Statistical evaluation of differential expression on cDNA nylon arrays with replicated experiments

Treatment with an SLC12A1 antagonist inhibits tumorigenesis in a subset of hepatocellular carcinomas

A central aim in cancer research is to identify genes with altered expression patterns in tumor specimens and their potential role in tumorigenesis. Most types of tumors, including hepatocellular carcinoma (HCC), are heterogeneous in terms of genotype and phenotype. Thus, traditional analytical methods like the t-test fail to identify all oncogenes from expression profiles. In this study, we performed a meta-Cancer Outlier Profile Analysis (meta-COPA) across six microarray datasets for HCC from the GEO database. We found that gene SLC12A1 was overexpressed in the Hep3B cell line, compared with five other HCC cell lines and L02 cells. We also found that the upregulation of SLC12A1 was mediated by histone methylation within its promoter region, and that SLC12A1 is a positive regulator of the WNK1/ERK5 pathway. Consistent with in vitro results, treatment with the SLC12A1 antagonist Bumetanide delayed tumor formation and reduced Hep3B cell tumor size in mouse xenografts. In summary, our research reveals a novel subset of HCCs that are sensitive to SLC12A1 antagonist treatment, thereby offering a new strategy for precision HCC treatment.

The Use of Atomic Force Microscopy for 3D Analysis of Nucleic Acid Hybridization on Microarrays

Oligonucleotide microarrays are considered today to be one of the most efficient methods of gene diagnostics. The capability of atomic force microscopy (AFM) to characterize the three-dimensional morphology of single molecules on a surface allows one to use it as an effective tool for the 3D analysis of a microarray for the detection of nucleic acids. The high resolution of AFM offers ways to decrease the detection threshold of target DNA and increase the signal-to-noise ratio. In this work, we suggest an approach to the evaluation of the results of hybridization of gold nanoparticle-labeled nucleic acids on silicon microarrays based on an AFM analysis of the surface both in air and in liquid which takes into account of their three-dimensional structure. We suggest a quantitative measure of the hybridization results which is based on the fraction of the surface area occupied by the nanoparticles.

Computational Strategies for Analyzing Data in Gene Expression Microarray Experiments

Microarray analysis has become a widely used method for generating gene expression data on a genomic scale. Microarrays have been enthusiastically applied in many fields of biological research, even though several open questions remain about the analysis of such data. A wide range of approaches are available for computational analysis, but no general consensus exists as to standard for microarray data analysis protocol. Consequently, the choice of data analysis technique is a crucial element depending both on the data and on the goals of the experiment. Therefore, basic understanding of bioinformatics is required for optimal experimental design and meaningful interpretation of the results. This review summarizes some of the common themes in DNA microarray data analysis, including data normalization and detection of differential expression. Algorithms are demonstrated by analyzing cDNA microarray data from an experiment monitoring gene expression in T helper cells. Several computational biology strategies, along with their relative merits, are overviewed and potential areas for additional research discussed. The goal of the review is to provide a computational framework for applying and evaluating such bioinformatics strategies. Solid knowledge of microarray informatics contributes to the implementation of more efficient computational protocols for the given data obtained through microarray experiments.

Spatial and temporal analysis of gene expression during growth and fusion of the mouse facial prominences

Orofacial malformations resulting from genetic and/or environmental causes are frequent human birth defects yet their etiology is often unclear because of insufficient information concerning the molecular, cellular and morphogenetic processes responsible for normal facial development. We have, therefore, derived a comprehensive expression dataset for mouse orofacial development, interrogating three distinct regions – the mandibular, maxillary and frontonasal prominences. To capture the dynamic changes in the transcriptome during face formation, we sampled five time points between E10.5–E12.5, spanning the developmental period from establishment of the prominences to their fusion to form the mature facial platform. Seven independent biological replicates were used for each sample ensuring robustness and quality of the dataset. Here, we provide a general overview of the dataset, characterizing aspects of gene expression changes at both the spatial and temporal level. Considerable coordinate regulation occurs across the three prominences during this period of facial growth and morphogenesis, with a switch from expression of genes involved in cell proliferation to those associated with differentiation. An accompanying shift in the expression of polycomb and trithorax genes presumably maintains appropriate patterns of gene expression in precursor or differentiated cells, respectively. Superimposed on the many coordinated changes are prominence-specific differences in the expression of genes encoding transcription factors, extracellular matrix components, and signaling molecules. Thus, the elaboration of each prominence will be driven by particular combinations of transcription factors coupled with specific cell:cell and cell:matrix interactions. The dataset also reveals several prominence-specific genes not previously associated with orofacial development, a subset of which we externally validate. Several of these latter genes are components of bidirectional transcription units that likely share cis-acting sequences with well-characterized genes. Overall, our studies provide a valuable resource for probing orofacial development and a robust dataset for bioinformatic analysis of spatial and temporal gene expression changes during embryogenesis.

Statistical identification of gene association by CID in application of constructing ER regulatory network

Background

A variety of high-throughput techniques are now available for constructing comprehensive gene regulatory networks in systems biology. In this study, we report a new statistical approach for facilitating in silico inference of regulatory network structure. The new measure of association, coefficient of intrinsic dependence (CID), is model-free and can be applied to both continuous and categorical distributions. When given two variables X and Y, CID answers whether Y is dependent on X by examining the conditional distribution of Y given X. In this paper, we apply CID to analyze the regulatory relationships between transcription factors (TFs) (X) and their downstream genes (Y) based on clinical data. More specifically, we use estrogen receptor α (ERα) as the variable X, and the analyses are based on 48 clinical breast cancer gene expression arrays (48A).

