Computer modeling of promoter organization as a tool to study transcriptional coregulation

In silico promoter analysis and functional validation identify CmZFH, the co-regulator of hypoxia-responsive genes CmScylla and CmLPCAT

Oxygen (O₂) plays an essential role in aerobic organisms including terrestrial insects. Under hypoxic stress, the cowpea bruchid (Callosobruchus maculatus) ceases feeding and growth. However, larvae, particularly 4th instar larvae exhibit very high tolerance to hypoxia and can recover normal growth once brought to normoxia. To better understand the molecular mechanism that enables insects to cope with low O₂ stress, we performed RNA-seq to distinguish hypoxia-responsive genes in midguts and subsequently identified potential common cis-elements in promoters of hypoxia-induced and -repressed genes, respectively. Selected elements were subjected to gel-shift and transient transfection assays to confirm their cis-regulatory function. Of these putative common cis-elements, AREB6 appeared to regulate the expression of CmLPCAT and CmScylla, two hypoxia-induced genes. CmZFH, the putative AREB6-binding protein, was hypoxia-inducible. Transient expression of CmZFH in Drosophila S2 cells activated CmLPCAT and CmScylla, and their induction was likely through interaction of CmZFH with AREB6. Binding to AREB6 was further confirmed by bacterially expressed CmZFH recombinant protein. Deletion analyses indicated that the N-terminal zinc-finger cluster of CmZFH was the key AREB6-binding domain. Through in silico and experimental exploration, we discovered novel transcriptional regulatory components associated with gene expression dynamics under hypoxia that facilitated insect survival.

Co-regulation analysis of co-expressed modules under cold and pathogen stress conditions in tomato

A primary mechanism for controlling the development of multicellular organisms is transcriptional regulation, which carried out by transcription factors (TFs) that recognize and bind to their binding sites on promoter region. The distance from translation start site, order, orientation, and spacing between cis elements are key factors in the concentration of active nuclear TFs and transcriptional regulation of target genes. In this study, overrepresented motifs in cold and pathogenesis responsive genes were scanned via Gibbs sampling method, this method is based on detection of overrepresented motifs by means of a stochastic optimization strategy that searches for all possible sets of short DNA segments. Then, identified motifs were checked by TRANSFAC, PLACE and Soft Berry databases in order to identify putative TFs which, interact to the motifs. Several cis/trans regulatory elements were found using these databases. Moreover, cross-talk between cold and pathogenesis responsive genes were confirmed. Statistical analysis was used to determine distribution of identified motifs on promoter region. In addition, co-regulation analysis results, illustrated genes in pathogenesis responsive module are divided into two main groups. Also, promoter region was crunched to six subareas in order to draw the pattern of distribution of motifs in promoter subareas. The result showed the majority of motifs are concentrated on 700 nucleotides upstream of the translational start site (ATG). In contrast, this result isn't true in another group. In other words, there was no difference between total and compartmentalized regions in cold responsive genes.

The RNA-binding protein HuR inhibits expression of CCL5 and limits recruitment of macrophages into tumors

The RNA-binding protein HuR promotes tumor growth by affecting proliferation, metastasis, apoptosis, and angiogenesis. Although immune cells, especially tumor-associated macrophages, are critical components of the tumor stroma, the influence of HuR in tumors on the recruitment of immune cells remains poorly understood. In the present study, we, therefore, aimed to elucidate the impact of tumor cell HuR on the interaction between tumor cells and macrophages. To this end, we stably depleted HuR in human MCF-7 breast cancer cells. We found that HuR-deficient cells not only showed reduced proliferation, they further expressed elevated levels of the chemokine CCL5. HuR-dependent repression of CCL5 was neither caused by altered CCL5 mRNA stability, nor by changes in CCL5 translation. Instead, loss of HuR augmented transcription of CCL5, which was mediated via an interferon-stimulated response element in the CCL5 promoter. Furthermore, HuR depletion enhanced macrophage recruitment into MCF-7 tumor spheroids, an effect which was completely lost upon neutralization of CCL5. HuR expression further negatively correlated with CCL5 expression and macrophage appearance in a cohort of breast tumors. Thus, while HuR is well-characterized to support various pro-tumorigenic features in tumor cells, we provide evidence that it limits the recruitment of macrophages into tumors by repressing CCL5. As macrophage infiltration is associated with poor prognosis, our findings underline the highly cell-type and context specific role of HuR in tumorigenesis.

A vector platform for the rapid and efficient engineering of stable complex transgenes

We describe the generation of a set of plasmid vector tools that allow the rapid generation of complex-interacting stable transgenes in immortalized and primary cells. Of particular importance is inclusion of a mechanism to monitor the activation status of regulatory pathways via a reporter cassette (using Gaussia Luciferase), with control of additional transgene expression through doxycycline de-repression. The resulting vectors can be used to assess regulatory pathway activation and are well suited for regulatory pathway crosstalk studies. The system incorporates MultiSite-Gateway cloning for the rapid generation of vectors allowing flexible choice of promoters and transgenes, and Sleeping Beauty transposase technology for efficient incorporation of multiple transgenes in into host cell DNA. The vectors and a library of compatible Gateway Entry clones are available from the non-profit plasmid repository Addgene.

The lymphotoxin β receptor is a potential therapeutic target in renal inflammation

Accumulation of inflammatory cells in different renal compartments is a hallmark of progressive kidney diseases including glomerulonephritis (GN). Lymphotoxin β receptor (LTβR) signaling is crucial for the formation of lymphoid tissue, and inhibition of LTβR signaling has ameliorated several non-renal inflammatory models. Therefore, we tested whether LTβR signaling could also have a role in renal injury. Renal biopsies from patients with GN were found to express both LTα and LTβ ligands, as well as LTβR. The LTβR protein and mRNA were localized to tubular epithelial cells, parietal epithelial cells, crescents, and cells of the glomerular tuft, whereas LTβ was found on lymphocytes and tubular epithelial cells. Human tubular epithelial cells, mesangial cells, and mouse parietal epithelial cells expressed both LTα and LTβ mRNA upon stimulation with TNF in vitro. Several chemokine mRNAs and proteins were expressed in response to LTβR signaling. Importantly, in a murine lupus model, LTβR blockade improved renal function without the reduction of serum autoantibody titers or glomerular immune complex deposition. Thus, a preclinical mouse model and human studies strongly suggest that LTβR signaling is involved in renal injury and may be a suitable therapeutic target in renal diseases.

