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PubMed2006

Transcriptome kinetics of arsenic-induced adaptive response in zebrafish liver.

Arsenic is a prominent environmental toxicant and carcinogen; however, its molecular mechanism of toxicity and carcinogenicity remains poorly understood. In this study, we performed microarray-based expression profiling on liver of zebrafish exposed to 15 parts/million (ppm) arsenic [As(V)] for 8-96 h to identify global transcriptional changes and biological networks involved in arsenic-induced adaptive responses in vivo. We found that there was an increase of transcriptional activity associated with metabolism, especially for biosyntheses, membrane transporter activities, cytoplasm, and endoplasmic reticulum in the 96 h of arsenic treatment, while transcriptional programs for proteins in catabolism, energy derivation, and stress response remained active throughout the arsenic treatment. Many differentially expressed genes encoding proteins involved in heat shock proteins, DNA damage/repair, antioxidant activity, hypoxia induction, iron homeostasis, arsenic metabolism, and ubiquitin-dependent protein degradation were identified, suggesting strongly that DNA and protein damage as a result of arsenic metabolism and oxidative stress caused major cellular injury. These findings were comparable with those reported in mammalian systems, suggesting that the zebrafish liver coupled with the available microarray technology present an excellent in vivo toxicogenomic model for investigating arsenic toxicity. We proposed an in vivo, acute arsenic-induced adaptive response model of the zebrafish liver illustrating the relevance of many transcriptional activities that provide both global and specific information of a coordinated adaptive response to arsenic in the liver.

Adaptation, Physiological↗
PubMed2006

Identification of arthritis-related gene clusters by microarray analysis of two independent mouse models for rheumatoid arthritis.

Rheumatoid arthritis (RA) is an autoimmune disease affecting approximately 1% of the population worldwide. Previously, we showed that human T-cell leukemia virus type I-transgenic mice and interleukin-1 receptor antagonist-knockout mice develop autoimmunity and joint-specific inflammation that resembles human RA. To identify genes involved in the pathogenesis of arthritis, we analyzed the gene expression profiles of these animal models by using high-density oligonucleotide arrays. We found 1,467 genes that were differentially expressed from the normal control mice by greater than threefold in one of these animal models. The gene expression profiles of the two models correlated well. We extracted 554 genes whose expression significantly changed in both models, assuming that pathogenically important genes at the effector phase would change in both models. Then, each of these commonly changed genes was mapped into the whole genome in a scale of the 1-megabase pairs. We found that the transcriptome map of these genes did not distribute evenly on the chromosome but formed clusters. These identified gene clusters include the major histocompatibility complex class I and class II genes, complement genes, and chemokine genes, which are well known to be involved in the pathogenesis of RA at the effector phase. The activation of these gene clusters suggests that antigen presentation and lymphocyte chemotaxis are important for the development of arthritis. Moreover, by searching for such clusters, we could detect genes with marginal expression changes. These gene clusters include schlafen and membrane-spanning four-domains subfamily A genes whose function in arthritis has not yet been determined. Thus, by combining two etiologically different RA models, we succeeded in efficiently extracting genes functioning in the development of arthritis at the effector phase. Furthermore, we demonstrated that identification of gene clusters by transcriptome mapping is a useful way to find potentially pathogenic genes among genes whose expression change is only marginal.

Animals↗
PubMed2006

Reporter metabolite analysis of transcriptional profiles of a Staphylococcus aureus strain with normal phenotype and its isogenic hemB mutant displaying the small-colony-variant phenotype.