Results

The analytical utility of CID was evaluated in comparison with four commonly used statistical methods, Galton-Pearson's correlation coefficient (GPCC), Student's t-test (STT), coefficient of determination (CoD), and mutual information (MI). When being compared to GPCC, CoD, and MI, CID reveals its preferential ability to discover the regulatory association where distribution of the mRNA expression levels on X and Y does not fit linear models. On the other hand, when CID is used to measure the association of a continuous variable (Y) against a discrete variable (X), it shows similar performance as compared to STT, and appears to outperform CoD and MI. In addition, this study established a two-layer transcriptional regulatory network to exemplify the usage of CID, in combination with GPCC, in deciphering gene networks based on gene expression profiles from patient arrays.

Conclusion

CID is shown to provide useful information for identifying associations between genes and transcription factors of interest in patient arrays. When coupled with the relationships detected by GPCC, the association predicted by CID are applicable to the construction of transcriptional regulatory networks. This study shows how information from different data sources and learning algorithms can be integrated to investigate whether relevant regulatory mechanisms identified in cell models can also be partially re-identified in clinical samples of breast cancers.

Availability

the implementation of CID in R codes can be freely downloaded from .

Amplification biases: possible differences among deviating gene expressions

Background

Gene expression profiling has become a tool of choice to study pathological or developmental questions but in most cases the material is scarce and requires sample amplification. Two main procedures have been used: in vitro transcription (IVT) and polymerase chain reaction (PCR), the former known as linear and the latter as exponential. Previous reports identified enzymatic pitfalls in PCR and IVT protocols; however the possible differences between the sequences affected by these amplification defaults were only rarely explored.

Results

Screening a bovine cDNA array dedicated to embryonic stages with embryonic (n = 3) and somatic tissues (n = 2), we proceeded to moderate amplifications starting from 1 μg of total RNA (global PCR or IVT one round). Whatever the tissue, 16% of the probes were involved in deviating gene expressions due to amplification defaults. These distortions were likely due to the molecular features of the affected sequences (position within a gene, GC content, hairpin number) but also to the relative abundance of these transcripts within the tissues. These deviating genes mainly encoded housekeeping genes from physiological or cellular processes (70%) and constituted 2 subsets which did not overlap (molecular features, signal intensities, gene ID). However, the differential expressions identified between embryonic stages were both reliable (minor intersect with biased expressions) and relevant (biologically validated). In addition, the relative expression levels of those genes were biologically similar between amplified and unamplified samples.

Conclusion

Conversely to the most recent reports which challenged the use of intense amplification procedures on minute amounts of RNA, we chose moderate PCR and IVT amplifications for our gene profiling study. Conclusively, it appeared that systematic biases arose even with moderate amplification procedures, independently of (i) the sample used: brain, ovary or embryos, (ii) the enzymatic properties initially inferred (exponential or linear) and (iii) the preliminary optimization of the protocols. Moreover the use of an in-house developed array, small-sized but well suited to the tissues we worked with, was of real interest for the search of differential expressions.

Gene expression variation in Down's syndrome mice allows prioritization of candidate genes

RNA from eight Ts65Dn mice (a model of Down syndrome) and eight euploid mice were analysed by real-time PCR to examine inter-individual gene expression levels as a function of trisomy.

Background

Down's syndrome (DS), or trisomy 21, is a complex developmental disorder that exhibits many clinical signs that vary in occurrence and severity among patients. The molecular mechanisms responsible for DS have thus far remained elusive. We argue here that normal variation in gene expression in the population contributes to the heterogeneous clinical picture of DS, and we estimated the amplitude of this variation in 50 mouse orthologs of chromosome 21 genes in brain regions of Ts65Dn (a mouse model of DS). We analyzed the RNAs of eight Ts65Dn and eight euploid mice by real-time polymerase chain reaction.

Results

In pooled RNAs, we confirmed that trisomic/euploid gene expression ratios were close to 1.5. However, we observed that inter-individual gene expression levels spanned a broad range of values. We identified three categories of genes: genes with expression levels consistently higher in Ts65Dn than in euploids (9, 17, and 7 genes in cerebellum, cortex, and midbrain, respectively); genes whose expression levels partially overlap between the two groups (10, 9, and 14 genes); and genes with intermingled expression, which cannot be used to differentiate trisomics from euploids (12, 5 and 9 genes). Of the genes in the first category, App, Cbr1, and Mrps6 exhibited tight regulation in the three tissues and are therefore attractive candidates for further research.

Conclusion

This is the first analysis addressing inter-individual gene expression levels as a function of trisomy. We propose a strategy allowing discrimination between candidates for the constant features of DS and those genes that may contribute to the partially penetrant signs of DS.

A global view of gene expression in lithium and zinc treated sea urchin embryos: new components of gene regulatory networks

BACKGROUND

The genome of the sea urchin Strongylocentrotus purpuratus has recently been sequenced because it is a major model system for the study of gene regulatory networks. Embryonic expression patterns for most genes are unknown, however.

