Cofactor binding evokes latent differences in DNA binding specificity between Hox proteins

Nuclear microenvironments modulate transcription from low-affinity enhancers

Transcription factors bind low-affinity DNA sequences for only short durations. It is not clear how brief, low-affinity interactions can drive efficient transcription. Here, we report that the transcription factor Ultrabithorax (Ubx) utilizes low-affinity binding sites in the Drosophila melanogaster shavenbaby (svb) locus and related enhancers in nuclear microenvironments of high Ubx concentrations. Related enhancers colocalize to the same microenvironments independently of their chromosomal location, suggesting that microenvironments are highly differentiated transcription domains. Manipulating the affinity of svb enhancers revealed an inverse relationship between enhancer affinity and Ubx concentration required for transcriptional activation. The Ubx cofactor, Homothorax (Hth), was co-enriched with Ubx near enhancers that require Hth, even though Ubx and Hth did not co-localize throughout the nucleus. Thus, microenvironments of high local transcription factor and cofactor concentrations could help low-affinity sites overcome their kinetic inefficiency. Mechanisms that generate these microenvironments could be a general feature of eukaryotic transcriptional regulation.

Using competition assays to quantitatively model cooperative binding by transcription factors and other ligands

BACKGROUND

The affinities of DNA binding proteins for target sites can be used to model the regulation of gene expression. These proteins can bind to DNA cooperatively, strongly impacting their affinity and specificity. However, current methods for measuring cooperativity do not provide the means to accurately predict binding behavior over a wide range of concentrations.

METHODS

We use standard computational and mathematical methods, and develop novel methods as described in Results.

RESULTS

We explore some complexities of cooperative binding, and develop an improved method for relating in vitro measurements to in vivo function, based on ternary complex formation. We derive expressions for the equilibria among the various complexes, and explore the limitations of binding experiments that model the system using a single parameter. We describe how to use single-ligand binding and ternary complex formation in tandem to determine parameters that have thermodynamic relevance. We develop an improved method for finding both single-ligand dissociation constants and concentrations simultaneously. We show how the cooperativity factor can be found when only one of the single-ligand dissociation constants can be measured.

CONCLUSIONS

The methods that we develop constitute an optimized approach to accurately model cooperative binding.

GENERAL SIGNIFICANCE

The expressions and methods we develop for modeling and analyzing DNA binding and cooperativity are applicable to most cases where multiple ligands bind to distinct sites on a common substrate. The parameters determined using these methods can be fed into models of higher-order cooperativity to increase their predictive power.

A hypermorphic antioxidant response element is associated with increased MS4A6A expression and Alzheimer's disease

Late onset Alzheimer's disease (AD) is a multifactorial disorder, with AD risk influenced by both environmental and genetic factors. Recent genome-wide association studies (GWAS) have identified genetic loci associated with increased risk of developing AD. The MS4A (membrane-spanning 4-domains subfamily A) gene cluster is one of the most significant loci associated with AD risk, and MS4A6A expression is correlated with AD pathology. We identified a single nucleotide polymorphism, rs667897, at the MS4A locus that creates an antioxidant response element and links MS4A6A expression to the stress responsive Cap-n-Collar (CNC) transcription factors NRF1 (encoded by NFE2L1) and NRF2 (encoded by NFE2L2). The risk allele of rs667897 generates a strong CNC binding sequence that is activated by proteostatic stress in an NRF1-dependent manner, and is associated with increased expression of the gene MS4A6A. Together, these findings suggest that the cytoprotective CNC regulatory network aberrantly activates MS4A6A expression and increases AD risk in a subset of the population.

Recruitment and delivery of the fission yeast Rst2 transcription factor via a local genome structure counteracts repression by Tup1-family corepressors

Transcription factors (TFs) determine the transcription activity of target genes and play a central role in controlling the transcription in response to various environmental stresses. Three dimensional genome structures such as local loops play a fundamental role in the regulation of transcription, although the link between such structures and the regulation of TF binding to cis-regulatory elements remains to be elucidated. Here, we show that during transcriptional activation of the fission yeast fbp1 gene, binding of Rst2 (a critical C2H2 zinc-finger TF) is mediated by a local loop structure. During fbp1 activation, Rst2 is first recruited to upstream-activating sequence 1 (UAS1), then it subsequently binds to UAS2 (a critical cis-regulatory site located approximately 600 base pairs downstream of UAS1) through a loop structure that brings UAS1 and UAS2 into spatially close proximity. Tup11/12 (the Tup-family corepressors) suppress direct binding of Rst2 to UAS2, but this suppression is counteracted by the recruitment of Rst2 at UAS1 and following delivery to UAS2 through a loop structure. These data demonstrate a previously unappreciated mechanism for the recruitment and expansion of TF-DNA interactions within a promoter mediated by local three-dimensional genome structures and for timely TF-binding via counteractive regulation by the Tup-family corepressors.

Coop-Seq Analysis Demonstrates that Sox2 Evokes Latent Specificities in the DNA Recognition by Pax6

Sox2 and Pax6 co-regulate genes in neural lineages and the lens by forming a ternary complex likely facilitated allosterically through DNA. We used the quantitative and scalable cooperativity-by-sequencing (Coop-seq) approach to interrogate Sox2/Pax6 dimerization on a DNA library where five positions of the Pax6 half-site were randomized yielding 1024 cooperativity factors. Consensus positions normally required for the high-affinity DNA binding by Pax6 need to be mutated for effective dimerization with Sox2. Out of the five randomized bases, a 5' thymidine is present in most of the top ranking elements. However, this thymidine maps to a region outside of the Pax half site and is not expected to directly interact with Pax6 in known binding modes suggesting structural reconfigurations. Re-analysis of ChIP-seq data identified several genomic regions where the cooperativity promoting sequence pattern is co-bound by Sox2 and Pax6. A highly conserved Sox2/Pax6 bound site near the Sprouty2 locus was verified to promote cooperative dimerization designating Sprouty2 as a potential target reliant on Sox2/Pax6 cooperativity in several neural cell types. Collectively, the functional interplay of Sox2 and Pax6 demands the relaxation of high-affinity binding sites and is enabled by alternative DNA sequences. We conclude that this binding mode evolved to warrant that a subset of target genes is only regulated in the presence of suitable partner factors.

Identification of Human Lineage-Specific Transcriptional Coregulators Enabled by a Glossary of Binding Modules and Tunable Genomic Backgrounds

Transcription factors (TFs) control cellular processes by binding specific DNA motifs to modulate gene expression. Motif enrichment analysis of regulatory regions can identify direct and indirect TF binding sites. Here, we created a glossary of 108 non-redundant TF-8mer "modules" of shared specificity for 671 metazoan TFs from publicly available and new universal protein binding microarray data. Analysis of 239 ENCODE TF chromatin immunoprecipitation sequencing datasets and associated RNA sequencing profiles suggest the 8mer modules are more precise than position weight matrices in identifying indirect binding motifs and their associated tethering TFs. We also developed GENRE (genomically equivalent negative regions), a tunable tool for construction of matched genomic background sequences for analysis of regulatory regions. GENRE outperformed four state-of-the-art approaches to background sequence construction. We used our TF-8mer glossary and GENRE in the analysis of the indirect binding motifs for the co-occurrence of tethering factors, suggesting novel TF-TF interactions. We anticipate that these tools will aid in elucidating tissue-specific gene-regulatory programs.

