A novel, high-performance random array platform for quantitative gene expression profiling

Differential Gene Expression in the Penile Cavernosum of Streptozotocin-Induced Diabetic Rats

PURPOSE

Men with diabetes mellitus (DM) often present with severe erectile dysfunction (ED). This ED is less responsive to current pharmacological therapies. If we know the upregulated or downregulated genes of diabetic ED, we can inhibit or enhance the expression of such genes through RNA or gene overexpression.

METHODS

To investigate gene changes associated with ED in type 1 DM, we examined the alterations of gene expression in the cavernosum of streptozotocin-induced diabetic rats. Specifically, we considered 11,636 genes (9,623 upregulated and 2,013 downregulated) to be differentially expressed in the diabetic rat cavernosum group (n=4) compared to the control group (n=4). The analysis of differentially expressed genes using the gene ontology (GO) classification indicated that the following were enriched: downregulated genes such as cell cycle, extracellular matrix, glycosylphosphatidylinositol-anchor biosynthesis and upregulated genes such as calcium signaling, neurotrophin signaling, apoptosis, arginine and proline metabolism, gap junction, transforming growth factor-β signaling, tight junction, vascular smooth muscle contraction, and vascular endothelial growth factor (VEGF) signaling. We examined a more than 2-fold upregulated or downregulated change in expression, using real time polymerase chain reaction. Analysis of differentially expressed genes, using the GO classification, indicated the enrichment.

RESULTS

Of the 41,105 genes initially considered, statistical filtering of the array analysis showed 9,623 upregulated genes and 2,013 downregulated genes with at least 2-fold changes in expression (P<0.05). With Bonferroni correction, SLC2A9 (solute carrier family 2 member 9), LRRC20 (leucine rick repeat containing 20), PLK1 (polo like kinase 1), and AATK (apoptosis-associated tyrosine kinase) were all 2-fold changed genes.

CONCLUSION

This study broadens the scope of candidate genes that may be relevant to the pathophysiology of diabetic ED. In particular, their enhancement or inhibition could represent a novel treatment for diabetic ED.

Mdwgan-gp: data augmentation for gene expression data based on multiple discriminator WGAN-GP

BACKGROUND

Although gene expression data play significant roles in biological and medical studies, their applications are hampered due to the difficulty and high expenses of gathering them through biological experiments. It is an urgent problem to generate high quality gene expression data with computational methods. WGAN-GP, a generative adversarial network-based method, has been successfully applied in augmenting gene expression data. However, mode collapse or over-fitting may take place for small training samples due to just one discriminator is adopted in the method.

RESULTS

In this study, an improved data augmentation approach MDWGAN-GP, a generative adversarial network model with multiple discriminators, is proposed. In addition, a novel method is devised for enriching training samples based on linear graph convolutional network. Extensive experiments were implemented on real biological data.

CONCLUSIONS

The experimental results have demonstrated that compared with other state-of-the-art methods, the MDWGAN-GP method can produce higher quality generated gene expression data in most cases.

Approaches in Gene Coexpression Analysis in Eukaryotes

Simple Summary

Genes whose expression levels rise and fall similarly in a large set of samples, may be considered coexpressed. Gene coexpression analysis refers to the en masse discovery of coexpressed genes from a large variety of transcriptomic experiments. The type of biological networks that studies gene coexpression, known as Gene Coexpression Networks, consist of an undirected graph depicting genes and their coexpression relationships. Coexpressed genes are clustered in smaller subnetworks, the predominant biological roles of which can be determined through enrichment analysis. By studying well-annotated gene partners, the attribution of new roles to genes of unknown function or assumption for participation in common metabolic pathways can be achieved, through a guilt-by-association approach. In this review, we present key issues in gene coexpression analysis, as well as the most popular tools that perform it.

Abstract

Gene coexpression analysis constitutes a widely used practice for gene partner identification and gene function prediction, consisting of many intricate procedures. The analysis begins with the collection of primary transcriptomic data and their preprocessing, continues with the calculation of the similarity between genes based on their expression values in the selected sample dataset and results in the construction and visualisation of a gene coexpression network (GCN) and its evaluation using biological term enrichment analysis. As gene coexpression analysis has been studied extensively, we present most parts of the methodology in a clear manner and the reasoning behind the selection of some of the techniques. In this review, we offer a comprehensive and comprehensible account of the steps required for performing a complete gene coexpression analysis in eukaryotic organisms. We comment on the use of RNA-Seq vs. microarrays, as well as the best practices for GCN construction. Furthermore, we recount the most popular webtools and standalone applications performing gene coexpression analysis, with details on their methods, features and outputs.

Identification of differentially expressed genes and signaling pathways in human conjunctiva and reproductive tract infected with Chlamydia trachomatis

Background

Currently, Chlamydia trachomatis–specific host defense mechanisms in humans remain poorly defined. To study the characteristics of host cells infected early with Chlamydia trachomatis, we used bioinformatics methods to analyze the RNA transcription profiles of the conjunctiva, fallopian tubes, and endometrium in humans infected with Chlamydia trachomatis.

Method

The gene expression profiles of GSE20430, GSE20436, GSE26692, and GSE41075 were downloaded from the Gene Expression Synthesis (GEO) database. Then, we obtained the differentially expressed genes (DEGs) through the R 4.0.1 software. STRING was used to construct protein–protein interaction (PPI) networks; then, the Cytoscape 3.7.2 software was used to visualize the PPI and screen hub genes. GraphPad Prism 8.0 software was used to verify the expression of the hub gene. In addition, the gene–miRNA interaction was constructed on the NetworkAnalyst 3.0 platform using the miRTarBase v8.0 database.

Results

A total of 600 and 135 DEGs were screened out in the conjunctival infection group and the reproductive tract infection group, respectively. After constructing a PPI network and verifying the hub genes, CSF2, CD40, and CSF3 in the reproductive tract infection group proved to have considerable statistical significance.

Conclusion

In our research, the key genes in the biological process of reproductive tract infection with Chlamydia trachomatis were clarified through bioinformatics analysis. These hub genes may be further used in clinical treatment and clinical diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40246-021-00313-8.

The GPR120 agonist TUG-891 promotes metabolic health by stimulating mitochondrial respiration in brown fat

Brown adipose tissue (BAT) activation stimulates energy expenditure in human adults, which makes it an attractive target to combat obesity and related disorders. Recent studies demonstrated a role for G protein-coupled receptor 120 (GPR120) in BAT thermogenesis. Here, we investigated the therapeutic potential of GPR120 agonism and addressed GPR120-mediated signaling in BAT We found that activation of GPR120 by the selective agonist TUG-891 acutely increases fat oxidation and reduces body weight and fat mass in C57Bl/6J mice. These effects coincided with decreased brown adipocyte lipid content and increased nutrient uptake by BAT, confirming increased BAT activity. Consistent with these observations, GPR120 deficiency reduced expression of genes involved in nutrient handling in BAT Stimulation of brown adipocytes in vitro with TUG-891 acutely induced O₂ consumption, through GPR120-dependent and GPR120-independent mechanisms. TUG-891 not only stimulated GPR120 signaling resulting in intracellular calcium release, mitochondrial depolarization, and mitochondrial fission, but also activated UCP1. Collectively, these data suggest that activation of brown adipocytes with the GPR120 agonist TUG-891 is a promising strategy to increase lipid combustion and reduce obesity.

Signalling mechanisms underlying doxorubicin and Nox2 NADPH oxidase-induced cardiomyopathy: involvement of mitofusin-2

BACKGROUND AND PURPOSE

The anthracycline doxorubicin (DOX), although successful as a first-line cancer treatment, induces cardiotoxicity linked with increased production of myocardial ROS, with Nox2 NADPH oxidase-derived superoxide reported to play a key role. The aim of this study was to identify novel mechanisms underlying development of cardiac remodelling/dysfunction further to DOX-stimulated Nox2 activation.