RESULTS

Using large-scale screens on arrays carrying 50% to 70% of all genes, we identified novel territory-specific markers. Our strategy was based on computational selection of genes that are differentially expressed in lithium-treated embryos, which form excess endomesoderm, and in zinc-treated embryos, in which endomesoderm specification is blocked. Whole-mount in situ hybridization (WISH) analysis of 700 genes indicates that the apical organ region is eliminated in lithium-treated embryos. Conversely, apical and specifically neural markers are expressed more broadly in zinc-treated embryos, whereas endomesoderm signaling is severely reduced. Strikingly, the number of serotonergic neurons is amplified by at least tenfold in zinc-treated embryos. WISH analysis further indicates that there is crosstalk between the Wnt (wingless int), Notch, and fibroblast growth factor signaling pathways in secondary mesoderm cell specification and differentiation, similar to signaling cascades that function during development of presomitic mesoderm in mouse embryogenesis. We provide differential expression data for more than 4,000 genes and WISH patterns of more than 250 genes, and more than 2,400 annotated WISH images.

CONCLUSION

Our work provides tissue-specific expression patterns for a large fraction of the sea urchin genes that have not yet been included in existing regulatory networks and await functional integration. Furthermore, we noted neuron-inducing activity of zinc on embryonic development; this is the first observation of such activity in any organism.

Conserved molecular portraits of bovine and human blastocysts as a consequence of the transition from maternal to embryonic control of gene expression

The present study investigated mRNA expression profiles of bovine oocytes and blastocysts by using a cross-species hybridization approach employing an array consisting of 15,529 human cDNAs as probe, thus enabling the identification of conserved genes during human and bovine preimplantation development. Our analysis revealed 419 genes that were expressed in both oocytes and blastocysts. The expression of 1,324 genes was detected exclusively in the blastocyst, in contrast to 164 in the oocyte including a significant number of novel genes. Genes indicative for transcriptional and translational control (ELAVL4, TACC3) were overexpressed in the oocyte, whereas cellular trafficking (SLC2A14, SLC1A3), proteasome (PSMA1, PSMB3), cell cycle (BUB3, CCNE1, GSPT1), and protein modification and turnover (TNK1, UBE3A) genes were found to be overexpressed in blastocysts. Transcripts implicated in chromatin remodeling were found in both oocytes (NASP, SMARCA2) and blastocysts (H2AFY, HDAC7A). The trophectodermal markers PSG2 and KRT18 were enriched 5- and 50-fold in the blastocyst. Pathway analysis revealed differential expression of genes involved in 107 distinct signaling and metabolic pathways. For example, phosphatidylinositol signaling and gluconeogenesis were prominent pathways identified in the blastocyst. Expression patterns in bovine and human blastocysts were to a large extent identical. This analysis compared the transcriptomes of bovine oocytes and blastocysts and provides a solid foundation for future studies on the first major differentiation events in blastocysts and identification of a set of markers indicative for regular mammalian development.

Nodal signaling activates differentiation genes during zebrafish gastrulation

Nodal signals induce mesodermal and endodermal progenitors during vertebrate development. To determine the role of Nodal signaling at a genomic level, we isolated Nodal-regulated genes by expression profiling using macroarrays and gene expression databases. Putative Nodal-regulated genes were validated by in situ hybridization screening in wild type and Nodal signaling mutants. 46 genes were identified, raising the currently known number of Nodal-regulated genes to 72. Based on their expression patterns along the dorsoventral axis, most of these genes can be classified into two groups. One group is expressed in the dorsal margin, whereas the other group is expressed throughout the margin. In addition to transcription factors and signaling components, the screens identified several new functional classes of Nodal-regulated genes, including cytoskeletal components and molecules involved in protein secretion or endoplasmic reticulum stress. We found that x-box binding protein-1 (xbp1) is a direct target of Nodal signaling and required for the terminal differentiation of the hatching gland, a specialized secretory organ whose specification is also dependent on Nodal signaling. These results indicate that Nodal signaling regulates not only specification genes but also differentiation genes.

Analysis of Oct4-dependent transcriptional networks regulating self-renewal and pluripotency in human embryonic stem cells

The POU domain transcription factor OCT4 is a key regulator of pluripotency in the early mammalian embryo and is highly expressed in the inner cell mass of the blastocyst. Consistent with its essential role in maintaining pluripotency, Oct4 expression is rapidly downregulated during formation of the trophoblast lineage. To enhance our understanding of the molecular basis of this differentiation event in humans, we used a functional genomics approach involving RNA interference-mediated suppression of OCT4 function in a human ESC line and analysis of the resulting transcriptional profiles to identify OCT4-dependent genes in human cells. We detected altered expression of >1,000 genes, including targets regulated directly by OCT4 either positively (NANOG, SOX2, REX1, LEFTB, LEFTA/EBAF DPPA4, THY1, and TDGF1) or negatively (CDX2, EOMES, BMP4, TBX18, Brachyury [T], DKK1, HLX1, GATA6, ID2, and DLX5), as well as targets for the OCT4-associated stem cell regulators SOX2 and NANOG. Our data set includes regulators of ACTIVIN, BMP, fibroblast growth factor, and WNT signaling. These pathways are implicated in regulating human ESC differentiation and therefore further validate the results of our analysis. In addition, we identified a number of differentially expressed genes that are involved in epigenetics, chromatin remodeling, apoptosis, and metabolism that may point to underlying molecular mechanisms that regulate pluripotency and trophoblast differentiation in humans. Significant concordance between this data set and previous comparisons between inner cell mass and trophectoderm in human embryos indicates that the study of human ESC differentiation in vitro represents a useful model of early embryonic differentiation in humans.