Predicting Variation of DNA Shape Preferences in Protein-DNA Interaction in Cancer Cells with a New Biophysical Model

DNA shape readout is an important mechanism of transcription factor target site recognition, in addition to the sequence readout. Several machine learning-based models of transcription factor-DNA interactions, considering DNA shape features, have been developed in recent years. Here, we present a new biophysical model of protein-DNA interactions by integrating the DNA shape properties. It is based on the neighbor dinucleotide dependency model BayesPI2, where new parameters are restricted to a subspace spanned by the dinucleotide form of DNA shape features. This allows a biophysical interpretation of the new parameters as a position-dependent preference towards specific DNA shape features. Using the new model, we explore the variation of DNA shape preferences in several transcription factors across various cancer cell lines and cellular conditions. The results reveal that there are DNA shape variations at FOXA1 (Forkhead Box Protein A1) binding sites in steroid-treated MCF7 cells. The new biophysical model is useful for elucidating the finer details of transcription factor-DNA interaction, as well as for predicting cancer mutation effects in the future.

The Hox proteins Ubx and AbdA collaborate with the transcription pausing factor M1BP to regulate gene transcription

In metazoans, the pausing of RNA polymerase II at the promoter (paused Pol II) has emerged as a widespread and conserved mechanism in the regulation of gene transcription. While critical in recruiting Pol II to the promoter, the role transcription factors play in transitioning paused Pol II into productive Pol II is, however, little known. By studying how Drosophila Hox transcription factors control transcription, we uncovered a molecular mechanism that increases productive transcription. We found that the Hox proteins AbdA and Ubx target gene promoters previously bound by the transcription pausing factor M1BP, containing paused Pol II and enriched with promoter-proximal Polycomb Group (PcG) proteins, yet lacking the classical H3K27me3 PcG signature. We found that AbdA binding to M1BP-regulated genes results in reduction in PcG binding, the release of paused Pol II, increases in promoter H3K4me3 histone marks and increased gene transcription. Linking transcription factors, PcG proteins and paused Pol II states, these data identify a two-step mechanism of Hox-driven transcription, with M1BP binding leading to Pol II recruitment followed by AbdA targeting, which results in a change in the chromatin landscape and enhanced transcription.

Segmental arithmetic: summing up the Hox gene regulatory network for hindbrain development in chordates

Organization and development of the early vertebrate hindbrain are controlled by a cascade of regulatory interactions that govern the process of segmentation and patterning along the anterior-posterior axis via Hox genes. These interactions can be assembled into a gene regulatory network that provides a framework to interpret experimental data, generate hypotheses, and identify gaps in our understanding of the progressive process of hindbrain segmentation. The network can be broadly separated into a series of interconnected programs that govern early signaling, segmental subdivision, secondary signaling, segmentation, and ultimately specification of segmental identity. Hox genes play crucial roles in multiple programs within this network. Furthermore, the network reveals properties and principles that are likely to be general to other complex developmental systems. Data from vertebrate and invertebrate chordate models are shedding light on the origin and diversification of the network. Comprehensive cis-regulatory analyses of vertebrate Hox gene regulation have enabled powerful cross-species gene regulatory comparisons. Such an approach in the sea lamprey has revealed that the network mediating segmental Hox expression was present in ancestral vertebrates and has been maintained across diverse vertebrate lineages. Invertebrate chordates lack hindbrain segmentation but exhibit conservation of some aspects of the network, such as a role for retinoic acid in establishing nested Hox expression domains. These comparisons lead to a model in which early vertebrates underwent an elaboration of the network between anterior-posterior patterning and Hox gene expression, leading to the gene-regulatory programs for segmental subdivision and rhombomeric segmentation. WIREs Dev Biol 2017, 6:e286. doi: 10.1002/wdev.286 For further resources related to this article, please visit the WIREs website.

Differences in DNA Binding Specificity of Floral Homeotic Protein Complexes Predict Organ-Specific Target Genes

Floral organ identities in plants are specified by the combinatorial action of homeotic master regulatory transcription factors. However, how these factors achieve their regulatory specificities is still largely unclear. Genome-wide in vivo DNA binding data show that homeotic MADS domain proteins recognize partly distinct genomic regions, suggesting that DNA binding specificity contributes to functional differences of homeotic protein complexes. We used in vitro systematic evolution of ligands by exponential enrichment followed by high-throughput DNA sequencing (SELEX-seq) on several floral MADS domain protein homo- and heterodimers to measure their DNA binding specificities. We show that specification of reproductive organs is associated with distinct binding preferences of a complex formed by SEPALLATA3 and AGAMOUS. Binding specificity is further modulated by different binding site spacing preferences. Combination of SELEX-seq and genome-wide DNA binding data allows differentiation between targets in specification of reproductive versus perianth organs in the flower. We validate the importance of DNA binding specificity for organ-specific gene regulation by modulating promoter activity through targeted mutagenesis. Our study shows that intrafamily protein interactions affect DNA binding specificity of floral MADS domain proteins. Differential DNA binding of MADS domain protein complexes plays a role in the specificity of target gene regulation.

Inherent limitations of probabilistic models for protein-DNA binding specificity

The specificities of transcription factors are most commonly represented with probabilistic models. These models provide a probability for each base occurring at each position within the binding site and the positions are assumed to contribute independently. The model is simple and intuitive and is the basis for many motif discovery algorithms. However, the model also has inherent limitations that prevent it from accurately representing true binding probabilities, especially for the highest affinity sites under conditions of high protein concentration. The limitations are not due to the assumption of independence between positions but rather are caused by the non-linear relationship between binding affinity and binding probability and the fact that independent normalization at each position skews the site probabilities. Generally probabilistic models are reasonably good approximations, but new high-throughput methods allow for biophysical models with increased accuracy that should be used whenever possible.

Transcription factors (TFs), a class of DNA-binding proteins, play a central role in the regulation of gene expression. TFs control the rate of transcription by binding to the genome in a sequence-specific manner. Thus, one important aspect in the study of gene regulation mechanism is to model the binding specificities of TFs, namely the features of the DNA sequences that a TF prefers to bind. Multiple models have been proposed to characterize the binding specificities of TFs, among which the class of probabilistic models is the most popular. In this study, we point out several major limitations of the well-established probabilistic model by comparing it with the biophysical model. Through simulations we demonstrate that the probabilistic model is only an approximation of the biophysical model. The latter has most of the advantages of the former, and is a more accurate representation of binding specificities. We propose a shift from the probabilistic model to the biophysical model in future studies of protein-DNA interactions.