Identification and expression analyses of MYB and WRKY transcription factor genes in Papaver somniferum L

Papaver somniferum L. is an herbaceous, annual and diploid plant that is important from pharmacological and strategic point of view. The cDNA clones of two putative MYB and WRKY genes were isolated (GeneBank accession numbers KP411870 and KP203854, respectively) from this plant, via the nested-PCR method, and characterized. The MYB transcription factor (TF) comprises 342 amino acids, and exhibits the structural features of the R2R3MYB protein family. The WRKY TF, a 326 amino acid-long polypeptide, falls structurally into the group II of WRKY protein family. Quantitative real-time PCR (qRT-PCR) analyses indicate the presence of these TFs in all organs of P. somniferum L. and Papaver bracteatum L. Highest expression levels of these two TFs were observed in the leaf tissues of P. somniferum L. while in P. bracteatum L. the espression levels were highest in the root tissues. Promoter analysis of the 10 co-expressed gene clustered involved in noscapine biosynthesis pathway in P. somniferum L. suggested that not only these 10 genes are co-expressed, but also share common regulatory motifs and TFs including MYB and WRKY TFs, and that may explain their common regulation.

Multiple elements controlling the expression of wheat high molecular weight glutenin paralogs

Analysis of gene expression data generated by high-throughput microarray transcript profiling experiments coupled with cis-regulatory elements enrichment study and cluster analysis can be used to define modular gene programs and regulatory networks. Unfortunately, the high molecular weight glutenin subunits of wheat (Triticum aestivum) are more similar than microarray data alone would allow to distinguish between the three homoeologous gene pairs. However, combining complementary DNA (cDNA) expression libraries with microarray data, a co-expressional network was built that highlighted the hidden differences between these highly similar genes. Duplex clusters of cis-regulatory elements were used to focus the co-expressional network of transcription factors to the putative regulatory network of Glu-1 genes. The focused network helped to identify several transcriptional gene programs in the endosperm. Many of these programs demonstrated a conserved temporal pattern across the studied genotypes; however, few others showed variance. Based on this network, transient gene expression assays were performed with mutated promoters to inspect the control of tissue specificity. Results indicated that the interactions of the ABRE│CBF cluster with distal promoter regions may have a dual role in regulation by both recruiting the transcription complex as well as suppressing it in non-endosperm tissue. A putative model of regulation is discussed.

Hyperosmolarity invokes distinct anti-inflammatory mechanisms in pulmonary epithelial cells: evidence from signaling and transcription layers

Hypertonic saline (HTS) has been used intravenously to reduce organ dysfunction following injury and as an inhaled therapy for cystic fibrosis lung disease. The role and mechanism of HTS inhibition was explored in the TNFα and IL-1β stimulation of pulmonary epithelial cells. Hyperosmolar (HOsm) media (400 mOsm) inhibited the production of select cytokines stimulated by TNFα and IL-1β at the level of mRNA translation, synthesis and release. In TNFα stimulated A549 cells, HOsm media inhibited I-κBα phosphorylation, NF-κB translocation into the nucleus and NF-κB nuclear binding. In IL-1β stimulated cells HOsm inhibited I-κBα phosphorylation without affecting NF-κB translocation or nuclear binding. Incubation in HOsm conditions inhibited both TNFα and IL-1β stimulated nuclear localization of interferon response factor 1 (IRF-1). Additional transcription factors such as AP-1, Erk-1/2, JNK and STAT-1 were unaffected by HOsm. HTS and sorbitol supplemented media produced comparable outcomes in all experiments, indicating that the effects of HTS were mediated by osmolarity, not by sodium. While not affecting MAPK modules discernibly in A549 cells, both HOsm conditions inhibit IRF-1 against TNFα or IL-1β, but inhibit p65 NF-kB translocation only against TNFα but not IL-1β. Thus, anti-inflammatory mechanisms of HTS/HOsm appear to disrupt cytokine signals at distinct intracellular steps.

Calcitonin receptor family evolution and fishing for function using in silico promoter analysis

In the present study the calcitonin receptor (CTR) sub-family of family B G-protein coupled receptors (GPCRs) in teleosts is evaluated and put in the context of the families overall evolution from echinodermates to vertebrates. Echinodermates, hemichordates, cephalochordates and tunicates have a single gene that encodes a receptor that bears similarity to the vertebrate calcitonin receptor (CTR) and calcitonin-like receptor (CTR/CLR). In tetrapods one gene encodes the calcitonin receptor (CALCR) and another gene the calcitonin receptor-like receptor (CALCRL). The evolution of CALCR has been under strong conservative pressure and a single copy is also found in fishes and high conservation of gene organisation and synteny exits from teleosts to human. A teleost specific CTR innovation that occurred after their divergence from holostei is the presence of several HBDs in the N-terminus. CALCRL had a different evolutionary trajectory from CALCR and although a single gene copy is present in tetrapods the sarcopterygii fish, the coelacanth, has 1 copy of CALCRL but also a fish specific form CALCRL3. The ray-finned fish, the spotted gar, has 1 copy of CALCRL and 1 of CALCRL3 but the teleost specific whole genome duplication has resulted in a CALCRL1 and CALCRL2 in addition to the fish specific CALCRL3. Strong conservation of CALCRL gene structure exists from human to fish. Promoter analysis in silico reveals that the duplicated CALCRL genes in the teleosts, zebrafish, takifugu, tetraodon and medaka, have divergent promoters and different putative co-regulated gene partners suggesting their function is different.

