Extracytoplasmic function (ECF) sigma factor σF is involved in Caulobacter crescentus response to heavy metal stress

Background The α-proteobacterium Caulobacter crescentus inhabits low-nutrient environments and can tolerate certain levels of heavy metals in these sites. It has been reported that C. crescentus responds to exposure to various heavy metals by altering the expression of a large number of genes. Results In this work, we show that the ECF sigma factor σF is one of the regulatory proteins involved in the control of the transcriptional response to chromium and cadmium. Microarray experiments indicate that σF controls eight genes during chromium stress, most of which were previously described as induced by heavy metals. Surprisingly, σF itself is not strongly auto-regulated under metal stress conditions. Interestingly, σF-dependent genes are not induced in the presence of agents that generate reactive oxygen species. Promoter analyses revealed that a conserved σF-dependent sequence is located upstream of all genes of the σF regulon. In addition, we show that the second gene in the sigF operon acts as a negative regulator of σF function, and the encoded protein has been named NrsF (Negative regulator of sigma F). Substitution of two conserved cysteine residues (C131 and C181) in NrsF affects its ability to maintain the expression of σF-dependent genes at basal levels. Furthermore, we show that σF is released into the cytoplasm during chromium stress and in cells carrying point mutations in both conserved cysteines of the protein NrsF. Conclusion A possible mechanism for induction of the σF-dependent genes by chromium and cadmium is the inactivation of the putative anti-sigma factor NrsF, leading to the release of σF to bind RNA polymerase core and drive transcription of its regulon.

Expression analysis and in silico characterization of intronic long noncoding RNAs in renal cell carcinoma: emerging functional associations

Abstract Background Intronic and intergenic long noncoding RNAs (lncRNAs) are emerging gene expression regulators. The molecular pathogenesis of renal cell carcinoma (RCC) is still poorly understood, and in particular, limited studies are available for intronic lncRNAs expressed in RCC Methods Microarray experiments were performed with custom-designed arrays enriched with probes for lncRNAs mapping to intronic genomic regions. Samples from 18 primary RCC tumors and 11 nontumor adjacent matched tissues were analyzed. Meta-analyses were performed with microarray expression data from three additional human tissues (normal liver, prostate tumor and kidney nontumor samples), and with large-scale public data for epigenetic regulatory marks and for evolutionarily conserved sequences. Results A signature of 29 intronic lncRNAs differentially expressed between RCC and nontumor samples was obtained (false discovery rate (FDR) <5%). A signature of 26 intronic lncRNAs significantly correlated with the RCC five-year patient survival outcome was identified (FDR <5%, p-value ≤0.01). We identified 4303 intronic antisense lncRNAs expressed in RCC, of which 22% were significantly (p <0.05) cis correlated with the expression of the mRNA in the same locus across RCC and three other human tissues. Gene Ontology (GO) analysis of those loci pointed to 'regulation of biological processes’ as the main enriched category. A module map analysis of the protein-coding genes significantly (p <0.05) trans correlated with the 20% most abundant lncRNAs, identified 51 enriched GO terms (p <0.05). We determined that 60% of the expressed lncRNAs are evolutionarily conserved. At the genomic loci containing the intronic RCC-expressed lncRNAs, a strong association (p <0.001) was found between their transcription start sites and genomic marks such as CpG islands, RNA Pol II binding and histones methylation and acetylation. Conclusion Intronic antisense lncRNAs are widely expressed in RCC tumors. Some of them are significantly altered in RCC in comparison with nontumor samples. The majority of these lncRNAs is evolutionarily conserved and possibly modulated by epigenetic modifications. Our data suggest that these RCC lncRNAs may contribute to the complex network of regulatory RNAs playing a role in renal cell malignant transformation.