In this study, full-genome DNA microarrays based on the sequence of Staphylococcus aureus N315 were used to compare the transcriptome of a clinical S. aureus strain with a normal phenotype to that of its isogenic mutant with a stable small-colony-variant (SCV) phenotype (hemB::ermB). In addition to standard statistical analyses, systems biology advances were applied to identify reporter metabolites and to achieve a more detailed survey of genome-wide expression differences between the hemB mutant and its parental strain. Genes of enzymes involved in glycolytic and fermentative pathways were found to be up-regulated in the hemB mutant. Furthermore, our analyses allowed identification of additional differences between the normal-phenotype S. aureus and the SCV, most of which were related to metabolism. Profound differences were identified especially in purine biosynthesis as well as in arginine and proline metabolism. Of particular interest, a hypothetical gene of the Crp/Fnr family (SA2424) that is part of the arginine-deiminase (AD) pathway, whose homologue in Streptococcus suis is assumed to be involved in intracellular persistence, showed significantly increased transcription in the hemB mutant. The hemB mutant potentially uses the up-regulated AD pathway to produce ATP or (through ammonia production) to counteract the acidic environment that prevails intracellularly. Moreover, genes involved in capsular polysaccharide and cell wall synthesis were found to be significantly up-regulated in the hemB mutant and therefore potentially responsible for the changed cell morphology of SCVs. In conclusion, the identified differences may be responsible for the SCV phenotype and its association with chronic and persistent infections.

Arginine↗
PubMed2005

Validation of a first-generation long-oligonucleotide microarray for transcriptional profiling in the pig.

A first-generation porcine oligonucleotide set, representing 13,297 cDNAs and ESTs, has been designed by Qiagen-Operon for transcriptional profiling. To validate this set, microarrays containing each 70-mer oligonucleotide, referred to as the Qiagen-NRSP8 array, were hybridized with targets from porcine adult liver, lung, muscle, or small intestine. Transcriptome analyses showed that 11,328 of the oligonucleotides demonstrated expression in at least one tissue. Statistical analyses revealed that 1810 genes showed differential expression among tissues (Bonferroni adjusted p < 0.05). Biological pathways identified by DAVID/EASE analysis using a list of 423 tissue-selective genes matched archetypal pathways in the corresponding human or mouse tissue. Real-time quantitative PCR confirmed expression patterns for 9 of 11 genes tested. Our results demonstrate that this first-generation porcine oligonucleotide array is informative and the specificity is high. This is essential validation for investigators using the Qiagen-NRSP8 array for porcine functional genomics and for using the pig in modeling important physiological problems.

Animals↗
PubMed2005

Endurance training modulates the muscular transcriptome response to acute exercise.

We hypothesized that in untrained individuals (n=6) a single bout of ergometer endurance exercise provokes a concerted response of muscle transcripts towards a slow-oxidative muscle phenotype over a 24-h period. We further hypothesized this response during recovery to be attenuated after six weeks of endurance training. We monitored the expression profile of 220 selected transcripts in muscle biopsies before as well as 1, 8, and 24 h after a 30-min near-maximal bout of exercise. The generalized gene response of untrained vastus lateralis muscle peaked after 8 h of recovery (P=0.001). It involved multiple transcripts of oxidative metabolism and glycolysis. Angiogenic and cell regulatory transcripts were transiently reduced after 1 h independent of the training state. In the trained state, the induction of most transcripts 8 h after exercise was less pronounced despite a moderately higher relative exercise intensity, partially because of increased steady-state mRNA concentration, and the level of metabolic and extracellular RNAs was reduced during recovery from exercise. Our data suggest that the general response of the transcriptome for regulatory and metabolic processes is different in the trained state. Thus, the response is specifically modified with repeated bouts of endurance exercise during which muscle adjustments are established.

Adult↗
PubMed2005

Analysis of the epidermal growth factor receptor specific transcriptome: effect of receptor expression level and an activating mutation.