Expression profiling of drug response--from genes to pathways

Understanding individual response to a drug -what determines its efficacy and tolerability -is the major bottleneck in current drug development and clinical trials. Intracellular response and metabolism, for example through cytochrome P-450 enzymes, may either enhance or decrease the effect of different drugs, dependent on the genetic variant. Microarrays offer the potential to screen the genetic composition of the individual patient However, experiments are «noisy» and must be accompanied by solid and robust data analysis. Furthermore, recent research aims at the combination of high-throughput data with methods of mathematical modeling, enabling problem-oriented assistance in the drug discovery process. This article will discuss state-of-the-art DNA array technology platforms and the basic elements of data analysis and bioinformatics research in drug discovery. Enhancing single-gene analysis, we will present a new method for interpreting gene expression changes in the context of entire pathways. Furthermore, we will introduce the concept of systems biology as a new paradigm for drug development and highlight our recent research - the development of a modeling and simulation platform for biomedical applications. We discuss the potentials of systems biology for modeling the drug response of the individual patient.

Surface Modification for DNA and Protein Microarrays

Microarrays of biomolecules are emerging as powerful tools for genomics, proteomics, and clinical assays, since they make it possible to screen biologically important binding events in a parallel and high throughput fashion. Because the microarrays are fabricated on a solid support, coating of the surface and immobilization strategy of the biomolecules are major issues for successful microarray fabrication. This review deals with both DNA microarrays and protein microarrays, and focuses on the various modification approaches for the two-dimensional surface materials and three-dimensional ones. In addition, the immobilization strategies including adsorption, covalent attachment, physical entrapment, and affinity attachment of the biomolecules are summarized, and advantage and limitation of representative efforts are discussed.

Age-specific hormonal decline is accompanied by transcriptional changes in human sebocytes in vitro

The importance of hormones in endogenous aging has been displayed by recent studies performed on animal models and humans. To decipher the molecular mechanisms involved in aging we maintained human sebocytes at defined hormone-substituted conditions that corresponded to average serum levels of females from 20 (f20) to 60 (f60) years of age. The corresponding hormone receptor expression was demonstrated by reverse transcription-polymerase chain reaction (RT-PCR), Western blotting and immunocytochemistry. Cells at f60 produced significantly lower lipids than at f20. Increased mRNA and protein levels of c-Myc and increased protein levels of FN1, which have been associated with aging, were detected in SZ95 sebocytes at f60 compared to those detected at f20 after 5 days of treatment. Expression profiling employing a cDNA microarray composed of 15 529 cDNAs identified 899 genes with altered expression levels at f20 vs. f60. Confirmation of gene regulation was performed by real-time RT-PCR. The functional annotation of these genes according to the Gene Ontology identified pathways related to mitochondrial function, oxidative stress, ubiquitin-mediated proteolysis, cell cycle, immune responses, steroid biosynthesis and phospholipid degradation - all hallmarks of aging. Twenty-five genes in common with those identified in aging kidneys and several genes involved in neurodegenerative diseases were also detected. This is the first report describing the transcriptome of human sebocytes and its modification by a cocktail of hormones administered in age-specific levels and provides an in vitro model system, which approximates some of the hormone-dependent changes in gene transcription that occur during aging in humans.

Proliferative phase endosperm promoters from Arabidopsis thaliana

Endosperm accounts for a large proportion of human nutrition and is also a major determinant of seed viability and size, not only in cereals, but also in species with ephemeral endosperms, such as soybean and oilseed rape. The extent of endosperm proliferation early in seed development is a crucial component in setting seed size; therefore, a biotechnological approach for the modification of this trait requires promoters active in early endosperm. To find such promoters, we constructed an array based on cDNAs extracted from developing Arabidopsis seeds enriched for proliferating endosperm. Hybridization with RNA extracted from vegetative and reproductive tissues, including endosperm, and subsequent data filtering yielded sets of endosperm-expressed and endosperm-preferred genes, including many hundreds not previously identified in array experiments designed to detect genes expressed in Arabidopsis seeds. Of eight promoters selected for validation, seven were active in early endosperm, three with no detected activity elsewhere in the plant. Therefore, this strategy has yielded proliferative phase endosperm promoters which should be useful in altering seed size.

Expression profiling of drug response--from genes to pathways

Understanding individual response to a drug-what determines its efficacy and tolerability-is the major bottleneck in current drug development and clinical trials. Intracellular response and metabolism, for example through cytochrome P-450 enzymes, may either enhance or decrease the effect of different drugs, dependent on the genetic variant. Microarrays offer the potential to screen the genetic composition of the individual patient. However, experiments are "noisy" and must be accompanied by solid and robust data analysis. Furthermore, recent research aims at the combination of high-throughput data with methods of mathematical modeling, enabling problem-oriented assistance in the drug discovery process. This article will discuss state-of-the-art DNA array technology platforms and the basic elements of data analysis and bioinformatics research in drug discovery. Enhancing single-gene analysis, we will present a new method for interpreting gene expression changes in the context of entire pathways. Furthermore, we will introduce the concept of systems biology as a new paradigm for drug development and highlight our recent research-the development of a modeling and simulation platform for biomedical applications. We discuss the potentials of systems biology for modeling the drug response of the individual patient.