EXPERIMENTAL APPROACH

Nox2-/- and wild-type (WT) littermate mice were administered DOX (12 mg·kg-1 over 3 weeks) prior to study at 4 weeks. Detailed mechanisms were investigated in murine HL-1 cardiomyocytes, employing a robust model of oxidative stress, gene silencing and pharmacological tools.

KEY RESULTS

DOX-induced cardiac dysfunction, cardiomyocyte remodelling, superoxide production and apoptosis in WT mice were attenuated in Nox2-/- mice. Transcriptional analysis of left ventricular tissue identified 152 differentially regulated genes (using adjusted P < 0.1) in DOX-treated Nox2-/- versus WT mice, and network analysis highlighted 'Cell death and survival' as the biological function most significant to the dataset. The mitochondrial membrane protein, mitofusin-2 (Mfn2), appeared as a strong candidate, with increased expression (1.5-fold), confirmed by qPCR (1.3-fold), matching clear published evidence of promotion of cardiomyocyte cell death. In HL-1 cardiomyocytes, targeted siRNA knockdown of Nox2 decreased Mfn2 protein expression, but not vice versa. While inhibition of Nox2 activity along with DOX treatment attenuated its apoptotic and cytotoxic effects, reduced apoptosis after Mfn2 silencing reflected a sustained cytotoxic response and reduced cell viability.

CONCLUSIONS AND IMPLICATIONS

DOX-induced and Nox2-mediated up-regulation of Mfn2, rather than contributing to cardiomyocyte dysfunction through apoptotic pathways, appears to promote a protective mechanism.

LINKED ARTICLES

This article is part of a themed section on New Insights into Cardiotoxicity Caused by Chemotherapeutic Agents. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.21/issuetoc.

Nijmegen Breakage Syndrome fibroblasts and iPSCs: cellular models for uncovering disease-associated signaling pathways and establishing a screening platform for anti-oxidants

Nijmegen Breakage Syndrome (NBS) is associated with cancer predisposition, premature aging, immune deficiency, microcephaly and is caused by mutations in the gene coding for NIBRIN (NBN) which is involved in DNA damage repair. Dermal-derived fibroblasts from NBS patients were reprogrammed into induced pluripotent stem cells (iPSCs) in order to bypass premature senescence. The influence of antioxidants on intracellular levels of ROS and DNA damage were screened and it was found that EDHB-an activator of the hypoxia pathway, decreased DNA damage in the presence of high oxidative stress. Furthermore, NBS fibroblasts but not NBS-iPSCs were found to be more susceptible to the induction of DNA damage than their healthy counterparts. Global transcriptome analysis comparing NBS to healthy fibroblasts and NBS-iPSCs to embryonic stem cells revealed regulation of P53 in NBS fibroblasts and NBS-iPSCs. Cell cycle related genes were down-regulated in NBS fibroblasts. Furthermore, oxidative phosphorylation was down-regulated and glycolysis up-regulated specifically in NBS-iPSCs compared to embryonic stem cells. Our study demonstrates the utility of NBS-iPSCs as a screening platform for anti-oxidants capable of suppressing DNA damage and a cellular model for studying NBN de-regulation in cancer and microcephaly.

Single-Step Imprinting of Femtoliter Microwell Arrays Allows Digital Bioassays with Attomolar Limit of Detection

Bead-based microwell array technology is growing as an ultrasensitive analysis tool as exemplified by the successful commercial applications from Illumina and Quanterix for nucleic acid analysis and ultrasensitive protein measurements, respectively. High-efficiency seeding of magnetic beads is key for these applications and is enhanced by hydrophilic-in-hydrophobic microwell arrays, which are unfortunately often expensive or labor-intensive to manufacture. Here, we demonstrate a new single-step manufacturing approach for imprinting cheap and disposable hydrophilic-in-hydrophobic microwell arrays suitable for digital bioassays. Imprinting of arrays with hydrophilic-in-hydrophobic microwells is made possible using an innovative surface energy replication approach by means of a hydrophobic thiol-ene polymer formulation. In this polymer, hydrophobic-moiety-containing monomers self-assemble at the hydrophobic surface of the imprinting stamp, which results in a hydrophobic replica surface after polymerization. After removing the stamp, microwells with hydrophobic walls and a hydrophilic bottom are obtained. We demonstrate that the hydrophilic-in-hydrophobic imprinted microwell arrays enable successful and efficient self-assembly of individual water droplets and seeding of magnetic beads with loading efficiencies up to 96%. We also demonstrate the suitability of the microwell arrays for the isolation and digital counting of single molecules achieving a limit of detection of 17.4 aM when performing a streptavidin-biotin binding assay as model system. Since this approach is up-scalable through reaction injection molding, we expect it will contribute substantially to the translation of ultrasensitive digital microwell array technology toward diagnostic applications.

A Synthetic Kinome Microarray Data Generator

Cellular pathways involve the phosphorylation and dephosphorylation of proteins. Peptide microarrays called kinome arrays facilitate the measurement of the phosphorylation activity of hundreds of proteins in a single experiment. Analyzing the data from kinome microarrays is a multi-step process. Typically, various techniques are possible for a particular step, and it is necessary to compare and evaluate them. Such evaluations require data for which correct analysis results are known. Unfortunately, such kinome data is not readily available in the community. Further, there are no established techniques for creating artificial kinome datasets with known results and with the same characteristics as real kinome datasets. In this paper, a methodology for generating synthetic kinome array data is proposed. The methodology relies on actual intensity measurements from kinome microarray experiments and preserves their subtle characteristics. The utility of the methodology is demonstrated by evaluating methods for eliminating heterogeneous variance in kinome microarray data. Phosphorylation intensities from kinome microarrays often exhibit such heterogeneous variance and its presence can negatively impact downstream statistical techniques that rely on homogeneity of variance. It is shown that using the output from the proposed synthetic data generator, it is possible to critically compare two variance stabilization methods.

A user-friendly workflow for analysis of Illumina gene expression bead array data available at the arrayanalysis.org portal

BACKGROUND

Illumina whole-genome expression bead arrays are a widely used platform for transcriptomics. Most of the tools available for the analysis of the resulting data are not easily applicable by less experienced users. ArrayAnalysis.org provides researchers with an easy-to-use and comprehensive interface to the functionality of R and Bioconductor packages for microarray data analysis. As a modular open source project, it allows developers to contribute modules that provide support for additional types of data or extend workflows.

RESULTS

To enable data analysis of Illumina bead arrays for a broad user community, we have developed a module for ArrayAnalysis.org that provides a free and user-friendly web interface for quality control and pre-processing for these arrays. This module can be used together with existing modules for statistical and pathway analysis to provide a full workflow for Illumina gene expression data analysis. The module accepts data exported from Illumina's GenomeStudio, and provides the user with quality control plots and normalized data. The outputs are directly linked to the existing statistics module of ArrayAnalysis.org, but can also be downloaded for further downstream analysis in third-party tools.

CONCLUSIONS

The Illumina bead arrays analysis module is available at http://www.arrayanalysis.org . A user guide, a tutorial demonstrating the analysis of an example dataset, and R scripts are available. The module can be used as a starting point for statistical evaluation and pathway analysis provided on the website or to generate processed input data for a broad range of applications in life sciences research.

Applying genome-wide gene-based expression quantitative trait locus mapping to study population ancestry and pharmacogenetics

BACKGROUND

Gene-based analysis has become popular in genomic research because of its appealing biological and statistical properties compared with those of a single-locus analysis. However, only a few, if any, studies have discussed a mapping of expression quantitative trait loci (eQTL) in a gene-based framework. Neither study has discussed ancestry-informative eQTL nor investigated their roles in pharmacogenetics by integrating single nucleotide polymorphism (SNP)-based eQTL (s-eQTL) and gene-based eQTL (g-eQTL).