Overexpression or expression of activating mutations of the epidermal growth factor receptor (EGFR) is common in cancer and correlates with neoplastic progression. The present study employed Affymetrix oligonucleotide arrays to profile genes induced by ligand-activated EGFR with the receptor either moderately expressed or overexpressed at an in-itself transforming level. These changes were compared to those induced by the naturally occurring constitutively active variant EGFRvIII. This study provides novel insight on the activities and mechanisms of EGFRvIII and EGFR mediated transformation, as genes encoding proteins with functions in promoting cell proliferation, invasion, antiapoptosis, and angiogenesis featured prominently in the EGFRvIII- and EGFR-expressing cells. Surprisingly, it was found that ligand-activated EGFR induced the expression of a large group of genes known to be inducible by interferons. Expression of this module was absent in the EGFRvIII-expressing cell line and the parental cell line. Treatment with the specific EGFR inhibitor AG1478 indicated that the regulations were primary, receptor-mediated events. Furthermore, activation of this module correlated with activation of STAT1 and STAT3. The results thus demonstrate that ligand-activated EGFR at different expression levels results in different kinetics of signaling and induction of gene expression. In addition, the constitutively active variant EGFRvIII seems to activate only a subset of signal pathways and induce a subset of genes as compared to the ligand-activated EGFR.

Animals↗
PubMed2024

Meningioma transcriptomic landscape demonstrates novel subtypes with regional associated biology and patient outcome.

Meningiomas, although mostly benign, can be recurrent and fatal. World Health Organization (WHO) grading of the tumor does not always identify high-risk meningioma, and better characterizations of their aggressive biology are needed. To approach this problem, we combined 13 bulk RNA sequencing (RNA-seq) datasets to create a dimension-reduced reference landscape of 1,298 meningiomas. The clinical and genomic metadata effectively correlated with landscape regions, which led to the identification of meningioma subtypes with specific biological signatures. The time to recurrence also correlated with the map location. Further, we developed an algorithm that maps new patients onto this landscape, where the nearest neighbors predict outcome. This study highlights the utility of combining bulk transcriptomic datasets to visualize the complexity of tumor populations. Further, we provide an interactive tool for understanding the disease and predicting patient outcomes. This resource is accessible via the online tool Oncoscape, where the scientific community can explore the meningioma landscape.

Meningioma↗
PubMed2006

Transcriptome of local innate and adaptive immunity during early phase of infectious bronchitis viral infection.

To understand the mechanistic basis of local innate and adaptive immunity against infectious bronchitis virus (IBV) at the molecular level, we examined the gene transcription profile of tracheal epithelial layers 3 d after infection of chickens with an attenuated IBV-Massachusetts strain. Results suggested that the transcription levels of 365 genes were either upregulated or downregulated (2-fold and higher) after IBV infection. Among the upregulated 250 genes, 25 were directly immune-related genes. These upregulated immune response genes included TLR2, TLR3, interferon-induced antiviral genes (Mx), and genes responsible for cytotoxic T cell killing such as Fas antigen and granzyme-A. Overall, a diversity of innate immunity and helper T cell type 1 (Th1)-biased adaptive immunity are activated in the host's early defense against IBV invasion, and they are responsible for the rapid clearance of virus from the local infection.

Animals↗
PubMed2026

A transcription factor regulatory atlas for activity inference and perturbation prediction.

Inferring transcription factor (TF) activity from transcriptomes and predicting transcriptome-wide responses to TF perturbations remain challenging, in part because available TF-mRNA resources often face a trade-off between precision and coverage and typically lack signed regulatory information. Here, we present TFActProfiler, a TF-mRNA resource and computational framework that learns signed, quantitative TF-mRNA regulatory coefficients by integrating heterogeneous prior evidence (ChIP-based, motif-based, and curated TF-mRNA annotations) with large-scale bulk and single-cell RNA-seq atlases. TFActProfiler contains 2&#x2009;606&#x2009;176 signed TF-mRNA interactions and improves TF activity inference in TF knockdown benchmarks relative to widely used regulon resources while retaining broad TF and target coverage. In addition, because the same learned regulatory coefficients can be used to model downstream transcriptional effects, TFActProfiler enables prediction of transcriptome-wide gene expression responses to TF knockdown without training on task-matched perturbation data. When perturbation datasets are available, TFActProfiler can be further refined to achieve performance comparable to state-of-the-art machine-learning baselines. By providing a direction-aware representation of TF-mRNA regulation for both activity inference and perturbation-response modeling, TFActProfiler supports systematic dissection of gene regulatory programs across diverse cellular contexts.

