Characterizing the physical genome

Uncovering transcription factor modules using one- and three-dimensional analyses

Transcriptional regulation is a critical mediator of many normal cellular processes, as well as disease progression. Transcription factors (TFs) often co-localize at cis-regulatory elements on the DNA, form protein complexes, and collaboratively regulate gene expression. Machine learning and Bayesian approaches have been used to identify TF modules in a one-dimensional context. However, recent studies using high throughput technologies have shown that TF interactions should also be considered in three-dimensional nuclear space. Here, we describe methods for identifying TF modules and discuss how moving from a one-dimensional to a three-dimensional paradigm, along with integrated experimental and computational approaches, can lead to a better understanding of TF association networks.

MicroRNAs in the pathogenesis of cancer

MicroRNAs (miRs) are small (19-25 nucleotides) non-protein-coding RNAs involved in development, differentiation, and aging; they act by inducing messenger RNA (mRNA) silencing through degradation, and post-transcriptional or decoy activity. miR profiles of human solid and hematologic malignancies have highlighted their potential value as tumor markers in cancer patient management. Different experimental lines of evidence have confirmed that deregulation of miRs not only results as consequence of cancer progression but also directly promotes tumor initiation and progression in a cause-effect manner. These findings reveal a potential and appealing role for miRs as cancer therapeutic targets. This review focuses on the causes and consequences of miR deregulation in carcinogenesis and tumor progression. The work aims at providing the molecular bases for the understanding of the potential role of miRs in the translational and clinical setting.

GLOBE: Analysis of DNA-protein interaction analysis

Emulsion PCR, a hyper, multi, parallel PCR in water-phase droplets in water-in-oil (w/o) emulsion, can be used to make a genetic l ibrary on beads (GLOBE). In GLOBE, we have developed a novel high-throughput screening system for the analysis of the recognition sequences of DNA-binding proteins, which can be prepared by using either an in vivo or an in vitro protein synthesis system. The system can contribute to the low-cost comprehensive analysis of transcription factor-binding regions.

Navigating public microarray databases

With the ever-escalating amount of data being produced by genome-wide microarray studies, it is of increasing importance that these data are captured in public databases so that researchers can use this information to complement and enhance their own studies. Many groups have set up databases of expression data, ranging from large repositories, which are designed to comprehensively capture all published data, through to more specialized databases. The public repositories, such as ArrayExpress at the European Bioinformatics Institute contain complete datasets in raw format in addition to processed data, whilst the specialist databases tend to provide downstream analysis of normalized data from more focused studies and data sources. Here we provide a guide to the use of these public microarray resources.

The role of rare structural variants in the genetics of autism spectrum disorders

Autism is a neurodevelopmental disorder characterized by impaired social interaction and communication and restricted interests and behaviors. Despite high estimates of heritability, genetic causes of ASD have long been elusive, due in part to a high degree of genetic and phenotypic heterogeneity (Bailey et al., 1995). Recently, important advances have been made in the genetics of ASD with the use of new technologies for the direct detection of copy number variation (CNV) in the human genome. CNV studies have revealed that de novo deletions and duplications, typically less than 1 Mb in size, are strongly associated with ASD, suggesting that spontaneous structural mutations play a more important role in the etiology of disease than was previously recognized. Rare mutations have been identified at many different locations in the genome, and multiple 'hot spots' have been identified where identical rearrangements recur with high frequency. These findings are consistent with the hypothesis that autism, like mental retardation, is caused by a large number of individually rare mutations. These studies serve as a model for how other emerging technologies for mutation detection (e.g. next generation sequencing platforms) could be used to further elucidate the role of rare sequence changes in ASD.

Toxicogenomics: transcription profiling for toxicology assessment

Toxicogenomics, the application of transcription profiling to toxicology, has been widely used for elucidating the molecular and cellular actions of chemicals and other environmental stressors on biological systems, predicting toxicity before any functional damages, and classification of known or new toxicants based on signatures of gene expression. The success of a toxicogenomics study depends upon close collaboration among experts in different fields, including a toxicologist or biologist, a bioinformatician, statistician, physician and, sometimes, mathematician. This review is focused on toxicogenomics studies, including transcription profiling technology, experimental design, significant gene extraction, toxicological results interpretation, potential pathway identification, database input and the applications of toxicogenomics in various fields of toxicological study.

