyper-spectral photomicrographs, randomly collected 400X magnication, are obtained with a CCD camera (Sensovation) from 59 different patient biopsies (20 N, 19 B, 20 M) mounted as a microarray on a single glass slide. The spectra of each pixel are normalized and analyzed to discriminate among tissue features: gland nuclei, gland cytoplasm and lamina propria/lumens. Spectral features permit the automatic extraction of 3298 nuclei with classification as N, B or M. When nuclei are extracted from each of the 59 biopsies the average classification among N, B and M nuclei is 97.1%; classification of the biopsies, based on the average nuclei classification, is 100%. However, when the nuclei are extracted from a subset of biopsies, and the prediction is made on nuclei in the remaining biopsies, there is a marked decrement in performance to 60% across the 3 classes. Similarly the biopsy classification drops to 54%. In spite of these classification differences, which we believe are due to instrument and biopsy normalization issues, hyper-spectral analysis has the potential to achieve diagnostic efficiency needed for objective microscopic diagnosis.
Sarah E Mercer
Full Text Available The inability to functionally repair tissues that are lost as a consequence of disease or injury remains a significant challenge for regenerative medicine. The molecular and cellular processes involved in complete restoration of tissue architecture and function are expected to be complex and remain largely unknown. Unlike humans, certain salamanders can completely regenerate injured tissues and lost appendages without scar formation. A parsimonious hypothesis would predict that all of these regenerative activities are regulated, at least in part, by a common set of genes. To test this hypothesis and identify genes that might control conserved regenerative processes, we performed a comprehensive microarray analysis of the early regenerative response in five regeneration-competent tissues from the newt Notophthalmus viridescens. Consistent with this hypothesis, we established a molecular signature for regeneration that consists of common genes or gene family members that exhibit dynamic differential regulation during regeneration in multiple tissue types. These genes include members of the matrix metalloproteinase family and its regulators, extracellular matrix components, genes involved in controlling cytoskeleton dynamics, and a variety of immune response factors. Gene Ontology term enrichment analysis validated and supported their functional activities in conserved regenerative processes. Surprisingly, dendrogram clustering and RadViz classification also revealed that each regenerative tissue had its own unique temporal expression profile, pointing to an inherent tissue-specific regenerative gene program. These new findings demand a reconsideration of how we conceptualize regenerative processes and how we devise new strategies for regenerative medicine.
Mercer, Sarah E.; Cheng, Chia-Ho; Atkinson, Donald L.; Krcmery, Jennifer; Guzman, Claudia E.; Kent, David T.; Zukor, Katherine; Marx, Kenneth A.; Odelberg, Shannon J.; Simon, Hans-Georg
The inability to functionally repair tissues that are lost as a consequence of disease or injury remains a significant challenge for regenerative medicine. The molecular and cellular processes involved in complete restoration of tissue architecture and function are expected to be complex and remain largely unknown. Unlike humans, certain salamanders can completely regenerate injured tissues and lost appendages without scar formation. A parsimonious hypothesis would predict that all of these regenerative activities are regulated, at least in part, by a common set of genes. To test this hypothesis and identify genes that might control conserved regenerative processes, we performed a comprehensive microarray analysis of the early regenerative response in five regeneration-competent tissues from the newt Notophthalmus viridescens. Consistent with this hypothesis, we established a molecular signature for regeneration that consists of common genes or gene family members that exhibit dynamic differential regulation during regeneration in multiple tissue types. These genes include members of the matrix metalloproteinase family and its regulators, extracellular matrix components, genes involved in controlling cytoskeleton dynamics, and a variety of immune response factors. Gene Ontology term enrichment analysis validated and supported their functional activities in conserved regenerative processes. Surprisingly, dendrogram clustering and RadViz classification also revealed that each regenerative tissue had its own unique temporal expression profile, pointing to an inherent tissue-specific regenerative gene program. These new findings demand a reconsideration of how we conceptualize regenerative processes and how we devise new strategies for regenerative medicine. PMID:23300656
Nalin C W Goonesekere
Full Text Available The lack of specific symptoms at early tumor stages, together with a high biological aggressiveness of the tumor contribute to the high mortality rate for pancreatic cancer (PC, which has a five year survival rate of less than 5%. Improved screening for earlier diagnosis, through the detection of diagnostic and prognostic biomarkers provides the best hope of increasing the rate of curatively resectable carcinomas. Though many serum markers have been reported to be elevated in patients with PC, so far, most of these markers have not been implemented into clinical routine due to low sensitivity or specificity. In this study, we have identified genes that are significantly upregulated in PC, through a meta-analysis of large number of microarray datasets. We demonstrate that the biological functions ascribed to these genes are clearly associated with PC and metastasis, and that that these genes exhibit a strong link to pathways involved with inflammation and the immune response. This investigation has yielded new targets for cancer genes, and potential biomarkers for pancreatic cancer. The candidate list of cancer genes includes protein kinase genes, new members of gene families currently associated with PC, as well as genes not previously linked to PC. In this study, we are also able to move towards developing a signature for hypomethylated genes, which could be useful for early detection of PC. We also show that the significantly upregulated 800+ genes in our analysis can serve as an enriched pool for tissue and serum protein biomarkers in pancreatic cancer.
Suresh V. Kuchipudi
Full Text Available The data described in this article pertain to the article by Kuchipudi et al. (2014 titled “Highly Pathogenic Avian Influenza Virus Infection in Chickens But Not Ducks Is Associated with Elevated Host Immune and Pro-inflammatory Responses” . While infection of chickens with highly pathogenic avian influenza (HPAI H5N1 virus subtypes often leads to 100% mortality within 1 to 2 days, infection of ducks in contrast causes mild or no clinical signs. The rapid onset of fatal disease in chickens, but with no evidence of severe clinical symptoms in ducks, suggests underlying differences in their innate immune mechanisms. We used Chicken Genechip microarrays (Affymetrix to analyse the gene expression profiles of primary chicken and duck lung cells infected with a low pathogenic avian influenza (LPAI H2N3 virus and two HPAI H5N1 virus subtypes to understand the molecular basis of host susceptibility and resistance in chickens and ducks. Here, we described the experimental design, quality control and analysis that were performed on the data set. The data are publicly available through the Gene Expression Omnibus (GEOdatabase with accession number GSE33389, and the analysis and interpretation of these data are included in Kuchipudi et al. (2014 .
Dakshinamurti, Krishnamurti; Bagchi, Rushita A; Abrenica, Bernard; Czubryt, Michael P
Biotin is a B vitamin involved in multiple metabolic pathways. In humans, biotin deficiency is relatively rare but can cause dermatitis, alopecia, and perosis. Low biotin levels occur in individuals with type-2 diabetes, and supplementation with biotin plus chromium may improve blood sugar control. The acute effect on pancreatic gene expression of biotin repletion following chronic deficiency is unclear, therefore we induced biotin deficiency in adult male rats by feeding them a 20% raw egg white diet for 6 weeks. Animals were then randomized into 2 groups: one group received a single biotin supplement and returned to normal chow lacking egg white, while the second group remained on the depletion diet. After 1 week, pancreata were removed from biotin-deficient (BD) and biotin-repleted (BR) animals and RNA was isolated for microarray analysis. Biotin depletion altered gene expression in a manner indicative of inflammation, fibrosis, and defective pancreatic function. Conversely, biotin repletion activated numerous repair and anti-inflammatory pathways, reduced fibrotic gene expression, and induced multiple genes involved in pancreatic endocrine and exocrine function. A subset of the results was confirmed by quantitative real-time PCR analysis, as well as by treatment of pancreatic AR42J cells with biotin. The results indicate that biotin repletion, even after lengthy deficiency, results in the rapid induction of repair processes in the pancreas.
Full Text Available Abstract Background This study aimed to determine the miRNA profile in breast cancer stem cells (BCSCs and to explore the functions of characteristic BCSC miRNAs. Methods We isolated ESA+CD44+CD24-/low BCSCs from MCF-7 cells using fluorescence-activated cell sorting (FACS. A human breast cancer xenograft assay was performed to validate the stem cell properties of the isolated cells, and microarray analysis was performed to screen for BCSC-related miRNAs. These BCSC-related miRNAs were selected for bioinformatic analysis and target prediction using online software programs. Results The ESA+CD44+CD24-/low cells had up to 100- to 1000-fold greater tumor-initiating capability than the MCF-7 cells. Tumors initiated from the ESA+CD44+CD24-/low cells were included of luminal epithelial and myoepithelial cells, indicating stem cell properties. We also obtained miRNA profiles of ESA+CD44+CD24-/low BCSCs. Most of the possible targets of potential tumorigenesis-related miRNAs were oncogenes, anti-oncogenes or regulatory genes. Conclusions We identified a subset of miRNAs that were differentially expressed in BCSCs, providing a starting point to explore the functions of these miRNAs. Evaluating characteristic BCSC miRNAs represents a new method for studying breast cancer-initiating cells and developing therapeutic strategies aimed at eradicating the tumorigenic subpopulation of cells in breast cancer.
Kafieh, Rahele; Mehridehnavi, Alireza
In this study, we considered some competitive learning methods including hard competitive learning and soft competitive learning with/without fixed network dimensionality for reliability analysis in microarrays. In order to have a more extensive view, and keeping in mind that competitive learning methods aim at error minimization or entropy maximization (different kinds of function optimization), we decided to investigate the abilities of mixture decomposition schemes. Therefore, we assert that this study covers the algorithms based on function optimization with particular insistence on different competitive learning methods. The destination is finding the most powerful method according to a pre-specified criterion determined with numerical methods and matrix similarity measures. Furthermore, we should provide an indication showing the intrinsic ability of the dataset to form clusters before we apply a clustering algorithm. Therefore, we proposed Hopkins statistic as a method for finding the intrinsic ability of a data to be clustered. The results show the remarkable ability of Rayleigh mixture model in comparison with other methods in reliability analysis task. PMID:24083134
Penelope A Bryant
Full Text Available BACKGROUND: A central issue in the design of microarray-based analysis of global gene expression is the choice between using cells of single type and a mixture of cells. This study quantified the proportion of lipopolysaccharide (LPS induced differentially expressed monocyte genes that could be measured in peripheral blood mononuclear cells (PBMC, and determined the extent to which gene expression in the non-monocyte cell fraction diluted or obscured fold changes that could be detected in the cell mixture. METHODOLOGY/PRINCIPAL FINDINGS: Human PBMC were stimulated with LPS, and monocytes were then isolated by positive (Mono+ or negative (Mono- selection. The non-monocyte cell fraction (MonoD remaining after positive selection of monocytes was used to determine the effect of non-monocyte cells on overall expression. RNA from LPS-stimulated PBMC, Mono+, Mono- and MonoD samples was co-hybridised with unstimulated RNA for each cell type on oligonucleotide microarrays. There was a positive correlation in gene expression between PBMC and both Mono+ (0.77 and Mono- (0.61-0.67 samples. Analysis of individual genes that were differentially expressed in Mono+ and Mono- samples showed that the ability to detect expression of some genes was similar when analysing PBMC, but for others, differential expression was either not detected or changed in the opposite direction. As a result of the dilutional or obscuring effect of gene expression in non-monocyte cells, overall about half of the statistically significant LPS-induced changes in gene expression in monocytes were not detected in PBMC. However, 97% of genes with a four fold or greater change in expression in monocytes after LPS stimulation, and almost all (96-100% of the top 100 most differentially expressed monocyte genes were detected in PBMC. CONCLUSIONS/SIGNIFICANCE: The effect of non-responding cells in a mixture dilutes or obscures the detection of subtle changes in gene expression in an individual
H.M.J. Sontrop; P.D. Moerland; R. van den Ham; M.J.T. Reinders; W.F.J. Verhaegh
Background: Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for
cDNA microarray technology is used to profile complex diseases and discover novel disease-related genes. In inflammatory disease such as rheumatoid arthritis, expression patterns of diverse cell types contribute to the pathology. We have monitored gene expression in this disease state with a microarray of selected human genes of probable significance in inflammation as well as with genes expressed in peripheral human blood cells. Messenger RNA from cultured macrophages, chondrocyte cell lines...
Hirasawa, Takashi; Yoshikawa, Katsunori; Nakakura, Yuki; Nagahisa, Keisuke; Furusawa, Chikara; Katakura, Yoshio; Shimizu, Hiroshi; Shioya, Suteaki
During industrial production process using yeast, cells are exposed to the stress due to the accumulation of ethanol, which affects the cell growth activity and productivity of target products, thus, the ethanol stress-tolerant yeast strains are highly desired. To identify the target gene(s) for constructing ethanol stress tolerant yeast strains, we obtained the gene expression profiles of two strains of Saccharomyces cerevisiae, namely, a laboratory strain and a strain used for brewing Japanese rice wine (sake), in the presence of 5% (v/v) ethanol, using DNA microarray. For the selection of target genes for breeding ethanol stress tolerant strains, clustering of DNA microarray data was performed. For further selection, the ethanol sensitivity of the knockout mutants in each of which the gene selected by DNA microarray analysis is deleted, was also investigated. The integration of the DNA microarray data and the ethanol sensitivity data of knockout strains suggests that the enhancement of expression of genes related to tryptophan biosynthesis might confer the ethanol stress tolerance to yeast cells. Indeed, the strains overexpressing tryptophan biosynthesis genes showed a stress tolerance to 5% ethanol. Moreover, the addition of tryptophan to the culture medium and overexpression of tryptophan permease gene conferred ethanol stress tolerance to yeast cells. These results indicate that overexpression of the genes for trypophan biosynthesis increases the ethanol stress tolerance. Tryptophan supplementation to culture and overexpression of the tryptophan permease gene are also effective for the increase in ethanol stress tolerance. Our methodology for the selection of target genes for constructing ethanol stress tolerant strains, based on the data of DNA microarray analysis and phenotypes of knockout mutants, was validated.
