Meta-analysis of genome-wide association data identifies a risk locus for major mood disorders on 3p21.1.

The major mood disorders, which include bipolar disorder and major depressive disorder (MDD), are considered heritable traits, although previous genetic association studies have had limited success in robustly identifying risk loci. We performed a meta-analysis of five case-control cohorts for major mood disorder, including over 13,600 individuals genotyped on high-density SNP arrays. We identified SNPs at 3p21.1 associated with major mood disorders (rs2251219, P = 3.63 x 10(-8); odds ratio = 0.87; 95% confidence interval, 0.83-0.92), with supportive evidence for association observed in two out of three independent replication cohorts. These results provide an example of a shared genetic susceptibility locus for bipolar disorder and MDD.

Changes associated with laboratory rearing in antennal sensilla patterns of Triatoma infestans, Rhodnius prolixus, and Rhodnius pallescens (Hemiptera, Reduviidae, Triatominae)

We examined changes in the array of antennal sensilla of three species of Triatominae (Triatoma infestans, Rhodnius prolixus, and R. pallescens) following their establishment for different periods in laboratory culture. In each case, the laboratory colonies were compared with conspecific samples taken directly from the field, by quantitative analysis of the sensilla arrays on the three distal segments of the antenna in terms of the densities of three types of chemoreceptors (basiconics and thick and thin walled trichoids) and one type of mechanoreceptor (bristles). Sensilla densities were compared by ANOVA or non-parametric tests, and by multivariate discriminant analysis. Strains of the same species reared in different laboratories showed significant differences in their sensilla arrays, especially when compared to field-collected material from the same geographic origin. A Bolivian strain of T. infestans reared in the laboratory for 15 years and fed at monthly intervals, showed greatest differences from its conspecific wild forms, especially in terms of reductions in the number of chemoreceptors. By contrast, an Argentine strain of T. infestans reared for 25 years in the laboratory and fed weekly, showed a relative increase in the density of mechanoreceptors. A Colombian strain of R. prolixus reared for 20 years and fed weekly or fortnightly, showed only modest differences in the sensilla array when compared to its wild populations from the same area. However, a Colombian strain of R. pallescens reared for 12 years and fed fortnightly, did show highly significant reductions in one form of chemoreceptor compared to its conspecific wild populations. For all populations, multivariate analysis clearly discriminated between laboratory and field collected specimens, suggesting that artificial rearing can lead to modifications in the sensory array. This not only supports the idea of morphological plasticity in these species, but also suggests caution in the use of long-established laboratory material for experimental studies designed to extrapolate the natural behaviour and physiology of these species.

Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

Quantifying network properties in multi-electrode recordings: spatiotemporal characterization and inter-trial variation of evoked gamma oscillations in mouse somatosensory cortex in vitro.

Linking the structural connectivity of brain circuits to their cooperative dynamics and emergent functions is a central aim of neuroscience research. Graph theory has recently been applied to study the structure-function relationship of networks, where dynamical similarity of different nodes has been turned into a "static" functional connection. However, the capability of the brain to adapt, learn and process external stimuli requires a constant dynamical functional rewiring between circuitries and cell assemblies. Hence, we must capture the changes of network functional connectivity over time. Multi-electrode array data present a unique challenge within this framework. We study the dynamics of gamma oscillations in acute slices of the somatosensory cortex from juvenile mice recorded by planar multi-electrode arrays. Bursts of gamma oscillatory activity lasting a few hundred milliseconds could be initiated only by brief trains of electrical stimulations applied at the deepest cortical layers and simultaneously delivered at multiple locations. Local field potentials were used to study the spatio-temporal properties and the instantaneous synchronization profile of the gamma oscillatory activity, combined with current source density (CSD) analysis. Pair-wise differences in the oscillation phase were used to determine the presence of instantaneous synchronization between the different sites of the circuitry during the oscillatory period. Despite variation in the duration of the oscillatory response over successive trials, they showed a constant average power, suggesting that the rate of expenditure of energy during the gamma bursts is consistent across repeated stimulations. Within each gamma burst, the functional connectivity map reflected the columnar organization of the neocortex. Over successive trials, an apparently random rearrangement of the functional connectivity was observed, with a more stable columnar than horizontal organization. This work reveals new features of evoked gamma oscillations in developing cortex.

