Evaluation of the gene-specific dye bias in cDNA microarray experiments

Identification of potential target genes associated with the reversion of androgen-dependent skeletal muscle atrophy

Muscle wasting or atrophy is extensively associated with human systemic diseases including diabetes, cancer, and kidney failure. Accumulating evidence from transcriptional profiles has noted that a common set of genes, termed atrogenes, is modulated in atrophying muscles. However, the transcriptional changes that trigger the reversion or attenuation of muscle atrophy have not been characterized at the molecular level until now. Here, we applied cDNA microarrays to investigate the transcriptional response of androgen-sensitive Levator ani muscle (LA) during atrophy reversion. Most of the differentially expressed genes behaved as atrogenes and responded to castration-induced atrophy. However, seven genes (APLN, DUSP5, IGF1, PIK3IP1, KLHL38, PI15, and MKL1) did not respond to castration but instead responded exclusively to testosterone replacement. Considering that almost all proteins encoded by these genes are associated with the reversion of atrophy and may function as regulators of cell proliferation/growth, our results provide new perspectives on the existence of anti-atrogenes.

Dysregulation of mitotic machinery genes precedes genome instability during spontaneous pre-malignant transformation of mouse ovarian surface epithelial cells

Background

Based in epidemiological evidence, repetitive ovulation has been proposed to play a role in the origin of ovarian cancer by inducing an aberrant wound rupture-repair process of the ovarian surface epithelium (OSE). Accordingly, long term cultures of isolated OSE cells undergo in vitro spontaneous transformation thus developing tumorigenic capacity upon extensive subcultivation. In this work, C57BL/6 mouse OSE (MOSE) cells were cultured up to passage 28 and their RNA and DNA copy number profiles obtained at passages 2, 5, 7, 10, 14, 18, 23, 25 and 28 by means of DNA microarrays. Gene ontology, pathway and network analyses were focused in passages earlier than 20, which is a hallmark of malignancy in this model.

Results

At passage 14, 101 genes were up-regulated in absence of significant DNA copy number changes. Among these, the top-3 enriched functions (>30 fold, adj p < 0.05) comprised 7 genes coding for centralspindlin, chromosome passenger and minichromosome maintenance protein complexes. The genes Ccnb1 (Cyclin B1), Birc5 (Survivin), Nusap1 and Kif23 were the most recurrent in over a dozen GO terms related to the mitotic process. On the other hand, Pten plus the large non-coding RNAs Malat1 and Neat1 were among the 80 down-regulated genes with mRNA processing, nuclear bodies, ER-stress response and tumor suppression as relevant terms. Interestingly, the earliest discrete segmental aneuploidies arose by passage 18 in chromosomes 7, 10, 11, 13, 15, 17 and 19. By passage 23, when MOSE cells express the malignant phenotype, the dysregulated gene expression repertoire expanded, DNA imbalances enlarged in size and covered additional loci.

Conclusion

Prior to early aneuploidies, overexpression of genes coding for the mitotic apparatus in passage-14 pre-malignant MOSE cells indicate an increased proliferation rate suggestive of replicative stress. Concomitant down-regulation of nuclear bodies and RNA processing related genes suggests altered control of nuclear RNA maturation, features recently linked to impaired DNA damage response leading to genome instability. These results, combined with cytogenetic analysis by other authors in this model, suggest that transcriptional profile at passage 14 might induce cytokinesis failure by which tetraploid cells approach a near-tetraploid stage containing primary chromosome aberrations that initiate the tumorigenic drive.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-3068-5) contains supplementary material, which is available to authorized users.

DNA microarray unravels rapid changes in transcriptome of MK-801 treated rat brain

AIM: To investigate the impact of MK-801 on gene expression patterns genome wide in rat brain regions.

METHODS: Rats were treated with an intraperitoneal injection of MK-801 [0.08 (low-dose) and 0.16 (high-dose) mg/kg] or NaCl (vehicle control). In a first series of experiment, the frontoparietal electrocorticogram was recorded 15 min before and 60 min after injection. In a second series of experiments, the whole brain of each animal was rapidly removed at 40 min post-injection, and different regions were separated: amygdala, cerebral cortex, hippocampus, hypothalamus, midbrain and ventral striatum on ice followed by DNA microarray (4 × 44 K whole rat genome chip) analysis.

RESULTS: Spectral analysis revealed that a single systemic injection of MK-801 significantly and selectively augmented the power of baseline gamma frequency (30-80 Hz) oscillations in the frontoparietal electroencephalogram. DNA microarray analysis showed the largest number (up- and down- regulations) of gene expressions in the cerebral cortex (378), midbrain (376), hippocampus (375), ventral striatum (353), amygdala (301), and hypothalamus (201) under low-dose (0.08 mg/kg) of MK-801. Under high-dose (0.16 mg/kg), ventral striatum (811) showed the largest number of gene expression changes. Gene expression changes were functionally categorized to reveal expression of genes and function varies with each brain region.

CONCLUSION: Acute MK-801 treatment increases synchrony of baseline gamma oscillations, and causes very early changes in gene expressions in six individual rat brain regions, a first report.

DNA microarray-based analysis of voluntary resistance wheel running reveals novel transcriptome leading robust hippocampal plasticity

In two separate experiments, voluntary resistance wheel running with 30% of body weight (RWR), rather than wheel running (WR), led to greater enhancements, including adult hippocampal neurogenesis and cognitive functions, in conjunction with hippocampal brain‐derived neurotrophic factor (BDNF) signaling (Lee et al., J Appl Physiol, 2012; Neurosci Lett., 2013). Here we aimed to unravel novel molecular factors and gain insight into underlying molecular mechanisms for RWR‐enhanced hippocampal functions; a high‐throughput whole‐genome DNA microarray approach was applied to rats performing voluntary running for 4 weeks. RWR rats showed a significant decrease in average running distances although average work levels increased immensely, by about 11‐fold compared to WR, resulting in muscular adaptation for the fast‐twitch plantaris muscle. Global transcriptome profiling analysis identified 128 (sedentary × WR) and 169 (sedentary × RWR) up‐regulated (>1.5‐fold change), and 97 (sedentary × WR) and 468 (sedentary × RWR) down‐regulated (<0.75‐fold change) genes. Functional categorization using both pathway‐ or specific‐disease‐state‐focused gene classifications and Ingenuity Pathway Analysis (IPA) revealed expression pattern changes in the major categories of disease and disorders, molecular functions, and physiological system development and function. Genes specifically regulated with RWR include the newly identified factors of NFATc1, AVPR1A, and FGFR4, as well as previously known factors, BDNF and CREB mRNA. Interestingly, RWR down‐regulated multiple inflammatory cytokines (IL1B, IL2RA, and TNF) and chemokines (CXCL1, CXCL10, CCL2, and CCR4) with the SYCP3, PRL genes, which are potentially involved in regulating hippocampal neuroplastic changes. These results provide understanding of the voluntary‐RWR‐related hippocampal transcriptome, which will open a window to the underlying mechanisms of the positive effects of exercise, with therapeutic value for enhancing hippocampal functions.

New information on the voluntary RWR influenced transcriptome in rat hippocampus. Selected gene candidates may be a critical role in the development of hippocampal adaptations in RWR.

Comparative analysis of response to selection with three insecticides in the dengue mosquito Aedes aegypti using mRNA sequencing

Background

Mosquito control programmes using chemical insecticides are increasingly threatened by the development of resistance. Such resistance can be the consequence of changes in proteins targeted by insecticides (target site mediated resistance), increased insecticide biodegradation (metabolic resistance), altered transport, sequestration or other mechanisms. As opposed to target site resistance, other mechanisms are far from being fully understood. Indeed, insecticide selection often affects a large number of genes and various biological processes can hypothetically confer resistance. In this context, the aim of the present study was to use RNA sequencing (RNA-seq) for comparing transcription level and polymorphism variations associated with adaptation to chemical insecticides in the mosquito Aedes aegypti. Biological materials consisted of a parental susceptible strain together with three child strains selected across multiple generations with three insecticides from different classes: the pyrethroid permethrin, the neonicotinoid imidacloprid and the carbamate propoxur.

