Wun-Yi Shu

Identification of Human Housekeeping Genes and Tissue-Selective Genes by Microarray Meta-Analysis

Background Categorizing protein-encoding transcriptomes of normal tissues into housekeeping genes and tissue-selective genes is a fundamental step toward studies of genetic functions and genetic associations to tissue-specific diseases. Previous studies have been mainly based on a few data sets with limited samples in each tissue, which restrained the representativeness of their identified genes, and resulted in low consensus among them. Results This study compiled 1,431 samples in 43 normal human tissues from 104 microarray data sets. We developed a new method to improve gene expression assessment, and showed that more than ten samples are needed to robustly identify the protein-encoding transcriptome of a tissue. We identified 2,064 housekeeping genes and 2,293 tissue-selective genes, and analyzed gene lists by functional enrichment analysis. The housekeeping genes are mainly involved in fundamental cellular functions, and the tissue-selective genes are strikingly related to functions and diseases corresponding to tissue-origin. We also compared agreements and related functions among our housekeeping genes and those of previous studies, and pointed out some reasons for the low consensuses. Conclusions The results indicate that sufficient samples have improved the identification of protein-encoding transcriptome of a tissue. Comprehensive meta-analysis has proved the high quality of our identified HK and TS genes. These results could offer a useful resource for future research on functional and genomic features of HK and TS genes.

Identification of Reference Genes across Physiological States for qRT-PCR through Microarray Meta-Analysis

Background The accuracy of quantitative real-time PCR (qRT-PCR) is highly dependent on reliable reference gene(s). Some housekeeping genes which are commonly used for normalization are widely recognized as inappropriate in many experimental conditions. This study aimed to identify reference genes for clinical studies through microarray meta-analysis of human clinical samples. Methodology/Principal Findings After uniform data preprocessing and data quality control, 4,804 Affymetrix HU-133A arrays performed by clinical samples were classified into four physiological states with 13 organ/tissue types. We identified a list of reference genes for each organ/tissue types which exhibited stable expression across physiological states. Furthermore, 102 genes identified as reference gene candidates in multiple organ/tissue types were selected for further analysis. These genes have been frequently identified as housekeeping genes in previous studies, and approximately 71% of them fall into Gene Expression (GO:0010467) category in Gene Ontology. Conclusions/Significance Based on microarray meta-analysis of human clinical sample arrays, we identified sets of reference gene candidates for various organ/tissue types and then examined the functions of these genes. Additionally, we found that many of the reference genes are functionally related to transcription, RNA processing and translation. According to our results, researchers could select single or multiple reference gene(s) for normalization of qRT-PCR in clinical studies.

Microarray meta-analysis database (M 2 DB): a uniformly pre-processed, quality controlled, and manually curated human clinical microarray database

BackgroundOver the past decade, gene expression microarray studies have greatly expanded our knowledge of genetic mechanisms of human diseases. Meta-analysis of substantial amounts of accumulated data, by integrating valuable information from multiple studies, is becoming more important in microarray research. However, collecting data of special interest from public microarray repositories often present major practical problems. Moreover, including low-quality data may significantly reduce meta-analysis efficiency.ResultsM2DB is a human curated microarray database designed for easy querying, based on clinical information and for interactive retrieval of either raw or uniformly pre-processed data, along with a set of quality-control metrics. The database contains more than 10,000 previously published Affymetrix GeneChip arrays, performed using human clinical specimens. M2DB allows online querying according to a flexible combination of five clinical annotations describing disease state and sampling location. These annotations were manually curated by controlled vocabularies, based on information obtained from GEO, ArrayExpress, and published papers. For array-based assessment control, the online query provides sets of QC metrics, generated using three available QC algorithms. Arrays with poor data quality can easily be excluded from the query interface. The query provides values from two algorithms for gene-based filtering, and raw data and three kinds of pre-processed data for downloading.ConclusionM2DB utilizes a user-friendly interface for QC parameters, sample clinical annotations, and data formats to help users obtain clinical metadata. This database provides a lower entry threshold and an integrated process of meta-analysis. We hope that this research will promote further evolution of microarray meta-analysis.