Rethinking periodontal inflammation

Clinical signs and symptoms, as well as medical and dental history, are all considered in the clinical determination of gingival inflammation and periodontal disease severity. However, the "biologic systems model" highlights that the clinical presentation of periodontal disease is closely tied to the underlying biologic phenotype. We propose that the determination and integration of subject-level factors, microbial composition, systemic immune response, and gingival tissue inflammatory mediator responses will better reflect the biology of the biofilm-gingival interface in a specific patient and may provide insights on clinical management. Disease classifications and multivariable models further refine the biologic basis for the increasing severity of periodontal disease expression. As such, new classifications may better identify disease-susceptible and treatment-non-responsive individuals than current classifications that are heavily influenced by probing and attachment level measurements alone. New data also suggest that the clinical characteristics of some complex diseases, such as periodontal disease, are influenced by the genetic and epigenetic contributions to clinical phenotype. Although the genetic basis for periodontal disease is considered imperative for setting an inflammatory capacity for an individual and, thus, a threshold for severity, there is evidence to suggest an epigenetic component is involved as well. Many factors long associated with periodontitis, including bacterial accumulations, smoking, and diabetes, are known to produce strong epigenetic changes in tissue behavior. We propose that we are now able to rethink periodontal disease in terms of a biologic systems model that may help to establish more homogeneous diagnostic categories and can provide insight into the expected response to treatment.

Genome-wide analysis of chromatin status using tiling microarrays

The eukaryotic genome is packaged into chromatin, and chromatin modification and remodeling play an important role in transcriptional regulation, DNA replication, recombination and repair. Recent findings have shown that various post-translational histone modifications cooperate to recruit different effector proteins that bring about mobilization of the nucleosomes and cause distinct downstream consequences. The combination of chromatin immunoprecipitation (ChIP) using antibodies directed against the core histones or specific histone modifications, with high-resolution tiling microarray analysis allows the examination of nucleosome occupancy and histone modification status genome-wide. Comparing genome-wide chromatin status with global gene expression patterns can reveal causal connections between specific patterns of histone modifications and the resulting gene expression. Here, we describe current methods based on recent advances in microarray technology to conduct such studies.

Genomic signal processing: from matrix algebra to genetic networks

DNA microarrays make it possible, for the first time, to record the complete genomic signals that guide the progression of cellular processes. Future discovery in biology and medicine will come from the mathematical modeling of these data, which hold the key to fundamental understanding of life on the molecular level, as well as answers to questions regarding diagnosis, treatment, and drug development. This chapter reviews the first data-driven models that were created from these genome-scale data, through adaptations and generalizations of mathematical frameworks from matrix algebra that have proven successful in describing the physical world, in such diverse areas as mechanics and perception: the singular value decomposition model, the generalized singular value decomposition model comparative model, and the pseudoinverse projection integrative model. These models provide mathematical descriptions of the genetic networks that generate and sense the measured data, where the mathematical variables and operations represent biological reality. The variables, patterns uncovered in the data, correlate with activities of cellular elements such as regulators or transcription factors that drive the measured signals and cellular states where these elements are active. The operations, such as data reconstruction, rotation, and classification in subspaces of selected patterns, simulate experimental observation of only the cellular programs that these patterns represent. These models are illustrated in the analyses of RNA expression data from yeast and human during their cell cycle programs and DNA-binding data from yeast cell cycle transcription factors and replication initiation proteins. Two alternative pictures of RNA expression oscillations during the cell cycle that emerge from these analyses, which parallel well-known designs of physical oscillators, convey the capacity of the models to elucidate the design principles of cellular systems, as well as guide the design of synthetic ones. In these analyses, the power of the models to predict previously unknown biological principles is demonstrated with a prediction of a novel mechanism of regulation that correlates DNA replication initiation with cell cycle-regulated RNA transcription in yeast. These models may become the foundation of a future in which biological systems are modeled as physical systems are today.

The use of high-dimensional biology (genomics, transcriptomics, proteomics, and metabolomics) to understand the preterm parturition syndrome