ConTra v3: a tool to identify transcription factor binding sites across species, update 2017

Transcription factors are important gene regulators with distinctive roles in development, cell signaling and cell cycling, and they have been associated with many diseases. The ConTra v3 web server allows easy visualization and exploration of predicted transcription factor binding sites (TFBSs) in any genomic region surrounding coding or non-coding genes. In this updated version, with a completely re-implemented user interface using latest web technologies, users can choose from nine reference organisms ranging from human to yeast. ConTra v3 can analyze promoter regions, 5΄-UTRs, 3΄-UTRs and introns or any other genomic region of interest. Thousands of position weight matrices are available to choose from for detecting specific binding sites. Besides this visualization option, additional new exploration functionality is added to the tool that will automatically detect TFBSs having at the same time the highest regulatory potential, the highest conservation scores of the genomic regions covered by the predicted TFBSs and strongest co-localizations with genomic regions exhibiting regulatory activity. The ConTra v3 web server is freely available at http://bioit2.irc.ugent.be/contra/v3.

WSMD: weakly-supervised motif discovery in transcription factor ChIP-seq data

Although discriminative motif discovery (DMD) methods are promising for eliciting motifs from high-throughput experimental data, due to consideration of computational expense, most of existing DMD methods have to choose approximate schemes that greatly restrict the search space, leading to significant loss of predictive accuracy. In this paper, we propose Weakly-Supervised Motif Discovery (WSMD) to discover motifs from ChIP-seq datasets. In contrast to the learning strategies adopted by previous DMD methods, WSMD allows a "global" optimization scheme of the motif parameters in continuous space, thereby reducing the information loss of model representation and improving the quality of resultant motifs. Meanwhile, by exploiting the connection between DMD framework and existing weakly supervised learning (WSL) technologies, we also present highly scalable learning strategies for the proposed method. The experimental results on both real ChIP-seq datasets and synthetic datasets show that WSMD substantially outperforms former DMD methods (including DREME, HOMER, XXmotif, motifRG and DECOD) in terms of predictive accuracy, while also achieving a competitive computational speed.

Hox5 Paralogous Genes Modulate Th2 Cell Function during Chronic Allergic Inflammation via Regulation of Gata3

Allergic asthma is a significant health burden in western countries, and continues to increase in prevalence. Th2 cells contribute to the development of disease through release of the cytokines IL-4, IL-5, and IL-13, resulting in increased airway eosinophils and mucus hypersecretion. The molecular mechanisms behind the disease pathology remain largely unknown. In this study we investigated a potential regulatory role for the Hox5 gene family, Hoxa5, Hoxb5, and Hoxc5, genes known to be important in lung development within mesenchymal cell populations. We found that Hox5-mutant mice show exacerbated pathology compared with wild-type controls in a chronic allergen model, with an increased Th2 response and exacerbated lung tissue pathology. Bone marrow chimera experiments indicated that the observed enhanced pathology was mediated by immune cell function independent of mesenchymal cell Hox5 family function. Examination of T cells grown in Th2 polarizing conditions showed increased proliferation, enhanced Gata3 expression, and elevated production of IL-4, IL-5, and IL-13 in Hox5-deficient T cells compared with wild-type controls. Overexpression of FLAG-tagged HOX5 proteins in Jurkat cells demonstrated HOX5 binding to the Gata3 locus and decreased Gata3 and IL-4 expression, supporting a role for HOX5 proteins in direct transcriptional control of Th2 development. These results reveal a novel role for Hox5 genes as developmental regulators of Th2 immune cell function that demonstrates a redeployment of mesenchyme-associated developmental genes.

Transcriptional regulatory network of WOX11 is involved in the control of crown root development, cytokinin signals, and redox in rice

The rice root system is mainly composed of post-embryonic shoot-borne roots called crown roots. WOX11, encoding a WUSCHEL-related homeobox domain transcription factor, is a key regulator of crown root growth and development in rice (Oryza sativa. L). In addition to specifically activating crown root development, WOX11 is also involved in lateral root initiation, root hair formation, and abiotic stresses. However, the gene regulatory network downstream of WOX11 remains largely unknown. Here, we studied the transcriptome of wox11 root tips by RNA-Seq and determined direct WOX11-binding targets by bioinformatic and biochemical analysis. The transcriptomic analysis revealed 664 differentially expressed genes, which covered a wide range of functions related to root development, cytokinin homeostasis/signaling, stress response, and redox metabolic processes. Bioinformatic analysis also revealed that the WOX11-binding motif was distributed over 41% (273/664) of the differentially expressed genes, and was mostly enriched in the promoter and intron regions. We used qRT-PCR and/or in situ hybridization to confirm co-expression of some of the WOX11-regulated genes in crown root development. We also used electrophoretic mobility shift assay and chromatin immunoprecipitation with anti-WOX11 antibody to validate direct regulation of these genes by WOX11. The analysis identified several genes that acted downstream of WOX11 in controlling crown root formation, cytokinin signaling, stress response, and redox metabolism. This work built a hierarchical regulatory model of WOX11 in rice crown root development.

Evolution of reduced co-activator dependence led to target expansion of a starvation response pathway

Although combinatorial regulation is a common feature in gene regulatory networks, how it evolves and affects network structure and function is not well understood. In S. cerevisiae, the phosphate starvation (PHO) responsive transcription factors Pho4 and Pho2 are required for gene induction and survival during phosphate starvation. In the related human commensal C. glabrata, Pho4 is required but Pho2 is dispensable for survival in phosphate starvation and is only partially required for inducing PHO genes. Phylogenetic survey suggests that reduced dependence on Pho2 evolved in C. glabrata and closely related species. In S. cerevisiae, less Pho2-dependent Pho4 orthologs induce more genes. In C. glabrata, its Pho4 binds to more locations and induces three times as many genes as Pho4 in S. cerevisiae does. Our work shows how evolution of combinatorial regulation allows for rapid expansion of a gene regulatory network’s targets, possibly extending its physiological functions.

The diversity of life on Earth has intrigued generations of scientists and nature lovers alike. Research over recent decades has revealed that much of the diversity we can see did not require the invention of new genes. Instead, living forms diversified mostly by using old genes in new ways – for example, by changing when or where an existing gene became active. This kind of change is referred to as “regulatory evolution”.

A class of proteins called transcription factors are hot spots in regulatory evolution. These proteins recognize specific sequences of DNA to control the activity of other genes, and so represent the “readers” of the genetic information. Small changes to how a transcription factor is regulated, or the genes it targets, can lead to dramatic changes in an organism. Before we can understand how life on Earth evolved to be so diverse, scientists must first answer how transcription factors evolve and what consequences this has on their target genes.

So far, most studies of regulatory evolution have focused on networks of transcription factors and genes that control how an organism develops. He et al. have now studied a regulatory network that is behind a different process, namely how an organism responds to stress or starvation. These two types of regulatory networks are structured differently and work in different ways. These differences made He et al. wonder if the networks evolved differently too.

