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

The Human Transcription Factors

Transcription factors (TFs) recognize specific DNA sequences to control chromatin and transcription, forming a complex system that guides expression of the genome. Despite keen interest in understanding how TFs control gene expression, it remains challenging to determine how the precise genomic binding sites of TFs are specified and how TF binding ultimately relates to regulation of transcription. This review considers how TFs are identified and functionally characterized, principally through the lens of a catalog of over 1,600 likely human TFs and binding motifs for two-thirds of them. Major classes of human TFs differ markedly in their evolutionary trajectories and expression patterns, underscoring distinct functions. TFs likewise underlie many different aspects of human physiology, disease, and variation, highlighting the importance of continued effort to understand TF-mediated gene regulation.

The forkhead-box family of transcription factors: key molecular players in colorectal cancer pathogenesis

Colorectal cancer (CRC) is the third most commonly occurring cancer worldwide and the fourth most frequent cause of death having an oncological origin. It has been found that transcription factors (TF) dysregulation, leading to the significant expression modifications of genes, is a widely distributed phenomenon regarding human malignant neoplasias. These changes are key determinants regarding tumour’s behaviour as they contribute to cell differentiation/proliferation, migration and metastasis, as well as resistance to chemotherapeutic agents. The forkhead box (FOX) transcription factor family consists of an evolutionarily conserved group of transcriptional regulators engaged in numerous functions during development and adult life. Their dysfunction has been associated with human diseases. Several FOX gene subgroup transcriptional disturbances, affecting numerous complex molecular cascades, have been linked to a wide range of cancer types highlighting their potential usefulness as molecular biomarkers. At least 14 FOX subgroups have been related to CRC pathogenesis, thereby underlining their role for diagnosis, prognosis and treatment purposes.

This manuscript aims to provide, for the first time, a comprehensive review of FOX genes’ roles during CRC pathogenesis. The molecular and functional characteristics of most relevant FOX molecules (FOXO, FOXM1, FOXP3) have been described within the context of CRC biology, including their usefulness regarding diagnosis and prognosis. Potential CRC therapeutics (including genome-editing approaches) involving FOX regulation have also been included. Taken together, the information provided here should enable a better understanding of FOX genes’ function in CRC pathogenesis for basic science researchers and clinicians.

AptaTRACE Elucidates RNA Sequence-Structure Motifs from Selection Trends in HT-SELEX Experiments

Aptamers, short RNA or DNA molecules that bind distinct targets with high affinity and specificity, can be identified using high-throughput systematic evolution of ligands by exponential enrichment (HT-SELEX), but scalable analytic tools for understanding sequence-function relationships from diverse HT-SELEX data are not available. Here we present AptaTRACE, a computational approach that leverages the experimental design of the HT-SELEX protocol, RNA secondary structure, and the potential presence of many secondary motifs to identify sequence-structure motifs that show a signature of selection. We apply AptaTRACE to identify nine motifs in C-C chemokine receptor type 7 targeted by aptamers in an in vitro cell-SELEX experiment. We experimentally validate two aptamers whose binding required both sequence and structural features. AptaTRACE can identify low-abundance motifs, and we show through simulations that, because of this, it could lower HT-SELEX cost and time by reducing the number of selection cycles required.

PISTILLATA paralogs in Tarenaya hassleriana have diverged in interaction specificity

BACKGROUND

Floral organs are specified by MADS-domain transcription factors that act in a combinatorial manner, as summarized in the (A)BCE model. However, this evolutionarily conserved model is in contrast to a remarkable amount of morphological diversity in flowers. One of the mechanisms suggested to contribute to this diversity is duplication of floral MADS-domain transcription factors. Although gene duplication is often followed by loss of one of the copies, sometimes both copies are retained. If both copies are retained they will initially be redundant, providing freedom for one of the paralogs to change function. Here, we examine the evolutionary fate and functional consequences of a transposition event at the base of the Brassicales that resulted in the duplication of the floral regulator PISTILLATA (PI), using Tarenaya hassleriana (Cleomaceae) as a model system.

RESULTS

The transposition of a genomic region containing a PI gene led to two paralogs which are located at different positions in the genome. The original PI copy is syntenic in position with most angiosperms, whereas the transposed copy is syntenic with the PI genes in Brassicaceae. The two PI paralogs of T. hassleriana have very similar expression patterns. However, they may have diverged in function, as only one of these PI proteins was able to act heterologously in the first whorl of A. thaliana flowers. We also observed differences in protein complex formation between the two paralogs, and the two paralogs exhibit subtle differences in DNA-binding specificity. Sequence analysis indicates that most of the protein sequence divergence between the two T. hassleriana paralogs emerged in a common ancestor of the Cleomaceae and the Brassicaceae.

CONCLUSIONS

We found that the PI paralogs in T. hassleriana have similar expression patterns, but may have diverged at the level of protein function. Data suggest that most protein sequence divergence occurred rapidly, prior to the origin of the Brassicaceae and Cleomaceae. It is tempting to speculate that the interaction specificities of the Brassicaceae-specific PI proteins are different compared to the PI found in other angiosperms. This could lead to PI regulating partly different genes in the Brassicaceae, and ultimately might result in change floral in morphology.

Flexibility and structure of flanking DNA impact transcription factor affinity for its core motif

Spatial and temporal expression of genes is essential for maintaining phenotype integrity. Transcription factors (TFs) modulate expression patterns by binding to specific DNA sequences in the genome. Along with the core binding motif, the flanking sequence context can play a role in DNA-TF recognition. Here, we employ high-throughput in vitro and in silico analyses to understand the influence of sequences flanking the cognate sites in binding of three most prevalent eukaryotic TF families (zinc finger, homeodomain and bZIP). In vitro binding preferences of each TF toward the entire DNA sequence space were correlated with a wide range of DNA structural parameters, including DNA flexibility. Results demonstrate that conformational plasticity of flanking regions modulates binding affinity of certain TF families. DNA duplex stability and minor groove width also play an important role in DNA-TF recognition but differ in how exactly they influence the binding in each specific case. Our analyses further reveal that the structural features of preferred flanking sequences are not universal, as similar DNA-binding folds can employ distinct DNA recognition modes.