A novel pairwise comparison method for in silico discovery of statistically significant cis-regulatory elements in eukaryotic promoter regions: application to Arabidopsis

Cis regulatory elements (CREs), located within promoter regions, play a significant role in the blueprint for transcriptional regulation of genes. There is a growing interest to study the combinatorial nature of CREs including presence or absence of CREs, the number of occurrences of each CRE, as well as of their order and location relative to their target genes. Comparative promoter analysis has been shown to be a reliable strategy to test the significance of each component of promoter architecture. However, it remains unclear what level of difference in the number of occurrences of each CRE is of statistical significance in order to explain different expression patterns of two genes. In this study, we present a novel statistical approach for pairwise comparison of promoters of Arabidopsis genes in the context of number of occurrences of each CRE within the promoters. First, using the sample of 1000 Arabidopsis promoters, the results of the goodness of fit test and non-parametric analysis revealed that the number of occurrences of CREs in a promoter sequence is Poisson distributed. As a promoter sequence contained functional and non-functional CREs, we addressed the issue of the statistical distribution of functional CREs by analyzing the ChIP-seq datasets. The results showed that the number of occurrences of functional CREs over the genomic regions was determined as being Poisson distributed. In accordance with the obtained distribution of CREs occurrences, we suggested the Audic and Claverie (AC) test to compare two promoters based on the number of occurrences for the CREs. Superiority of the AC test over Chi-square (2×2) and Fisher's exact tests was also shown, as the AC test was able to detect a higher number of significant CREs. The two case studies on the Arabidopsis genes were performed in order to biologically verify the pairwise test for promoter comparison. Consequently, a number of CREs with significantly different occurrences was identified between the promoters. The results of the pairwise comparative analysis together with the expression data for the studied genes revealed the biological significance of the identified CREs.

Elucidating functional context within microarray data by integrated transcription factor-focused gene-interaction and regulatory network analysis

Microarrays do not yield direct evidence for functional connections between genes. However, transcription factors (TFs) and their binding sites (TFBSs) in promoters are important for inducing and coordinating changes in RNA levels, and thus represent the first layer of functional interaction. Similar to genes, TFs act only in context, which is why a TF/TFBS-based promoter analysis of genes needs to be done in the form of gene(TF)-gene networks, not individual TFs or TFBSs. In addition, integration of the literature and various databases (e.g. GO, MeSH, etc) allows the adding of genes relevant for the functional context of the data even if they were initially missed by the microarray as their RNA levels did not change significantly. Here, we outline a TF-TFBSs network-based strategy to assess the involvement of transcription factors in agonist signaling and demonstrate its utility in deciphering the response of human microvascular endothelial cells (HMEC-1) to leukemia inhibitory factor (LIF). Our strategy identified a central core of eight TFs, of which only STAT3 had previously been definitively linked to LIF in endothelial cells. We also found potential molecular mechanisms of gene regulation in HMEC-1 upon stimulation with LIF that allow for the prediction of changes of genes not used in the analysis. Our approach, which is readily applicable to a wide variety of expression microarray and next generation sequencing RNA-seq results, illustrates the power of a TF-gene networking approach for elucidation of the underlying biology.

ACSM4 polymorphisms are associated with rapid AIDS progression in HIV-infected patients

: Our aim was to explore the association among ACSM4 and PECI polymorphisms and AIDS progression in 454 HIV-infected patients never treated with antiretroviral drugs (146 long-term nonprogressors, 228 moderate progressors, and 80 rapid progressors). For ACSM4 polymorphisms, rs7137120 AA/AG and rs7961991 CC/CT genotypes had higher odds of having a rapid AIDS progression [odds ratio (OR) = 3.21; 95% of confidence interval (95% CI) = 1.26 to 8.16; P = 0.014 and OR = 3.60; 95% CI = 1.38 to 9.36; P = 0.009, respectively]. Additionally, the ACSM4 haplotype integrated for both rs7961991 A and rs7137120 C alleles had higher odds of having a rapid AIDS progression (OR = 2.85; 95% CI = 1.28 to 6.25; P = 0.010). For PECI polymorphisms, no significant associations were found. In conclusion, ACSM4 polymorphisms might play a significant role in AIDS progression.

Approaches to modeling gene regulatory networks: a gentle introduction

This chapter is split into two main sections; first, I will present an introduction to gene networks. Second, I will discuss various approaches to gene network modeling which will include some examples for using different data sources. Computational modeling has been used for many different biological systems and many approaches have been developed addressing the different needs posed by the different application fields. The modeling approaches presented here are not limited to gene regulatory networks and occasionally I will present other examples. The material covered here is an update based on several previous publications by Thomas Schlitt and Alvis Brazma (FEBS Lett 579(8),1859-1866, 2005; Philos Trans R Soc Lond B Biol Sci 361(1467), 483-494, 2006; BMC Bioinformatics 8(suppl 6), S9, 2007) that formed the foundation for a lecture on gene regulatory networks at the In Silico Systems Biology workshop series at the European Bioinformatics Institute in Hinxton.

From the Large Scale Expression Analysis of Lupus Nephritis to Targeted Molecular Medicine

Lupus nephritis (LN) is one of the most severe complications of systemic lupus erythematosus (SLE). Current treatments for LN lack sufficient efficacy as they do not necessarily target the LN responsible pathways and therapeutic responses vary widely in the patient population. LN mouse models have been useful in delineating disease pathogenesis and for testing novel therapies, but they do not entirely represent the events happening in human LN. This review describes how recently developed systems biology technologies can help to integrate current knowledge with large scale experimental data to generate new hypotheses and insight into the regulatory events occurring in LN.

Role of cold shock Y-box protein-1 in inflammation, atherosclerosis and organ transplant rejection

Chemokines (chemoattractant cytokines) are crucial regulators of immune cell extravasation from the bloodstream into inflamed tissue. Dysfunctional regulation and perpetuated chemokine gene expression are linked to progressive chronic inflammatory diseases and, in respect to transplanted organs, may trigger graft rejection. RANTES (regulated upon activation, normal T cell expressed and secreted (also known as CCL5)) is a model chemokine with relevance in numerous inflammatory diseases where the innate immune response predominates. Transcription factor Y-box binding protein-1 (YB-1) serves as a trans-regulator of CCL5 gene transcription in vascular smooth muscle cells and leucocytes. This review provides an update on YB-1 as a mediator of inflammatory processes and focuses on the role of YB-1 in CCL5 expression in diseases with monocytic cell infiltrates, albeit acute or chronic. Paradigms of such diseases encompass atherosclerosis and transplant rejection where cold shock protein YB-1 takes a dominant role in transcriptional regulation.