Khaoustov, V. I.; Risin, D.; Pellis, N. R.; Yoffe, B.; McIntire, L. V. (Principal Investigator)
Developed at NASA, the rotary cell culture system (RCCS) allows the creation of unique microgravity environment of low shear force, high-mass transfer, and enables three-dimensional (3D) cell culture of dissimilar cell types. Recently we demonstrated that a simulated microgravity is conducive for maintaining long-term cultures of functional hepatocytes and promote 3D cell assembly. Using deoxyribonucleic acid (DNA) microarray technology, it is now possible to measure the levels of thousands of different messenger ribonucleic acids (mRNAs) in a single hybridization step. This technique is particularly powerful for comparing gene expression in the same tissue under different environmental conditions. The aim of this research was to analyze gene expression of hepatoblastoma cell line (HepG2) during early stage of 3D-cell assembly in simulated microgravity. For this, mRNA from HepG2 cultured in the RCCS was analyzed by deoxyribonucleic acid microarray. Analyses of HepG2 mRNA by using 6K glass DNA microarray revealed changes in expression of 95 genes (overexpression of 85 genes and downregulation of 10 genes). Our preliminary results indicated that simulated microgravity modifies the expression of several genes and that microarray technology may provide new understanding of the fundamental biological questions of how gravity affects the development and function of individual cells.
Kashofer, Karl; Viertler, Christian; Pichler, Martin; Zatloukal, Kurt
Analysis of RNA isolated from fixed and paraffin-embedded tissues is widely used in biomedical research and molecular pathological diagnostics. We have performed a comprehensive and systematic investigation of the impact of factors in the pre-analytical workflow, such as different fixatives, fixation time, RNA extraction method and storage of tissues in paraffin blocks, on several downstream reactions including complementary DNA (cDNA) synthesis, quantitative reverse transcription polymerase chain reaction (qRT-PCR) and microarray hybridization. We compared the effects of routine formalin fixation with the non-crosslinking, alcohol-based Tissue Tek Xpress Molecular Fixative (TTXMF, Sakura Finetek), and cryopreservation as gold standard for molecular analyses. Formalin fixation introduced major changes into microarray gene expression data and led to marked gene-to-gene variations in delta-ct values of qRT-PCR. We found that qRT-PCR efficiency and gene-to-gene variations were mainly attributed to differences in the efficiency of cDNA synthesis as the most sensitive step. These differences could not be reliably detected by quality assessment of total RNA isolated from formalin-fixed tissues by electrophoresis or spectrophotometry. Although RNA from TTXMF fixed samples was as fragmented as RNA from formalin fixed samples, much higher cDNA yield and lower ct-values were obtained in qRT-PCR underlining the negative impact of crosslinking by formalin. In order to better estimate the impact of pre-analytical procedures such as fixation on the reliability of downstream analysis, we applied a qRT-PCR-based assay using amplicons of different length and an assay measuring the efficiency of cDNA generation. Together these two assays allowed better quality assessment of RNA extracted from fixed and paraffin-embedded tissues and should be used to supplement quality scores derived from automated electrophoresis. A better standardization of the pre-analytical workflow, application
Hatt, Lotte; Aagaard, Mads M; Bach, Cathrine; Graakjaer, Jesper; Sommer, Steffen; Agerholm, Inge E; Kølvraa, Steen; Bojesen, Anders
Methylation-based non-invasive prenatal testing of fetal aneuploidies is an alternative method that could possibly improve fetal aneuploidy diagnosis, especially for trisomy 13(T13) and trisomy 18(T18). Our aim was to study the methylation landscape in placenta DNA from trisomy 13, 18 and 21 pregnancies in an attempt to find trisomy-specific methylation differences better suited for non-invasive prenatal diagnosis. We have conducted high-resolution methylation specific bead chip microarray analyses assessing more than 450,000 CpGs analyzing placentas from 12 T21 pregnancies, 12 T18 pregnancies and 6 T13 pregnancies. We have compared the methylation landscape of the trisomic placentas to the methylation landscape from normal placental DNA and to maternal blood cell DNA. Comparing trisomic placentas to normal placentas we identified 217 and 219 differentially methylated CpGs for CVS T18 and CVS T13, respectively (delta β>0.2, FDR<0.05), but only three differentially methylated CpGs for T21. However, the methylation differences was only modest (delta β<0.4), making them less suitable as diagnostic markers. Gene ontology enrichment analysis revealed that the gene set connected to theT18 differentially methylated CpGs was highly enriched for GO terms related to"DNA binding" and "transcription factor binding" coupled to the RNA polymerase II transcription. In the gene set connected to the T13 differentially methylated CpGs we found no significant enrichments.
Nolwenn M Dheilly
Full Text Available BACKGROUND: The Pacific oyster Crassostrea gigas (Mollusca, Lophotrochozoa is an alternative and irregular protandrous hermaphrodite: most individuals mature first as males and then change sex several times. Little is known about genetic and phenotypic basis of sex differentiation in oysters, and little more about the molecular pathways regulating reproduction. We have recently developed and validated a microarray containing 31,918 oligomers (Dheilly et al., 2011 representing the oyster transcriptome. The application of this microarray to the study of mollusk gametogenesis should provide a better understanding of the key factors involved in sex differentiation and the regulation of oyster reproduction. METHODOLOGY/PRINCIPAL FINDINGS: Gene expression was studied in gonads of oysters cultured over a yearly reproductive cycle. Principal component analysis and hierarchical clustering showed a significant divergence in gene expression patterns of males and females coinciding with the start of gonial mitosis. ANOVA analysis of the data revealed 2,482 genes differentially expressed during the course of males and/or females gametogenesis. The expression of 434 genes could be localized in either germ cells or somatic cells of the gonad by comparing the transcriptome of female gonads to the transcriptome of stripped oocytes and somatic tissues. Analysis of the annotated genes revealed conserved molecular mechanisms between mollusks and mammals: genes involved in chromatin condensation, DNA replication and repair, mitosis and meiosis regulation, transcription, translation and apoptosis were expressed in both male and female gonads. Most interestingly, early expressed male-specific genes included bindin and a dpy-30 homolog and female-specific genes included foxL2, nanos homolog 3, a pancreatic lipase related protein, cd63 and vitellogenin. Further functional analyses are now required in order to investigate their role in sex differentiation in oysters
Full Text Available Abstract Background Gene expression measurements from breast cancer (BrCa tumors are established clinical predictive tools to identify tumor subtypes, identify patients showing poor/good prognosis, and identify patients likely to have disease recurrence. However, diverse breast cancer datasets in conjunction with diagnostic clinical arrays show little overlap in the sets of genes identified. One approach to identify a set of consistently dysregulated candidate genes in these tumors is to employ meta-analysis of multiple independent microarray datasets. This allows one to compare expression data from a diverse collection of breast tumor array datasets generated on either cDNA or oligonucleotide arrays. Results We gathered expression data from 9 published microarray studies examining estrogen receptor positive (ER+ and estrogen receptor negative (ER- BrCa tumor cases from the Oncomine database. We performed a meta-analysis and identified genes that were universally up or down regulated with respect to ER+ versus ER- tumor status. We surveyed both the proximal promoter and 3' untranslated regions (3'UTR of our top-ranking genes in each expression group to test whether common sequence elements may contribute to the observed expression patterns. Utilizing a combination of known transcription factor binding sites (TFBS, evolutionarily conserved mammalian promoter and 3'UTR motifs, and microRNA (miRNA seed sequences, we identified numerous motifs that were disproportionately represented between the two gene classes suggesting a common regulatory network for the observed gene expression patterns. Conclusion Some of the genes we identified distinguish key transcripts previously seen in array studies, while others are newly defined. Many of the genes identified as overexpressed in ER- tumors were previously identified as expression markers for neoplastic transformation in multiple human cancers. Moreover, our motif analysis identified a collection of
Jehee, Fernanda Sarquis; Rosenberg, Carla; Krepischi-Santos, Ana Cristina; Kok, Fernando; Knijnenburg, Jeroen; Froyen, Guy; Vianna-Morgante, Angela M; Opitz, John M; Passos-Bueno, Maria Rita
FG syndrome is an X-linked multiple congenital anomalies (MCA) syndrome. It has been mapped to four distinct loci FGS1-4, through linkage analysis (Xq13, Xp22.3, and Xp11.4-p11.3) and based on the breakpoints of an X chromosome inversion (Xq11:Xq28), but so far no gene has been identified. We describe a boy with FG syndrome who has an inherited duplication at band Xq22.3 detected by comparative genomic hybridization microarray (Array-CGH). These duplication maps outside all four loci described so far for FG syndrome, representing therefore a new locus, which we propose to be called FGS5. MID2, a gene closely related to MID1, which is known to be mutated in Opitz G/BBB syndrome, maps within the duplicated segment of our patient. Since FG and Opitz G/BBB syndromes share many manifestations we considered MID2 a candidate gene for FG syndrome. We also discuss the involvement of other potential genes within the duplicated segment and its relationship with clinical symptoms of our patient, as well as the laboratory abnormalities found in his mother, a carrier of the duplication.
Ma, Lan; Lei, Zhen; Liu, Xia; Liu, Dianjun; Wang, Zhenxin
DNA methylation is a crucial epigenetic modification and is closely related to tumorigenesis. Herein, a surface ligation-based high throughput method combined with bisulfite treatment is developed for analysis of methylated genomic DNA. In this method, a DNA microarray is employed as a reaction platform, and resonance light scattering (RLS) of nanoparticles is used as the detection principle. The specificity stems from allele-specific ligation of Taq DNA ligase, which is further enhanced by improving the fidelity of Taq DNA ligase in a heterogeneous reaction. Two amplification techniques, rolling circle amplification (RCA) and silver enhancement, are employed after the ligation reaction and a gold nanoparticle (GNP) labeling procedure is used to amplify the signal. As little as 0.01% methylated DNA (i.e. 2 pmol L(-1)) can be distinguished from the cocktail of methylated and unmethylated DNA by the proposed method. More importantly, this method shows good accuracy and sensitivity in profiling the methylation level of genomic DNA of three selected colonic cancer cell lines. This strategy provides a high throughput alternative with reasonable sensitivity and resolution for cancer study and diagnosis.
Gu, Junxia; Liang, Yuting; Qiao, Longwei; Li, Xiaoyun; Li, Xingang; Lu, Yaojuan; Zheng, Qiping
Multiple studies have recently demonstrated the oncogenic property of URI (or RMP, a member of the prefoldin family of molecular chaperones) during progression of hepatocellular carcinoma, ovarian cancer, and possibly prostate cancer. Most recently, we have shown that URI/RMP is up-regulated in cervical cancer, another reproductive system tumor beside ovarian and prostate cancers. To investigate if URI/RMP also plays a role in other reproductive system tumors, especially in endometrioid adenocarcinoma, we analyzed URI/RMP expression in a TMA (tissue microarray) containing tissues from 30 cases of endometrioid adenocarcinoma (which covers tumor tissues from Grade I through Grade III) and adjacent endometrium by immunohistochemistry (IHC) and densitometry analysis using image-pro plus 6.0 software. Our results showed that the mean density of URI/RMP expression in cancerous tissue is slightly higher than that of the adjacent endometrial tissue, though not statistically significant (p>0.05). There is no significant difference either between the mean density of Grade III cancerous tissue and that of Grade I and II cancers. Notably, we detected significantly higher signal intensity in cancerous tissue of all 7 Grade III cases than that of their adjacent endometrial tissue (ptissues of adjacent endometrium or gland suggests a diagnostic and possibly, a prognostic value of URI/RMP in endometrioid adenocarcinoma.
Full Text Available Rheumatoid arthritis (RA is a chronic inflammatory disease of autoimmune origin. Huo-luo-xiao-ling dan (HLXL is an herbal mixture that has been used in traditional Chinese medicine over several decades to treat chronic inflammatory diseases including RA. However, the mechanism of the anti-arthritic action of this herbal remedy is poorly understood at the molecular level. In this study, we determined by microarray analysis the effects of HLXL on the global gene expression profile of the draining lymph node cells (LNC in the rat adjuvant arthritis (AA model of human RA. In LNC restimulated in vitro with the disease-related antigen mycobacterial heat-shock protein 65 (Bhsp65, 84 differentially expressed genes (DEG (64 upregulated and 20 downregulated versus 120 DEG (94 upregulated and 26 downregulated were identified in HLXL-treated versus vehicle (Water-treated rats, respectively, and 62 DEG (45 upregulated and 17 downregulated were shared between the two groups. The most affected pathways in response to HLXL treatment included immune response, inflammation, cellular proliferation and apoptosis, and metabolic processes, many of which are directly relevant to arthritis pathogenesis. These results would advance our understanding of the mechanisms underlying the anti-arthritic activity of HLXL.
