Identification of a novel cis-regulatory element involved in the heat shock response in Caenorhabditis elegans using microarray gene expression and computational methods

MOPAT: a graph-based method to predict recurrent cis-regulatory modules from known motifs

The identification of cis-regulatory modules (CRMs) can greatly advance our understanding of eukaryotic regulatory mechanism. Current methods to predict CRMs from known motifs either depend on multiple alignments or can only deal with a small number of known motifs provided by users. These methods are problematic when binding sites are not well aligned in multiple alignments or when the number of input known motifs is large. We thus developed a new CRM identification method MOPAT (motif pair tree), which identifies CRMs through the identification of motif modules, groups of motifs co-ccurring in multiple CRMs. It can identify ‘orthologous’ CRMs without multiple alignments. It can also find CRMs given a large number of known motifs. We have applied this method to mouse developmental genes, and have evaluated the predicted CRMs and motif modules by microarray expression data and known interacting motif pairs. We show that the expression profiles of the genes containing CRMs of the same motif module correlate significantly better than those of a random set of genes do. We also show that the known interacting motif pairs are significantly included in our predictions. Compared with several current methods, our method shows better performance in identifying meaningful CRMs.

DiRE: identifying distant regulatory elements of co-expressed genes

Regulation of gene expression in eukaryotic genomes is established through a complex cooperative activity of proximal promoters and distant regulatory elements (REs) such as enhancers, repressors and silencers. We have developed a web server named DiRE, based on the Enhancer Identification (EI) method, for predicting distant regulatory elements in higher eukaryotic genomes, namely for determining their chromosomal location and functional characteristics. The server uses gene co-expression data, comparative genomics and profiles of transcription factor binding sites (TFBSs) to determine TFBS-association signatures that can be used for discriminating specific regulatory functions. DiRE's unique feature is its ability to detect REs outside of proximal promoter regions, as it takes advantage of the full gene locus to conduct the search. DiRE can predict common REs for any set of input genes for which the user has prior knowledge of co-expression, co-function or other biologically meaningful grouping. The server predicts function-specific REs consisting of clusters of specifically-associated TFBSs and it also scores the association of individual transcription factors (TFs) with the biological function shared by the group of input genes. Its integration with the Array2BIO server allows users to start their analysis with raw microarray expression data. The DiRE web server is freely available at http://dire.dcode.org.

Sepsid even-skipped enhancers are functionally conserved in Drosophila despite lack of sequence conservation

The gene expression pattern specified by an animal regulatory sequence is generally viewed as arising from the particular arrangement of transcription factor binding sites it contains. However, we demonstrate here that regulatory sequences whose binding sites have been almost completely rearranged can still produce identical outputs. We sequenced the even-skipped locus from six species of scavenger flies (Sepsidae) that are highly diverged from the model species Drosophila melanogaster, but share its basic patterns of developmental gene expression. Although there is little sequence similarity between the sepsid eve enhancers and their well-characterized D. melanogaster counterparts, the sepsid and Drosophila enhancers drive nearly identical expression patterns in transgenic D. melanogaster embryos. We conclude that the molecular machinery that connects regulatory sequences to the transcription apparatus is more flexible than previously appreciated. In exploring this diverse collection of sequences to identify the shared features that account for their similar functions, we found a small number of short (20-30 bp) sequences nearly perfectly conserved among the species. These highly conserved sequences are strongly enriched for pairs of overlapping or adjacent binding sites. Together, these observations suggest that the local arrangement of binding sites relative to each other is more important than their overall arrangement into larger units of cis-regulatory function.

Genome-wide investigation reveals pathogen-specific and shared signatures in the response of Caenorhabditis elegans to infection

Microarray analysis of the transcriptional response of C. elegans to four bacterial pathogens revealed that different infections trigger responses, some of which are common to all four pathogens, such as necrotic cell death, which has been associated with infection in humans.

Background

There are striking similarities between the innate immune systems of invertebrates and vertebrates. Caenorhabditis elegans is increasingly used as a model for the study of innate immunity. Evidence is accumulating that C. elegans mounts distinct responses to different pathogens, but the true extent of this specificity is unclear. Here, we employ direct comparative genomic analyses to explore the nature of the host immune response.

Results

Using whole-genome microarrays representing 20,334 genes, we analyzed the transcriptional response of C. elegans to four bacterial pathogens. Different bacteria provoke pathogen-specific signatures within the host, involving differential regulation of 3.5-5% of all genes. These include genes that encode potential pathogen-recognition and antimicrobial proteins. Additionally, variance analysis revealed a robust signature shared by the pathogens, involving 22 genes associated with proteolysis, cell death and stress responses. The expression of these genes, including those that mediate necrosis, is similarly altered following infection with three bacterial pathogens. We show that necrosis aggravates pathogenesis and accelerates the death of the host.

Conclusion

Our results suggest that in C. elegans, different infections trigger both specific responses and responses shared by several pathogens, involving immune defense genes. The response shared by pathogens involves necrotic cell death, which has been associated with infection in humans. Our results are the first indication that necrosis is important for disease susceptibility in C. elegans. This opens the way for detailed study of the means by which certain bacteria exploit conserved elements of host cell-death machinery to increase their effective virulence.

ModuleMiner - improved computational detection of cis-regulatory modules: are there different modes of gene regulation in embryonic development and adult tissues?

ModuleMiner detects cis-regulatory modules in a set of co-expressed genes in tissue-specific microarray clusters and in embryonic development datasets.

We present ModuleMiner, a novel algorithm for computationally detecting cis-regulatory modules (CRMs) in a set of co-expressed genes. ModuleMiner outperforms other methods for CRM detection on benchmark data, and successfully detects CRMs in tissue-specific microarray clusters and in embryonic development gene sets. Interestingly, CRM predictions for differentiated tissues exhibit strong enrichment close to the transcription start site, whereas CRM predictions for embryonic development gene sets are depleted in this region.

Large-scale analysis of transcriptional cis-regulatory modules reveals both common features and distinct subclasses

Analysis of 280 experimentally-verified cis-regulatory modules from Drosophila reveal features both common to all and unique to distinct subclasses of modules.

Background

Transcriptional cis-regulatory modules (for example, enhancers) play a critical role in regulating gene expression. While many individual regulatory elements have been characterized, they have never been analyzed as a class.

Results

We have performed the first such large-scale study of cis-regulatory modules in order to determine whether they have common properties that might aid in their identification and contribute to our understanding of the mechanisms by which they function. A total of 280 individual, experimentally verified cis-regulatory modules from Drosophila were analyzed for a range of sequence-level and functional properties. We report here that regulatory modules do indeed share common properties, among them an elevated GC content, an increased level of interspecific sequence conservation, and a tendency to be transcribed into RNA. However, we find that dense clustering of transcription factor binding sites, especially homotypic clustering, which is commonly believed to be a general characteristic of regulatory modules, is rather a feature that belongs chiefly to a specific subclass. This has important implications for current computational approaches, many of which are biased toward this subset. We explore two new strategies to assess binding site clustering and gauge their performances with respect to their ability to detect all 280 modules and various functionally coherent subsets.

Conclusion

Our findings demonstrate that cis-regulatory modules share common features that help to define them as a class and that may lead to new insights into mechanisms of gene regulation. However, these properties alone may not be sufficient to reliably distinguish regulatory from non-regulatory sequences. We also demonstrate that there are distinct subclasses of cis-regulatory modules that are more amenable to in silico detection than others and that these differences must be taken into account when attempting genome-wide regulatory element discovery.