Results

After ten generations, insecticide-selected strains showed elevated resistance levels to the insecticides used for selection. RNA-seq data allowed detecting over 13,000 transcripts, of which 413 were differentially transcribed in insecticide-selected strains as compared to the susceptible strain. Among them, a significant enrichment of transcripts encoding cuticle proteins, transporters and enzymes was observed. Polymorphism analysis revealed over 2500 SNPs showing > 50% allele frequency variations in insecticide-selected strains as compared to the susceptible strain, affecting over 1000 transcripts. Comparing gene transcription and polymorphism patterns revealed marked differences among strains. While imidacloprid selection was linked to the over transcription of many genes, permethrin selection was rather linked to polymorphism variations. Focusing on detoxification enzymes revealed that permethrin selection strongly affected the polymorphism of several transcripts encoding cytochrome P450 monooxygenases likely involved in insecticide biodegradation.

Conclusions

The present study confirmed the power of RNA-seq for identifying concomitantly quantitative and qualitative transcriptome changes associated with insecticide resistance in mosquitoes. Our results suggest that transcriptome modifications can be selected rapidly by insecticides and affect multiple biological functions. Previously neglected by molecular screenings, polymorphism variations of detoxification enzymes may play an important role in the adaptive response of mosquitoes to insecticides.

Uranium perturbs signaling and iron uptake response in Arabidopsis thaliana roots

The early plant root response to uranyl was characterized using complete Arabidopsis transcriptome microarrays.

Comparative analysis of seed transcriptomes of ambient ozone-fumigated 2 different rice cultivars

High ozone (O3) concentrations not only damage plant life but also cause considerable losses in plant productivity. To screen for molecular factors usable as potential biomarkers to identify for O3-sensitive and -tolerant lines and design O3 tolerant crops, our project examines the effects of O3 on rice, using high-throughput omics approaches. In this study, we examined growth and yield parameters of 4 rice cultivars fumigated for a life-time with ambient air (mean O3: 31.4-32.7 ppb) or filtered air (mean O3: 6.6-8.3 ppb) in small open-top chambers (sOTCs) to select O3-sensitive (indica cv Takanari) and O3-tolerant (japonica cv Koshihikari) cultivars for analysis of seed transcriptomes using Agilent 4 × 44K rice oligo DNA chip. Total RNA from dry mature dehusked seeds of Takanari and Koshihikari cultivars was extracted using a modified protocol based on cethyltrimethylammonium bromide extraction buffer and phenol-chloroform-isoamylalcohol treatment, followed by DNA microarray analysis using the established dye-swap method. Direct comparison of Koshihikari and Takanari O3 transcriptomes in seeds of rice plants fumigated with ambient O3 in sOTCs successfully showed that genes encoding proteins involved in jasmonic acid, GABA biosynthesis, cell wall and membrane modification, starch mobilization, and secondary metabolite biosynthesis are differently regulated in sensitive cv Takanari and tolerant cv Koshihikari. MapMan analysis further mapped the molecular factors activated by O3, confirming Takanari is rightly classified as an O3 sensitive genotype.

Memory-related gene expression profile of the male rat hippocampus induced by teeth extraction and occlusal support recovery

OBJECTIVES

The present study aimed to identify the effect of memory-related genes on male rats tested for spatial memory with either molar teeth extraction or its restoration by occlusal support using experimental dentures.

DESIGN

Memory-related genes were detected from hippocampi of male Wistar rats (exposed to teeth extraction with or without dentures, or no extraction (control)) (7-week old) after behavioural testing (via the radial maze task) using a DNA microarray. The time course of the expression of these genes was evaluated by quantitative real-time polymerase chain reaction (PCR) (on 49-week-old rats).

RESULTS

In preliminary experiments, to determine which memory genes are affected by spatial memory training, DNA microarray analysis revealed that thyrotropin-releasing hormone (Trh) and tenascin XA (Tnxa) were up-regulated and neuronatin (Nnat) and S100a9 were down-regulated after the maze training. The expression of Tnxa, Nnat and S100a9 of 49-week-old rats (during the time course) via quantitative real-time PCR was consistent with the results of microarrays of the preliminary experiment. Expression of Trh that was evaluated by quantitative real-time PCR did not agree with the results for this gene from the microarray for all groups. Therefore, expression of Trh may have increased in only young, trained rats. The expression of S100a9 prior to the maze task was down-regulated in only the extraction group.

CONCLUSION

These results demonstrated that Trh, Tnxa and Nnat genes were affected according to the degree of memory in male rats. This study also indicated that S100a9 is a memory-related gene, which is affected by the presence of occlusal support.

Detecting and comparing non-coding RNAs in the high-throughput era

In recent years there has been a growing interest in the field of non-coding RNA. This surge is a direct consequence of the discovery of a huge number of new non-coding genes and of the finding that many of these transcripts are involved in key cellular functions. In this context, accurately detecting and comparing RNA sequences has become important. Aligning nucleotide sequences is a key requisite when searching for homologous genes. Accurate alignments reveal evolutionary relationships, conserved regions and more generally any biologically relevant pattern. Comparing RNA molecules is, however, a challenging task. The nucleotide alphabet is simpler and therefore less informative than that of amino-acids. Moreover for many non-coding RNAs, evolution is likely to be mostly constrained at the structural level and not at the sequence level. This results in very poor sequence conservation impeding comparison of these molecules. These difficulties define a context where new methods are urgently needed in order to exploit experimental results to their full potential. This review focuses on the comparative genomics of non-coding RNAs in the context of new sequencing technologies and especially dealing with two extremely important and timely research aspects: the development of new methods to align RNAs and the analysis of high-throughput data.

Partial resistance to clubroot in Arabidopsis is based on changes in the host primary metabolism and targeted cell division and expansion capacity

To date, studies of the molecular basis of disease resistance mainly focused on qualitative resistance. However, deciphering mechanisms underlying quantitative resistance could lead to insights into the relationship between qualitative and quantitative resistance and guide the utilization of these two types of resistance to produce durably resistant cultivars. A functional genomics approach, using the CATMA whole-genome microarray, was used to detect changes in gene expression associated with partial quantitative resistance in the Arabidopsis thaliana-Plasmodiophora brassicae pathosystem. The time course of transcript abundance during partial clubroot resistance response was monitored at the whole plant level, and direct comparisons between partial resistance and susceptibility responses were made using the same host genotype. An increasingly complex host response was revealed, as was the differential influence of P. brassicae infection on the transcription of Arabidopsis genes according to the isolate used. We observed, at the transcriptomic level, that metabolic diversion by the pathogen was reduced or delayed, classical plant defense responses were induced earlier and/or more strongly, and cell enlargement and proliferation were actively inhibited in the partial quantitative resistance response compared to the susceptible one.

Array comparative genomic hybridization: an overview of protocols, applications, and technology trends

From the earliest observations of human chromosomes in the late 1800s to modern day next generation sequencing technologies, much has been learned about human cancers by the vigorous application of the techniques of the day. In general, resolution has improved tremendously, and correspondingly the size of the datasets generated has grown exponentially such that computational methods required to handle massive datasets have had to be devised. This chapter provides a brief synopsis of the evolution of such techniques as an introduction to the subsequent chapters that provide methods and applications, relevant to research, and clinical diagnostics.