The chemical phosphate is an essential nutrient for all living things, and He et al. compared how two different species of yeast responded to a lack of phosphate. The key difference was how much a major transcription factor known as Pho4 depended on a so-called co-activator protein named Pho2 to carry out its role. Baker’s yeast (Saccharomyces cerevisiae), which is commonly used in laboratory experiments, requires both Pho4 and Pho2 to activate about 20 genes when inorganic phosphate is not available in its environment. However, in a related yeast species called Candida glabrata, Pho4 has evolved to depend less on Pho2. He et al. went on to show that, as well as being less dependent on Pho2, Pho4 in C. glabrata activates more than three times as many genes as Pho4 in S. cerevisiae does in the absence of phosphate. These additional gene targets for Pho4 in C. glabrata are predicted to extend the network’s activities, and allow it to regulate new process including the yeast’s responses to other types of stress and the building of the yeast’s cell wall.

Together these findings show a new way that regulatory networks can evolve, that is, by reducing its dependence on the co-activator, a transcription factor can expand the number of genes it targets. This has not been seen for regulatory networks related to development, suggesting that different networks can indeed evolve in different ways. Lastly, because disease-causing microbes are often stressed inside their hosts and C. glabrata sometimes infects humans, understanding how this yeast’s response to stress has evolved may lead to new ways to prevent and treat this infection.

Modeling protein-DNA binding via high-throughput in vitro technologies

Protein-DNA binding plays a central role in gene regulation and by that in all processes in the living cell. Novel experimental and computational approaches facilitate better understanding of protein-DNA binding preferences via high-throughput measurement of protein binding to a large number of DNA sequences and inference of binding models from them. Here we review the state of the art in measuring protein-DNA binding in vitro, emphasizing the advantages and limitations of different technologies. In addition, we describe models for representing protein-DNA binding preferences and key computational approaches to learn those from high-throughput data. Using large experimental data sets, we test the performance of different models based on different measuring techniques. We conclude with pertinent open problems.

Network-based approaches that exploit inferred transcription factor activity to analyze the impact of genetic variation on gene expression

Over the past decade, a number of methods have emerged for inferring protein-level transcription factor activities in individual samples based on prior information about the structure of the gene regulatory network. We discuss how this has enabled new methods for dissecting trans-acting mechanisms that underpin genetic variation in gene expression.

Transcription factor-DNA binding: beyond binding site motifs

Sequence-specific transcription factors (TFs) regulate gene expression by binding to cis-regulatory elements in promoter and enhancer DNA. While studies of TF-DNA binding have focused on TFs' intrinsic preferences for primary nucleotide sequence motifs, recent studies have elucidated additional layers of complexity that modulate TF-DNA binding. In this review, we discuss technological developments for identifying TF binding preferences and highlight recent discoveries that elaborate how TF interactions, local DNA structure, and genomic features influence TF-DNA binding. We highlight novel approaches for characterizing functional binding site motifs that promise to inform our understanding of how TF binding controls gene expression and ultimately contributes to phenotype.

Systematic dissection of genomic features determining transcription factor binding and enhancer function

Enhancers regulate gene expression through the binding of sequence-specific transcription factors (TFs) to cognate motifs. Various features influence TF binding and enhancer function-including the chromatin state of the genomic locus, the affinities of the binding site, the activity of the bound TFs, and interactions among TFs. However, the precise nature and relative contributions of these features remain unclear. Here, we used massively parallel reporter assays (MPRAs) involving 32,115 natural and synthetic enhancers, together with high-throughput in vivo binding assays, to systematically dissect the contribution of each of these features to the binding and activity of genomic regulatory elements that contain motifs for PPARγ, a TF that serves as a key regulator of adipogenesis. We show that distinct sets of features govern PPARγ binding vs. enhancer activity. PPARγ binding is largely governed by the affinity of the specific motif site and higher-order features of the larger genomic locus, such as chromatin accessibility. In contrast, the enhancer activity of PPARγ binding sites depends on varying contributions from dozens of TFs in the immediate vicinity, including interactions between combinations of these TFs. Different pairs of motifs follow different interaction rules, including subadditive, additive, and superadditive interactions among specific classes of TFs, with both spatially constrained and flexible grammars. Our results provide a paradigm for the systematic characterization of the genomic features underlying regulatory elements, applicable to the design of synthetic regulatory elements or the interpretation of human genetic variation.

Combinatorial bZIP dimers display complex DNA-binding specificity landscapes

How transcription factor dimerization impacts DNA-binding specificity is poorly understood. Guided by protein dimerization properties, we examined DNA binding specificities of 270 human bZIP pairs. DNA interactomes of 80 heterodimers and 22 homodimers revealed that 72% of heterodimer motifs correspond to conjoined half-sites preferred by partnering monomers. Remarkably, the remaining motifs are composed of variably-spaced half-sites (12%) or 'emergent' sites (16%) that cannot be readily inferred from half-site preferences of partnering monomers. These binding sites were biochemically validated by EMSA-FRET analysis and validated in vivo by ChIP-seq data from human cell lines. Focusing on ATF3, we observed distinct cognate site preferences conferred by different bZIP partners, and demonstrated that genome-wide binding of ATF3 is best explained by considering many dimers in which it participates. Importantly, our compendium of bZIP-DNA interactomes predicted bZIP binding to 156 disease associated SNPs, of which only 20 were previously annotated with known bZIP motifs.

Transcription factor family-specific DNA shape readout revealed by quantitative specificity models

Transcription factors (TFs) achieve DNA‐binding specificity through contacts with functional groups of bases (base readout) and readout of structural properties of the double helix (shape readout). Currently, it remains unclear whether DNA shape readout is utilized by only a few selected TF families, or whether this mechanism is used extensively by most TF families. We resequenced data from previously published HT‐SELEX experiments, the most extensive mammalian TF–DNA binding data available to date. Using these data, we demonstrated the contributions of DNA shape readout across diverse TF families and its importance in core motif‐flanking regions. Statistical machine‐learning models combined with feature‐selection techniques helped to reveal the nucleotide position‐dependent DNA shape readout in TF‐binding sites and the TF family‐specific position dependence. Based on these results, we proposed novel DNA shape logos to visualize the DNA shape preferences of TFs. Overall, this work suggests a way of obtaining mechanistic insights into TF–DNA binding without relying on experimentally solved all‐atom structures.

Unveiling DNA structural features of promoters associated with various types of TSSs in prokaryotic transcriptomes and their role in gene expression

Next-generation sequencing studies have revealed that a variety of transcripts are present in the prokaryotic transcriptome and a significant fraction of them are functional, being involved in various regulatory activities apart from coding for proteins. Identification of promoters associated with different transcripts is necessary for characterization of the transcriptome. Promoter regions have been shown to have unique structural features as compared with their flanking region, in organisms covering all domains of life. Here we report an in silico analysis of DNA sequence dependent structural properties like stability, bendability and curvature in the promoter region of six different prokaryotic transcriptomes. Using these structural features, we predicted promoters associated with different categories of transcripts (mRNA, internal, antisense and non-coding), which constitute the transcriptome. Promoter annotation using structural features is fairly accurate and reliable with about 50% of the primary promoters being characterized by all three structural properties while at least one property identifies 95%. We also studied the relative differences of these structural features in terms of gene expression and found that the features, viz. lower stability, lesser bendability and higher curvature are more prominent in the promoter regions which are associated with high gene expression as compared with low expression genes. Hence, promoters, which are associated with higher gene expression, get annotated well using DNA structural features as compared with those, which are linked to lower gene expression.