Transcription Factors↗
PubMed2005

mSin3A corepressor regulates diverse transcriptional networks governing normal and neoplastic growth and survival.

mSin3A is a core component of a large multiprotein corepressor complex with associated histone deacetylase (HDAC) enzymatic activity. Physical interactions of mSin3A with many sequence-specific transcription factors has linked the mSin3A corepressor complex to the regulation of diverse signaling pathways and associated biological processes. To dissect the complex nature of mSin3A's actions, we monitored the impact of conditional mSin3A deletion on the developmental, cell biological, and transcriptional levels. mSin3A was shown to play an essential role in early embryonic development and in the proliferation and survival of primary, immortalized, and transformed cells. Genetic and biochemical analyses established a role for mSin3A/HDAC in p53 deacetylation and activation, although genetic deletion of p53 was not sufficient to attenuate the mSin3A null cell lethal phenotype. Consistent with mSin3A's broad biological activities beyond regulation of the p53 pathway, time-course gene expression profiling following mSin3A deletion revealed deregulation of genes involved in cell cycle regulation, DNA replication, DNA repair, apoptosis, chromatin modifications, and mitochondrial metabolism. Computational analysis of the mSin3A transcriptome using a knowledge-based database revealed several nodal points through which mSin3A influences gene expression, including the Myc-Mad, E2F, and p53 transcriptional networks. Further validation of these nodes derived from in silico promoter analysis showing enrichment for Myc-Mad, E2F, and p53 cis-regulatory elements in regulatory regions of up-regulated genes following mSin3A depletion. Significantly, in silico promoter analyses also revealed specific cis-regulatory elements binding the transcriptional activator Stat and the ISWI ATP-dependent nucleosome remodeling factor Falz, thereby expanding further the mSin3A network of regulatory factors. Together, these integrated genetic, biochemical, and computational studies demonstrate the involvement of mSin3A in the regulation of diverse pathways governing many aspects of normal and neoplastic growth and survival and provide an experimental framework for the analysis of essential genes with diverse biological functions.

Animals↗
PubMed2024

Identification of miRNA expression profile in middle ear cholesteatoma using small RNA-sequencing.

BACKGROUND: The present study aims to identify the differential miRNA expression profile in middle ear cholesteatoma and explore their potential roles in its pathogenesis. METHODS: Cholesteatoma and matched normal retroauricular skin tissue samples were collected from patients diagnosed with acquired middle ear cholesteatoma. The miRNA expression profiling was performed using small RNA sequencing, which further validated by quantitative real-time PCR (qRT-PCR). Target genes of differentially expressed miRNAs in cholesteatoma were predicted. The interaction network of 5 most significantly differentially expressed miRNAs was visualized using Cytoscape. Further Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analyses were processed to investigate the biological functions of miRNAs in cholesteatoma. RESULTS: The miRNA expression profile revealed 121 significantly differentially expressed miRNAs in cholesteatoma compared to normal skin tissues, with 56 upregulated and 65 downregulated. GO and KEGG pathway enrichment analyses suggested their significant roles in the pathogenesis of cholesteatoma. The interaction network of the the 2 most upregulated (hsa-miR-21-5p and hsa-miR-142-5p) and 3 most downregulated (hsa-miR-508-3p, hsa-miR-509-3p and hsa-miR-211-5p) miRNAs identified TGFBR2, MBNL1, and NFAT5 as potential key target genes in middle ear cholesteatoma. CONCLUSIONS: This study provides a comprehensive miRNA expression profile in middle ear cholesteatoma, which may aid in identifying therapeutic targets for its management.

