Scanning microarrays at multiple intensities enhances discovery of differentially expressed genes

In silico Identification and Taxonomic Distribution of Plant Class C GH9 Endoglucanases

The glycoside hydrolase 9 superfamily, mainly comprising the endoglucanases, is represented in all three domains of life. The current division of GH9 enzymes, into three subclasses, namely A, B, and C, is centered on parameters derived from sequence information alone. However, this classification is ambiguous, and is limited by the paralogous ancestry of classes B and C endoglucanases, and paucity of biochemical and structural data. Here, we extend this classification schema to putative GH9 endoglucanases present in green plants, with an emphasis on identifying novel members of the class C subset. These enzymes cleave the β(1 → 4) linkage between non-terminal adjacent D-glucopyranose residues, in both, amorphous and crystalline regions of cellulose. We utilized non redundant plant GH9 enzymes with characterized molecular data, as the training set to construct Hidden Markov Models (HMMs) and train an Artificial Neural Network (ANN). The parameters that were used for predicting dominant enzyme function, were derived from this training set, and subsequently refined on 147 sequences with available expression data. Our knowledge-based approach, can ascribe differential endoglucanase activity (A, B, or C) to a query sequence with high confidence, and was used to construct a local repository of class C GH9 endoglucanases (GH9C = 241) from 32 sequenced green plants.

Transcriptional profiling of PRKG2-null growth plate identifies putative down-stream targets of PRKG2

Background

Kinase activity of cGMP-dependent, type II, protein kinase (PRKG2) is required for the proliferative to hypertrophic transition of growth plate chondrocytes during endochondral ossification. Loss of PRKG2 function in rodent and bovine models results in dwarfism. The objective of this study was to identify pathways regulated or impacted by PRKG2 loss of function that may be responsible for disproportionate dwarfism at the molecular level.

Methods

Microarray technology was used to compare growth plate cartilage gene expression in dwarf versus unaffected Angus cattle to identify putative downstream targets of PRGK2.

Results

Pathway enrichment of 1284 transcripts (nominal p < 0.05) was used to identify candidate pathways consistent with the molecular phenotype of disproportionate dwarfism. Analysis with the DAVID pathway suite identified differentially expressed genes that clustered in the MHC, cytochrome B, WNT, and Muc1 pathways. A second analysis with pathway studio software identified differentially expressed genes in a host of pathways (e.g. CREB1, P21, CTNNB1, EGFR, EP300, JUN, P53, RHOA, and SRC). As a proof of concept, we validated the differential expression of five genes regulated by P53, including CEBPA, BRCA1, BUB1, CD58, and VDR by real-time PCR (p < 0.05).

Conclusions

Known and novel targets of PRKG2 were identified as enriched pathways in this study. This study indicates that loss of PRKG2 function results in differential expression of P53 regulated genes as well as additional pathways consistent with increased proliferation and apoptosis in the growth plate due to achondroplastic dwarfism.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-015-1136-6) contains supplementary material, which is available to authorized users.

Optimizing scan parameters for antibody microarray experiments: accelerating robust systems diagnostics for life sciences

Microarray experiments are a centerpiece of postgenomics life sciences and the current efforts to develop systems diagnostics for personalized medicine. The majority of antibody microarray experiments are fluorescence-based, which utilizes a scanner to convert target signals into image files for subsequent quantification. Certain scan parameters such as the laser power and photomultiplier tube gain (PMT) can influence the readout of fluorescent intensities and thus may affect data quantitation. To date, however, there is no consensus of how to determine the optimal settings of microarray scanners. Here we show that different settings of the laser power and PMT not only affect the signal intensities but also the accuracy of antibody microarray experiments. More importantly, we demonstrate an experimental approach using two fluorescent dyes to determine optimal settings of scan parameters for microarray experiments. These measures provide added quality control of microarray experiments, and thus help to improve the accuracy of quantitative outcome in microarray experiments in the above contexts.

