Statistical methodology for the analysis of dye-switch microarray experiments

<p>Abstract</p> <p>Background</p> <p>In individually dye-balanced microarray designs, each biological sample is hybridized on two different slides, once with <it>Cy3 </it>and once with <it>Cy5</it>. 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.</p> <p>Results</p> <p>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.</p> <p>Conclusion</p> <p>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.</p

A generally applicable validation scheme for the assessment of factors involved in reproducibility and quality of DNA-microarray data

BACKGROUND: In research laboratories using DNA-microarrays, usually a number of researchers perform experiments, each generating possible sources of error. There is a need for a quick and robust method to assess data quality and sources of errors in DNA-microarray experiments. To this end, a novel and cost-effective validation scheme was devised, implemented, and employed. RESULTS: A number of validation experiments were performed on Lactococcus lactis IL1403 amplicon-based DNA-microarrays. Using the validation scheme and ANOVA, the factors contributing to the variance in normalized DNA-microarray data were estimated. Day-to-day as well as experimenter-dependent variances were shown to contribute strongly to the variance, while dye and culturing had a relatively modest contribution to the variance. CONCLUSION: Even in cases where 90 % of the data were kept for analysis and the experiments were performed under challenging conditions (e.g. on different days), the CV was at an acceptable 25 %. Clustering experiments showed that trends can be reliably detected also from genes with very low expression levels. The validation scheme thus allows determining conditions that could be improved to yield even higher DNA-microarray data quality

DNA microarray experimental design and software based data normalization and analysis

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A simple method for statistical analysis of intensity differences in microarray-derived gene expression data

BACKGROUND: Microarray experiments offer a potent solution to the problem of making and comparing large numbers of gene expression measurements either in different cell types or in the same cell type under different conditions. Inferences about the biological relevance of observed changes in expression depend on the statistical significance of the changes. In lieu of many replicates with which to determine accurate intensity means and variances, reliable estimates of statistical significance remain problematic. Without such estimates, overly conservative choices for significance must be enforced. RESULTS: A simple statistical method for estimating variances from microarray control data which does not require multiple replicates is presented. Comparison of datasets from two commercial entities using this difference-averaging method demonstrates that the standard deviation of the signal scales at a level intermediate between the signal intensity and its square root. Application of the method to a dataset related to the β-catenin pathway yields a larger number of biologically reasonable genes whose expression is altered than the ratio method. CONCLUSIONS: The difference-averaging method enables determination of variances as a function of signal intensities by averaging over the entire dataset. The method also provides a platform-independent view of important statistical properties of microarray data

Methionine Adenosyltransferase 1a (MAT1A) Enhances Cell Survival During Chemotherapy Treatment and is Associated with Drug Resistance in Bladder Cancer PDX Mice.

Bladder cancer is among the top ten most common cancers, with about ~380,000 new cases and ~150,000 deaths per year worldwide. Tumor relapse following chemotherapy treatment has long been a significant challenge towards completely curing cancer. We have utilized a patient-derived bladder cancer xenograft (PDX) platform to characterize molecular mechanisms that contribute to relapse following drug treatment in advanced bladder cancer. Transcriptomic profiling of bladder cancer xenograft tumors by RNA-sequencing analysis, before and after relapse, following a 21-day cisplatin/gemcitabine drug treatment regimen identified methionine adenosyltransferase 1a (MAT1A) as one of the significantly upregulated genes following drug treatment. Survey of patient tumor sections confirmed elevated levels of MAT1A in individuals who received chemotherapy. Overexpression of MAT1A in 5637 bladder cancer cells increased tolerance to gemcitabine and stalled cell proliferation rates, suggesting MAT1A upregulation as a potential mechanism by which bladder cancer cells persist in a quiescent state to evade chemotherapy

Changes in the transcriptome and metabolome during the initiation of growth cessation in hybrid aspens