RESULTS

In this g-eQTL mapping study, the transcript expression levels of genes (transcript-level genes; T-genes) were correlated with the SNPs of genes (sequence-level genes; S-genes) by using a method of gene-based partial least squares (PLS). Ancestry-informative transcripts were identified using a rank-score-based multivariate association test, and ancestry-informative eQTL were identified using Fisher's exact test. Furthermore, key ancestry-predictive eQTL were selected in a flexible discriminant analysis. We analyzed SNPs and gene expression of 210 independent people of African-, Asian- and European-descent. We identified numerous cis- and trans-acting g-eQTL and s-eQTL for each population by using PLS. We observed ancestry information enriched in eQTL. Furthermore, we identified 2 ancestry-informative eQTL associated with adverse drug reactions and/or drug response. Rs1045642, located on MDR1, is an ancestry-informative eQTL (P = 2.13E-13, using Fisher's exact test) associated with adverse drug reactions to amitriptyline and nortriptyline and drug responses to morphine. Rs20455, located in KIF6, is an ancestry-informative eQTL (P = 2.76E-23, using Fisher's exact test) associated with the response to statin drugs (e.g., pravastatin and atorvastatin). The ancestry-informative eQTL of drug biotransformation genes were also observed; cross-population cis-acting expression regulators included SPG7, TAP2, SLC7A7, and CYP4F2. Finally, we also identified key ancestry-predictive eQTL and established classification models with promising training and testing accuracies in separating samples from close populations.

CONCLUSIONS

In summary, we developed a gene-based PLS procedure and a SAS macro for identifying g-eQTL and s-eQTL. We established data archives of eQTL for global populations. The program and data archives are accessible at http://www.stat.sinica.edu.tw/hsinchou/genetics/eQTL/HapMapII.htm. Finally, the results from our investigations regarding the interrelationship between eQTL, ancestry information, and pharmacodynamics provide rich resources for future eQTL studies and practical applications in population genetics and medical genetics.

Adoption of array technologies into the clinical laboratory

Array-based methods are making substantial contributions to the discovery of disease biomarkers and are fueling the growth of multianalyte testing for disease diagnosis and treatment. The distillation of high-density array results into sets of signature markers promises to improve disease staging, risk stratification and treatment decisions. To accommodate the growing requirement for multiplex testing, clinical laboratories are converting several single-analyte tests into array-based formats. However, adoption of array technologies provides several challenges to the laboratory, which must evaluate these new formats, train laboratory personnel, market the new services and obtain reimbursement for new analytes. Liquid-bead arrays are an attractive format for routine clinical diagnostics due to a combination of appropriate analyte density, simultaneous array decoding and detection, and flexibility for rapid customization. In this review, the suitability of several array platforms to diagnostic testing and applications of liquid-bead arrays for cystic fibrosis testing, multidisease carrier status assays and leukemia subtyping are discussed. As our understanding of the clinical utility of new or established biomarkers and recommendations for testing change, flexibility and adaptability of array platforms will be imperative. Future development of novel assay formats and improved quantitation will expand the number of diseases tested and lead to further integration into the diagnostic laboratory.

Cross-platform prediction of gene expression signatures

Gene expression signatures can predict the activation of oncogenic pathways and other phenotypes of interest via quantitative models that combine the expression levels of multiple genes. However, as the number of platforms to measure genome-wide gene expression proliferates, there is an increasing need to develop models that can be ported across diverse platforms. Because of the range of technologies that measure gene expression, the resulting signal values can vary greatly. To understand how this variation can affect the prediction of gene expression signatures, we have investigated the ability of gene expression signatures to predict pathway activation across Affymetrix and Illumina microarrays. We hybridized the same RNA samples to both platforms and compared the resultant gene expression readings, as well as the signature predictions. Using a new approach to map probes across platforms, we found that the genes in the signatures from the two platforms were highly similar, and that the predictions they generated were also strongly correlated. This demonstrates that our method can map probes from Affymetrix and Illumina microarrays, and that this mapping can be used to predict gene expression signatures across platforms.

Understanding cooperativity of microRNAs via microRNA association networks

Background

MicroRNAs (miRNAs) are key components in post-transcriptional gene regulation in multicellular organisms. As they control cooperatively a large number of their target genes, they affect the complexity of gene regulation. One of the challenges to understand miRNA-mediated regulation is to identify co-regulating miRNAs that simultaneously regulate their target genes in a network perspective.

Results

We created miRNA association network by using miRNAs sharing target genes based on sequence complementarity and co-expression patterns of miRNA-target pairs. The degree of association between miRNAs can be assessed by the level of concordance between targets of miRNAs. Cooperatively regulating miRNAs have been identified by network topology-based approach. Cooperativity of miRNAs is evaluated by their shared transcription factors and functional coherence of target genes. Pathway enrichment analysis of target genes in the cooperatively regulating miRNAs revealed the mutually exclusive functional landscape of miRNA cooperativity. In addition, we found that one miRNA in the miRNA association network could be involved in many cooperatively regulating miRNAs in a condition-specific and combinatorial manner. Sequence and structural similarity analysis within miRNA association network showed that pre-miRNA secondary structure may be involved in the expression of mature miRNA's function.

Conclusions

On the system level, we identified cooperatively regulating miRNAs in the miRNA association network. We showed that the secondary structures of pre-miRNAs in cooperatively regulating miRNAs are highly similar. This study demonstrates the potential importance of the secondary structures of pre-miRNAs in both cooperativity and specificity of target genes.

In vitro three-dimensional modeling of fallopian tube secretory epithelial cells

Background

Fallopian tube secretory epithelial cells (FTSECs) have been implicated as a cell-of-origin for high-grade serous epithelial ovarian cancer. However, there are relatively few in vitro models of this tissue type available for use in studies of FTSEC biology and malignant transformation. In vitro three-dimensional (3D) cell culture models aim to recreate the architecture and geometry of tissues in vivo and restore the complex network of cell-cell/cell-matrix interactions that occur throughout the surface of the cell membrane.

Results

We have established and characterized 3D spheroid culture models of primary FTSECs. FTSEC spheroids contain central cores of hyaline matrix surrounded by mono- or multi-layer epithelial sheets. We found that 3D culturing alters the molecular characteristics of FTSECs compared to 2D cultures of the same cells. Gene expression profiling identified more than a thousand differentially expressed genes between 3D and 2D cultures of the same FTSEC lines. Pathways significantly under-represented in 3D FTSEC cultures were associated with cell cycle progression and DNA replication. This was also reflected in the reduced proliferative indices observed in 3D spheroids stained for the proliferation marker MIB1. Comparisons with gene expression profiles of fresh fallopian tube tissues revealed that 2D FTSEC cultures clustered with follicular phase tubal epithelium, whereas 3D FTSEC cultures clustered with luteal phase samples.

Conclusions

This 3D model of fallopian tube secretory epithelial cells will advance our ability to study the underlying biology and etiology of fallopian tube tissues and the pathogenesis of high-grade serous epithelial ovarian cancer.

Size based sorting and patterning of microbeads by evaporation driven flow in a 3D micro-traps array

We present a three-dimensional (3D) micro-traps array for size selective sorting and patterning of microbeads via evaporation-driven capillary flow. The interconnected micro-traps array was manufactured by silicon micromachining. Microliters of aqueous solution containing particle mixtures of different sized (0.2 to 20 μm diameter) beads were dispensed onto the micro-traps substrate. The smaller particles spontaneously wicked towards the periphery of the chip, while the larger beads were orderly docked within the micro-traps array.

Distinct gene expression signatures in lynch syndrome and familial colorectal cancer type x

Introduction

Heredity is estimated to cause at least 20% of colorectal cancer. The hereditary nonpolyposis colorectal cancer subset is divided into Lynch syndrome and familial colorectal cancer type X (FCCTX) based on presence of mismatch repair (MMR) gene defects.

Purpose

We addressed the gene expression signatures in colorectal cancer linked to Lynch syndrome and FCCTX with the aim to identify candidate genes and to map signaling pathways relevant in hereditary colorectal carcinogenesis.