Phenotypic Nonspecificity as the Result of Limited Specificity of Transcription Factor Function

Drosophila transcription factor (TF) function is phenotypically nonspecific. Phenotypic nonspecificity is defined as one phenotype being induced or rescued by multiple TFs. To explain this unexpected result, a hypothetical world of limited specificity is explored where all TFs have unique random distributions along the genome due to low information content of DNA sequence recognition and somewhat promiscuous cooperative interactions with other TFs. Transcription is an emergent property of these two conditions. From this model, explicit predictions are made. First, many more cases of TF nonspecificity are expected when examined. Second, the genetic analysis of regulatory sequences should uncover cis-element bypass and, third, genetic analysis of TF function should generally uncover differential pleiotropy. In addition, limited specificity provides evolutionary opportunity and explains the inefficiency of expression analysis in identifying genes required for biological processes.

Direct Single-Molecule Observation of Sequential DNA Bending Transitions by the Sox2 HMG Box

Sox2 is a pioneer transcription factor that initiates cell fate reprogramming through locus-specific differential regulation. Mechanistically, it was assumed that Sox2 achieves its regulatory diversity via heterodimerization with partner transcription factors. Here, utilizing single-molecule fluorescence spectroscopy, we show that Sox2 alone can modulate DNA structural landscape in a dosage-dependent manner. We propose that such stoichiometric tuning of regulatory DNAs is crucial to the diverse biological functions of Sox2, and represents a generic mechanism of conferring functional plasticity and multiplicity to transcription factors.

The cis-regulatory logic underlying abdominal Hox-mediated repression versus activation of regulatory elements in Drosophila

During development diverse transcription factor inputs are integrated by cis-regulatory modules (CRMs) to yield cell-specific gene expression. Defining how CRMs recruit the appropriate combinations of factors to either activate or repress gene expression remains a challenge. In this study, we compare and contrast the ability of two CRMs within the Drosophila embryo to recruit functional Hox transcription factor complexes. The DCRE CRM recruits Ultrabithorax (Ubx) and Abdominal-A (Abd-A) Hox complexes that include the Extradenticle (Exd) and Homothorax (Hth) transcription factors to repress the Distal-less leg selector gene, whereas the RhoA CRM selectively recruits Abd-A/Exd/Hth complexes to activate rhomboid and stimulate Epidermal Growth Factor secretion in sensory cell precursors. By swapping binding sites between these elements, we found that the RhoA Exd/Hth/Hox site configuration that mediates Abd-A specific activation can convey transcriptional repression by both Ubx and Abd-A when placed into the DCRE. We further show that the orientation and spacing of Hox sites relative to additional binding sites within the RhoA and DCRE is critical to mediate cell- and segment-specific output. These results indicate that the configuration of Exd, Hth, and Hox site within RhoA is neither Abd-A specific nor activation specific. Instead Hox specific output is largely dependent upon the presence of appropriately spaced and oriented binding sites for additional TF inputs. Taken together, these studies provide insight into the cis-regulatory logic used to generate cell-specific outputs via recruiting Hox transcription factor complexes.

An axial Hox code controls tissue segmentation and body patterning in Nematostella vectensis

Hox genes encode conserved developmental transcription factors that govern anterior-posterior (A-P) pattering in diverse bilaterian animals, which display bilateral symmetry. Although Hox genes are also present within Cnidaria, these simple animals lack a definitive A-P axis, leaving it unclear how and when a functionally integrated Hox code arose during evolution. We used short hairpin RNA (shRNA)-mediated knockdown and CRISPR-Cas9 mutagenesis to demonstrate that a Hox-Gbx network controls radial segmentation of the larval endoderm during development of the sea anemone Nematostella vectensis. Loss of Hox-Gbx activity also elicits marked defects in tentacle patterning along the directive (orthogonal) axis of primary polyps. On the basis of our results, we propose that an axial Hox code may have controlled body patterning and tissue segmentation before the evolution of the bilaterian A-P axis.

Specificity landscapes unmask submaximal binding site preferences of transcription factors

We have developed Differential Specificity and Energy Landscape (DiSEL) analysis to comprehensively compare DNA-protein interactomes (DPIs) obtained by high-throughput experimental platforms and cutting edge computational methods. While high-affinity DNA binding sites are identified by most methods, DiSEL uncovered nuanced sequence preferences displayed by homologous transcription factors. Pairwise analysis of 726 DPIs uncovered homolog-specific differences at moderate- to low-affinity binding sites (submaximal sites). DiSEL analysis of variants of 41 transcription factors revealed that many disease-causing mutations result in allele-specific changes in binding site preferences. We focused on a set of highly homologous factors that have different biological roles but "read" DNA using identical amino acid side chains. Rather than direct readout, our results indicate that DNA noncontacting side chains allosterically contribute to sculpt distinct sequence preferences among closely related members of transcription factor families.

Identification of a functional antioxidant response element at the HIF1A locus

Reactive oxygen species (ROS), which are a byproduct of oxidative metabolism, serve as signaling molecules in a number of physiological settings. However, if their levels are not tightly maintained, excess ROS lead to potentially cytotoxic oxidative stress. Accordingly, several transcriptional regulatory networks have evolved to include components that are highly ROS-responsive. Depending on the context, these regulatory networks can leverage ROS to respond to nutrient conditions, metabolism, or other physiological signals, or to respond to oxidative stress. However, ROS signaling is complex, so regulatory interactions between various ROS-responsive transcription factors are still being mapped out. Here we show that the transcription factor NRF2, a key regulator of the adaptive response to oxidative stress, directly regulates expression of HIF1A, which encodes HIF1α, a key transcriptional regulator of the adaptive response to hypoxia. We used an integrative genomics approach to identify HIF1A as a ROS-responsive transcript and we found an NRF2-bound antioxidant response element (ARE) approximately 30 kilobases upstream of HIF1A. This ARE sequence is deeply conserved, and we verified that it is directly bound and activated by NRF2. In addition, we found that HIF1A is upregulated in breast and bladder tumors with high NRF2 activity. Taken together, our results demonstrate that NRF2 targets a functional ARE at the HIF1A locus, and reveal a direct regulatory connection between two important oxygen responsive transcription factors.