High-dimensional biology (HDB) refers to the simultaneous study of the genetic variants (DNA variation), transcription (messenger RNA [mRNA]), peptides and proteins, and metabolites of an organ, tissue, or an organism in health and disease. The fundamental premise is that the evolutionary complexity of biological systems renders them difficult to comprehensively understand using only a reductionist approach. Such complexity can become tractable with the use of "omics" research. This term refers to the study of entities in aggregate. The current nomenclature of "omics" sciences includes genomics for DNA variants, transcriptomics for mRNA, proteomics for proteins, and metabolomics for intermediate products of metabolism. Another discipline relevant to medicine is pharmacogenomics. The two major advances that have made HDB possible are technological breakthroughs that allow simultaneous examination of thousands of genes, transcripts, and proteins, etc., with high-throughput techniques and analytical tools to extract information. What is conventionally considered hypothesis-driven research and discovery-driven research (through "omic" methodologies) are complementary and synergistic. Here we review data which have been derived from: 1) genomics to examine predisposing factors for preterm birth; 2) transcriptomics to determine changes in mRNA in reproductive tissues associated with preterm labour and preterm prelabour rupture of membranes; 3) proteomics to identify differentially expressed proteins in amniotic fluid of women with preterm labour; and 4) metabolomics to identify the metabolic footprints of women with preterm labour likely to deliver preterm and those who will deliver at term. The complementary nature of discovery science and HDB is emphasised.

Molecular profiling reveals myeloid leukemia cell lines to be faithful model systems characterized by distinct genomic aberrations

To model and investigate different facets of leukemia pathogenesis, a widely accepted approach is to use immortalized leukemia cell lines. Although these provide powerful tools to our knowledge, few studies have addressed the question whether hematopoietic cell lines represent accurate and reliable model systems. To improve the molecular characterization of these model systems, we analyzed 17 myeloid leukemia cell lines using DNA microarray technology. By array-based comparative genomic hybridization, we identified recurrent genomic DNA gains and losses, as well as high-level amplifications. Parallel analysis of gene expression helped delineate potential candidate genes, and unsupervised analysis of gene expression data revealed cell lines to cluster in part based on underlying cytogenetic abnormalities. Comparison with clinical leukemia specimens showed that key signatures were retained, as myeloid cell lines with characteristic cytogenetic aberrations co-clustered with leukemia samples carrying the respective abnormality. Signatures were also quite robust, as expression data from cell lines correlated highly with published data. Thus, our analyses demonstrate myeloid cell lines to exhibit conserved and stable signatures reflecting the underlying primary cytogenetic aberrations. Our refined molecular characterization of myeloid cell lines supports the utility of cell lines as faithful and powerful model systems and provides additional insights into the molecular mechanisms of leukemogenesis.

Singular value decomposition of genome-scale mRNA lengths distribution reveals asymmetry in RNA gel electrophoresis band broadening

We describe the singular value decomposition (SVD) of yeast genome-scale mRNA lengths distribution data measured by DNA microarrays. SVD uncovers in the mRNA abundance levels data matrix of genes x arrays, i.e., electrophoretic gel migration lengths or mRNA lengths, mathematically unique decorrelated and decoupled "eigengenes." The eigengenes are the eigenvectors of the arrays x arrays correlation matrix, with the corresponding series of eigenvalues proportional to the series of the "fractions of eigen abundance." Each fraction of eigen abundance indicates the significance of the corresponding eigengene relative to all others. We show that the eigengenes fit "asymmetric Hermite functions," a generalization of the eigenfunctions of the quantum harmonic oscillator and the integral transform which kernel is a generalized coherent state. The fractions of eigen abundance fit a geometric series as do the eigenvalues of the integral transform which kernel is a generalized coherent state. The "asymmetric generalized coherent state" models the measured data, where the profiles of mRNA abundance levels of most genes as well as the distribution of the peaks of these profiles fit asymmetric Gaussians. We hypothesize that the asymmetry in the distribution of the peaks of the profiles is due to two competing evolutionary forces. We show that the asymmetry in the profiles of the genes might be due to a previously unknown asymmetry in the gel electrophoresis thermal broadening of a moving, rather than a stationary, band of RNA molecules.

In Vitro selection of DNA binding sites for transcription factor, PhaR, from Paracoccus denitrificans using genetic library on microbeads and flow cytometry

We attempted the selection of a site for DNA binding to a transcription factor, PhaR, from Paracoccus denitrificans expressed by cell-free protein synthesis, from a random oligonucleotide library on microbeads that was constructed by the emulsion PCR technique. PhaR is a repressor protein in P. denitrificans that binds to the phaP promoter region. We acquired three types of PhaR-binding DNA fragment using this system. The selected fragments contained a perfect PhaR binding consensus site (TGC I), a sequence similar to that of TGC I, and another PhaR binding site (TGC II).

Engineering RNA-based circuits

Nucleic acids can modulate gene function by base-pairing, via the molecular recognition of proteins and metabolites, and by catalysis. This diversity of functions can be combined with the ability to engineer nucleic acids based on Watson-Crick base-pairing rules to create a modular set of molecular "tools" for biotechnological and medical interventions in cellular metabolism. However, these individual RNA-based tools are most powerful when combined into rational logical or regulatory circuits, and the circuits can in turn be evolved for optimal function. Examples of genetic circuits that control translation and transcription are herein detailed, and more complex circuits with medical applications are anticipated.