Assessing the detection capacity of microarrays as bio/nanosensing platforms

Microarray is one of the most powerful detection systems with multiplexing and high throughput capability. It has significant potential as a versatile biosensing platform for environmental monitoring, pathogen detection, medical therapeutics, and drug screening to name a few. To date, however, microarray applications are still limited to preliminary screening of genome-scale transcription profiling or gene ontology analysis. Expanding the utility of microarrays as a detection tool for various biological and biomedical applications requires information about performance such as the limits of detection and quantification, which are considered as an essential information to decide the detection sensitivity of sensing devices. Here we present a calibration design that integrates detection limit theory and linear dynamic range to obtain a performance index of microarray detection platform using oligonucleotide arrays as a model system. Two different types of limits of detection and quantification are proposed by the prediction or tolerance interval for two common cyanine fluorescence dyes, Cy3 and Cy5. Besides oligonucleotide, the proposed method can be generalized to other microarray formats with various biomolecules such as complementary DNA, protein, peptide, carbohydrate, tissue, or other small biomolecules. Also, it can be easily applied to other fluorescence dyes for further dye chemistry improvement.

Multiparametric analysis, sorting, and transcriptional profiling of plant protoplasts and nuclei according to cell type

Flow cytometry has been employed for the analysis of higher plants for approximately the last 30 years. For the angiosperms, ∼500,000 species, itself a daunting number, parametric measurements enabled through the use of flow cytometers started with basic descriptors of the individual cells and their contents, and have both inspired the development of novel cytometric methods that subsequently have been applied to organisms within other kingdoms of life, and adopted cytometric methods devised for other species, particularly mammals. Higher plants offer unique challenges in terms of flow cytometric analysis, notably the facts that their organs and tissues are complex three-dimensional assemblies of different cell types, and that their individual cells are, in general, larger than those of mammals.This chapter provides an overview of the general types of parametric measurement that have been applied to plants, and provides detailed methods for selected examples based on the plant model Arabidopsis thaliana. These illustrate the use of flow cytometry for the analysis of protoplasts and nuclear DNA contents (genome size and the cell cycle). These are further integrated with measurements focusing on specific cell types, based on transgenic expression of Fluorescent Proteins (FPs), and on analysis of the spectrum of transcripts found within protoplasts and nuclei. These measurements were chosen in particular to illustrate, respectively, the issues encountered in the flow analysis and sorting of large biological cells, typified by protoplasts; how to handle flow analyses under conditions that require processing of large numbers of samples in which the individual samples contain only a very small minority of objects of interest; and how to deal with exceptionally small amounts of RNA within the sorted samples.

Bayesian hierarchical model for estimating gene expression intensity using multiple scanned microarrays

We propose a method for improving the quality of signal from DNA microarrays by using several scans at varying scanner sensitivities. A Bayesian latent intensity model is introduced for the analysis of such data. The method improves the accuracy at which expressions can be measured in all ranges and extends the dynamic range of measured gene expression at the high end. Our method is generic and can be applied to data from any organism, for imaging with any scanner that allows varying the laser power, and for extraction with any image analysis software. Results from a self-self hybridization data set illustrate an improved precision in the estimation of the expression of genes compared to what can be achieved by applying standard methods and using only a single scan.

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.

Transcriptional profiles underlying parent-of-origin effects in seeds of Arabidopsis thaliana

BACKGROUND

Crossing plants of the same species but different ploidies can have dramatic effects on seed growth, but little is known about the alterations to transcriptional programmes responsible for this. Parental genomic imbalance particularly affects proliferation of the endosperm, with an increased ratio of paternally to maternally contributed genomes ('paternal excess') associated with overproliferation, while maternal excess inhibits endosperm growth. One interpretation is that interploidy crosses disrupt the balance in the seed of active copies of parentally imprinted genes. This is supported by the observation that mutations in imprinted FIS-class genes of Arabidopsis thaliana share many features of the paternal excess phenotype. Here we investigated gene expression underlying parent-of-origin effects in Arabidopsis through transcriptional profiling of siliques generated by interploidy crosses and FIS-class mutants.

RESULTS

We found that fertilized fis1 mutant seeds have similar profiles to seeds with paternal excess, showing that the shared phenotypes are underpinned by similar patterns of gene expression. We identified genes strongly associated with enhanced or inhibited seed growth; this provided many candidates for further investigation including MADS-box transcription factors, cell cycle genes, and genes involved in hormone pathways.