Experimental design

The 18 k whole-genome c-DNA-mediated annealing, selection, extension, and ligation (WG-DASL) assay was applied to 123 colorectal cancers, including 39 Lynch syndrome tumors and 37 FCCTX tumors. Target genes were technically validated using real-time quantitative RT-PCR (qRT-PCR) and the expression signature was validated in independent datasets.

Results

Colorectal cancers linked to Lynch syndrome and FCCTX showed distinct gene expression profiles, which by significance analysis of microarrays (SAM) differed by 2188 genes. Functional pathways involved were related to G-protein coupled receptor signaling, oxidative phosphorylation, and cell cycle function and mitosis. qRT-PCR verified altered expression of the selected genes NDUFA9, AXIN2, MYC, DNA2 and H2AFZ. Application of the 2188-gene signature to independent datasets showed strong correlation to MMR status.

Conclusion

Distinct genetic profiles and deregulation of different canonical pathways apply to Lynch syndrome and FCCTX and key targets herein may be relevant to pursue for refined diagnostic and therapeutic strategies in hereditary colorectal cancer.

Dynamic microbead arrays for biosensing applications

In this paper we present the development of an optical tweezers platform capable of creating on-demand dynamic microbead arrays for the multiplexed detection of biomolecules. We demonstrate the use of time-shared optical tweezers to dynamically assemble arrays of sensing microspheres, while simultaneously recording fluorescence signals in real time. The detection system is able to achieve multiplexing by using quantum dot nanocrystals as both signaling probes and encoding labels on the surface of the trapped microbeads. The encoding can be further extended by using a range of bead sizes. Finally, the platform is used to detect and identify three genes expressed by pathogenic strains of Escherichia coli O157:H7. The in situ actuation enabled by the optical tweezers, combined with multiplexed fluorescence detection offers a new tool, readily adaptable to biosensing applications in microfluidic devices, and could potentially enable the development of on-demand diagnostics platforms.

Evaluation of Different Normalization and Analysis Procedures for Illumina Gene Expression Microarray Data Involving Small Changes

While Illumina microarrays can be used successfully for detecting small gene expression changes due to their high degree of technical replicability, there is little information on how different normalization and differential expression analysis strategies affect outcomes. To evaluate this, we assessed concordance across gene lists generated by applying different combinations of normalization strategy and analytical approach to two Illumina datasets with modest expression changes. In addition to using traditional statistical approaches, we also tested an approach based on combinatorial optimization. We found that the choice of both normalization strategy and analytical approach considerably affected outcomes, in some cases leading to substantial differences in gene lists and subsequent pathway analysis results. Our findings suggest that important biological phenomena may be overlooked when there is a routine practice of using only one approach to investigate all microarray datasets. Analytical artefacts of this kind are likely to be especially relevant for datasets involving small fold changes, where inherent technical variation-if not adequately minimized by effective normalization-may overshadow true biological variation. This report provides some basic guidelines for optimizing outcomes when working with Illumina datasets involving small expression changes.

Investigation of transcriptional responses of juvenile mouse bone marrow to power frequency magnetic fields

To seek alterations in gene transcription in bone marrow cells following in vivo exposure of juvenile mice to power frequency magnetic fields, young (21-24-day old) C57BL/6 mice were exposed to a 100μT 50Hz magnetic field for 2h. Transcription was analysed by three methods, High Coverage Expression Profiling (HiCEP), Illumina microarrays and quantitative real-time polymerase chain reaction (QRT-PCR). A pilot HiCEP experiment with 6 exposed (E) and 6 non-exposed (NE) mice identified four candidate responsive transcripts (two unknown transcripts (AK152075 and F10-NED), phosphatidylinositol binding clathrin assembly protein (Picalm) and exportin 7 (Xpo7)). A larger experiment compared 19 E and 15 NE mice using two independent QRT-PCR assays and repeated microarray assays. No significant field-dependent changes were seen, although Picalm showed a trend to significance in one QRT-PCR assay (E/NE=0.91; P=0.06). However, the study was underpowered to detect an effect of this magnitude (52% power at P=0.05). These data indicate the current experimental constraints in detecting small changes in transcription that may occur in response to magnetic fields. These constraints result from technical limitations in the accuracy of assays and biological variation, which together were sufficient to account statistically for the number of differentially expressed transcripts identified in the pilot experiment.

Identification of biomarkers of human skin ageing in both genders. Wnt signalling - a label of skin ageing?

The goal of our work has been to investigate the mechanisms of gender-independent human skin ageing and examine the hypothesis of skin being an adequate model of global ageing. For this purpose, whole genome gene profiling was employed in sun-protected skin obtained from European Caucasian young and elderly females (mean age 26.7±4 years [n1 = 7] and 70.75±3.3 years [n2 = 4], respectively) and males (mean age 25.8±5.2 years [n3 = 6] and 76±3.8 years [n4 = 7], respectively) using the Illumina array platform. Confirmation of gene regulation was performed by real-time RT-PCR and immunohistochemistry. 523 genes were significantly regulated in female skin and 401 genes in male skin for the chosen criteria. Of these, 183 genes exhibited increased and 340 decreased expression in females whereas 210 genes showed increased and 191 decreased expression in males with age. In total, 39 genes were common in the target lists of significant regulated genes in males and females. 35 of these genes showed increased (16) or decreased (19) expression independent of gender. Only 4 overlapping genes (OR52N2, F6FR1OP2, TUBAL3 and STK40) showed differential regulation with age. Interestingly, Wnt signalling pathway showed to be significantly downregulated in aged skin with decreased gene and protein expression for males and females, accordingly. In addition, several genes involved in central nervous system (CNS) ageing (f.i. APP, TAU) showed to be expressed in human skin and were significanlty regulated with age. In conclusion, our study provides biomarkers of endogenous human skin ageing in both genders and highlight the role of Wnt signalling in this process. Furthermore, our data give evidence that skin could be used as a good alternative to understand ageing of different tissues such as CNS.

Sex-biased genetic effects on gene regulation in humans

Human regulatory variation, reported as expression quantitative trait loci (eQTLs), contributes to differences between populations and tissues. The contribution of eQTLs to differences between sexes, however, has not been investigated to date. Here we explore regulatory variation in females and males and demonstrate that 12%–15% of autosomal eQTLs function in a sex-biased manner. We show that genes possessing sex-biased eQTLs are expressed at similar levels across the sexes and highlight cases of genes controlling sexually dimorphic and shared traits that are under the control of distinct regulatory elements in females and males. This study illustrates that sex provides important context that can modify the effects of functional genetic variants.

Genetics of gene expression responses to temperature stress in a sea urchin gene network

Stress responses play an important role in shaping species distributions and robustness to climate change. We investigated how stress responses alter the contribution of additive genetic variation to gene expression during development of the purple sea urchin, Strongylocentrotus purpuratus, under increased temperatures that model realistic climate change scenarios. We first measured gene expression responses in the embryos by RNA-seq to characterize molecular signatures of mild, chronic temperature stress in an unbiased manner. We found that an increase from 12 to 18 °C caused widespread alterations in gene expression including in genes involved in protein folding, RNA processing and development. To understand the quantitative genetic architecture of this response, we then focused on a well-characterized gene network involved in endomesoderm and ectoderm specification. Using a breeding design with wild-caught individuals, we measured genetic and gene-environment interaction effects on 72 genes within this network. We found genetic or maternal effects in 33 of these genes and that the genetic effects were correlated in the network. Fourteen network genes also responded to higher temperatures, but we found no significant genotype-environment interactions in any of the genes. This absence may be owing to an effective buffering of the temperature perturbations within the network. In support of this hypothesis, perturbations to regulatory genes did not affect the expression of the genes that they regulate. Together, these results provide novel insights into the relationship between environmental change and developmental evolution and suggest that climate change may not expose large amounts of cryptic genetic variation to selection in this species.