The Oct4 and Nanog transcription network regulates pluripotency in mouse embryonic stem cells

Oct4 and Nanog are transcription factors required to maintain the pluripotency and self-renewal of embryonic stem (ES) cells. Using the chromatin immunoprecipitation paired-end ditags method, we mapped the binding sites of these factors in the mouse ES cell genome. We identified 1,083 and 3,006 high-confidence binding sites for Oct4 and Nanog, respectively. Comparative location analyses indicated that Oct4 and Nanog overlap substantially in their targets, and they are bound to genes in different configurations. Using de novo motif discovery algorithms, we defined the cis-acting elements mediating their respective binding to genomic sites. By integrating RNA interference-mediated depletion of Oct4 and Nanog with microarray expression profiling, we demonstrated that these factors can activate or suppress transcription. We further showed that common core downstream targets are important to keep ES cells from differentiating. The emerging picture is one in which Oct4 and Nanog control a cascade of pathways that are intricately connected to govern pluripotency, self-renewal, genome surveillance and cell fate determination.

Affinity selection of DNA-binding protein complexes using mRNA display

Comprehensive analysis of DNA–protein interactions is important for mapping transcriptional regulatory networks on a genome-wide level. Here we present a new application of mRNA display for in vitro selection of DNA-binding protein heterodimeric complexes. Under improved selection conditions using a TPA-responsive element (TRE) as a bait DNA, known interactors c-fos and c-jun were simultaneously enriched about 100-fold from a model library (a 1:1:20 000 mixture of c-fos, c-jun and gst genes) after one round of selection. Furthermore, almost all kinds of the AP-1 family genes including c-jun, c-fos, junD, junB, atf2 and b-atf were successfully selected from an mRNA display library constructed from a mouse brain poly A⁺ RNA after six rounds of selection. These results indicate that the mRNA display selection system can identify a variety of DNA-binding protein complexes in a single experiment. Since almost all transcription factors form heterooligomeric complexes to bind with their target DNA, this method should be most useful to search for DNA-binding transcription factor complexes.

Evaluation of experimental designs for two-color cDNA microarrays

The major goal of two-color cDNA microarray experiments is to measure the relative gene expression level (i.e., relative amount of mRNA) of each gene between samples in studies of gene expression. More specifically, given an N-sample experiment, we need all N(N - 1)/2 relative expression levels of all sample pairs of each gene for identification of the differentially expressed genes and for clustering of gene expression patterns. However, the intensities observed from two-color cDNA microarray experiments do not simply represent the relative gene expression level. They are composed of signal (gene expression level), noise, and other factors. In discussions on the experimental design of two-color cDNA microarray experiments, little attention has been given to the fact that different combinations of test and control samples will produce microarray intensities data with varying intrinsic composition of factors. As a consequence, not all experimental designs for two-color cDNA microarray experiments are able to provide all possible relative gene expression levels. This phenomenon has never been addressed. To obtain all possible relative gene expression levels, a novel method for two-color cDNA microarray experimental design evaluation is necessary that will allow the making of an accurate choice. In this study, we propose a model-based approach to illustrate how the factor composition of microarray intensities changed with different experimental designs in two-color cDNA microarray experiments. By analyzing 12 experimental designs (including 5 general forms), we demonstrate that not all experimental designs are able to provide all possible relative gene expression levels due to the differences in factor composition. Our results indicate that whether an experimental design can provide all possible relative expression levels of all sample pairs for each gene should be the first criterion to be considered in an evaluation of experimental designs for two-color cDNA microarray experiments.

Using bioinformatics and genome analysis for new therapeutic interventions

The genome era provides two sources of knowledge to investigators whose goal is to discover new cancer therapies: first, information on the 20,000 to 40,000 genes that comprise the human genome, the proteins they encode, and the variation in these genes and proteins in human populations that place individuals at risk or that occur in disease; second, genome-wide analysis of cancer cells and tissues leads to the identification of new drug targets and the design of new therapeutic interventions. Using genome resources requires the storage and analysis of large amounts of diverse information on genetic variation, gene and protein functions, and interactions in regulatory processes and biochemical pathways. Cancer bioinformatics deals with organizing and analyzing the data so that important trends and patterns can be identified. Specific gene and protein targets on which cancer cells depend can be identified. Therapeutic agents directed against these targets can then be developed and evaluated. Finally, molecular and genetic variation within a population may become the basis of individualized treatment.

