Machine learning classifier approaches for predicting response to RTK-type-III inhibitors demonstrate high accuracy using transcriptomic signatures and ex vivo data.

Motivation: The application of machine learning (ML) techniques in the medical field has demonstrated both successes and challenges in the precision medicine era. The ability to accurately classify a subject as a potential responder versus a nonresponder to a given therapy is still an active area of research pushing the field to create new approaches for applying machine-learning techniques. In this study, we leveraged publicly available data through the BeatAML initiative. Specifically, we used gene count data, generated via RNA-seq, from 451 individuals matched with ex vivo data generated from treatment with RTK-type-III inhibitors. Three feature selection techniques were tested, principal component analysis, Shapley Additive Explanation (SHAP) technique and differential gene expression analysis, with three different classifiers, XGBoost, LightGBM and random forest (RF). Sensitivity versus specificity was analyzed using the area under the curve (AUC)-receiver operating curves (ROCs) for every model developed. Results: Our work demonstrated that feature selection technique, rather than the classifier, had the greatest impact on model performance. The SHAP technique outperformed the other feature selection techniques and was able to with high accuracy predict outcome response, with the highest performing model: Foretinib with 89% AUC using the SHAP technique and RF classifier. Our ML pipelines demonstrate that at the time of diagnosis, a transcriptomics signature exists that can potentially predict response to treatment, demonstrating the potential of using ML applications in precision medicine efforts. Availability and implementation: https://github.com/UD-CRPL/RCDML. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

DNA Methylation Analysis Reveals Distinct Patterns in Satellite Cell-Derived Myogenic Progenitor Cells of Subjects with Spastic Cerebral Palsy.

Spastic type cerebral palsy (CP) is a complex neuromuscular disorder that involves altered skeletal muscle microanatomy and growth, but little is known about the mechanisms contributing to muscle pathophysiology and dysfunction. Traditional genomic approaches have provided limited insight regarding disease onset and severity, but recent epigenomic studies indicate that DNA methylation patterns can be altered in CP. Here, we examined whether a diagnosis of spastic CP is associated with intrinsic DNA methylation differences in myoblasts and myotubes derived from muscle resident stem cell populations (satellite cells; SCs). Twelve subjects were enrolled (6 CP; 6 control) with informed consent/assent. Skeletal muscle biopsies were obtained during orthopedic surgeries, and SCs were isolated and cultured to establish patient-specific myoblast cell lines capable of proliferation and differentiation in culture. DNA methylation analyses indicated significant differences at 525 individual CpG sites in proliferating SC-derived myoblasts (MB) and 1774 CpG sites in differentiating SC-derived myotubes (MT). Of these, 79 CpG sites were common in both culture types. The distribution of differentially methylated 1 Mbp chromosomal segments indicated distinct regional hypo- and hyper-methylation patterns, and significant enrichment of differentially methylated sites on chromosomes 12, 13, 14, 15, 18, and 20. Average methylation load across 2000 bp regions flanking transcriptional start sites was significantly different in 3 genes in MBs, and 10 genes in MTs. SC derived MBs isolated from study participants with spastic CP exhibited fundamental differences in DNA methylation compared to controls at multiple levels of organization that may reveal new targets for studies of mechanisms contributing to muscle dysregulation in spastic CP.

Rapid COVID-19 Prognostic Blood Test for Disease Severity Using Epigenetic Immune System Biomarkers.

OBJECTIVE: To develop a novel whole-blood epigenetic biomarker of immune system status, or EpiMarker, that would indicate whether a person with a recent COVID-19 diagnosis is at risk for severe symptoms including Acute Respiratory Distress Syndrome. METHODS: Using a novel methyl-sensitive restriction endonuclease approach to measure site-specific DNA methylation profiles, immune system phentoype EpiMarkers are identified using a machine-learning computational bioinformatics platform. The result is a diagnostic network of 20 to 40 immuno DNA methylation sites having the greatest predictive power for identifying patients whose COVID-19 disease will likely progress to ARDS requiring ICU/intubation care. RESULTS: Immune system status in peripheral whole blood provides a sensitive and responsive sentinel signal reflecting how different functional pathways are currently being regulated in a subject. Deciphering this signal status of how immune cells are set to respond provides deep functional information regarding patient health and potential disease phenotypes resulting from a cytokine storm characteristic of a hyper immune inflammatory response to COVID-19 infection. CONCLUSIONS: The ability to identify future potential changes in patient health using this novel EpiMarker technology opens new avenues for defending populations from severe disease risks of Acute Respiratory Distress Syndrome. POLICY IMPLICATIONS: A successful EpiMarker Assay for COVID-19 disease severity risk would allow for two important applications: (1) patients could be triaged early in the course of infection to allow for critical decisions for allocating resources, both in terms of hospital infrastructure (ICU beds, ventilators) and therapeutic drug treatments; and (2) pre-infection, individuals could be screened to identify personnel at low-risk for mission critical assignments (first responders, doctors, nurses, military personnel, etc.) during future pandemics and ongoing battles with viral pathogens like influenza.