Multiple inputs into a posterior-specific regulatory network in the Ciona notochord

The gene regulatory networks underlying Ciona notochord fate specification and differentiation have been extensively investigated, but the regulatory basis for regionalized expression within the notochord is not understood. Here we identify three notochord-expressed genes, C11.331, C12.115 and C8.891, with strongly enriched expression in the secondary notochord cells at the posterior tip of the tail. C11.331 and C12.115 share a distinctive expression pattern that is highly enriched in the secondary notochord lineage but also graded within that lineage with the strongest expression at the posterior tip. Both genes show similar responses to pharmacological perturbations of Wnt and FGF signaling, consistent with an important role for Wnt and FGF ligands expressed at the tail tip. Reporter analysis indicates that the C11.331 cis-regulatory regions are extensively distributed, with multiple non-overlapping regions conferring posterior notochord-enriched expression. Fine-scale analysis of a minimal cis-regulatory module identifies discrete positive and negative elements including a strong silencer. Truncation of the silencer region leads to increased expression in the primary notochord, indicating that C11.331 expression is influenced by putative regulators of primary versus secondary notochord fate. The minimal CRM contains predicted ETS, GATA, LMX and Myb sites, all of which lead to reduced expression in secondary notochord when mutated. These results show that the posterior-enriched notochord expression of C11.331 depends on multiple inputs, including Wnt and FGF signals from the tip of the tail, multiple notochord-specific regulators, and yet-to-be identified regulators of regional identity within the notochord.

Effects of depth on reef fish communities: Insights of a "deep refuge hypothesis" from Southwestern Atlantic reefs

Deeper reefs are often considered to be less susceptible to local and global disturbances, such as overfishing, pollution and climate change, compared to shallow reefs and therefore could act as refugia for shallow water species. Hence, the interest on deeper reefs has happened at a time when shallow reefs are undergoing unprecedented changes. Here we investigated the hypothesis that fish community differed from shallow to deeper reefs due to factors apart from habitat structure and quality and therefore discuss for the first-time insights of a “deep refuge hypothesis” from Brazilian reefs. We collected data on fish community, benthic community and physiological conditions of two coral species on shallow (< 6 m) and deep reefs (> 25 m). No significant difference on substratum composition was observed comparing sites and depths. Additionally, physiological data on corals also showed similar oxidative status and growth conditions when comparing the two-coral species in shallow and deep reefs. Conversely, our study demonstrated strong differences on reef fish communities in terms of abundance, species richness, trophic groups, size classes and groups of interest when comparing shallow and deeper reefs. Fish abundance was 2-fold higher and species richness was up to 70% higher on deeper reefs. Also, a significant difference was observed comparing trophic groups of reef fish. Macrocarnivore, Mobile invertebrate feeders, Planktivores, Sessile Invertebrates Feeders and Roving Herbivores were more abundant on deeper reefs. On the other hand, Territorialist Herbivores almost exclusively dominated shallow reefs. Strong differences were also observed comparing the abundance of reef fish groups of interest and their respective size classes between shallow and deeper reefs. Ornamental, Great Herbivores and Groupers showed clear differences, with higher abundances being observed in deeper reefs. Considering size classes, larger individuals (> 15 cm) of Great Herbivores, Groupers and Snapper were uniquely recorded at deeper reefs. Additionally, individuals with > 30 cm were recorded almost exclusively on deeper reefs for all the analyzed groups of interest. Our findings suggest that fishing pressure on the target species may be attenuated on deeper reefs, and these regions may therefore be considered as areas of refuge from shallow water impacts. Therefore, the likely potential for deeper reefs protect species from natural or anthropogenic disturbances increases the attention of marine conservation planning and resource management on including deeper reefs in protected areas.

The Generic Facet of Hox Protein Function

Hox transcription factors are essential to promote morphological diversification of the animal body. A substantial number of studies have focused on how Hox proteins reach functional specificity, an issue that arises from the fact that these transcription factors control distinct developmental functions despite sharing similar molecular properties. In this review, we highlight that, besides specific functions, for which these transcription factors are renowned, Hox proteins also often have nonspecific functions. We next discuss some emerging principles of these generic functions and how they relate to specific functions and explore our current grasp of the underlying molecular mechanisms.

Using controls to limit false discovery in the era of big data

Background

Procedures for controlling the false discovery rate (FDR) are widely applied as a solution to the multiple comparisons problem of high-dimensional statistics. Current FDR-controlling procedures require accurately calculated p-values and rely on extrapolation into the unknown and unobserved tails of the null distribution. Both of these intermediate steps are challenging and can compromise the reliability of the results.

Results

We present a general method for controlling the FDR that capitalizes on the large amount of control data often found in big data studies to avoid these frequently problematic intermediate steps. The method utilizes control data to empirically construct the distribution of the test statistic under the null hypothesis and directly compares this distribution to the empirical distribution of the test data. By not relying on p-values, our control data-based empirical FDR procedure more closely follows the foundational principles of the scientific method: that inference is drawn by comparing test data to control data. The method is demonstrated through application to a problem in structural genomics.

Conclusions

The method described here provides a general statistical framework for controlling the FDR that is specifically tailored for the big data setting. By relying on empirically constructed distributions and control data, it forgoes potentially problematic modeling steps and extrapolation into the unknown tails of the null distribution. This procedure is broadly applicable insofar as controlled experiments or internal negative controls are available, as is increasingly common in the big data setting.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2356-2) contains supplementary material, which is available to authorized users.

Allosterism and signal transfer in DNA

We analysed the basic mechanisms of signal transmission in DNA and the origins of the allostery exhibited by systems such as the ternary complex BAMHI-DNA-GRDBD. We found that perturbation information generated by a primary protein binding event travels as a wave to distant regions of DNA following a hopping mechanism. However, such a structural perturbation is transient and does not lead to permanent changes in the DNA geometry and interaction properties at the secondary binding site. The BAMHI-DNA-GRDBD allosteric mechanism does not occur through any traditional models: direct (protein-protein), indirect (reorganization of the secondary site) readout or solvent-release. On the contrary, it is generated by a subtle and less common entropy-mediated mechanism, which might have an important role to explain other DNA-mediated cooperative effects.