Zhao, Jia; Patwa, Tasneem H.; Pal, Manoj; Qiu, Weilian; Lubman, David M.
Summary Protein glycosylation and phosphorylation are very common posttranslational modifications. The alteration of these modifications in cancer cells is closely related to the onset and progression of cancer and other disease states. In this protocol, strategies for monitoring the changes in protein glycosylation and phosphorylation in serum or tissue cells on a global scale and specifically characterizing these alterations are included. The technique is based on lectin affinity enrichment for glycoproteins, all liquid-phase two-dimensional fractionation, protein microarray, and mass spectrometry technology. Proteins are separated based on pI in the first dimension using chromatofocusing (CF) or liquid isoelectric focusing (IEF) followed by the second-dimension separation using nonporous silica RP-HPLC. Five lectins with different binding specificities to glycan structures are used for screening glycosylation patterns in human serum through a biotin–streptavidin system. Fluorescent phosphodyes and phosphospecific antibodies are employed to detect specific phosphorylated proteins in cell lines or human tissues. The purified proteins of interest are identified by peptide sequencing. Their modifications including glycosylation and phosphorylation could be further characterized by mass-spectrometry-based approaches. These strategies can be used in biological samples for large-scale glycoproteome/phosphoproteome screening as well as for individual protein modification analysis. PMID:19241043
Full Text Available Objectives : Neurological disorders have been one of main therapeutic targets of acupuncture. The present study investigated the protective effects of Gwakhyangjeonggisan herbal acupuncture solution (GHAS. Methods : We performed 3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide (MTT assay in glioblastoma cells, and did microarray analysis with cells exposed to reactive oxigen species (ROS of hydrogen peroxide by 8.0 k Human cDNA, with cut-off level of 2-fold changes in gene expression. Results : MTT assay showed protective effect of GHAS on the glioblastoma cells exposed to hydrogen peroxide. When glioblastoma cells were exposed to hydrogen peroxide, 24 genes were downregulated. When the cells were pretreated with GHAS before exposure to hydrogen peroxide, 46 genes were downregulated. Many of the genes downregulated by hydrogen peroxide stimulation were decreased in the amount of downregulation or reversed to upregulation. Conclusions : The gene expression changes observed in the present study are supposed to be related to the protective molecular mechanism of GHAS in the glioblastoma cells exposed to ROS stress.
William Grundy; Manuel Ares, Jr.; David Haussler
The authors 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. They 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, they use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.
Stein, T. Peter; Wade, Charles E.
PURPOSE OF REVIEW: In response to decreased usage, skeletal muscle undergoes adaptive reductive remodeling due to the decrease in tension on the weight bearing components of the musculo-skeletal system. This response occurs with uncomplicated disuse (e.g. bed rest, space flight), as a secondary consequence of several widely prevalent chronic diseases for which activity is reduced (e.g. chronic obstructive pulmonary disease and chronic heart failure) and is part of the aging process. The problem is therefore one of considerable clinical importance. RECENT FINDINGS: The impaired function and exercise intolerance is related more to the associated muscle wasting rather than to the specific organ system primarily impacted by the disease. Progress has continued in describing the use of anabolic drugs and dietary manipulation. The major advance in the field has been: (i) the discovery of the atrogin-1 gene and (ii) the application of microarray expression analysis and proteomics with the objectives of obtaining comprehensive understanding of the pathways changed with disuse atrophy. SUMMARY: Disuse atrophy is a common clinical problem. There is a need for therapeutic interventions that do not involve exercise. A better understanding of the changes, particularly at the molecular level, could indicate hitherto unsuspected sites for nutritional and pharmacological intervention.
Full Text Available Abstract Background The biomedical literature is a rich source of associative information but too vast for complete manual review. We have developed an automated method of literature interrogation called "Literature Lab" that identifies and ranks associations existing in the literature between gene sets, such as those derived from microarray experiments, and curated sets of key terms (i.e. pathway names, medical subject heading (MeSH terms, etc. Results Literature Lab was developed using differentially expressed gene sets from three previously published cancer experiments and tested on a fourth, novel gene set. When applied to the genesets from the published data including an in vitro experiment, an in vivo mouse experiment, and an experiment with human tumor samples, Literature Lab correctly identified known biological processes occurring within each experiment. When applied to a novel set of genes differentially expressed between locally invasive and metastatic prostate cancer, Literature Lab identified a strong association between the pathway term "FOSB" and genes with increased expression in metastatic prostate cancer. Immunohistochemistry subsequently confirmed increased nuclear FOSB staining in metastatic compared to locally invasive prostate cancers. Conclusion This work demonstrates that Literature Lab can discover key biological processes by identifying meritorious associations between experimentally derived gene sets and key terms within the biomedical literature.
Full Text Available Background/Aims: Neural stem/ progenitor cells (NPCs endure important changes in cell volume during growth, proliferation and migration. As a first approach to know about NPC response to cell volume changes, the Regulatory Volume Decrease (RVD subsequent to hypotonic swelling was investigated. Methods: NPCs obtained from the mesencephalon and the subventricular zone of embryonic and adult mice, respectively, were grown and cultured as neurospheres. Cell volume changes were measured by large-angle light-scattering and taurine efflux by [3H]-taurine. Expression of genes encoding molecules related to RVD was analysed using a DNA microarray obtained from NPC samples. Results: Embryonic and adult NPCs exposed to osmolarity reduction (H15, H30, H40 exhibited rapid swelling followed by RVD. The magnitude, efficiency and pharmacological profile, of RVD and of [3H]-taurine osmosensitive efflux were comparable to those found in cultured brain cells, astrocytes and neurons. The relative expression of genes encoding molecules related to volume regulation, i.e. K+ and Cl- channels, cotransporters, exchangers and aquaporins were identified in NPCs. Conclusion: NPCs show the ability to respond to hypotonic-evoked volume changes by adaptative recovery processes, similar to those found in other cultured brain cells. Genes related to molecules involved in RVD were found expressed in NPCs.
Yue, Liling; Han, Cuicui; Li, Zubin; Li, Xin; Liu, Deshui; Liu, Shulin; Yu, Haitao
The aim of this study was to compare the expression of fucosyltransferase 8 (FUT8) in breast cancer tissue and to investigate the relationship between this marker with tumor progression and its applicability to differential diagnosis. An immunohistochemical study was performed for FUT8 using the tissue microarray technique. In addition, the mRNA and protein levels of FUT8 in the tissue were also tested by real-time PCR and Western blot. There was a significant difference in cytoplasmic expression of FUT8 between breast cancer tissue and matched normal tissue (ptissues ranging from negative, weak positive, positive and strong positive were 2.7%, 40.2%, 54% and 3.2%, respectively. High FUT8 protein expression correlated with lymphatic metastasis (p=0.008) and with stage status (p=0.039). We detected that reduced FUT8 expression correlated with disease-free survival (p=0.02) and overall survival (p=0.04) of breast cancer patients. Expression of FUT8 can stratify breast cancer tissue and may be considered a prognostic marker for breast cancer patients.
Mohsenzadegan, Monireh; Madjd, Zahra; Asgari, Mojgan; Abolhasani, Maryam; Shekarabi, Mehdi; Taeb, Jaleh; Shariftabrizi, Ahmad
New gene expressed in prostate (NGEP) is a newly diagnosed prostate-specific gene that is expressed only in normal prostate and prostate cancer cells. Discovery of tissue-specific markers may promote the development of novel targets for immunotherapy of prostate cancer. In the present study, the staining pattern and clinical significance of NGEP were evaluated in a series of prostate tissues composed of 123 prostate cancer, 19 high-grade prostatic intraepithelial neoplasia and 44 samples of benign prostate tissue included in tissue microarrays using immunohistochemistry. Our study demonstrated that NGEP localized mainly in the apical and lateral membranes and was also partially distributed in the cytoplasm of epithelial cells of normal prostate tissue. All of the examined prostate tissues expressed NGEP with a variety of intensities; the level of expression was significantly more in the benign prostate tissues compared to malignant prostate samples (P value tissues, and the intensity of expression is inversely proportional to the level of malignancy. NGEP could be an attractive target for immune-based therapy of prostate cancer patients as an alternative to the conventional therapies particularly in indolent patients.
Full Text Available Personalized therapy is “the right drug for the right patient at the right time”. Here we reported a case of personalized therapy using gene expression signature (GES related drug discovery to treat a patient with drug-resistant metastases from breast-tumor. Methods: After mRNA obtained from metastatic liver tissue was performed by microarray, GES of genomic profiles were uncovered by bioinformatics tool and targeting drugs related with GES were mined by drug-bank. Several targeting-drugs approved by FDA were selected to treat the patient. Results: 1198 genes were uncovered for the higher expression by two-fold to compare normal liver specimens in which 10 of mined genes were identified as set-1 GES for metastasis and 16 of genes were uncovered as set-2 directly for primary breast tumor. Drug-bank platform were used to discover drugs for target set-1/2 genes. Eventually, medropxyoprogesterone (MPA targeting set-I gene and doxorubicin targeting set-2 gene were selected for the patient because the two drugs have already been approved by FDA. After doxorubicin and MPA were administered, patient's metastatic-tumor showed complete response. Conclusions: We not only analyze genomic expression profiles but also discover sensitive compounds for drug-resistant tumor. We successfully select drugs approved by FDA to treat the patient.
Jakupović, Mirza; Heintz, Manuel; Reichmann, Peter; Mendgen, Kurt; Hahn, Matthias
Rust fungi are plant parasites which colonise host tissue with an intercellular mycelium that forms haustoria within living plant cells. To identify genes expressed during biotrophic growth, EST sequencing was performed with a haustorium-specific cDNA library from Uromyces fabae. One thousand seventeen ESTs were generated, which assembled into 530 contigs. Several of the most frequently represented sequences in the EST database were identical to the in planta induced genes (PIGs) identified previously (Hahn, M., Mendgen, K., 1997. Characterisation of in planta-induced rust genes isolated from a haustorium-specific cDNA library, Mol. Plant-Microbe Interact. 10, 427-437). Virus-encoded sequences were identified, providing evidence for two novel RNA mycoviruses in U. fabae. Microarray hybridisation revealed many cDNAs that were significantly activated in rust-infected leaves compared to germinated uredospores. Very strong in planta expression was found for two PIGs encoding putative metallothioneins. Furthermore, several genes involved in ribosome biogenesis and translation, glycolysis, amino acid metabolism, stress response, and detoxification showed an increased expression in the parasitic mycelium. These data indicate a strong shift in gene expression in rust fungi between germination and the biotrophic stage of development.
Full Text Available Abstract Background Lactococcus garvieae is a bacterial pathogen that affects different animal species in addition to humans. Despite the widespread distribution and emerging clinical significance of L. garvieae in both veterinary and human medicine, there is almost a complete lack of knowledge about the genetic content of this microorganism. In the present study, the genomic content of L. garvieae CECT 4531 was analysed using bioinformatics tools and microarray-based comparative genomic hybridization (CGH experiments. Lactococcus lactis subsp. lactis IL1403 and Streptococcus pneumoniae TIGR4 were used as reference microorganisms. Results The combination and integration of in silico analyses and in vitro CGH experiments, performed in comparison with the reference microorganisms, allowed establishment of an inter-species hybridization framework with a detection threshold based on a sequence similarity of ≥ 70%. With this threshold value, 267 genes were identified as having an analogue in L. garvieae, most of which (n = 258 have been documented for the first time in this pathogen. Most of the genes are related to ribosomal, sugar metabolism or energy conversion systems. Some of the identified genes, such as als and mycA, could be involved in the pathogenesis of L. garvieae infections. Conclusions In this study, we identified 267 genes that were potentially present in L. garvieae CECT 4531. Some of the identified genes could be involved in the pathogenesis of L. garvieae infections. These results provide the first insight into the genome content of L. garvieae.
Full Text Available Abstract Background The increasing complexity of genomic data presents several challenges for biologists. Limited computer monitor views of data complexity and the dynamic nature of data in the midst of discovery increase the challenge of integrating experimental results with information resources. The use of Gene Ontology enables researchers to summarize results of quantitative analyses in this framework, but the limitations of typical browser presentation restrict data access. Results Here we describe extensions to the treemap design to visualize and query genome data. Treemaps are a space-filling visualization technique for hierarchical structures that show attributes of leaf nodes by size and color-coding. Treemaps enable users to rapidly compare sizes of nodes and sub-trees, and we use Gene Ontology categories, levels of RNA, and other quantitative attributes of DNA microarray experiments as examples. Our implementation of treemaps, Treemap 4.0, allows user-defined filtering to focus on the data of greatest interest, and these queried files can be exported for secondary analyses. Links to model system web pages from Treemap 4.0 enable users access to details about specific genes without leaving the query platform. Conclusions Treemaps allow users to view and query the data from an experiment on a single computer monitor screen. Treemap 4.0 can be used to visualize various genome data, and is particularly useful for revealing patterns and details within complex data sets.