Comparative promoter analysis in vivo: identification of a dendritic cell-specific promoter module

Dendritic cells (DCs) are important immune cells. This study focused on transcriptional networks active in murine DCs, but DCs are difficult to study using conventional molecular techniques. Therefore, comparative promoter analysis was used to identify evolutionarily conserved features between the murine CD11c and DC-STAMP promoters. A promoter framework consisting of 4 transcription factor binding sites was identified that included signal transducer and activator of transcription, homeodomain transcription factors, and 2 members of the Brn POU domain factors family. This promoter module was functionally verified by in vivo promoter analysis and site-directed mutagenesis. Hematopoietic stem cells were engineered by lentiviral vectors and expression of green fluorescent protein reporter was monitored in primary hematopoietic cell types that develop without further manipulation in irradiated recipient mice. The verified promoter module was then modeled and used in a bioinformatics-based search for other potential coregulated genes in murine DCs. A promoter database search identified 2 additional genes, Ppef2 and Pftk1, which have a similar promoter organization and are preferentially expressed in murine DCs. The results define a regulatory network linked to development of murine DCs.

SP1 regulates the transcription of BMPR1A

BACKGROUND

BMPR1A is a cell surface receptor in the bone morphogenetic protein (BMP) pathway. Mutations in BMPR1A predispose to juvenile polyposis (JP). Sp1 and related proteins are widely expressed regulators of gene transcription, including members of the BMP pathway. We set out to identify important transcription factor binding sites (TFBS) in the recently identified BMPR1A promoter and to assess for the role of Sp1 and associated proteins in its regulation.

MATERIALS AND METHODS

The BMPR1A promoter was cloned into a luciferase reporter vector. Deletion fragments of this promoter insert were then constructed, of varying lengths and opposing directions, and were used to transfect HEK-293 and CRL-1459 cells. In silico analysis was performed to screen for relevant TFBS. Site-directed mutagenesis (SDM) was then employed to individually disrupt these TFBS in the wild-type (WT) vector. SDM constructs were then assessed for activity.

RESULTS

Light activity from the deletion constructs ranged between 3% and 129% of the WT promoter. ModelInspector identified eight potential binding sites for Sp1- and Sp1-associated proteins that mapped to areas of marked loss or gain of activity from the deletion constructs. SDM of these TFBS led to a drop in activity in five mutants, which included 3 Sp1 sites, an ETSF site, and NFκB site.

CONCLUSIONS

By combining in silico analysis and experimental data, Sp1 was found to be a candidate factor that likely plays a role in the transcriptional regulation of BMPR1A. This study potentially provides further insight toward the molecular basis of JP, and suggests that Sp1 plays a role in BMP signaling.

Pathways and promoter networks analysis provides systems topology for systems biology approaches

Systems-level approaches provide help in characterizing the complexity of renal disease. In this review, we illustrate, using a series of recent examples of integrative studies based on pathway analysis and promoter networks, how new techniques allow the analysis of the layout of complex systems and, through this, help answer questions related to renal disease processes. These technologies include the identification of regulatory pathways dysregulated in the context of renal disease, and techniques for studying promoter networks. Both approaches make use of technologies applied to large-scale transcriptomics, transcriptomic profiling by DNA microarrays, or next-generation sequencing.

Next generation sequencing in functional genomics

Genome-wide sequencing has enabled modern biomedical research to relate more and more events in healthy as well as disease-affected cells and tissues to the genomic sequence. Now next generation sequencing (NGS) extends that reach into multiple almost complete genomes of the same species, revealing more and more details about how individual genomes as well as individual aspects of their regulation differ from each other. The inclusion of NGS-based transcriptome sequencing, chromatin-immunoprecipitation (ChIP) of transcription factor binding and epigenetic analyses (usually based on DNA methylation or histone modification ChIP) completes the picture with unprecedented resolution enabling the detection of even subtle differences such as alternative splicing of individual exons. Functional genomics aims at the elucidation of the molecular basis of biological functions and requires analyses that go far beyond the primary analysis of the reads such as mapping to a genome template sequence. The various and complex interactions between the genome, gene products and metabolites define biological function, which necessitates inclusion of results other than sequence tags in quite elaborative approaches. However, the extra efforts pay off in revealing mechanisms as well as providing the foundation for new strategies in systems biology and personalized medicine. This review emphasizes the particular contribution NGS-based technologies make to functional genomics research with a special focus on gene regulation by transcription factor binding sites.

A specific mutation in the distant sonic hedgehog (SHH) cis-regulator (ZRS) causes Werner mesomelic syndrome (WMS) while complete ZRS duplications underlie Haas type polysyndactyly and preaxial polydactyly (PPD) with or without triphalangeal thumb

Werner mesomelic syndrome (WMS) is an autosomal dominant disorder with unknown molecular etiology characterized by hypo- or aplasia of the tibiae in addition to the preaxial polydactyly (PPD) of the hands and feet and/or five-fingered hand with absence of thumbs. We show that point mutations of a specific nucleotide within the sonic hedgehog (SHH) regulatory region (ZRS) cause WMS. In a previously unpublished WMS family, we identified the causative G>A transition at position 404 of the ZRS, and in six affected family members of a second WMS family we found a 404G>C mutation of the ZRS. The 404G>A ZRS mutation is known as the "Cuban mutation" of PPD type II (PPD2). Interestingly, the index patient of that family had tibial hypoplasia as well. These data provide the first evidence that WMS is caused by a specific ZRS mutation, which leads to strong ectopic SHH expression. In contrast, we show that complete duplications of the ZRS region lead to type Haas polysyndactyly or triphalangeal thumb-polysyndactyly syndrome, but do not affect lower limb development. We suggest the term "ZRS-associated syndromes" and a clinical subclassification for the continuum of limb malformations caused by different molecular alterations of the ZRS.

