Genome-wide Context Research Articles

Genome Editing, Transcriptional Regulation, and Forward Genetic Screening Using CRISPR-Cas12a Systems in Yarrowia lipolytica.

Class II Type V endonucleases have increasingly been adapted to develop sophisticated and easily accessible synthetic biology tools for genome editing, transcriptional regulation, and functional genomic screening in a wide range of organisms. One such endonuclease, Cas12a, presents itself as an attractive alternative to Cas9-based systems. The ability to mature its own guide RNAs (gRNAs) from a single transcript has been leveraged for easy multiplexing, and its lack of requirement of a tracrRNA element, also allows for short gRNA expression cassettes. To extend these functionalities into the industrially relevant oleaginous yeast Yarrowia lipolytica, we developed a set of CRISPR-Cas12a vectors for easy multiplexed gene knockout, repression, and activation. We further extended the utility of this CRISPR-Cas12a system to functional genomic screening by constructing a genome-wide guide library targeting every gene with an eightfold coverage. Pooled CRISPR screens conducted with this library were used to profile Cas12a guide activities and develop a machine learning algorithm that could accurately predict highly efficient Cas12a gRNA. In this protocols chapter, we first present a method by which protein coding genes may be functionally disrupted via indel formation with CRISPR-Cas12a systems. Further, we describe how Cas12a fused to a transcriptional regulator can be used in conjunction with shortened gRNA to achieve transcriptional repression or activation. Finally, we describe the design, cloning, and validation of a genome-wide library as well as a protocol for the execution of a pooled CRISPR screen, to determine guide activity profiles in a genome-wide context in Y. lipolytica. The tools and strategies discussed here expand the list of available synthetic biology tools for facile genome engineering in this industrially important host.

Tobacco Smoking-Related Mutational Signatures in Classifying Smoking-Associated and Nonsmoking-Associated NSCLC.

Patient-reported smoking history is frequently used as a stratification factor in NSCLC-directed clinical research. Nevertheless, this classification does not fully reflect the mutational processes ina tumor. Next-generation sequencing can identify mutational signatures associated with tobacco smoking, such as single-base signature 4 and indel-based signature3. This provides an opportunity to redefine the classification of smoking- and nonsmoking-associated NSCLC on the basis of individual genomic tumor characteristics and could contribute to reducing the lung cancer stigma. Whole genome sequencing data and clinical records were obtained from three prospective cohorts of metastatic NSCLC (N= 316). Relative contributions and absolute counts of single-base signature 4 and indel-based signature 3 were combined with relative contributions of age-related signatures to divide the cohort into smoking-associated ("smoking high") and nonsmoking-associated ("smoking low") clusters. The smoking high (n= 169) and smoking low (n= 147) clusters differed considerably in tumor mutational burden, signature contribution, and mutational landscape. This signature-based classification overlapped considerably with smoking history. Yet, 26% of patients with an active smoking history were included in the smoking low cluster, of which 52% harbored an EGFR/ALK/RET/ROS1 alteration, and 4% of patients without smoking history were included in the smoking high cluster. These discordant samples had similar genomic contexts to the rest of their respective cluster. A substantial subset of metastatic NSCLC is differently classified into smoking- and nonsmoking-associated tumors on the basis of smoking-related mutational signatures than on the basis of smoking history. This signature-based classification more accurately classifies patients on the basis of genome-wide context and should therefore be considered as a stratification factor in clinical research.

The efficacy of selection may increase or decrease with selfing depending upon the recombination environment.

Much theory has focused on how a population's selfing rate affects the ability of natural selection to remove deleterious mutations from a population. However, most such theory has focused on mutations of a given dominance and fitness effect in isolation. It remains unclear how selfing affects the purging of deleterious mutations in a genome-wide context where mutations with different selection and dominance coefficients co-segregate. Here, we use individual-based forward simulations and analytical models to investigate how mutation, selection and recombination interact with selfing rate to shape genome-wide patterns of mutation accumulation and fitness. In addition to recovering previously described results for how selfing affects the efficacy of selection against mutations of a given dominance class, we find that the interaction of purifying selection against mutations of different dominance classes changes with selfing and recombination rates. In particular, when recombination is low and recessive deleterious mutations are common, outcrossing populations transition from purifying selection to pseudo-overdominance, dramatically reducing the efficacy of selection. At these parameter combinations, the efficacy of selection remains low until populations hit a threshold selfing rate, above which it increases. In contrast, selection is more effective in outcrossing than (partial) selfing populations when recombination rates are moderate to high and recessive deleterious mutations are rare.