Clemens D Cohen
Full Text Available BACKGROUND: Diabetic nephropathy (DN is a complex and chronic metabolic disease that evolves into a progressive fibrosing renal disorder. Effective transcriptomic profiling of slowly evolving disease processes such as DN can be problematic. The changes that occur are often subtle and can escape detection by conventional oligonucleotide DNA array analyses. METHODOLOGY/PRINCIPAL FINDINGS: We examined microdissected human renal tissue with or without DN using Affymetrix oligonucleotide microarrays (HG-U133A by standard Robust Multi-array Analysis (RMA. Subsequent gene ontology analysis by Database for Annotation, Visualization and Integrated Discovery (DAVID showed limited detection of biological processes previously identified as central mechanisms in the development of DN (e.g. inflammation and angiogenesis. This apparent lack of sensitivity may be associated with the gene-oriented averaging of oligonucleotide probe signals, as this includes signals from cross-hybridizing probes and gene annotation that is based on out of date genomic data. We then examined the same CEL file data using a different methodology to determine how well it could correlate transcriptomic data with observed biology. ChipInspector (CI is based on single probe analysis and de novo gene annotation that bypasses probe set definitions. Both methods, RMA and CI, used at default settings yielded comparable numbers of differentially regulated genes. However, when verified by RT-PCR, the single probe based analysis demonstrated reduced background noise with enhanced sensitivity and fewer false positives. CONCLUSIONS/SIGNIFICANCE: Using a single probe based analysis approach with de novo gene annotation allowed an improved representation of the biological processes linked to the development and progression of DN. The improved analysis was exemplified by the detection of Wnt signaling pathway activation in DN, a process not previously reported to be involved in this disease.
Werf, M.J. van der; Pieterse, B.; Luijk, N. van; Schuren, F.; Werff van der - Vat, B. van der; Overkamp, K.; Jellema, R.H.
The value of the multivariate data analysis tools principal component analysis (PCA) and principal component discriminant analysis (PCDA) for prioritizing leads generated by microarrays was evaluated. To this end, Pseudomonas putida S12 was grown in independent triplicate fermentations on four
Werf, M.J. van der; Pieterse, B.; Luijk, N. van; Schuren, F.; Werff van der - Vat, B. van der; Overkamp, K.; Jellema, R.H.
The value of the multivariate data analysis tools principal component analysis (PCA) and principal component discriminant analysis (PCDA) for prioritizing leads generated by microarrays was evaluated. To this end, Pseudomonas putida S12 was grown in independent triplicate fermentations on four diffe
Full Text Available Background. Microarray technology shows great potential but previous studies were limited by small number of samples in the colorectal cancer (CRC research. The aims of this study are to investigate gene expression profile of CRCs by pooling cDNA microarrays using PAM, ANN, and decision trees (CART and C5.0. Methods. Pooled 16 datasets contained 88 normal mucosal tissues and 1186 CRCs. PAM was performed to identify significant expressed genes in CRCs and models of PAM, ANN, CART, and C5.0 were constructed for screening candidate genes via ranking gene order of significances. Results. The first screening identified 55 genes. The test accuracy of each model was over 0.97 averagely. Less than eight genes achieve excellent classification accuracy. Combining the results of four models, we found the top eight differential genes in CRCs; suppressor genes, CA7, SPIB, GUCA2B, AQP8, IL6R and CWH43; oncogenes, SPP1 and TCN1. Genes of higher significances showed lower variation in rank ordering by different methods. Conclusion. We adopted a two-tier genetic screen, which not only reduced the number of candidate genes but also yielded good accuracy (nearly 100%. This method can be applied to future studies. Among the top eight genes, CA7, TCN1, and CWH43 have not been reported to be related to CRC.
Full Text Available Abstract Background RNA amplification is necessary for profiling gene expression from small tissue samples. Previous studies have shown that the T7 based amplification techniques are reproducible but may distort the true abundance of targets. However, the consequences of such distortions on the ability to detect biological variation in expression have not been explored sufficiently to define the true extent of usability and limitations of such amplification techniques. Results We show that expression ratios are occasionally distorted by amplification using the Affymetrix small sample protocol version 2 due to a disproportional shift in intensity across biological samples. This occurs when a shift in one sample cannot be reflected in the other sample because the intensity would lie outside the dynamic range of the scanner. Interestingly, such distortions most commonly result in smaller ratios with the consequence of reducing the statistical significance of the ratios. This becomes more critical for less pronounced ratios where the evidence for differential expression is not strong. Indeed, statistical analysis by limma suggests that up to 87% of the genes with the largest and therefore most significant ratios (p -20 in the unamplified group have a p-value below 10e-20 in the amplified group. On the other hand, only 69% of the more moderate ratios (10e-20 -10 in the unamplified group have a p-value below 10e-10 in the amplified group. Our analysis also suggests that, overall, limma shows better overlap of genes found to be significant in the amplified and unamplified groups than the Z-scores statistics. Conclusion We conclude that microarray analysis of amplified samples performs best at detecting differences in gene expression, when these are large and when limma statistics are used.
Orland, A; Knapp, K; König, G M; Ulrich-Merzenich, G; Knöß, W
Even though herbal medicines have played an important role in disease management and health for many centuries, their present frequent use is challenged by the necessity to determine their complex composition and their multitarget mode of action. In the present study, modern methods were investigated towards their potential in the characterization of herbal substances. As a model the herbal substance Chelidonii herba was used, for which several reports on liver toxicities exist. Extracts of Chelidonii herba with different solvents were characterized phytochemically and functionally by experiments with HepG2 liver cells. Chelidonii herba was extracted with four solvents of different polarity (dichloromethane, water, ethanol, and ethanol 50% (V/V); four replicates each). The different extracts were characterized metabolomically by (1)H-NMR fingerprinting analysis and principal component analysis (PCA). The content of alkaloids was additionally determined by RP-HPLC. Functional characterization was achieved by the determination of cell proliferation and by transcriptomics techniques (Whole Genome Gene Expression Microarrays v2, Agilent Technologies) in HepG2 cells after exposure to the different extracts (four experimental replicates each). Based on data from (1)H-NMR fingerprints and RP-HPLC analyses the different extracts showed a divergent composition of constituents depending on the solvent used. HepG2 liver cells responded differentially to the four extracts. Microarray analysis revealed a significant regulation of genes and signal cascades related to biotransformation. Also liver-toxic signal cascades were activated. Neither the activated genes nor the proliferation response could be clearly related to the differing alkaloid content of the extracts. Different manufacturing processes lead to different herbal preparations. A systems biology approach combining a metabolomic plant analysis with a functional characterization by gene expression profiling in HepG2
Full Text Available A comparative genomic microarray comprising 2,457 genes from two whole genomes of S. aureus was employed for the comparative genome hybridization analysis of 50 strains of divergent clonal lineages, including methicillin-resistant S. aureus (MRSA, methicillin-susceptible S. aureus (MSSA, and swine strains in China. Large-scale validation was confirmed via polymerase chain reaction in 160 representative clinical strains. All of the 50 strains were clustered into seven different complexes by phylogenetic tree analysis. Thirteen gene clusters were specific to different S. aureus clones. Ten gene clusters, including seven known (vSa3, vSa4, vSaα, vSaβ, Tn5801, and phage ϕSa3 and three novel (C8, C9, and C10 gene clusters, were specific to human MRSA. Notably, two global regulators, sarH2 and sarH3, at cluster C9 were specific to human MRSA, and plasmid pUB110 at cluster C10 was specific to swine MRSA. Three clusters known to be part of SCCmec, vSa4 or Tn5801, and vSaα as well as one novel gene cluster C12 with homology with Tn554 of S. epidermidis were identified as MRSA-specific gene clusters. The replacement of ST239-spa t037 with ST239-spa t030 in Beijing may be a result of its acquisition of vSa4, phage ϕSa1, and ϕSa3. In summary, thirteen critical gene clusters were identified to be contributors to the evolution of host specificity and antibiotic resistance in Chinese S. aureus.
Full Text Available Feature selection has become the essential step in biomarker discovery from high-dimensional genomics data. It is recognized that different feature selection techniques may result in different set of biomarkers, that is, different groups of genes highly correlated to a given pathological condition, but few direct comparisons exist which quantify these differences in a systematic way. In this paper, we propose a general methodology for comparing the outcomes of different selection techniques in the context of biomarker discovery. The comparison is carried out along two dimensions: (i measuring the similarity/dissimilarity of selected gene sets; (ii evaluating the implications of these differences in terms of both predictive performance and stability of selected gene sets. As a case study, we considered three benchmarks deriving from DNA microarray experiments and conducted a comparative analysis among eight selection methods, representatives of different classes of feature selection techniques. Our results show that the proposed approach can provide useful insight about the pattern of agreement of biomarker discovery techniques.
Prync, A E Sterin; Yankilevich, P; Barrero, P R; Bello, R; Marangunich, L; Vidal, A; Criscuolo, M; Benasayag, L; Famulari, A L; Domínguez, R O; Kauffman, M A; Diez, R A
Recombinant human interferon-beta (IFN-b) is a well-established treatment for multiple sclerosis (MS). The regulatory process for marketing authorization of biosimilars is currently under debate in certain countries. In the EU, EMEA has clearly defined the process including overarching and product-specific guidelines, which includes clinical testing. Biosimilarity needs to be based on comparability criteria, including at least molecular characterization, biological activity relevant for the therapeutic effect and relative bioavailability ("bioequivalence"). In the case of such complex diseases as MS, where the effect of treatment is not so directly measurable, in vitro tools can provide additional data to support comparability. Genomic microarrays assays might be useful to compare multisource biopharmaceuticals. The aim of the present study was to compare the pharmacodynamic genomic effects (in terms of transcriptional regulation) of two recombinant human IFN-I(2)1a preparations on lymphocytes of multiple sclerosis patients using a whole genome microarray assay. We performed an ex vivo whole genome expression profiling of the effect of two preparations of IFN-I(2)1a on non-adherent mononuclears from five relapsing-remitting MS patients analyzing microarrays (CodeLink Human Whole Genome). Patients blood was drawn, PBMCs isolated and cultured in three different conditions: culture medium (control), 1,000 U/ml of IFN-I(2)1a (BLA- (STOFERON, Bio Sidus) and 1,000 U/ml of IFN-I(2)1a (REBIF, Serono) RNA was purified from non-adherent cells (mostly lymphocytes), amplified and hybridized. Raw data were generated by CodeLink proprietary software. Data normalization, quality control and analysis of differential gene expression between treatments were done using linear model for microarray data. Functional annotation analysis of IFN-I(2)1a MS treatment transcription was done using DAVID. Out of the approximately 45,000 human sequences examined, no evidence of differential
Full Text Available Abstract Background Malignant cells in tumours of B-cell origin account for 0.1% to 98% of the total cell content, depending on disease entity. Recently, gene expression profiles (GEPs of B-cell lymphomas based on microarray technologies have contributed significantly to improved sub-classification and diagnostics. However, the varying degrees of malignant B-cell frequencies in analysed samples influence the interpretation of the GEPs. Based on emerging next-generation sequencing technologies (NGS like tag sequencing (tag-seq for GEP, it is expected that the detection of mRNA transcripts from malignant B-cells can be supplemented. This study provides a quantitative assessment and comparison of the ability of microarrays and tag-seq to detect mRNA transcripts from malignant B-cells. A model system was established by eight serial dilutions of the malignant B-cell lymphoma cell line, OCI-Ly8, into the embryonic kidney cell line, HEK293, prior to parallel analysis by exon microarrays and tag-seq. Results We identified 123 and 117 differentially expressed genes between pure OCI-Ly8 and HEK293 cells by exon microarray and tag-seq, respectively. There were thirty genes in common, and of those, most were B-cell specific. Hierarchical clustering from all dilutions based on the differentially expressed genes showed that neither technology could distinguish between samples with less than 1% malignant B-cells from non-B-cells. A novel statistical concept was developed to assess the ability to detect single genes for both technologies, and used to demonstrate an inverse proportional relationship with the sample purity. Of the 30 common genes, the detection capability of a representative set of three B-cell specific genes - CD74, HLA-DRA, and BCL6 - was analysed. It was noticed that at least 5%, 13% and 22% sample purity respectively was required for detection of the three genes by exon microarray whereas at least 2%, 4% and 51% percent sample purity of
Hedjazi, Lyamine; Le Lann, Marie-Véronique; Kempowsky, Tatiana; Dalenc, Florence; Aguilar-Martin, Joseph; Favre, Gilles
Microarray profiling has recently generated the hope to gain new insights into breast cancer biology and thereby improve the performance of current prognostic tools. However, it also poses several serious challenges to classical data analysis techniques related to the characteristics of resulting data, mainly high dimensionality and low signal-to-noise ratio. Despite the tremendous research work performed to handle the first challenge in the feature selection framework, very little attention ...