Reverse transcription quantitative real-time polymerase chain reaction reference genes in the spared nerve injury model of neuropathic pain : validation and literature search

La douleur neuropathique est définie comme une douleur causée par une lésion du système nerveux somato-sensoriel. Elle se caractérise par des douleurs exagérées, spontanées, ou déclenchées par des stimuli normalement non douloureux (allodynie) ou douloureux (hyperalgésie). Bien qu'elle concerne 7% de la population, ses mécanismes biologiques ne sont pas encore élucidés. L'étude des variations d'expressions géniques dans les tissus-clés des voies sensorielles (notamment le ganglion spinal et la corne dorsale de la moelle épinière) à différents moments après une lésion nerveuse périphérique permettrait de mettre en évidence de nouvelles cibles thérapeutiques. Elles se détectent de manière sensible par reverse transcription quantitative real-time polymerase chain reaction (RT- qPCR). Pour garantir des résultats fiables, des guidelines ont récemment recommandé la validation des gènes de référence utilisés pour la normalisation des données ("Minimum information for publication of quantitative real-time PCR experiments", Bustin et al 2009). Après recherche dans la littérature des gènes de référence fréquemment utilisés dans notre modèle de douleur neuropathique périphérique SNI (spared nerve injury) et dans le tissu nerveux en général, nous avons établi une liste de potentiels bons candidats: Actin beta (Actb), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal proteins 18S (18S), L13a (RPL13a) et L29 (RPL29), hypoxanthine phosphoribosyltransferase 1 (HPRT1) et hydroxymethyl-bilane synthase (HMBS). Nous avons évalué la stabilité d'expression de ces gènes dans le ganglion spinal et dans la corne dorsale à différents moments après la lésion nerveuse (SNI) en calculant des coefficients de variation et utilisant l'algorithme geNorm qui compare les niveaux d'expression entre les différents candidats et détermine la paire de gènes restante la plus stable. Il a aussi été possible de classer les gènes selon leur stabilité et d'identifier le nombre de gènes nécessaires pour une normalisation la plus précise. Les gènes les plus cités comme référence dans le modèle SNI ont été GAPDH, HMBS, Actb, HPRT1 et 18S. Seuls HPRT1 and 18S ont été précédemment validés dans des arrays de RT-qPCR. Dans notre étude, tous les gènes testés dans le ganglion spinal et dans la corne dorsale satisfont au critère de stabilité exprimé par une M-value inférieure à 1. Par contre avec un coefficient de variation (CV) supérieur à 50% dans le ganglion spinal, 18S ne peut être retenu. La paire de gènes la plus stable dans le ganglion spinal est HPRT1 et Actb et dans la corne dorsale il s'agit de RPL29 et RPL13a. L'utilisation de 2 gènes de référence stables suffit pour une normalisation fiable. Nous avons donc classé et validé Actb, RPL29, RPL13a, HMBS, GAPDH, HPRT1 et 18S comme gènes de référence utilisables dans la corne dorsale pour le modèle SNI chez le rat. Dans le ganglion spinal 18S n'a pas rempli nos critères. Nous avons aussi déterminé que la combinaison de deux gènes de référence stables suffit pour une normalisation précise. Les variations d'expression génique de potentiels gènes d'intérêts dans des conditions expérimentales identiques (SNI, tissu et timepoints post SNI) vont pouvoir se mesurer sur la base d'une normalisation fiable. Non seulement il sera possible d'identifier des régulations potentiellement importantes dans la genèse de la douleur neuropathique mais aussi d'observer les différents phénotypes évoluant au cours du temps après lésion nerveuse.

Impact of normalization on miRNA microarray expression profiling.