Contiguously hydrophobic sequences are functionally significant throughout the human exome

Hydrophobic interactions have long been established as essential for stabilizing struc-tured proteins as well as drivers of aggregation, but the impact of hydrophobicity on thefunctional significance of sequence variants has rarely been considered in a genome-wide context. Here we test the role of hydrophobicity on functional impact across70,000 disease- and non–disease-associated single-nucleotide polymorphisms (SNPs),using enrichment of disease association as an indicator of functionality. We find thatfunctional impact is uncorrelated with hydrophobicity of the SNP itself and only weaklycorrelated with the average local hydrophobicity, but is strongly correlated with boththe size and minimum hydrophobicity of the contiguously hydrophobic sequence (or“blob”) that contains the SNP. Disease association is found to vary by more than sixfoldas a function of contiguous hydrophobicity parameters, suggesting utility as a prior foridentifying causal variation. We further find signatures of differential selective constrainton hydrophobic blobs and that SNPs splitting a long hydrophobic blob or joiningtwo short hydrophobic blobs are particularly likely to be disease associated. Trends arepreserved for both aggregating and nonaggregating proteins, indicating that the role ofcontiguous hydrophobicity extends well beyond aggregation risk.

Calling differentially methylated regions from whole genome bisulphite sequencing with DMRcate.

Whole genome bisulphite sequencing (WGBS) permits the genome-wide study of single molecule methylation patterns. One of the key goals of mammalian cell-type identity studies, in both normal differentiation and disease, is to locate differential methylation patterns across the genome. We discuss the most desirable characteristics for DML (differentially methylated locus) and DMR (differentially methylated region) detection tools in a genome-wide context and choose a set of statistical methods that fully or partially satisfy these considerations to compare for benchmarking. Our data simulation strategy is both biologically informed—employing distribution parameters derived from large-scale consortium datasets—and thorough. We report DML detection ability with respect to coverage, group methylation difference, sample size, variability and covariate size, both marginally and jointly, and exhaustively with respect to parameter combination. We also benchmark these methods on FDR control and computational time. We use this result to backend and introduce an expanded version of DMRcate: an existing DMR detection tool for microarray data that we have extended to now call DMRs from WGBS data. We compare DMRcate to a set of alternative DMR callers using a similarly realistic simulation strategy. We find DMRcate and RADmeth are the best predictors of DMRs, and conclusively find DMRcate the fastest.

More Than Just Letters and Chemistry: Genomics Goes Mechanics

Although ubiquitously thought of as a simple string of letters, DNA exhibits complex physicochemical properties. As a result, DNA can store information beyond the extensively studied explicit genetic message. The mechanical code of DNA has not been studied systematically in a genome-wide context until recent groundbreaking work by Basu et al.

Genome-wide haplotype association study in imaging genetics using whole-brain sulcal openings of 16,304 UK Biobank subjects

Neuroimaging-genetics cohorts gather two types of data: brain imaging and genetic data. They allow the discovery of associations between genetic variants and brain imaging features. They are invaluable resources to study the influence of genetics and environment in the brain features variance observed in normal and pathological populations. This study presents a genome-wide haplotype analysis for 123 brain sulcus opening value (a measure of sulcal width) across the whole brain that include 16,304 subjects from UK Biobank. Using genetic maps, we defined 119,548 blocks of low recombination rate distributed along the 22 autosomal chromosomes and analyzed 1,051,316 haplotypes. To test associations between haplotypes and complex traits, we designed three statistical approaches. Two of them use a model that includes all the haplotypes for a single block, while the last approach considers each haplotype independently. All the statistics produced were assessed as rigorously as possible. Thanks to the rich imaging dataset at hand, we used resampling techniques to assess False Positive Rate for each statistical approach in a genome-wide and brain-wide context. The results on real data show that genome-wide haplotype analyses are more sensitive than single-SNP approach and account for local complex Linkage Disequilibrium (LD) structure, which makes genome-wide haplotype analysis an interesting and statistically sound alternative to the single-SNP counterpart.

Mapping DNA Topoisomerase Binding and Cleavage Genome Wide Using Next-Generation Sequencing Techniques.