Diversification of transcription factor-DNA interactions and the evolution of gene regulatory networks

Sequence-specific transcription factors (TFs) bind short DNA sequences in the genome to regulate the expression of target genes. In the last decade, numerous technical advances have enabled the determination of the DNA-binding specificities of many of these factors. Large-scale screens of many TFs enabled the creation of databases of TF DNA-binding specificities, typically represented as position weight matrices (PWMs). Although great progress has been made in determining and predicting binding specificities systematically, there are still many surprises to be found when studying a particular TF's interactions with DNA in detail. Paralogous TFs' binding specificities can differ in subtle ways, in a manner that is not immediately apparent from looking at their PWMs. These differences affect gene regulatory outputs and enable TFs to rewire transcriptional networks over evolutionary time. This review discusses recent observations made in the study of TF-DNA interactions that highlight the importance of continued in-depth analysis of TF-DNA interactions and their inherent complexity. This article is categorized under: Biological Mechanisms > Regulatory Biology.

Developmentally regulated autophagy is required for eye formation in Drosophila

The compound eye of the fruit fly Drosophila melanogaster is one of the most intensively studied and best understood model organs in the field of developmental genetics. Herein we demonstrate that autophagy, an evolutionarily conserved selfdegradation process of eukaryotic cells, is essential for eye development in this organism. Autophagic structures accumulate in a specific pattern in the developing eye disc, predominantly in the morphogenetic furrow (MF) and differentiation zone. Silencing of several autophagy genes (Atg) in the eye primordium severely affects the morphology of the adult eye through triggering ectopic cell death. In Atg mutant genetic backgrounds however genetic compensatory mechanisms largely rescue autophagic activity in, and thereby normal morphogenesis of, this organ. We also show that in the eye disc the expression of a key autophagy gene, Atg8a, is controlled in a complex manner by the anterior Hox paralog Lab (Labial), a master regulator of early development. Atg8a transcription is repressed in front of, while activated along, the MF by Lab. The amount of autophagic structures then remains elevated behind the moving MF. These results indicate that eye development in Drosophila depends on the cell death-suppressing and differentiating effects of the autophagic process. This novel, developmentally regulated function of autophagy in the morphogenesis of the compound eye may shed light on a more fundamental role for cellular self-digestion in differentiation and organ formation than previously thought.

ABBREVIATIONS

αTub84B, α-Tubulin at 84B; Act5C, Actin5C; AO, acridine orange; Atg, autophagy-related; Ato, Atonal; CASP3, caspase 3; Dcr-2; Dicer-2; Dfd, Deformed; DZ, differentiation zone; eGFP, enhanced green fluorescent protein; EM, electron microscopy; exd, extradenticle; ey, eyeless; FLP, flippase recombinase; FRT, FLP recognition target; Gal4, gene encoding the yeast transcription activator protein GAL4; GFP, green fluorescent protein; GMR, Glass multimer reporter; Hox, homeobox; hth, homothorax; lab, labial; L3F, L3 feeding larval stage; L3W, L3 wandering larval stage; lf, loss-of-function; MAP1LC3, microtubule-associated protein 1 light chain 3; MF, morphogenetic furrow; PE, phosphatidylethanolamine; PBS, phosphate-buffered saline; PI3K/PtdIns3K, class III phosphatidylinositol 3-kinase; PZ, proliferation zone; Ref(2)P, refractory to sigma P, RFP, red fluorescent protein; RNAi, RNA interference; RpL32, Ribosomal protein L32; RT-PCR, reverse transcription-coupled polymerase chain reaction; S.D., standard deviation; SQSTM1, Sequestosome-1, Tor, Target of rapamycin; TUNEL, terminal deoxynucleotidyl transferase mediated dUTP nick end labeling assay; UAS, upstream activation sequence; qPCR, quantitative real-time polymerase chain reaction; w, white.

The floral homeotic protein SEPALLATA3 recognizes target DNA sequences by shape readout involving a conserved arginine residue in the MADS-domain

SEPALLATA3 of Arabidopsis thaliana is a MADS-domain transcription factor (TF) and a key regulator of flower development. MADS-domain proteins bind to sequences termed 'CArG-boxes' [consensus 5'-CC(A/T)₆ GG-3']. Because only a fraction of the CArG-boxes in the Arabidopsis genome are bound by SEPALLATA3, more elaborate principles have to be discovered to better understand which features turn CArG-boxes into genuine recognition sites. Here, we investigate to what extent the shape of the DNA is involved in a 'shape readout' that contributes to the binding of SEPALLATA3. We determined in vitro binding affinities of SEPALLATA3 to DNA probes that all contain the CArG-box motif, but differ in their predicted DNA shape. We found that binding affinity correlates well with a narrow minor groove of the DNA. Substitution of canonical bases with non-standard bases supports the hypothesis of minor groove shape readout by SEPALLATA3. Analysis of mutant SEPALLATA3 proteins further revealed that a highly conserved arginine residue, which is expected to contact the DNA minor groove, contributes significantly to the shape readout. Our studies show that the specific recognition of cis-regulatory elements by a plant MADS-domain TF, and by inference probably also of other TFs of this type, heavily depends on shape readout mechanisms.

The multisystemic functions of FOXD1 in development and disease

Transcription factors (TFs) participate in a wide range of cellular processes due to their inherent function as essential regulatory proteins. Their dysfunction has been linked to numerous human diseases. The forkhead box (FOX) family of TFs belongs to the "winged helix" superfamily, consisting of proteins sharing a related winged helix-turn-helix DNA-binding motif. FOX genes have been extensively present during vertebrates and invertebrates' evolution, participating in numerous molecular cascades and biological functions, such as embryonic development and organogenesis, cell cycle regulation, metabolism control, stem cell niche maintenance, signal transduction, and many others. FOXD1, a forkhead TF, has been related to different key biological processes such as kidney and retina development and embryo implantation. FOXD1 dysfunction has been linked to different pathologies, thereby constituting a diagnostic biomarker and a promising target for future therapies. This paper aims to present, for the first time, a comprehensive review of FOXD1's role in mouse development and human disease. Molecular, structural, and functional aspects of FOXD1 are presented in light of physiological and pathogenic conditions, including its role in human disease aetiology, such as cancer and recurrent pregnancy loss. Taken together, the information given here should enable a better understanding of FOXD1 function for basic science researchers and clinicians.

