Putting microarrays in a context: integrated analysis of diverse biological data

In recent years, multiple types of high-throughput functional genomic data that facilitate rapid functional annotation of sequenced genomes have become available. Gene expression microarrays are the most commonly available source of such data. However, genomic data often sacrifice specificity for scale, yielding very large quantities of relatively lower-quality data than traditional experimental methods. Thus sophisticated analysis methods are necessary to make accurate functional interpretation of these large-scale data sets. This review presents an overview of recently developed methods that integrate the analysis of microarray data with sequence, interaction, localisation and literature data, and further outlines current challenges in the field. The focus of this review is on the use of such methods for gene function prediction, understanding of protein regulation and modelling of biological networks.     

Bayesian robust inference for differential gene expression in microarrays with multiple samples

We consider the problem of identifying differentially expressed genes under different conditions using gene expression microarrays. Because of the many steps involved in the experimental process, from hybridization to image analysis, cDNA microarray data often contain outliers. For example, an outlying data value could occur because of scratches or dust on the surface, imperfections in the glass, or imperfections in the array production. We develop a robust Bayesian hierarchical model for testing for differential expression. Errors are modeled explicitly using a t-distribution, which accounts for outliers. The model includes an exchangeable prior for the variances, which allows different variances for the genes but still shrinks extreme empirical variances. Our model can be used for testing for differentially expressed genes among multiple samples, and it can distinguish between the different possible patterns of differential expression when there are three or more samples. Parameter estimation is carried out using a novel version of Markov chain Monte Carlo that is appropriate when the model puts mass on subspaces of the full parameter space. The method is illustrated using two publicly available gene expression data sets. We compare our method to six other baseline and commonly used techniques, namely the t-test, the Bonferroni-adjusted t-test, significance analysis of microarrays (SAM), Efron's empirical Bayes, and EBarrays in both its lognormal-normal and gamma-gamma forms. In an experiment with HIV data, our method performed better than these alternatives, on the basis of between-replicate agreement and disagreement.     

A novel magnetic resonance-based method to measure gene expression in living cells

In unicellular and multicellular eukaryotes, elaborate gene regulatory mechanisms facilitate a broad range of biological processes from cell division to morphological differentiation. In order to fully understand the gene regulatory networks involved in these biological processes, the spatial and temporal patterns of expression of many thousands of genes will need to be determined in real time in living organisms. Currently available techniques are not sufficient to achieve this goal; however, novel methods based on magnetic resonance (MR) imaging may be particularly useful for sensitive detection of gene expression in opaque tissues. This report describes a novel reporter gene system that monitors gene expression dynamically and quantitatively, in yeast cells, by measuring the accumulation of inorganic polyphosphate (polyP) using MR spectroscopy (MRS) or MR spectroscopic imaging (MRI). Because this system is completely non-invasive and does not require exogenous substrates, it is a powerful tool for studying gene expression in multicellular organisms, as well.     

Development of a capillary isoelectric focusing immunoassay to measure DJ-1 isoforms in biological samples

We report on the development of a novel assay protocol for the separation and detection of charge isoforms of DJ-1 in biological samples by automated capillary isoelectric focusing followed by immunological detection. DJ-1 (PARK7) is considered as a biomarker candidate for Parkinson’s disease and may potentially support the differentiation of clinical subtypes of the disease. The new method allows for separation and subsequent relative quantitative comparison of different isoforms of DJ-1 in biological samples. The assay was successfully applied to the analysis of DJ-1 isoform patterns in brains from mice subjected to normal or high-fat diet and revealed statistically significant group differences. Furthermore, in a pooled and concentrated sample of human cerebrospinal fluid that was depleted of albumin and immunoglobulin G, four different charge variants of DJ-1 could be detected. Taken together, the capillary isoelectric focusing immunoassay for DJ-1 represents a promising tool that may ultimately serve in clinical biomarker studies.     

Using DNA microarrays to study gene expression in closely related species

MOTIVATION: Comparisons of gene expression levels within and between species have become a central tool in the study of the genetic basis for phenotypic variation, as well as in the study of the evolution of gene regulation. DNA microarrays are a key technology that enables these studies. Currently, however, microarrays are only available for a small number of species. Thus, in order to study gene expression levels in species for which microarrays are not available, researchers face three sets of choices: (i) use a microarray designed for another species, but only compare gene expression levels within species, (ii) construct a new microarray for every species whose gene expression profiles will be compared or (iii) build a multi-species microarray with probes from each species of interest. Here, we use data collected using a multi-primate cDNA array to evaluate the reliability of each approach. RESULTS: We find that, for inter-species comparisons, estimates of expression differences based on multi-species microarrays are more accurate than those based on multiple species-specific arrays. We also demonstrate that within-species expression differences can be estimated using a microarray for a closely related species, without discernible loss of information. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Exploiting microarrays to reveal differential gene expression in the nervous system

Microarrays have been used in a wide variety of experimental systems, but realizing their full potential is contingent on sophisticated and rigorous experimental design and data analysis. This article highlights what is needed to get the most out of microarrays in terms of accurately and effectively revealing differential gene expression and regulation in the nervous system.     