Next-generation sequencing (NGS) platforms have been adapted to generate genome-wide maps and sequence context of binding and cleavage of DNA topoisomerases (topos). Continuous refinements of these techniques have resulted in the acquisition of data with unprecedented depth and resolution, which has shed new light on in vivo topo behavior. Topos regulate DNA topology through the formation of reversible single- or double-stranded DNA breaks. Topo activity is critical for DNA metabolism in general, and in particular to support transcription and replication. However, the binding and activity of topos over the genome in vivo was difficult to study until the advent of NGS. Over and above traditional chromatin immunoprecipitation (ChIP)-seq approaches that probe protein binding, the unique formation of covalent protein–DNA linkages associated with DNA cleavage by topos affords the ability to probe cleavage and, by extension, activity over the genome. NGS platforms have facilitated genome-wide studies mapping the behavior of topos in vivo, how the behavior varies among species and how inhibitors affect cleavage. Many NGS approaches achieve nucleotide resolution of topo binding and cleavage sites, imparting an extent of information not previously attainable. We review the development of NGS approaches to probe topo interactions over the genome in vivo and highlight general conclusions and quandaries that have arisen from this rapidly advancing field of topoisomerase research.

Identification of Bone Metastasis-associated Genes of Gastric Cancer by Genome-wide Transcriptional Profiling

Background:Gastric cancer is one of the leading causes of cancer-related mortality worldwide. Genome-wide transcriptional profiling has provided valuable insights into the molecular basis underlying processes involved in gastric cancer initiation and progression. </P><P> Objective: To understand the pathological and biological mechanisms of gastric cancer metastasis in a genome-wide context. </P><P> Method: In this study, we constructed libraries from blood of gastric cancer patients with, and without, bone metastasis. High-throughput sequencing combined with differential expression analysis was used to investigate transcriptional changes.Results:We identified a total of 425 significantly differentially expressed genes. Protein-protein interaction network analysis suggested that most of these genes are involved in DNA replication, DNA damage response, collagen homeostasis and cell adhesion. Furthermore, our data suggested that NFkappaB and DNA damage response pathways were the key regulators of the bone metastasis associated with gastric cancer. Finally, most of these target genes were involved in pathways such as extracellular matrix organization and extracellular structure organization as revealed by gene set enrichment assay.Conclusion:Our study provides a comprehensive analysis of the transcriptional alterations involved in gastric cancer bone metastasis, which provides greater insights into the complexity of regulatory changes during tumorigenesis and offers novel diagnostic as well as therapeutic avenues.

DNA Conformation Regulates Gene Expression: The MYC Promoter and Beyond.

Emerging evidence suggests that DNA topology plays an instructive role in cell fate control through regulation of gene expression. Transcription produces torsional stress, and the resultant supercoiling of the DNA molecule generates an array of secondary structures. In turn, local DNA architecture is harnessed by the cell, acting within sensory feedback mechanisms to mediate transcriptional output. MYC is a potent oncogene, which is upregulated in the majority of cancers; thus numerous studies have focused on detailed understanding of its regulation. Dissection of regulatory regions within the MYC promoter provided the first hint that intimate feedback between DNA topology and associated DNA remodeling proteins is critical for moderating transcription. As evidence of such regulation is also found in the context of many other genes, here we expand on the prototypical example of the MYC promoter, and also explore DNA architecture in a genome-wide context as a global mechanism of transcriptional control.

Direct Interaction of Chivosazole F with Actin Elicits Cell Responses Similar to Latrunculin A but Distinct from Chondramide.

The microbial metabolite Chivosazole F has been described to affect the cytoskeleton and to inhibit actin polymerization in vitro. Applying orthogonal genomic and proteomics approaches, we now show for the first time that Chivosazole F exerts its effect by directly interacting with actin and demonstrate the cellular impact of Chivosazole F in an unbiased, genome-wide context in yeast and in mammalian cells. Furthermore, mutation-based resistance mapping identifies two SNPs located in the putative Chivosazole F binding site of actin. Comparing chemogenomic profiles and responses to the Chivosazole F-resistant SNPs shows a partially conserved mechanism of action for Chivosazole F and Latrunculin A, but clear divergence from Chondramide. In addition, C14orf80 is an evolutionarily highly conserved ORF, lacking any functional annotation. As editing of C14orf80 leads to Chivosazole F hyper-resistance, we propose a function for this gene product in counteracting perturbation of actin filaments.