Matrix metalloproteinases of epithelial origin in facial sebum of patients with acne and their regulation by isotretinoin

Acne vulgaris is a skin disorder of the sebaceous follicles, involving hyperkeratinization and perifollicular inflammation. Matrix metalloproteinases (MMP) have a predominant role in inflammatory matrix remodeling and hyperproliferative skin disorders. We investigated the expression of MMP and tissue inhibitors of MMP (TIMP) in facial sebum specimens from acne patients, before and after treatment with isotretinoin. Gelatin zymography and Western-blot analysis revealed that sebum contains proMMP-9, which was decreased following per os or topical treatment with isotretinoin and in parallel to the clinical improvement of acne. Sebum also contains MMP-1, MMP-13, TIMP-1, and TIMP-2, as assessed by ELISA and western blot, but only MMP-13 was decreased following treatment with isotretinoin. The origin of MMP and TIMP in sebum is attributed to keratinocytes and sebocytes, since we found that HaCaT keratinocytes in culture secrete proMMP-2, proMMP-9, MMP-1, MMP-13, TIMP-1, and TIMP-2. SZ95 sebocytes in culture secreted proMMP-2 and proMMP-9, which was also confirmed by microarray analysis. Isotretinoin inhibited the arachidonic acid-induced secretion and mRNA expression of proMMP-2 and -9 in both cell types and of MMP-13 in HaCaT keratinocytes. These data indicate that MMP and TIMP of epithelial origin may be involved in acne pathogenesis, and that isotretinoin-induced reduction in MMP-9 and -13 may contribute to the therapeutic effects of the agent in acne.

Primary Differentiation in the Human Blastocyst: Comparative Molecular Portraits of Inner Cell Mass and Trophectoderm Cells

The primary differentiation event during mammalian development occurs at the blastocyst stage and leads to the delineation of the inner cell mass (ICM) and the trophectoderm (TE). We provide the first global mRNA expression data from immunosurgically dissected ICM cells, TE cells, and intact human blastocysts. Using a cDNA microarray composed of 15,529 cDNAs from known and novel genes, we identify marker transcripts specific to the ICM (e.g., OCT4/POU5F1, NANOG, HMGB1, and DPPA5) and TE (e.g., CDX2, ATP1B3, SFN, and IPL), in addition to novel ICM- and TE-specific expressed sequence tags. The expression patterns suggest that the emergence of pluripotent ICM and TE cell lineages from the morula is controlled by metabolic and signaling pathways, which include inter alia, WNT, mitogen-activated protein kinase, transforming growth factor-beta, NOTCH, integrin-mediated cell adhesion, phosphatidylinositol 3-kinase, and apoptosis. These data enhance our understanding of the first step in human cellular differentiation and, hence, the derivation of both embryonic stem cells and trophoblastic stem cells from these lineages.

Complementation of human papillomavirus type 16 E6 and E7 by Jagged1-specific Notch1-phosphatidylinositol 3-kinase signaling involves pleiotropic oncogenic functions independent of CBF1;Su(H);Lag-1 activation

We have analyzed the induction and role of phosphatidylinositol 3-kinase (PI3K) by Notch signaling in human papillomavirus (HPV)-derived cancers. Jagged1, in contrast to Delta1, is preferentially upregulated in human cervical tumors. Jagged1 and not Delta1 expression sustained in vivo tumors by HPV16 oncogenes in HaCaT cells. Further, Jagged1 expression correlates with the rapid induction of PI3K-mediated epithelial-mesenchymal transition in both HaCaT cells and a human cervical tumor-derived cell line, suggestive of Delta1;Serrate/Jagged;Lag2 ligand-specific roles. Microarray analysis and dominant-negatives reveal that Notch-PI3K oncogenic functions can be independent of CBF1;Su(H);Lag-1 activation and instead relies on Deltex1, an alternative Notch effector.

Sample size for identifying differentially expressed genes in microarray experiments

Microarray technology allows simultaneous comparison of expression levels of thousands of genes under each condition. This paper concerns sample size calculation in the identification of differentially expressed genes between a control and a treated sample. In a typical experiment, only a fraction of genes (altered genes) is expected to be differentially expressed between two samples. Sample size determination depends on a number of factors including the specified significance level (alpha), the desired statistical power (1-beta), the fraction (eta) of truly altered genes out of the total g genes studied, and the effect sizes (Delta) for the altered genes. This paper proposes a method to calculate the number of arrays required to detect at least 100lambda % (where 0 < lambda < or = 1) of the truly altered genes under the model of an equal effect size for all altered genes. The required numbers of arrays are tabulated for various values of alpha, beta, Delta, eta, and lambda for the one-sample and two-sample t-tests for g = 10,000. Based on the proposed approach, to identify up to 90% of truly altered genes among the unknown number of truly altered genes, the estimated numbers of arrays needed appear to be manageable. For instance, when the standardized effect size is at least 2.0, the number of arrays needed is less than or equal to 14 for the two-sample t-test and is less than or equal to 10 for the one-sample t-test. As the cost per array declines, such array numbers become practical. The proposed method offers a simple, intuitive, and practical way to determine the number of arrays needed in microarray experiments in which the true correlation structure among the genes under investigation cannot be reasonably assumed. An example dataset is used to illustrate the use of the proposed approach to plan microarray experiments.

Whole-genome approaches for large-scale gene identification and expression analysis in mammalian preimplantation embryos

The elucidation, unravelling and understanding of the molecular basis of transcriptional control during preimplantion development is of utmost importance if we are to intervene and eliminate or reduce abnormalities associated with growth, disease and infertility by applying assisted reproduction. Importantly, these studies should enhance our knowledge of basic reproductive biology and its application to regenerative medicine and livestock production. A major obstacle impeding progress in these areas is the ability to successfully generate molecular portraits of preimplantation embryos from their minute amounts of RNA. The present review describes the various approaches whereby classical embryology fuses with molecular biology, high-throughput genomics and systems biology to address and solve questions related to early development in mammals.