CONCLUSIONS

The work presented here is a step towards understanding the effects on seed development of the related phenomena of parental genome balance and imprinting.

Effects of scanning sensitivity and multiple scan algorithms on microarray data quality

Background

Maximizing the utility of DNA microarray data requires optimization of data acquisition through selection of an appropriate scanner setting. To increase the amount of useable data, several approaches have been proposed that incorporate multiple scans at different sensitivities to reduce the quantification error and to minimize effects of saturation. However, no direct comparison of their efficacy has been made. In the present study we compared individual scans at low, medium and high sensitivity with three methods for combining data from multiple scans (either 2-scan or 3-scan cases) using an actual dataset comprising 40 technical replicates of a reference RNA standard.

Results

Of the individual scans, the low scan exhibited the lowest background signal, the highest signal-to-noise ratio, and equivalent reproducibility to the medium and high scans. Most multiple scan approaches increased the range of probe intensities compared to the individual scans, but did not increase the dynamic range (the proportion of useable data). Approaches displayed striking differences in the background signal and signal-to-noise ratio. However, increased probe intensity range and improved signal-to-noise ratios did not necessarily correlate with improved reproducibility. Importantly, for one multiple scan method that combined 3 scans, reproducibility was significantly improved relative to individual scans and all other multiple scan approaches. The same method using 2 scans yielded significantly lower reproducibility, attributable to a lack-of-fit of the statistical model.

Conclusions

Our data indicate that implementation of a suitable multiple scan approach can improve reproducibility, but that model validation is critical to ensure accurate estimates of probe intensity.

Direct calibration of PICKY-designed microarrays

Background

Few microarrays have been quantitatively calibrated to identify optimal hybridization conditions because it is difficult to precisely determine the hybridization characteristics of a microarray using biologically variable cDNA samples.

Results

Using synthesized samples with known concentrations of specific oligonucleotides, a series of microarray experiments was conducted to evaluate microarrays designed by PICKY, an oligo microarray design software tool, and to test a direct microarray calibration method based on the PICKY-predicted, thermodynamically closest nontarget information. The complete set of microarray experiment results is archived in the GEO database with series accession number GSE14717. Additional data files and Perl programs described in this paper can be obtained from the website under the PICKY Download area.

Conclusion

PICKY-designed microarray probes are highly reliable over a wide range of hybridization temperatures and sample concentrations. The microarray calibration method reported here allows researchers to experimentally optimize their hybridization conditions. Because this method is straightforward, uses existing microarrays and relatively inexpensive synthesized samples, it can be used by any lab that uses microarrays designed by PICKY. In addition, other microarrays can be reanalyzed by PICKY to obtain the thermodynamically closest nontarget information for calibration.

Repeated Measurements on Distinct Scales With Censoring-A Bayesian Approach Applied to Microarray Analysis of Maize

We analyze data collected in a somatic embryogenesis experiment carried out on Zea mays at Iowa State University. The main objective of the study was to identify the set of genes in maize that actively participate in embryo development. Embryo tissue was sampled and analyzed at various time periods and under different mediums and light conditions. As is the case in many microarray experiments, the operator scanned each slide multiple times to find the slide-specific 'optimal' laser and sensor settings. The multiple readings of each slide are repeated measurements on different scales with differing censoring; they cannot be considered to be replicate measurements in the traditional sense. Yet it has been shown that the choice of reading can have an impact on genetic inference. We propose a hierarchical modeling approach to estimating gene expression that combines all available readings on each spot and accounts for censoring in the observed values. We assess the statistical properties of the proposed expression estimates using a simulation experiment. As expected, combining all available scans using an approach with good statistical properties results in expression estimates with noticeably lower bias and root mean squared error relative to other approaches that have been proposed in the literature. Inferences drawn from the somatic embryogenesis experiment, which motivated this work changed drastically when data were analyzed using the standard approaches or using the methodology we propose.