Regulation of gene expression with thyroid hormone in rats with myocardial infarction

Introduction

The expression of hundreds of genes is altered in response to left ventricular (LV) remodeling following large transmural myocardial infarction (MI). Thyroid hormone (TH) improves LV remodeling and cardiac performance after MI. However, the molecular basis is unknown.

Methods

MI was produced by ligation of the left anterior descending coronary artery in female SD rats. Rats were divided into the following groups: (1) Sham MI, (2) MI, and (3) MI+T4 treatment (T4 pellet 3.3 mg, 60 days release, implanted subcutaneously immediately following MI). Four weeks after surgery, total RNA was isolated from LV non-infarcted areas for microarray analysis using the Illumina RatRef-12 Expression BeadChip Platform.

Results

Signals were detected in 13,188 genes (out of 22,523), of which the expression of 154 genes were decreased and the expression of 200 genes were increased in MI rats compared with Sham MI rats (false discovery rate (FDR) <0.05). Compared to MI rats, T4 treatment decreased expression of 27 genes and increased expression of 28 genes. In particular, 6 genes down-regulated by MI and 12 genes up-regulated by MI were reversed by T4. Most of the 55 genes altered by T4 treatment are in the category of molecular function under binding (24) and biological processes which includes immune system process (9), multi-organism process (5) and biological regulation (19) nonexclusively.

Conclusions

These results suggest that altered expression of genes for molecular function and biological process may be involved in the beneficial effects of thyroid hormone treatment following MI in rats.

Gene expression profiles in white blood cells of volunteers exposed to a 50 Hz electromagnetic field

Consistent and independently replicated laboratory evidence to support a causative relationship between environmental exposure to extremely low-frequency electromagnetic fields (EMFs) at power line frequencies and the associated increase in risk of childhood leukemia has not been obtained. In particular, although gene expression responses have been reported in a wide variety of cells, none has emerged as robust, widely replicated effects. DNA microarrays facilitate comprehensive searches for changes in gene expression without a requirement to select candidate responsive genes. To determine if gene expression changes occur in white blood cells of volunteers exposed to an ELF-EMF, each of 17 pairs of male volunteers age 20-30 was subjected either to a 50 Hz EMF exposure of 62.0 ± 7.1 μT for 2 h or to a sham exposure (0.21 ± 0.05 μT) at the same time (11:00 a.m. to 13:00 p.m.). The alternative regime for each volunteer was repeated on the following day and the two-day sequence was repeated 6 days later, with the exception that a null exposure (0.085 ± 0.01 μT) replaced the sham exposure. Five blood samples (10 ml) were collected at 2 h intervals from 9:00 to 17:00 with five additional samples during the exposure and sham or null exposure periods on each study day. RNA samples were pooled for the same time on each study day for the group of 17 volunteers that were subjected to the ELF-EMF exposure/sham or null exposure sequence and were analyzed on Illumina microarrays. Time courses for 16 mammalian genes previously reported to be responsive to ELF-EMF exposure, including immediate early genes, stress response, cell proliferation and apoptotic genes were examined in detail. No genes or gene sets showed consistent response profiles to repeated ELF-EMF exposures. A stress response was detected as a transient increase in plasma cortisol at the onset of either exposure or sham exposure on the first study day. The cortisol response diminished progressively on subsequent exposures or sham exposures, and was attributable to mild stress associated with the experimental protocol.

Recurrent variations in DNA methylation in human pluripotent stem cells and their differentiated derivatives

Human pluripotent stem cells (hPSCs) are potential sources of cells for modeling disease and development, drug discovery, and regenerative medicine. However, it is important to identify factors that may impact the utility of hPSCs for these applications. In an unbiased analysis of 205 hPSC and 130 somatic samples, we identified hPSC-specific epigenetic and transcriptional aberrations in genes subject to X chromosome inactivation (XCI) and genomic imprinting, which were not corrected during directed differentiation. We also found that specific tissue types were distinguished by unique patterns of DNA hypomethylation, which were recapitulated by DNA demethylation during in vitro directed differentiation. Our results suggest that verification of baseline epigenetic status is critical for hPSC-based disease models in which the observed phenotype depends on proper XCI or imprinting and that tissue-specific DNA methylation patterns can be accurately modeled during directed differentiation of hPSCs, even in the presence of variations in XCI or imprinting.

Patterns of cis regulatory variation in diverse human populations

The genetic basis of gene expression variation has long been studied with the aim to understand the landscape of regulatory variants, but also more recently to assist in the interpretation and elucidation of disease signals. To date, many studies have looked in specific tissues and population-based samples, but there has been limited assessment of the degree of inter-population variability in regulatory variation. We analyzed genome-wide gene expression in lymphoblastoid cell lines from a total of 726 individuals from 8 global populations from the HapMap3 project and correlated gene expression levels with HapMap3 SNPs located in cis to the genes. We describe the influence of ancestry on gene expression levels within and between these diverse human populations and uncover a non-negligible impact on global patterns of gene expression. We further dissect the specific functional pathways differentiated between populations. We also identify 5,691 expression quantitative trait loci (eQTLs) after controlling for both non-genetic factors and population admixture and observe that half of the cis-eQTLs are replicated in one or more of the populations. We highlight patterns of eQTL-sharing between populations, which are partially determined by population genetic relatedness, and discover significant sharing of eQTL effects between Asians, European-admixed, and African subpopulations. Specifically, we observe that both the effect size and the direction of effect for eQTLs are highly conserved across populations. We observe an increasing proximity of eQTLs toward the transcription start site as sharing of eQTLs among populations increases, highlighting that variants close to TSS have stronger effects and therefore are more likely to be detected across a wider panel of populations. Together these results offer a unique picture and resource of the degree of differentiation among human populations in functional regulatory variation and provide an estimate for the transferability of complex trait variants across populations.

Teratoma formation of human embryonic stem cells in three-dimensional perfusion culture bioreactors

Teratoma formation in mice is today the most stringent test for pluripotency that is available for human pluripotent cells, as chimera formation and tetraploid complementation cannot be performed with human cells. The teratoma assay could also be applied for assessing the safety of human pluripotent cell-derived cell populations intended for therapeutic applications. In our study we examined the spontaneous differentiation behaviour of human embryonic stem cells (hESCs) in a perfused 3D multi-compartment bioreactor system and compared it with differentiation of hESCs and human induced pluripotent cells (hiPSCs) cultured in vitro as embryoid bodies and in vivo in an experimental mouse model of teratoma formation. Results from biochemical, histological/immunohistological and ultrastuctural analyses revealed that hESCs cultured in bioreactors formed tissue-like structures containing derivatives of all three germ layers. Comparison with embryoid bodies and the teratomas revealed a high degree of similarity of the tissues formed in the bioreactor to these in the teratomas at the histological as well as transcriptional level, as detected by comparative whole-genome RNA expression profiling. The 3D culture system represents a novel in vitro model that permits stable long-term cultivation, spontaneous multi-lineage differentiation and tissue formation of pluripotent cells that is comparable to in vivo differentiation. Such a model is of interest, e.g. for the development of novel cell differentiation strategies. In addition, the 3D in vitro model could be used for teratoma studies and pluripotency assays in a fully defined, controlled environment, alternatively to in vivo mouse models.

Use of non-amplified RNA samples for microarray analysis of gene expression

Demand for high quality gene expression data has driven the development of revolutionary microarray technologies. The quality of the data is affected by the performance of the microarray platform as well as how the nucleic acid targets are prepared. The most common method for target nucleic acid preparation includes in vitro transcription amplification of the sample RNA. Although this method requires a small amount of starting material and is reported to have high reproducibility, there are also technical disadvantages such as amplification bias and the long, laborious protocol. Using RNA derived from human brain, breast and colon, we demonstrate that a non-amplification method, which was previously shown to be inferior, could be transformed to a highly quantitative method with a dynamic range of five orders of magnitude. Furthermore, the correlation coefficient calculated by comparing microarray assays using non-amplified samples with qRT-PCR assays was approximately 0.9, a value much higher than when samples were prepared using amplification methods. Our results were also compared with data from various microarray platforms studied in the MicroArray Quality Control (MAQC) project. In combination with micro-columnar 3D-Gene™ microarray, this non-amplification method is applicable to a variety of genetic analyses, including biomarker screening and diagnostic tests for cancer.