Characterization of a novel Caenorhabditis elegans prolyl 4-hydroxylase with a unique substrate specificity and restricted expression in the pharynx and excretory duct

Collagen prolyl 4-hydroxylases (C-P4Hs) have a critical role in collagen synthesis, since 4-hydroxyproline residues are necessary for folding of the triple-helical molecules. Vertebrate C-P4Hs are alpha(2)beta(2) tetramers in which the beta subunit is identical to protein-disulfide isomerase (PDI). Three isoforms of the catalytic alpha subunit, PHY-1, PHY-2, and PHY-3, have been characterized from Caenorhabditis elegans, PHY-1 and PHY-2 being responsible for the hydroxylation of cuticle collagens, whereas PHY-3 is predicted to be involved in collagen synthesis in early embryos. We have characterized transcripts of two additional C. elegans alpha subunit-like genes, Y43F8B.4 and C14E2.4. Three transcripts were generated from Y43F8B.4, and a polypeptide encoded by one of them, named PHY-4.1, assembled into active (PHY-4.1)(2)/(PDI-2)(2) tetramers and PHY-4.1/PDI-2 dimers when coexpressed with C. elegans PDI-2 in insect cells. The C14E2.4 transcript was found to have a frameshift leading to the absence of codons for two residues critical for P4H catalytic activity. Thus, C. elegans has altogether four functional C-P4H alpha subunits, PHY-1, PHY-2, PHY-3, and PHY-4.1. The tetramers and dimers containing recombinant PHY-4.1 had a distinct substrate specificity from the other C-P4Hs in that they hydroxylated poly(l-proline) and certain other proline-rich peptides, including ones that are expressed in the pharynx, in addition to collagen-like peptides. These data and the observed restricted expression of the phy-4.1 transcript and PHY-4.1 polypeptide in the pharyngeal gland cells and the excretory duct suggest that in addition to collagens, PHY-4.1 may hydroxylate additional proline-rich proteins in vivo.

Phylogenetic footprinting analysis in the upstream regulatory regions of the Drosophila enhancer of split genes

During Drosophila development Suppressor of Hairless [Su(H)]-dependent Notch activation upregulates transcription of the Enhancer of split-Complex [E(spl)-C] genes. Drosophila melanogaster E(spl) genes share common transcription regulators including binding sites for Su(H), proneural, and E(spl) basic-helix-loop-helix (bHLH) proteins. However, the expression patterns of E(spl) genes during development suggest that additional factors are involved. To better understand regulators responsible for these expression patterns, recently available sequence and annotation data for multiple Drosophila genomes were used to compare the E(spl) upstream regulatory regions from more than nine Drosophila species. The mgamma and mbeta regulatory regions are the most conserved of the bHLH genes. Fine analysis of Su(H) sites showed that high-affinity Su(H) paired sites and the Su(H) paired site plus proneural site (SPS + A) architecture are completely conserved in a subset of Drosophila E(spl) genes. The SPS + A module is also present in the upstream regulatory regions of the more ancient mosquito and honeybee E(spl) bHLH genes. Additional transcription factor binding sites were identified upstream of the E(spl) genes and compared between species of Drosophila. Conserved sites provide new understandings about E(spl) regulation during development. Conserved novel sequences found upstream of multiple E(spl) genes may play a role in the expression of these genes.

Computational discovery of cis-regulatory modules in Drosophila without prior knowledge of motifs

Prediction of cis-regulatory modules ab initio, without any input of relevant motifs, is achieved with two novel methods.

We consider the problem of predicting cis-regulatory modules without knowledge of motifs. We formulate this problem in a pragmatic setting, and create over 30 new data sets, using Drosophila modules, to use as a 'benchmark'. We propose two new methods for the problem, and evaluate these, as well as two existing methods, on our benchmark. We find that the challenge of predicting cis-regulatory modules ab initio, without any input of relevant motifs, is a realizable goal.

Comparative analysis of regulatory motif discovery tools for transcription factor binding sites

In the post-genomic era, identification of specific regulatory motifs or transcription factor binding sites (TFBSs) in non-coding DNA sequences, which is essential to elucidate transcriptional regulatory networks, has emerged as an obstacle that frustrates many researchers. Consequently, numerous motif discovery tools and correlated databases have been applied to solving this problem. However, these existing methods, based on different computational algorithms, show diverse motif prediction efficiency in non-coding DNA sequences. Therefore, understanding the similarities and differences of computational algorithms and enriching the motif discovery literatures are important for users to choose the most appropriate one among the online available tools. Moreover, there still lacks credible criterion to assess motif discovery tools and instructions for researchers to choose the best according to their own projects. Thus integration of the related resources might be a good approach to improve accuracy of the application. Recent studies integrate regulatory motif discovery tools with experimental methods to offer a complementary approach for researchers, and also provide a much-needed model for current researches on transcriptional regulatory networks. Here we present a comparative analysis of regulatory motif discovery tools for TFBSs.

Predicting combinatorial binding of transcription factors to regulatory elements in the human genome by association rule mining

Background

Cis-acting transcriptional regulatory elements in mammalian genomes typically contain specific combinations of binding sites for various transcription factors. Although some cis-regulatory elements have been well studied, the combinations of transcription factors that regulate normal expression levels for the vast majority of the 20,000 genes in the human genome are unknown. We hypothesized that it should be possible to discover transcription factor combinations that regulate gene expression in concert by identifying over-represented combinations of sequence motifs that occur together in the genome. In order to detect combinations of transcription factor binding motifs, we developed a data mining approach based on the use of association rules, which are typically used in market basket analysis. We scored each segment of the genome for the presence or absence of each of 83 transcription factor binding motifs, then used association rule mining algorithms to mine this dataset, thus identifying frequently occurring pairs of distinct motifs within a segment.

Results

Support for most pairs of transcription factor binding motifs was highly correlated across different chromosomes although pair significance varied. Known true positive motif pairs showed higher association rule support, confidence, and significance than background. Our subsets of high-confidence, high-significance mined pairs of transcription factors showed enrichment for co-citation in PubMed abstracts relative to all pairs, and the predicted associations were often readily verifiable in the literature.

Conclusion

Functional elements in the genome where transcription factors bind to regulate expression in a combinatorial manner are more likely to be predicted by identifying statistically and biologically significant combinations of transcription factor binding motifs than by simply scanning the genome for the occurrence of binding sites for a single transcription factor.

Identification of tissue-specific cis-regulatory modules based on interactions between transcription factors

BACKGROUND

Evolutionary conservation has been used successfully to help identify cis-acting DNA regions that are important in regulating tissue-specific gene expression. Motivated by increasing evidence that some DNA regulatory regions are not evolutionary conserved, we have developed an approach for cis-regulatory region identification that does not rely upon evolutionary sequence conservation.

RESULTS

The conservation-independent approach is based on an empirical potential energy between interacting transcription factors (TFs). In this analysis, the potential energy is defined as a function of the number of TF interactions in a genomic region and the strength of the interactions. By identifying sets of interacting TFs, the analysis locates regions enriched with the binding sites of these interacting TFs. We applied this approach to 30 human tissues and identified 6232 putative cis-regulatory modules (CRMs) regulating 2130 tissue-specific genes. Interestingly, some genes appear to be regulated by different CRMs in different tissues. Known regulatory regions are highly enriched in our predicted CRMs. In addition, DNase I hypersensitive sites, which tend to be associated with active regulatory regions, significantly overlap with the predicted CRMs, but not with more conserved regions. We also find that conserved and non-conserved CRMs regulate distinct gene groups. Conserved CRMs control more essential genes and genes involved in fundamental cellular activities such as transcription. In contrast, non-conserved CRMs, in general, regulate more non-essential genes, such as genes related to neural activity.