Abstract P261: Genome-wide Association Study of Susceptibility to Particulate Matter-associated Reduced Heart Rate Variability

Background: Heart rate variability (HRV) is a heritable electrocardiographic measure of cardiac autonnomic control that is consistently and inversely associated with ambient particulate matter (PM) air pollution and risk of both incident cardiovascular disease, and death. However, genetic susceptibility to PM-associated decreases in HRV has not been characterized. Methods: To characterize such susceptibility in a genome-wide context, we conducted cohort-, race/ethnicity-, and sex-stratified longitudinal analyses of ten Women’s Health Initiative clinical trials and Atherosclerosis Risk in Communities Study subpopulations (total n: 27,121; mean age: 64.6 yr; 81% female; 25% black; 7% Hispanic; mean visits/person: 2.5). In each subpopulation, we log-transformed three previously validated and reliable measures of HRV: RR interval duration (RR); root mean square of successive differences in normal-to-normal RR (RMSSD); and standard deviation of normal-to-normal RR (SDNN). We also estimated mean concentrations of PM < 10 μm on the day of and before HRV measurement. We then used generalized estimating equations (GEE) methods adapted for low prevalence exposure to leverage the repeated measures of HRV and PM10. The GEE models estimated interactions between approximately 2.5 million single nucleotide polymorphisms (SNPs) and PM10 concentrations dichotomized at subpopulation-specific 90th percentiles, while adjusting for age, geographic region or center, season, calendar year, and ancestry. We combined the SNP x PM10 interaction estimates in a Bayesian meta-analysis accounting for ancestral heterogeneity to identify trans-ethnic interactions exceeding genome-wide thresholds: log10 Bayes Factor (BF) > 6 and posterior probability of heterogeneity (PHet) < 0.5. Results: Preliminary analyses of RMSSD provided suggestive evidence of a trans-ethnically important interaction at five SNPs on one locus. The lead SNP (rs17809071; T allele frequency range: 3-16%) is located on chromosome 4, 120 kilobases downstream from SPRY1 (log10BF = 5.31; PHet = 0.14). SPRY1 encodes sprouty receptor tyrosine kinase signaling antagonist 1 which is expressed in cardiac fibroblasts, antagonizes cytokine-induced epicardial fibrosis, and inhibits adipogenesis. Conclusions: Findings from this genome-wide association study of SNP x PM10 interactions suggest that genetic factors may affect susceptibility to PM10-associated decreases in HRV among racially/ethnically diverse populations of men and women protected by the U.S. Environmental Protection Agency under the Clean Air Act.

Telomere binding protein TRB1 is associated with promoters of translation machinery genes in vivo.

Recently we characterised TRB1, a protein from a single-myb-histone family, as a structural and functional component of telomeres in Arabidopsis thaliana. TRB proteins, besides their ability to bind specifically to telomeric DNA using their N-terminally positioned myb-like domain of the same type as in human shelterin proteins TRF1 or TRF2, also possess a histone-like domain which is involved in protein-protein interactions e.g., with POT1b. Here we set out to investigate the genome-wide localization pattern of TRB1 to reveal its preferential sites of binding to chromatin in vivo and its potential functional roles in the genome-wide context. Our results demonstrate that TRB1 is preferentially associated with promoter regions of genes involved in ribosome biogenesis, in addition to its roles at telomeres. This preference coincides with the frequent occurrence of telobox motifs in the upstream regions of genes in this category, but it is not restricted to the presence of a telobox. We conclude that TRB1 shows a specific genome-wide distribution pattern which suggests its role in regulation of genes involved in biogenesis of the translational machinery, in addition to its preferential telomeric localization.

Tip60 complex binds to active Pol II promoters and a subset of enhancers and co-regulates the c-Myc network in mouse embryonic stem cells.