Relative impact of key sources of systematic noise in Affymetrix and Illumina gene-expression microarray experiments

BACKGROUND

Systematic processing noise, which includes batch effects, is very common in microarray experiments but is often ignored despite its potential to confound or compromise experimental results. Compromised results are most likely when re-analysing or integrating datasets from public repositories due to the different conditions under which each dataset is generated. To better understand the relative noise-contributions of various factors in experimental-design, we assessed several Illumina and Affymetrix datasets for technical variation between replicate hybridisations of Universal Human Reference (UHRR) and individual or pooled breast-tumour RNA.

RESULTS

A varying degree of systematic noise was observed in each of the datasets, however in all cases the relative amount of variation between standard control RNA replicates was found to be greatest at earlier points in the sample-preparation workflow. For example, 40.6% of the total variation in reported expressions were attributed to replicate extractions, compared to 13.9% due to amplification/labelling and 10.8% between replicate hybridisations. Deliberate probe-wise batch-correction methods were effective in reducing the magnitude of this variation, although the level of improvement was dependent on the sources of noise included in the model. Systematic noise introduced at the chip, run, and experiment levels of a combined Illumina dataset were found to be highly dependent upon the experimental design. Both UHRR and pools of RNA, which were derived from the samples of interest, modelled technical variation well although the pools were significantly better correlated (4% average improvement) and better emulated the effects of systematic noise, over all probes, than the UHRRs. The effect of this noise was not uniform over all probes, with low GC-content probes found to be more vulnerable to batch variation than probes with a higher GC-content.

CONCLUSIONS

The magnitude of systematic processing noise in a microarray experiment is variable across probes and experiments, however it is generally the case that procedures earlier in the sample-preparation workflow are liable to introduce the most noise. Careful experimental design is important to protect against noise, detailed meta-data should always be provided, and diagnostic procedures should be routinely performed prior to downstream analyses for the detection of bias in microarray studies.

Estimates of array and pool-construction variance for planning efficient DNA-pooling genome wide association studies

Background

Until recently, genome-wide association studies (GWAS) have been restricted to research groups with the budget necessary to genotype hundreds, if not thousands, of samples. Replacing individual genotyping with genotyping of DNA pools in Phase I of a GWAS has proven successful, and dramatically altered the financial feasibility of this approach. When conducting a pool-based GWAS, how well SNP allele frequency is estimated from a DNA pool will influence a study's power to detect associations. Here we address how to control the variance in allele frequency estimation when DNAs are pooled, and how to plan and conduct the most efficient well-powered pool-based GWAS.

Methods

By examining the variation in allele frequency estimation on SNP arrays between and within DNA pools we determine how array variance [var(e_array)] and pool-construction variance [var(e_construction)] contribute to the total variance of allele frequency estimation. This information is useful in deciding whether replicate arrays or replicate pools are most useful in reducing variance. Our analysis is based on 27 DNA pools ranging in size from 74 to 446 individual samples, genotyped on a collective total of 128 Illumina beadarrays: 24 1M-Single, 32 1M-Duo, and 72 660-Quad.

Results

For all three Illumina SNP array types our estimates of var(e_array) were similar, between 3-4 × 10^-4 for normalized data. Var(e_construction) accounted for between 20-40% of pooling variance across 27 pools in normalized data.

Conclusions

We conclude that relative to var(e_array), var(e_construction) is of less importance in reducing the variance in allele frequency estimation from DNA pools; however, our data suggests that on average it may be more important than previously thought. We have prepared a simple online tool, PoolingPlanner (available at http://www.kchew.ca/PoolingPlanner/), which calculates the effective sample size (ESS) of a DNA pool given a range of replicate array values. ESS can be used in a power calculator to perform pool-adjusted calculations. This allows one to quickly calculate the loss of power associated with a pooling experiment to make an informed decision on whether a pool-based GWAS is worth pursuing.

An Exponential-Gamma Convolution Model for Background Correction of Illumina BeadArray Data

Illumina BeadArrays are becoming an increasingly popular Microarray platform due to its high data quality and relatively low cost. One distinct feature of Illumina BeadArrays is that each array has thousands of negative control bead types containing oligonucleotide sequences that are not specific to any target genes in the genome. This design provides a way of directly estimating the distribution of the background noise. In the literature of background correction for BeadArray data, the information from negative control beads is either ignored, used in a naive way that can lead to a loss in efficiency, or the noise is assumed to be normally distributed. However, we show with real data that the noise can be skewed. In this study we propose an exponential-gamma convolution model for background correction of Illumina BeadArray data. Using both simulated and real data examples, we show that the proposed method can improve the signal estimation and detection of differentially expressed genes when the signal to noise ratio is large and the noise has a skewed distribution.

Genetic and genomic analyses of RNA polymerase II-pausing factor in regulation of mammalian transcription and cell growth

Many mammalian genes are occupied by paused RNA polymerase II (pol II) in the promoter-proximal region on both sides of the transcription start site. However, the impact of pol II pausing on gene expression and cell biology is not fully understood. In this study, we used a Cre-Lox system to conditionally knock out the b subunit of mouse negative elongation factor (Nelf-b), a key pol II-pausing factor, in mouse embryonic fibroblasts. We found that Nelf-b was associated with the promoter-proximal region of the majority of expressed genes, yet genetic ablation of Nelf-b only affected the steady-state mRNA levels of a small percentage of the Nelf-b-associated genes. Interestingly, Nelf-b deletion also increased levels of transcription start site upstream transcripts at multiple negative elongation factor-associated genes. The direct target genes of Nelf-b were highly enriched with those involved in the control of cell growth and cell death. Correspondingly, Nelf-b knock-out mouse embryonic fibroblasts exhibited slower progression from quiescence to proliferation, as well as in a cycling cell population. Furthermore, Nelf-b deletion also resulted in increased apoptosis. Thus, the genetic and genomic studies provide new physiological and molecular insight into Nelf-mediated pol II pausing.

Activation of the immune response is a key feature of aging in mice

The process of aging is complex involving numerous factors centered on transcriptional changes with advanced age. This study was aimed at elucidating mechanisms involved in mouse aging by conducting both gene expression and biochemical analyses on isolated mouse brain, heart and kidney. The gene expression analysis was not aimed at solely highlighting age-related transcriptional changes but also revealing regulated biological processes, cellular compartments, signaling and metabolic pathways. We have uncovered a conserved increase in the expression of genes mediating immune responses in all the tissues analyzed. In addition, elevated levels of lipid hydroperoxides (LPO)—an indicator of increased levels of radical oxygen species, implicate an oxidative stress-mediated activity of NF-kB signaling. In summary, these results suggest that transcriptional changes are most probably the downstream effect of environmental and endogenous factors constantly affecting the organism during its lifetime. In addition, we propose LPO as a potential biomarker of aging.

Mechanisms underlying the radioprotective properties of γ-tocotrienol: comparative gene expression profiling in tocol-treated endothelial cells

Among the eight naturally occurring vitamin E analogs, γ-tocotrienol (GT3) is a particularly potent radioprophylactic agent in vivo. Moreover, GT3 protects endothelial cells from radiation injury not only by virtue of its antioxidant properties but also by inhibition of 3-hydroxy-3-methyl-glutaryl-CoA (HMG-CoA) reductase and by improving the availability of the nitric oxide synthase cofactor tetrahydrobiopterin. Nevertheless, the precise mechanisms underlying the superior radioprotective properties of GT3 compared with other tocols are not known. This study, therefore, examined the differences in gene expression profiles between GT3 and its tocopherol counterpart, γ-tocopherol, as well as between GT3 and α-tocopherol in human endothelial cells. Cells were treated with vehicle or the appropriate tocol for 24 h, after which total RNA was isolated and genome-wide gene expression profiles were obtained using the Illumina platform. GT3 was far more potent in inducing gene-expression changes than α-tocopherol or γ-tocopherol. In particular, GT3 induced multiple changes in pathways known to be of importance in the cellular response to radiation exposure. Affected GO functional clusters included response to oxidative stress, response to DNA damage stimuli, cell cycle phase, regulation of cell death, regulation of cell proliferation, hematopoiesis, and blood vessel development. These results form the basis for further studies to determine the exact importance of differentially affected GO functional clusters in endothelial radioprotection by GT3.