Changing MADS-Box Transcription Factor Protein-Protein Interactions as a Mechanism for Generating Floral Morphological Diversity

Flowers display fantastic morphological diversity. Despite extreme variability in form, floral organ identity is specified by a core set of deeply conserved proteins-the floral MADS-box transcription factors. This indicates that while core gene function has been maintained, MADS-box transcription factors have evolved to regulate different downstream genes. Thus, the evolution of gene regulation downstream of the MADS-box transcription factors is likely central to the evolution of floral form. Gene regulation is determined by the combination of transcriptional regulators present at a particular cis-regulatory element at a particular time. Therefore, the interactions between transcription factors can be of profound importance in determining patterns of gene regulation. Here, after a short primer on flowers and floral morphology, I discuss the centrality of protein-protein interactions to MADS-box transcription factor function, and review the evidence that the evolution of MADS-box protein-protein interactions is a key driver in the evolution of gene regulation downstream of the MADS-box genes.

Global pairwise RNA interaction landscapes reveal core features of protein recognition

RNA–protein interactions permeate biology. Transcription, translation, and splicing all hinge on the recognition of structured RNA elements by RNA-binding proteins. Models of RNA–protein interactions are generally limited to short linear motifs and structures because of the vast sequence sampling required to access longer elements. Here, we develop an integrated approach that calculates global pairwise interaction scores from in vitro selection and high-throughput sequencing. We examine four RNA-binding proteins of phage, viral, and human origin. Our approach reveals regulatory motifs, discriminates between regulated and non-regulated RNAs within their native genomic context, and correctly predicts the consequence of mutational events on binding activity. We design binding elements that improve binding activity in cells and infer mutational pathways that reveal permissive versus disruptive evolutionary trajectories between regulated motifs. These coupling landscapes are broadly applicable for the discovery and characterization of protein–RNA recognition at single nucleotide resolution.

RNA–protein interactions often depend on the recognition of extended RNA elements but the identification of these motifs is challenging. Here, the authors present a global integrated approach to analyze RNA–protein binding landscapes, mapping extended RNA interaction motifs for four RNA-binding proteins.

DNA sequence+shape kernel enables alignment-free modeling of transcription factor binding

Motivation

Transcription factors (TFs) bind to specific DNA sequence motifs. Several lines of evidence suggest that TF-DNA binding is mediated in part by properties of the local DNA shape: the width of the minor groove, the relative orientations of adjacent base pairs, etc. Several methods have been developed to jointly account for DNA sequence and shape properties in predicting TF binding affinity. However, a limitation of these methods is that they typically require a training set of aligned TF binding sites.

Results

We describe a sequence + shape kernel that leverages DNA sequence and shape information to better understand protein-DNA binding preference and affinity. This kernel extends an existing class of k-mer based sequence kernels, based on the recently described di-mismatch kernel. Using three in vitro benchmark datasets, derived from universal protein binding microarrays (uPBMs), genomic context PBMs (gcPBMs) and SELEX-seq data, we demonstrate that incorporating DNA shape information improves our ability to predict protein-DNA binding affinity. In particular, we observe that (i) the k-spectrum + shape model performs better than the classical k-spectrum kernel, particularly for small k values; (ii) the di-mismatch kernel performs better than the k-mer kernel, for larger k; and (iii) the di-mismatch + shape kernel performs better than the di-mismatch kernel for intermediate k values.

Availability and implementation

The software is available at https://bitbucket.org/wenxiu/sequence-shape.git.

Supplementary information

Supplementary data are available at Bioinformatics online.

A feed-forward relay integrates the regulatory activities of Bicoid and Orthodenticle via sequential binding to suboptimal sites

Datta et al. define three major classes of enhancers that are differentially sensitive to binding and transcriptional activation by Bicoid (Bcd) and Orthodenticle (Otd). The specific activities of enhancers in each class are mediated by DNA motif variants preferentially bound by Bcd or Otd and the presence or absence of sites for cofactors that interact with these proteins.

The K50 (lysine at amino acid position 50) homeodomain (HD) protein Orthodenticle (Otd) is critical for anterior patterning and brain and eye development in most metazoans. In Drosophila melanogaster, another K50HD protein, Bicoid (Bcd), has evolved to replace Otd's ancestral function in embryo patterning. Bcd is distributed as a long-range maternal gradient and activates transcription of a large number of target genes, including otd. Otd and Bcd bind similar DNA sequences in vitro, but how their transcriptional activities are integrated to pattern anterior regions of the embryo is unknown. Here we define three major classes of enhancers that are differentially sensitive to binding and transcriptional activation by Bcd and Otd. Class 1 enhancers are initially activated by Bcd, and activation is transferred to Otd via a feed-forward relay (FFR) that involves sequential binding of the two proteins to the same DNA motif. Class 2 enhancers are activated by Bcd and maintained by an Otd-independent mechanism. Class 3 enhancers are never bound by Bcd, but Otd binds and activates them in a second wave of zygotic transcription. The specific activities of enhancers in each class are mediated by DNA motif variants preferentially bound by Bcd or Otd and the presence or absence of sites for cofactors that interact with these proteins. Our results define specific patterning roles for Bcd and Otd and provide mechanisms for coordinating the precise timing of gene expression patterns during embryonic development.

True equilibrium measurement of transcription factor-DNA binding affinities using automated polarization microscopy

The complex patterns of gene expression in metazoans are controlled by selective binding of transcription factors (TFs) to regulatory DNA. To improve the quantitative understanding of this process, we have developed a novel method that uses fluorescence anisotropy measurements in a controlled delivery system to determine TF-DNA binding energies in solution with high sensitivity and throughput. Owing to its large dynamic range, the method, named high performance fluorescence anisotropy (HiP-FA), allows for reliable quantification of both weak and strong binding; binding specificities are calculated on the basis of equilibrium constant measurements for mutational DNA variants. We determine the binding preference landscapes for 26 TFs and measure high absolute affinities, but mostly lower binding specificities than reported by other methods. The revised binding preferences give rise to improved predictions of in vivo TF occupancy and enhancer expression. Our approach provides a powerful new tool for the systems-biological analysis of gene regulation.

Methods to measure selective transcription factor-DNA binding often lack sensitivity and are not performed in solution. Here the authors develop a method to perform fluorescence anisotropy measurements of transcription factor-DNA binding energies with high sensitivity and throughput.