Profiling miRNA levels in cells with miRNA microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. We have developed a method to select nonchanging miRNAs (invariants) and use them to compute linear regression normalization coefficients or variance stabilizing normalization (VSN) parameters. We compared the invariants normalization to normalization by scaling, quantile, and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only a few miRNAs are affected (by p53 overexpression in squamous carcinoma cells versus control). All normalization methods performed better than no normalization. Normalization procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other data sets including those from one color miRNA microarray platforms, focused gene expression arrays, and gene expression analysis using quantitative PCR.

Molecular risk assessment of BIG 1-98 participants by expression profiling using RNA from archival tissue.

Background: The purpose of the work reported here is to test reliable molecular profiles using routinely processed formalin-fixed paraffin-embedded (FFPE) tissues from participants of the clinical trial BIG 1-98 with a median follow-up of 60 months. Methods: RNA from fresh frozen (FF) and FFPE tumor samples of 82 patients were used for quality control, and independent FFPE tissues of 342 postmenopausal participants of BIG 1-98 with ER-positive cancer were analyzed by measuring prospectively selected genes and computing scores representing the functions of the estrogen receptor (eight genes, ER_8), the progesterone receptor (five genes, PGR_5), Her2 (two genes, HER2_2), and proliferation (ten genes, PRO_10) by quantitative reverse transcription PCR (qRT-PCR) on TaqMan Low Density Arrays. Molecular scores were computed for each category and ER_8, PGR_5, HER2_2, and PRO_10 scores were combined into a RISK_25 score. Results: Pearson correlation coefficients between FF- and FFPE-derived scores were at least 0.94 and high concordance was observed between molecular scores and immunohistochemical data. The HER2_2, PGR_ 5, PRO_10 and RISK_25 scores were significant predictors of disease free-survival (DFS) in univariate Cox proportional hazard regression. PRO_10 and RISK_25 scores predicted DFS in patients with histological grade II breast cancer and in lymph node positive disease. The PRO_10 and PGR_ 5 scores were independent predictors of DFS in multivariate Cox regression models incorporating clinical risk indicators; PRO_10 outperformed Ki-67 labeling index in multivariate Cox proportional hazard analyses. Conclusions: Scores representing the endocrine responsiveness and proliferation status of breast cancers were developed from gene expression analyses based on RNA derived from FFPE tissues. The validation of the molecular scores with tumor samples of participants of the BIG 1-98 trial demonstrates that such scores can serve as independent prognostic factors to estimate disease free survival (DFS) in postmenopausal patients with estrogen receptor positive breast cancer.

Emergence of dhfrXVb and blaCARB-4 gene cassettes in class 1 integrons from clinical Pseudomonas aeruginosa isolated in Amazon region

Integrons play a role in horizontal acquisition and expression of genes, as well as gene reservoir, contributing for the resistance phenotype, particularly relevant to bacteria of clinical importance. We aimed to determine the composition and the organization of the class 1 integron variable region present in Pseudomonas aeruginosa clinical isolates from Brazil. Strains carrying class 1 integrons were resistant to the majority of antibiotics tested, except to imipenem and ceftazidime. Sequence analysis of the integron variable region revealed the presence of the blaCARB-4 gene into two distinct cassette arrays: aacA4-dhfrXVb-blaCARB-4 and aadB-aacA4-blaCARB-4 . dhfrXVb gene cassette, which is rare in Brazil and in P. aeruginosa species, was found in one isolate. PFGE analysis showed the spread of blaCARB-4 among P. aeruginosa clones. The occurrence of blaCARB-4 and dhfrXVb in Brazil may contribute for developing resistance to clinically important antibiotics, and shows a diversified scenarium of these elements occurring in Amazon clinical settings, where no study about integron dinamycs was performed to date.