Constitutive gene expression profile segregates toxicity in locally advanced breast cancer patients treated with high-dose hyperfractionated radical radiotherapy

[EN] Breast cancer patients show a wide variation in normal tissue reactions after radiotherapy. The individual sensitivity to x-rays limits the efficiency of the therapy. Prediction of individual sensitivity to radiotherapy could help to select the radiation protocol and to improve treatment results. The aim of this study was to assess the relationship between gene expression profiles of ex vivo un-irradiated and irradiated lymphocytes and the development of toxicity due to high-dose hyperfractionated radiotherapy in patients with locally advanced breast cancer. Raw data from microarray experiments were uploaded to the Gene Expression Omnibus Database http://www.ncbi.nlm.nih.gov/geo/ (GEO accession GSE15341). We obtained a small group of 81 genes significantly regulated by radiotherapy, lumped in 50 relevant pathways. Using ANOVA and t-test statistical tools we found 20 and 26 constitutive genes (0 Gy) that segregate patients with and without acute and late toxicity, respectively. Non-supervised hierarchical clustering was used for the visualization of results. Six and 9 pathways were significantly regulated respectively. Concerning to irradiated lymphocytes (2 Gy), we founded 29 genes that separate patients with acute toxicity and without it. Those genes were gathered in 4 significant pathways. We could not identify a set of genes that segregates patients with and without late toxicity. In conclusion, we have found an association between the constitutive gene expression profile of peripheral blood lymphocytes and the development of acute and late toxicity in consecutive, unselected patients. These observations suggest the possibility of predicting normal tissue response to irradiation in high-dose non-conventional radiation therapy regimens. Prospective studies with higher number of patients are needed to validate these preliminary results.

Identification of Drosophila heart-specific Cis-Regulatory Modules under Hox control

Cardiac morphogenesis is a complex process governed by evolutionarily conserved transcription factors and signaling molecules. The Drosophila cardiac tube is linear, made of 52 pairs of cardiomyocytes (CMs), which express specific transcription factor genes that have human homologues implicated in Congenital Heart Diseases (CHDs) (NKX2-5, GATA4 and TBX5). The Drosophila cardiac tube is linear and composed of a rostral portion named aorta and a caudal one called heart, distinguished by morphological and functional differences controlled by Hox genes, key regulators of axial patterning. Overexpression and inactivation of the Hox gene abdominal-A (abd-A), which is expressed exclusively in the heart, revealed that abd-A controls heart identity. The aim of our work is to isolate the heart-specific cisregulatory sequences of abd-A direct target genes, the realizator genes granting heart identity. In each segment of the heart, four pairs of cardiomyocytes (CMs) express tinman (tin), homologous to NKX2-5, and acquire strong contractile and automatic rhythmic activities. By tyramide amplified FISH, we found that seven genes, encoding ion channels, pumps or transporters, are specifically expressed in the Tin-CMs of the heart. We initially used online available tools to identify their heart-specific cisregutatory modules by looking for Conserved Non-coding Sequences containing clusters of binding sites for various cardiac transcription factors, including Hox proteins. Based on these data we generated several reporter gene constructs and transgenic embryos, but none of them showed reporter gene expression in the heart. In order to identify additional abd-A target genes, we performed microarray experiments comparing the transcriptomes of aorta versus heart and identified 144 genes overexpressed in the heart. In order to find the heart-specific cis-regulatory regions of these target genes we developed a new bioinformatic approach where prediction is based on pattern matching and ordered statistics. We first retrieved Conserved Noncoding Sequences from the alignment between the D.melanogaster and D.pseudobscura genomes. We scored for combinations of conserved occurrences of ABD-A, ABD-B, TIN, PNR, dMEF2, MADS box, T-box and E-box sites and we ranked these results based on two independent strategies. On one hand we ranked the putative cis-regulatory sequences according to best scored ABD-A biding sites, on the other hand we scored according to conservation of binding sites. We integrated and ranked again the two lists obtained independently to produce a final rank. We generated nGFP reporter construct flies for in vivo validation. We identified three 1kblong heart-specific enhancers. By in vivo and in vitro experiments we are determining whether they are direct abd-A targets, demonstrating the role of a Hox gene in the realization of heart identity. The identified abd-A direct target genes may be targets also of the NKX2-5, GATA4 and/or TBX5 homologues tin, pannier and Doc genes, respectively. The identification of sequences coregulated by a Hox protein and the homologues of transcription factors causing CHDs, will provide a mean to test whether these factors function as Hox cofactors granting cardiac specificity to Hox proteins, increasing our knowledge on the molecular mechanisms underlying CHDs. Finally, it may be investigated whether these Hox targets are involved in CHDs.