Full Text Available Abstract Background Staphylococcus aureus (S. aureus, is responsible for many infectious diseases, ranging from benign skin infections to life-threatening endocarditis and toxic shock syndrome. Ortho-phenylphenol (OPP is an antimicrobial agent and an active ingredient of EPA-registered disinfectants with wide human exposure in various agricultural, hospital and veterinary disinfectant products. Despite many uses, an understanding of a cellular response to OPP and it's mechanism of action, targeted genes, and the connectivity between targeted genes and the rest of cell metabolism remains obscure. Results Herein, we performed a genome-wide transcriptome analysis of the cellular responses of S. aureus when exposed to 0.82 mM of OPP for 20 and 60 min. Our data indicated that OPP downregulated the biosynthesis of many amino acids, which are required for protein synthesis. In particular, the genes encoding the enzymes of the diaminopimelate (DAP pathway which results in lysine biosynthesis were significantly downregualted. Intriguingly, we revealed that the transcription of genes encoding ribosomal proteins was upregulated by OPP and at the same time, the genes encoding iron acquisition and transport were downregulated. The genes encoding virulence factors were upregulated and genes encoding phospholipids were downregulated upon 20 min exposure to OPP. Conclusion By using microarray analysis that enables us to simultaneously and globally examine the complete transcriptome during cellular responses, we have revealed novel information regarding the mode of action of OPP on Staphylococcus: OPP inhibits anabolism of many amino acids and highly downregulates the genes that encode the enzymes involved in the DAP pathway. Lysine and DAP are essential for building up the peptidoglycan cell wall. It was concluded that the mode of action of OPP is similar to the mechanism of action of some antibiotics. The discovery of this phenomenon provides useful
Lancet Jeffrey E
Full Text Available Abstract Background Farnesyl protein transferase inhibitors (FTIs were originally developed to inhibit oncogenic ras, however it is now clear that there are several other potential targets for this drug class. The FTI tipifarnib (ZARNESTRA™, R115777 has recently demonstrated clinical responses in adults with refractory and relapsed acute leukemias. This study was conducted to identify genetic markers and pathways that are regulated by tipifarnib in acute myeloid leukemia (AML. Methods Tipifarnib-mediated gene expression changes in 3 AML cell lines and bone marrow samples from two patients with AML were analyzed on a cDNA microarray containing approximately 7000 human genes. Pathways associated with these expression changes were identified using the Ingenuity Pathway Analysis tool. Results The expression analysis identified a common set of genes that were regulated by tipifarnib in three leukemic cell lines and in leukemic blast cells isolated from two patients who had been treated with tipifarnib. Association of modulated genes with biological functional groups identified several pathways affected by tipifarnib including cell signaling, cytoskeletal organization, immunity, and apoptosis. Gene expression changes were verified in a subset of genes using real time RT-PCR. Additionally, regulation of apoptotic genes was found to correlate with increased Annexin V staining in the THP-1 cell line but not in the HL-60 cell line. Conclusions The genetic networks derived from these studies illuminate some of the biological pathways affected by FTI treatment while providing a proof of principle for identifying candidate genes that might be used as surrogate biomarkers of drug activity.
Borel, Nicole; Mukhopadhyay, Sanghamitra; Kaiser, Carmen; Sullivan, Erin D; Miller, Richard D; Timms, Peter; Summersgill, James T; Ramirez, Julio A; Pospischil, Andreas
Chlamydophila pneumoniae infection has been implicated as a potential risk factor for atherosclerosis, however the mechanism leading to persistent infection and its role in the disease process remains to be elucidated. We validated the use of tissue microarray (TMA) technology, in combination with immunohistochemistry (IHC), to test antibodies (GroEL, GroES, GspD, Ndk and Pyk) raised against differentially expressed proteins under an interferon-gamma (IFN-gamma) induced model of chlamydial persistence. In the cell pellet array, we were able to identify differences in protein expression patterns between untreated and IFN-gamma treated samples. Typical, large chlamydial inclusions could be observed in the untreated samples with all antibodies, whereas the number of inclusions were decreased and were smaller and atypical in shape in the IFN-gamma treated samples. The staining results obtained with the TMA method were generally similar to the changes observed between normal and IFN-gamma persistence using proteomic analysis. Subsequently, it was shown in a second TMA including archival atheromatous heart tissues from 12 patients undergoing heart transplantation, that GroEL, GroES, GspD and Pyk were expressed in atheromatous heart tissue specimens as well, and were detectable morphologically within lesions by IHC. TMA technology proved useful in documenting functional proteomics data with the morphologic distribution of GroEL, GroES, GspD, Ndk and Pyk within formalin-fixed, paraffin-embedded cell pellets and tissues from patients with severe coronary atherosclerosis. The antibodies GroEL and GroES, which were upregulated under persistence in proteomic analysis, displayed positive reaction in atheromatous heart tissue from 10 out of 12 patients. These may be useful markers for the detection of persistent infection in vitro and in vivo.
Full Text Available Abstract Background Chlamydophila pneumoniae infection has been implicated as a potential risk factor for atherosclerosis, however the mechanism leading to persistent infection and its role in the disease process remains to be elucidated. Methods We validated the use of tissue microarray (TMA technology, in combination with immunohistochemistry (IHC, to test antibodies (GroEL, GroES, GspD, Ndk and Pyk raised against differentially expressed proteins under an interferon-gamma (IFN-γ induced model of chlamydial persistence. Results In the cell pellet array, we were able to identify differences in protein expression patterns between untreated and IFN-γ treated samples. Typical, large chlamydial inclusions could be observed in the untreated samples with all antibodies, whereas the number of inclusions were decreased and were smaller and atypical in shape in the IFN-γ treated samples. The staining results obtained with the TMA method were generally similar to the changes observed between normal and IFN-γ persistence using proteomic analysis. Subsequently, it was shown in a second TMA including archival atheromatous heart tissues from 12 patients undergoing heart transplantation, that GroEL, GroES, GspD and Pyk were expressed in atheromatous heart tissue specimens as well, and were detectable morphologically within lesions by IHC. Conclusion TMA technology proved useful in documenting functional proteomics data with the morphologic distribution of GroEL, GroES, GspD, Ndk and Pyk within formalin-fixed, paraffin-embedded cell pellets and tissues from patients with severe coronary atherosclerosis. The antibodies GroEL and GroES, which were upregulated under persistence in proteomic analysis, displayed positive reaction in atheromatous heart tissue from 10 out of 12 patients. These may be useful markers for the detection of persistent infection in vitro and in vivo.
Edna C Holman
Full Text Available Among vertebrates, salamanders stand out for their remarkable capacity to quickly regrow a myriad of tissues and organs after injury or amputation. The limb regeneration process in axolotls (Ambystoma mexicanum has been well studied for decades at the cell-tissue level. While several developmental genes are known to be reactivated during this epimorphic process, less is known about the role of microRNAs in urodele amphibian limb regeneration. Given the compelling evidence that many microRNAs tightly regulate cell fate and morphogenetic processes through development and adulthood by modulating the expression (or re-expression of developmental genes, we investigated the possibility that microRNA levels change during limb regeneration. Using two different microarray platforms to compare the axolotl microRNA expression between mid-bud limb regenerating blastemas and non-regenerating stump tissues, we found that miR-21 was overexpressed in mid-bud blastemas compared to stump tissue. Mature A. mexicanum ("Amex" miR-21 was detected in axolotl RNA by Northern blot and differential expression of Amex-miR-21 in blastema versus stump was confirmed by quantitative RT-PCR. We identified the Amex Jagged1 as a putative target gene for miR-21 during salamander limb regeneration. We cloned the full length 3'UTR of Amex-Jag1, and our in vitro assays demonstrated that its single miR-21 target recognition site is functional and essential for the response of the Jagged1 gene to miR-21 levels. Our findings pave the road for advanced in vivo functional assays aimed to clarify how microRNAs such as miR-21, often linked to pathogenic cell growth, might be modulating the redeployment of developmental genes such as Jagged1 during regenerative processes.
Holman, Edna C; Campbell, Leah J; Hines, John; Crews, Craig M
Among vertebrates, salamanders stand out for their remarkable capacity to quickly regrow a myriad of tissues and organs after injury or amputation. The limb regeneration process in axolotls (Ambystoma mexicanum) has been well studied for decades at the cell-tissue level. While several developmental genes are known to be reactivated during this epimorphic process, less is known about the role of microRNAs in urodele amphibian limb regeneration. Given the compelling evidence that many microRNAs tightly regulate cell fate and morphogenetic processes through development and adulthood by modulating the expression (or re-expression) of developmental genes, we investigated the possibility that microRNA levels change during limb regeneration. Using two different microarray platforms to compare the axolotl microRNA expression between mid-bud limb regenerating blastemas and non-regenerating stump tissues, we found that miR-21 was overexpressed in mid-bud blastemas compared to stump tissue. Mature A. mexicanum ("Amex") miR-21 was detected in axolotl RNA by Northern blot and differential expression of Amex-miR-21 in blastema versus stump was confirmed by quantitative RT-PCR. We identified the Amex Jagged1 as a putative target gene for miR-21 during salamander limb regeneration. We cloned the full length 3'UTR of Amex-Jag1, and our in vitro assays demonstrated that its single miR-21 target recognition site is functional and essential for the response of the Jagged1 gene to miR-21 levels. Our findings pave the road for advanced in vivo functional assays aimed to clarify how microRNAs such as miR-21, often linked to pathogenic cell growth, might be modulating the redeployment of developmental genes such as Jagged1 during regenerative processes.
Holman, Edna C.; Campbell, Leah J.; Hines, John; Crews, Craig M.
Among vertebrates, salamanders stand out for their remarkable capacity to quickly regrow a myriad of tissues and organs after injury or amputation. The limb regeneration process in axolotls (Ambystoma mexicanum) has been well studied for decades at the cell-tissue level. While several developmental genes are known to be reactivated during this epimorphic process, less is known about the role of microRNAs in urodele amphibian limb regeneration. Given the compelling evidence that many microRNAs tightly regulate cell fate and morphogenetic processes through development and adulthood by modulating the expression (or re-expression) of developmental genes, we investigated the possibility that microRNA levels change during limb regeneration. Using two different microarray platforms to compare the axolotl microRNA expression between mid-bud limb regenerating blastemas and non-regenerating stump tissues, we found that miR-21 was overexpressed in mid-bud blastemas compared to stump tissue. Mature A. mexicanum (“Amex”) miR-21 was detected in axolotl RNA by Northern blot and differential expression of Amex-miR-21 in blastema versus stump was confirmed by quantitative RT-PCR. We identified the Amex Jagged1 as a putative target gene for miR-21 during salamander limb regeneration. We cloned the full length 3′UTR of Amex-Jag1, and our in vitro assays demonstrated that its single miR-21 target recognition site is functional and essential for the response of the Jagged1 gene to miR-21 levels. Our findings pave the road for advanced in vivo functional assays aimed to clarify how microRNAs such as miR-21, often linked to pathogenic cell growth, might be modulating the redeployment of developmental genes such as Jagged1 during regenerative processes. PMID:23028429
Full Text Available BACKGROUND: Water buffalo and goats are natural hosts for S. japonicum in endemic areas of China. The susceptibility of these two hosts to schistosome infection is different, as water buffalo are less conducive to S. japonicum growth and development. To identify genes that may affect schistosome development and survival, we compared gene expression profiles of schistosomes derived from these two natural hosts using high-throughput microarray technology. RESULTS: The worm recovery rate was lower and the length and width of worms from water buffalo were smaller compared to those from goats following S. japonicum infection for 7 weeks. Besides obvious morphological difference between the schistosomes derived from the two hosts, differences were also observed by scanning and transmission electron microscopy. Microarray analysis showed differentially expressed gene patterns for parasites from the two hosts, which revealed that genes related to lipid and nucleotide metabolism, as well as protein folding, sorting, and degradation were upregulated, while others associated with signal transduction, endocrine function, development, immune function, endocytosis, and amino acid/carbohydrate/glycan metabolism were downregulated in schistosomes from water buffalo. KEGG pathway analysis deduced that the differentially expressed genes mainly involved lipid metabolism, the MAPK and ErbB signaling pathways, progesterone-mediated oocyte maturation, dorso-ventral axis formation, reproduction, and endocytosis, etc. CONCLUSION: The microarray gene analysis in schistosomes derived from water buffalo and goats provide a useful platform to disclose differences determining S. japonicum host compatibility to better understand the interplay between natural hosts and parasites, and identify schistosome target genes associated with susceptibility to screen vaccine candidates.