Quantitative Analysis of the DNA Methylation Sensitivity of Transcription Factor Complexes

Although DNA modifications play an important role in gene regulation, the underlying mechanisms remain elusive. We developed EpiSELEX-seq to probe the sensitivity of transcription factor binding to DNA modification in vitro using massively parallel sequencing. Feature-based modeling quantifies the effect of cytosine methylation (⁵mC) on binding free energy in a position-specific manner. Application to the human bZIP proteins ATF4 and C/EBPβ and three different Pbx-Hox complexes shows that ⁵mCpG can both increase and decrease affinity, depending on where the modification occurs within the protein-DNA interface. The TF paralogs tested vary in their methylation sensitivity, for which we provide a structural rationale. We show that ⁵mCpG can also enhance in vitro p53 binding and provide evidence for increased in vivo p53 occupancy at methylated binding sites, correlating with primed enhancer histone marks. Our results establish a powerful strategy for dissecting the epigenomic modulation of protein-DNA interactions and their role in gene regulation.

Accurate and sensitive quantification of protein-DNA binding affinity

Transcription factors (TFs) control gene expression by binding to genomic DNA in a sequence-specific manner. Mutations in TF binding sites are increasingly found to be associated with human disease, yet we currently lack robust methods to predict these sites. Here, we developed a versatile maximum likelihood framework named No Read Left Behind (NRLB) that infers a biophysical model of protein-DNA recognition across the full affinity range from a library of in vitro selected DNA binding sites. NRLB predicts human Max homodimer binding in near-perfect agreement with existing low-throughput measurements. It can capture the specificity of the p53 tetramer and distinguish multiple binding modes within a single sample. Additionally, we confirm that newly identified low-affinity enhancer binding sites are functional in vivo, and that their contribution to gene expression matches their predicted affinity. Our results establish a powerful paradigm for identifying protein binding sites and interpreting gene regulatory sequences in eukaryotic genomes.

Divergence in DNA Specificity among Paralogous Transcription Factors Contributes to Their Differential In Vivo Binding

Paralogous transcription factors (TFs) are oftentimes reported to have identical DNA-binding motifs, despite the fact that they perform distinct regulatory functions. Differential genomic targeting by paralogous TFs is generally assumed to be due to interactions with protein co-factors or the chromatin environment. Using a computational-experimental framework called iMADS (integrative modeling and analysis of differential specificity), we show that, contrary to previous assumptions, paralogous TFs bind differently to genomic target sites even in vitro. We used iMADS to quantify, model, and analyze specificity differences between 11 TFs from 4 protein families. We found that paralogous TFs have diverged mainly at medium- and low-affinity sites, which are poorly captured by current motif models. We identify sequence and shape features differentially preferred by paralogous TFs, and we show that the intrinsic differences in specificity among paralogous TFs contribute to their differential in vivo binding. Thus, our study represents a step forward in deciphering the molecular mechanisms of differential specificity in TF families.

Comprehensive, high-resolution binding energy landscapes reveal context dependencies of transcription factor binding

Transcription factors (TFs) are primary regulators of gene expression in cells, where they bind specific genomic target sites to control transcription. Quantitative measurements of TF-DNA binding energies can improve the accuracy of predictions of TF occupancy and downstream gene expression in vivo and shed light on how transcriptional networks are rewired throughout evolution. Here, we present a sequencing-based TF binding assay and analysis pipeline (BET-seq, for Binding Energy Topography by sequencing) capable of providing quantitative estimates of binding energies for more than one million DNA sequences in parallel at high energetic resolution. Using this platform, we measured the binding energies associated with all possible combinations of 10 nucleotides flanking the known consensus DNA target interacting with two model yeast TFs, Pho4 and Cbf1. A large fraction of these flanking mutations change overall binding energies by an amount equal to or greater than consensus site mutations, suggesting that current definitions of TF binding sites may be too restrictive. By systematically comparing estimates of binding energies output by deep neural networks (NNs) and biophysical models trained on these data, we establish that dinucleotide (DN) specificities are sufficient to explain essentially all variance in observed binding behavior, with Cbf1 binding exhibiting significantly more nonadditivity than Pho4. NN-derived binding energies agree with orthogonal biochemical measurements and reveal that dynamically occupied sites in vivo are both energetically and mutationally distant from the highest affinity sites.

BEESEM: estimation of binding energy models using HT-SELEX data

Motivation

Characterizing the binding specificities of transcription factors (TFs) is crucial to the study of gene expression regulation. Recently developed high-throughput experimental methods, including protein binding microarrays (PBM) and high-throughput SELEX (HT-SELEX), have enabled rapid measurements of the specificities for hundreds of TFs. However, few studies have developed efficient algorithms for estimating binding motifs based on HT-SELEX data. Also the simple method of constructing a position weight matrix (PWM) by comparing the frequency of the preferred sequence with single-nucleotide variants has the risk of generating motifs with higher information content than the true binding specificity.

Results

We developed an algorithm called BEESEM that builds on a comprehensive biophysical model of protein-DNA interactions, which is trained using the expectation maximization method. BEESEM is capable of selecting the optimal motif length and calculating the confidence intervals of estimated parameters. By comparing BEESEM with the published motifs estimated using the same HT-SELEX data, we demonstrate that BEESEM provides significant improvements. We also evaluate several motif discovery algorithms on independent PBM and ChIP-seq data. BEESEM provides significantly better fits to in vitro data, but its performance is similar to some other methods on in vivo data under the criterion of the area under the receiver operating characteristic curve (AUROC). This highlights the limitations of the purely rank-based AUROC criterion. Using quantitative binding data to assess models, however, demonstrates that BEESEM improves on prior models.

Availability and Implementation

Freely available on the web at http://stormo.wustl.edu/resources.html .