Two-sided effect of Cordyceps sinensis on dendritic cells in different physiological stages

Cordyceps sinensis (CS), a Chinese tonifying herb, has been widely used for centuries in Asian countries as a medicine and a health supplement. Although ample evidence indicates that CS can modulate immune responses, the functional effect of CS on dendritic cells (DCs) is still unclear. This study examines how CS affects human monocyte‐derived DCs in two physiological states: naïve and LPS‐induced inflammatory. Our experimental results demonstrate that CS acts as an activator and maturation inducer of immature DCs by stimulating the expression of costimulatory molecules and proinflammatory cytokines by DCs, enhancing the DC‐induced, allogeneic T cell proliferation, and reducing the endocytic ability of DCs. In contrast, CS suppresses the LPS‐induced, inflammatory response by decreasing the LPS‐induced expression of costimulatory molecules and proinflammatory cytokines by DCs. CS also suppresses the LPS‐induced, DC‐elicited, allogeneic T cell proliferation and shifts the LPS‐activated, DC‐driven Th1 response toward a Th2 response. These results demonstrate that CS differentially regulates the DC activities according to the presence or absence of the inflammatory signs. Restated, with the lack of an ongoing inflammatory environment, CS primes DCs toward a Th1‐type immunity, whereas in a potential inflammatory reaction, CS balances the over‐reactivity of elicited Th1 immunity. This investigation illustrates the Yin‐Yang balancing effects of CS as a medicine and a health supplement.

Intra- and Inter-Individual Variance of Gene Expression in Clinical Studies

Background Variance in microarray studies has been widely discussed as a critical topic on the identification of differentially expressed genes; however, few studies have addressed the influence of estimating variance. Methodology/Principal Findings To break intra- and inter-individual variance in clinical studies down to three levels–technical, anatomic, and individual–we designed experiments and algorithms to investigate three forms of variances. As a case study, a group of “inter-individual variable genes” were identified to exemplify the influence of underestimated variance on the statistical and biological aspects in identification of differentially expressed genes. Our results showed that inadequate estimation of variance inevitably led to the inclusion of non-statistically significant genes into those listed as significant, thereby interfering with the correct prediction of biological functions. Applying a higher cutoff value of fold changes in the selection of significant genes reduces/eliminates the effects of underestimated variance. Conclusions/Significance Our data demonstrated that correct variance evaluation is critical in selecting significant genes. If the degree of variance is underestimated, “noisy” genes are falsely identified as differentially expressed genes. These genes are the noise associated with biological interpretation, reducing the biological significance of the gene set. Our results also indicate that applying a higher number of fold change as the selection criteria reduces/eliminates the differences between distinct estimations of variance.

UVB Radiation Induces Persistent Activation of Ribosome and Oxidative Phosphorylation Pathways

Abstract Tsai, M-L., Chang, K-Y., Chiang, C-S., Shu, W-Y., Weng, T-C., Chen, C. R., Huang, C-L., Lin, H-K. and Hsu, I. C. UVB Radiation Induces Persistent Activation of Ribosome and Oxidative Phosphorylation Pathways. Radiat. Res. 171, 716–724 (2009). Ultraviolet B (UVB) radiation has strong biological effects and modulates the expression of many genes. The major biological pathways affected by UVB radiation remain controversial. In this work, we used a loop-design microarray approach and applied rigorous statistical analyses to identify differentially regulated genes at 4, 8, 16 or 24 h after UVB irradiation. The most prominent biological categories in lists of differentially regulated gene sets were extracted by functional enrichment analysis. With this approach, we determined that genes participating in two prime cellular processes, the ribosome pathway and the oxidative phosphorylation pathway, were persistently activated after UVB irradiation. Mitochondrial activity assays confirmed increased activity for up to 24 h after UVB irradiation. These results suggest that the persistent activation of ribosome and oxidative phosphorylation pathways may have a key role in UVB-radiation-induced cellular responses. For the first time, the specific cellular pathways that respond to UVB radiation consistently and persistently can be delineated with confidence using a loop-design microarray approach and functional bioinformatics analysis. The results of this study offer further insight into UVB-radiation-induced stress responses.

Distinct Epidermal Keratinocytes Respond to Extremely Low-Frequency Electromagnetic Fields Differently