Floret-specific differences in gene expression and support for the hypothesis that tapetal degeneration of Zea mays L. occurs via programmed cell death

The maize (Zea mays) spikelet consists of two florets, each of which contains three developmentally synchronized anthers. Morphologically, the anthers in the upper and lower florets proceed through apparently similar developmental programs. To test for global differences in gene expression and to identify genes that are coordinately regulated during maize anther development, RNA samples isolated from upper and lower floret anthers at six developmental stages were hybridized to cDNA microarrays. Approximately 9% of the tested genes exhibited statistically significant differences in expression between anthers in the upper and lower florets. This finding indicates that several basic biological processes are differentially regulated between upper and lower floret anthers, including metabolism, protein synthesis and signal transduction. Genes that are coordinately regulated across anther development were identified via cluster analysis. Analysis of these results identified stage-specific, early in development, late in development and bi-phasic expression profiles. Quantitative RT-PCR analysis revealed that four genes whose homologs in other plant species are involved in programmed cell death are up-regulated just prior to the time the tapetum begins to visibly degenerate (i.e., the mid-microspore stage). This finding supports the hypothesis that developmentally normal tapetal degeneration occurs via programmed cell death.

Characterisation and correction of signal fluctuations in successive acquisitions of microarray images

Background

There are many sources of variation in dual labelled microarray experiments, including data acquisition and image processing. The final interpretation of experiments strongly relies on the accuracy of the measurement of the signal intensity. For low intensity spots in particular, accurately estimating gene expression variations remains a challenge as signal measurement is, in this case, highly subject to fluctuations.

Results

To evaluate the fluctuations in the fluorescence intensities of spots, we used series of successive scans, at the same settings, of whole genome arrays. We measured the decrease in fluorescence and we evaluated the influence of different parameters (PMT gain, resolution and chemistry of the slide) on the signal variability, at the level of the array as a whole and by intensity interval. Moreover, we assessed the effect of averaging scans on the fluctuations. We found that the extent of photo-bleaching was low and we established that 1) the fluorescence fluctuation is linked to the resolution e.g. it depends on the number of pixels in the spot 2) the fluorescence fluctuation increases as the scanner voltage increases and, moreover, is higher for the red as opposed to the green fluorescence which can introduce bias in the analysis 3) the signal variability is linked to the intensity level, it is higher for low intensities 4) the heterogeneity of the spots and the variability of the signal and the intensity ratios decrease when two or three scans are averaged.

Conclusion

Protocols consisting of two scans, one at low and one at high PMT gains, or multiple scans (ten scans) can introduce bias or be difficult to implement. We found that averaging two, or at most three, acquisitions of microarrays scanned at moderate photomultiplier settings (PMT gain) is sufficient to significantly improve the accuracy (quality) of the data and particularly those for spots having low intensities and we propose this as a general approach. For averaging and precise image alignment at sub-pixel levels we have made a program freely available on our web-site to facilitate implementation of this approach.

Reconstruction and functional analysis of altered molecular pathways in human atherosclerotic arteries

Background

Atherosclerosis affects aorta, coronary, carotid, and iliac arteries most frequently than any other body vessel. There may be common molecular pathways sustaining this process. Plaque presence and diffusion is revealed by circulating factors that can mediate systemic reaction leading to plaque rupture and thrombosis.

Results

We used DNA microarrays and meta-analysis to study how the presence of calcified plaque modifies human coronary and carotid gene expression. We identified a series of potential human atherogenic genes that are integrated in functional networks involved in atherosclerosis. Caveolae and JAK/STAT pathways, and S100A9/S100A8 interacting proteins are certainly involved in the development of vascular disease. We found that the system of caveolae is directly connected with genes that respond to hormone receptors, and indirectly with the apoptosis pathway.

Cytokines, chemokines and growth factors released in the blood flux were investigated in parallel. High levels of RANTES, IL-1ra, MIP-1alpha, MIP-1beta, IL-2, IL-4, IL-5, IL-6, IL-7, IL-17, PDGF-BB, VEGF and IFN-gamma were found in plasma of atherosclerotic patients and might also be integrated in the molecular networks underlying atherosclerotic modifications of these vessels.

Conclusion

The pattern of cytokine and S100A9/S100A8 up-regulation characterizes atherosclerosis as a proinflammatory disorder. Activation of the JAK/STAT pathway is confirmed by the up-regulation of IL-6, STAT1, ISGF3G and IL10RA genes in coronary and carotid plaques. The functional network constructed in our research is an evidence of the central role of STAT protein and the caveolae system to contribute to preserve the plaque. Moreover, Cav-1 is involved in SMC differentiation and dyslipidemia confirming the importance of lipid homeostasis in the atherosclerotic phenotype.