CONCLUSION

These results demonstrate that identifying relevant sets of binding motifs can help in the mapping of DNA regulatory regions, and suggest that non-conserved CRMs play an important role in gene regulation.

Fine-tuning enhancer models to predict transcriptional targets across multiple genomes

Networks of regulatory relations between transcription factors (TF) and their target genes (TG)- implemented through TF binding sites (TFBS)- are key features of biology. An idealized approach to solving such networks consists of starting from a consensus TFBS or a position weight matrix (PWM) to generate a high accuracy list of candidate TGs for biological validation. Developing and evaluating such approaches remains a formidable challenge in regulatory bioinformatics. We perform a benchmark study on 34 Drosophila TFs to assess existing TFBS and cis-regulatory module (CRM) detection methods, with a strong focus on the use of multiple genomes. Particularly, for CRM-modelling we investigate the addition of orthologous sites to a known PWM to construct phyloPWMs and we assess the added value of phylogenentic footprinting to predict contextual motifs around known TFBSs. For CRM-prediction, we compare motif conservation with network-level conservation approaches across multiple genomes. Choosing the optimal training and scoring strategies strongly enhances the performance of TG prediction for more than half of the tested TFs. Finally, we analyse a 35^th TF, namely Eyeless, and find a significant overlap between predicted TGs and candidate TGs identified by microarray expression studies. In summary we identify several ways to optimize TF-specific TG predictions, some of which can be applied to all TFs, and others that can be applied only to particular TFs. The ability to model known TF-TG relations, together with the use of multiple genomes, results in a significant step forward in solving the architecture of gene regulatory networks.

MORPH: probabilistic alignment combined with hidden Markov models of cis-regulatory modules

The discovery and analysis of cis-regulatory modules (CRMs) in metazoan genomes is crucial for understanding the transcriptional control of development and many other biological processes. Cross-species sequence comparison holds much promise for improving computational prediction of CRMs, for elucidating their binding site composition, and for understanding how they evolve. Current methods for analyzing orthologous CRMs from multiple species rely upon sequence alignments produced by off-the-shelf alignment algorithms, which do not exploit the presence of binding sites in the sequences. We present here a unified probabilistic framework, called MORPH, that integrates the alignment task with binding site predictions, allowing more robust CRM analysis in two species. The framework sums over all possible alignments of two sequences, thus accounting for alignment ambiguities in a natural way. We perform extensive tests on orthologous CRMs from two moderately diverged species Drosophila melanogaster and D. mojavensis, to demonstrate the advantages of the new approach. We show that it can overcome certain computational artifacts of traditional alignment tools and provide a different, likely more accurate, picture of cis-regulatory evolution than that obtained from existing methods. The burgeoning field of cis-regulatory evolution, which is amply supported by the availability of many related genomes, is currently thwarted by the lack of accurate alignments of regulatory regions. Our work will fill in this void and enable more reliable analysis of CRM evolution.

Interspecies comparison of regulatory sequences is a major focus in the bioinformatics community today. There is extensive ongoing effort toward measuring the extent and patterns of binding site turnover in cis-regulatory modules. A major roadblock in such an analysis has been the fact that traditional alignment methods are not very accurate for regulatory sequences. This is partly because the alignment is performed independently from the binding site predictions and turnover analysis. This article describes a new computational method to compare and align two orthologous regulatory sequences. It uses a unified probabilistic framework to perform alignment and binding site prediction simultaneously, rather than one after the other. Predictions of binding sites and their evolutionary relationships are obtained after summing over all possible alignments, making them robust to alignment ambiguities. The method can also be used to predict new cis-regulatory modules. The article presents extensive applications of the method on synthetic as well as real data. These include the analysis of over 200 cis-regulatory modules in D. melanogaster and their orthologs in D. mojavensis. This analysis reveals a significantly greater degree of conservation of binding sites between these two species than will be inferred from existing alignment tools.

Computational identification and functional validation of regulatory motifs in cartilage-expressed genes

Chondrocyte gene regulation is important for the generation and maintenance of cartilage tissues. Several regulatory factors have been identified that play a role in chondrogenesis, including the positive transacting factors of the SOX family such as SOX9, SOX5, and SOX6, as well as negative transacting factors such as C/EBP and delta EF1. However, a complete understanding of the intricate regulatory network that governs the tissue-specific expression of cartilage genes is not yet available. We have taken a computational approach to identify cis-regulatory, transcription factor (TF) binding motifs in a set of cartilage characteristic genes to better define the transcriptional regulatory networks that regulate chondrogenesis. Our computational methods have identified several TFs, whose binding profiles are available in the TRANSFAC database, as important to chondrogenesis. In addition, a cartilage-specific SOX-binding profile was constructed and used to identify both known, and novel, functional paired SOX-binding motifs in chondrocyte genes. Using DNA pattern-recognition algorithms, we have also identified cis-regulatory elements for unknown TFs. We have validated our computational predictions through mutational analyses in cell transfection experiments. One novel regulatory motif, N1, found at high frequency in the COL2A1 promoter, was found to bind to chondrocyte nuclear proteins. Mutational analyses suggest that this motif binds a repressive factor that regulates basal levels of the COL2A1 promoter.

A novel ensemble learning method for de novo computational identification of DNA binding sites

Background

Despite the diversity of motif representations and search algorithms, the de novo computational identification of transcription factor binding sites remains constrained by the limited accuracy of existing algorithms and the need for user-specified input parameters that describe the motif being sought.

Results

We present a novel ensemble learning method, SCOPE, that is based on the assumption that transcription factor binding sites belong to one of three broad classes of motifs: non-degenerate, degenerate and gapped motifs. SCOPE employs a unified scoring metric to combine the results from three motif finding algorithms each aimed at the discovery of one of these classes of motifs. We found that SCOPE's performance on 78 experimentally characterized regulons from four species was a substantial and statistically significant improvement over that of its component algorithms. SCOPE outperformed a broad range of existing motif discovery algorithms on the same dataset by a statistically significant margin.

Conclusion

SCOPE demonstrates that combining multiple, focused motif discovery algorithms can provide a significant gain in performance. By building on components that efficiently search for motifs without user-defined parameters, SCOPE requires as input only a set of upstream sequences and a species designation, making it a practical choice for non-expert users. A user-friendly web interface, Java source code and executables are available at .

Inference of transcription modification in long-live yeast strains from their expression profiles

Background

Three kinases: Sch9, PKA and TOR, are suggested to be involved in both the replicative and chronological ageing in yeast. They function in pathways whose down-regulation leads to life span extension. Several stress response proteins, including two transcription factors Msn2 and Msn4, mediate the longevity extension phenotype associated with decreased activity of either Sch9, PKA, or TOR. However, the mechanisms of longevity, especially the underlying transcription program have not been fully understood.

Results

We measured the gene expression profiles in wild type yeast and three long-lived mutants: sch9Δ, ras2Δ, and tor1Δ. To elucidate the transcription program that may account for the longevity extension, we identified the transcription factors that are systematically and significantly associated with the expression differentiation in these mutants with respect to wild type by integrating microarray expression data with motif and ChIP-chip data, respectively. Our analysis suggests that three stress response transcription factors, Msn2, Msn4 and Gis1, are activated in all the three mutants. We also identify some other transcription factors such as Fhl1 and Hsf1, which may also be involved in the transcriptional modification in the long-lived mutants.