Variation in peach fruit susceptibility to Monilinia laxa and gene expression

Brown rot caused by Monilinia laxa and Monilinia fructigena is considered one of the most important diseases affecting Prunus species. Although some losses can result from the rotten fruits in the orchard, most of the damage is caused to fruits during the post-harvest phase. Several studies reported that brown rot incidence during fruit development highly varies; it was found that at a period corresponding to the the pit hardening stage, fruit susceptibility drastically decreases, to be quickly restored afterwards. However the molecular basis of this phenomenon is still not well understood. Furthermore, no difference in the rot incidence was found between wound and un-wound fruits, suggesting that resistance associated more to a specifc biochemical response of the fruit, rather than to a higher mechanical resistance. So far, the interaction Monilinia-peach was analyzed through chemical approaches. In this study, a bio-molecular approach was undertaken in order to reveal alteration in gene expression associated to the variation of susceptibility. In this thesis three different methods for gene expression analysis were used to analyze the alterations in gene expression occurring in peach fruits during the pit hardening stage, in a period encompassing the temporary change in Monilinia susceptibility: real time PCR, microarray and cDNA AFLP techniques. In 2005, peach fruits (cv.K2) were weekly harvested during a 19-week long-period, starting from the fourth week after full bloom, until full maturity. At each sampling time, three replicates of 5 fruits each were dipped in the M.laxa conidial suspension or in distilled water, as negative control. The fruits were maintained at room temperature for 3 hours; afterwards, they were peeled with a scalpel; the peel was immediately frozen in liquid nitrogen and transferred to -80 °C until use. The degree of susceptibility of peach fruit to the pathogen was determined on 3 replicates of 20 fruits each, as percentage of infected fruits, after one week at 20 °C. Real time PCR analysis was performed to study the variation in expression of those genes encoding for the enzymes of the phenylpropanoid pathway (phenylalanine ammonia lyase (PAL), chalcone synthase (CHS), cinnamate 4-hydroxylase (C4H), leucoanthocyanidine reductase (LAR), hydroxycinnamoyl CoA quinate hydroxycinnamoyl transferase (HQT) and of the jasmonate pathway, such as lipoxygenase (LOX), both involved in the production of important defense compounds. Alteration in gene expression was monitored on fruit samples of a period encompassing the pit hardening stage and the corresponding temporary resistance to M.laxa infections, weekly, from the 6thto the 12th week after full bloom (AFB) inoculated with M. laxa or mock-inoculated. The data suggest a critical change in the expression level of the phenylpropanoid pathway from the 7th to the 8th week AFB; such change could be directly physiologically associated to the peach growth and it could indirectly determine the decrease of susceptibility of peach fruit to Monilinia rot during the subsequent weeks. To investigate on the transcriptome variation underneath the temporary loss of susceptibility of peach fruits to Monilinia rot, the microarray and the cDNA AFLP techniques were used. The samples harvested on the 8th week AFB (named S, for susceptible ones) and on the 12th week AFB (named R, for resistant ones) were compared, both inoculated or mock-inoculated. The microarray experiments were carried out at the University of Padua (Dept. of Environmental Agronomy and Crop Science), using the μPEACH1.0 microarray together with the suited protocols. The analysis showed that 30 genes (corresponding to the 0.6% of the total sequences (4806) contained in the μPeach1.0 microarray) were found up-regulated and 31 ( 0.6%) down regulated in RH vs. SH fruits. On the other hand, 20 genes (0.4%) were shown to be up-regulated and 13 (0.3%) down-regulated in the RI vs. SI fruit. No genes were found differentially expressed in the mock-inoculated resistant fruits (RH) vs. the inoculated resistant ones (RI). Among the up-regulated genes an ATP sulfurylase, an heat shock protein 70, the major allergen Pru P1, an harpin inducing protein and S-adenosylmethionine decarboxylase were found, conversely among the down-regulated ones, cinnamyl alcohol dehydrogenase, an histidine- containing phosphotransfer protein and the ferritin were found. The microarray experimental results and the data indirectly derived, were tested by Real Time PCR analysis. cDNA AFLP analysis was also performed on the same samples. 339 transcript derived fragments considered significant for Monilinia resistance, were selected, sequenced and classified. Genes potentially involved in cell rescue and defence were well represented (8%); several genes (12.1%) involved in the protein folding, post-transductional modification and genes (9.2%) involved in cellular transport were also found. A further 10.3% of genes were classified as involved in the metabolism of aminoacid, carbohydrate and fatty acid. On the other hand, genes involved in the protein synthesis (5.7%) and in signal transduction and communication (5.7%) were found. Among the most interesting genes found differentially expressed between susceptible and resistant fruits, genes encoding for pathogenesis related (PR) proteins were found. To investigate on the association of Monilinia resistance and PR biological function, the major allergen Pru P1 (GenBank accession AM493970) and its isoform (here named Pru P2), were expressed in heterologous system and in vitro assayed for their anti-microbial activity. The ribonuclease activity of the recombinant Pru P1 and Pru P2 proteins was assayed against peach total RNA. As the other PR10 proteins, they showed a ribonucleolytic activity, that could be important to contrast pathogen penetration. Moreover Pru P1 and Pru P2 recombinant proteins were checked for direct antimicrobial activity. No inhibitory effect of Pru P1 or Pru P2 was detected against the selected fungi.