ADHD animal model characterization: transcriptomics and proteomics analyses

Mechanisms underlying behavioral abnormalities of patients with attention-deficit hyperactivity disorder (ADHD) disorder are still unknown. It is worth clarifying alterations in the brain of animal models for ADHD. The animals with neonatal treatment with 6-hydroxydopamine (6-OHDA) and congenic wiggling (Wig) rats show motor hyperactivities during a period of darkness at 4 weeks of age. In rats with 6-OHDA lesions, subcutaneous injection of methamphetamine attenuates hyperactivity, the reverse of its effect in Wig rats. To understand mechanisms underlying such behavioral abnormalities, transcriptomics and proteomics analyses may provide novel information in brain research. The expression of genes and proteins in brain regions can be measured by DNA microarray and two-dimensional gel electrophoresis, respectively. We have shown different expressions of genes and proteins in brains of rats with neonatal 6-OHDA lesions and Wig rats.

Unraveling the ischemic brain transcriptome in a permanent middle cerebral artery occlusion mouse model by DNA microarray analysis

Brain ischemia, also termed cerebral ischemia, is a condition in which there is insufficient blood flow to the brain to meet metabolic demand, leading to tissue death (cerebral infarction) due to poor oxygen supply (cerebral hypoxia). Our group is interested in the protective effects of neuropeptides for alleviating brain ischemia, as well as the underlying mechanisms of their action. The present study was initiated to investigate molecular responses at the level of gene expression in ischemic brain tissue. To achieve this, we used a mouse permanent middle cerebral artery occlusion (PMCAO) model in combination with high-throughput DNA microarray analysis on an Agilent microarray platform. Briefly, the right (ipsilateral) and left (contralateral) hemispheres of PMCAO model mice were dissected at two time points, 6 and 24 hours post-ischemia. Total RNA from the ischemic (ipsilateral) hemisphere was subjected to DNA microarray analysis on a mouse whole genome 4x44K DNA chip using a dye-swap approach. Functional categorization using the gene ontology (GO, MGD/AMIGO) of numerous changed genes revealed expression pattern changes in the major categories of cellular process, biological regulation, regulation of biological process, metabolic process and response to stimulus. Reverse-transcriptase PCR (RT-PCR) analysis on randomly selected highly up- or downregulated genes validated, in general, the microarray data. Using two time points for this analysis, major and minor trends in gene expression and/or functions were observed in relation to early- and late-response genes and differentially regulated genes that were further classified into specific pathways or disease states. We also examined the expression of these genes in the contralateral hemisphere, which suggested the presence of bilateral effects and/or differential regulation. This study provides the first ischemia-related transcriptome analysis of the mouse brain, laying a strong foundation for studies designed to elucidate the mechanisms regulating ischemia and to explore the neuroprotective effects of agents such as target neuropeptides.

Seeking gene candidates responsible for developmental origins of health and disease

Human epidemiological evidence has led scientists to theorize that undernutrition during gestation is an important early origin of adult diseases. Animal models have successfully demonstrated that maternal diet could contribute to some adult diseases. Undernutrition is perceived harmful in pregnant women, whereas calorie restriction is a strategy proven to extend healthy and maximum lifespan in adult. This diagrammatically opposite effect of nutritional condition might provide us with hints to search for genes underlying health conditions. Here, we have initiated a study examining the effect of undernutrition on maternal and fetal livers, utilizing high-throughput DNA microarray analysis for screening genome-wide changes in their transcriptomes. Briefly, pregnant mice were exposed to food deprivation (FD) on gestation day (GD) 17, and cesarean section was performed on GD18. Control mice were supplied with chow ad libitum until sacrifice. Total RNA extracted from mother and fetal livers for each control and treatment (FD) was analyzed with an Agilent mouse whole genome DNA chip. A total of 3058 and 3126 up- (>1.5-fold) and down- (<0.75-fold) regulated genes, and 1475 and 1225 up- (>1.5-fold) and down- (<0.75-fold) regulated genes showed differential expression at the mRNA level, in the maternal and fetal livers, respectively. Interestingly, 103 genes up-regulated in the mother were down-regulated in the fetus, whereas 108 down-regulated maternal genes were up-regulated in the fetus; these 211 genes are potential candidates related to longevity or health. The role of some of these genes, in context of the proposed mechanisms for developmental origins of health and disease is discussed.

Sequence-dependent fluorescence of cyanine dyes on microarrays

Cy3 and Cy5 are among the most commonly used oligonucleotide labeling molecules. Studies of nucleic acid structure and dynamics use these dyes, and they are ubiquitous in microarray experiments. They are sensitive to their environment and have higher quantum yield when bound to DNA. The fluorescent intensity of terminal cyanine dyes is also known to be significantly dependent on the base sequence of the oligonucleotide. We have developed a very precise and high-throughput method to evaluate the sequence dependence of oligonucleotide labeling dyes using microarrays and have applied the method to Cy3 and Cy5. We used light-directed in-situ synthesis of terminally-labeled microarrays to determine the fluorescence intensity of each dye on all 1024 possible 5′-labeled 5-mers. Their intensity is sensitive to all five bases. Their fluorescence is higher with 5′ guanines, and adenines in subsequent positions. Cytosine suppresses fluorescence. Intensity falls by half over the range of all 5-mers for Cy3, and two-thirds for Cy5. Labeling with 5′-biotin-streptavidin-Cy3/-Cy5 gives a completely different sequence dependence and greatly reduces fluorescence compared with direct terminal labeling.

Joint genetic analysis of gene expression data with inferred cellular phenotypes

Even within a defined cell type, the expression level of a gene differs in individual samples. The effects of genotype, measured factors such as environmental conditions, and their interactions have been explored in recent studies. Methods have also been developed to identify unmeasured intermediate factors that coherently influence transcript levels of multiple genes. Here, we show how to bring these two approaches together and analyse genetic effects in the context of inferred determinants of gene expression. We use a sparse factor analysis model to infer hidden factors, which we treat as intermediate cellular phenotypes that in turn affect gene expression in a yeast dataset. We find that the inferred phenotypes are associated with locus genotypes and environmental conditions and can explain genetic associations to genes in trans. For the first time, we consider and find interactions between genotype and intermediate phenotypes inferred from gene expression levels, complementing and extending established results.

The first step in transmitting heritable information, expressing RNA molecules, is highly regulated and depends on activations of specific pathways and regulatory factors. The state of the cell is hard to measure, making it difficult to understand what drives the changes in the gene expression. To close this gap, we apply a statistical model to infer the state of the cell, such as activations of transcription factors and molecular pathways, from gene expression data. We demonstrate how the inferred state helps to explain the effects of variation in the DNA and environment on the expression trait via both direct regulatory effects and interactions with the genetic state. Such analysis, exploiting inferred intermediate phenotypes, will aid understanding effects of genetic variability on global traits and will help to interpret the data from existing and forthcoming large scale studies.

Portrait of ependymoma recurrence in children: biomarkers of tumor progression identified by dual-color microarray-based gene expression analysis

Background

Children with ependymoma may experience a relapse in up to 50% of cases depending on the extent of resection. Key biological events associated with recurrence are unknown.

Methodology/Principal Findings

To discover the biology behind the recurrence of ependymomas, we performed CGHarray and a dual-color gene expression microarray analysis of 17 tumors at diagnosis co-hybridized with the corresponding 27 first or subsequent relapses from the same patient. As treatment and location had only limited influence on specific gene expression changes at relapse, we established a common signature for relapse. Eighty-seven genes showed an absolute fold change ≥2 in at least 50% of relapses and were defined as the gene expression signature of ependymoma recurrence. The most frequently upregulated genes are involved in the kinetochore (ASPM, KIF11) or in neural development (CD133, Wnt and Notch pathways). Metallothionein (MT) genes were downregulated in up to 80% of the recurrences. Quantitative PCR for ASPM, KIF11 and MT3 plus immunohistochemistry for ASPM and MT3 confirmed the microarray results. Immunohistochemistry on an independent series of 24 tumor pairs at diagnosis and at relapse confirmed the decrease of MT3 expression at recurrence in 17/24 tumor pairs (p = 0.002). Conversely, ASPM expression was more frequently positive at relapse (87.5% vs 37.5%, p = 0.03). Loss or deletion of the MT genes cluster was never observed at relapse. Promoter sequencing after bisulfite treatment of DNA from primary tumors and recurrences as well as treatment of short-term ependymoma cells cultures with a demethylating agent showed that methylation was not involved in MT3 downregulation. However, in vitro treatment with a histone deacetylase inhibitor or zinc restored MT3 expression.