Host and invader impact of transfer of the clc genomic island into Pseudomonas aeruginosa PAO1

Genomic islands, large potentially mobile regions of bacterial chromosomes, are a major contributor to bacteria evolution. Here, we investigated the fitness cost and phenotypic differences between the bacterium Pseudomonas aeruginosa PAO1 and a derivative carrying one integrated copy of the clc element, a 103-kb genomic island [and integrative and conjugative element (ICE)] originating in Pseudomonas sp. strain B13 and a close relative of genomic islands found in clinical and environmental isolates of P. aeruginosa. By using a combination of whole genome transcriptome profiling, phenotypic arrays, competition experiments, and biofilm formation studies, only few differences became apparent, such as reduced biofilm growth and fourfold stationary phase repression of genes involved in acetoin metabolism in PAO1 containing the clc element. In contrast, PAO1 carrying the clc element acquired the capacity to grow on 3-chlorobenzoate and 2-aminophenol as sole carbon and energy substrates. No fitness loss >1% was detectable in competition experiments between PAO1 and PAO1 carrying the clc element. The genes from the clc element were not silent in PAO1, and excision was observed, although transfer of clc from PAO1 to other recipient bacteria was reduced by two orders of magnitude. Our results indicate that newly acquired mobile DNA not necessarily invoke an important fitness cost on their host. Absence of immediate detriment to the host may have contributed to the wide distribution of genomic islands like clc in bacterial genomes

High-density electric source imaging (esi) in focal epilepsy: a prospective study of 150 operated patients

Purpose: EEG is mandatory in the diagnosis of the epilepsy syndrome. However, its potential as imaging tool is still under estimated. In the present study, we aim to determine the prerequisites of maximal benefit of electric source imaging (ESI) to localize the irritative zone in patients with focal epilepsy. Methods: One hundred fifty patients suffering from focal epilepsy and with minimum 1 year postoperative follow-up were studied prospectively and blinded to the underlying diagnosis. We evaluated the influence of two important factors on sensitivity and specificity of ESI: the number of electrodes (low resolution, LR-ESI: <30 versus high resolution, HR-ESI: 128-256 electrodes), and the use of individual MRI (i-MRI) versus template MRI (t-MRI) as the head model. Findings: ESI had a sensitivity of 85% and a specificity of 87% when HR-ESI with i-MRI was used. Using LR-ESI, sensitivity decreased to 68%, or even 57% when only t-MRI was available. The sensitivity of HR-ESI/i-MRI compared favorably with those of MRI (76%), PET (69%) and ictal/interictal SPECT (64%). Interpretation: This study on a large patient group shows excellent sensitivity and specificity of ESI if 128 EEG channels or more are used for ESI and if the results are coregistered to the patient's individual MRI. Localization precision is as high as or even higher than established brain imagery techniques. HR-ESI appears to be a valuable additional imaging tool, given that larger electrode arrays are easily and rapidly applied with modern EEG equipment and that structural MRI is nearly always available for these patients.