Gene networks associated with conditional fear in mice identified using a systems genetics approach

Background

Our understanding of the genetic basis of learning and memory remains shrouded in mystery. To explore the genetic networks governing the biology of conditional fear, we used a systems genetics approach to analyze a hybrid mouse diversity panel (HMDP) with high mapping resolution.

Results

A total of 27 behavioral quantitative trait loci were mapped with a false discovery rate of 5%. By integrating fear phenotypes, transcript profiling data from hippocampus and striatum and also genotype information, two gene co-expression networks correlated with context-dependent immobility were identified. We prioritized the key markers and genes in these pathways using intramodular connectivity measures and structural equation modeling. Highly connected genes in the context fear modules included Psmd6, Ube2a and Usp33, suggesting an important role for ubiquitination in learning and memory. In addition, we surveyed the architecture of brain transcript regulation and demonstrated preservation of gene co-expression modules in hippocampus and striatum, while also highlighting important differences. Rps15a, Kif3a, Stard7, 6330503K22RIK, and Plvap were among the individual genes whose transcript abundance were strongly associated with fear phenotypes.

Conclusion

Application of our multi-faceted mapping strategy permits an increasingly detailed characterization of the genetic networks underlying behavior.

Exploiting blank spots for model-based background correction in discovering genes with DNA array data

Motivated by a real data set deriving from a study on the genetic determinants of the behavior of Mycobacterium tuberculosis (MTB) hosted in macrophage, we take advantage of the presence of control spots and illustrate modelling issues for background correction and the ensuing empirical findings resulting from a Bayesian hierarchical approach to the problem of detecting differentially expressed genes. We prove the usefulness of a fully integrated approach where background correction and normalization are embedded in a single model-based framework, creating a new tailored model to account for the peculiar features of DNA array data where null expressions are planned by design. We also advocate the use of an alternative normalization device resulting from a suitable reparameterization. The new model is validated by using both simulated and our MTB data. This work suggests that the presence of a substantial fraction of exact null expressions might be the effect of an imperfect background calibration and shows how this can be suitably re-calibrated with the information coming from control spots. The proposed idea can be extended to all experiments in which a subset of genes whose expression levels can be ascribed mainly to background noise is planned by design.

Upregulation of IL17RB during natural allergen exposure in patients with seasonal allergic rhinitis

BACKGROUND

Seasonal allergic rhinitis (SAR) to Japanese cedar (Cryptomeria japonica; JC) is an IgE-mediated type I allergy affecting the nasal mucosa. However, the molecular mechanisms that underlie SAR are only partially understood. The aim of the study was to identify novel genes related to SAR during natural exposure to pollens, by using microarray analysis.

METHODS

Subjects were 32 SAR patients and 25 controls. Total RNA was extracted from CD4(+) T cells isolated from peripheral blood mononuclear cells and subjected to microarray analysis with Illumina Human Ref8 BeadChip arrays. The Mann-Whitney test was performed to identify genes whose expression was altered during allergen exposure. Quantitative real-time reverse transcription-polymerase chain reaction (RT-PCR) was performed on samples collected from SAR patients and controls to verify the microarray results.

RESULTS

Microarray analysis showed that the expression of 3 genes was significantly altered during allergen exposure. Among these 3 genes, the expression of interleukin 17 receptor beta (IL17RB) was confirmed to be upregulated in SAR patients compared to that of the IL17RB gene in healthy, non-allergic controls. The average fold change of IL17RB expression in the real-time RT-PCR experiment was 3.9 (P = 0.003).

CONCLUSIONS

The present study identified upregulation of IL17RB during natural allergen exposure in patients with SAR, which may further elucidate the molecular mechanisms underlying SAR.

An integrated genomic and epigenomic approach predicts therapeutic response to zebularine in human liver cancer

Epigenomic changes such as aberrant hypermethylation and subsequent atypical gene silencing are characteristic features of human cancer. Here, we report a comprehensive characterization of epigenomic modulation caused by zebularine, an effective DNA methylation inhibitor, in human liver cancer. Using transcriptomic and epigenomic profiling, we identified a zebularine response signature that classified liver cancer cell lines into two major subtypes with different drug responses. In drug-sensitive cell lines, zebularine caused inhibition of proliferation coupled with increased apoptosis, whereas drug-resistant cell lines showed up-regulation of oncogenic networks (for example, E2F1, MYC, and TNF) that drive liver cancer growth in vitro and in preclinical mouse models. Assessment of zebularine-based therapy in xenograft mouse models demonstrated potent therapeutic effects against tumors established from zebularine-sensitive but not zebularine-resistant liver cancer cells, leading to increased survival and decreased pulmonary metastasis. Integration of the zebularine gene expression and demethylation response signatures allowed differentiation of patients with hepatocellular carcinoma according to their survival and disease recurrence. This integrated signature identified a subclass of patients within the poor-survivor group that is likely to benefit from therapeutic agents that target the cancer epigenome.

Gene expression profiling reveals Cyp26b1 to be an activin regulated gene involved in ovarian granulosa cell proliferation

Activin, a member of the TGF-β superfamily, is an important modulator of FSH synthesis and secretion and is involved in reproductive dysfunctions and cancers. It also regulates ovarian follicle development. To understand the mechanisms and pathways by which activin regulates follicle function, we performed a microarray study and identified 240 activin regulated genes in mouse granulosa cells. The gene most strongly inhibited by activin was Cyp26b1, which encodes a P450 cytochrome enzyme that degrades retinoic acid (RA). Cyp26b1 has been shown to play an important role in male germ cell meiosis, but its expression is largely lost in the ovary around embryonic d 12.5. This study demonstrated that Cyp26b1 mRNA was expressed in granulosa cells of follicles at all postnatal developmental stages. A striking inverse spatial and temporal correlation between Cyp26b1 and activin-βA mRNA expression was observed. Cyp26b1 expression was also elevated in a transgenic mouse model that has decreased activin expression. The Cyp26 inhibitor R115866 stimulated the proliferation of primary cultured mouse granulosa cells, and a similar effect was observed with RA and activin. A pan-RA receptor inhibitor, AGN194310, abolished the stimulatory effect of either RA or activin on granulosa cell proliferation, indicating an involvement of RA receptor-mediated signaling. Overall, this study provides new insights into the mechanisms of activin action in the ovary. We conclude that Cyp26b1 is expressed in the postnatal mouse ovary, regulated by activin, and involved in the control of granulosa cell proliferation.

Microarray-Based Gene Expression Studies in Ovarian Cancer

Background

DNA microarray technology is a powerful genomic tool that has the potential to elucidate the relationship between clinical features of cancers and their underlying biological alterations.

Methods

We performed a systemic search in PubMed and Medline databases for recently published articles. The search terms used included “genome-wide,” “microarrays,” “ovarian cancer,” “prognosis” “gene expression profiling,” “molecular marker,” and “molecular biomarker.”

Results

Genome-wide expression profiling using DNA microarray technology has enhanced our understanding of the genes that influence ovarian cancer development, histopathologic subtype, progression, response to therapy, and overall survival.

Conclusions

Gene expression profiling has demonstrated its utility in ovarian cancer research. It is hoped that with technologic, statistical, and bioinformatic advances, the reliability and reproducibility of this technique will increase, spawning clinical applications that may enhance our understanding of the disease and our ability to care for patients in the future.