Conclusions/Significance

The most frequent molecular events associated with ependymoma recurrence were over-expression of kinetochore proteins and down-regulation of metallothioneins. Metallothionein-3 expression is epigenetically controlled and can be restored in vitro by histone deacetylase inhibitors.

Influenza A virus protein PB1-F2 exacerbates IFN-beta expression of human respiratory epithelial cells

The PB1-F2 protein of the influenza A virus (IAV) contributes to viral pathogenesis by a mechanism that is not well understood. PB1-F2 was shown to modulate apoptosis and to be targeted by the CD8(+) T cell response. In this study, we examined the downstream effects of PB1-F2 protein during IAV infection by measuring expression of the cellular genes in response to infection with wild-type WSN/33 and PB1-F2 knockout viruses in human lung epithelial cells. Wild-type virus infection resulted in a significant induction of genes involved in innate immunity. Knocking out the PB1-F2 gene strongly decreased the magnitude of expression of cellular genes implicated in antiviral response and MHC class I Ag presentation, suggesting that PB1-F2 exacerbates innate immune response. Biological network analysis revealed the IFN pathway as a link between PB1-F2 and deregulated genes. Using quantitative RT-PCR and IFN-β gene reporter assay, we determined that PB1-F2 mediates an upregulation of IFN-β expression that is dependent on NF-κB but not on AP-1 and IFN regulatory factor-3 transcription factors. Recombinant viruses knocked out for the PB1-F2 and/or the nonstructural viral protein 1 (the viral antagonist of the IFN response) genes provide further evidence that PB1-F2 increases IFN-β expression and that nonstructural viral protein 1 strongly antagonizes the effect of PB1-F2 on the innate response. Finally, we compared the effect of PB1-F2 variants taken from several IAV strains on IFN-β expression and found that PB1-F2-mediated IFN-β induction is significantly influenced by its amino acid sequence, demonstrating its importance in the host cell response triggered by IAV infection.

Bayesian integrated modeling of expression data: a case study on RhoG

BACKGROUND

DNA microarrays provide an efficient method for measuring activity of genes in parallel and even covering all the known transcripts of an organism on a single array. This has to be balanced against that analyzing data emerging from microarrays involves several consecutive steps, and each of them is a potential source of errors. Errors tend to accumulate when moving from the lower level towards the higher level analyses because of the sequential nature. Eliminating such errors does not seem feasible without completely changing the technologies, but one should nevertheless try to meet the goal of being able to realistically assess degree of the uncertainties that are involved when drawing the final conclusions from such analyses.

RESULTS

We present a Bayesian hierarchical model for finding differentially expressed genes between two experimental conditions, proposing an integrated statistical approach where correcting signal saturation, systematic array effects, dye effects, and finding differentially expressed genes, are all modeled jointly. The integration allows all these components, and also the associated errors, to be considered simultaneously. The inference is based on full posterior distribution of gene expression indices and on quantities derived from them rather than on point estimates. The model was applied and tested on two different datasets.

CONCLUSIONS

The method presents a way of integrating various steps of microarray analysis into a single joint analysis, and thereby enables extracting information on differential expression in a manner, which properly accounts for various sources of potential error in the process.

Data analysis issues for allele-specific expression using Illumina's GoldenGate assay

Background

High-throughput measurement of allele-specific expression (ASE) is a relatively new and exciting application area for array-based technologies. In this paper, we explore several data sets which make use of Illumina's GoldenGate BeadArray technology to measure ASE. This platform exploits coding SNPs to obtain relative expression measurements for alleles at approximately 1500 positions in the genome.

Results

We analyze data from a mixture experiment where genomic DNA samples from pairs of individuals of known genotypes are pooled to create allelic imbalances at varying levels for the majority of SNPs on the array. We observe that GoldenGate has less sensitivity at detecting subtle allelic imbalances (around 1.3 fold) compared to extreme imbalances, and note the benefit of applying local background correction to the data. Analysis of data from a dye-swap control experiment allowed us to quantify dye-bias, which can be reduced considerably by careful normalization. The need to filter the data before carrying out further downstream analysis to remove non-responding probes, which show either weak, or non-specific signal for each allele, was also demonstrated. Throughout this paper, we find that a linear model analysis of the data from each SNP is a flexible modelling strategy that allows for testing of allelic imbalances in each sample when replicate hybridizations are available.

Conclusions

Our analysis shows that local background correction carried out by Illumina's software, together with quantile normalization of the red and green channels within each array, provides optimal performance in terms of false positive rates. In addition, we strongly encourage intensity-based filtering to remove SNPs which only measure non-specific signal. We anticipate that a similar analysis strategy will prove useful when quantifying ASE on Illumina's higher density Infinium BeadChips.

Infection of bovine dendritic cells by rinderpest or measles viruses induces different changes in host transcription

The morbilliviruses are a closely related genus which are very similar in their sequences and share a common receptor, but nevertheless show significant restriction in the host species in which they cause disease. One contribution to this restriction might be the nature of the hosts' responses to infection. We have used microarrays to study the changes in the transcriptome of bovine dendritic cells after infection with wild-type (pathogenic) and vaccine (apathogenic) strains of rinderpest virus (RPV), a bovine pathogen, and a wild-type isolate of measles virus (MV), a morbillivirus that causes disease only in humans and some other primates. We found that, as previously observed in human cells, MV induces a rapid interferon response, while that induced by RPV was delayed and much reduced in magnitude. Pathogenic and apathogenic RPV also showed significant differences, with the latter inducing a slightly higher interferon response as well as significant effects on transcription of genes involved in cell cycle regulation.

Omic analyses unravels global molecular changes in the brain and liver of a rat model for chronic Sake (Japanese alcoholic beverage) intake

The effects of chronic administration of Sake (Japanese alcoholic beverage, Nihonshu) on brain and liver of female F334 (Fisher) rats were surveyed via global omic analyses using DNA microarray, 2-DE, and proton nuclear magnetic resonance. Rats weaned at 4 wk of age were given free access to Sake (15% alcohol), instead of water. At 13 months of age, and 24 h after withdrawal of Sake supply, rats were sacrificed, and the whole brain and liver tissues dissected for analyses. In general, molecular changes in brain were found to be less than those in liver. Transcriptomics data revealed 36 and 9, and 80 and 62 up- and down-regulated genes, in the brain and liver, respectively, with binding and catalytic activity gene categories the most prominently changed. Results suggested Sake-induced fragility of brain and liver toxicity/damage, though no significant abnormalities in growth were seen. At protein level, a striking decrease was found in the expression of NADH dehydrogenase (ubiquinone) Fe-S protein 1 in brain, suggesting attenuation of mitochondrial metabolism. In liver, results again suggested an attenuation of mitochondrial function and, in addition, glycoproteins with unknown function were induced at protein and gene levels, suggesting possible changes in glycoprotein binding in that organ. Metabolomic analysis of brain revealed significant increases in valine, arginine/ornithine, alanine, glutamine, and choline with decreases in isoleucine, N-acetyl aspartate, taurine, glutamate, and gamma aminobutyric acid. Our results provide a detailed inventory of molecular components of both brain and liver after Sake intake, and may help to better understand effects of chronic Sake drinking.