Epigenetic machine learning: utilizing DNA methylation patterns to predict spastic cerebral palsy.

BACKGROUND: Spastic cerebral palsy (CP) is a leading cause of physical disability. Most people with spastic CP are born with it, but early diagnosis is challenging, and no current biomarker platform readily identifies affected individuals. The aim of this study was to evaluate epigenetic profiles as biomarkers for spastic CP. A novel analysis pipeline was employed to assess DNA methylation patterns between peripheral blood cells of adolescent subjects (14.9 ± 0.3 years old) with spastic CP and controls at single CpG site resolution. RESULTS: Significantly hypo- and hyper-methylated CpG sites associated with spastic CP were identified. Nonmetric multidimensional scaling fully discriminated the CP group from the controls. Machine learning based classification modeling indicated a high potential for a diagnostic model, and 252 sets of 40 or fewer CpG sites achieved near-perfect accuracy within our adolescent cohorts. A pilot test on significantly younger subjects (4.0 ± 1.5 years old) identified subjects with 73% accuracy. CONCLUSIONS: Adolescent patients with spastic CP can be distinguished from a non-CP cohort based on DNA methylation patterns in peripheral blood cells. A clinical diagnostic test utilizing a panel of CpG sites may be possible using a simulated classification model. A pilot validation test on patients that were more than 10 years younger than the main adolescent cohorts indicated that distinguishing methylation patterns are present earlier in life. This study is the first to report an epigenetic assay capable of distinguishing a CP cohort.

Epigenetic DNA Methylation Profiling with MSRE: A Quantitative NGS Approach Using a Parkinson's Disease Test Case.

Epigenetics is a rapidly developing field focused on deciphering chemical fingerprints that accumulate on human genomes over time. As the nascent idea of precision medicine expands to encompass epigenetic signatures of diagnostic and prognostic relevance, there is a need for methodologies that provide high-throughput DNA methylation profiling measurements. Here we report a novel quantification methodology for computationally reconstructing site-specific CpG methylation status from next generation sequencing (NGS) data using methyl-sensitive restriction endonucleases (MSRE). An integrated pipeline efficiently incorporates raw NGS metrics into a statistical discrimination platform to identify functional linkages between shifts in epigenetic DNA methylation and disease phenotypes in samples being analyzed. In this pilot proof-of-concept study we quantify and compare DNA methylation in blood serum of individuals with Parkinson's Disease relative to matched healthy blood profiles. Even with a small study of only six samples, a high degree of statistical discrimination was achieved based on CpG methylation profiles between groups, with 1008 statistically different CpG sites (p < 0.0025, after false discovery rate correction). A methylation load calculation was used to assess higher order impacts of methylation shifts on genes and pathways and most notably identified FGF3, FGF8, HTT, KMTA5, MIR8073, and YWHAG as differentially methylated genes with high relevance to Parkinson's Disease and neurodegeneration (based on PubMed literature citations). Of these, KMTA5 is a histone methyl-transferase gene and HTT is Huntington Disease Protein or Huntingtin, for which there are well established neurodegenerative impacts. The future need for precision diagnostics now requires more tools for exploring epigenetic processes that may be linked to cellular dysfunction and subsequent disease progression.

Partitioning of Respiration in an Animal-Algal Symbiosis: Implications for Different Aerobic Capacity between Symbiodinium spp.