Targeting tumor stroma using engineered mesenchymal stem cells reduces the growth of pancreatic carcinoma

OBJECTIVE

To analyze the efficacy of engineered mesenchymal stem cell based therapy directed towards pancreatic tumor stroma.

SUMMARY BACKGROUND DATA

Mesenchymal stem cells (MSC) are actively recruited to tumor stroma where they enhance tumor growth and metastases. Upregulation of chemotactic cytokine (CCL5) by MSCs within the tumor stroma has been shown to play a central role in this process. Murine MSCs were engineered to express reporter genes or therapeutic genes under control of the CCL5 promoter and adoptively transferred into mice with growing pancreatic tumors. The effect on tumor growth and metastases was then evaluated.

METHODS

MSCs isolated from bone marrow of C57/Bl6 p53 mice were stably transfected with red fluorescent protein (RFP), enhanced green fluorescent protein (eGFP), or herpes simplex virus (HSV) thymidine kinase (Tk) gene driven by the RANTES promoter. MSCs were intravenously applied once per week over 3 weeks to mice carrying an orthotopic, syngeneic pancreatic Panc02 tumor.

RESULTS

eGFP and RFP signals driven by the CCL5 promoter were detected by fluorescence in treated pancreatic tumor samples. The HSV-Tk therapy group treated intraperitoneal with the prodrug ganciclovir 5 to 7 days after stem cell application lead to a 50% reduction of primary pancreatic tumor growth (P < 0.0003, student t test) and reduced liver metastases (0% vs. 60%).

CONCLUSION

The active homing of MSCs into primary pancreatic tumor stroma and activation of the CCL5 promoter was verified using eGFP- and RFP-reporter genes. In the presence of ganciclovir, HSV-Tk transfected MSCs led to a significant reduction of primary pancreatic tumor growth and incidence of metastases.

A guide to the integrated application of on-line data mining tools for the inference of gene functions at the systems level

Genes function in networks to achieve a common biological response. Thus, inferences into the biological role of individual genes can be gained by analyzing their association with other genes with more precisely defined functions. Here, we present a guide, using the well-characterized Arabidopsis thaliana pathogenesis-related protein 2 gene (PR-2) as an example, to document how the sequential use of web-based tools can be applied to integrate information from different databases and associate the function of an individual gene with a network of genes and additionally identify specific biological processes in which they collectively function. The analysis begins by performing a global expression correlation analysis to build a functionally associated gene network. The network is subsequently analyzed for Gene Ontology enrichment, stimuli and mutant-specific transcriptional responses and enriched putative promoter regulatory elements that may be responsible for their correlated relationships. The results for the PR-2 gene are entirely consistent with the published literature documenting the accuracy of this type of analysis. Furthermore, this type of analysis can also be performed on other organisms with the appropriate data available and will greatly assist in understanding individual gene functions in a systems context.

Defining human diabetic nephropathy on the molecular level: integration of transcriptomic profiles with biological knowledge

Diabetic nephropathy (DN) is the most common cause for end stage renal disease (ESRD). Next to environmental factors, genetic predispositions determine the susceptibility for DN and its rate of progression to ESRD. With the availability of genome wide expression profiling we have the opportunity to define relevant pathways activated in the individual diabetic patient, integrating both environmental exposure and genetic background. In this review we summarize current understanding of how to link comprehensive gene expression data sets with biomedical knowledge and present strategies to build a transcriptional network of DN. Information about the individual disease processes of DN might allow the implementation of a personalized molecular medicine approach with mechanism-based patient management. Web based search engines like Nephromine are essential tools to facilitate access to molecular data of genomics, proteomics and metabolomics of DN.

Computational identification of transcription frameworks of early committed spermatogenic cells

It is known that transcription factors (TFs) work in cooperation with each other to govern gene expression and thus single TF studies may not always reflect the underlying biology. Using microarray data obtained from two independent studies of the first wave of spermatogenesis, we tested the hypothesis that co-expressed spermatogenic genes in cells committed to differentiation are regulated by a set of distinct combinations of TF modules. A computational approach was designed to identify over-represented module combinations in the promoter regions of genes associated with transcripts that either increase or decrease in abundance between the first two major spermatogenic cell types: spermatogonia and spermatocytes. We identified five TFs constituting four module combinations that were correlated with expression and repression of similarly regulated genes. These modules were biologically assessed in the context that they represent the key transcriptional mediators in the developmental transition from the spermatogonia to spermatocyte.

In silico promoters: modelling of cis-regulatory context facilitates target predictio

Elucidation of gene regulatory complexity holds much promise towards aiding therapeutic interventions in medical research. It has become progressively more evident that the characterization of highly conserved regulatory modules within promoters may assist in the elucidation of distinct cis-motif and trans-element regulatory interactions, shared in response to stimulus-evoked pathological changes. With special emphasis on the promoter, accurate analyses of cis-motif architecture combined with integrative in silico modelling might serve as a more refined approach for prediction and study of regulatory targets and major regulators governing transcriptional control. In this review, we have highlighted key examples and recent advances implementing in silico promoter models that could serve as essential contributions for future research in molecular medicine.

Linkage of pluripotent stem cell-associated transcripts to regulatory gene networks

Knowledge of the transcriptional circuitry responsible for pluripotentiality and self-renewal in embryonic stem cells is tantamount to understanding early mammalian development and a prerequisite to determining their therapeutic potential. Various techniques have employed genomics to identify transcripts that were abundant in stem cells, in an attempt to define the molecular basis of 'stemness'. In this study, we have extended traditional genomic analyses to identify cis-elements that might be implicated in the control of embryonic stem cell-restricted gene promoters. The strategy relied on the generation of a problem-specific list from serial analysis of gene expression profiles and subsequent promoter analyses to identify frameworks of multiple cis-elements conserved in space and orientation among genes from the problem-specific list. Subsequent experimental data suggest that 2 novel transcription factors, B-Myb and Maz, predicted from these models, are implicated either in the maintenance of the undifferentiated stem cell state or in early steps of differentiation.