HOXA9 transcriptionally regulates the EPHB4 receptor to modulate trophoblast migration and invasion

INTRODUCTION

Functional placenta formation is crucially dependent on extravillous trophoblast migration and invasion. EPHB4 has been identified to play a negative but important role in regulating trophoblast biological function, whereas the upstream regulation mechanism remains unknown. As reported, there is a transcriptional stimulation of EPHB4 expression consequent to HOXA9 activation in endothelial cells (ECs). Therefore, this study is conducted to investigate the role of HOXA9 and its relationship with EPHB4 in trophoblast cells.

METHOD

Both mRNA and protein expression levels of HOXA9 and EPHB4 were measured in preeclamptic placenta (n = 15) and normal placenta (n = 15). Next, the expression and location of HOXA9 and EPHB4 in first-trimester villi were shown via immunohistochemistry. Trophoblast cell line HTR-8/SVneo was used to explore the effect of HOXA9 on EPHB4 expression and trophoblast bioactivity by gain- and loss-of function studies. In addition, chromatin immunoprecipitation (ChIP) and luciferase assays were conducted to clarify the regulation mechanism of HOXA9 on EPHB4 expression in HTR-8/SVneo.

RESULT

HOXA9 and EPHB4 expression were increased in preeclamptic placenta compared with normal placenta. HOXA9 could promote EPHB4 expression and impaired HTR-8/SVneo cells migration and invasion. ChIP and luciferase assays revealed that HOXA9 could directly bind to EPHB4 promoter and promoted its transcription.

CONCLUSION

HOXA9 transcriptionally regulated EPHB4 expression to modulate trophoblasts migration and invasion, which may suggest a contribution of HOXA9-EPHB4 in the poor placentation in the pathogenesis of preeclampsia.

Transcriptional Regulation by Wild-Type and Cancer-Related Mutant Forms of p53

TP53 missense mutations produce a mutant p53 protein that cannot activate the p53 tumor suppressive transcriptional response, which is the primary selective pressure for TP53 mutation. Specific codons of TP53, termed hotspot mutants, are mutated at elevated frequency. Hotspot forms of mutant p53 possess oncogenic properties in addition to being deficient in tumor suppression. Such p53 mutants accumulate to high levels in the cells they inhabit, causing transcriptional alterations that produce pro-oncogenic activities, such as increased pro-growth signaling, invasiveness, and metastases. These forms of mutant p53 very likely use features of wild-type p53, such as interactions with the transcriptional machinery, to produce oncogenic effects. In this review, we discuss commonalities between wild-type and mutant p53 proteins with an emphasis on transcriptional processes.

Genome-Wide Binding of Posterior HOXA/D Transcription Factors Reveals Subgrouping and Association with CTCF

Homeotic genes code for key transcription factors (HOX-TFs) that pattern the animal body plan. During embryonic development, Hox genes are expressed in overlapping patterns and function in a partially redundant manner. In vitro biochemical screens probing the HOX-TF sequence specificity revealed largely overlapping sequence preferences, indicating that co-factors might modulate the biological function of HOX-TFs. However, due to their overlapping expression pattern, high protein homology, and insufficiently specific antibodies, little is known about their genome-wide binding preferences. In order to overcome this problem, we virally expressed tagged versions of limb-expressed posterior HOX genes (HOXA9-13, and HOXD9-13) in primary chicken mesenchymal limb progenitor cells (micromass). We determined the effect of each HOX-TF on cellular differentiation (chondrogenesis) and gene expression and found that groups of HOX-TFs induce distinct regulatory programs. We used ChIP-seq to determine their individual genome-wide binding profiles and identified between 12,721 and 28,572 binding sites for each of the nine HOX-TFs. Principal Component Analysis (PCA) of binding profiles revealed that the HOX-TFs are clustered in two subgroups (Group 1: HOXA/D9, HOXA/D10, HOXD12, and HOXA13 and Group 2: HOXA/D11 and HOXD13), which are characterized by differences in their sequence specificity and by the presence of cofactor motifs. Specifically, we identified CTCF binding sites in Group 1, indicating that this subgroup of HOX-proteins cooperates with CTCF. We confirmed this interaction by an independent biological assay (Proximity Ligation Assay) and demonstrated that CTCF is a novel HOX cofactor that specifically associates with Group 1 HOX-TFs, pointing towards a possible interplay between HOX-TFs and chromatin architecture.

Hox genes encode transcription factors that determine the vertebrate body plan and pattern structures and organs in the developing embryo. Despite decades of effort and research on Hox genes, little is known about the HOX-DNA binding properties in vivo. This lack of knowledge is mainly due to the absence of appropriate antibodies to distinguish between different HOX transcription factors. Here, we adapt a cell culture system that allows us to investigate HOX-DNA binding on a genome-wide scale. With this approach, we define and directly compare the genome-wide binding sites of nine posterior HOXA and HOXD transcription factors. We report that the in vivo HOX binding specificity differs from the in vitro specificity and find that HOX-TFs largely rely on co-factor binding and not only on direct HOX-DNA binding. Finally, we identify a novel HOX co-factor, a genome architecture protein, CTCF suggesting a possible interplay between HOX-TF function and chromatin architecture.

Regulatory elements in molecular networks

Regulatory elements determine the connectivity of molecular networks and mediate a variety of regulatory processes ranging from DNA looping to transcriptional, posttranscriptional, and posttranslational regulation. This review highlights our current understanding of the different types of regulatory elements found in molecular networks with a focus on DNA regulatory elements. We highlight technical advances and current challenges for the mapping of regulatory elements at the genome-wide scale, and describe new computational methods to uncover these elements via reconstructing regulatory networks from large genomic datasets. WIREs Syst Biol Med 2017, 9:e1374. doi: 10.1002/wsbm.1374 For further resources related to this article, please visit the WIREs website.

SELEX-Seq: A Method to Determine DNA Binding Specificities of Plant Transcription Factors

Systematic evolution of ligands by exponential enrichment (SELEX) is a method that allows isolating specific nucleotide sequences that interact with a DNA binding protein of choice. By using a transcription factor (TF) and a randomized pool of double-stranded DNA, this technique can be used to characterize TF DNA binding specificities and affinities. The method is based on protein-DNA complex immunoprecipitation with protein-specific antibodies and subsequent DNA selection and amplification. Application of massively parallel sequencing (-seq) at each cycle of SELEX allows determining the relative affinities to any DNA sequence for any transcription factor or TF complex. The resulting TF DNA binding motifs can be used to predict potential DNA binding sites in genomes and thereby direct target genes of TFs.