Multi-level mixed effects models for bead arrays

MOTIVATION

Bead arrays are becoming a popular platform for high-throughput expression arrays. However, the number of the beads targeting a transcript and the variation of their intensities differ from sample to sample in these arrays. This property results in different accuracy of expression intensities of a transcript across arrays.

RESULTS

We provide evidence, with publicly available spike-in data, that the false discovery rate of differential expression is reduced by modeling bead-level variability with a multi-level mixed effects model. We compare the performance of our proposed model to existing analysis methods for bead arrays: the unweighted t-test and other weighted methods. Additionally, we provide theoretical insights into when the multi-level mixed effects model outperforms other methods. Finally, we provide a software program for differential expression analysis using the multi-level mixed effects model that analyzes tens of thousands of genes efficiently.

AVAILABILITY

The software program is freely available on web at http://ephpublic.aecom.yu.edu/sites/rkim/Supplementary.

Preprocessing of gene expression data by optimally robust estimators

Background

The preprocessing of gene expression data obtained from several platforms routinely includes the aggregation of multiple raw signal intensities to one expression value. Examples are the computation of a single expression measure based on the perfect match (PM) and mismatch (MM) probes for the Affymetrix technology, the summarization of bead level values to bead summary values for the Illumina technology or the aggregation of replicated measurements in the case of other technologies including real-time quantitative polymerase chain reaction (RT-qPCR) platforms. The summarization of technical replicates is also performed in other "-omics" disciplines like proteomics or metabolomics.

Preprocessing methods like MAS 5.0, Illumina's default summarization method, RMA, or VSN show that the use of robust estimators is widely accepted in gene expression analysis. However, the selection of robust methods seems to be mainly driven by their high breakdown point and not by efficiency.

Results

We describe how optimally robust radius-minimax (rmx) estimators, i.e. estimators that minimize an asymptotic maximum risk on shrinking neighborhoods about an ideal model, can be used for the aggregation of multiple raw signal intensities to one expression value for Affymetrix and Illumina data. With regard to the Affymetrix data, we have implemented an algorithm which is a variant of MAS 5.0.

Using datasets from the literature and Monte-Carlo simulations we provide some reasoning for assuming approximate log-normal distributions of the raw signal intensities by means of the Kolmogorov distance, at least for the discussed datasets, and compare the results of our preprocessing algorithms with the results of Affymetrix's MAS 5.0 and Illumina's default method.

The numerical results indicate that when using rmx estimators an accuracy improvement of about 10-20% is obtained compared to Affymetrix's MAS 5.0 and about 1-5% compared to Illumina's default method. The improvement is also visible in the analysis of technical replicates where the reproducibility of the values (in terms of Pearson and Spearman correlation) is increased for all Affymetrix and almost all Illumina examples considered. Our algorithms are implemented in the R package named RobLoxBioC which is publicly available via CRAN, The Comprehensive R Archive Network (http://cran.r-project.org/web/packages/RobLoxBioC/).

Conclusions

Optimally robust rmx estimators have a high breakdown point and are computationally feasible. They can lead to a considerable gain in efficiency for well-established bioinformatics procedures and thus, can increase the reproducibility and power of subsequent statistical analysis.

Comparison of normalization methods for Illumina BeadChip HumanHT-12 v3

Background

Normalization of microarrays is a standard practice to account for and minimize effects which are not due to the controlled factors in an experiment. There is an overwhelming number of different methods that can be applied, none of which is ideally suited for all experimental designs. Thus, it is important to identify a normalization method appropriate for the experimental setup under consideration that is neither too negligent nor too stringent. Major aim is to derive optimal results from the underlying experiment. Comparisons of different normalization methods have already been conducted, none of which, to our knowledge, comparing more than a handful of methods.

Results

In the present study, 25 different ways of pre-processing Illumina Sentrix BeadChip array data are compared. Among others, methods provided by the BeadStudio software are taken into account. Looking at different statistical measures, we point out the ideal versus the actual observations. Additionally, we compare qRT-PCR measurements of transcripts from different ranges of expression intensities to the respective normalized values of the microarray data. Taking together all different kinds of measures, the ideal method for our dataset is identified.

Conclusions

Pre-processing of microarray gene expression experiments has been shown to influence further downstream analysis to a great extent and thus has to be carefully chosen based on the design of the experiment. This study provides a recommendation for deciding which normalization method is best suited for a particular experimental setup.

A data integration approach to mapping OCT4 gene regulatory networks operative in embryonic stem cells and embryonal carcinoma cells

It is essential to understand the network of transcription factors controlling self-renewal of human embryonic stem cells (ESCs) and human embryonal carcinoma cells (ECs) if we are to exploit these cells in regenerative medicine regimes. Correlating gene expression levels after RNAi-based ablation of OCT4 function with its downstream targets enables a better prediction of motif-specific driven expression modules pertinent for self-renewal and differentiation of embryonic stem cells and induced pluripotent stem cells.We initially identified putative direct downstream targets of OCT4 by employing CHIP-on-chip analysis. A comparison of three peak analysis programs revealed a refined list of OCT4 targets in the human EC cell line NCCIT, this list was then compared to previously published OCT4 CHIP-on-chip datasets derived from both ES and EC cells. We have verified an enriched POU-motif, discovered by a de novo approach, thus enabling us to define six distinct modules of OCT4 binding and regulation of its target genes.A selection of these targets has been validated, like NANOG, which harbours the evolutionarily conserved OCT4-SOX2 binding motif within its proximal promoter. Other validated targets, which do not harbour the classical HMG motif are USP44 and GADD45G, a key regulator of the cell cycle. Over-expression of GADD45G in NCCIT cells resulted in an enrichment and up-regulation of genes associated with the cell cycle (CDKN1B, CDKN1C, CDK6 and MAPK4) and developmental processes (BMP4, HAND1, EOMES, ID2, GATA4, GATA5, ISL1 and MSX1). A comparison of positively regulated OCT4 targets common to EC and ES cells identified genes such as NANOG, PHC1, USP44, SOX2, PHF17 and OCT4, thus further confirming their universal role in maintaining self-renewal in both cell types. Finally we have created a user-friendly database (http://biit.cs.ut.ee/escd/), integrating all OCT4 and stem cell related datasets in both human and mouse ES and EC cells.In the current era of systems biology driven research, we envisage that our integrated embryonic stem cell database will prove beneficial to the booming field of ES, iPS and cancer research.

Elevated myocardial Na+/H+ exchanger isoform 1 activity elicits gene expression that leads to cardiac hypertrophy

In myocardial disease, elevated expression and activity of Na(+)/H(+) exchanger isoform 1 (NHE1) are detrimental. To better understand the involvement of NHE1, transgenic mice with elevated heart-specific NHE1 expression were studied. N-line mice expressed wild-type NHE1, and K-line mice expressed activated NHE1. Cardiac morphology, interstitial fibrosis, and cardiac function were examined by histological staining and echocardiography. Differences in gene expression between the N-line or K-line and nontransgenic littermates were probed with genechip analysis. We found that NHE1 K-line (but not N-line) hearts developed hypertrophy, including elevated heart weight-to-body weight ratio and increased cross-sectional area of the cardiomyocytes, interstitial fibrosis, as well as depressed cardiac function. N-line hearts had modest changes in gene expression (50 upregulations and 99 downregulations, P < 0.05), whereas K-line hearts had a very strong transcriptional response (640 upregulations and 677 downregulations, P < 0.05). In addition, the magnitude of expression alterations was much higher in K-line than N-line mice. The most significant changes in gene expression were involved in cardiac hypertrophy, cardiac necrosis/cell death, and cardiac infarction. Secreted phosphoprotein 1 and its signaling pathways were upregulated while peroxisome proliferator-activated receptor gamma signaling was downregulated in K-line mice. Our study shows that expression of activated NHE1 elicits specific pathways of gene activation in the myocardium that lead to cardiac hypertrophy, cell death, and infarction.