Contact

stormo@wustl.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Relationship between histone modifications and transcription factor binding is protein family specific

The very small fraction of putative binding sites (BSs) that are occupied by transcription factors (TFs) in vivo can be highly variable across different cell types. This observation has been partly attributed to changes in chromatin accessibility and histone modification (HM) patterns surrounding BSs. Previous studies focusing on BSs within DNA regulatory regions found correlations between HM patterns and TF binding specificities. However, a mechanistic understanding of TF-DNA binding specificity determinants is still not available. The ability to predict in vivo TF binding on a genome-wide scale requires the identification of features that determine TF binding based on evolutionary relationships of DNA binding proteins. To reveal protein family-dependent mechanisms of TF binding, we conducted comprehensive comparisons of HM patterns surrounding BSs and non-BSs with exactly matched core motifs for TFs in three cell lines: 33 TFs in GM12878, 37 TFs in K562, and 18 TFs in H1-hESC. These TFs displayed protein family-specific preferences for HM patterns surrounding BSs, with high agreement among cell lines. Moreover, compared to models based on DNA sequence and shape at flanking regions of BSs, HM-augmented quantitative machine-learning methods resulted in increased performance in a TF family-specific manner. Analysis of the relative importance of features in these models indicated that TFs, displaying larger HM pattern differences between BSs and non-BSs, bound DNA in an HM-specific manner on a protein family-specific basis. We propose that TF family-specific HM preferences reveal distinct mechanisms that assist in guiding TFs to their cognate BSs by altering chromatin structure and accessibility.

A unified approach for quantifying and interpreting DNA shape readout by transcription factors

Transcription factors (TFs) interpret DNA sequence by probing the chemical and structural properties of the nucleotide polymer. DNA shape is thought to enable a parsimonious representation of dependencies between nucleotide positions. Here, we propose a unified mathematical representation of the DNA sequence dependence of shape and TF binding, respectively, which simplifies and enhances analysis of shape readout. First, we demonstrate that linear models based on mononucleotide features alone account for 60-70% of the variance in minor groove width, roll, helix twist, and propeller twist. This explains why simple scoring matrices that ignore all dependencies between nucleotide positions can partially account for DNA shape readout by a TF Adding dinucleotide features as sequence-to-shape predictors to our model, we can almost perfectly explain the shape parameters. Building on this observation, we developed a post hoc analysis method that can be used to analyze any mechanism-agnostic protein-DNA binding model in terms of shape readout. Our insights provide an alternative strategy for using DNA shape information to enhance our understanding of how cis-regulatory codes are interpreted by the cellular machinery.

Systematic prediction of DNA shape changes due to CpG methylation explains epigenetic effects on protein-DNA binding

BACKGROUND

DNA shape analysis has demonstrated the potential to reveal structure-based mechanisms of protein-DNA binding. However, information about the influence of chemical modification of DNA is limited. Cytosine methylation, the most frequent modification, represents the addition of a methyl group at the major groove edge of the cytosine base. In mammalian genomes, cytosine methylation most frequently occurs at CpG dinucleotides. In addition to changing the chemical signature of C/G base pairs, cytosine methylation can affect DNA structure. Since the original discovery of DNA methylation, major efforts have been made to understand its effect from a sequence perspective. Compared to unmethylated DNA, however, little structural information is available for methylated DNA, due to the limited number of experimentally determined structures. To achieve a better mechanistic understanding of the effect of CpG methylation on local DNA structure, we developed a high-throughput method, methyl-DNAshape, for predicting the effect of cytosine methylation on DNA shape.

RESULTS

Using our new method, we found that CpG methylation significantly altered local DNA shape. Four DNA shape features-helix twist, minor groove width, propeller twist, and roll-were considered in this analysis. Distinct distributions of effect size were observed for different features. Roll and propeller twist were the DNA shape features most strongly affected by CpG methylation with an effect size depending on the local sequence context. Methylation-induced changes in DNA shape were predictive of the measured rate of cleavage by DNase I and suggest a possible mechanism for some of the methylation sensitivities that were recently observed for human Pbx-Hox complexes.

CONCLUSIONS

CpG methylation is an important epigenetic mark in the mammalian genome. Understanding its role in protein-DNA recognition can further our knowledge of gene regulation. Our high-throughput methyl-DNAshape method can be used to predict the effect of cytosine methylation on DNA shape and its subsequent influence on protein-DNA interactions. This approach overcomes the limited availability of experimental DNA structures that contain 5-methylcytosine.

Integrated analysis of motif activity and gene expression changes of transcription factors

The ability to predict transcription factors based on sequence information in regulatory elements is a key step in systems-level investigation of transcriptional regulation. Here, we have developed a novel tool, IMAGE, for precise prediction of causal transcription factors based on transcriptome profiling and genome-wide maps of enhancer activity. High precision is obtained by combining a near-complete database of position weight matrices (PWMs), generated by compiling public databases and systematic prediction of PWMs for uncharacterized transcription factors, with a state-of-the-art method for PWM scoring and a novel machine learning strategy, based on both enhancers and promoters, to predict the contribution of motifs to transcriptional activity. We applied IMAGE to published data obtained during 3T3-L1 adipocyte differentiation and showed that IMAGE predicts causal transcriptional regulators of this process with higher confidence than existing methods. Furthermore, we generated genome-wide maps of enhancer activity and transcripts during human mesenchymal stem cell commitment and adipocyte differentiation and used IMAGE to identify positive and negative transcriptional regulators of this process. Collectively, our results demonstrate that IMAGE is a powerful and precise method for prediction of regulators of gene expression.

Expanding the repertoire of DNA shape features for genome-scale studies of transcription factor binding

Uncovering the mechanisms that affect the binding specificity of transcription factors (TFs) is critical for understanding the principles of gene regulation. Although sequence-based models have been used successfully to predict TF binding specificities, we found that including DNA shape information in these models improved their accuracy and interpretability. Previously, we developed a method for modeling DNA binding specificities based on DNA shape features extracted from Monte Carlo (MC) simulations. Prediction accuracies of our models, however, have not yet been compared to accuracies of models incorporating DNA shape information extracted from X-ray crystallography (XRC) data or Molecular Dynamics (MD) simulations. Here, we integrated DNA shape information extracted from MC or MD simulations and XRC data into predictive models of TF binding and compared their performance. Models that incorporated structural information consistently showed improved performance over sequence-based models regardless of data source. Furthermore, we derived and validated nine additional DNA shape features beyond our original set of four features. The expanded repertoire of 13 distinct DNA shape features, including six intra-base pair and six inter-base pair parameters and minor groove width, is available in our R/Bioconductor package DNAshapeR and enables a comprehensive structural description of the double helix on a genome-wide scale.