Cnidarian-dinoflagellate symbioses are ecologically important and the subject of much investigation. However, our understanding of critical aspects of symbiosis physiology, such as the partitioning of total respiration between the host and symbiont, remains incomplete. Specifically, we know little about how the relationship between host and symbiont respiration varies between different holobionts (host-symbiont combinations). We applied molecular and biochemical techniques to investigate aerobic respiratory capacity in naturally symbiotic Exaiptasia pallida sea anemones, alongside animals infected with either homologous ITS2-type A4 Symbiodinium or a heterologous isolate of Symbiodinium minutum (ITS2-type B1). In naturally symbiotic anemones, host, symbiont, and total holobiont mitochondrial citrate synthase (CS) enzyme activity, but not host mitochondrial copy number, were reliable predictors of holobiont respiration. There was a positive association between symbiont density and host CS specific activity (mg protein(-1)), and a negative correlation between host- and symbiont CS specific activities. Notably, partitioning of total CS activity between host and symbiont in this natural E. pallida population was significantly different to the host/symbiont biomass ratio. In re-infected anemones, we found significant between-holobiont differences in the CS specific activity of the algal symbionts. Furthermore, the relationship between the partitioning of total CS activity and the host/symbiont biomass ratio differed between holobionts. These data have broad implications for our understanding of cnidarian-algal symbiosis. Specifically, the long-held assumption of equivalency between symbiont/host biomass and respiration ratios can result in significant overestimation of symbiont respiration and potentially erroneous conclusions regarding the percentage of carbon translocated to the host. The interspecific variability in symbiont aerobic capacity provides further evidence for distinct physiological differences that should be accounted for when studying diverse host-symbiont combinations.

Distribution of CpG Motifs in Upstream Gene Domains in a Reef Coral and Sea Anemone: Implications for Epigenetics in Cnidarians.

Coral reefs are under assault from stressors including global warming, ocean acidification, and urbanization. Knowing how these factors impact the future fate of reefs requires delineating stress responses across ecological, organismal and cellular scales. Recent advances in coral reef biology have integrated molecular processes with ecological fitness and have identified putative suites of temperature acclimation genes in a Scleractinian coral Acropora hyacinthus. We wondered what unique characteristics of these genes determined their coordinate expression in response to temperature acclimation, and whether or not other corals and cnidarians would likewise possess these features. Here, we focus on cytosine methylation as an epigenetic DNA modification that is responsive to environmental stressors. We identify common conserved patterns of cytosine-guanosine dinucleotide (CpG) motif frequencies in upstream promoter domains of different functional gene groups in two cnidarian genomes: a coral (Acropora digitifera) and an anemone (Nematostella vectensis). Our analyses show that CpG motif frequencies are prominent in the promoter domains of functional genes associated with environmental adaptation, particularly those identified in A. hyacinthus. Densities of CpG sites in upstream promoter domains near the transcriptional start site (TSS) are 1.38x higher than genomic background levels upstream of -2000 bp from the TSS. The increase in CpG usage suggests selection to allow for DNA methylation events to occur more frequently within 1 kb of the TSS. In addition, observed shifts in CpG densities among functional groups of genes suggests a potential role for epigenetic DNA methylation within promoter domains to impact functional gene expression responses in A. digitifera and N. vectensis. Identifying promoter epigenetic sequence motifs among genes within specific functional groups establishes an approach to describe integrated cellular responses to environmental stress in reef corals and potential roles of epigenetics on survival and fitness in the face of global climate change.

DNA methylation and temperature stress in an Antarctic polychaete, Spiophanes tcherniai.

Epigenetic modifications of DNA and histones are a primary mechanism by which gene expression activities may be modified in response to environmental stimuli. Here we characterize patterns of methyl-cytosine composition in the marine polychaete Spiophanes tcherniai from McMurdo Sound, Antarctica. We cultured adult worms at two temperatures, -1.5°C (ambient control) and +4°C (warm treatment), for 4 weeks. We observed a rapid capacity for S. tcherniai organismal respiration rates and underlying catalytic rates of citrate synthase at +4°C to return to control levels in less than 4 weeks. We profiled changes in the methylation states of CpG sites in these treatments using an NGS strategy to computationally reconstruct and quantify methylation status across the genome. In our analysis we recovered 120,000 CpG sites in assembled contigs from both treatments. Of those, we were able to align 28,000 CpG sites in common between the two sample groups. In comparing these aligned sites between treatments, only 3000 (11%) evidenced a change in methylation state, but over 85% of changes involved a gain of a 5-methyl group on a CpG site (net increase in methyation). The ability to score CpG sites as partially methylated among gDNA copies in a sample opens up a new avenue for assessing DNA methylation responses to changing environments. By quantitatively distinguishing a "mixed" population of copies of one CpG site, we can begin to identify dynamic, non-binary, continuous-response reactions in DNA methylation intensity or density that previously may have been overlooked as noise.

Protein languages differ depending on microorganism lifestyle.