Yang, Jianmei; Hong, Yang; Yuan, Chunxiu; Fu, Zhiqiang; Shi, Yaojun; Zhang, Min; Shen, Liuhong; Han, Yanhui; Zhu, Chuangang; Li, Hao; Lu, Ke; Liu, Jinming; Feng, Xingang; Lin, Jiaojiao
Background Water buffalo and goats are natural hosts for S. japonicum in endemic areas of China. The susceptibility of these two hosts to schistosome infection is different, as water buffalo are less conducive to S. japonicum growth and development. To identify genes that may affect schistosome development and survival, we compared gene expression profiles of schistosomes derived from these two natural hosts using high-throughput microarray technology. Results The worm recovery rate was lower and the length and width of worms from water buffalo were smaller compared to those from goats following S. japonicum infection for 7 weeks. Besides obvious morphological difference between the schistosomes derived from the two hosts, differences were also observed by scanning and transmission electron microscopy. Microarray analysis showed differentially expressed gene patterns for parasites from the two hosts, which revealed that genes related to lipid and nucleotide metabolism, as well as protein folding, sorting, and degradation were upregulated, while others associated with signal transduction, endocrine function, development, immune function, endocytosis, and amino acid/carbohydrate/glycan metabolism were downregulated in schistosomes from water buffalo. KEGG pathway analysis deduced that the differentially expressed genes mainly involved lipid metabolism, the MAPK and ErbB signaling pathways, progesterone-mediated oocyte maturation, dorso-ventral axis formation, reproduction, and endocytosis, etc. Conclusion The microarray gene analysis in schistosomes derived from water buffalo and goats provide a useful platform to disclose differences determining S. japonicum host compatibility to better understand the interplay between natural hosts and parasites, and identify schistosome target genes associated with susceptibility to screen vaccine candidates. PMID:23940568
Nelson, T.A.; Holmes, S.; Alekseyenko, A.V.; Shenoy, M.; DeSantis, T.; Wu, C.H.; Andersen, G.L.; Winston, J.; Sonnenburg, J.; Pasricha, P.J.; Spormann, A.
Irritable bowel syndrome (IBS) is a chronic, episodic gastrointestinal disorder that is prevalent in a significant fraction of western human populations; and changes in the microbiota of the large bowel have been implicated in the pathology of the disease. Using a novel comprehensive, high-density DNA microarray (PhyloChip) we performed a phylogenetic analysis of the microbial community of the large bowel in a rat model in which intracolonic acetic acid in neonates was used to induce long lasting colonic hypersensitivity and decreased stool water content and frequency, representing the equivalent of human constipation-predominant IBS. Our results revealed a significantly increased compositional difference in the microbial communities in rats with neonatal irritation as compared with controls. Even more striking was the dramatic change in the ratio of Firmicutes relative to Bacteroidetes, where neonatally irritated rats were enriched more with Bacteroidetes and also contained a different composition of species within this phylum. Our study also revealed differences at the level of bacterial families and species. The PhyloChip is a useful and convenient method to study enteric microflora. Further, this rat model system may be a useful experimental platform to study the causes and consequences of changes in microbial community composition associated with IBS.
Full Text Available The choroid plexus (CP are highly vascularized branched structures that protrude into the ventricles of the brain, and form a unique interface between the blood and the cerebrospinal fluid (CSF, the blood-CSF barrier, that are the main site of production and secretion of CSF. Sex hormones are widely recognized as neuroprotective agents against several neurodegenerative diseases, and the presence of sex hormones cognate receptors suggest that it may be a target for these hormones. In an effort to provide further insight into the neuroprotective mechanisms triggered by sex hormones we analyzed gene expression differences in the CP of female and male rats subjected to gonadectomy, using microarray technology. In gonadectomized female and male animals, 3045 genes were differentially expressed by 1.5-fold change, compared to sham controls. Analysis of the CP transcriptome showed that the top-five pathways significantly regulated by the sex hormone background are olfactory transduction, taste transduction, metabolism, steroid hormone biosynthesis and circadian rhythm pathways. These results represent the first overview of global expression changes in CP of female and male rats induced by gonadectomy and suggest that sex hormones are implicated in pathways with central roles in CP functions and CSF homeostasis.
Romanowicz, Hanna; Strapagiel, Dominik; Słomka, Marcin; Sobalska-Kwapis, Marta; Kępka, Ewa; Siewierska-Górska, Anna; Zadrożny, Marek; Bieńkiewicz, Jan; Smolarz, Beata
Breast cancer is the most common cause of malignancy and mortality in women worldwide. This study aimed at localising homologous recombination repair (HR) genes and their chromosomal loci and correlating their nucleotide variants with susceptibility to breast cancer. In this study, authors analysed the association between single nucleotide polymorphisms (SNPs) in homologous recombination repair genes and the incidence of breast cancer in the population of Polish women. Blood samples from 94 breast cancer patients were analysed as test group. Individuals were recruited into the study at the Department of Oncological Surgery and Breast Diseases of the Institute of the Polish Mother's Memorial Hospital in Lodz, Poland. Healthy controls (n = 500) were obtained from the Biobank Laboratory, Department of Molecular Biophysics, University of Lodz. Then, DNA of breast cancer patients was compared with one of the disease-free women. The test was supported by microarray analysis. Statistically significant correlations were identified between breast cancer and 3 not described previously SNPs of homologous recombination repair genes BRCA1 and BRCA2: rs59004709, rs4986852 and rs1799950. Further studies on larger groups are warranted to support the hypothesis of correlation between the abovementioned genetic variants and breast cancer risk.
Juul, Sandra E; Beyer, Richard P; Bammler, Theo K; McPherson, Ronald J; Wilkerson, Jasmine; Farin, Federico M
Recombinant human erythropoietin (rEpo) is neuroprotective in neonatal models of brain injury. Proposed mechanisms of neuroprotection include activation of gene pathways that decrease oxidative injury, inflammation, and apoptosis, while increasing vasculogenesis and neurogenesis. To determine the effects of rEpo on gene expression in 10-d-old BALB-c mice with unilateral brain injury, we compared microarrays from the hippocampi of brain-injured pups treated with saline or rEpo to similarly treated sham animals. Total RNA was extracted 24 h after brain injury and analyzed using Affymetrix GeneChip Mouse Exon 1.0 ST Arrays. We identified sex-specific differences in hippocampal gene expression after brain injury and after high-dose rEpo treatment using single-gene and gene set analysis. Although high-dose rEpo had minimal effects on hippocampal gene expression in shams, at 24-h post brain injury, high-dose rEpo treatment significantly decreased the proinflammatory and antiapoptotic response noted in saline-treated brain-injured comparison animals.
Full Text Available Background: The Tissue Microarray Data Exchange Specification (TMA DES is an eXtensible Markup Language (XML specification for encoding TMA experiment data in a machine-readable format that is also human readable. TMA DES defines Common Data Elements (CDEs that form a basic vocabulary for describing TMA data. TMA data are routinely subjected to univariate and multivariate statistical analysis to determine differences or similarities between pathologically distinct groups of tumors for one or more markers or between markers for different groups. Such statistical analysis tests include the t-test, ANOVA, Chi-square, Mann-Whitney U, and Kruskal-Wallis tests. All these generate output that needs to be recorded and stored with TMA data. Materials and Methods: We propose extending the TMA DES to include syntactic and semantic definitions of CDEs for describing the results of statistical analyses performed upon TMA DES data. These CDEs are described in this paper and it is illustrated how they can be added to the TMA DES. We created a Document Type Definition (DTD file defining the syntax for these CDEs, and a set of ISO 11179 entries providing semantic definitions for them. We describe how we wrote a program in R that read TMA DES data from an XML file, performed statistical analyses on that data, and created a new XML file containing both the original XML data and CDEs representing the results of our analyses. This XML file was submitted to XML parsers in order to confirm that they conformed to the syntax defined in our extended DTD file. TMA DES XML files with deliberately introduced errors were also parsed in order to verify that our new DTD file could perform error checking. Finally, we also validated an existing TMA DES XML file against our DTD file in order to demonstrate the backward compatibility of our DTD. Results: Our experiments demonstrated the encoding of analysis results using our proposed CDEs. We used XML parsers to confirm that these
Peyser, Brian D; Irizarry, Rafael A; Tiffany, Carol W; Chen, Ou; Yuan, Daniel S; Boeke, Jef D; Spencer, Forrest A
Saccharomyces cerevisiae knockout collection TAG microarrays are an emergent platform for rapid, genome-wide functional characterization of yeast genes. TAG arrays report abundance of unique oligonucleotide 'TAG' sequences incorporated into each deletion mutation of the yeast knockout collection, allowing measurement of relative strain representation across experimental conditions for all knockout mutants simultaneously. One application of TAG arrays is to perform genome-wide synthetic lethality screens, known as synthetic lethality analyzed by microarray (SLAM). We designed a fully defined spike-in pool to resemble typical SLAM experiments and performed TAG microarray hybridizations. We describe a method for analyzing two-color array data to efficiently measure the differential knockout strain representation across two experimental conditions, and use the spike-in pool to show that the sensitivity and specificity of this method exceed typical current approaches.
Amin, Waqas; Srinivasan, Malini; Song, Sang Yong; Parwani, Anil V; Becich, Michael J
The National Mesothelioma Virtual Bank (NMVB) was established to provide annotated biospecimens to the mesothelioma research community. The resource provides tissue microarrays (TMA) to evaluate the biomarkers along with a variety of other resected mesothelioma specimens. In this manuscript, we describe the immunohistochemical evaluation of the mesothelioma TMA with three key antibodies that are used in making the diagnosis of mesothelioma, and compared the immunohistochemical assessment between manual scoring and image analysis. The TMA was assessed for the immunohistochemical expression of calretinin (N=39), cytokeratin (CK) 5/6 (N=33), and D2-40 (N=37). Immunohistochemistry was evaluated by semi-quantitative (manual) scoring using light microscope (MS) and by automated image analysis (AS). Calretinin staining was seen in both cytoplasmic and nuclear locations. CK5/6 stain was localized to the cytoplasm. D2-40 stain showed only membranous expression in our cases. • Based on the pathologist’s scores, calretinin was positive in 31 of the 39 cases (80%), CK 5/6 in 15 of the 33 cases (46%) and D2-40 in 18 of the 37 cases (49%). • The percent-positive agreement between manual scores and image analysis was 90% (35/39), 94% (31/33), and 95% (35/37) for calretinin, CK 5/6, and D2-40, respectively. There was a substantial agree-ment between manual and automated scores for calretinin (kappa = 0.614) and an almost perfect agreement for CK5/6 (kappa = 0.879) and D2-40 (kappa = 0.892). Our study confirms that the immunohistochemical staining pattern of mesotheliomas in the NMVB UPMC TMA is similar to other studies. Our findings also show that automated image analysis provides similar results to manual scoring by pathologists, and provides a reproducible, objective, and accurate platform for immunohistochemical assessment of biomarker expression. Copyright © 2013 Elsevier GmbH. All rights reserved.
Chen, Hong; Wang, Jingjing; Yang, Hong; Chen, Dan; Li, Panpan
Forkhead box M1 (FOXM1) and hedgehog (Hh) signaling pathway are implicated in the formation and development of human tumors, including cervical cancer. Previous studies have indicated that FOXM1 may be a downstream target gene of the Hh signaling pathway, but their association in cervical cancer is largely unknown. In the present study, the expression of FOXM1 and Hh signaling molecules was evaluated by immunohistochemical analysis in a tissue microarray that contained 70 cervical cancer tissues and 10 normal cervical tissues. In addition, the association of these molecules with clinicopathological parameters, and the association between FOXM1 and various molecules involved in the Hh signaling pathway was investigated. The results indicated that FOXM1 and Hh signaling molecules were overexpressed in cervical cancer tissues. The protein expression levels of FOXM1, glioma-associated oncogene 1 (GLI1) and smoothened (SMO) correlated with the clinical stage of the tumors, while the protein expression levels of Sonic Hh (SHh), patched 1 (PTCH1) and GLI1 correlated with the pathological grade of the tumors. The expression levels of GLI1 were lower in tissues without lymph node metastasis than in tissues with lymph node metastasis. In addition, FOXM1 expression correlated with GLI1, SHh and PTCH1 expression in cancer tissues. These findings confirmed the participation of FOXM1 and the Hh signaling pathway in cervical cancer. Furthermore, the finding that FOXM1 may be a downstream target gene of the Hh signaling pathway in cervical cancer provides a potential novel diagnostic and therapeutic target for cervical cancer.
Zilina, Olga; Teek, Rita; Tammur, Pille; Kuuse, Kati; Yakoreva, Maria; Vaidla, Eve; Mölter-Väär, Triin; Reimand, Tiia; Kurg, Ants; Ounap, Katrin
Chromosomal microarray analysis (CMA) is now established as the first-tier cytogenetic diagnostic test for fast and accurate detection of chromosomal abnormalities in patients with developmental delay/intellectual disability (DD/ID), multiple congenital anomalies (MCA), and autism spectrum disorders (ASD). We present our experience with using CMA for postnatal and prenatal diagnosis in Estonian patients during 2009-2012. Since 2011, CMA is on the official service list of the Estonian Health Insurance Fund and is performed as the first-tier cytogenetic test for patients with DD/ID, MCA or ASD. A total of 1191 patients were analyzed, including postnatal (1072 [90%] patients and 59 [5%] family members) and prenatal referrals (60 [5%] fetuses). Abnormal results were reported in 298 (25%) patients, with a total of 351 findings (1-3 per individual): 147 (42%) deletions, 106 (30%) duplications, 89 (25%) long contiguous stretches of homozygosity (LCSH) events (>5 Mb), and nine (3%) aneuploidies. Of all findings, 143 (41%) were defined as pathogenic or likely pathogenic; for another 143 findings (41%), most of which were LCSH, the clinical significance remained unknown, while 61 (18%) reported findings can now be reclassified as benign or likely benign. Clinically relevant findings were detected in 126 (11%) patients. However, the proportion of variants of unknown clinical significance was quite high (41% of all findings). It seems that our ability to detect chromosomal abnormalities has far outpaced our ability to understand their role in disease. Thus, the interpretation of CMA findings remains a rather difficult task requiring a close collaboration between clinicians and cytogeneticists.