BackgroundTip60 (KAT5) is the histone acetyltransferase (HAT) of the mammalian Tip60/NuA4 complex. While Tip60 is important for early mouse development and mouse embryonic stem cell (mESC) pluripotency, the function of Tip60 as reflected in a genome-wide context is not yet well understood.ResultsGel filtration of nuclear mESCs extracts indicate incorporation of Tip60 into large molecular complexes and exclude the existence of large quantities of “free” Tip60 within the nuclei of ESCs. Thus, monitoring of Tip60 binding to the genome should reflect the behaviour of Tip60-containing complexes. The genome-wide mapping of Tip60 binding in mESCs by chromatin immunoprecipitation (ChIP) coupled with high-throughput sequencing (ChIP-seq) shows that the Tip60 complex is present at promoter regions of predominantly active genes that are bound by RNA polymerase II (Pol II) and contain the H3K4me3 histone mark. The coactivator HAT complexes, Tip60- and Mof (KAT8)-containing (NSL and MSL), show a global overlap at promoters, whereas distinct binding profiles at enhancers suggest different regulatory functions of each essential HAT complex. Interestingly, Tip60 enrichment peaks at about 200 bp downstream of the transcription start sites suggesting a function for the Tip60 complexes in addition to histone acetylation. The comparison of genome-wide binding profiles of Tip60 and c-Myc, a somatic cell reprogramming factor that binds predominantly to active genes in mESCs, demonstrate that Tip60 and c-Myc co-bind at 50–60 % of their binding sites. We also show that the Tip60 complex binds to a subset of bivalent developmental genes and defines a set of mESC-specific enhancer as well as super-enhancer regions.ConclusionsOur study suggests that the Tip60 complex functions as a global transcriptional co-activator at most active Pol II promoters, co-regulates the ESC-specific c-Myc network, important for ESC self-renewal and cell metabolism and acts at a subset of active distal regulatory elements, or super enhancers, in mESCs.Electronic supplementary materialThe online version of this article (doi:10.1186/s13072-015-0039-z) contains supplementary material, which is available to authorized users.

In silico identification and expression analysis of MscS like gene family in rice

Mechanosensitive channels are membrane proteins that open and shut in response to mechanical forces produced by osmotic pressure, sound, touch and gravity. These channels are involved in multiple physiological functions including hypoosmotic pressure, pain, hearing, blood pressure and cell volume regulation. In plants, these channels play a major role in proprioception, gravity sensing and maintenance of plastid shape and size. In the present study, we identified the mechanosensitive channel of small conductance like (MscS) homologue gene family in rice and analyzed their structure, phylogenetic relationship, localization and expression pattern. Five MscS like genes of rice (OsMSL) were found to be distributed on four chromosomes and clustered into two major groups. Subcellular localization predictions of the OsMSL family revealed their localization to plasma membrane, plastid envelope and mitochondria. The predicted gene structure, bonafide conserved signature motif, domain and the presence of transmembrane regions in each OsMSL strongly supported their identity as members of MscS-like gene family. Furthermore, in silico expression analysis of OsMSL genes revealed differential regulation patterns in tissue specific and abiotic stress libraries. These findings indicate that the in silico approach used here successfully identified in a genome-wide context MscS like gene family in rice, and further suggest the functional importance of MscS-like genes in rice.

Multiple lineages of ancient CR1 retroposons shaped the early genome evolution of amniotes.

Chicken repeat 1 (CR1) retroposons are long interspersed elements (LINEs) that are ubiquitous within amniote genomes and constitute the most abundant family of transposed elements in birds, crocodilians, turtles, and snakes. They are also present in mammalian genomes, where they reside as numerous relics of ancient retroposition events. Yet, despite their relevance for understanding amniote genome evolution, the diversity and evolution of CR1 elements has never been studied on an amniote-wide level. We reconstruct the temporal and quantitative activity of CR1 subfamilies via presence/absence analyses across crocodilian phylogeny and comparative analyses of 12 crocodilian genomes, revealing relative genomic stasis of retroposition during genome evolution of extant Crocodylia. Our large-scale phylogenetic analysis of amniote CR1 subfamilies suggests the presence of at least seven ancient CR1 lineages in the amniote ancestor; and amniote-wide analyses of CR1 successions and quantities reveal differential retention (presence of ancient relics or recent activity) of these CR1 lineages across amniote genome evolution. Interestingly, birds and lepidosaurs retained the fewest ancient CR1 lineages among amniotes and also exhibit smaller genome sizes. Our study is the first to analyze CR1 evolution in a genome-wide and amniote-wide context and the data strongly suggest that the ancestral amniote genome contained myriad CR1 elements from multiple ancient lineages, and remnants of these are still detectable in the relatively stable genomes of crocodilians and turtles. Early mammalian genome evolution was thus characterized by a drastic shift from CR1 prevalence to dominance and hyperactivity of L2 LINEs in monotremes and L1 LINEs in therians.