Genexpressionsanalyse boviner mesenchymaler Stammzellen und deren in-vitro-differenzierten Folgelinien

Mesenchymale Stamzellen (MSC) sind Vertreter der adulten Stammzellen. Sie bergen durch ihre große Plastizität ein immenses Potential für die klinische Nutzung in Form von Stammzelltherapien. Zellen dieses Typs kommen vornehmlich im Knochenmark der großen Röhrenknochen vor und können zu Knochen, Knorpel und Fettzellen differenzieren. MSC leisten einen wichtigen Beitrag im Rahmen regenerativer Prozesse, beispielsweise zur Heilung von Frakturen. Breite Studien demonstrieren bereits jetzt auch bei komplexeren Erkrankungen (z.B. Osteoporose) therapeutisch vielversprechende Einsatzmöglichkeiten. Oft kommen hierbei aus MSC gezielt differenzierte Folgelinien aus Zellkulturen zum Einsatz. Dies bedingt eine kontrollierte Steuerung der Differenzierungsprozesse in vitro. Der Differenzierung einer Stammzelle liegt eine komplexe Veränderung ihrer Genexpression zugrunde. Genexpressionsmuster zur Erhaltung und Proliferation der Stammzellen müssen durch solche, die der linienspezifischen Differenzierung dienen, ersetzt werden. Die mit der Differenzierung einhergehende, transkriptomische Neuausrichtung ist für das Verständnis der Prozesse grundlegend und wurde bislang nur unzureichend untersucht. Ziel der vorliegenden Arbeit ist eine transkriptomweite und vergleichende Genexpressionsanalyse Mesenchymaler Stammzellen und deren in vitro differenzierten Folgelinien mittels Plasmid - DNA Microarrays und Sequenziertechniken der nächsten Generation (RNA-Seq, Illumina Plattform). In dieser Arbeit diente das Hausrind (Bos taurus) als Modellorganismus, da es genetisch betrachtet eine hohe Ähnlichkeit zum Menschen aufweist und Knochenmark als Quelle von MSC gut verfügbar ist. Primärkulturen Mesenchymaler Stammzellen konnten aus dem Knochenmark von Rindern erfolgreich isoliert werden. Es wurden in vitro Zellkultur - Versuche durchgeführt, um die Zellen zu Osteoblasten, Chondrozyten und Adipozyten zu differenzieren. Zur Genexpressionsanalyse wurde RNA aus jungen MSC und einer MSC Langzeitkultur („alte MSC“), sowie aus den differenzierten Zelllinien isoliert und für nachfolgende Experimente wo nötig amplifiziert. Der Erfolg der Differenzierungen konnte anhand der Genexpression von spezifischen Markergenen und mittels histologischer Färbungen belegt werden. Hierbei zeigte sich die Differenzierung zu Osteoblasten und Adipozyten erfolgreich, während die Differenzierung zu Chondrozyten trotz diverser Modifikationen am Protokoll nicht erfolgreich durchgeführt werden konnte. Eine vergleichende Hybridisierung zur Bestimmung differentieller Genexpression (MSC