Gene expression profiling in acute myeloid leukemia

Over the last decades, significant advances have been made in the knowledge and treatment of acute myeloid leukemia (AML). The WHO has recognized this new information by incorporating into its classification morphologic, immunophenotypic, genetic, and clinical features in an attempt to define biologically and clinically relevant entities. Nevertheless, well-defined cytogenetic subgroups exhibit considerable heterogeneity, and in many AML subtypes the pathogenic event is still not known. A classification system based on the underlying molecular pathogenetic abnormalities would be ideal, but such detailed knowledge is not yet available. Novel approaches in genomics, such as surveying the expression levels of thousands of genes in parallel using DNA microarray technology, open possibilities to further refine the studies on AML. Today, gene expression profiling in AML is becoming well established and has already been proven to be valuable in diagnosing different cytogenetic subtypes, discovering novel AML subclasses, and predicting clinical outcome. Recently, gene expression profiling studies in AML showed a remarkable level of concordance in findings, which may ultimately lead to an increasingly refined molecular taxonomy. While many challenges remain to be overcome, a combination of gene expression profiling with other microarray-based applications, high-throughput mutational analyses and proteomic approaches will not only significantly contribute to the classification and therapeutic decision making of AML, but also give important insights into the true pathobiologic nature of this type of leukemia.

Comparative genomic hybridization on mouse cDNA microarrays and its application to a murine lymphoma model

Microarray-based formats offer a high-resolution alternative to conventional, chromosome-based comparative genomic hybridization (CGH) methods for assessing DNA copy number alteration (CNA) genome-wide in human cancer. For murine tumors, array CGH should provide even greater advantage, since murine chromosomes are more difficult to individually discern. We report here the adaptation and evaluation of a cDNA microarray-based CGH method for the routine characterization of CNAs in murine tumors, using mouse cDNA microarrays representing approximately 14,000 different genes, thereby providing an average mapping resolution of 109 kb. As a first application, we have characterized CNAs in a set of 10 primary and recurrent lymphomas derived from a Myc-induced murine lymphoma model. In primary lymphomas and more commonly in Myc-independent relapses, we identified a recurrent genomic DNA loss at chromosome 3G3-3H4, and recurrent amplifications at chromosome 3F2.1-3G3 and chromosome 15E1/E2-15F3, the boundaries of which we defined with high resolution. Further, by profiling gene expression using the same microarray platform, we identified within CNAs the relevant subset of candidate cancer genes displaying comparably altered expression, including Mcl1 (myeloid cell leukemia sequence 1), a highly expressed antiapoptotic gene residing within the chr 3 amplicon peak. CGH on mouse cDNA microarrays therefore represents a reliable method for the high-resolution characterization of CNAs in murine tumors, and a powerful approach for elucidating the molecular events in tumor development and progression in murine models.

PCR amplification from single DNA molecules on magnetic beads in emulsion: application for high-throughput screening of transcription factor targets

We have developed a novel method of genetic library construction on magnetic microbeads based on solid-phase single-molecule PCR in a fine and robust water-phase compartment formed in water-in-oil (w/o) emulsions. In this method, critically diluted DNA fragments were distributed over the emulsion as templates, where beads crosslinked with multiple primers and other PCR components were encapsulated to form multiple reaction compartments. The delivered DNA was then amplified and covalently immobilized on the beads in parallel, within individual compartments, to construct a genetic library on beads (GLOBE), which was readily applicable to a genomewide global scanning of genetic elements recognized by a defined DNA-binding protein. We constructed a GLOBE of Paracoccus denitrificans and selected gene beads that were bound to the His-tagged transcription factor PhaR by flow cytometry. As a result of flow cytometry screening with an anti-His fluorescent antibody, the PhaR target fragments were enriched 1200-fold from this library with this system. Therefore, this system is a powerful tool for analyzing the transcription network on a genomewide scale.

Cytogenetic and molecular genetic alterations in hepatocellular carcinoma

Specific chromosome aberrations are frequently detected during the development of hepatocellular carcinoma. Molecular cytogenetic approaches such as comparative genomic hybridization and loss of heterozygosity analyses have provided fruitful information on changes in HCC cases at the genomic level. Mapping of chromosome gains and losses have frequently resulted in the identification of oncogenes and tumor suppressors, respectively. In this review, we summarize some frequently detected chromosomal aberrations reported for hepatocellular carcinoma cases using comparative genomic hybridization and loss of heterozygosity studies. Focus will be on gains of 1q, 8q, and 20q, and losses of 4q, 8p, 13q, 16q, and 17p. We then examine the candidate oncogenes and tumor suppressors located within these regions, and explore their possible functions in hepatocarcinogenesis. Finally, the impact of microarray-based screening platforms will be discussed.