Reconstructing complex regions of genomes using long-read sequencing technology

Obtaining high-quality sequence continuity of complex regions of recent segmental duplication remains one of the major challenges of finishing genome assemblies. In the human and mouse genomes, this was achieved by targeting large-insert clones using costly and laborious capillary-based sequencing approaches. Sanger shotgun sequencing of clone inserts, however, has now been largely abandoned, leaving most of these regions unresolved in newer genome assemblies generated primarily by next-generation sequencing hybrid approaches. Here we show that it is possible to resolve regions that are complex in a genome-wide context but simple in isolation for a fraction of the time and cost of traditional methods using long-read single molecule, real-time (SMRT) sequencing and assembly technology from Pacific Biosciences (PacBio). We sequenced and assembled BAC clones corresponding to a 1.3-Mbp complex region of chromosome 17q21.31, demonstrating 99.994% identity to Sanger assemblies of the same clones. We targeted 44 differences using Illumina sequencing and find that PacBio and Sanger assemblies share a comparable number of validated variants, albeit with different sequence context biases. Finally, we targeted a poorly assembled 766-kbp duplicated region of the chimpanzee genome and resolved the structure and organization for a fraction of the cost and time of traditional finishing approaches. Our data suggest a straightforward path for upgrading genomes to a higher quality finished state.

Advances in development of gene-gene interaction analy-sis methods based on SNP data: a review

The SNP-based association analysis has become one of the most important approaches to interpret the underlying molecular mechanisms for human complex diseases. Nevertheless, the widely-used singe-locus analysis is only capable of capturing a small portion of susceptible SNPs with prominent marginal effects, leaving the important genetic component, epistasis or joint effects, to be undetectable. Identifying the complex interplays among multiple genes in the genome-wide context is an essential task for systematically unraveling the molecular mechanisms for complex diseases. Many approaches have been used to detect genome-wide gene-gene interactions and provided new insights into the genetic basis of complex diseases. This paper reviewed recent advances of the methods for detecting gene-gene interaction, categorized into three types, model-based and model-free statistical methods, and data mining methods, based on their characteristics in theory and numerical algorithm. In particular, the basic principle, numerical implementation and cautions for application for each method were elucidated. In addition, this paper briefly discussed the limitations and challenges associated with detecting genome-wide epistasis, in order to provide some methodological consultancies for scientists in the related fields.

Genomewide interaction and enrichment analysis on antidepressant response

Genomewide association studies (GWASs) on antidepressant efficacy have yielded modest results. A possible reason is that response is influenced by other factors, which possibly interact with genetic variation. We used a GWAS model to predict antidepressant response, by including predictors previously known to affect response, such as quality of life (QoL). We also evaluated the association between genes, previously implicated in gene-environment (G × E) interactions, and response using an enrichment analysis. We examined a sample of 1426 depressed patients from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial: 774 responders, 652 non-responders and 418,865 single nucleotide polymorphisms (SNPs) were analysed. First, in a GWAS model, we investigated whether genetic variations interact with patients' levels of QoL to predict response, after controlling for demographic characteristics, severity and population stratification. Second, we conducted an enrichment analysis exploring whether candidate genes that have emerged from prior G × E interaction studies on depression are associated with treatment response. The GWAS model, with QoL as a moderator, yielded one SNP (rs520210) associated with response in the NEDD4L gene (p = 3.64 × 10⁻⁸). In the Caucasian sample only, we observed a drop in significance for this SNP. The enrichment analysis showed that SNPs within serotonergic genes contained more significant markers that predicted response, compared with a random set of genes in the genome. Our findings point to possible target genes, which are proposed for further independent replication. Our enrichment analysis provides further support, in a genomewide context, of the role of serotonergic genes in influencing antidepressant response.

D-Light on promoters: a client-server system for the analysis and visualization of cis-regulatory elements

BackgroundThe binding of transcription factors to DNA plays an essential role in the regulation of gene expression. Numerous experiments elucidated binding sequences which subsequently have been used to derive statistical models for predicting potential transcription factor binding sites (TFBS). The rapidly increasing number of genome sequence data requires sophisticated computational approaches to manage and query experimental and predicted TFBS data in the context of other epigenetic factors and across different organisms.ResultsWe have developed D-Light, a novel client-server software package to store and query large amounts of TFBS data for any number of genomes. Users can add small-scale data to the server database and query them in a large scale, genome-wide promoter context. The client is implemented in Java and provides simple graphical user interfaces and data visualization. Here we also performed a statistical analysis showing what a user can expect for certain parameter settings and we illustrate the usage of D-Light with the help of a microarray data set.ConclusionsD-Light is an easy to use software tool to integrate, store and query annotation data for promoters. A public D-Light server, the client and server software for local installation and the source code under GNU GPL license are available at http://biwww.che.sbg.ac.at/dlight.