Following an increase in the use of electric appliances that can generate 50 or 60 Hz electromagnetic fields, concerns have intensified regarding the biological effects of extremely low-frequency electromagnetic fields (ELF-EMFs) on human health. Previous epidemiological studies have suggested the carcinogenic potential of environmental exposure to ELF-EMFs, specifically at 50 or 60 Hz. However, the biological mechanism facilitating the effects of ELF-EMFs remains unclear. Cellular studies have yielded inconsistent results regarding the biological effects of ELF-EMFs. The inconsistent results might have been due to diverse cell types. In our previous study, we indicated that 1.5 mT, 60 Hz ELF-EMFs will cause G1 arrest through the activation of the ATM-Chk2-p21 pathway in human keratinocyte HaCaT cells. The aim of the current study was to investigate whether ELF-EMFs cause similar effects in a distinct epidermal keratinocyte, primary normal human epidermal keratinocytes (NHEK), by using the same ELF-EMF exposure system and experimental design. We observed that ELF-EMFs exerted no effects on cell growth, cell proliferation, cell cycle distribution, and the activation of ATM signaling pathway in NHEK cells. We demonstrated that the 2 epidermal keratinocytes responded to ELF-EMFs differently. To further validate this finding, we simultaneously exposed the NHEK and HaCaT cells to ELF-EMFs in the same incubator for 168 h and observed the cell growths. The simultaneous exposure of the two cell types results showed that the NHEK and HaCaT cells exhibited distinct responses to ELF-EMFs. Thus, we confirmed that the biological effects of ELF-EMFs in epidermal keratinocytes are cell type specific. Our findings may partially explain the inconsistent results of previous studies when comparing results across various experimental models.

Gene Expression Profiling of Dendritic Cells in Different Physiological Stages under Cordyceps sinensis Treatment

Cordyceps sinensis (CS) has been commonly used as herbal medicine and a health supplement in China for over two thousand years. Although previous studies have demonstrated that CS has benefits in immunoregulation and anti-inflammation, the precise mechanism by which CS affects immunomodulation is still unclear. In this study, we exploited duplicate sets of loop-design microarray experiments to examine two different batches of CS and analyze the effects of CS on dendritic cells (DCs), in different physiology stages: naïve stage and inflammatory stage. Immature DCs were treated with CS, lipopolysaccharide (LPS), or LPS plus CS (LPS/CS) for two days, and the gene expression profiles were examined using cDNA microarrays. The results of two loop-design microarray experiments showed good intersection rates. The expression level of common genes found in both loop-design microarray experiments was consistent, and the correlation coefficients (Rs), were higher than 0.96. Through intersection analysis of microarray results, we identified 295 intersecting significantly differentially expressed (SDE) genes of the three different treatments (CS, LPS, and LPS/CS), which participated mainly in the adjustment of immune response and the regulation of cell proliferation and death. Genes regulated uniquely by CS treatment were significantly involved in the regulation of focal adhesion pathway, ECM-receptor interaction pathway, and hematopoietic cell lineage pathway. Unique LPS regulated genes were significantly involved in the regulation of Toll-like receptor signaling pathway, systemic lupus erythematosus pathway, and complement and coagulation cascades pathway. Unique LPS/CS regulated genes were significantly involved in the regulation of oxidative phosphorylation pathway. These results could provide useful information in further study of the pharmacological mechanisms of CS. This study also demonstrates that with a rigorous experimental design, the biological effects of a complex compound can be reliably studied by a complex system like cDNA microarray.

THEME: A web tool for loop-design microarray data analysis

A number of recent studies have shown that loop-design is more efficient than reference control design. Data analysis for loop-design microarray experiments is commonly undertaken using linear models and statistical tests. These techniques require specialized knowledge in statistical programming. However, limited loop-design web-based tools are available. We have developed the THEME (Tsing Hua Engine of Microarray Experiment) that exploits all necessary data analysis tools for loop-design microarray studies. THEME allows users to construct linear models and to apply multiple user-defined statistical tests of hypotheses for detection of DEG (differentially expressed genes). Users can modify entries of design matrix for experimental design as well as that of contrast matrix for statistical tests of hypotheses. The output of multiple user-defined statistical tests of hypotheses, DEG lists, can be cross-validated. The web platform provides data assessment and visualization tools that significantly assist users when evaluating the performance of microarray experimental procedures. THEME is also a MIAME (Minimal Information About a Microarray Experiment) compliant system, which enables users to export formatted files for GEO (Gene Expression Omnibus) submission. THEME offers comprehensive web services to biologists for data analysis of loop-design microarray experiments. This web-based resource is especially useful for core facility service as well as collaboration projects when researchers are not at the same site. Data analysis procedures, starting from uploading raw data files to retrieving DEG lists, can be flexibly operated with natural workflows. These features make THEME a reliable and powerful on-line system for data analysis of loop-design microarrays. The THEME server is available at http://metadb.bmes.nthu.edu.tw/theme/.

Determining the Zero‐Force Binding Energetics of an Intercalated DNA Complex by a Single‐Molecule Approach

Thermodynamic profiles of the interaction between small molecules and nucleic acids are essential in rational drug design, compound identification, and compound optimization. An accurate prediction of the binding affinity constant (KA) is very important to determine the binding energetics of the driving forces in drug–DNA interactions because the binding free energy (DGobs) is calculated directly from the binding affinity. [1–3]