Cross-Family Transcription Factor Interactions: An Additional Layer of Gene Regulation

Specific and dynamic gene expression strongly depends on transcription factor (TF) activity and most plant TFs function in a combinatorial fashion. They can bind to DNA and control the expression of the corresponding gene in an additive fashion or cooperate by physical interactions, forming larger protein complexes. The importance of protein-protein interactions between members of a particular plant TF family has long been recognised; however, a significant number of interfamily TF interactions has recently been reported. The biological implications and the molecular mechanisms involved in cross-family interactions have now started to be elucidated and the examples illustrate potential roles in the bridging of biological processes. Hence, cross-family TF interactions expand the molecular toolbox for plants with additional mechanisms to control and fine-tune robust gene expression patterns and to adapt to their continuously changing environment.

Quantitative profiling of selective Sox/POU pairing on hundreds of sequences in parallel by Coop-seq

Cooperative binding of transcription factors is known to be important in the regulation of gene expression programs conferring cellular identities. However, current methods to measure cooperativity parameters have been laborious and therefore limited to studying only a few sequence variants at a time. We developed Coop-seq (cooperativity by sequencing) that is capable of efficiently and accurately determining the cooperativity parameters for hundreds of different DNA sequences in a single experiment. We apply Coop-seq to 12 dimer pairs from the Sox and POU families of transcription factors using 324 unique sequences with changed half-site orientation, altered spacing and discrete randomization within the binding elements. The study reveals specific dimerization profiles of different Sox factors with Oct4. By contrast, Oct4 and the three neural class III POU factors Brn2, Brn4 and Oct6 assemble with Sox2 in a surprisingly indistinguishable manner. Two novel half-site configurations can support functional Sox/Oct dimerization in addition to known composite motifs. Moreover, Coop-seq uncovers a nucleotide switch within the POU half-site when spacing is altered, which is mirrored in genomic loci bound by Sox2/Oct4 complexes.

Thermodynamic Additivity for Impacts of Base-Pair Substitutions on Association of the Egr-1 Zinc-Finger Protein with DNA

The transcription factor Egr-1 specifically binds as a monomer to its 9 bp target DNA sequence, GCGTGGGCG, via three zinc fingers and plays important roles in the brain and cardiovascular systems. Using fluorescence-based competitive binding assays, we systematically analyzed the impacts of all possible single-nucleotide substitutions in the target DNA sequence and determined the change in binding free energy for each. Then, we measured the changes in binding free energy for sequences with multiple substitutions and compared them with the sum of the changes in binding free energy for each constituent single substitution. For the DNA variants with two or three nucleotide substitutions in the target sequence, we found excellent agreement between the measured and predicted changes in binding free energy. Interestingly, however, we found that this thermodynamic additivity broke down with a larger number of substitutions. For DNA sequences with four or more substitutions, the measured changes in binding free energy were significantly larger than predicted. On the basis of these results, we analyzed the occurrences of high-affinity sequences in the genome and found that the genome contains millions of such sequences that might functionally sequester Egr-1.

Synthetic genome readers target clustered binding sites across diverse chromatin states

Targeting the genome with sequence-specific DNA-binding molecules is a major goal at the interface of chemistry, biology, and precision medicine. Polyamides, composed of N-methylpyrrole and N-methylimidazole monomers, are a class of synthetic molecules that can be rationally designed to "read" specific DNA sequences. However, the impact of different chromatin states on polyamide binding in live cells remains an unresolved question that impedes their deployment in vivo. Here, we use cross-linking of small molecules to isolate chromatin coupled to sequencing to map the binding of two bioactive and structurally distinct polyamides to genomes directly within live H1 human embryonic stem cells. This genome-wide view from live cells reveals that polyamide-based synthetic genome readers bind cognate sites that span a range of binding affinities. Polyamides can access cognate sites within repressive heterochromatin. The occupancy patterns suggest that polyamides could be harnessed to target loci within regions of the genome that are inaccessible to other DNA-targeting molecules.

Integrated analysis of RNA-binding protein complexes using in vitro selection and high-throughput sequencing and sequence specificity landscapes (SEQRS)

RNA-binding proteins (RBPs) collaborate to control virtually every aspect of RNA function. Tremendous progress has been made in the area of global assessment of RBP specificity using next-generation sequencing approaches both in vivo and in vitro. Understanding how protein-protein interactions enable precise combinatorial regulation of RNA remains a significant problem. Addressing this challenge requires tools that can quantitatively determine the specificities of both individual proteins and multimeric complexes in an unbiased and comprehensive way. One approach utilizes in vitro selection, high-throughput sequencing, and sequence-specificity landscapes (SEQRS). We outline a SEQRS experiment focused on obtaining the specificity of a multi-protein complex between Drosophila RBPs Pumilio (Pum) and Nanos (Nos). We discuss the necessary controls in this type of experiment and examine how the resulting data can be complemented with structural and cell-based reporter assays. Additionally, SEQRS data can be integrated with functional genomics data to uncover biological function. Finally, we propose extensions of the technique that will enhance our understanding of multi-protein regulatory complexes assembled onto RNA.

DNA Shape Features Improve Transcription Factor Binding Site Predictions In Vivo

Interactions of transcription factors (TFs) with DNA comprise a complex interplay between base-specific amino acid contacts and readout of DNA structure. Recent studies have highlighted the complementarity of DNA sequence and shape in modeling TF binding in vitro. Here, we have provided a comprehensive evaluation of in vivo datasets to assess the predictive power obtained by augmenting various DNA sequence-based models of TF binding sites (TFBSs) with DNA shape features (helix twist, minor groove width, propeller twist, and roll). Results from 400 human ChIP-seq datasets for 76 TFs show that combining DNA shape features with position-specific scoring matrix (PSSM) scores improves TFBS predictions. Improvement has also been observed using TF flexible models and a machine-learning approach using a binary encoding of nucleotides in lieu of PSSMs. Incorporating DNA shape information is most beneficial for E2F and MADS-domain TF families. Our findings indicate that incorporating DNA sequence and shape information benefits the modeling of TF binding under complex in vivo conditions.

SELMAP - SELEX affinity landscape MAPping of transcription factor binding sites using integrated microfluidics

Transcription factors (TFs) alter gene expression in response to changes in the environment through sequence-specific interactions with the DNA. These interactions are best portrayed as a landscape of TF binding affinities. Current methods to study sequence-specific binding preferences suffer from limited dynamic range, sequence bias, lack of specificity and limited throughput. We have developed a microfluidic-based device for SELEX Affinity Landscape MAPping (SELMAP) of TF binding, which allows high-throughput measurement of 16 proteins in parallel. We used it to measure the relative affinities of Pho4, AtERF2 and Btd full-length proteins to millions of different DNA binding sites, and detected both high and low-affinity interactions in equilibrium conditions, generating a comprehensive landscape of the relative TF affinities to all possible DNA 6-mers, and even DNA10-mers with increased sequencing depth. Low quantities of both the TFs and DNA oligomers were sufficient for obtaining high-quality results, significantly reducing experimental costs. SELMAP allows in-depth screening of hundreds of TFs, and provides a means for better understanding of the regulatory processes that govern gene expression.

Identification of DNA-binding proteins using multi-features fusion and binary firefly optimization algorithm

Background

DNA-binding proteins (DBPs) play fundamental roles in many biological processes. Therefore, the developing of effective computational tools for identifying DBPs is becoming highly desirable.