Identification of amplified and highly expressed genes in amplicons of the T-cell line huT78 detected by cDNA microarray CGH

Background

Conventional Comparative Genomic Hybridization (CGH) has been widely used for detecting copy number alterations in cancer and for identifying regions containing candidate tumor responsible genes. Recently, several studies have shown the utility of cDNA microarray CGH for studing gene copy changes in various types of tumors. However, no such studies on T-cell lymphomas have been performed. To date T-cell lymphomas analyzed by the use of chromosome CGH have revealed only slight copy number alterations and not gene amplifications.

Results

In the present study, we describe the characterization of three amplicons of the T-cell line huT78 located at 2q34-q37, 8q23-q24 and 20p, where new amplified and overexpressed genes are found. The use of a cDNA microarray containing 7.657 transcripts allowed the identification of certain genes, such as BCLX, PCNA, FKBP1A, IGFBP2 and cMYC, that are amplified, highly expressed, and also contained in the amplicons on 20p and 2q. The expresion of these genes was analyzed in 39 T-cell lymphomas and 3 other T-cell lines.

Conclusion

By the use of conventional CGH and CGH and expression cDNA microarrays we defined three amplicons in the T-cell line huT78 and identified several novel gene amplifications (BCLX, PCNA, FKBP1A, IGFBP2 and cMYC). We showed that overexpression of the amplified genes could be attributable to gene dosage. We speculate that deregulation of those genes could be important in the development of T-cell lymphomas and/or in the maintenance of T-cell lines.

Protein microarrays for the diagnosis of allergic diseases: state-of-the-art and future development

In the emerging field of

Mapping DNA-protein interactions in large genomes by sequence tag analysis of genomic enrichment

Identifying the chromosomal targets of transcription factors is important for reconstructing the transcriptional regulatory networks underlying global gene expression programs. We have developed an unbiased genomic method called sequence tag analysis of genomic enrichment (STAGE) to identify the direct binding targets of transcription factors in vivo. STAGE is based on high-throughput sequencing of concatemerized tags derived from target DNA enriched by chromatin immunoprecipitation. We first used STAGE in yeast to confirm that RNA polymerase III genes are the most prominent targets of the TATA-box binding protein. We optimized the STAGE protocol and developed analysis methods to allow the identification of transcription factor targets in human cells. We used STAGE to identify several previously unknown binding targets of human transcription factor E2F4 that we independently validated by promoter-specific PCR and microarray hybridization. STAGE provides a means of identifying the chromosomal targets of DNA-associated proteins in any sequenced genome.

Gene expression analysis of chromosomal regions with gain or loss of genetic material detected by comparative genomic hybridization

Comparative genomic hybridization (CGH) has been widely used to detect copy number alterations in cancer and to identify regions containing candidate tumor-responsible genes; however, gene expression changes have been described only in highly amplified regions (amplicons). To study the overall impact of slight copy number changes on gene expression, we analyzed 16 T-cell lymphomas by using CGH and a custom-designed cDNA microarray containing 7,657 genes and expressed sequence tags related to tumorigenesis. We evaluated mean gene expression and variability within CGH-altered regions and explored the relationship between the effects of the gene and its position within these regions. Minimally overlapping CGH candidate areas (6q25, 13q21-q22, and 19q13.1) revealed a weak relationship between altered genomic content and gene expression. However, some candidate genes showed modified expression within these regions in the majority of tumors; these candidate genes were evaluated and confirmed in another independent series of 23 T-cell lymphomas by use of the same cDNA microarray and by FISH on a tissue microarray. When all the CGH regions detected for each tumor were considered, we found a significant increase or decrease in the mean expression of the genes contained in gained or lost regions, respectively. In addition, we found that the expression of a gene was dependent not only on its position within an altered region but also on its own mechanism of regulation: genes in the same altered region responded very differently to the gain or loss of genetic material. Supplementary material for this article can be found on the Genes, Chromosomes, and Cancer website at http://www.interscience.wiley.com/jpages/1045-2257/suppmat/index.html.