The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations

Background

A major challenge in computational biology is to extract knowledge about the genetic nature of disease from high-throughput data. However, an important obstacle to both biological understanding and clinical applications is the "black box" nature of the decision rules provided by most machine learning approaches, which usually involve many genes combined in a highly complex fashion. Achieving biologically relevant results argues for a different strategy. A promising alternative is to base prediction entirely upon the relative expression ordering of a small number of genes.

Results

We present a three-gene version of "relative expression analysis" (RXA), a rigorous and systematic comparison with earlier approaches in a variety of cancer studies, a clinically relevant application to predicting germline BRCA1 mutations in breast cancer and a cross-study validation for predicting ER status. In the BRCA1 study, RXA yields high accuracy with a simple decision rule: in tumors carrying mutations, the expression of a "reference gene" falls between the expression of two differentially expressed genes, PPP1CB and RNF14. An analysis of the protein-protein interactions among the triplet of genes and BRCA1 suggests that the classifier has a biological foundation.

Conclusion

RXA has the potential to identify genomic "marker interactions" with plausible biological interpretation and direct clinical applicability. It provides a general framework for understanding the roles of the genes involved in decision rules, as illustrated for the difficult and clinically relevant problem of identifying BRCA1 mutation carriers.

Optimal designs for 2-color microarray experiments

Statisticians can play a crucial role in the design of gene expression studies to ensure the most effective allocation of available resources. This paper considers Pareto optimal designs for gene expression studies involving 2-color microarrays. Pareto optimality enables the recommendation of designs that are particularly efficient for the effects of most interest to biologists. This is relevant in the microarray context where analysis is typically carried out separately for those effects. Our approach will allow for effects of interest that correspond to contrasts rather than solely considering parameters of the linear model. We further develop the approach to cater for additional experimental considerations such as contrasts that are of equal scientific interest. This amounts to partitioning all relevant contrasts into subsets of effects that are of equal importance. Based on the partitions, a penalty is employed in order to recommend designs for complex and varied microarray experiments. Finally, we address the issue of gene-specific dye bias. We illustrate using studies of leukemia and breast cancer.

Adaptable gene-specific dye bias correction for two-channel DNA microarrays

DNA microarray technology is a powerful tool for monitoring gene expression or for finding the location of DNA-bound proteins. DNA microarrays can suffer from gene-specific dye bias (GSDB), causing some probes to be affected more by the dye than by the sample. This results in large measurement errors, which vary considerably for different probes and also across different hybridizations. GSDB is not corrected by conventional normalization and has been difficult to address systematically because of its variance. We show that GSDB is influenced by label incorporation efficiency, explaining the variation of GSDB across different hybridizations. A correction method (Gene- And Slide-Specific Correction, GASSCO) is presented, whereby sequence-specific corrections are modulated by the overall bias of individual hybridizations. GASSCO outperforms earlier methods and works well on a variety of publically available datasets covering a range of platforms, organisms and applications, including ChIP on chip. A sequence-based model is also presented, which predicts which probes will suffer most from GSDB, useful for microarray probe design and correction of individual hybridizations. Software implementing the method is publicly available.

From experimental setup to data analysis in transcriptomics: copper metabolism in the human pathogen Candida albicans

Transcript profiling by microarray analysis offers a great opportunity to reveal unknown effects in a comprehensive context. To be able to interpret the data, some basic issues in experimental setting and design including type and number of replications have to be considered and are discussed in this work. In order to facilitate and automate data interpretation, the experimental data were projected and clustered by Correspondence Analysis, subsequently associated with gene ontology (GO) terms for functional classification. We applied the technology to investigate copper metabolism in the human pathogen Candida albicans. The presented dataset gives an example of how different fluorescent labeling, biological and technical replicas and data analysis strategies for microarray experiments may influence the final outcome of the results.

A multiple-loop, double-cube microarray design applied to prostate cancer cell lines with variable sensitivity to histone deacetylase inhibitors

PURPOSE

Although microarray technology has been widely adopted by the scientific community, analysis of the ensuing data remains challenging. In this article, we present our experience with a complex design microarray experiment on resistance mechanisms of histone deacetylase inhibitors (HDACI).

EXPERIMENTAL DESIGN

To improve our understanding of the underlying mechanism of HDACI resistance in prostate cancer cells, we designed a novel "multiple-loop, double-cube" cDNA microarray experiment. In the experiment of 22 arrays, DU145 and PC3 cells were treated with two different HDACIs (vorinostat and valproic acid) and incubation periods (48 and 96 h). Preprocessing included exploratory analyses of the quality of the arrays and intensity-dependent within-array Loess normalization. An ANOVA model was used for inference. The results were validated by Western blot analysis of known treatment targets.

RESULTS

Treatment of PC3 and DU145 cells with HDACIs caused 2.8% to 10% (P<0.001) differential expression across conditions; 51% to 73% of these genes were up-regulated and 28% to 49% were down-regulated. The extent of differential expression was associated with cell line (DU145>PC3), HDACI (valproic acid >or= vorinostat), and duration of treatment (96>48 h). We identified known and new treatment targets involved in cell cycle and apoptosis.

CONCLUSION

A multiple-loop, double-cube microarray design can be used to identify HDACI-induced changes in gene expression possibly related to drug resistance.

Transcriptional profiling of pea ABR17 mediated changes in gene expression in Arabidopsis thaliana

BACKGROUND

Pathogenesis-related proteins belonging to group 10 (PR10) are elevated in response to biotic and abiotic stresses in plants. Previously, we have shown a drastic salinity-induced increase in the levels of ABR17, a member of the PR10 family, in pea. Furthermore, we have also demonstrated that the constitutive expression of pea ABR17 cDNA in Arabidopsis thaliana and Brassica napus enhances their germination and early seedling growth under stress. Although it has been reported that several members of the PR10 family including ABR17 possess RNase activity, the exact mechanism by which the aforementioned characteristics are conferred by ABR17 is unknown at this time. We hypothesized that a study of differences in transcriptome between wild type (WT) and ABR17 transgenic A. thaliana may shed light on this process.

RESULTS

The molecular changes brought about by the expression of pea ABR17 cDNA in A. thaliana in the presence or absence of salt stress were investigated using microarrays consisting of 70-mer oligonucleotide probes representing 23,686 Arabidopsis genes. Statistical analysis identified number of genes which were over represented among up- or down-regulated transcripts in the transgenic line. Our results highlight the important roles of many abscisic acid (ABA) and cytokinin (CK) responsive genes in ABR17 transgenic lines. Although the transcriptional changes followed a general salt response theme in both WT and transgenic seedlings under salt stress, many genes exhibited differential expression patterns when the transgenic and WT lines were compared. These genes include plant defensins, heat shock proteins, other defense related genes, and several transcriptional factors. Our microarray results for selected genes were validated using quantitative real-time PCR.

CONCLUSION

Transcriptional analysis in ABR17 transgenic Arabidopsis plants, both under normal and saline conditions, revealed significant changes in abundance of transcripts for many stress responsive genes, as well as those related to plant growth and development. Our results also suggest that ABR17 may mediate stress tolerance through the modulation of many ABA- and CK-responsive genes and may further our understanding of the role of ABR17 in mediating plant stress responses.

Designing Toxicogenomics Studies that use DNA Array Technology

Background

Bioassays are routinely used to evaluate the toxicity of test agents. Experimental designs for bioassays are largely encompassed by fixed effects linear models. In toxicogenomics studies where DNA arrays measure mRNA levels, the tissue samples are typically generated in a bioassay. These measurements introduce additional sources of variation, which must be properly managed to obtain valid tests of treatment effects.