Resolution of large and small differences in gene expression using models for the Bayesian analysis of gene expression levels and spotted DNA microarrays

Background  

The detection of small yet statistically significant differences in gene expression in spotted DNA microarray studies is an ongoing challenge. Meeting this challenge requires careful examination of the performance of a range of statistical models, as well as empirical examination of the effect of replication on the power to resolve these differences.     

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

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

Genome scans and gene expression microarrays converge to identify gene regulatory loci relevant in schizophrenia

Multiple linkage regions have been reported in schizophrenia, and some appear to harbor susceptibility genes that are differentially expressed in postmortem brain tissue derived from unrelated individuals. We combined traditional genome-wide linkage analysis in a multiplex family with lymphocytic genome-wide expression analysis. A genome scan suggested linkage to a chromosome 4q marker (D4S1530, LOD 2.17, θ=0) using a dominant model. Haplotype analysis using flanking microsatellite markers delineated a 14 Mb region that cosegregated with all those affected. Subsequent genome-wide scan with SNP genotypes supported the evidence of linkage to 4q33–35.1 (LOD=2.39) using a dominant model. Genome-wide microarray analysis of five affected and five unaffected family members identified two differentially expressed genes within the haplotype AGA and GALNT7 (aspartylglucosaminidase and UDP-N-acetyl-alpha-D-galactosamine: polypeptide N-acetylgalactosaminyltransferase 7) with nominal significance; however, these genes did not remain significant following analysis of covariance. We carried out genome-wide linkage analyses between the quantitative expression phenotype and genetic markers. AGA expression levels showed suggestive linkage to multiple markers in the haplotype (maximum LOD=2.37) but to no other genomic region. GALNT7 expression levels showed linkage to regulatory loci at 4q28.1 (maximum LOD=3.15) and in the haplotype region at 4q33–35.1 (maximum LOD=2.37). ADH1B (alcohol dehydrogenase IB) was linked to loci at 4q21–q23 (maximum LOD=3.08) and haplotype region at 4q33–35.1 (maximum LOD=2.27). Seven differentially expressed genes were validated with RT-PCR. Three genes in the 4q33–35.1 haplotype region were also differentially expressed in schizophrenia in postmortem dorsolateral prefrontal cortex: AGA, HMGB2, and SCRG1. These results indicate that combining differential gene expression with linkage analysis may help in identifying candidate genes and potential regulatory sites. Moreover, they also replicate recent findings of complex trans- and cis- regulation of genes.     

A high-throughput method to measure the sensitivity of yeast cells to genotoxic agents in liquid cultures

The sensitivity of yeast Saccharomyces cerevisiae to DNA damaging agents is better represented when cells are grown in liquid media than on solid plates. However, systematic assessment of several strains that are grown in different conditions is a cumbersome undertaking. We report an assay to determine cell growth based on automatic measurements of optical densities of very small (100 microl) liquid cell cultures. Furthermore, an algorithm was elaborated to analyze large data files obtained from the cell growth curves, which are described by the growth rate--that starts at zero and accelerates to the maximal rate (mu(m))--and by the lag time (lambda). Cell dilution spot test for colony formation on solid media and the growth curve assay were used in parallel to analyze the phenotypes of cells after treatments with three different classes of DNA damaging agents (methyl methanesulfonate, bleomycin, and ultraviolet light). In these experiments the survival of the WT (wild type) and a number of DNA repair-deficient strains were compared. The results show that only the cell growth curve assay could uncover subtle phenotypes when WT cells, or mutant strains that are only weakly affected in DNA repair proficiency, were treated with low doses of cytotoxic compounds. The growth curve assay was also applied to establish whether histone acetyltransferases and deacetylases affect the resistance of yeast cells to UV irradiation. Out of 20 strains tested the sir2delta and rpd3delta cells were found to be more resistant than the WT, while gcn5delta and spt10delta cells were found to be more sensitive. This new protocol is sensitive, provides quantifiable data, offers increased screening capability and speed compared to the colony formation test.     