Global role of TATA box-binding protein recruitment to promoters in mediating gene expression profiles

The recruitment of TATA box-binding protein (TBP) to promoters is one of the rate-limiting steps during transcription initiation. However, the global importance of TBP recruitment in determining the absolute and changing levels of transcription across the genome is not known. We used a genomic approach to explore the relationship between TBP recruitment to promoters and global gene expression profiles in Saccharomyces cerevisiae. Our data indicate that first, RNA polymerase III promoters are the most prominent binding targets of TBP in vivo. Second, the steady-state transcript levels of genes throughout the genome are proportional to the occupancy of their promoters by TBP, and changes in the expression levels of these genes are closely correlated with changes in TBP recruitment to their promoters. Third, a consensus TATA element does not appear to be a major determinant of either TBP binding or gene expression throughout the genome. Our results indicate that the recruitment of TBP to promoters in vivo is of universal importance in determining gene expression levels in yeast, regardless of the nature of the core promoter or the type of activator or repressor that may mediate changes in transcription. The primary data reported here are available at http://www.iyerlab.org/tbp.

Genomic imbalances in mental retardation

INTRODUCTION

It has been estimated that cytogenetically visible rearrangements are present in approximately 1% of newborns. These chromosomal changes can cause a wide range of deleterious developmental effects, including mental retardation (MR). It is assumed that many other cases exist where the cause is a submicroscopic deletion or duplication. To facilitate the detection of such cases, different techniques have been developed, which have differing efficiency as to the number of loci and patients that can be tested.

METHODS

We implemented multiplex amplifiable probe hybridisation (MAPH) to test areas known to be rearranged in MR patients (for example, subtelomeric/pericentromeric regions and those affected in microdeletion syndromes) and to look for new regions that might be related to MR.

RESULTS

In this study, over 30 000 screens for duplications and deletions were carried out; 162 different loci tested in each of 188 developmentally delayed patients. The analysis resulted in the detection of 19 rearrangements, of which approximately 65% would not have been detected by conventional cytogenetic analysis. A significant fraction (46%) of the rearrangements found were interstitial, despite the fact that only a limited number of these loci have so far been tested.

DISCUSSION

Our results strengthen the arguments for whole genome screening within this population, as it can be assumed that many more interstitial rearrangements would be detected. The strengths of MAPH for this analysis are the simplicity, the high throughput potential, and the high resolution of analysis. This combination should help in the future identification of the specific genes that are responsible for MR.

A Simple Epigenetic Method for the Diagnosis and Classification of Brain Tumors

The new, simple, and reliable method for the diagnosis of brain tumors is described. It is based on a TLC quantitative determination of 5-methylcytosine (m5C) in relation to its damage products of DNA from tumor tissue. Currently, there is evidence that oxidative stress through reactive oxygen species (ROS) plays an important role in the etiology and progression of several human diseases. Oxidative damage of DNA, lipids, and proteins is deleterious for the cell. m5C, along with other basic components of DNA, is the target for ROS, which results in the appearance of new modified nucleic acid bases. If so, m5C residue constitutes a mutational hotspot position, whether it occurs within a nucleotide sequence of a structural gene or a regulatory region. Here, we show the results of the analysis of 82 DNA samples taken from brain tumor tissues. DNA was isolated and hydrolyzed into nucleotides, which, after labeling with [γ-32P]ATP, were separated on TLC. Chromatograms were evaluated using PhosphorImager and the amounts of 5-methyldeoxycytosine (m5dC) were calculated as a ratio (R) of m5dC to m5dC + deoxycytosine + deoxythymidine spot intensities. The R value could not only be a good diagnostic marker for brain tumors but also a factor differentiating low-grade and high-grade gliomas. Therefore, DNA methylation pattern might be a useful tool to give a primary diagnosis of a brain tumor or as a marker for the early detection of the relapse of the disease. This method has several advantages over those existing nowadays.

Genomic microarrays in the spotlight

Microarray-based comparative genomic hybridization (array-CGH) has emerged as a revolutionary platform, enabling the high-resolution detection of DNA copy number aberrations. In this article we outline the use and limitations of genomic clones, cDNA clones and PCR products as targets for genomic microarray construction. Furthermore, the applications and future aspects of these arrays for DNA copy number analysis in research and diagnostics, epigenetic profiling and gene annotation are discussed. These recent developments of genomic microarrays mark only the beginning of a new generation of high-resolution and high-throughput tools for genetic analysis.