Extremal properties of certain risk models

Cette thèse s'intéresse à étudier les propriétés extrémales de certains modèles de risque d'intérêt dans diverses applications de l'assurance, de la finance et des statistiques. Cette thèse se développe selon deux axes principaux, à savoir: Dans la première partie, nous nous concentrons sur deux modèles de risques univariés, c'est-à- dire, un modèle de risque de déflation et un modèle de risque de réassurance. Nous étudions le développement des queues de distribution sous certaines conditions des risques commun¬s. Les principaux résultats sont ainsi illustrés par des exemples typiques et des simulations numériques. Enfin, les résultats sont appliqués aux domaines des assurances, par exemple, les approximations de Value-at-Risk, d'espérance conditionnelle unilatérale etc. La deuxième partie de cette thèse est consacrée à trois modèles à deux variables: Le premier modèle concerne la censure à deux variables des événements extrême. Pour ce modèle, nous proposons tout d'abord une classe d'estimateurs pour les coefficients de dépendance et la probabilité des queues de distributions. Ces estimateurs sont flexibles en raison d'un paramètre de réglage. Leurs distributions asymptotiques sont obtenues sous certaines condi¬tions lentes bivariées de second ordre. Ensuite, nous donnons quelques exemples et présentons une petite étude de simulations de Monte Carlo, suivie par une application sur un ensemble de données réelles d'assurance. L'objectif de notre deuxième modèle de risque à deux variables est l'étude de coefficients de dépendance des queues de distributions obliques et asymétriques à deux variables. Ces distri¬butions obliques et asymétriques sont largement utiles dans les applications statistiques. Elles sont générées principalement par le mélange moyenne-variance de lois normales et le mélange de lois normales asymétriques d'échelles, qui distinguent la structure de dépendance de queue comme indiqué par nos principaux résultats. Le troisième modèle de risque à deux variables concerne le rapprochement des maxima de séries triangulaires elliptiques obliques. Les résultats théoriques sont fondés sur certaines hypothèses concernant le périmètre aléatoire sous-jacent des queues de distributions. -- This thesis aims to investigate the extremal properties of certain risk models of interest in vari¬ous applications from insurance, finance and statistics. This thesis develops along two principal lines, namely: In the first part, we focus on two univariate risk models, i.e., deflated risk and reinsurance risk models. Therein we investigate their tail expansions under certain tail conditions of the common risks. Our main results are illustrated by some typical examples and numerical simu¬lations as well. Finally, the findings are formulated into some applications in insurance fields, for instance, the approximations of Value-at-Risk, conditional tail expectations etc. The second part of this thesis is devoted to the following three bivariate models: The first model is concerned with bivariate censoring of extreme events. For this model, we first propose a class of estimators for both tail dependence coefficient and tail probability. These estimators are flexible due to a tuning parameter and their asymptotic distributions are obtained under some second order bivariate slowly varying conditions of the model. Then, we give some examples and present a small Monte Carlo simulation study followed by an application on a real-data set from insurance. The objective of our second bivariate risk model is the investigation of tail dependence coefficient of bivariate skew slash distributions. Such skew slash distributions are extensively useful in statistical applications and they are generated mainly by normal mean-variance mixture and scaled skew-normal mixture, which distinguish the tail dependence structure as shown by our principle results. The third bivariate risk model is concerned with the approximation of the component-wise maxima of skew elliptical triangular arrays. The theoretical results are based on certain tail assumptions on the underlying random radius.

Improved Innate and Adaptive Immunostimulation by Genetically Modified HIV-1 Protein Expressing NYVAC Vectors.

Attenuated poxviruses are safe and capable of expressing foreign antigens. Poxviruses are applied in veterinary vaccination and explored as candidate vaccines for humans. However, poxviruses express multiple genes encoding proteins that interfere with components of the innate and adaptive immune response. This manuscript describes two strategies aimed to improve the immunogenicity of the highly attenuated, host-range restricted poxvirus NYVAC: deletion of the viral gene encoding type-I interferon-binding protein and development of attenuated replication-competent NYVAC. We evaluated these newly generated NYVAC mutants, encoding HIV-1 env, gag, pol and nef, for their ability to stimulate HIV-specific CD8 T-cell responses in vitro from blood mononuclear cells of HIV-infected subjects. The new vectors were evaluated and compared to the parental NYVAC vector in dendritic cells (DCs), RNA expression arrays, HIV gag expression and cross-presentation assays in vitro. Deletion of type-I interferon-binding protein enhanced expression of interferon and interferon-induced genes in DCs, and increased maturation of infected DCs. Restoration of replication competence induced activation of pathways involving antigen processing and presentation. Also, replication-competent NYVAC showed increased Gag expression in infected cells, permitting enhanced cross-presentation to HIV-specific CD8 T cells and proliferation of HIV-specific memory CD8 T-cells in vitro. The recombinant NYVAC combining both modifications induced interferon-induced genes and genes involved in antigen processing and presentation, as well as increased Gag expression. This combined replication-competent NYVAC is a promising candidate for the next generation of HIV vaccines.

Angiogenesis-related gene expression profile with independent prognostic value in advanced ovarian carcinoma.