vs. Differenzierung) mittels selbst hergestellter Plasmid - DNA Microarrays ergab für die Osteogenese mit Genen wie destrin und enpp1, für die undifferenzierten MSC mit dem Gen sema3c neue Kandidatengene, deren biologische Funktion aufzuklären in zukünftigen Experimenten vielversprechende Ergebnisse liefern sollte. Die Analyse der transkriptomweiten Genexpression mittels NGS lieferte einen noch umfangreicheren Einblick ins Differenzierungsgeschehen. Es zeigte sich eine hohe Ähnlichkeit im Expressionsprofil von jungen MSC und Adipozyten, sowie zwischen den Profilen der alten MSC (eine Langzeitkultur) und Osteoblasten. Die alten MSC wiesen deutliche Anzeichen für eine spontane Differenzierung in die osteogene Richtung auf. Durch Analyse der 100 am stärksten exprimierten Gene jeder Zelllinie ließen sich für junge MSC und Adipozyten besonders Gene der extrazellulären Matrix (z.B col1a1,6 ; fn1 uvm.) auffinden. Sowohl Osteoblasten, als auch die alten MSC exprimieren hingegen verstärkt Gene mit Bezug zur oxidativen Phosphorylierung, sowie ribosomale Proteine. Eine Betrachtung der differentiellen Genexpression (junge MSC vs. Differenzierung) mit anschließender Pathway Analyse und Genontologie Anreicherungsstatistik unterstützt diese Ergebnisse vor allem bei Osteoblasten, wo nun jedoch zusätzlich auch Gene zur Regulation der Knochenentwicklung und Mineralisierung in den Vordergrund treten. Für Adipozyten konnte mit Genen des „Jak-STAT signaling pathway“, der Fokalen Adhäsion, sowie Genen des „Cytokine-cytokine receptor interaction pathway“ sehr spannende Einsichten in die Biologie dieses Zelltyps erlangt werden, die sicher weiterer Untersuchungen bedürfen. In undifferenzierten MSC konnte durch differentielle Genexpressionsanalyse die Rolle des nicht kanonischen Teils des WNT Signalweges als für die Aufrechterhaltung des Stammzellstatus potentiell äußerst einflussreich ermittelt werden. Die hier diskutierten Ergebnisse zeigen beispielhaft, dass besonders mittels Genexpressionsanalyse im Hochdurchsatzverfahren wertvolle Einblicke in die komplexe Biologie der Stammzelldifferenzierung möglich sind. Als Grundlage für nachfolgende Arbeiten konnten interessante Gene ermittelt und Hypothesen zu deren Einfluss auf Stammzelleigenschaften und Differenzierungsprozesse aufgestellt werden. Um einen besseren Einblick in den Differenzierungsverlauf zu ermöglichen, könnten künftig NGS Analysen zu unterschiedlichen Differenzierungszeitpunkten durchgeführt werden. Zudem wären weitere Anstrengungen zur erfolgreichen Etablierung der chondrogenen Differenzierung zur vollständigen Analyse der Genexpression des trilinearen Differenzierungspotentials von MSC wünschenswert.