Identifying global regulators in transcriptional regulatory networks in bacteria

The machinery for cells to take decisions, when environmental conditions change, includes protein-DNA interactions defined by transcriptional factors and their targets around promoters. Properties of global regulators are revised attempting to reach diagnostic explicit criteria for their definition and eventual future computational identification. These include among others, the number of regulated genes, the number and type of co-regulators, the different sigma-classes of promoters and the number of transcriptional factors they regulate, the size of the evolutionary family they belong to, and the variety of conditions where they exert their control. As a consequence, global versus local regulation can be identified, as shown for Escherichia coli and eventually in other genomes.

Genomics, transcriptomics, proteomics, and numbers

OBJECTIVE

To review the advances in clinically useful molecular biologic techniques and to identify their applications in clinical practice, as presented at the 11th Annual William Beaumont Hospital DNA Symposium.

DATA SOURCES

The 8 manuscripts submitted were reviewed, and their major findings were compared with literature on the same or related topics.

STUDY SELECTION

Manuscripts address the use of molecular techniques in microbiology to evaluate infectious disease and epidemiology; molecular microbiology methods, including rapid-cycle real-time polymerase chain reaction; peroxisome proliferator-activated receptor gamma as a potential therapeutic target in inflammatory bowel disease or colon cancer; the effect of nonapoptotic doses of the bisbenizamide dye Hoechst 33342 on luciferase expression in plasmid-transfected BC3H-1 myocytes; the routine use of cystic fibrosis screening and its challenges; and the use of flow cytometry and/or chromosomal translocation in the diagnostic evaluation of hematopoietic malignancies.

DATA SYNTHESIS

Three current issues related to the use of molecular tests in clinical laboratories are (1) the restriction on introducing new tests secondary to existing patents or licenses; (2) the preanalytic variables for the different specimen types currently in use, including whole blood, plasma, serum, fresh or frozen tissues, and free-circulating DNA; and (3) the interpretation of studies evaluating the association of complex diseases with a single mutation or single-nucleotide polymorphism. Molecular methods have had a major impact on infectious disease through the rapid identification of organisms, the evaluation of outbreaks, and the characterization of drug resistance when compared with standard culture techniques. The activation of peroxisome proliferator-activated receptor gamma stimulated by thiazolidinedione is useful in the treatment of type II diabetes mellitus and may have value in preventing inflammatory bowel disease or colon cancer. Hoechst 33342 binding to adenine-thymine-rich regions in the minor groove of DNA is a fluorescent stain for DNA and initiates apoptosis at >10 microg/mL. Lower doses of Hoechst 33342 promote luciferase expression by a mechanism that may involve binding to cryptic promoters facilitated by dye-associated misalignment of the tertiary structure of DNA. The routine use of cystic fibrosis screening is complicated by the more than 1000 mutations associated with the disease. The use of 4-color flow cytometry and the detection of chromosomal translocation are both invaluable aids in establishing the diagnosis of lymphoid or myeloid hematopoietic malignancies.

CONCLUSIONS

The current postgenomic era will continue to emphasize the use of microarrays and database software for genomic, transcriptomic, and proteomic screening in the search for useful clinical assays. The number of molecular pathologic techniques will expand as additional disease-associated mutations are defined.

The Longhorn Array Database (LAD): an open-source, MIAME compliant implementation of the Stanford Microarray Database (SMD)

BACKGROUND

The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms.

DESCRIPTION

The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD is available at http://www.longhornarraydatabase.org

CONCLUSIONS

Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data.

Definition of a critical region on chromosome 18 for congenital aural atresia by arrayCGH

Deletions of the long arm of chromosome 18 occur in approximately 1 in 10,000 live births. Congenital aural atresia (CAA), or narrow external auditory canals, occurs in approximately 66% of all patients who have a terminal deletion 18q. The present report describes a series of 20 patients with CAA, of whom 18 had microscopically visible 18q deletions. The extent and nature of the chromosome-18 deletions were studied in detail by array-based comparative genomic hybridization (arrayCGH). High-resolution chromosome-18 profiles were obtained for all patients, and a critical region of 5 Mb that was deleted in all patients with CAA could be defined on 18q22.3-18q23. Therefore, this region can be considered as a candidate region for aural atresia. The array-based high-resolution copy-number screening enabled a refined cytogenetic diagnosis in 12 patients. Our approach appeared to be applicable to the detection of genetic mosaicisms and, in particular, to a detailed delineation of ring chromosomes. This study clearly demonstrates the power of the arrayCGH technology in high-resolution molecular karyotyping. Deletion and amplification mapping can now be performed at the submicroscopic level and will allow high-throughput definition of genomic regions harboring disease genes.