Gene expression profiling of mouse postnatal cerebellar development using oligonucleotide microarrays designed to detect differences in glycoconjugate expression

Differences in gene expression patterns between adult and postnatal day 7 (P7) mouse cerebellum, at the peak of granule neuron migration, were analyzed by hybridization to the GLYCOv2 glycogene array. This custom designed oligonucleotide array focuses on glycosyl transferases, carbohydrate-binding proteins, proteoglycans and related genes, and 173 genes were identified as being differentially expressed with statistical confidence. Expression levels for 11 of these genes were compared by RT-PCR, and their differential expression between P7 and adult cerebellum confirmed. Within the group of genes showing differential expression, the sialyltransferases (SiaTs) and GalNAc-Ts that were elevated at P7 prefer glycoprotein substrates, whilst the SiaTs and GalNAc-Ts that were elevated in the adult preferentially modify glycolipids, consistent with a role for gangliosides in maintaining neuronal function in the adult. Also within this group, three proteoglycans--versican, bamacan and glypican-2--were elevated at P7, along with growth factor midkine, which is known to bind to multiple types of proteoglycans, and fibroblast growth factor receptor 1, whose activity is known to be influenced by heparan sulfate proteoglycans. Two sulfotransferases that can modify the extent of proteoglycan sulfation were also differentially regulated, and may modify the interaction of a subset of proteoglycans with their binding partners during cerebellar development. Bamacan, glypican-2 and midkine were shown to be expressed in different cell types, and their roles in cerebellar development during granule neuron migration and maturation are discussed.     

Simple method to measure power density entering a plane biological sample at millimeter wavelengths

A simple method for measuring microwave power density is described. It is applicable to situations where exposure of samples in the near field of a horn is necessary. A transmitted power method is used to calibrate the power density entering the surface of the sample. Once the calibration is available, the power density is known in terms of the incident and reflected powers within the waveguide. The calibration has been carried out for liquid samples in a quartz cell. Formulas for calculating specific absorption rate (SAR) are derived in terms of the power density and the complex dielectric constant of the sample. An error analysis is also given.     

A high-performance liquid chromatographic method to measure sphingosine 1-phosphate and related compounds from sphingosine kinase assays and other biological samples

Sphingosine 1-phosphate is an intermediate of sphingosine catabolism as well as a potent signaling compound. Conditions were established for the extraction and analysis of sphingosine 1-phosphate and other sphingoid base 1-phosphates from in vitro sphingosine kinase assays and other biological samples. The sphingoid base 1-phosphates were extracted in high yield (85%) using small C-18 reverse-phase columns (LiChroprep RP-18). After the extracts were treated with 0.1 N KOH to remove glycerolipids, the sphingoid base 1-phosphates were converted to fluorescent o-phthalaldehyde derivatives that were separated by HPLC using C-18 columns with a mobile phase of methanol:10 mM potassium phosphate (pH 7.2):1 M tetrabutylammonium dihydrogen phosphate (in water) (83:16:1, v/v/v). The o-phthalaldehyde derivative of sphingosine 1-phosphate was reasonably stable (t(1/2) > or = 18 h) when EDTA was present and could be detected in picomole amounts. The HPLC retention time of the sphingoid base 1-phosphates could be shifted by adjusting the mobile phase to pH 5.5, which is useful in separating overlapping compounds (such as sphingosine 1-phosphate and 4-D-hydroxysphinganine) and in confirming the identity of sphingoid base 1-phosphates in biological samples. The extraction procedure and HPLC method facilitated assays of sphingosine kinase with different sphingoid bases as substrates and/or inhibitors and enabled the quantitation of sphingoid base 1-phosphates in human plasma, serum, and platelets as well as in strains of Saccharomyces cerevisae with mutations in sphingolipid metabolism.     

Establishment of a novel gene expression method,BICES (biomass-inducible chromosome-based expression system), and its application to the production of 2,3-butanediol and acetoin

In this study, we describe a novel method for producing valuable chemicals from glucose and xylose in Escherichia coli. The notable features in our method are avoidance of plasmids and expensive inducers for foreign gene expression to reduce production costs; foreign genes are knocked into the chromosome, and their expression is induced with xylose that is present in most biomass feedstock. As loci for the gene knock-in, lacZYA and some pseudogenes are chosen to minimize unexpected effects of the knock-in on cell physiology. The promoter of xylF is inducible with xylose and is combined with the T7 RNA polymerase–T7 promoter system to ensure strong gene expression. This expression system was named BICES (biomass-inducible chromosome-based expression system). As examples of BICES application, 2,3-butanediol and acetoin were successfully produced from glucose and xylose, and the maximal concentrations reached 54 g L⁻¹ [99.6% in (R,S)-form] and 31 g L⁻¹, respectively. 2,3-Butanediol and acetoin are industrially important chemicals that are, at present, produced primarily through petrochemical processes. To demonstrate usability of BICES in practical situations, we produced these chemicals from a saccharified cedar solution. From these results, we can conclude that BICES is suitable for practical production of valuable chemicals from biomass.