Cambial meristem dormancy in trees involves extensive remodelling of the transcriptome

The establishment of the dormant state in meristems involves considerable physiological and metabolic alterations necessary for surviving unfavourable growth conditions. However, a global molecular analysis of dormancy in meristems has been hampered by the difficulty in isolating meristem cells. We used cryosectioning to isolate purified cambial meristem cells from the woody plant Populus tremula during active growth and dormancy. These samples were used to generate meristem-specific cDNA libraries and for cDNA microarray experiments to define the global transcriptional changes underlying cambial dormancy. The results indicate a significant reduction in the complexity of the cambial transcriptome in the dormant state. Although cell division is terminated in the dormant cambium, the cell cycle machinery appears to be maintained in a skeletal state as suggested by the continued presence of transcripts for several cell cycle regulators. The downregulation of PttPIN1 and PttPIN2 transcripts explains the reduced basipetal polar auxin transport during dormancy. The induction of a member of the SINA family of ubiquitin ligases implicated in auxin signalling indicates a potential mechanism for modulation of auxin sensitivity during cambial dormancy. The metabolic alterations during dormancy are mirrored in the induction of genes involved in starch breakdown and the glyoxysomal cycle. Interestingly, the induction of RGA1 like gene suggests modification of gibberellin signalling in cambial dormancy. The induction of genes such as poplar orthologues of FIE and HAP2 indicates a potential role for these global regulators of transcription in orchestrating extensive changes in gene expression during dormancy.

Application of mixture models to detect differentially expressed genes

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

A simple implementation of a normal mixture approach to differential gene expression in multiclass microarrays

Motivation: An important problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. We provide a straightforward and easily implemented method for estimating the posterior probability that an individual gene is null. The problem can be expressed in a two-component mixture framework, using an empirical Bayes approach. Current methods of implementing this approach either have some limitations due to the minimal assumptions made or with more specific assumptions are computationally intensive. Results: By converting to a z-score the value of the test statistic used to test the significance of each gene, we propose a simple two-component normal mixture that models adequately the distribution of this score. The usefulness of our approach is demonstrated on three real datasets.

Mixture models for detecting differentially expressed genes in microarrays

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

Uncertainty and topographic visualisations

This thesis is a study of low-dimensional visualisation methods for data visualisation under certainty of the input data. It focuses on the two main feed-forward neural network algorithms which are NeuroScale and Generative Topographic Mapping (GTM) by trying to make both algorithms able to accommodate the uncertainty. The two models are shown not to work well under high levels of noise within the data and need to be modified. The modification of both models, NeuroScale and GTM, are verified by using synthetic data to show their ability to accommodate the noise. The thesis is interested in the controversy surrounding the non-uniqueness of predictive gene lists (PGL) of predicting prognosis outcome of breast cancer patients as available in DNA microarray experiments. Many of these studies have ignored the uncertainty issue resulting in random correlations of sparse model selection in high dimensional spaces. The visualisation techniques are used to confirm that the patients involved in such medical studies are intrinsically unclassifiable on the basis of provided PGL evidence. This additional category of ‘unclassifiable’ should be accommodated within medical decision support systems if serious errors and unnecessary adjuvant therapy are to be avoided.

Predictive gene lists for breast cancer prognosis: a topographic visualisation study