Bioinformatics applications for pathway analysis of microarray data

Changes in transcript levels are assessed by microarray analysis on an individual basis, essentially resulting in long lists of genes that were found to have significantly changed transcript levels. However, in biology these changes do not occur as independent events as such lists suggest, but in a highly coordinated and interdependent manner. Understanding the biological meaning of the observed changes requires elucidating such biological interdependencies. The most common way to achieve this is to project the gene lists onto distinct biological processes often represented in the form of gene-ontology (GO) categories or metabolic and regulatory pathways as derived from literature analysis. This review focuses on different approaches and tools employed for this task, starting form GO-ranking methods, covering pathway mappings, finally converging on biological network analysis. A brief outlook of the application of such approaches to the newest microarray-based technologies (Chromatin-ImmunoPrecipitation, ChIP-on-chip) concludes the review.

GSMA: Gene Set Matrix Analysis, An Automated Method for Rapid Hypothesis Testing of Gene Expression Data

Background

Microarray technology has become highly valuable for identifying complex global changes in gene expression patterns. The assignment of functional information to these complex patterns remains a challenging task in effectively interpreting data and correlating results from across experiments, projects and laboratories. Methods which allow the rapid and robust evaluation of multiple functional hypotheses increase the power of individual researchers to data mine gene expression data more efficiently.

Results

We have developed (gene set matrix analysis) GSMA as a useful method for the rapid testing of group-wise up- or down-regulation of gene expression simultaneously for multiple lists of genes (gene sets) against entire distributions of gene expression changes (datasets) for single or multiple experiments. The utility of GSMA lies in its flexibility to rapidly poll gene sets related by known biological function or as designated solely by the end-user against large numbers of datasets simultaneously.

Conclusions

GSMA provides a simple and straightforward method for hypothesis testing in which genes are tested by groups across multiple datasets for patterns of expression enrichment.

Current approaches to gene regulatory network modelling

Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

Genome-wide identification of novel expression signatures reveal distinct patterns and prevalence of binding motifs for p53, nuclear factor-kappaB and other signal transcription factors in head and neck squamous cell carcinoma

Microarray profiling of ten head and neck cancer lines revealed novel p53 and NF-κB transcriptional gene expression signatures which distinguished tumor cell subsets in association with their p53 status.

Background

Differentially expressed gene profiles have previously been observed among pathologically defined cancers by microarray technologies, including head and neck squamous cell carcinomas (HNSCCs). However, the molecular expression signatures and transcriptional regulatory controls that underlie the heterogeneity in HNSCCs are not well defined.

Results

Genome-wide cDNA microarray profiling of ten HNSCC cell lines revealed novel gene expression signatures that distinguished cancer cell subsets associated with p53 status. Three major clusters of over-expressed genes (A to C) were defined through hierarchical clustering, Gene Ontology, and statistical modeling. The promoters of genes in these clusters exhibited different patterns and prevalence of transcription factor binding sites for p53, nuclear factor-κB (NF-κB), activator protein (AP)-1, signal transducer and activator of transcription (STAT)3 and early growth response (EGR)1, as compared with the frequency in vertebrate promoters. Cluster A genes involved in chromatin structure and function exhibited enrichment for p53 and decreased AP-1 binding sites, whereas clusters B and C, containing cytokine and antiapoptotic genes, exhibited a significant increase in prevalence of NF-κB binding sites. An increase in STAT3 and EGR1 binding sites was distributed among the over-expressed clusters. Novel regulatory modules containing p53 or NF-κB concomitant with other transcription factor binding motifs were identified, and experimental data supported the predicted transcriptional regulation and binding activity.

Conclusion

The transcription factors p53, NF-κB, and AP-1 may be important determinants of the heterogeneous pattern of gene expression, whereas STAT3 and EGR1 may broadly enhance gene expression in HNSCCs. Defining these novel gene signatures and regulatory mechanisms will be important for establishing new molecular classifications and subtyping, which in turn will promote development of targeted therapeutics for HNSCC.

Transcriptional activators and repressors for the neuron-specific expression of a metabotropic glutamate receptor

Metabotropic glutamate receptor 1 (mGlu1) has a discrete distribution in the central nervous system restricted to neurons. Its expression undergoes important changes during development and in response to physiological and pathological modifications. Here, we have determined the structure of the mGlu1 gene and demonstrated that mGlu1 transcription takes places at alternative first exons. Moreover, we have identified active promoter regions upstream from the two most expressed first exons by means of luciferase reporter gene assays performed in primary cerebellar granule neurons. Targeted mutations of active elements constituting the core promoter and electrophoretic mobility shift assays demonstrated that the factors thyroid transcription factor-1 and CCAAT/enhancer-binding proteins beta act synergistically to promote mGlu1 transcription. We have also elucidated the molecular bases for the neuron-specific expression of mGlu1 identifying a neural restrictive silencing element and a regulatory factor for X box element, which suppressed mGlu1 expression in nonneuronal cells. These results reveal the molecular bases for cell- and context-specific expression of an important glutamate receptor critically involved in synaptogenesis, neuronal differentiation, synaptic transmission, and plasticity.

Synthetic promoters: genetic control through cis engineering

Technological advances in plant genetics integrated with systems biology and bioinformatics has yielded a myriad of novel biological data and insights into plant metabolism. This unprecedented advance has provided a platform for targeted manipulation of transcriptional activity through synthetic promoter engineering, and holds great promise as a way to further our understanding of regulatory complexity. The challenge and strategy for predictive experimental gene expression is the accurate design and use of molecular 'switches' and modules that will regulate single or multiple plant transgenes in direct response to specific environmental, physiological and chemical cues. In particular, focusing on cis-motif rearrangement, future plant biotechnology applications and the elucidation of cis- and trans-regulatory mechanisms could greatly benefit from using plant synthetic promoters.