Microarray analysis of vegetative phase change in maize

Vegetative phase change is the developmental transition from the juvenile phase to the adult phase in which a plant becomes competent for sexual reproduction. The gain of ability to flower is often accompanied by changes in patterns of differentiation in newly forming vegetative organs. In maize, juvenile leaves differ from adult leaves in morphology, anatomy and cell wall composition. Whereas the normal sequence of juvenile followed by adult is repeated with every sexual generation, this sequence can be altered in maize by the isolation and culture of the shoot apex from an adult phase plant: an 'adult' meristem so treated reverts to forming juvenile vegetative organs. To begin to unravel the as-yet poorly understood molecular mechanisms underlying phase change in maize, we compared gene expression in two juvenile sample types, leaf 4 and culture-derived leaves 3 or 4, with an adult sample type (leaf 9) using cDNA microarrays. All samples were leaf primordia at plastochron 6. A gene was scored as 'phase induced' if it was up- or downregulated in both juvenile sample types, compared with the adult sample type, with at least a twofold change in gene expression at a P-value of < or =0.005. Some 221 expressed sequence tags (ESTs) were upregulated in juveniles, and 28 ESTs were upregulated in adults. The largest class of juvenile-induced genes was comprised of those involved in photosynthesis, suggesting that maize plants are primed for energy production early in vegetative growth by the developmental induction of photosynthetic genes.

Global gene expression analysis of the shoot apical meristem of maize (Zea mays L.)

All above-ground plant organs are derived from shoot apical meristems (SAMs). Global analyses of gene expression were conducted on maize (Zea mays L.) SAMs to identify genes preferentially expressed in the SAM. The SAMs were collected from 14-day-old B73 seedlings via laser capture microdissection (LCM). The RNA samples extracted from LCM-collected SAMs and from seedlings were hybridized to microarrays spotted with 37 660 maize cDNAs. Approximately 30% (10 816) of these cDNAs were prepared as part of this study from manually dissected B73 maize apices. Over 5000 expressed sequence tags (ESTs) (about 13% of the total) were differentially expressed (P < 0.0001) between SAMs and seedlings. Of these, 2783 and 2248 ESTs were up- and down-regulated in the SAM, respectively. The expression in the SAM of several of the differentially expressed ESTs was validated via quantitative RT-PCR and/or in situ hybridization. The up-regulated ESTs included many regulatory genes including transcription factors, chromatin remodeling factors and components of the gene-silencing machinery, as well as about 900 genes with unknown functions. Surprisingly, transcripts that hybridized to 62 retrotransposon-related cDNAs were also substantially up-regulated in the SAM. Complementary DNAs derived from the LCM-collected SAMs were sequenced to identify additional genes that are expressed in the SAM. This generated around 550 000 ESTs (454-SAM ESTs) from two genotypes. Consistent with the microarray results, approximately 14% of the 454-SAM ESTs from B73 were retrotransposon-related. Possible roles of genes that are preferentially expressed in the SAM are discussed.

Signal stability of Cy3 and Cy5 on antibody microarrays

Background

The antibody microarray technique is a newly emerging proteomics tool for differential protein expression analyses that uses fluorescent dyes Cy 3 and Cy 5. Environmental factors, such as light exposure, can affect the signal intensity of fluorescent dyes on microarray slides thus, it is logical to scan microarray slides immediately after the final wash and drying processes. However, no research data are available concerning time-dependent changes of fluorescent signals on antibody microarray slides to this date. In the present study, microarray slides were preserved at -20°C after regular microarray experiments and were rescanned at day 10, 20 and 30 to evaluate change in signal intensity.

Results

Fluorescent intensities of microarray spots were detected using a confocal laser scanner after the experiment at day 0, and re-examined at day 10, 20 and 30, respectively. Fluorescent intensities of rescanned microarray spots did not show significant changes when compared with those scanned immediately after standard microarray experiments.

Conclusion

Microarray slides can be preserved and rescanned multiple times using a confocal laser scanner over a period of days or weeks.