At 9 550 years of age, Old Rasmus, a Norway spruce (Picea abies), located in the Dalarna province in Sweden is recognized as the oldest surviving tree in the world. Old Rasmus exemplifies a robust capacity to survive in changing conditions, making trees a unique and fascinating subject for study. For perennial trees located in high latitudes one of the most important survival mechanisms is to be able to predict the coming winter and to halt growth in time. Poplars (Populus sp.) use mainly two environmental signals, temperature and light (day length), to predict the coming winter. However, of these two signals day length predominates. Towards the end of summer when the days shorten the trees recognize a critical day length and thereafter start the processes to halt growth and prepare for the impending winter. This thesis focuses on the early gene expression and metabolic responses exhibited in hybrid aspen (Populus tremula L. x tremuloides) induced by a shorter day length below the critical day length. In our effort to identify and describe these responses we used high throughput technologies such as microarray and GC-MS to generate data. We show that similar responses exists in hybrid aspen as in Arabidopsis, with initial responses in carbohydrate and secondary metabolism pathways and circadian clock associated genes. Our results provide evidence that the hormone Gibberellin (GA) is linked with the photoperiodic regulation pathway by affecting PHYTOCHROME A (PHYA) expression and thereby the levels of transcripts that act downstream of PHYA. We also suggest that in Populus the protein GIGANTEA1 (GI1) might be able to influencing growth cessation process by regulating the expression of FLOWERING LOCUS T2 (FT2) independently of CONSTANS2 (CO2)

Transcriptional Profiling of PRKG2-Null Growth Plate Identifies Putative Down-Stream Targets of PRKG2

Kinase activity of cGMP-dependent, type II, protein kinase (PRKG2) is required for the proliferative to hypertrophic transition of growth plate chondrocytes during endochondral ossification. Loss of PRKG2 function in rodent and bovine models results in dwarfism. The objective of this study was to identify pathways regulated or impacted by PRKG2 loss of function that may be responsible for disproportionate dwarfism at the molecular level. Microarray technology was used to compare growth plate cartilage gene expression in dwarf versus unaffected Angus cattle to identify putative downstream targets of PRGK2. Pathway enrichment of 1284 transcripts (nominal p \u3c 0.05) was used to identify candidate pathways consistent with the molecular phenotype of disproportionate dwarfism. Analysis with the DAVID pathway suite identified differentially expressed genes that clustered in the MHC, cytochrome B, WNT, and Muc1 pathways. A second analysis with pathway studio software identified differentially expressed genes in a host of pathways (e.g. CREB1, P21, CTNNB1, EGFR, EP300, JUN, P53, RHOA, and SRC). As a proof of concept, we validated the differential expression of five genes regulated by P53, including CEBPA, BRCA1, BUB1, CD58, and VDR by real-time PCR (p \u3c 0.05). Known and novel targets of PRKG2 were identified as enriched pathways in this study. This study indicates that loss of PRKG2 function results in differential expression of P53 regulated genes as well as additional pathways consistent with increased proliferation and apoptosis in the growth plate due to achondroplastic dwarfism

Pathway based microarray analysis based on multi-membership gene regulation

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityRecent developments in automation and novel experimental techniques have led to the accumulation of vast amounts of biological data and the emergence of numerous databases to store the wealth of information. Consequentially, bioinformatics have drawn considerable attention, accompanied by the development of a plethora of tools for the analysis of biological data. DNA microarrays constitute a prominent example of a high-throughput experimental technique that has required substantial contribution of bioinformatics tools. Following its popularity there is an on-going effort to integrate gene expression with other types of data in a common analytical approach. Pathway based microarray analysis seeks to facilitate microarray data in conjunction with biochemical pathway data and look for a coordinated change in the expression of genes constituting a pathway. However, it has been observed that genes in a pathway may show variable expression, with some appearing activated while others repressed. This thesis aims to add some contribution to pathway based microarray analysis and assist the interpretation of such observations, based on the fact that in all organisms a substantial number of genes take part in more than one biochemical pathway. It explores the hypothesis that the expression of such genes represents a net effect of their contribution to all their constituent pathways, applying statistical and data mining approaches. A heuristic search methodology is proposed to manipulate the pathway contribution of genes to follow underlying trends and interpret microarray results centred on pathway behaviour. The methodology is further refined to account for distinct genes encoding enzymes that catalyse the same reaction, and applied to modules, shorter chains of reactions forming sub-networks within pathways. Results based on various datasets are discussed, showing that the methodology is promising and may assist a biologist to decipher the biochemical state of an organism, in experiments where pathways exhibit variable expression.School of Information Systems, Computing and Mathematics, Brunel Universit