Few quantitative measures of genome architecture or organization exist to support assumptions of differences between microorganisms that are broadly defined as being free-living or pathogenic. General principles about complete proteomes exist for codon usage, amino acid biases and essential or core genes. Genome-wide shifts in amino acid usage between free-living and pathogenic microorganisms result in fundamental differences in the complexity of their respective proteomes that are size and gene content independent. These differences are evident across broad phylogenetic groups-a result of environmental factors and population genetic forces rather than phylogenetic distance. A novel comparative analysis of amino acid usage-utilizing linguistic analyses of word frequency in language and text-identified a global pattern of higher peptide word repetition in 376 free-living versus 421 pathogen genomes across broad ranges of genome size, G+C content and phylogenetic ancestry. This imprint of repetitive word usage indicates free-living microorganisms have a bias for repetitive sequence usage compared to pathogens. These findings quantify fundamental differences in microbial genomes relative to life-history function.

RNA-Seq reveals infection-related global gene changes in Phytophthora phaseoli, the causal agent of lima bean downy mildew.

Lima bean is an important vegetable processing crop to the mid-Atlantic USA and is highly susceptible to the oomycete pathogen Phytophthora phaseoli, which causes downy mildew. Genetic resistance and fungicides are used to manage P. phaseoli and often fail. Currently, the molecular basis of the interaction between this host and pathogen is unknown. To begin to rectify this situation, we used Illumina RNA-Seq to perform a global transcriptome analysis comparing P. phaseoli growing in culture with P. phaseoli infecting its host. Sequence reads from a total of six libraries mapped to gene models from the closely related late blight pathogen, Phytophthora infestans, resulting in 10 427 P. phaseoli genes with homology to P. infestans and expression in at least one library. Of these, 318 P. phaseoli homologues matched known or putative virulence genes in P. infestans. Two well-studied classes, RxLRs and elicitins, were up-regulated in planta, whereas the reverse was true for another class, called crinklers. These results are discussed with respect to the differences and similarities in the pathogenicity mechanisms of P. phaseoli and P. infestans.

Effects of Ag nanoparticles on survival and oxygen consumption of zebra fish embryos, Danio rerio.

Ultrafine silver (Ag) particles, defined as having one dimension in 1-100 nanometer (nm) size range, pose a unique threat to aquatic ecosystems due to their wide use in the healthcare and commercial industries. Previous studies have demonstrated some consequences of nanosilver exposure for earlier life stages of aquatic organisms, but few focus on the effects on metabolic processes such as oxygen consumption. Additionally, few authors have tackled the issue of how size, shape and composition of nanosilver particles are important in determining their level of bioactivity and biodistribution in the aquatic environment. In this study, embryos of the zebra fish, Danio rerio, (n = 2373) were exposed to varying concentrations of two Ag particle sizes, 12 and 21 nm, at time points 24 and 48 h after fertilization. The 12 nm particles were found to be more bioactive with a lethal dose 50 (LD(50)) concentration of 15.8 µg/mL compared to 50.1 µg/mL for 21 nm particles. The effective dose level (ED) was measured as 12.6 µg/mL for the 12 nm particles and 5.0 µg/mL for the 21 nm particles. Using survival curves, we found that in terms of number of particles in suspension, 21 nm particles have a greater impact on survival than 12 nm particles. Our measured respiration rates for 24 and 48 h embryos (n = 528) exposed to 0 0.02-0.14 mg/mL Ag showed no active upregulation of an energetically expensive detoxification pathway at this early point in development. Results from this study illustrate that advancements in the development of environmentally friendly nanoparticles can only occur if there is continued research to identify the most bioactive characteristics of these metallic particles.

Transcriptome and metabolite responses to predation in a South pacific soft coral.

Sinularia polydactyla, a dioecious, abundant soft coral in the South Pacific, exhibits biochemical phenotypic plasticity in secondary metabolite production in relation to predation intensity. However, it is unclear to what extent changes in secondary metabolites, such as 11beta-acetoxypukalide, may result from specific, induced pathway activities at the level of gene expression. To investigate both chemical changes and differences in mRNA diversity in response to predation stress, artificial predation experiments were conducted in situ on colonies of S. polydactyla. Multivariate statistical analyses of coral biochemical metabolites and our kinetic transcriptome profiling technique indicate that that the induction of 11beta-acetoxypukalide by predation stress likely results from the upregulation of either one dominant transcript or a very small set of transcripts, indicative of a targeted upregulation rather than a generalized, genetic stress response. Overall, this work establishes a routine method for integrating high-throughput transcriptome and metabolome data sets to allow for the identification of metabolites whose intracellular concentrations can be readily linked to gene expression events in response to specific treatments in non-model organisms.