Conclusion

Combining microarray expression data with other data sources such as motif and ChIP-chip data provides biological insights into the transcription modification that leads to life span extension. In the chronologically long-lived mutant: sch9Δ, ras2Δ, and tor1Δ, several common stress response transcription factors are activated compared with the wild type according to our systematic transcription inference.

PAP: a comprehensive workbench for mammalian transcriptional regulatory sequence analysis

Given the recent explosion of publications that employ microarray technology to monitor genome-wide expression and that correlate these expression changes to biological processes or to disease states, the determination of the transcriptional regulation of these co-expressed genes is the next major step toward deciphering the genetic network governing the pathway or disease under study. Although computational approaches have been proposed for this purpose, there is no integrated and user-friendly software application that allows experimental biologists to tackle this problem in higher eukaryotes. We have previously reported a systematic, statistical model of mammalian transcriptional regulatory sequence analysis. We have now made crucial extensions to this model and have developed a comprehensive, user-friendly web application suite termed the Promoter Analysis Pipeline (PAP). PAP is available at: http://bioinformatics.wustl.edu/webTools/portalModule/PromoterSearch.do

Structure-based prediction of C2H2 zinc-finger binding specificity: sensitivity to docking geometry

Predicting the binding specificity of transcription factors is a critical step in the characterization and computational identification and of cis-regulatory elements in genomic sequences. Here we use protein–DNA structures to predict binding specificity and consider the possibility of predicting position weight matrices (PWM) for an entire protein family based on the structures of just a few family members. A particular focus is the sensitivity of prediction accuracy to the docking geometry of the structure used. We investigate this issue with the goal of determining how similar two docking geometries must be for binding specificity predictions to be accurate. Docking similarity is quantified using our recently described interface alignment score (IAS). Using a molecular-mechanics force field, we predict high-affinity nucleotide sequences that bind to the second zinc-finger (ZF) domain from the Zif268 protein, using different C₂H₂ ZF domains as structural templates. We identify a strong relationship between IAS values and prediction accuracy, and define a range of IAS values for which accurate structure-based predictions of binding specificity is to be expected. The implication of our results for large-scale, structure-based prediction of PWMs is discussed.

Knockdown of mitochondrial heat shock protein 70 promotes progeria-like phenotypes in caenorhabditis elegans

Mitochondrial heat shock protein 70 (mthsp70) functions as a mitochondrial import motor and is essential in mitochondrial biogenesis and energy generation in eukaryotic cells. HSP-6 (hsp70F) is a nematode orthologue of mthsp70. Knockdown of HSP-6 by RNA interference in young adult nematodes caused a reduction in the levels of ATP-2, HSP-60 and CLK-1, leading to abnormal mitochondrial morphology and lower ATP levels. As a result, RNA interference-treated worms had lower motility, defects in oogenesis, earlier accumulation of autofluorescent material, and a shorter life span. These are the major phenotypes observed during the aging of worms, suggesting that the reduction of HSP-6 causes early aging or progeria-like phenotypes. The amount of HSP-6 became dramatically reduced at the expected mean life span in not only wild-type but also in long and short life span mutant worms (wild-type, daf-2, and daf-16). Mitochondrial HSP-60 and ATP-2 were also reduced following the reduction of HSP-6 during aging. These results suggest that the reduction of HSP-6 causes defects in mitochondrial function at the final stage of aging, leading to mortality.

Mapping determinants of gene expression plasticity by genetical genomics in C. elegans

Recent genetical genomics studies have provided intimate views on gene regulatory networks. Gene expression variations between genetically different individuals have been mapped to the causal regulatory regions, termed expression quantitative trait loci. Whether the environment-induced plastic response of gene expression also shows heritable difference has not yet been studied. Here we show that differential expression induced by temperatures of 16 °C and 24 °C has a strong genetic component in Caenorhabditis elegans recombinant inbred strains derived from a cross between strains CB4856 (Hawaii) and N2 (Bristol). No less than 59% of 308 trans-acting genes showed a significant eQTL-by-environment interaction, here termed plasticity quantitative trait loci. In contrast, only 8% of an estimated 188 cis-acting genes showed such interaction. This indicates that heritable differences in plastic responses of gene expression are largely regulated in trans. This regulation is spread over many different regulators. However, for one group of trans-genes we found prominent evidence for a common master regulator: a transband of 66 coregulated genes appeared at 24 °C. Our results suggest widespread genetic variation of differential expression responses to environmental impacts and demonstrate the potential of genetical genomics for mapping the molecular determinants of phenotypic plasticity.

It is widely documented that environmental changes will induce differential expression of genes, yet it is unknown how these patterns of environment-induced expression plasticity are inherited and how they differ between genetically divergent individuals of a biological species. In this paper the authors used recombinant inbred lines of the nematode worm C. elegans that were derived from parental lines originally collected in Bristol (United Kingdom) and Hawaii, and measured genome-wide gene expression at two different temperatures. Using statistical analysis tools developed for quantitative trait locus mapping, they found genes with genetically determined differences in their plastic response to temperature changes. A majority of them were found to be regulated by genes at a different genome position (regulated in trans). A striking observation was a group of 66 genes that share a common potential regulator and may be related to differences in fertility plasticity. These results show that differential responses of different genotypes to environmental changes are widespread. Because all species are subjected to environmental change, both at individual and evolutionary time scales, the authors' work calls for studying the heritable component of plasticity of gene regulation in other organisms to enhance understanding of the environmental forces that drive evolutionary adaptation.

Detection of broadly expressed neuronal genes in C. elegans

The genes that are expressed in most or all types of neurons define generic neuronal features and provide a window into the developmental origin and function of the nervous system. Few such genes (sometimes referred to as pan-neuronal or broadly expressed neuronal genes) have been defined to date and the mechanisms controlling their regulation are not well understood. As a first step in investigating their regulation, we used a computational approach to detect sequences overrepresented in their promoter elements. We identified a ten-nucleotide cis-regulatory motif shared by many broadly expressed neuronal genes and demonstrated that it is involved in control of neuronal expression. Our results further suggest that global and cell-type-specific controls likely act in concert to establish pan-neuronal gene expression. Using the newly discovered motif and genome-level gene expression data, we identified a set of 234 candidate broadly expressed genes. The known involvement of many of these genes in neurogenesis and physiology of the nervous system supports the utility of this set for future targeted analyses.

Stubb: a program for discovery and analysis of cis-regulatory modules

Given the DNA-binding specificities (motifs) of one or more transcription factors, an important bioinformatics problem is to discover significant clusters of binding sites for the transcription factors(s). Such clusters often correspond to cis-regulatory modules mediating regulation of an adjacent gene. In earlier work, we developed the Stubb program that uses a probabilistic model and a maximum likelihood approach to efficiently detect cis-regulatory modules over genomic scales. It may optionally exploit a second related genome to improve module prediction accuracy. We describe here the use of a web-based interface for the Stubb program. The interface is equipped with a special post-processing step for in-depth analysis of specific modules, in order to reveal individual binding sites predicted in the module. The web server may be accessed at the URL .