Background: The controversy surrounding the non-uniqueness of predictive gene lists (PGL) of small selected subsets of genes from very large potential candidates as available in DNA microarray experiments is now widely acknowledged 1. Many of these studies have focused on constructing discriminative semi-parametric models and as such are also subject to the issue of random correlations of sparse model selection in high dimensional spaces. In this work we outline a different approach based around an unsupervised patient-specific nonlinear topographic projection in predictive gene lists. Methods: We construct nonlinear topographic projection maps based on inter-patient gene-list relative dissimilarities. The Neuroscale, the Stochastic Neighbor Embedding(SNE) and the Locally Linear Embedding(LLE) techniques have been used to construct two-dimensional projective visualisation plots of 70 dimensional PGLs per patient, classifiers are also constructed to identify the prognosis indicator of each patient using the resulting projections from those visualisation techniques and investigate whether a-posteriori two prognosis groups are separable on the evidence of the gene lists. A literature-proposed predictive gene list for breast cancer is benchmarked against a separate gene list using the above methods. Generalisation ability is investigated by using the mapping capability of Neuroscale to visualise the follow-up study, but based on the projections derived from the original dataset. Results: The results indicate that small subsets of patient-specific PGLs have insufficient prognostic dissimilarity to permit a distinction between two prognosis patients. Uncertainty and diversity across multiple gene expressions prevents unambiguous or even confident patient grouping. Comparative projections across different PGLs provide similar results. Conclusion: The random correlation effect to an arbitrary outcome induced by small subset selection from very high dimensional interrelated gene expression profiles leads to an outcome with associated uncertainty. This continuum and uncertainty precludes any attempts at constructing discriminative classifiers. However a patient's gene expression profile could possibly be used in treatment planning, based on knowledge of other patients' responses. We conclude that many of the patients involved in such medical studies are intrinsically unclassifiable on the basis of provided PGL evidence. This additional category of 'unclassifiable' should be accommodated within medical decision support systems if serious errors and unnecessary adjuvant therapy are to be avoided.

MediPlEx - a tool to combine in silico & experimental gene expression profiles of the model legume Medicago truncatula

Background: Expressed Sequence Tags (ESTs) are in general used to gain a first insight into gene activities from a species of interest. Subsequently, and typically based on a combination of EST and genome sequences, microarray-based expression analyses are performed for a variety of conditions. In some cases, a multitude of EST and microarray experiments are conducted for one species, covering different tissues, cell states, and cell types. Under these circumstances, the challenge arises to combine results derived from the different expression profiling strategies, with the goal to uncover novel information on the basis of the integrated datasets. Findings: Using our new analysis tool, MediPlEx (MEDIcago truncatula multiPLe EXpression analysis), expression data from EST experiments, oligonucleotide microarrays and Affymetrix GeneChips® can be combined and analyzed, leading to a novel approach to integrated transcriptome analysis. We have validated our tool via the identification of a set of well-characterized AM-specific and AM-induced marker genes, identified by MediPlEx on the basis of in silico and experimental gene expression profiles from roots colonized with AM fungi. Conclusions: MediPlEx offers an integrated analysis pipeline for different sets of expression data generated for the model legume Medicago truncatula. As expected, in silico and experimental gene expression data that cover the same biological condition correlate well. The collection of differentially expressed genes identified via MediPlEx provides a starting point for functional studies in plant mutants.

Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations

We present statistical methods for analyzing replicated cDNA microarray expression data and report the results of a controlled experiment. The study was conducted to investigate inherent variability in gene expression data and the extent to which replication in an experiment produces more consistent and reliable findings. We introduce a statistical model to describe the probability that mRNA is contained in the target sample tissue, converted to probe, and ultimately detected on the slide. We also introduce a method to analyze the combined data from all replicates. Of the 288 genes considered in this controlled experiment, 32 would be expected to produce strong hybridization signals because of the known presence of repetitive sequences within them. Results based on individual replicates, however, show that there are 55, 36, and 58 highly expressed genes in replicates 1, 2, and 3, respectively. On the other hand, an analysis by using the combined data from all 3 replicates reveals that only 2 of the 288 genes are incorrectly classified as expressed. Our experiment shows that any single microarray output is subject to substantial variability. By pooling data from replicates, we can provide a more reliable analysis of gene expression data. Therefore, we conclude that designing experiments with replications will greatly reduce misclassification rates. We recommend that at least three replicates be used in designing experiments by using cDNA microarrays, particularly when gene expression data from single specimens are being analyzed.

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

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