Lewis E H Bingle
Full Text Available The type III protein secretion system is an important pathogenicity factor of enteropathogenic and enterohaemorrhagic Escherichia coli pathotypes. The genes encoding this apparatus are located on a pathogenicity island (the locus of enterocyte effacement and are transcriptionally activated by the master regulator Ler. In each pathotype Ler is also known to regulate genes located elsewhere on the chromosome, but the full extent of the Ler regulon is unclear, especially for enteropathogenic E. coli. The Ler regulon was defined for two strains of E. coli: E2348/69 (enteropathogenic and EDL933 (enterohaemorrhagic in mid and late log phases of growth by DNA microarray analysis of the transcriptomes of wild-type and ler mutant versions of each strain. In both strains the Ler regulon is focused on the locus of enterocyte effacement - all major transcriptional units of which are activated by Ler, with the sole exception of the LEE1 operon during mid-log phase growth in E2348/69. However, the Ler regulon does extend more widely and also includes unlinked pathogenicity genes: in E2348/69 more than 50 genes outside of this locus were regulated, including a number of known or potential pathogenicity determinants; in EDL933 only 4 extra-LEE genes, again including known pathogenicity factors, were activated. In E2348/69, where the Ler regulon is clearly growth phase dependent, a number of genes including the plasmid-encoded regulator operon perABC, were found to be negatively regulated by Ler. Negative regulation by Ler of PerC, itself a positive regulator of the ler promoter, suggests a negative feedback loop involving these proteins.
Full Text Available Abstract Background Salmonella enterica subsp. enterica is one of the leading food-borne pathogens in the USA and European countries. Outcome of human Salmonella serotype Typhimurium infections ranges from mild self-limiting diarrhoea to severe diarrhoea that requires hospitalization. Increased knowledge of the mechanisms that are responsible for causing infection and especially the severity of infection is of high interest. Results Strains were selected from patients with mild infections (n = 9 and patients with severe infections (n = 9 and clinical data allowed us to correct for known underlying diseases. Additionally, outbreak isolates (n = 3 were selected. Strains were analyzed on a DNA-DNA microarray for presence or absence of 281 genes covering marker groups of genes related to pathogenicity, phages, antimicrobial resistance, fimbriae, mobility, serotype and metabolism. Strains showed highly similar profiles when comparing virulence associated genes, but differences between strains were detected in the prophage marker group. The Salmonella virulence plasmid was present in 72% of the strains, but presence or absence of the virulence plasmid did not correspond to disease symptoms. A dendrogram clustered strains into four groups. Clustering confirmed DT104 as being a clonal phagetype. Clustering of the remaining strains was mainly correlated to presence or absence of the virulence plasmid and mobile elements such as transposons. Each of the four clusters in the tree represented an almost equal amount of strains causing severe or mild symptoms of infection. Conclusions We investigated clinical significance of known virulence factors of Salmonella serotype Typhimurium strains causing different disease symptoms, and conclude that the few detected differences in Salmonella serotype Typhimurium do not affect outcome of human disease.
Full Text Available Withania somnifera (L. Dunal (Indian ginseng, winter cherry, Solanaceae is widely used in traditional medicine. Roots are either chewed or used to prepare beverages (aqueous decocts. The major secondary metabolites of Withania somnifera are the withanolides, which are C-28-steroidal lactone triterpenoids. Withania somnifera extracts exert chemopreventive and anticancer activities in vitro and in vivo. The aims of the present in silico study were, firstly, to investigate whether tumor cells develop cross-resistance between standard anticancer drugs and withanolides and, secondly, to elucidate the molecular determinants of sensitivity and resistance of tumor cells towards withanolides. Using IC50 concentrations of eight different withanolides (withaferin A, withaferin A diacetate, 3-azerininylwithaferin A, withafastuosin D diacetate, 4-B-hydroxy-withanolide E, isowithanololide E, withafastuosin E, and withaperuvin and 19 established anticancer drugs, we analyzed the cross-resistance profile of 60 tumor cell lines. The cell lines revealed cross-resistance between the eight withanolides. Consistent cross-resistance between withanolides and nitrosoureas (carmustin, lomustin, and semimustin was also observed. Then, we performed transcriptomic microarray-based COMPARE and hierarchical cluster analyses of mRNA expression to identify mRNA expression profiles predicting sensitivity or resistance towards withanolides. Genes from diverse functional groups were significantly associated with response of tumor cells to withaferin A diacetate, e.g. genes functioning in DNA damage and repair, stress response, cell growth regulation, extracellular matrix components, cell adhesion and cell migration, constituents of the ribosome, cytoskeletal organization and regulation, signal transduction, transcription factors, and others.
Colombara, Danny V.; Hughes, James P.; Burnett-Hartman, Andrea N.; Hawes, Stephen E.; Galloway, Denise A.; Schwartz, Stephen M.; Bostick, Roberd M.; Potter, John D.; Manhart, Lisa E.
Background Liquid bead microarray antibody (LBMA) assays are used to assess pathogen-cancer associations. However, studies analyze LBMA data differently, limiting comparability. Methods We generated 10,000 Monte Carlo-type simulations of log-normal antibody distributions (exposure) with 200 cases and 200 controls (outcome). We estimated type I error rates, statistical power, and bias associated with t-tests, logistic regression with a linear exposure and with the exposure dichotomized at 200 units, 400 units, the mean among controls plus two standard deviations, and the value corresponding to the optimal sensitivity and specificity. We also applied these models, and data visualizations (kernel density plots, receiver operating characteristic (ROC) curves, predicted probability plots, and Q-Q plots), to two empirical datasets to assess the consistency of the exposure-outcome relationship. Results All strategies had acceptable type I error rates (0.03≤P≤0.048), except for the dichotomization according to optimal sensitivity and specificity, which had a type I error rate of 0.27. Among the remaining methods, logistic regression with a linear predictor (Power=1.00) and t-tests (Power=1.00) had the highest power to detect a mean difference of 1.0 MFI (median fluorescence intensity) on the log scale and were unbiased. Dichotomization methods upwardly biased the risk estimates. Conclusion These results indicate that logistic regression with linear predictors and unpaired t-tests are superior to logistic regression with dichotomized predictors for assessing disease associations with LBMA data. Logistic regression with continuous linear predictors and t-tests are preferable to commonly used LBMA dichotomization methods. PMID:26071614
Nino-Soto, M I; Jozani, R J; Bridle, B; Mallard, B A
Three lines of commercialYorkshire pigs with defined SLA-DRB1 alleles were developed at the University of Guelph for xenotransplantation and immune response studies. Two of the SLA-DRB1 alleles have been previously reported (SLA-DRB1*0502 and *0701), whereas the third one is a new allele. The influence of defined SLA-DRB1 alleles on transcriptional patterns of immune-related genes in blood mononuclear cells (BMCs) of pigs was explored using cDNA microarray. Microarray analysis showed significant differential expression of inflammatory genes in association with the various SLA-DRB1 alleles. A better understanding of the association between SLA genotypes and gene activity can increase the knowledge of the function of these molecules, as well as define new strategies to control animal health and optimize animal production.
Screening for gene copy-number alterations (CNAs) has improved by applying genome-wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high-resolution platforms: BAC arrays (32K...... of 32 additional regions present in 2-3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy-number variations. LOH analysis using dChip revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping...
Lutter, D; Langmann, Th; Ugocsai, P; Moehle, C; Seibold, E; Splettstoesser, W D; Gruber, P; Lang, E W; Schmitz, G
The analysis of large-scale gene expression profiles is still a demanding and extensive task. Modern machine learning and data mining techniques developed in linear algebra, like Independent Component Analysis (ICA), become increasingly popular as appropriate tools for analyzing microarray data. We applied ICA to analyze kinetic gene expression profiles of human monocyte derived macrophages (MDM) from three different donors infected with Francisella tularensis holartica and compared them to more classical methods like hierarchical clustering. Results were compared using a pathway analysis tool, based on the Gene Ontology and the MeSH database. We could show that both methods lead to time-dependent gene regulatory patterns which fit well to known TNFalpha induced immune responses. In comparison, the nonexclusive attribute of ICA results in a more detailed view and a higher resolution in time dependent behavior of the immune response genes. Additionally, we identified NFkappaB as one of the main regulatory genes during response to F. tularensis infection.
Zhu, Hong; Wang, Qiang; Yao, Yizheng; Fang, Jian; Sun, Fengying; Ni, Ying; Shen, Yixin; Wang, Hua; Shao, Shihe
Although Helicobacter pylori (H.pylori) is the dominant gastrointestinal pathogen, the genetic and molecular mechanisms underlying H.pylori-related diseases have not been fully elucidated. Long non-coding RNAs (lncRNAs) have been identified in eukaryotic cells, many of which play important roles in regulating biological processes and pathogenesis. However, the expression changes of lncRNAs in human infected by H.pylori have been rarely reported. This study aimed to identify the dysregulated lncRNAs in human gastric epithelial cells and tissues infected with H.pylori. The aberrant expression profiles of lncRNAs and mRNAs in GES-1 cells with or without H.pylori infection were explored by microarray analysis. LncRNA-mRNA co-expression network was constructed based on Pearson correlation analysis. Gene Ontology (GO) and KEGG Pathway analyses of aberrantly expressed mRNAs were performed to identify the related biological functions and pathologic pathways. The expression changes of target lncRNAs were validated by qRT-PCR to confirm the microarray data in both cells and clinical specimens. Three hundred three lncRNAs and 565 mRNAs were identified as aberrantly expressed transcripts (≥2 or ≤0.5-fold change, P microarray. These dysregulated lncRNAs might contribute to the pathological processes during H.pylori infection.
Utsumi, Yoshinori; Tanaka, Maho; Kurotani, Atsushi; Yoshida, Takuhiro; Mochida, Keiichi; Matsui, Akihiro; Ishitani, Manabu; Sraphet, Supajit; Whankaew, Sukhuman; Asvarak, Thipa; Narangajavana, Jarunya; Triwitayakorn, Kanokporn; Sakurai, Tetsuya; Seki, Motoaki
Cassava anthracnose disease (CAD), caused by the fungus Colletotrichum gloeosporioides f. sp. Manihotis, is a serious disease of cassava (Manihot esculenta) worldwide. In this study, we established a cassava oligonucleotide-DNA microarray representing 59,079 probes corresponding to approximately 30,000 genes based on original expressed sequence tags and RNA-seq information from cassava, and applied it to investigate the molecular mechanisms of resistance to fungal infection using two cassava cultivars, Huay Bong 60 (HB60, resistant to CAD) and Hanatee (HN, sensitive to CAD). Based on quantitative real-time reverse transcription PCR and expression profiling by the microarray, we showed that the expressions of various plant defense-related genes, such as pathogenesis-related (PR) genes, cell wall-related genes, detoxification enzyme, genes related to the response to bacterium, mitogen-activated protein kinase (MAPK), genes related to salicylic acid, jasmonic acid and ethylene pathways were higher in HB60 compared with HN. Our results indicated that the induction of PR genes in HB60 by fungal infection and the higher expressions of defense response-related genes in HB60 compared with HN are likely responsible for the fungal resistance in HB60. We also showed that the use of our cassava oligo microarray could improve our understanding of cassava molecular mechanisms related to environmental responses and development, and advance the molecular breeding of useful cassava plants.
Kim, Won Tae; Seo, Sung-Pil; Byun, Young Joon; Kang, Ho-Won; Kim, Yong-June; Lee, Sang-Cheol; Jeong, Pildu; Seo, Yoonhee; Choe, Soo Young; Kim, Dong-Joon; Kim, Seon-Kyu; Moon, Sung-Kwon; Choi, Yung-Hyun; Lee, Geun Taek; Kim, Isaac Yi; Yun, Seok Joong; Kim, Wun-Jae
There is a growing interest in the use of naturally occurring agents in cancer prevention. This study investigated the garlic extract affects in bladder cancer (BC) prevention. The effect of garlic extract in cancer prevention was evaluated using the T24 BC BALB/C-nude mouse xenograft model. Microarray analysis of tissues was performed to identify differences in gene expression between garlic extract intake and control diet, and gene network analysis was performed to assess candidate mechanisms of action. Furthermore, we investigated the expression value of selected genes in the data of 165 BC patients. Compared to the control group, significant differences in tumor volume and tumor weight were observed in the groups fed 20 mg/kg (p2 and ptissue microarray analysis. A gene network analysis of 279 of these genes (p<0.01) was performed using Cytoscape/ClueGo software: 36 genes and 37 gene ontologies were mapped to gene networks. Protein kinase A (PKA) signaling pathway including AKAP12, RDX, and RAB13 genes were identified as potential mechanisms for the activity of garlic extract in cancer prevention. In BC patients, AKAP12 and RDX were decreased but, RAB13 was increased. Oral garlic extract has strong cancer prevention activity in vivo and an acceptable safety profile. PKA signaling process, especially increasing AKAP12 and RDX and decreasing RAB13, are candidate pathways that may mediate this prevention effect.