Regulatory networks: Linking microarray data to systems biology

Gene regulation and aging are intrinsically linked and these links often reach directly to transcription factors and their actions in gene regulation. However, it is very difficult to follow all the individual directions such factors can affect. Therefore, the opposite approach became more popular recently, i.e. observing the endpoints of all these actions. Microarrays are the preferred technology to monitor large-scale changes in transcripts across whole genomes. The trade-off for being able to survey whole genome transcriptomes is that the results are mere observations, which do not directly reveal the underlying mechanisms that represent the real link to transcription factors and their actions. Fortunately, a combination of knowledge mining (including but not restricted to literature mining) with genomics analyses can be harnessed to elucidate at least some of the regulatory networks orchestrating the transcriptional changes observed by microarray experiments. Thus, a considerable part of the functional system structure of cells and organisms can be revealed, which is a pivotal prerequisite for any meaningful systems biology approach towards aging related phenotypes.

KBERG: KnowledgeBase for Estrogen Responsive Genes

Estrogen has a profound impact on human physiology affecting transcription of numerous genes. To decipher functional characteristics of estrogen responsive genes, we developed KnowledgeBase for Estrogen Responsive Genes (KBERG). Genes in KBERG were derived from Estrogen Responsive Gene Database (ERGDB) and were analyzed from multiple aspects. We explored the possible transcription regulation mechanism by capturing highly conserved promoter motifs across orthologous genes, using promoter regions that cover the range of [−1200, +500] relative to the transcription start sites. The motif detection is based on ab initio discovery of common cis-elements from the orthologous gene cluster from human, mouse and rat, thus reflecting a degree of promoter sequence preservation during evolution. The identified motifs are linked to transcription factor binding sites based on the TRANSFAC database. In addition, KBERG uses two established ontology systems, GO and eVOC, to associate genes with their function. Users may assess gene functionality through the description terms in GO. Alternatively, they can gain gene co-expression information through evidence from human EST libraries via eVOC. KBERG is a user-friendly system that provides links to other relevant resources such as ERGDB, UniGene, Entrez Gene, HomoloGene, GO, eVOC and GenBank, and thus offers a platform for functional exploration and potential annotation of genes responsive to estrogen. KBERG database can be accessed at .

Cell-autonomous CCL5 transcription by memory CD8 T cells is regulated by IL-4

Immunological memory is associated with the display of improved effector functions. The maintenance by CD8 memory cells of high levels of untranslated CCL5 mRNA allows these cells to immediately secrete this chemokine upon Ag stimulation. Untranslated mRNA storage is a newly described process supporting the immediate display of an effector function by memory lymphocytes. We have tested the capacity of different cytokines to regulate the memorization of CCL5 by memory CD8 T cells. We found that IL-4 treatment of murine CD8 T cells impairs immediate CCL5 secretion capacity by inhibiting CCL5 mRNA transcription through a STAT6-dependent pathway. The inhibition by IL-4 is reversible, as memory CD8 T cells reconstitute their CCL5 mRNA stores and reacquire their immediate CCL5 secretion capacity when IL-4 is withdrawn. This recovery is cell autonomous because it proceeds in culture medium in the absence of exogenous growth factors, suggesting that CCL5 expression by memory CD8 T cells is a default process. Overall, these results indicate that the expression of CCL5 is an intrinsic property acquired by memory CD8 T cells that is regulated by environmental factors.

Computational prediction of novel components of lung transcriptional networks

MOTIVATION

Little is known regarding the transcriptional mechanisms involved in forming and maintaining epithelial cell lineages of the mammalian respiratory tract.

RESULTS

Herein, a motif discovery approach was used to identify novel transcriptional regulators in the lung using genes previously found to be regulated by Foxa2 or Wnt signaling pathways. A human-mouse comparison of both novel and known motifs was also performed. Some of the factors and families identified here were previously shown to be involved epithelial cell differentiation (ETS family, HES-1 and MEIS-1), and ciliogenesis (RFX family), but have never been characterized in lung epithelia. Other unidentified over-represented motifs suggest the existence of novel mammalian lung transcription factors. Of the fraction of motifs examined we describe 25 transcription factor family predictions for lung. Fifteen novel factors were shown here to be expressed in mouse lung, and/or human bronchial or distal lung epithelial tissues or lung epithelial cell lineages.

AVAILABILITY

DME: http://rulai.cshl.edu/dme. MATCOMPARE: http://rulai.cshl.edu/MatCompare. MOTIFCLASS is available from the authors.

New Onto-Tools: Promoter-Express, nsSNPCounter and Onto-Translate

The Onto-Tools suite is composed of an annotation database and eight complementary, web-accessible data mining tools: Onto-Express, Onto-Compare, Onto-Design, Onto-Translate, Onto-Miner, Pathway-Express, Promoter-Express and nsSNPCounter. Promoter-Express is a new tool added to the Onto-Tools ensemble that facilitates the identification of transcription factor binding sites active in specific conditions. nsSNPCounter is another new tool that allows computation and analysis of synonymous and non-synonymous codon substitutions for studying evolutionary rates of protein coding genes. Onto-Translate has also been enhanced to expand its scope and accuracy by fully utilizing the capabilities of the Onto-Tools database. Currently, Onto-Translate allows arbitrary mappings between 28 types of IDs for 53 organisms. Onto-Tools are freely available at .

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.

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.

Measuring similarities between transcription factor binding sites

Background

Collections of transcription factor binding profiles (Transfac, Jaspar) are essential to identify regulatory elements in DNA sequences. Subsets of highly similar profiles complicate large scale analysis of transcription factor binding sites.

Results

We propose to identify and group similar profiles using two independent similarity measures: χ² distances between position frequency matrices (PFMs) and correlation coefficients between position weight matrices (PWMs) scores.

Conclusion

We show that these measures complement each other and allow to associate Jaspar and Transfac matrices. Clusters of highly similar matrices are identified and can be used to optimise the search for regulatory elements. Moreover, the application of the measures is illustrated by assigning E-box matrices of a SELEX experiment and of experimentally characterised binding sites of circadian clock genes to the Myc-Max cluster.