Results

An analysis of covariance model is developed which combines a fixed-effects linear model for the bioassay with important variance components associated with DNA array measurements. These models can accommodate the dominant characteristics of measurements from DNA arrays, and they account for technical variation associated with normalization, spots, dyes, and batches as well as the biological variation associated with the bioassay. An example illustrates how the model is used to identify valid designs and to compare competing designs.

Conclusions

Many toxicogenomics studies are bioassays which measure gene expression using DNA arrays. These studies can be designed and analyzed using standard methods with a few modifications to account for characteristics of array measurements, such as multiple endpoints and normalization. As much as possible, technical variation associated with probes, dyes, and batches are managed by blocking treatments within these sources of variation. An example shows how some practical constraints can be accommodated by this modelling and how it allows one to objectively compare competing designs.

Assessing probe-specific dye and slide biases in two-color microarray data

BACKGROUND

A primary reason for using two-color microarrays is that the use of two samples labeled with different dyes on the same slide, that bind to probes on the same spot, is supposed to adjust for many factors that introduce noise and errors into the analysis. Most users assume that any differences between the dyes can be adjusted out by standard methods of normalization, so that measures such as log ratios on the same slide are reliable measures of comparative expression. However, even after the normalization, there are still probe specific dye and slide variation among the data. We define a method to quantify the amount of the dye-by-probe and slide-by-probe interaction. This serves as a diagnostic, both visual and numeric, of the existence of probe-specific dye bias. We show how this improved the performance of two-color array analysis for arrays for genomic analysis of biological samples ranging from rice to human tissue.

RESULTS

We develop a procedure for quantifying the extent of probe-specific dye and slide bias in two-color microarrays. The primary output is a graphical diagnostic of the extent of the bias which called ECDF (Empirical Cumulative Distribution Function), though numerical results are also obtained.

CONCLUSION

We show that the dye and slide biases were high for human and rice genomic arrays in two gene expression facilities, even after the standard intensity-based normalization, and describe how this diagnostic allowed the problems causing the probe-specific bias to be addressed, and resulted in important improvements in performance. The R package LMGene which contains the method described in this paper has been available to download from Bioconductor.

Integrated transcriptomics, proteomics, and metabolomics analyses to survey ozone responses in the leaves of rice seedling

Ozone (O(3)), a serious air pollutant, is known to significantly reduce photosynthesis, growth, and yield and to cause foliar injury and senescence. Here, integrated transcriptomics, proteomics, and metabolomics approaches were applied to investigate the molecular responses of O(3) in the leaves of 2-week-old rice (cv. Nipponbare) seedlings exposed to 0.2 ppm O(3) for a period of 24 h. On the basis of the morphological alteration of O(3)-exposed rice leaves, transcript profiling of rice genes was performed in leaves exposed for 1, 12, and 24 h using rice DNA microarray chip. A total of 1535 nonredundant genes showed altered expression of more than 5-fold over the control, representing 8 main functional categories. Genes involved in information storage and processing (10%) and cellular processing and signaling categories (24%) were highly represented within 1 h of O(3) treatment; transcriptional factor and signal transduction, respectively, were the main subcategories. Genes categorized into information storage and processing (17, 23%), cellular processing and signaling (20, 16%) and metabolism (18, 19%) were mainly regulated at 12 and 24 h; their main subcategories were ribosomal protein, post-translational modification, and signal transduction and secondary metabolites biosynthesis, respectively. Two-dimensional gel electrophoresis-based proteomics analyses in combination with tandem mass spectrometer identified 23 differentially expressed protein spots (21 nonredundant proteins) in leaves exposed to O(3) for 24 h compared to respective control. Identified proteins were found to be involved in cellular processing and signaling (32%), photosynthesis (19%), and defense (14%). Capillary electrophoresis-mass spectrometry-based metabolomic profiling revealed accumulation of amino acids, gamma-aminobutyric acid, and glutathione in O(3) exposed leaves until 24 h over control. This systematic survey showed that O(3) triggers a chain reaction of altered gene, protein and metabolite expressions involved in multiple cellular processes in rice.

Proteomics- and transcriptomics-based screening of differentially expressed proteins and genes in brain of Wig rat: a model for attention deficit hyperactivity disorder (ADHD) research

Two global omics approaches were applied to develop an inventory of differentially expressed proteins and genes in Wig rat, a promising animal model of attention-deficit hyperactivity disorder (ADHD). The frontal cortex, striatum, and midbrain of Wig rat at 4 weeks of age were dissected for proteomics and transcriptomics analyses. Two-dimensional gel electrophoresis detected 13, 1, and 16 differentially expressed silver nitrate-stained spots in the frontal cortex, striatum, and midbrain, respectively. Peptide mass fingerprinting/tandem mass spectrometry identified 19 nonredundant proteins, belonging to 7 functional categories, namely, signal transduction, energy metabolism, cellular transport, protein with binding function, protein synthesis, cytoskeleton, and cell rescue. Interestingly, 10 proteins that were indentified in the present study were also previously reported in studies involving neurodegenerative diseases and psychiatric disorders, such as Alzheimer's disease (AD), Parkinson's disease, and Schizophrenia. Moreover, some of the proteins identified in the midbrain were involved in synaptic vesicular transport, suggesting abnormality in neurotransmitter release in this region. On the other hand, transcriptomics analysis of combined frontal cortex, striatum, and midbrain by rat whole genome 44K DNA oligo microarray revealed highly up-regulated (28) and down-regulated (33) genes. Functional categorization of these genes showed cellular transport, metabolism, protein fate, signal transduction, and transcription as the major categories, with 26% genes of unknown function. Some of the identified genes were related to AD, fragile X syndrome, and ADHD. This is a first comprehensive study providing insight into molecular components in Wig rat brain, and will help to elucidate the roles of identified proteins and genes in Wig rat brain, hopefully leading to uncovering the pathogenesis of ADHD.

Normalization for triple-target microarray experiments

BACKGROUND

Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes are Cy3 and Cy5. Recent improvements in the technology (dye-labelling, scanner and, image analysis) allow hybridization up to four samples simultaneously. The two additional dyes are Alexa488 and Alexa494. The triple-target or four-target technology is very promising, since it allows more flexibility in the design of experiments, an increase in the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. However, there have been few methods proposed for statistical analysis of such data. Moreover the lowess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow simultaneous correction of the raw data.

RESULTS

We propose a two-step normalization procedure for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized lowess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalize p differently labelled targets co-hybridized on a same array, for any value of p greater than 2.

CONCLUSION

The proposed normalization procedure is effective: the technical biases are reduced, the number of false positives is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is room for improving the microarray experiments by simultaneously hybridizing more than two samples.

Evaluating the biodegradation of aromatic hydrocarbons by monitoring of several functional genes

Various microbial activities determine the effectiveness of bioremediation processes. In this work, we evaluated the feasibility of gene array hybridization for monitoring the efficiency of biodegradation processes. Biodegradation of 14C-labelled naphthalene and toluene by the aromatic hydrocarbon-degrading Pseudomonas putida F1, P. putida mt-2 and P. putida G7 was followed in mixed liquid culture microcosm by a preliminary, nylon membrane-based gene array. In the beginning of the study, toluene was degraded rapidly and increased amount of toluene degradation genes was detected by the preliminary gene array developed for the study. After toluene was degraded, naphthalene mineralization started and the amount of naphthalene degradation genes increased as biodegradation proceeded. The amount of toluene degradation genes decreased towards the end of the study. The hybridization signal intensities determined by preliminary gene array were in good agreement with mineralization of naphthalene and toluene and with the amount of naphthalene dioxygenase and toluene dioxygenase genes quantified by dot blot hybridization. The clear correlation between the results obtained by the preliminary array and the biodegradation process suggests that gene array methods can be considered as a promising tool for monitoring the efficiency of biodegradation processes.