Giancarlo, R; Scaturro, D; Utro, F
The prediction of the number of clusters in a dataset, in particular microarrays, is a fundamental task in biological data analysis, usually performed via validation measures. Unfortunately, it has received very little attention and in fact there is a growing need for software tools/libraries dedicated to it. Here we present ValWorkBench, a software library consisting of eleven well known validation measures, together with novel heuristic approximations for some of them. The main objective of this paper is to provide the interested researcher with the full software documentation of an open source cluster validation platform having the main features of being easily extendible in a homogeneous way and of offering software components that can be readily re-used. Consequently, the focus of the presentation is on the architecture of the library, since it provides an essential map that can be used to access the full software documentation, which is available at the supplementary material website . The mentioned main features of ValWorkBench are also discussed and exemplified, with emphasis on software abstraction design and re-usability. A comparison with existing cluster validation software libraries, mainly in terms of the mentioned features, is also offered. It suggests that ValWorkBench is a much needed contribution to the microarray software development/algorithm engineering community. For completeness, it is important to mention that previous accurate algorithmic experimental analysis of the relative merits of each of the implemented measures [19,23,25], carried out specifically on microarray data, gives useful insights on the effectiveness of ValWorkBench for cluster validation to researchers in the microarray community interested in its use for the mentioned task.
Liu Johnson M
Full Text Available Abstract Background Patients with Fanconi anemia (FA suffer from multiple defects, most notably of the hematological compartment (bone marrow failure, and susceptibility to cancer. Cells from FA patients show increased spontaneous chromosomal damage, which is aggravated by exposure to low concentrations of DNA cross-linking agents such as mitomycin C or cisplatin. Five of the identified FA proteins form a nuclear core complex. However, the molecular function of these proteins remains obscure. Methods Oligonucleotide microarrays were used to compare the expression of approximately 12,000 genes from FA cells with matched controls. Expression profiles were studied in lymphoblastoid cell lines derived from three different FA patients, one from the FA-A and two from the FA-C complementation groups. The isogenic control cell lines were obtained by either transfecting the cells with vectors expressing the complementing cDNAs or by using a spontaneous revertant cell line derived from the same patient. In addition, we analyzed expression profiles from two cell line couples at several time points after a 1-hour pulse treatment with a discriminating dose of cisplatin. Results Analysis of the expression profiles showed differences in expression of a number of genes, many of which have unknown function or are difficult to relate to the FA defect. However, from a selected number of proteins involved in cell cycle regulation, DNA repair and chromatin structure, Western blot analysis showed that p21waf1/Cip1 was significantly upregulated after low dose cisplatin treatment in FA cells specifically (as well as being expressed at elevated levels in untreated FA cells. Conclusions The observed increase in expression of p21waf1/Cip1 after treatment of FA cells with crosslinkers suggests that the sustained elevated levels of p21waf1/Cip1 in untreated FA cells detected by Western blot analysis likely reflect increased spontaneous damage in these cells.
Full Text Available Voltage-gated calcium channels (VGCCs are well documented to play roles in cell proliferation, migration, and apoptosis; however, whether VGCCs regulate the onset and progression of cancer is still under investigation. The VGCC family consists of five members, which are L-type, N-type, T-type, R-type and P/Q type. To date, no holistic approach has been used to screen VGCC family genes in different types of cancer. We analyzed the transcript expression of VGCCs in clinical cancer tissue samples by accessing ONCOMINE (www.oncomine.org, a web-based microarray database, to perform a systematic analysis. Every member of the VGCCs was examined across 21 different types of cancer by comparing mRNA expression in cancer to that in normal tissue. A previous study showed that altered expression of mRNA in cancer tissue may play an oncogenic role and promote tumor development; therefore, in the present findings, we focus only on the overexpression of VGCCs in different types of cancer. This bioinformatics analysis revealed that different subtypes of VGCCs (CACNA1C, CACNA1D, CACNA1B, CACNA1G, and CACNA1I are implicated in the development and progression of diverse types of cancer and show dramatic up-regulation in breast cancer. CACNA1F only showed high expression in testis cancer, whereas CACNA1A, CACNA1C, and CACNA1D were highly expressed in most types of cancer. The current analysis revealed that specific VGCCs likely play essential roles in specific types of cancer. Collectively, we identified several VGCC targets and classified them according to different cancer subtypes for prospective studies on the underlying carcinogenic mechanisms. The present findings suggest that VGCCs are possible targets for prospective investigation in cancer treatment.
Oz, M.T.; Yilmaz, R.; Eyidogan, F.; Graaff, de L.H.; Yucel, M.; Oktem, H.A.
DNA microarrays, being high-density and high-throughput, allow quantitative analyses of thousands of genes and their expression patterns in parallel. In this study, Barley1 GereChip was used to investigate transcriptome changes associated with boron (B) toxicity in a sensitive barley cultivar (Horde
Pas, te M.F.W.; Hemert, van S.; Hulsegge, B.; Hoekman, A.J.W.; Pool, M.H.; Rebel, J.M.J.; Smits, M.A.
Pathway information provides insight into the biological processes underlying microarray data. Pathway information is widely available for humans and laboratory animals in databases through the internet, but less for other species, for example, livestock. Many software packages use species-specific
Mazagova, Magdalena; Henning, Robert H.; Duin, Marry; van Buiten, Azuwerus; Buikema, Hendrik; Deelman, Leo E.
Introduction: Microarrays have become the standard technique for discovering new genes involved in the development of (kidney) disease. Diabetic nephropathy is a frequent complication of diabetes and is characterized by renal fibrosis. As the pathways leading to fibrosis are initiated early in diabe
Soglio, V.; Costa, F.; Molthoff, J.W.; Weemen-Hendriks, M.; Schouten, H.J.; Gianfranceschi, L.
The knowledge of the molecular mechanisms underlying fruit quality traits is fundamental to devise efficient marker-assisted selection strategies and to improve apple breeding. In this study, cDNA microarray technology was used to identify genes whose expression changes during fruit development and
Full Text Available Cervical cancer is one of the leading female cancers in Taiwan and ranks as the fifth cause of cancer death in the female population. Human papillomavirus has been established as the causative agent for cervical neoplasia and cervical cancer. However, the tumor biology involved in the prognoses of different cell types in early cancers and tumor responses to radiation in advanced cancers remain largely unknown. The introduction of microarray technologies in the 1990s has provided genome-wide strategies for searching tens of thousands of genes simultaneously. In this review, we first summarize the two types of microarrays: oligonucleotides microarray and cDNA microarray. Then, we review the studies of functional genomics in cervical cancer. Gene expression studies that involved cervical cancer cell lines, cervical cells of cancer versus normal ectocervix, cancer tissues of different histology, radioresistant versus radiosensitive patients, and the combinatorial gene expression associated with chromosomal amplifications are discussed. In particular, CEACAM5, TACSTD1, S100P, and MSLN have shown to be upregulated in adenocarcinoma, and increased expression levels of CEACAM5 and TACSTD1 were significantly correlated with poorer patient outcomes. On the other hand, 35 genes, including apoptotic genes (e.g. BIK, TEGT, SSI-3, hypoxia-inducible genes (e.g. HIF1A, CA12, and tumor cell invasion and metastasis genes (e.g. CTSL, CTSB, PLAU, CD44, have been noted to echo the hypothesis that increased tumor hypoxia leads to radiation resistance in cervical cancer during radiation.
Culley, David E.; Kovacik, William P.; Brockman, Fred J.; Zhang, Weiwen
ABSTRACT-The recent completion of a draft genome sequence for Methanosarcina barkeri has allowed the application of various high throughput post-genomics technologies, such as nucleic acid microarrays and mass spectrometry of proteins to detect global changes in transcription and translation that occur in response to experimental treatments...
LIU Quanjun; ZHOU Qin; BAI Yunfei; GE Qinyu; LU Zuhong
A lab-in-a-tube microarray system is developed for sample inspection and signal detection by fabricating a flat transparent window cap of the Eppendorf tube. The oli- gonucleotide microarray is immobilized on the inner surface of the cap. A small vessel is placed in an Eppendorf tube for storing hybridization solutions. With the microarray system, the full biochemical processes, including gene fragment amplification, fluorescence labeling, hybridization, and fluorescence detection, have been performed in the sealed tube without opening the cap. The images are obtained from a fluorescence microscope and captured by a CCD, and the data are transported to a computer through the universal serial bus (USB). After noise reduction, signal intensity is determined from hybridization image and the presence of gene fragments is identified. The final data output includes sample information, process steps, and hybridization results. A lab-in- a-tube microarray system for detecting ten respiratory viruses at a single detection is designed. High detection throug- hput and accuracy have been demonstrated with the system.
Full Text Available Microarray technology results in high-dimensional and low-sample size data sets. Therefore, fitting sparse models is substantial because only a small number of influential genes can reliably be identified. A number of variable selection approaches have been proposed for high-dimensional time-to-event data based on Cox proportional hazards where censoring is present. The present study applied three sparse variable selection techniques of Lasso, smoothly clipped absolute deviation and the smooth integration of counting, and absolute deviation for gene expression survival time data using the additive risk model which is adopted when the absolute effects of multiple predictors on the hazard function are of interest. The performances of used techniques were evaluated by time dependent ROC curve and bootstrap .632+ prediction error curves. The selected genes by all methods were highly significant (P<0.001. The Lasso showed maximum median of area under ROC curve over time (0.95 and smoothly clipped absolute deviation showed the lowest prediction error (0.105. It was observed that the selected genes by all methods improved the prediction of purely clinical model indicating the valuable information containing in the microarray features. So it was concluded that used approaches can satisfactorily predict survival based on selected gene expression measurements.
Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol
RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated...... the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential...... gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays...
Trask, Heidi W; Cowper-Sal-lari, Richard; Sartor, Maureen A; Gui, Jiang; Heath, Catherine V; Renuka, Janhavi; Higgins, Azara-Jane; Andrews, Peter; Korc, Murray; Moore, Jason H; Tomlinson, Craig R
With no known exceptions, every published microarray study to determine differential mRNA levels in eukaryotes used RNA extracted from whole cells. It is assumed that the use of whole cell RNA in microarray gene expression analysis provides a legitimate profile of steady-state mRNA. Standard labeling methods and the prevailing dogma that mRNA resides almost exclusively in the cytoplasm has led to the long-standing belief that the nuclear RNA contribution is negligible. We report that unadulterated cytoplasmic RNA uncovers differentially expressed mRNAs that otherwise would not have been detected when using whole cell RNA and that the inclusion of nuclear RNA has a large impact on whole cell gene expression microarray results by distorting the mRNA profile to the extent that a substantial number of false positives are generated. We conclude that to produce a valid profile of the steady-state mRNA population, the nuclear component must be excluded, and to arrive at a more realistic view of a cell's gene expression profile, the nuclear and cytoplasmic RNA fractions should be analyzed separately.
Marasso, Simone L; Mombello, Domenico; Cocuzza, Matteo; Casalena, Davide; Ferrante, Ivan; Nesca, Alessandro; Poiklik, Piret; Rekker, Kadri; Aaspollu, Anu; Ferrero, Sergio; Pirri, Candido F
In this work a polymer lab-on-a-chip (LOC), fabricated through MEMS technology, was employed to execute a genetic protocol for the Single Nucleotide Polymorphisms (SNPs) detection. The LOC was made in Poly (methyl methacrylate) (PMMA) and has two levels: the lower one for the insertion and mixing of the reagents, the upper one for the interfacing with the DNA microarray chip. The hereditary hearing loss was chosen as case of study, since the demand for testing such a particular disorder is high and genetics behind the condition is quite clear. The Arrayed Primer EXtension (APEX) genetic protocol was implemented on the LOC to analyze the SNPs. A low density (for detection of up to 10 mutations) and a high density microarray chips (for detection of 245 mutations in 12 genes), containing the primers for the extension, were employed to carry out the APEX reaction on the LOC. Both the microarray chips provide a signal to noise ratio and efficiency comparable with a detection obtained in a conventional protocol in standard conditions. Moreover, significant reduction of the employed PCR volume (from 30 μL to 10 μL) was obtained using the low density chip.
Full Text Available Pre-eclampsia is a pregnancy complication characterized by hypertension and proteinuria. There are several factors associated with an increased risk of developing pre-eclampsia, one of which is increased uterine artery resistance, referred to as “notching”. However, some women do not progress into pre-eclampsia whereas others may have a higher risk of doing so. The placenta, central in pre-eclampsia pathology, may express genes associated with either protection or progression into pre-eclampsia. In order to search for genes associated with protection or progression, whole-genome profiling was performed. Placental tissue from 15 controls, 10 pre-eclamptic, 5 pre-eclampsia with notching, and 5 with notching only were analyzed using microarray and antibody microarrays to study some of the same gene product and functionally related ones. The microarray showed 148 genes to be significantly altered between the four groups. In the preeclamptic group compared to notch only, there was increased expression of genes related to chemotaxis and the NF-kappa B pathway and decreased expression of genes related to antigen processing and presentation, such as human leukocyte antigen B. Our results indicate that progression of pre-eclampsia from notching may involve the development of inflammation. Increased expression of antigen-presenting genes, as seen in the notch-only placenta, may prevent this inflammatory response and, thereby, protect the patient from developing pre-eclamps