Prevalence of Perkinsus marinus (dermo), Haplosporidium nelsoni (MSX), and QPX in bivalves of Delaware's inland bays and quantitative, high-throughput diagnosis of dermo by QPCR.

Restoration of oyster reef habitat in the Inland Bays of Delaware was accompanied by an effort to detect and determine relative abundance of the bivalve pathogens Perkinsus marinus, Haplosporidium nelsoni, and QPX. Both the oyster Crassostrea virginica and the clam Mercenaria mercenaria were sampled from the bays. In addition, oysters were deployed at eight sites around the bays as sentinels for the three parasites. Perkinsus marinus prevalence was measured with a real-time, quantitative polymerase chain reaction (PCR) methodology that enabled high-throughput detection of as few as 31 copies of the ribosomal non-transcribed spacer region in 500 ng oyster DNA. The other pathogens were assayed using PCR with species-specific primers. Perkinsus marinus was identified in Indian River Bay at moderate prevalence ( approximately 40%) in both an artificial reef and a wild oyster population whereas sentinel oysters were PCR-negative after 3-months exposure during summer and early fall. Haplosporidium nelsoni was restricted to one oyster deployed in Little Assawoman Bay. QPX and P. marinus were not detected among wild clams. While oysters in these bays have historically been under the greatest threat by MSX, it is apparent that P. marinus currently poses a greater threat to recovery of oyster aquaculture in Delaware's Inland Bays.

A functional approach to transcriptome profiling: linking gene expression patterns to metabolites that matter.

Secondary metabolites or natural products have been isolated from many marine organisms. These metabolites often have important bioactive functions; however, very little information is available regarding the biosynthesis and regulation of many secondary metabolites. At a time when use of marine-derived metabolites is rapidly expanding in industry and pharmacological fields, a better understanding of the genetic mechanisms controlling secondary metabolite production is necessary. We review the recent development of a novel transcriptome profiling methodology that allows for rapid and high-throughput screening of changes in mRNA sequence pools. The application of genomics-based techniques and the integration of both biochemical and molecular data sets in marine organisms complement ongoing drug discovery efforts.

Profiling transcriptome complexity and secondary metabolite synthesis in a benthic soft coral, Sinularia polydactyla.

Sinularia polydactyla, an abundant Indo-Pacific soft coral species, exhibits biochemical phenotypic plasticity, prompting investigations into differences in mRNA diversity and complexity in response to predation stress. Changes in transcriptome complexity of S. polydactyla cDNA libraries were measured using reannealing rate assays that employ an informatics-based analysis of kinetic profiles. This method allows for quick, high-throughput analysis of sequence complexity and has been used to compare transcriptome-level differences in other marine invertebrates. Here, S. polydactyla colonies were transplanted between two sites exhibiting high and low predation levels. Statistically significant differences between bite scar counts found on different transplant groups suggest site-specific variation in predation. Changes in mRNA pool complexity were quantified to indicate shifts in secondary metabolite concentration between treatment groups. Examining the complexity of the mRNA pool in this soft coral is one of the first steps toward understanding the mechanisms of phenotypic plasticity at a biochemical and molecular level.

Gene expression profiling of two related soft corals, Sinularia polydactyla and S. maxima, and their putative hybrid at different life-history stages.

The soft coral species, Sinularia polydactyla and Sinularia maxima are abundant in shallow coral reef habitats in Guam. Both species are gonochoric and mass spawning events can result in an apparent S. polydactyla-S. maxima hybrid exhibiting morphological characteristics of both parents. These morphological differences prompted our investigation of potential differences in gene expression patterns among these closely related species. In concert with interspecific level differences, intraspecific level differences in transcriptome diversity and complexity were also studied among juvenile, adult male, and adult female S. polydactyla colonies. To uncover these transcriptome-level differences, RNA was extracted from RNAlater(R)-preserved samples and cDNA libraries constructed using a nano-scale synthesis strategy. Changes in transcriptome complexity (mRNA sequence composition) of these libraries were measured using reannealing rate assays that employ an informatics-based analysis of kinetic profiles. This method allows for quick, high-throughput analysis of sequence complexity and has been used to compare transcriptome-level differences in other marine invertebrates. Comparisons of transcriptome data revealed diagnostic differences in the transcriptome pools. Examination of transcriptome changes in closely related species experiencing similar environmental parameters may enable us to understand developmental, morphological, and sex-specific changes in gene expression patterns.