Heat-shock transcription factor (HSF)-1 pathway required for Caenorhabditis elegans immunity

Innate immunity comprises physical barriers, pattern-recognition receptors, antimicrobial substances, phagocytosis, and fever. Here we report that increased temperature results in the activation of a conserved pathway involving the heat-shock (HS) transcription factor (HSF)-1 that enhances immunity in the invertebrate Caenorhabditis elegans. The HSF-1 defense response is independent of the p38 MAPK/PMK-1 pathway and requires a system of chaperones including small and 90-kDa inducible HS proteins. In addition, HSF-1 is needed for the effects of the DAF-2 insulin-like pathway in defense to pathogens, indicating that interacting pathways control stress response, aging, and immunity. The results also show that HSF-1 is required for C. elegans immunity against Pseudomonas aeruginosa, Salmonella enterica, Yersinia pestis, and Enterococcus faecalis, indicating that HSF-1 is part of a multipathogen defense pathway. Considering that several coinducers of HSF-1 are currently in clinical trials, this work opens the possibility that activation of HSF-1 could be used to boost immunity to treat infectious diseases and immunodeficiencies.

Computational identification of transcriptional regulatory elements in DNA sequence

Identification and annotation of all the functional elements in the genome, including genes and the regulatory sequences, is a fundamental challenge in genomics and computational biology. Since regulatory elements are frequently short and variable, their identification and discovery using computational algorithms is difficult. However, significant advances have been made in the computational methods for modeling and detection of DNA regulatory elements. The availability of complete genome sequence from multiple organisms, as well as mRNA profiling and high-throughput experimental methods for mapping protein-binding sites in DNA, have contributed to the development of methods that utilize these auxiliary data to inform the detection of transcriptional regulatory elements. Progress is also being made in the identification of cis-regulatory modules and higher order structures of the regulatory sequences, which is essential to the understanding of transcription regulation in the metazoan genomes. This article reviews the computational approaches for modeling and identification of genomic regulatory elements, with an emphasis on the recent developments, and current challenges.

Expression-guided in silico evaluation of candidate cis regulatory codes for Drosophila muscle founder cells

While combinatorial models of transcriptional regulation can be inferred for metazoan systems from a priori biological knowledge, validation requires extensive and time-consuming experimental work. Thus, there is a need for computational methods that can evaluate hypothesized cis regulatory codes before the difficult task of experimental verification is undertaken. We have developed a novel computational framework (termed “CodeFinder”) that integrates transcription factor binding site and gene expression information to evaluate whether a hypothesized transcriptional regulatory model (TRM; i.e., a set of co-regulating transcription factors) is likely to target a given set of co-expressed genes. Our basic approach is to simultaneously predict cis regulatory modules (CRMs) associated with a given gene set and quantify the enrichment for combinatorial subsets of transcription factor binding site motifs comprising the hypothesized TRM within these predicted CRMs. As a model system, we have examined a TRM experimentally demonstrated to drive the expression of two genes in a sub-population of cells in the developing Drosophila mesoderm, the somatic muscle founder cells. This TRM was previously hypothesized to be a general mode of regulation for genes expressed in this cell population. In contrast, the present analyses suggest that a modified form of this cis regulatory code applies to only a subset of founder cell genes, those whose gene expression responds to specific genetic perturbations in a similar manner to the gene on which the original model was based. We have confirmed this hypothesis by experimentally discovering six (out of 12 tested) new CRMs driving expression in the embryonic mesoderm, four of which drive expression in founder cells.

Although genome sequences and much gene expression data are readily available, the determination of sets of transcription factors regulating particular gene expression patterns remains a problem of fundamental importance. Tissue-specific gene expression in developing animals is regulated through the combinatorial interactions of transcription factors with DNA regulatory elements termed cis regulatory modules (CRMs). Although genetic and biochemical experiments allow the identification of transcription factors and CRMs, those experiments are laborious and time-consuming. Philippakis et al. introduce a new approach (termed “CodeFinder”) for quantifying the enrichment for particular combinations of transcription factor binding site motifs within predicted CRMs associated with a given gene set of interest, identified from gene expression data. The authors' analyses allowed them to discover a specific combination of transcription factor binding site motifs that constitute a core cis regulatory code for expression of a particular subset of genes in muscle founder cells, an embryonic cell population in the developing fruit fly (Drosophila melanogaster) mesoderm, and also led them to the discovery and subsequent experimental validation of novel, tissue-specific CRMs. Importantly, the CodeFinder approach is generally applicable, and thus could be used to support, refute, or refine a known or hypothesized cis regulatory code for any biological system or genome of interest.

Meta-analysis discovery of tissue-specific DNA sequence motifs from mammalian gene expression data

Background

A key step in the regulation of gene expression is the sequence-specific binding of transcription factors (TFs) to their DNA recognition sites. However, elucidating TF binding site (TFBS) motifs in higher eukaryotes has been challenging, even when employing cross-species sequence conservation. We hypothesized that for human and mouse, many orthologous genes expressed in a similarly tissue-specific manner in both human and mouse gene expression data, are likely to be co-regulated by orthologous TFs that bind to DNA sequence motifs present within noncoding sequence conserved between these genomes.

Results

We performed automated motif searching and merging across four different motif finding algorithms, followed by filtering of the resulting motifs for those that contain blocks of information content. Applying this motif finding strategy to conserved noncoding regions surrounding co-expressed tissue-specific human genes allowed us to discover both previously known, and many novel candidate, regulatory DNA motifs in all 18 tissue-specific expression clusters that we examined. For previously known TFBS motifs, we observed that if a TF was expressed in the specified tissue of interest, then in most cases we identified a motif that matched its TRANSFAC motif; conversely, of all those discovered motifs that matched TRANSFAC motifs, most of the corresponding TF transcripts were expressed in the tissue(s) corresponding to the expression cluster for which the motif was found.

Conclusion

Our results indicate that the integration of the results from multiple motif finding tools identifies and ranks highly more known and novel motifs than does the use of just one of these tools. In addition, we believe that our simultaneous enrichment strategies helped to identify likely human cis regulatory elements. A number of the discovered motifs may correspond to novel binding site motifs for as yet uncharacterized tissue-specific TFs. We expect this strategy to be useful for identifying motifs in other metazoan genomes.

Deciphering principles of transcription regulation in eukaryotic genomes

Transcription regulation has been responsible for organismal complexity and diversity in the course of biological evolution and adaptation, and it is determined largely by the context-dependent behavior of cis-regulatory elements (CREs). Therefore, understanding principles underlying CRE behavior in regulating transcription constitutes a fundamental objective of quantitative biology, yet these remain poorly understood. Here we present a deterministic mathematical strategy, the motif expression decomposition (MED) method, for deriving principles of transcription regulation at the single-gene resolution level. MED operates on all genes in a genome without requiring any a priori knowledge of gene cluster membership, or manual tuning of parameters. Applying MED to Saccharomyces cerevisiae transcriptional networks, we identified four functions describing four different ways that CREs can quantitatively affect gene expression levels. These functions, three of which have extrema in different positions in the gene promoter (short-, mid-, and long-range) whereas the other depends on the motif orientation, are validated by expression data. We illustrate how nature could use these principles as an additional dimension to amplify the combinatorial power of a small set of CREs in regulating transcription.