Increased Adherence and Expression of Virulence Genes in a Lineage of Escherichia coli O157:H7 Commonly Associated with Human Infections

Enterohemorrhagic Escherichia coli (EHEC) O157:H7, a food and waterborne pathogen, can be classified into nine phylogenetically distinct lineages, as determined by single nucleotide polymorphism genotyping. One lineage (clade 8) was found to be associated with hemolytic uremic syndrome (HUS), which can lead to kidney failure and death in some cases, particularly young children. Another lineage (clade 2) differs considerably in gene content and is phylogenetically distinct from clade 8, but caused significantly fewer cases of HUS in a prior study. Little is known, however, about how these two lineages vary with regard to phenotypic traits important for disease pathogenesis and in the expression of shared virulence genes.Here, we quantified the level of adherence to and invasion of MAC-T bovine epithelial cells, and examined the transcriptomes of 24 EHEC O157:H7 strains with varying Shiga toxin profiles from two common lineages. Adherence to epithelial cells was >2-fold higher for EHEC O157:H7 strains belonging to clade 8 versus clade 2, while no difference in invasiveness was observed between the two lineages. Whole-genome 70-mer oligo microarrays, which probe for 6088 genes from O157:H7 Sakai, O157:H7 EDL 933, pO157, and K12 MG1655, detected significant differential expression between clades in 604 genes following co-incubation with epithelial cells for 30 min; 186 of the 604 genes had a >1.5 fold change difference. Relative to clade 2, clade 8 strains showed upregulation of major virulence genes, including 29 of the 41 locus of enterocyte effacement (LEE) pathogenicity island genes, which are critical for adherence, as well as Shiga toxin genes and pO157 plasmid-encoded virulence genes. Differences in expression of 16 genes that encode colonization factors, toxins, and regulators were confirmed by qRT-PCR, which revealed a greater magnitude of change than microarrays.These findings demonstrate that the EHEC O157:H7 lineage associated with HUS expresses higher levels of virulence genes and has an enhanced ability to attach to epithelial cells relative to another common lineage

Modulation of Androgen Receptor Signaling in Hormonal Therapy-Resistant Prostate Cancer Cell Lines

Background: Prostate epithelial cells depend on androgens for survival and function. In (early) prostate cancer (PCa) androgens also regulate tumor growth, which is exploited by hormonal therapies in metastatic disease. The aim of the present study was to characterize the androgen receptor (AR) response in hormonal therapy-resistant PC346 cells and identify potential disease markers. Methodology/Principal Findings: Human 19K oligoarrays were used to establish the androgen-regulated expression profile of androgen-responsive PC346C cells and its derivative therapy-resistant sublines: PC346DCC (vestigial AR levels), PC346Flu1 (AR overexpression) and PC346Flu2 (T877A AR mutation). In total, 107 transcripts were differentially-expressed in PC346C and derivatives after R1881 or hydroxyflutamide stimulations. The AR-regulated expression profiles reflected the AR modifications of respective therapy-resistant sublines: AR overexpression resulted in stronger and broader transcriptional response to R1881 stimulation, AR down-regulation correlated with deficient response of AR-target genes and the T877A mutation resulted in transcriptional response to both R1881 and hydroxyflutamide. This AR-target signature was linked to multiple publicly available cell line and tumor derived PCa databases, revealing that distinct functional clusters were differentially modulated during PCa progression. Differentiation and secretory functions were up-regulated in primary PCa but repressed i