Genome complexity and repetitive DNA in metazoans from extreme marine environments.

As genomics converges with ecology and evolution to identify the fundamental linkages between genome structure and function, genome and transcriptome complexity will need to be measured in organisms from more diverse habitats, most often in the absence of complete sequence data. Here, we describe the complexity of ten genomes measured by a novel, high-throughput fluorescence-based kinetic hybridization assay. We applied the Shannon information index, H, and a related, fluorescence-adjusted index, H(f), as unique metrics of the hybridization kinetics to complement the conventional rate constant, k. A strong, positive relationship was present between H(f), and the repetitive DNA content of five eukaryotic genomes previously determined by Cot kinetic analyses (Onchorynchus keta, Ilyanassa obsoleta, Bos taurus, Limulus polyphemus, Saccharyomyces cerevisiae). This relationship was used to characterize the complexity of previously unstudied genomic samples in five metazoan taxa from three marine environments, including deep-sea hydrothermal vents (Alvinella pompejana), the temperate subtidal (Streblospio benedicti), and Antarctic coastal bays (Sterechinus neumayeri, Odontaster validus, Tritonia antarctica). Contrary to the predictions of nucleotypic theory, Antarctic invertebrates consistently had the lowest quantities of repetitive DNA in conjunction with low metabolic rates and highly protracted rates of cell division and larval development. Conversely, hydrothermal vent species with rapid cell division and growth do not have significantly different genome sizes or particularly low amounts of repetitive DNA as compared to non-vent, deep-sea taxa. Furthermore, there appears to be a positive correlation between the temperature at which the most abundant repetitive sequence classes anneal and habitat thermal stability. Thus, our study reveals a potential shift in repetitive sequence representation between these extreme environments that may be related to genome function in species living at these different thermal regimes.

Transcriptome profiling of individual larvae of two different developmental modes in the poecilogonous polychaete Streblospio benedicti (Spionidae).

Understanding the range of biochemical and physiological phenotypes in a cohort of embryos or larvae is crucial to understanding the lifespan, dispersal potential, and recruitment success of the early life history stages of a species. In this study, a novel kinetic assay has been employed to profile the transcriptome pool complexity in individual larvae of both planktotrophic and lecithotrophic developmental modes in the poecilogonous polycheate Streblospio benedicti. Using a nano-scale synthesis strategy, the mRNA pool in a single embryo or larva can be amplified into cDNA for quantitative characterization in a high-throughput, kinetic reannealing assay in a 96-well, microtiterplate format. This assay generates transcript-pool complexity estimates at 1 degrees C temperature increments for each sample producing 3,360 quantitative measurements per 96-well plate. Measuring transcriptome complexity on 8 individual planktotrophic and 8 individual lecithotrophic larvae (with 4 duplicate assays for each individual) reveals a more complex gene expression profile in planktotrophic larvae and a lower level of interindividual variation in expression patterns in lecithotrophic larvae. Although differences in these gene expression patterns are more likely due to physiological differences between feeding and non-feeding larval types in these late-stage individuals, this is one of the first assessments of inter-individual variation in gene expression patterns in marine invertebrate larvae and indicates a large potential for developmental variability.

eXPatGen: generating dynamic expression patterns for the systematic evaluation of analytical methods.

MOTIVATION: Experimental gene expression data sets, such as those generated by microarray or gene chip experiments, typically have significant noise and complicated interconnectivities that make understanding even simple regulatory patterns difficult. Given these complications, characterizing the effectiveness of different analysis techniques to uncover network groups and structures remains a challenge. Generating simulated expression patterns with known biological features of expression complexity, diversity and interconnectivities provides a more controlled means of investigating the appropriateness of different analysis methods. A simulation-based approach can systematically evaluate different gene expression analysis techniques and provide a basis for improved methods in dynamic metabolic network reconstruction. RESULTS: We have developed an on-line simulator, called eXPatGen, to generate dynamic gene expression patterns typical of microarray experiments. eXPatGen provides a quantitative network structure to represent key biological features, including the induction, repression, and cascade regulation of messenger RNA (mRNA). The simulation is modular such that the expression model can be replaced with other representations, depending on the level of biological detail required by the user. Two example gene networks, of 25 and 100 genes respectively, were simulated. Two standard analysis techniques, clustering and PCA analysis, were performed on the resulting expression patterns in order to demonstrate how the simulator might be used to evaluate different analysis methods and provide experimental guidance for biological studies of gene expression. AVAILABILITY: http://www.che.udel.edu/eXPatGen/