Comparative promoter analysis allows de novo identification of specialized cell junction-associated proteins

Shared transcription factor binding sites that are conserved in distance and orientation help control the expression of gene products that act together in the same biological context. New bioinformatics approaches allow the rapid characterization of shared promoter structures and can be used to find novel interacting molecules. Here, these principles are demonstrated by using molecules linked to the unique functional unit of the glomerular slit diaphragm. An evolutionarily conserved promoter model was generated by comparative genomics in the proximal promoter regions of the slit diaphragm-associated molecule nephrin. Phylogenetic promoter fingerprints of known elements of the slit diaphragm complex identified the nephrin model in the promoter region of zonula occludens-1 (ZO-1). Genome-wide scans using this promoter model effectively predicted a previously unrecognized slit diaphragm molecule, cadherin-5. Nephrin, ZO-1, and cadherin-5 mRNA showed stringent coexpression across a diverse set of human glomerular diseases. Comparative promoter analysis can identify regulatory pathways at work in tissue homeostasis and disease processes.

Genome-wide identification of direct targets of the Drosophila retinal determination protein Eyeless

The discovery of direct downstream targets of transcription factors (TFs) is necessary for understanding the genetic mechanisms underlying complex, highly regulated processes such as development. In this report, we have used a combinatorial strategy to conduct a genome-wide search for novel direct targets of Eyeless (Ey), a key transcription factor controlling early eye development in Drosophila. To overcome the lack of high-quality consensus binding site sequences, phylogenetic shadowing of known Ey binding sites in sine oculis (so) was used to construct a position weight matrix (PWM) of the Ey protein. This PWM was then used for in silico prediction of potential binding sites in the Drosophila melanogaster genome. To reduce the false positive rate, conservation of these potential binding sites was assessed by comparing the genomic sequences from seven Drosophila species. In parallel, microarray analysis of wild-type versus ectopic ey-expressing tissue, followed by microarray-based epistasis experiments in an atonal (ato) mutant background, identified 188 genes induced by ey. Intersection of in silico predicted conserved Ey binding sites with the candidate gene list produced through expression profiling yields a list of 20 putative ey-induced, eye-enriched, ato-independent, direct targets of Ey. The accuracy of this list of genes was confirmed using both in vitro and in vivo methods. Initial analysis reveals three genes, eyes absent, shifted, and Optix, as novel direct targets of Ey. These results suggest that the integrated strategy of computational biology, genomics, and genetics is a powerful approach to identify direct downstream targets for any transcription factor genome-wide.

Thermoregulation in the life cycle of nematodes

An unanswered question in the biology of many parasites is the mechanism by which environmental (or external) and intrinsic signals are integrated to determine the switch from one developmental stage to the next. This is particularly pertinent for nematode parasites, many of which have a free-living stage in the environment prior to infection of the mammalian host, or for parasites such as filarial nematodes, which utilise an insect vector for transmission. The environmental changes experienced by a parasite upon infection of a mammalian host are extremely complex and poorly understood. However, the ability of a parasite to sense its new environment must be intrinsically linked to its developmental programme, as progression of the life cycle is dependent upon the infection event. In this review, the relationship between temperature and development in filarial nematodes and in the free-living species Caenorhabditis elegans is summarised, with a focus on the role of heat shock factor and heat shock protein 90 in the nematode life cycle.

An integrated strategy for analyzing the unique developmental programs of different myoblast subtypes

An important but largely unmet challenge in understanding the mechanisms that govern the formation of specific organs is to decipher the complex and dynamic genetic programs exhibited by the diversity of cell types within the tissue of interest. Here, we use an integrated genetic, genomic, and computational strategy to comprehensively determine the molecular identities of distinct myoblast subpopulations within the Drosophila embryonic mesoderm at the time that cell fates are initially specified. A compendium of gene expression profiles was generated for primary mesodermal cells purified by flow cytometry from appropriately staged wild-type embryos and from 12 genotypes in which myogenesis was selectively and predictably perturbed. A statistical meta-analysis of these pooled datasets--based on expected trends in gene expression and on the relative contribution of each genotype to the detection of known muscle genes--provisionally assigned hundreds of differentially expressed genes to particular myoblast subtypes. Whole embryo in situ hybridizations were then used to validate the majority of these predictions, thereby enabling true-positive detection rates to be estimated for the microarray data. This combined analysis reveals that myoblasts exhibit much greater gene expression heterogeneity and overall complexity than was previously appreciated. Moreover, it implicates the involvement of large numbers of uncharacterized, differentially expressed genes in myogenic specification and subsequent morphogenesis. These findings also underscore a requirement for considerable regulatory specificity for generating diverse myoblast identities. Finally, to illustrate how the developmental functions of newly identified myoblast genes can be efficiently surveyed, a rapid RNA interference assay that can be scored in living embryos was developed and applied to selected genes. This integrated strategy for examining embryonic gene expression and function provides a substantially expanded framework for further studies of this model developmental system.

A systematic model to predict transcriptional regulatory mechanisms based on overrepresentation of transcription factor binding profiles

An important aspect of understanding a biological pathway is to delineate the transcriptional regulatory mechanisms of the genes involved. Two important tasks are often encountered when studying transcription regulation, i.e., (1) the identification of common transcriptional regulators of a set of coexpressed genes; (2) the identification of genes that are regulated by one or several transcription factors. In this study, a systematic and statistical approach was taken to accomplish these tasks by establishing an integrated model considering all of the promoters and characterized transcription factors (TFs) in the genome. A promoter analysis pipeline (PAP) was developed to implement this approach. PAP was tested using coregulated gene clusters collected from the literature. In most test cases, PAP identified the transcription regulators of the input genes accurately. When compared with chromatin immunoprecipitation experiment data, PAP's predictions are consistent with the experimental observations. When PAP was used to analyze one published expression-profiling data set and two novel coregulated gene sets, PAP was able to generate biologically meaningful hypotheses. Therefore, by taking a systematic approach of considering all promoters and characterized TFs in our model, we were able to make more reliable predictions about the regulation of gene expression in mammalian organisms.

Condition-specific coregulation with cis-regulatory motifs and modules in the mouse genome

Deciphering genetic regulatory codes remains a challenge. Here, we present an effective approach to identifying in vivo condition-specific coregulation with cis-regulatory motifs and modules in the mouse genome. A resampling-based algorithm was adopted to cluster our microarray data of a stress response, which generated 35 tight clusters with unique expression patterns containing 811 genes of 5652 genes significantly altered. Database searches identified many known motifs within the 3-kb regulatory regions of 40 genes from 3 clusters and modules with six to nine motifs that were commonly shared by 60-100% of these genes. The upstream regulatory region contained the highest frequency of these common motifs. CisModule program predictions were comparable with the results from database searches and found four potentially novel motifs. This result indicates that these motifs and modules could be responsible for gene coregulation of the stress response in the lacrimal gland.

A role for SIR-2.1 regulation of ER stress response genes in determining C. elegans life span

C. elegans SIR-2.1, a member of the Sir-2 family of NAD(+)-dependent protein deacetylases, has been shown to regulate nematode aging via the insulin/IGF pathway transcription factor daf-16. Treatment of C. elegans with the small molecule resveratrol, however, extends life span in a manner fully dependent upon sir-2.1, but independent of daf-16. Microarray analysis of worms treated with resveratrol demonstrates the transcriptional induction of a family of genes encoding prion-like glutamine/asparagine-rich proteins involved in endoplasmic reticulum (ER) stress response to unfolded proteins. RNA interference of abu-11, a member of this ER stress gene family, abolishes resveratrol-mediated life span extension, and overexpression of abu-11 extends the life span of transgenic animals. Furthermore, SIR-2.1 normally represses transcription of abu-11 and other ER stress gene family members, indicating that resveratrol extends life span by inhibiting sir-2.1-mediated repression of ER stress genes. Our findings demonstrate that abu-11 and other members of its ER stress gene family are positive determinants of C. elegans life span.