Humans↗
PubMed2026

Multi-level Transcriptomic and Machine-learning Analyses Identify MZT1 as a Proliferation-associated Prognostic Marker in Lung Adenocarcinoma.

BACKGROUND/AIM: Lung adenocarcinoma (LUAD) exhibits substantial molecular heterogeneity and variable clinical outcomes, highlighting the need for biomarkers that reflect core tumor biological processes. Centrosome-associated proteins regulate mitotic fidelity and genome stability, yet their roles in LUAD remain incompletely defined. In this study, we systematically characterized mitotic spindle organizing protein 1 (MOZART1; MZT1) and related family members in LUAD. MATERIALS AND METHODS: We performed integrated analyses combining bulk transcriptomic datasets, survival modeling, gene set enrichment, immune deconvolution, machine-learning based prognostic modeling, and single-cell RNA sequencing. Expression patterns and clinical associations of MZT family genes were evaluated across pan-cancer and LUAD cohorts. RESULTS: MZT family genes were consistently upregulated in tumor tissues, with MZT1 showing the most robust expression pattern. Elevated MZT1 expression was significantly associated with reduced overall survival. Functional analyses revealed coordinated activation of proliferative and genome maintenance pathways, including G2/M checkpoint regulation, E2F and MYC signaling, and DNA repair. A multivariable analysis indicated that the prognostic association of MZT1 was reduced after adjusting for canonical proliferation markers, suggesting partial overlap with established proliferation signals. The LASSO-based Cox model demonstrated stable time-dependent predictive performance at 1-, 3-, and 5-year survival. Immune analyses indicated associations between MZT1 expression and tumor microenvironmental features. Single-cell analysis showed that MZT1 expression was predominantly enriched in malignant epithelial cells and associated with proliferative cellular states. Protein-level validation supported concordance with transcriptomic findings. CONCLUSION: MZT1 is a proliferation-associated marker that integrates clinical risk, transcriptional programs, cellular heterogeneity, and predictive modeling in LUAD, providing a potential framework for biomarker development and risk stratification.

Humans↗
PubMed2004

Molecular identification of ERalpha-positive breast cancer cells by the expression profile of an intrinsic set of estrogen regulated genes.

Estrogens exert a key biological role in mammary gland epithelial cells and promote breast carcinogenesis and tumor progression. We recently identified a new large set of estrogen responsive genes from breast cancer (BC) cells by DNA microarray analysis of the gene expression profiles induced by 17beta-estradiol in ZR-75.1 and MCF-7 cells. The purpose of the present study was to test whether the expression pattern of hormone regulated genes from this set identifies estrogen receptor (ERalpha) positive, hormone responsive BC cells. To this aim, we carried out in silico metanalysis of ERalpha positive and ERalpha negative human BC cell line transcriptomes, focusing on two sets of 171 and 218 estrogen responsive genes, respectively. Results show that estrogen dependent gene activity in hormone responsive BC cells is significantly different from that of non-responsive cells and, alone, allows to discriminate these two cellular phenotypes. Indeed, we have identified 61 genes whose expression profile specifically marks ERalpha positive BC cells, suggesting that this gene set may be exploited for phenotypic characterization of breast tumors. This possibility was tested with data obtained by gene expression profiling of BC surgical samples, where the ERalpha positive phenotypes were highlighted by the expression profile of a subset of 27 such hormone responsive genes and four additional BC marker genes, not including ERs. These results provide direct evidence that the expression pattern of a limited number of estrogen responsive genes can be exploited to assess the estrogen signaling status of BC cells both in vitro and ex-vivo.

Biopsy↗
PubMed2005

Induction of apoptosis in mouse liver by microcystin-LR: a combined transcriptomic, proteomic, and simulation strategy.