Cross-species hybridisation of human and bovine orthologous genes on high density cDNA microarrays

BACKGROUND

Cross-species gene-expression comparison is a powerful tool for the discovery of evolutionarily conserved mechanisms and pathways of expression control. The usefulness of cDNA microarrays in this context is that broad areas of homology are compared and hybridization probes are sufficiently large that small inter-species differences in nucleotide sequence would not affect the analytical results. This comparative genomics approach would allow a common set of genes within a specific developmental, metabolic, or disease-related gene pathway to be evaluated in experimental models of human diseases. The objective of this study was to investigate the feasibility and reproducibility of cross-species analysis employing a human cDNA microarray as probe.

RESULTS

As a proof of principle, total RNA derived from human and bovine fetal brains was used as a source of labelled targets for hybridisation onto a human cDNA microarray composed of 349 characterised genes. Each gene was spotted 20 times representing 6,980 data points thus enabling highly reproducible spot quantification. Employing high stringency hybridisation and washing conditions, followed by data analysis, revealed slight differences in the expression levels and reproducibility of the signals between the two species. We also assigned each of the genes into three expression level categories- i.e. high, medium and low. The correlation co-efficient of cross hybridisation between the orthologous genes was 0.94. Verification of the array data by semi-quantitative RT-PCR using common primer sequences enabled co-amplification of both human and bovine transcripts. Finally, we were able to assign gene names to previously uncharacterised bovine ESTs.

CONCLUSIONS

Results of our study demonstrate the harnessing and utilisation power of comparative genomics and prove the feasibility of using human microarrays to facilitate the identification of co-expressed orthologous genes in common tissues derived from different species.

Transcript level alterations reflect gene dosage effects across multiple tissues in a mouse model of down syndrome

Human trisomy 21, which results in Down syndrome (DS), is one of the most complicated congenital genetic anomalies compatible with life, yet little is known about the molecular basis of DS. It is generally accepted that chromosome 21 (Chr21) transcripts are overexpressed by about 50% in cells with an extra copy of this chromosome. However, this assumption is difficult to test in humans due to limited access to tissues, and direct support for this idea is available for only a few Chr21 genes or in a limited number of tissues. The Ts65Dn mouse is widely used as a model for studies of DS because it is at dosage imbalance for the orthologs of about half of the 284 Chr21 genes. Ts65Dn mice have several features that directly parallel developmental anomalies of DS. Here we compared the expression of 136 mouse orthologs of Chr21 genes in nine tissues of the trisomic and euploid mice. Nearly all of the 77 genes which are at dosage imbalance in Ts65Dn showed increased transcript levels in the tested tissues, providing direct support for a simple model of increased transcription proportional to the gene copy number. However, several genes escaped this rule, suggesting that they may be controlled by additional tissue-specific regulatory mechanisms revealed in the trisomic situation.

Feature extraction and signal processing for nylon DNA microarrays

Background

High-density DNA microarrays require automatic feature extraction methodologies and softwares. These can be a potential source of non-reproducibility of gene expression measurements. Variation in feature location or in signal integration methodology may be a significant contribution to the observed variance in gene expression levels.

Results

We explore sources of variability in feature extraction from DNA microarrays on Nylon membrane with radioactive detection. We introduce a mathematical model of the signal emission and derive methods for correcting biases such as overshining, saturation or variation in probe amount. We also provide a quality metric which can be used qualitatively to flag weak or untrusted signals or quantitatively to modulate the weight of each experiment or gene in higher level analyses (clustering or discriminant analysis).

Conclusions

Our novel feature extraction methodology, based on a mathematical model of the radioactive emission, reduces variability due to saturation, neighbourhood effects and variable probe amount. Furthermore, we provide a fully automatic feature extraction software, BZScan, which implements the algorithms described in this paper.

Differential gene expression analysis in fish exposed to endocrine disrupting compounds

This review discusses various methodologies that can be used to understand, at the gene level, the consequences to fish upon exposure to endocrine disrupting compounds (EDCs). Several approaches for measuring expression of gene transcripts are discussed, including directed approaches, such as Northern blotting and quantitative reverse transcriptase polymerase chain reaction (RT-PCR) as well as open-ended approaches, such as differential display RT-PCR, subtractive hybridizations, and gene arrays. Each of these systems has advantages and disadvantages, strengths and weaknesses. Conducting experiments with each of these methods provides important information about the molecular mechanisms that result from exposure to EDCs, information which can be used in risk assessment of polluted sites found in the environment.

Microarrays: how many do you need?

We estimate the number of microarrays that is required in order to gain reliable results from a common type of study: the pairwise comparison of different classes of samples. We show that current knowledge allows for the construction of models that look realistic with respect to searches for individual differentially expressed genes and derive prototypical parameters from real data sets. Such models allow investigation of the dependence of the required number of samples on the relevant parameters: the biological variability of the samples within each class, the fold changes in expression that are desired to be detected, the detection sensitivity of the microarrays, and the acceptable error rates of the results. We supply experimentalists with general conclusions as well as a freely accessible Java applet at www.scai.fhg.de/special/bio/howmanyarrays/ for fine tuning simulations to their particular settings.