Mapping Dmef2-binding regulatory modules by using a ChIP-enriched in silico targets approach

Mapping the regulatory modules to which transcription factors bind in vivo is a key step toward understanding of global gene expression programs. We have developed a chromatin immunoprecipitation (ChIP)-chip strategy for identifying factor-specific regulatory regions acting in vivo. This method, called the ChIP-enriched in silico targets (ChEST) approach, combines immunoprecipitation of cross-linked protein-DNA complexes (X-ChIP) with in silico prediction of targets and generation of computed DNA microarrays. We report the use of ChEST in Drosophila to identify several previously unknown targets of myocyte enhancer factor 2 (MEF2), a key regulator of myogenic differentiation. Our approach was validated by demonstrating that the identified sequences act as enhancers in vivo and are able to drive reporter gene expression specifically in MEF2-positive muscle cells. Presented here, the ChEST strategy was originally designed to identify regulatory modules in Drosophila, but it can be adapted for any sequenced and annotated genome.

Computational identification of transcription factors involved in early cellular response to a stimulus

The response of genes to cell stimuli is often measured by microarrays. However, studying the function of these genes rarely elucidate as to how the stimuli activate or suppress these genes. To understand the mechanisms of cell stimulation, we describe a computational method for analyzing mammalian promoters of early response genes to detect the transcription factors activated by cell stimulation. We first analyzed promoters of the response genes, for transcription factor binding sites conserved between human and mouse. We then applied hypergeometric statistics in conjunction with Bonferroni correction to identify the top transcription factors whose binding sites were significantly over-represented among these promoters. In five data sets with early response genes, a significantly larger than expected number of genes had binding sites in their promoters for transcription factors previously known to be involved in response to the stimulus, while data sets with measurements at longer time points (24 hours) failed to show such over-representation. Because the end points of signal transduction pathways are transcription factors, this methodology is useful for exploring signaling pathways activated by various stimuli through microarray studies.

Identification of elements essential for transcription in Brugia malayi promoters

Little is known concerning promoter structure in the filarial parasites. Recently, transient transfection methods have been developed for the human filarial parasite Brugia malayi. These methods have been employed to localize the promoter for the 70kDa heat shock protein (BmHSP70) to a region extending 394nt upstream from the initiating codon of the BmHSP70 open reading frame. Replacement mutagenesis was used to define the elements necessary for BmHSP70 promoter activity in detail. Four domains, ranging in size from six to 22 nucleotides, were found to be necessary for full promoter activity. The two most distal domains encoded a binding site for the heat shock transcription factor and a putative binding site for the GAGA transcription factor, motifs that are found in many other HSP70 promoters. However, none of the essential domains contained sequences typical of cis elements that are usually found in the core domain of a eukaryotic promoter. The largest essential domain was located at positions -53 to -32, and included the splice leader addition site. These data suggest that the regulatory domains of the BmHSP70 promoter were similar to those found in other eukaryotes, but that the core promoter domain exhibited features that appeared to be distinct from those found in most other well-characterized eukaryotic promoters. An analysis of two additional promoters of B.malayi highly transcribed genes suggests that they also lack features commonly found in most eukaryotic core promoters, suggesting that the unique features of the BmHSP70 core promoter are not confined to this gene.

Heat shock response of Archaeoglobus fulgidus

The heat shock response of the hyperthermophilic archaeon Archaeoglobus fulgidus strain VC-16 was studied using whole-genome microarrays. On the basis of the resulting expression profiles, approximately 350 of the 2,410 open reading frames (ORFs) (ca. 14%) exhibited increased or decreased transcript abundance. These span a range of cell functions, including energy production, amino acid metabolism, and signal transduction, where the majority are uncharacterized. One ORF called AF1298 was identified that contains a putative helix-turn-helix DNA binding motif. The gene product, HSR1, was expressed and purified from Escherichia coli and was used to characterize specific DNA recognition regions upstream of two A. fulgidus genes, AF1298 and AF1971. The results indicate that AF1298 is autoregulated and is part of an operon with two downstream genes that encode a small heat shock protein, Hsp20, and cdc48, an AAA+ ATPase. The DNase I footprints using HSR1 suggest the presence of a cis-binding motif upstream of AF1298 consisting of CTAAC-N5-GTTAG. Since AF1298 is negatively regulated in response to heat shock and encodes a protein only distantly related to the N-terminal DNA binding domain of Phr of Pyrococcus furiosus, these results suggest that HSR1 and Phr may belong to an evolutionarily diverse protein family involved in heat shock regulation in hyperthermophilic and mesophilic Archaea organisms.

The promoters of human cell cycle genes integrate signals from two tumor suppressive pathways during cellular transformation

Deciphering regulatory events that drive malignant transformation represents a major challenge for systems biology. Here, we analyzed genome-wide transcription profiling of an in vitro cancerous transformation process. We focused on a cluster of genes whose expression levels increased as a function of p53 and p16(INK4A) tumor suppressors inactivation. This cluster predominantly consists of cell cycle genes and constitutes a signature of a diversity of cancers. By linking expression profiles of the genes in the cluster with the dynamic behavior of p53 and p16(INK4A), we identified a promoter architecture that integrates signals from the two tumor suppressive channels and that maps their activity onto distinct levels of expression of the cell cycle genes, which, in turn, correspond to different cellular proliferation rates. Taking components of the mitotic spindle as an example, we experimentally verified our predictions that p53-mediated transcriptional repression of several of these novel targets is dependent on the activities of p21, NFY, and E2F. Our study demonstrates how a well-controlled transformation process allows linking between gene expression, promoter architecture, and activity of upstream signaling molecules.

Applications of DNA microarrays in biology

DNA microarrays have enabled biology researchers to conduct large-scale quantitative experiments. This capacity has produced qualitative changes in the breadth of hypotheses that can be explored. In what has become the dominant mode of use, changes in the transcription rate of nearly all the genes in a genome, taking place in a particular tissue or cell type, can be measured in disease states, during development, and in response to intentional experimental perturbations, such as gene disruptions and drug treatments. The response patterns have helped illuminate mechanisms of disease and identify disease subphenotypes, predict disease progression, assign function to previously unannotated genes, group genes into functional pathways, and predict activities of new compounds. Directed at the genome sequence itself, microarrays have been used to identify novel genes, binding sites of transcription factors, changes in DNA copy number, and variations from a baseline sequence, such as in emerging strains of pathogens or complex mutations in disease-causing human genes. They also serve as a general demultiplexing tool to sort spatially the sequence-tagged products of highly parallel reactions performed in solution. A brief review of microarray platform technology options, and of the process steps involved in complete experiment workflows, is included.

Identification of regulatory targets of tissue-specific transcription factors: application to retina-specific gene regulation

Identification of tissue-specific gene regulatory networks can yield insights into the molecular basis of a tissue's development, function and pathology. Here, we present a computational approach designed to identify potential regulatory target genes of photoreceptor cell-specific transcription factors (TFs). The approach is based on the hypothesis that genes related to the retina in terms of expression, disease and/or function are more likely to be the targets of retina-specific TFs than other genes. A list of genes that are preferentially expressed in retina was obtained by integrating expressed sequence tag, SAGE and microarray datasets. The regulatory targets of retina-specific TFs are enriched in this set of retina-related genes. A Bayesian approach was employed to integrate information about binding site location relative to a gene's transcription start site. Our method was applied to three retina-specific TFs, CRX, NRL and NR2E3, and a number of potential targets were predicted. To experimentally assess the validity of the bioinformatic predictions, mobility shift, transient transfection and chromatin immunoprecipitation assays were performed with five predicted CRX targets, and the results were suggestive of CRX regulation in 5/5, 3/5 and 4/5 cases, respectively. Together, these experiments strongly suggest that RP1, GUCY2D, ABCA4 are novel targets of CRX.