Microcystins (MCs) are a family of cyclic heptapeptide hepatotoxins produced by freshwater species of cyanobacteria that have been implicated in the development of liver cancer, necrosis, and even deadly intrahepatic bleeding. MC-LR, the most toxic MC variant, is also the most commonly encountered in a contaminated aquatic system. This study presents the first data in the toxicological research of MCs that combines the use of standard apoptotic assays with transcriptomics, proteomic technologies, and computer simulations. By using histochemistry, DNA fragmentation assays, and flow cytometry analysis, we determined that MC-LR causes rapid, dose-dependent apoptosis in mouse liver when BALB/c mice are treated with MC-LR for 24 h at doses of either 50, 60, or 70 microg/kg of body weight. We then used gene expression profiling to demonstrate differential expressions (>2-fold) of 61 apoptosis-related genes in cells treated with MC-LR. Further proteomic analysis identified a total of 383 proteins of which 35 proteins were up-regulated and 30 proteins were down-regulated more than 2.5-fold when compared with controls. Combining computer simulations with the transcriptomic and proteomic data, we found that low doses (50 microg/kg) of MC-LR lead to apoptosis primarily through the BID-BAX-BCL-2 pathway, whereas high doses of MC-LR (70 microg/kg) caused apoptosis via a reactive oxygen species pathway. These results indicated that MC-LR exposure can cause apoptosis in mouse liver and revealed two independent pathways playing a major regulatory role in MC-LR-induced apoptosis, thereby contributing to a better understanding of the hepatotoxicity and the tumor-promoting mechanisms of MCs.

Animals↗
PubMed2005

Conversion of cDNA differential display results (DDRT-PCR) into quantitative transcription profiles.

BACKGROUND: Gene expression studies on non-model organisms require open-end strategies for transcription profiling. Gel-based analysis of cDNA fragments allows to detect alterations in gene expression for genes which have neither been sequenced yet nor are available in cDNA libraries. Commonly used protocols for gel-based transcript profiling are cDNA differential display (DDRT-PCR) and cDNA-AFLP. Both methods have been used merely as qualitative gene discovery tools so far. RESULTS: We developed procedures for the conversion of cDNA Differential Display data into quantitative transcription profiles. Amplified cDNA fragments are separated on a DNA sequencer and detector signals are converted into virtual gel images suitable for semi-automatic analysis. Data processing consists of four steps: (i) cDNA bands in lanes corresponding to samples treated with the same primer combination are matched in order to identify fragments originating from the same transcript, (ii) intensity of bands is determined by densitometry, (iii) densitometric values are normalized, and (iv) intensity ratio is calculated for each pair of corresponding bands. Transcription profiles are represented by sets of intensity ratios (control vs. treatment) for cDNA fragments defined by primer combination and DNA mobility. We demonstrated the procedure by analyzing DDRT-PCR data on the effect of secondary metabolites of oilseed rape Brassica napus on the transcriptome of the pathogenic fungus Leptosphaeria maculans. CONCLUSION: We developed a data processing procedure for the quantitative analysis of amplified cDNA fragments separated by electrophoresis. The system utilizes common software and provides an open-end alternative to DNA microarray analysis of the transcriptome. It is expected to work equally well with DDRT-PCR and cDNA-AFLP data and be useful particularly in research on organisms for which microarray analysis is not available or economical.

Brassica napus↗
PubMed2026

Transcriptome Analysis Reveals Key Drought-Stress-Responsive Genes in Two Bermudagrass Genotypes.