A microarray platform comparison for neuroscience applications

To address the need for high sensitivity in gene expression profiling of small neural tissue samples ( approximately 100 ng total RNA), we compared a novel RT-PCR-IVT protocol using fluor-reverse pairs on inkjet oligonucleotide microarrays and an RT-IVT protocol using 33P labeling on nylon cDNA arrays. The comparison protocol was designed to evaluate these systems for sensitivity, specificity, reproducibility, and linearity. We developed parameters, thresholds, and testing conditions that could be used to differentiate various systems that spanned detection chemistry and instrumentation; probe number and selection criteria; and sample processing protocols. We concluded that the inkjet system had better performance in sensitivity, specificity, and reproducibility than the nylon system, and similar performance in linearity. Between these two platforms, the data indicates that the inkjet system would perform better for the transcriptional profiling of 100 ng total RNA samples for neuroscience studies.

A DNA expression array to detect toxic stress response in European flounder (Platichthys flesus)

As a first stage in developing a DNA array-based approach to investigating the effects of pollutants on an environmentally relevant European fish species, we have constructed a 160-gene custom microarray for European flounder. Degenerate primers were used to amplify 110 different fragments of stress-related and other genes from European flounder cDNA and genomic DNA. Additionally, 22 fragments were obtained by suppressive subtractive hybridisation (SSH). These fragments were cloned and sequenced, then, with additional control genes, used to create a cDNA microarray for flounder. After optimisation of the arraying process, hepatic mRNA was isolated from flounder caught in the polluted Tyne and relatively unpolluted Alde estuaries. Fluorescent cDNA probes were synthesised from the mRNA and used in dual-colour hybridisations to the microarray. A number of transcripts were differentially expressed between Tyne and Alde female flounder but these changes were not significant, due to high inter-individual variation. However, in comparisons between Tyne and Alde male flounder, 11 transcripts were found to significantly differ in expression (P<0.05). Seven transcripts were more highly expressed in the Tyne male fish (CYP1A, UDPGT, alpha-2HS-glycoprotein, dihydropyrimidine dehydrogenase, Cu/Zn SOD, aldehyde dehydrogenase and paraoxonase). Four transcripts (Elongation factor 1 (EF1), EF2, Int-6 and complement component C3) were found to be significantly less abundant in the Tyne male fish. Selected genes were assayed by real-time PCR, then normalised to alpha-tubulin. These assays confirmed the significance of the array results for CYP1A, UDPGT and EF1, but not for Cu/Zn SOD. This study provides a link between traditional single-gene biomarker studies and the emerging field of eco-toxicogenomics, demonstrating the utility of microarray studies on environmentally sampled, non-model organisms.

Chemical discovery and global gene expression analysis in zebrafish

The zebrafish (Danio rerio) provides an excellent model for studying vertebrate development and human disease because of its ex utero, optically transparent embryogenesis and amenability to in vivo manipulation. The rapid embryonic developmental cycle, large clutch sizes and ease of maintenance at large numbers also add to the appeal of this species. Considerable genomic data has recently become publicly available that is aiding the construction of zebrafish microarrays, thus permitting global gene expression analysis. The zebrafish is also suitable for chemical genomics, in part as a result of the permeability of its embryos to small molecules and consequent avoidance of external confounding maternal effects. Finally, there is increasing characterization and analysis of zebrafish models of human disease. Thus, the zebrafish offers a high-quality, high-throughput bioassay tool for determining the biological effect of small molecules as well as for dissecting biological pathways.

A statistical approach in using cDNA array analysis to determine modest changes in gene expression in several brain regions after neurotoxic insult

Modest changes in gene expression of three-fold or less might be expected after mild to moderate neurotoxic exposure to classes of compounds, such as the substituted amphetamines, or at time points that are weeks after more severe neurotoxic exposures. When many genes appear to change expression by less than two-fold, it is crucial to run several pairs of arrays and use statistical analysis to determine which genes are really changing. This limits the number of genes that have to undergo the time consuming task of performing RT-PCR to validate change in expression levels. We describe here methods for statistically determining which genes are being expressed above background levels. These methods are used to compare expression differences among the striatum, parietal cortex, posterior lateral amygdaloid nucleus, and substantia nigra brain regions, all of which differ significantly in their gene expression profiles. In these comparisons, it was possible to distinguish differences among hundreds of genes with manageable estimated false discovery rates. The effect of amphetamine treatment on gene expression in posterior lateral amygdaloid nucleus was also evaluated. The expression data indicate that many genes have changed, but in this case it is more difficult to separate affected genes from false positives. The optimum list has 50 genes, of which 32% are expected to be false positives.

Testing for differentially expressed genes with microarray data

This paper compares the type I error and power of the one- and two-sample t-tests, and the one- and two-sample permutation tests for detecting differences in gene expression between two microarray samples with replicates using Monte Carlo simulations. When data are generated from a normal distribution, type I errors and powers of the one-sample parametric t-test and one-sample permutation test are very close, as are the two-sample t-test and two-sample permutation test, provided that the number of replicates is adequate. When data are generated from a t-distribution, the permutation tests outperform the corresponding parametric tests if the number of replicates is at least five. For data from a two-color dye swap experiment, the one-sample test appears to perform better than the two-sample test since expression measurements for control and treatment samples from the same spot are correlated. For data from independent samples, such as the one-channel array or two-channel array experiment using reference design, the two-sample t-tests appear more powerful than the one-sample t-tests.

Detection of genes with tissue-specific expression patterns using Akaike's information criterion procedure

We applied a method based on Akaike's information criterion (AIC) to detect genes whose expression profile is considerably different in some tissue(s) than in others. Such observations are detected as outliers, and the method we used was originally developed to detect outliers. The main advantage of the method is that objective decisions are possible because the procedure is independent of a significance level. We applied the method to 48 expression ratios corresponding to various tissues in each of 14,610 clones obtained from the RIKEN Expression Array Database (READ; http://read.gsc.riken.go.jp). As a result, for several tissues (e.g., muscle, heart, and tongue tissues that contain similar cell types) we objectively obtained specific clones without any "thresholding." Our study demonstrates the feasibility of the method for detecting tissue-specific gene expression patterns.