Statistical methodology for the analysis of dye-switch microarray experiments

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.

Transcripts of enriched germ cells responding to heat shock as potential markers for porcine semen quality

A cDNA microarray-assisted experiment was conducted to survey genes that respond early to heat shock in enriched immature porcine germ cells; the 5'-UTR flanking the highest upregulated gene, heat shock 105/110 kDa protein 1 (Hsph1 or Hsp105), in response to heat shock was also investigated. We established a porcine testis cDNA microarray with 9944 transcripts from two libraries constructed from the testes of mature boars, with or without heat shock. After a mild heat shock treatment (39 degrees C for 1h and recovered at 34 degrees C for 2h), 380 transcripts demonstrated significant gene expression in enriched immature germ cells; 326 were upregulated and 54 were downregulated. Ten transcripts of interest exhibiting significance analysis of microarrays (SAM) scores higher than the median were subjected to quantitative real-time PCR; three (Hsp105, Hspa4l and Thap4) were upregulated >1.5-fold. The sequence of the 5'-UTR of Hsp105, the highest upregulated transcript, was cloned and analyzed. A single nucleotide polymorphism (SNP) was found at position -762 (C or T) upstream of the translational start site (ATG codon). Only two genotypes (CC or TC) were found in the mature boars that were studied (n=31). A heterozygous genotype (TC) at this SNP site revealed an elevated percentage of morphologically normal sperm during hot and cold seasons; this SNP may be a useful marker for semen quality in boars. Furthermore, the cell-model established from enriched primitive germ cells has potential for the study of reproduction in mature animals.

Simultaneous interaction of Arabidopsis thaliana with Bradyrhizobium Sp. strain ORS278 and Pseudomonas syringae pv. tomato DC3000 leads to complex transcriptome changes

Induced systemic resistance (ISR) is a process elicited by telluric microbes, referred to as plant growth-promoting rhizobacteria (PGPR), that protect the host plant against pathogen attacks. ISR has been defined from studies using Pseudomonas strains as the biocontrol agent. Here, we show for the first time that a photosynthetic Bradyrhizobium sp. strain, ORS278, also exhibits the ability to promote ISR in Arabidopsis thaliana, indicating that the ISR effect may be a widespread ability. To investigate the molecular bases of this response, we performed a transcriptome analysis designed to reveal the changes in gene expression induced by the PGPR, the pathogen alone, or by both. The results confirm the priming pattern of ISR described previously, meaning that a set of genes, of which the majority was predicted to be influenced by jasmonic acid or ethylene, was induced upon pathogen attack when plants were previously colonized by PGPR. The analysis and interpretation of transcriptome data revealed that 12-oxo-phytodienoic acid, an intermediate of the jasmonic acid biosynthesis pathway, is likely to be an actor in the signaling cascade involved in ISR. In addition, we show that the PGPR counterbalanced the pathogen-induced changes in expression of a series of genes.

Correcting for gene-specific dye bias in DNA microarrays using the method of maximum likelihood

MOTIVATION

In two-color microarray experiments, well-known differences exist in the labeling and hybridization efficiency of Cy3 and Cy5 dyes. Previous reports have revealed that these differences can vary on a gene-by-gene basis, an effect termed gene-specific dye bias. If uncorrected, this bias can influence the determination of differentially expressed genes.

RESULTS

We show that the magnitude of the bias scales multiplicatively with signal intensity and is dependent on which nucleotide has been conjugated to the fluorescent dye. A method is proposed to account for gene-specific dye bias within a maximum-likelihood error modeling framework. Using two different labeling schemes, we show that correcting for gene-specific dye bias results in the superior identification of differentially expressed genes within this framework. Improvement is also possible in related ANOVA approaches.

AVAILABILITY

A software implementation of this procedure is freely available at http://cellcircuits.org/VERA

Optimization of minuscule samples for use with cDNA microarrays

The recent advent of microarray technology and RNA amplification allows us to compare the expression profiles of thousands of genes from small amounts of tissue or cells. We have compared and contrasted various methods of RNA preparation, RNA amplification, target labelling and array analysis in order to achieve a streamlined protocol for microarraying small samples. We have concluded that usage of the NIA 15K cDNA array set, in combination with RNA extraction using the Mini RNA Isolation kit (Zymo), amplification with the RiboAmp kit (Arcturus), followed by indirect labelling via the Atlas PowerScript Fluorescent Labelling kit (using a modified protocol), is optimal with a material derived from either very early stage mouse embryos or individually picked embryonic stem cell colonies. Normalisation using the analysis package Limma (Bioconductor) with data normalisation by print tip Loess, using the "normexp" function with an offset of 50 for background adjustment, and incorporating A-quantile between array normalisation was best with our results. Furthermore, RT-PCR confirmation of array results is achievable without amplification, thereby controlling for amplification bias. These methods will be of great utility in mapping the transcriptome of embryonic and other small samples.

Transcriptional profiling of indica rice cultivar IET8585 (Ajaya) infected with bacterial leaf blight pathogen Xanthomonas oryzae pv oryzae

An indica rice cultivar IET8585 (Ajaya) resists diverse races of the Xanthomonas oryzae pv oryzae pathogen attack, and is often cultivated as bacterial leaf blight (blb) resistant check in India. Earlier we reported a recessive blb resistance gene mapped to the long arm of chromosome 5 in IET8585. Recessive gene-mediated blb resistance mechanism is not yet clearly understood. Here we analyzed the transcriptional profile of the blb infected resistant cultivar by rice 22K oligo array. Microarray analysis revealed differential expression of numerous genes at both early (6 h) and late (120 h) stages of infection in the resistant IET8585 cultivar over the susceptible IR24. Some of the differential gene expressions were validated by both RT-PCR and Western blot analysis. Higher expression of ethylene response element binding protein (EREBP) transcription factor along with lower expression of alcohol dehydrogenase gene and reactive oxygen species (ROS) scavenging system may be responsible for hypersensitive cell death in the resistant cultivar upon bacterial infection. Induction of glutathione-mediated detoxification and flavonoid biosynthetic pathways along with up-regulation of defense genes during infection may inhibit pathogen spread in the host tissues. In light of this and previous studies a mechanism of recessive gene-mediated bacterial blight resistance in indica rice is discussed.

A novel technique for measuring variations in DNA copy-number: competitive genomic polymerase chain reaction

Background

Changes in genomic copy number occur in many human diseases including cancer. Characterization of these changes is important for both basic understanding and diagnosis of these diseases. Microarrays have recently become the standard technique and are commercially available. However, it is useful to have an affordable technique to complement them.

Results

We describe a novel polymerase chain reaction (PCR)-based technique, termed competitive genomic PCR (CGP). The main characteristic of CGP is that different adaptors are added to the sample and control genomic DNAs after appropriate restriction enzyme digestion. These adaptor-supplemented DNAs are subjected to competitive PCR using an adaptor-primer and a locus-specific primer. The amplified products are then separated according to size differences between the adaptors. CGP eliminates the tedious steps inherent in quantitative PCR and achieves moderate throughput. Assays with different X chromosome numbers showed that it can provide accurate quantification. High-resolution analysis of neuroblastoma cell lines around the MYCN locus revealed novel junctions for amplification, which were not detected by a commercial array.

Conclusion

CGP is a moderate throughput technique for analyzing changes in genomic copy numbers. Because CGP can measure any genomic locus using PCR primers, it is especially useful for detailed analysis of a genomic region of interest.

Improving the power to detect differentially expressed genes in comparative microarray experiments by including information from self-self hybridizations

Our ability to detect differentially expressed genes in a microarray experiment can be hampered when the number of biological samples of interest is limited. In this situation, we propose the use of information from self-self hybridizations to acuminate our inference of differential expression. A unified modelling strategy is developed to allow better estimation of the error variance. This principle is similar to the use of a pooled variance estimate in the two-sample t-test. The results from real dataset examples suggest that we can detect more genes that are differentially expressed in the combined models. Our simulation study provides evidence that this method increases sensitivity compared to using the information from comparative hybridizations alone, given the same control for false discovery rate. The largest increase in sensitivity occurs when the amount of information in the comparative hybridization is limited.