Drought inhibits grass development and survival. However, molecular-based studies on drought tolerance mechanisms in bermudagrass (Cynodon dactylon) remain scarce. Therefore, a drought-resistant bermudagrass (Tianshui) and a drought-sensitive (Zhengzhou) genotype were selected and subjected to 28&#x2009;days of 50% drought stress. Leaves were sampled for RNA sequencing. Under drought stress, 2410 differentially expressed genes (DEGs) were discovered in which 1214 were upregulated (tolerant vs. sensitive) and 1196 downregulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) indicated that these specific DEGs are notably present in hormonal signal transduction pathways, flavonoids biogenesis, carbohydrate metabolic processes, abscisic acid-mediated pathways, MAPK signaling, and gluconeogenesis. Additionally, the plant hormone signal transduction pathway is predominantly linked to abscisic acid signal transduction, and many other plant hormones were also drought-responsive. The study specifically targeted genes associated with the antioxidant enzyme system, with a particular emphasis on responsive TFs such as MYB, bHLH, bZIP, GRAS, and WRKY. This study establishes the theoretical framework and identifies gene sources for the genetic enhancement and breeding of bermudagrass in the future.

Cynodon↗
PubMed2004

Gene expression profiling in anaplastic large cell lymphoma and Hodgkin's disease.

Recent efforts have been made to isolate molecular targets that could explain different outcome between histological subtypes of lymphomas and to understand the molecular mechanisms underlying oncogenic events. Using the SSH technique, we compared the transcriptome of 2 cases of ALK+ and ALK- anaplastic large cell lymphoma (ALCL) and of 2 cases of classical Hodgkin's lymphoma (cHL) with opposite behavior. Regarding ALCL, we showed that ALK-positive tumors overexpressed genes involved in different signaling pathways such as activation or signaling of T-cells, regulation of apoptosis, phospholipase Cgamma and phosphatidyl inositol-3 Kinase. In addition, the characterization of a specific molecular signature may be of clinical relevance since ALK+ tumors generally have a better prognosis than ALK- ones. Similar problems of differential prognosis is observed in cases of cHL, which in addition, may be morphologically and immunologically indistinguishable. Therefore, we applied the same SSH technique to 2 cHL samples from patients with favorable and poor outcome, respectively. Forty-four cDNAs were significantly overexpressed in the poor outcome case. In addition to the defender against death cell 1 (DAD1) gene, overexpressed clones corresponded mostly to expressed sequence tags (ESTs). Interestingly, the present study identifies new genes which may be involved in the pathogenesis and/or clinical outcome of cHL and deserve further investigations.

Gene Expression Profiling↗
PubMed2005

An analysis of the use of genomic DNA as a universal reference in two channel DNA microarrays.

BACKGROUND: DNA microarray is an invaluable tool for gene expression explorations. In the two-dye microarray, fluorescence intensities of two samples, each labeled with a different dye, are compared after hybridization. To compare a large number of samples, the 'reference design' is widely used, in which all RNA samples are hybridized to a common reference. Genomic DNA is an attractive candidate for use as a universal reference, especially for bacterial systems with a low percentage of non-coding sequences. However, genomic DNA, comprising of both the sense and anti-sense strands, is unlike the single stranded cDNA usually used in microarray hybridizations. The presence of the antisense strand in the 'reference' leads to reactions between complementary labeled strands in solution and may cause the assay result to deviate from true values. RESULTS: We have developed a mathematical model to predict the validity of using genomic DNA as a reference in the microarray assay. The model predicts that the assay can accurately estimate relative concentrations for a wide range of initial cDNA concentrations. Experimental results of DNA microarray assay using genomic DNA as a reference correlated well to those obtained by a direct hybridization between two cDNA samples. The model predicts that the initial concentrations of labeled genomic DNA strands and immobilized strands, and the hybridization time do not significantly affect the assay performance. At low values of the rate constant for hybridization between immobilized and mobile strands, the assay performance varies with the hybridization time and initial cDNA concentrations. For the case where a microarray with immobilized single strands is used, results from hybridizations using genomic DNA as a reference will correspond to true ratios under all conditions. CONCLUSION: Simulation using the mathematical model, and the experimental study presented here show the potential utility of microarray assays using genomic DNA as a reference. We conclude that the use of genomic DNA as reference DNA should greatly facilitate comparative transcriptome analysis.

DNA↗