A call to fins! Zebrafish as a gerontological model

Among the wide variety of model organisms commonly used for studies on aging, such as worms, flies and rodents, a wide research gap exists between the invertebrate and vertebrate model systems. In developmental biology, a similar gap has been filled by the zebrafish (Danio rerio). We propose that the zebrafish is uniquely suited to serve as a bridge model for gerontology. With high fecundity and economical husbandry requirements, large populations of zebrafish may be generated quickly and cheaply, facilitating large-scale approaches including demographic studies and mutagenesis screens. A variety of mutants identified in such screens have led to modelling of human disease, including cardiac disorders and cancer. While zebrafish longevity is at least 50% longer than in commonly used mouse strains, as an ectothermic fish species, its life span may be readily modulated by caloric intake, ambient temperature and reproductive activity. These features, coupled with a growing abundance of biological resources, including an ongoing genome sequencing project, make the zebrafish a compelling model organism for studies on aging.

Simulation of DNA array hybridization experiments and evaluation of critical parameters during subsequent image and data analysis

BACKGROUND

Gene expression analyses based on complex hybridization measurements have increased rapidly in recent years and have given rise to a huge amount of bioinformatic tools such as image analyses and cluster analyses. However, the amount of work done to integrate and evaluate these tools and the corresponding experimental procedures is not high. Although complex hybridization experiments are based on a data production pipeline that incorporates a significant amount of error parameters, the evaluation of these parameters has not been studied yet in sufficient detail.

RESULTS

In this paper we present simulation studies on several error parameters arising in complex hybridization experiments. A general tool was developed that allows the design of exactly defined hybridization data incorporating, for example, variations of spot shapes, spot positions and local and global background noise. The simulation environment was used to judge the influence of these parameters on subsequent data analysis, for example image analysis and the detection of differentially expressed genes. As a guide for simulating expression data real experimental data were used and model parameters were adapted to these data. Our results show how measurement error can be balanced by the analysis tools.

CONCLUSIONS

We describe an implemented model for the simulation of DNA-array experiments. This tool was used to judge the influence of critical parameters on the subsequent image analysis and differential expression analysis. Furthermore the tool can be used to guide future experiments and to improve performance by better experimental design. Series of simulated images varying specific parameters can be downloaded from our web-site: http://www.molgen.mpg.de/~lh_bioinf/projects/simulation/biotech/

Genomic DNA standards for gene expression profiling in Mycobacterium tuberculosis

A fundamental problem in DNA microarray analysis is the lack of a common standard to compare the expression levels of different samples. Several normalization protocols have been proposed to overcome variables inherent in this technology. As yet, there are no satisfactory methods to exchange gene expression data among different research groups or to compare gene expression values under different stimulus-response profiles. We have tested a normalization procedure based on comparing gene expression levels to the signals generated from hybridizing genomic DNA (genomic normalization). This procedure was applied to DNA microarrays of Mycobacterium tuberculosis using RNA extracted from cultures growing to the logarithmic and stationary phases. The applied normalization procedure generated reproducible measurements of expression level for 98% of the putative mycobacterial ORFs, among which 5.2% were significantly changed comparing the logarithmic to stationary growth phase. Additionally, analysis of expression levels of a subset of genes by real time PCR technology revealed an agreement in expression of 90% of the examined genes when genomic DNA normalization was applied instead of 29-68% agreement when RNA normalization was used to measure the expression levels in the same set of RNA samples. Further examination of microarray expression levels displayed clusters of genes differentially expressed between the logarithmic, early stationary and late stationary growth phases. We conclude that genomic DNA standards offer advantages over conventional RNA normalization procedures and can be adapted for the investigation of microbial genomes.

Pharmacologic and pharmacokinetic profile of repifermin (KGF-2) in monkeys and comparative pharmacokinetics in humans

Repifermin (truncated, recombinant human keratinocyte growth factor-2, KGF-2) was evaluated in cynomolgus monkeys and healthy humans during a phase 1 trial. Monkeys received vehicle or repifermin at 20, 75, or 200 microg/kg IV or 750 microg/kg subcutaneous (SC) daily for 29 days. Clinical observations were made during the entire dosing period. Gross and microscopic changes were assessed at necropsy. Pharmacokinetic parameters and immunogenicity were evaluated in these monkeys and in humans, following a single or 7 daily IV bolus injections of 1, 5, 25, or 50 microg/kg repifermin. In monkeys, repifermin was well tolerated, and histologic evaluation demonstrated dose-dependent, reversible thickening of the mucosa throughout the alimentary tract, except for the stomach. In the alimentary tract tissues, nonepithelial tissues were not affected, indicating a specificity of repifermin for epithelial cells. Pharmacokinetics in both monkeys and humans were dose proportional, showed lack of drug accumulation with repeated daily dosing, and were characterized by high volumes of distribution and clearance rates, indicating substantial tissue binding and metabolism. Repifermin was not markedly immunogenic following multiple daily IV injections in either species. Serum repifermin concentrations in humans were comparable to those attained in monkeys that produced significant pharmacological effects on epithelial cells in the alimentary tract. These findings provide additional support for the ongoing clinical development of repifermin for diseases involving epithelial injury.