Results

In this study, we proposed an accurate method for the prediction of DBPs. Firstly, we focused on the challenge of improving DBP prediction accuracy with information solely from the sequence. Secondly, we used multiple informative features to encode the protein. These features included evolutionary conservation profile, secondary structure motifs, and physicochemical properties. Thirdly, we introduced a novel improved Binary Firefly Algorithm (BFA) to remove redundant or noisy features as well as select optimal parameters for the classifier. The experimental results of our predictor on two benchmark datasets outperformed many state-of-the-art predictors, which revealed the effectiveness of our method. The promising prediction performance on a new-compiled independent testing dataset from PDB and a large-scale dataset from UniProt proved the good generalization ability of our method. In addition, the BFA forged in this research would be of great potential in practical applications in optimization fields, especially in feature selection problems.

Conclusions

A highly accurate method was proposed for the identification of DBPs. A user-friendly web-server named iDbP (identification of DNA-binding Proteins) was constructed and provided for academic use.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1201-8) contains supplementary material, which is available to authorized users.

A unique stylopod patterning mechanism by Shox2-controlled osteogenesis

Vertebrate appendage patterning is programmed by Hox-TALE factor-bound regulatory elements. However, it remains unclear which cell lineages are commissioned by Hox-TALE factors to generate regional specific patterns and whether other Hox-TALE co-factors exist. In this study, we investigated the transcriptional mechanisms controlled by the Shox2 transcriptional regulator in limb patterning. Harnessing an osteogenic lineage-specific Shox2 inactivation approach we show that despite widespread Shox2 expression in multiple cell lineages, lack of the stylopod observed upon Shox2 deficiency is a specific result of Shox2 loss of function in the osteogenic lineage. ChIP-Seq revealed robust interaction of Shox2 with cis-regulatory enhancers clustering around skeletogenic genes that are also bound by Hox-TALE factors, supporting a lineage autonomous function of Shox2 in osteogenic lineage fate determination and skeleton patterning. Pbx ChIP-Seq further allowed the genome-wide identification of cis-regulatory modules exhibiting co-occupancy of Pbx, Meis and Shox2 transcriptional regulators. Integrative analysis of ChIP-Seq and RNA-Seq data and transgenic enhancer assays indicate that Shox2 patterns the stylopod as a repressor via interaction with enhancers active in the proximal limb mesenchyme and antagonizes the repressive function of TALE factors in osteogenesis.

A Robust Analytical Pipeline for Genome-Wide Identification of the Genes Regulated by a Transcription Factor: Combinatorial Analysis Performed Using gSELEX-Seq and RNA-Seq

For identifying the genes that are regulated by a transcription factor (TF), we have established an analytical pipeline that combines genomic systematic evolution of ligands by exponential enrichment (gSELEX)-Seq and RNA-Seq. Here, SELEX was used to select DNA fragments from an Aspergillus nidulans genomic library that bound specifically to AmyR, a TF from A. nidulans. High-throughput sequencing data were obtained for the DNAs enriched through the selection, following which various in silico analyses were performed. Mapping reads to the genome revealed the binding motifs including the canonical AmyR-binding motif, CGGN8CGG, as well as the candidate promoters controlled by AmyR. In parallel, differentially expressed genes related to AmyR were identified by using RNA-Seq analysis with samples from A. nidulans WT and amyR deletant. By obtaining the intersecting set of genes detected using both gSELEX-Seq and RNA-Seq, the genes directly regulated by AmyR in A. nidulans can be identified with high reliability. This analytical pipeline is a robust platform for comprehensive genome-wide identification of the genes that are regulated by a target TF.

Dry and wet approaches for genome-wide functional annotation of conventional and unconventional transcriptional activators

Transcription factors (TFs) are master gene products that regulate gene expression in response to a variety of stimuli. They interact with DNA in a sequence-specific manner using a variety of DNA-binding domain (DBD) modules. This allows to properly position their second domain, called "effector domain", to directly or indirectly recruit positively or negatively acting co-regulators including chromatin modifiers, thus modulating preinitiation complex formation as well as transcription elongation. At variance with the DBDs, which are comprised of well-defined and easily recognizable DNA binding motifs, effector domains are usually much less conserved and thus considerably more difficult to predict. Also not so easy to identify are the DNA-binding sites of TFs, especially on a genome-wide basis and in the case of overlapping binding regions. Another emerging issue, with many potential regulatory implications, is that of so-called "moonlighting" transcription factors, i.e., proteins with an annotated function unrelated to transcription and lacking any recognizable DBD or effector domain, that play a role in gene regulation as their second job. Starting from bioinformatic and experimental high-throughput tools for an unbiased, genome-wide identification and functional characterization of TFs (especially transcriptional activators), we describe both established (and usually well affordable) as well as newly developed platforms for DNA-binding site identification. Selected combinations of these search tools, some of which rely on next-generation sequencing approaches, allow delineating the entire repertoire of TFs and unconventional regulators encoded by the any sequenced genome.

Every transcription factor deserves its map: Scaling up epitope tagging of proteins to bypass antibody problems

Genome-wide identification of transcription factor binding sites with the ChIP-seq method is an extremely important scientific endeavor - one that should ideally be performed for every transcription factor in as many cell types as possible. A major hurdle on the way to this goal is the necessity for a specific, ChIP-grade antibody for each transcription factor of interest, which is often not available. Here, we describe CETCh-seq, a recently published method utilizing genome engineering with the CRISPR/Cas9 system to circumvent the need for a specific antibody. Using the CETCh-seq method, targeted genomic editing results in an epitope-tagged transcription factor, which is recognized by a well-characterized, standard antibody, efficacious for ChIP-seq. We have used CETCh-seq in human cancer cell lines as well as mouse embryonic stem cells. We find that roughly 60% of transcription factors tagged using CETCh-seq produce a high quality ChIP-seq map, a significant improvement over traditional antibody-based methods.

Heterogeneity of transcription factor binding specificity models within and across cell lines

Complex gene expression patterns are mediated by the binding of transcription factors (TFs) to specific genomic loci. The in vivo occupancy of a TF is, in large part, determined by the TF's DNA binding interaction partners, motivating genomic context-based models of TF occupancy. However, approaches thus far have assumed a uniform TF binding model to explain genome-wide cell-type–specific binding sites. Therefore, the cell type heterogeneity of TF occupancy models, as well as the extent to which binding rules underlying a TF's occupancy are shared across cell types, has not been investigated. Here, we develop an ensemble-based approach (TRISECT) to identify the heterogeneous binding rules for cell-type–specific TF occupancy and analyze the inter-cell-type sharing of such rules. Comprehensive analysis of 23 TFs, each with ChIP-seq data in four to 12 different cell types, shows that by explicitly capturing the heterogeneity of binding rules, TRISECT accurately identifies in vivo TF occupancy. Importantly, many of the binding rules derived from individual cell types are shared across cell types and reveal distinct yet functionally coherent putative target genes in different cell types. Closer inspection of the predicted cell-type–specific interaction partners provides insights into the context-specific functional landscape of a TF. Together, our novel ensemble-based approach reveals, for the first time, a widespread heterogeneity of binding rules, comprising the interaction partners within a cell type, many of which nevertheless transcend cell types. Notably, the putative targets of shared binding rules in different cell types, while distinct, exhibit significant functional coherence.