Androgen receptor binding sites identified by a GREF_GATA model

Changes in transcriptional regulation can be permissive for tumor progression by allowing for selective growth advantage of tumor cells. Tumor suppressors can effectively inhibit this process. The PMEPA1 gene, a potent inhibitor of prostate cancer cell growth is an androgen-regulated gene. We addressed the question of whether or not androgen receptor can directly bind to specific PMEPA1 promoter upstream sequences. To test this hypothesis we extended in silico prediction of androgen receptor binding sites by a modeling approach and verified the actual binding by in vivo chromatin immunoprecipitation assay. Promoter upstream sequences of highly androgen-inducible genes were examined from microarray data of prostate cancer cells for transcription factor binding sites (TFBSs). Results were analyzed to formulate a model for the description of specific androgen receptor binding site context in these sequences. In silico analysis and subsequent experimental verification of the selected sequences suggested that a model that combined a GREF and a GATA TFBS was sufficient for predicting a class of functional androgen receptor binding sites. The GREF matrix family represents androgen receptor, glucocorticoid receptor and progesterone receptor binding sites and the GATA matrix family represents GATA binding protein 1-6 binding sites. We assessed the regulatory sequences of the PMEPA1 gene by comparing our model-based GREF_GATA predictions to weight matrix-based predictions. Androgen receptor binding to predicted promoter upstream sequences of the PMEPA1 gene was confirmed by chromatin immunoprecipitation assay. Our results suggested that androgen receptor binding to cognate elements was consistent with the GREF_GATA model. In contrast, using only single GREF weight matrices resulted in additional matches, apparently false positives. Our findings indicate that complex models based on datasets selected by biological function can be superior predictors as they recognize TFBSs in their functional context.

Detecting seeded motifs in DNA sequences

The problem of detecting DNA motifs with functional relevance in real biological sequences is difficult due to a number of biological, statistical and computational issues and also because of the lack of knowledge about the structure of searched patterns. Many algorithms are implemented in fully automated processes, which are often based upon a guess of input parameters from the user at the very first step. In this paper, we present a novel method for the detection of seeded DNA motifs, composed by regions with a different extent of variability. The method is based on a multi-step approach, which was implemented in a motif searching web tool (MOST). Overrepresented exact patterns are extracted from input sequences and clustered to produce motifs core regions, which are then extended and scored to generate seeded motifs. The combination of automated pattern discovery algorithms and different display tools for the evaluation and selection of results at several analysis steps can potentially lead to much more meaningful results than complete automation can produce. Experimental results on different yeast and human real datasets proved the methodology to be a promising solution for finding seeded motifs. MOST web tool is freely available at .

Detection and preliminary analysis of motifs in promoters of anaerobically induced genes of different plant species

BACKGROUND AND AIMS

Plants can suffer from oxygen limitation during flooding or more complete submergence and may therefore switch from Kreb's cycle respiration to fermentation in association with the expression of anaerobically inducible genes coding for enzymes involved in glycolysis and fermentation. The aim of this study was to clarify mechanisms of transcriptional regulation of these anaerobic genes by identifying motifs shared by their promoter regions.

METHODS

Statistically significant motifs were detected by an in silico method from 13 promoters of anaerobic genes. The selected motifs were common for the majority of analysed promoters. Their significance was evaluated by searching for their presence in transcription factor-binding site databases (TRANSFAC, PlantCARE and PLACE). Using several negative control data sets, it was tested whether the motifs found were specific to the anaerobic group.

KEY RESULTS

Previously, anaerobic response elements have been identified in maize (Zea mays) and arabidopsis (Arabidopsis thaliana) genes. Known functional motifs were detected, such as GT and GC motifs, but also other motifs shared by most of the genes examined. Five motifs detected have not been found in plants hitherto but are present in the promoters of animal genes with various functions. The consensus sequences of these novel motifs are 5'-AAACAAA-3', 5'-AGCAGC-3', 5'-TCATCAC-3', 5'-GTTT(A/C/T)GCAA-3' and 5'-TTCCCTGTT-3'.

CONCLUSIONS

It is believed that the promoter motifs identified could be functional by conferring anaerobic sensitivity to the genes that possess them. This proposal now requires experimental verification.

Stress-induced co-expression of alternative respiratory chain components in Arabidopsis thaliana

Plant mitochondria contain non-phosphorylating bypasses of the respiratory chain, catalysed by the alternative oxidase (AOX) and alternative NADH dehydrogenases (NDH), as well as uncoupling (UCP) protein. Each of these components either circumvents or short-circuits proton translocation pathways, and each is encoded by a small gene family in Arabidopsis. Whole genome microarray experiments were performed with suspension cell cultures to examine the effects of various 3 h treatments designed to induce abiotic stress. The expression of over 60 genes encoding components of the classical, phosphorylating respiratory chain and tricarboxylic acid cycle remained largely constant when cells were subjected to a broad range of abiotic stresses, but expression of the alternative components responded differentially to the various treatments. In detailed time-course quantitative PCR analysis, specific members of both AOX and NDH gene families displayed coordinated responses to treatments. In particular, the co-expression of AOX1a and NDB2 observed under a number of treatments suggested co-regulation that may be directed by common sequence elements arranged hierarchically in the upstream promoter regions of these genes. A series of treatment sets were identified, representing the response of specific AOX and NDH genes to mitochondrial inhibition, plastid inhibition and abiotic stresses. These treatment sets emphasise the multiplicity of pathways affecting alternative electron transport components in plants.

MatInspector and beyond: promoter analysis based on transcription factor binding sites

MOTIVATION

Promoter analysis is an essential step on the way to identify regulatory networks. A prerequisite for successful promoter analysis is the prediction of potential transcription factor binding sites (TFBS) with reasonable accuracy. The next steps in promoter analysis can be tackled only with reliable predictions, e.g. finding phylogenetically conserved patterns or identifying higher order combinations of sites in promoters of co-regulated genes.

RESULTS

We present a new version of the program MatInspector that identifies TFBS in nucleotide sequences using a large library of weight matrices. By introducing a matrix family concept, optimized thresholds, and comparative analysis, the enhanced program produces concise results avoiding redundant and false-positive matches. We describe a number of programs based on MatInspector allowing in-depth promoter analysis (DiAlignTF, FrameWorker) and targeted design of regulatory sequences (SequenceShaper).