Gene regulatory networks for development

The genomic program for development operates primarily by the regulated expression of genes encoding transcription factors and components of cell signaling pathways. This program is executed by cis-regulatory DNAs (e.g., enhancers and silencers) that control gene expression. The regulatory inputs and functional outputs of developmental control genes constitute network-like architectures. In this PNAS Special Feature are assembled papers on developmental gene regulatory networks governing the formation of various tissues and organs in nematodes, flies, sea urchins, frogs, and mammals. Here, we survey salient points of these networks, by using as reference those governing specification of the endomesoderm in sea urchin embryos and dorsal-ventral patterning in the Drosophila embryo.

Modulefinder: a tool for computational discovery of cis regulatory modules

Regulation of gene expression occurs largely through the binding of sequence-specific transcription factors (TFs) to genomic binding sites (BSs). We present a rigorous scoring scheme, implemented as a C program termed "ModuleFinder", that evaluates the likelihood that a given genomic region is a cis regulatory module (CRM) for an input set of TFs according to its degree of: (1) homotypic site clustering; (2) heterotypic site clustering; and (3) evolutionary conservation across multiple genomes. Importantly, ModuleFinder obtains all parameters needed to appropriately weight the relative contributions of these sequence features directly from the input sequences and TFBS motifs, and does not need to first be trained. Using two previously described collections of experimentally verified CRMs in mammals and in fly as validation datasets, we show that ModuleFinder is able to identify CRMs with great sensitivity and specificity.

Genes Induced by Reovirus Infection Have a Distinct Modular Cis-Regulatory Architecture

The availability of complete genomes and global gene expression profiling has greatly facilitated analysis of complex genetic regulatory systems. We describe the use of a bioinformatics strategy for analyzing the cis-regulatory design of genes diferentially regulated during viral infection of a target cell. The large-scale transcriptional activity of human embryonic kidney (HEK293) cells to reovirus (serotype 3 Abney) infection was measured using the Affymetrix HU-95Av2 gene array. Comparing the 2000 base pairs of 5' upstream sequence for the most differentially expressed genes revealed highly preserved sequence regions, which we call "modules". Higher-order patterns of modules, called "super-modules", were significantly over-represented in the 5' upstream regions of transcriptionally responsive genes. These supermodules contain binding sites for multiple transcription factors and tend to define the role of genes in processes associated with reovirus infection. The supermodular design encodes a cis-regulatory logic for transducing upstream signaling for the control of expression of genes involved in similar biological processes. In the case of reovirus infection, these processes recapitulate the integrated response of cells including signal transduction, transcriptional regulation, cell cycle control, and apoptosis. The computational strategies described for analyzing gene expression data to discover cis-regulatory features and associating them with pathological processes represents a novel approach to studying the interaction of a pathogen with its target cells.

Using ascidian embryos to study the evolution of developmental gene regulatory networks

Ascidians are ideally positioned taxonomically at the base of the chordate tree to provide a point of comparison for developmental regulatory mechanisms that operate among protostomes, non-chordate deuterostomes, invertebrate chordates, and vertebrates. In this review, we propose a model for the gene regulatory network that gives rise to the ascidian notochord. The purpose of this model is not to clarify all of the interactions between molecules of this network, but to provide a working schematic of the regulatory architecture that leads to the specification of endoderm and the patterning of mesoderm in ascidian embryos. We describe a series of approaches, both computational and biological, that are currently being used, or are in development, for the study of ascidian embryo gene regulatory networks. It is our belief that the tools now available to ascidian biologists, in combination with a streamlined mode of development and small genome size, will allow for more rapid dissection of developmental gene regulatory networks than in more complex organisms such as vertebrates. It is our hope that the analysis of gene regulatory networks in ascidians can provide a basic template which will allow developmental biologists to superimpose the modifications and novelties that have arisen during deuterostome evolution.

Towards quantitative biology: integration of biological information to elucidate disease pathways and to guide drug discovery

Developing a new drug is a tedious and expensive undertaking. The recently developed high-throughput experimental technologies, summarised by the terms genomics, transcriptomics, proteomics and metabolomics provide for the first time ever the means to comprehensively monitor the molecular level of disease processes. The "-omics" technologies facilitate the systematic characterisation of a drug target's physiology, thereby helping to reduce the typically high attrition rates in discovery projects, and improving the overall efficiency of pharmaceutical research processes. Currently, the bottleneck for taking full advantage of the new experimental technologies are the rapidly growing volumes of automatically produced biological data. A lack of scalable database systems and computational tools for target discovery has been recognised as a major hurdle. In this review, an overview will be given on recent progress in computational biology that has an impact on drug discovery applications. The focus will be on novel in silico methods to reconstruct regulatory networks, signalling cascades, and metabolic pathways, with an emphasis on comparative genomics and microarray-based approaches. Promising methods, such as the mathematical simulation of pathway dynamics are discussed in the context of applications in discovery projects. The review concludes by exemplifying concrete data-driven studies in pharmaceutical research that demonstrate the value of integrated computational systems for drug target identification and validation, screening assay development, as well as drug candidate efficacy and toxicity evaluations.

Energy biogenesis: one key for coordinating two genomes

In metazoan organisms, energy production is the only example of a process that is under dual genetic control: nuclear and mitochondrial. We used a genomic approach to examine how energy genes of both the nuclear and mitochondrial genomes are coordinated, and discovered a novel genetic regulatory circuit in Drosophila melanogaster that is surprisingly simple and parsimonious. This circuit is based on a single DNA regulatory element and can explain both intra- and inter-genomic coordinated expression of genes involved in energy production, including the full complement of mitochondrial and nuclear oxidative phosphorylation genes, and the genes involved in the Krebs cycle.

Computational discovery of DNA motifs associated with cell type-specific gene expression in Ciona

Temporally and spatially co-expressed genes are expected to be regulated by common transcription factors and therefore to share cis-regulatory elements. In the ascidian Ciona intestinalis, the whole-genome sequences and genome-scale gene expression profiles allow the use of computational techniques to investigate cis-elements that control transcription. We collected 5' flanking sequences of 50 tissue-specific genes from genome databases of C. intestinalis and a closely related species Ciona savignyi. We searched for DNA motifs over-represented in upstream regions of a group of co-expressed genes. Several motifs were distributed predominantly in upstream regions of photoreceptor, pan-neuronal, or muscle-specific gene groups. One muscle-specific motif, M2, was distributed preferentially in regions from -200 to -100 bp relative to the translational start sites. Promoters of muscle-specific genes of C. intestinalis were isolated, connected with a green fluorescent protein gene (GFP), and introduced into C. intestinalis embryos. In muscle cells, these promoters specifically drove GFP expression, which mutations of the M2 sites greatly reduced. When M2 sites were located upstream of a basal promoter, the reporter GFP was specifically expressed in muscle cells. These results suggest the validity of our computational prediction of cis-regulatory elements. Thus, bioinformatics can help identify cis-regulatory elements involved in chordate development.