Self-self hybridization as an alternative experiment design to dye swap for two-color microarrays

Dye-specific bias effects, commonly observed in the two-color microarray platform, are normally corrected using the dye swap design. This design, however, is relatively expensive and labor-intensive. We propose a self-self hybridization design as an alternative to the dye swap design. In this design, the treated and control samples are labeled with Cy5 and Cy3 (or Cy3 and Cy5), respectively, without dye swap, along with a set of self-self hybridizations on the control sample. We compare this design with the dye swap design through investigation of mouse primary hepatocytes treated with three peroxisome proliferator-activated receptor-alpha (PPARalpha) agonists at three dose levels. Using Agilent's Whole Mouse Genome microarray, differentially expressed genes (DEG) were determined for both the self-self hybridization and dye swap designs. The DEG concordance between the two designs was over 80% across each dose treatment and chemical. Furthermore, 90% of DEG-associated biological pathways were in common between the designs, indicating that biological interpretations would be consistent. The reduced labor and expense for the self-self hybridization design make it an efficient substitute for the dye swap design. For example, in larger toxicogenomic studies, only about half the chips are required for the self-self hybridization design compared to that needed in the dye swap design.

Pre-processing Agilent microarray data

Background

Pre-processing methods for two-sample long oligonucleotide arrays, specifically the Agilent technology, have not been extensively studied. The goal of this study is to quantify some of the sources of error that affect measurement of expression using Agilent arrays and to compare Agilent's Feature Extraction software with pre-processing methods that have become the standard for normalization of cDNA arrays. These include log transformation followed by loess normalization with or without background subtraction and often a between array scale normalization procedure. The larger goal is to define best study design and pre-processing practices for Agilent arrays, and we offer some suggestions.

Results

Simple loess normalization without background subtraction produced the lowest variability. However, without background subtraction, fold changes were biased towards zero, particularly at low intensities. ROC analysis of a spike-in experiment showed that differentially expressed genes are most reliably detected when background is not subtracted. Loess normalization and no background subtraction yielded an AUC of 99.7% compared with 88.8% for Agilent processed fold changes. All methods performed well when error was taken into account by t- or z-statistics, AUCs ≥ 99.8%. A substantial proportion of genes showed dye effects, 43% (99%CI : 39%, 47%). However, these effects were generally small regardless of the pre-processing method.

Conclusion

Simple loess normalization without background subtraction resulted in low variance fold changes that more reliably ranked gene expression than the other methods. While t-statistics and other measures that take variation into account, including Agilent's z-statistic, can also be used to reliably select differentially expressed genes, fold changes are a standard measure of differential expression for exploratory work, cross platform comparison, and biological interpretation and can not be entirely replaced. Although dye effects are small for most genes, many array features are affected. Therefore, an experimental design that incorporates dye swaps or a common reference could be valuable.

Statistical analysis of an RNA titration series evaluates microarray precision and sensitivity on a whole-array basis

BACKGROUND

Concerns are often raised about the accuracy of microarray technologies and the degree of cross-platform agreement, but there are yet no methods which can unambiguously evaluate precision and sensitivity for these technologies on a whole-array basis.

RESULTS

A methodology is described for evaluating the precision and sensitivity of whole-genome gene expression technologies such as microarrays. The method consists of an easy-to-construct titration series of RNA samples and an associated statistical analysis using non-linear regression. The method evaluates the precision and responsiveness of each microarray platform on a whole-array basis, i.e., using all the probes, without the need to match probes across platforms. An experiment is conducted to assess and compare four widely used microarray platforms. All four platforms are shown to have satisfactory precision but the commercial platforms are superior for resolving differential expression for genes at lower expression levels. The effective precision of the two-color platforms is improved by allowing for probe-specific dye-effects in the statistical model. The methodology is used to compare three data extraction algorithms for the Affymetrix platforms, demonstrating poor performance for the commonly used proprietary algorithm relative to the other algorithms. For probes which can be matched across platforms, the cross-platform variability is decomposed into within-platform and between-platform components, showing that platform disagreement is almost entirely systematic rather than due to measurement variability.

CONCLUSION

The results demonstrate good precision and sensitivity for all the platforms, but highlight the need for improved probe annotation. They quantify the extent to which cross-platform measures can be expected to be less accurate than within-platform comparisons for predicting disease progression or outcome.

Genome-wide transcriptome profiling of the early cadmium response of Arabidopsis roots and shoots

Transcriptional regulation in response to cadmium treatment was investigated in both roots and leaves of Arabidopsis, using the whole genome CATMA microarray containing at least 24,576 independent probe sets. Arabidopsis plants were hydroponically treated with low (5 microM) or high (50 microM) cadmium concentrations during 2, 6, and 30 hours. At each time point, Cd level was determined using ICP-AES showing that both plant tissues are able to accumulate the heavy metal. RT-PCR of eight randomly selected genes confirmed the reliability of our microarray results. Analyses of response profiles demonstrate the existence of a regulatory network that differentially modulates gene expression in a tissue- and kinetic-specific manner in response to cadmium. One of the main response observed in roots was the induction of genes involved in sulfur assimilation-reduction and glutathione (GSH) metabolism. In addition, HPLC analysis of GSH and phytochelatin (PC) content shows a transient decrease of GSH after 2 and 6 h of metal treatment in roots correlated with an increase of PC contents. Altogether, our results suggest that to cope with cadmium, plants activate the sulfur assimilation pathway by increasing transcription of related genes to provide an enhanced supply of GSH for PC biosynthesis. Interestingly, in leaves an early induction of several genes encoding enzymes involved in the biosynthesis of phenylpropanoids was observed. Finally, our results provide new insights to understand the molecular mechanisms involved in transcriptional regulation in response to cadmium exposure in plants.

A model of anti-angiogenesis: differential transcriptosome profiling of microvascular endothelial cells from diffuse systemic sclerosis patients

The objective of this work was to identify genes involved in impaired angiogenesis by comparing the transcriptosomes of microvascular endothelial cells from normal subjects and patients affected by systemic sclerosis (SSc), as a unique human model disease characterized by insufficient angiogenesis. Total RNAs, prepared from skin endothelial cells of clinically healthy subjects and SSc patients affected by the diffuse form of the disease, were pooled, labeled with fluorochromes, and hybridized to 14,000 70 mer oligonucleotide microarrays. Genes were analyzed based on gene expression levels and categorized into different functional groups based on the description of the Gene Ontology (GO) consortium to identify statistically significant terms. Quantitative PCR was used to validate the array results. After data processing and application of the filtering criteria, the analyzable features numbered 6,724. About 3% of analyzable transcripts (199) were differentially expressed, 141 more abundantly and 58 less abundantly in SSc endothelial cells. Surprisingly, SSc endothelial cells over-express pro-angiogenic transcripts, but also show up-regulation of genes exerting a powerful negative control, and down-regulation of genes critical to cell migration and extracellular matrix-cytoskeleton coupling, all alterations that provide an impediment to correct angiogenesis. We also identified transcripts controlling haemostasis, inflammation, stimulus transduction, transcription, protein synthesis, and genome organization. An up-regulation of transcripts related to protein degradation and ubiquitination was observed in SSc endothelial cells. We have validated data on the main anti-angiogenesis-related genes by RT-PCR, western blotting, in vitro angiogenesis and immunohistochemistry. These observations indicate that microvascular endothelial cells of patients with SSc show abnormalities in a variety of genes that are able to account for defective angiogenesis.