The in vitro selection world

Through iterative cycles of selection, amplification, and mutagenesis, in vitro selection provides the ability to isolate molecules of desired properties and function from large pools (libraries) of random molecules with as many as 10(16) distinct species. This review, in recognition of a quarter of century of scientific discoveries made through in vitro selection, starts with a brief overview of the method and its history. It further covers recent developments in in vitro selection with a focus on tools that enhance the capabilities of in vitro selection and its expansion from being purely a nucleic acids selection to that of polypeptides and proteins. In addition, we cover how next generation sequencing and modern biological computational tools are being used to complement in vitro selection experiments. On the very least, sequencing and computational tools can translate the large volume of information associated with in vitro selection experiments to manageable, analyzable, and exploitable information. Finally, in vivo selection is briefly compared and contrasted to in vitro selection to highlight the unique capabilities of each method.

Regulation of Silk Genes by Hox and Homeodomain Proteins in the Terminal Differentiated Silk Gland of the Silkworm Bombyx mori

The silk gland of the silkworm Bombyx mori is a long tubular organ that is divided into several subparts along its anteroposterior (AP) axis. As a trait of terminal differentiation of the silk gland, several silk protein genes are expressed with unique regional specificities. Most of the Hox and some of the homeobox genes are also expressed in the differentiated silk gland with regional specificities. The expression patterns of Hox genes in the silk gland roughly correspond to those in embryogenesis showing "colinearity". The central Hox class protein Antennapedia (Antp) directly regulates the expression of several middle silk gland-specific silk genes, whereas the Lin-1/Isl-1/Mec3 (LIM)-homeodomain transcriptional factor Arrowhead (Awh) regulates the expression of posterior silk gland-specific genes for silk fiber proteins. We summarize our results and discuss the usefulness of the silk gland of Bombyx mori for analyzing the function of Hox genes. Further analyses of the regulatory mechanisms underlying the region-specific expression of silk genes will provide novel insights into the molecular bases for target-gene selection and regulation by Hox and homeodomain proteins.

How motif environment influences transcription factor search dynamics: Finding a needle in a haystack

Transcription factors (TFs) have to find their binding sites, which are distributed throughout the genome. Facilitated diffusion is currently the most widely accepted model for this search process. Based on this model the TF alternates between one-dimensional sliding along the DNA, and three-dimensional bulk diffusion. In this view, the non-specific associations between the proteins and the DNA play a major role in the search dynamics. However, little is known about how the DNA properties around the motif contribute to the search. Accumulating evidence showing that TF binding sites are embedded within a unique environment, specific to each TF, leads to the hypothesis that the search process is facilitated by favorable DNA features that help to improve the search efficiency. Here, we review the field and present the hypothesis that TF-DNA recognition is dictated not only by the motif, but is also influenced by the environment in which the motif resides.

Mechanisms of Specificity for Hox Factor Activity

Metazoans encode clusters of paralogous Hox genes that are critical for proper development of the body plan. However, there are a number of unresolved issues regarding how paralogous Hox factors achieve specificity to control distinct cell fates. First, how do Hox paralogs, which have very similar DNA binding preferences in vitro, drive different transcriptional programs in vivo? Second, the number of potential Hox binding sites within the genome is vast compared to the number of sites bound. Hence, what determines where in the genome Hox factors bind? Third, what determines whether a Hox factor will activate or repress a specific target gene? Here, we review the current evidence that is beginning to shed light onto these questions. In particular, we highlight how cooperative interactions with other transcription factors (especially PBC and HMP proteins) and the sequences of cis-regulatory modules provide a basis for the mechanisms of Hox specificity. We conclude by integrating a number of the concepts described throughout the review in a case study of a highly interrogated Drosophila cis-regulatory module named “The Distal-less Conserved Regulatory Element” (DCRE).

Quantification of Cooperativity in Heterodimer-DNA Binding Improves the Accuracy of Binding Specificity Models

Many transcription factors (TFs) have the ability to cooperate on DNA elements as heterodimers. Despite the significance of TF heterodimerization for gene regulation, a quantitative understanding of cooperativity between various TF dimer partners and its impact on heterodimer DNA binding specificity models is still lacking. Here, we used a novel integrative approach, combining microfluidics-steered measurements of dimer-DNA assembly with mechanistic modeling of the implicated protein-protein-DNA interactions to quantitatively interrogate the cooperative DNA binding behavior of the adipogenic peroxisome proliferator-activated receptor γ (PPARγ):retinoid X receptor α (RXRα) heterodimer. Using the high throughput MITOMI (mechanically induced trapping of molecular interactions) platform, we derived equilibrium DNA binding data for PPARγ, RXRα, as well as the PPARγ:RXRα heterodimer to more than 300 target DNA sites and variants thereof. We then quantified cooperativity underlying heterodimer-DNA binding and derived an integrative heterodimer DNA binding constant. Using this cooperativity-inclusive constant, we were able to build a heterodimer-DNA binding specificity model that has superior predictive power than the one based on a regular one-site equilibrium. Our data further revealed that individual nucleotide substitutions within the target site affect the extent of cooperativity in PPARγ:RXRα-DNA binding. Our study therefore emphasizes the importance of assessing cooperativity when generating DNA binding specificity models for heterodimers.

Aptamer-nanoparticle complexes as powerful diagnostic and therapeutic tools

Correct diagnosis and successful therapy are extremely important to enjoy a healthy life when suffering from a disease. To achieve these aims, various cutting-edge technologies have been designed and fabricated to diagnose and treat specific diseases. Among these technologies, aptamer-nanomaterial hybrids have received considerable attention from scientists and doctors because they have numerous advantages over other methods, such as good biocompatibility, low immunogenicity and controllable selectivity. In particular, aptamers, oligonucleic acids or peptides that bind to a specific target molecule, are regarded as outstanding biomolecules. In this review, several screening techniques for aptamers, also called systematic evolution of ligands by exponential enrichment (SELEX) methods, are introduced, and diagnostic and therapeutic aptamer applications are also presented. Furthermore, we describe diverse aptamer-nanomaterial conjugate designs and their applications for diagnosis and therapy.

Identification of plant transcription factor target sequences

Regulation of gene expression depends on specific cis-regulatory sequences located in the gene promoter regions. These DNA sequences are recognized by transcription factors (TFs) in a sequence-specific manner, and their identification could help to elucidate the regulatory networks that underlie plant physiological responses to developmental programs or to environmental adaptation. Here we review recent advances in high throughput methodologies for the identification of plant TF binding sites. Several approaches offer a map of the TF binding locations in vivo and of the dynamics of the gene regulatory networks. As an alternative, high throughput in vitro methods provide comprehensive determination of the DNA sequences recognized by TFs. These advances are helping to decipher the regulatory lexicon and to elucidate transcriptional network hierarchies in plants in response to internal or external cues. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.