BACKGROUND Ovarian carcinoma is the most important cause of gynecological cancer-related mortality in Western societies. Despite the improved median overall survival in patients receiving chemotherapy regimens such as paclitaxel and carboplatin combination, relapse still occurs in most advanced diseased patients. Increased angiogenesis is associated with rapid recurrence and decreased survival in ovarian cancer. This study was planned to identify an angiogenesis-related gene expression profile with prognostic value in advanced ovarian carcinoma patients. METHODOLOGY/PRINCIPAL FINDINGS RNAs were collected from formalin-fixed paraffin-embedded samples of 61 patients with III/IV FIGO stage ovarian cancer who underwent surgical cytoreduction and received a carboplatin plus paclitaxel regimen. Expression levels of 82 angiogenesis related genes were measured by quantitative real-time polymerase chain reaction using TaqMan low-density arrays. A 34-gene-profile which was able to predict the overall survival of ovarian carcinoma patients was identified. After a leave-one-out cross validation, the profile distinguished two groups of patients with different outcomes. Median overall survival and progression-free survival for the high risk group was 28.3 and 15.0 months, respectively, and was not reached by patients in the low risk group at the end of follow-up. Moreover, the profile maintained an independent prognostic value in the multivariate analysis. The hazard ratio for death was 2.3 (95% CI, 1.5 to 3.2; p<0.001). CONCLUSIONS/SIGNIFICANCE It is possible to generate a prognostic model for advanced ovarian carcinoma based on angiogenesis-related genes using formalin-fixed paraffin-embedded samples. The present results are consistent with the increasing weight of angiogenesis genes in the prognosis of ovarian carcinoma.

The molecular signature of the stroma response in prostate cancer-induced osteoblastic bone metastasis highlights expansion of hematopoietic and prostate epithelial stem cell niches.

The reciprocal interaction between cancer cells and the tissue-specific stroma is critical for primary and metastatic tumor growth progression. Prostate cancer cells colonize preferentially bone (osteotropism), where they alter the physiological balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption, and elicit prevalently an osteoblastic response (osteoinduction). The molecular cues provided by osteoblasts for the survival and growth of bone metastatic prostate cancer cells are largely unknown. We exploited the sufficient divergence between human and mouse RNA sequences together with redefinition of highly species-specific gene arrays by computer-aided and experimental exclusion of cross-hybridizing oligonucleotide probes. This strategy allowed the dissection of the stroma (mouse) from the cancer cell (human) transcriptome in bone metastasis xenograft models of human osteoinductive prostate cancer cells (VCaP and C4-2B). As a result, we generated the osteoblastic bone metastasis-associated stroma transcriptome (OB-BMST). Subtraction of genes shared by inflammation, wound healing and desmoplastic responses, and by the tissue type-independent stroma responses to a variety of non-osteotropic and osteotropic primary cancers generated a curated gene signature ("Core" OB-BMST) putatively representing the bone marrow/bone-specific stroma response to prostate cancer-induced, osteoblastic bone metastasis. The expression pattern of three representative Core OB-BMST genes (PTN, EPHA3 and FSCN1) seems to confirm the bone specificity of this response. A robust induction of genes involved in osteogenesis and angiogenesis dominates both the OB-BMST and Core OB-BMST. This translates in an amplification of hematopoietic and, remarkably, prostate epithelial stem cell niche components that may function as a self-reinforcing bone metastatic niche providing a growth support specific for osteoinductive prostate cancer cells. The induction of this combinatorial stem cell niche is a novel mechanism that may also explain cancer cell osteotropism and local interference with hematopoiesis (myelophthisis). Accordingly, these stem cell niche components may represent innovative therapeutic targets and/or serum biomarkers in osteoblastic bone metastasis.

DNA microarrays and plant defence

Recent progress in understanding plant defence has highlighted a complex, interacting network of signalling pathways leading to the induction of numerous genes. The advent of new technologies for the global analysis of gene expression is fundamentally affecting research in biology, and studies on plant defence should benefit from these new approaches. Genome-wide microarrays will provide a powerful tool for the discovery of all defence-related genes and should help in elucidating their function. The association of a particular signalling pathway with a defence response can be tested with microarrays and defined mutants. Comparison of transcript profiles after biotic and abiotic stresses reveals overlapping activation of defence-related genes and defines new concepts on how plants cope with multiple aggressions. The combination of expression data with other biochemical or metabolite measurements seems another promising approach. Finally, small-scale, dedicated microarrays containing sets of well-characterised genes might prove to be a very useful complement to more expensive, less accessible, large-scale arrays.