Local sequence features that influence AP-1 cis-regulatory activity

In the genome, most occurrences of transcription factor binding sites (TFBS) have no cis-regulatory activity, which suggests that flanking sequences contain information that distinguishes functional from nonfunctional TFBS. We interrogated the role of flanking sequences near Activator Protein 1 (AP-1) binding sites that reside in DNase I Hypersensitive Sites (DHS) and regions annotated as Enhancers. In these regions, we found that sequence features directly adjacent to the core motif distinguish high from low activity AP-1 sites. Some nearby features are motifs for other TFs that genetically interact with the AP-1 site. Other features are extensions of the AP-1 core motif, which cause the extended sites to match motifs of multiple AP-1 binding proteins. Computational models trained on these data distinguish between sequences with high and low activity AP-1 sites and also predict changes in cis-regulatory activity due to mutations in AP-1 core sites and their flanking sequences. Our results suggest that extended AP-1 binding sites, together with adjacent binding sites for additional TFs, encode part of the information that governs TFBS activity in the genome.

Auxin Response Factors: output control in auxin biology

The phytohormone auxin is involved in almost all developmental processes in land plants. Most, if not all, of these processes are mediated by changes in gene expression. Auxin acts on gene expression through a short nuclear pathway that converges upon the activation of a family of DNA-binding transcription factors. These AUXIN RESPONSE FACTORS (ARFs) are thus the effector of auxin response and translate the chemical signal into the regulation of a defined set of genes. Given the limited number of dedicated components in auxin signaling, distinct properties among the ARF family probably contribute to the establishment of multiple unique auxin responses in plant development. In the two decades following the identification of the first ARF in Arabidopsis, much has been learnt about how these transcription factors act, and how they generate unique auxin responses. Progress in genetics, biochemistry, genomics, and structural biology has helped to develop mechanistic models for ARF action. However, despite intensive efforts, many central questions are yet to be addressed. In this review, we highlight what has been learnt about ARF transcription factors, and identify outstanding questions and challenges for the near future.

Probing instructions for expression regulation in gene nucleotide compositions

Gene expression is orchestrated by distinct regulatory regions to ensure a wide variety of cell types and functions. A challenge is to identify which regulatory regions are active, what are their associated features and how they work together in each cell type. Several approaches have tackled this problem by modeling gene expression based on epigenetic marks, with the ultimate goal of identifying driving regions and associated genomic variations that are clinically relevant in particular in precision medicine. However, these models rely on experimental data, which are limited to specific samples (even often to cell lines) and cannot be generated for all regulators and all patients. In addition, we show here that, although these approaches are accurate in predicting gene expression, inference of TF combinations from this type of models is not straightforward. Furthermore these methods are not designed to capture regulation instructions present at the sequence level, before the binding of regulators or the opening of the chromatin. Here, we probe sequence-level instructions for gene expression and develop a method to explain mRNA levels based solely on nucleotide features. Our method positions nucleotide composition as a critical component of gene expression. Moreover, our approach, able to rank regulatory regions according to their contribution, unveils a strong influence of the gene body sequence, in particular introns. We further provide evidence that the contribution of nucleotide content can be linked to co-regulations associated with genome 3D architecture and to associations of genes within topologically associated domains.

Master Regulatory Transcription Factors in Plant Development: A Blooming Perspective

Transcription factors that trigger major developmental decisions in plants and animals are termed "master regulators". Such master regulators are classically seen as acting on the top of a regulatory hierarchy that determines a complete developmental program, and they usually encode transcription factors. Here, we introduce master regulators of flowering time and flower development as examples to show how analysis of molecular interactions and gene-regulatory networks in plants has changed our view on the molecular mechanisms by which these factors control developmental processes. A picture has emerged that emphasizes a complex combinatorial interplay in determining cell-type transcriptional programs, and a high level of feedback control. The expression of master regulators themselves is usually regulated by multiple factors integrating environmental and endogenous spatiotemporal cues. Master regulatory transcription factors regulate gene expression by different mechanisms, including modifications in chromatin status in the bound regions. A poorly understood phenomenon is how developmental master regulators exert functions in different cell- and organ types. This is especially relevant for those factors that have important functions in several developmental processes.

Conservation of Specificity in Two Low-Specificity Proteins

Many regulatory proteins bind peptide regions of target proteins and modulate their activity. Such regulatory proteins can often interact with highly diverse target peptides. In many instances, it is not known if the peptide-binding interface discriminates targets in a biological context, or whether biological specificity is achieved exclusively through external factors such as subcellular localization. We used an evolutionary biochemical approach to distinguish these possibilities for two such low-specificity proteins: S100A5 and S100A6. We used isothermal titration calorimetry to study the binding of peptides with diverse sequence and biochemistry to human S100A5 and S100A6. These proteins bound distinct, but overlapping, sets of peptide targets. We then studied the peptide binding properties of orthologs sampled from across five amniote species. Binding specificity was conserved along all lineages, for the last 320 million years, despite the low specificity of each protein. We used ancestral sequence reconstruction to determine the binding specificity of the last common ancestor of the paralogs. The ancestor bound the entire set of peptides bound by modern S100A5 and S100A6 proteins, suggesting that paralog specificity evolved via subfunctionalization. To rule out the possibility that specificity is conserved because it is difficult to modify, we identified a single historical mutation that, when reverted in human S100A5, gave it the ability to bind an S100A6-specific peptide. These results reveal strong evolutionary constraints on peptide binding specificity. Despite being able to bind a large number of targets, the specificity of S100 peptide interfaces is likely important for the biology of these proteins.

Genome-wide prediction of minor-groove electrostatic potential enables biophysical modeling of protein-DNA binding

Protein–DNA binding is a fundamental component of gene regulatory processes, but it is still not completely understood how proteins recognize their target sites in the genome. Besides hydrogen bonding in the major groove (base readout), proteins recognize minor-groove geometry using positively charged amino acids (shape readout). The underlying mechanism of DNA shape readout involves the correlation between minor-groove width and electrostatic potential (EP). To probe this biophysical effect directly, rather than using minor-groove width as an indirect measure for shape readout, we developed a methodology, DNAphi, for predicting EP in the minor groove and confirmed the direct role of EP in protein–DNA binding using massive sequencing data. The DNAphi method uses a sliding-window approach to mine results from non-linear Poisson–Boltzmann (NLPB) calculations on DNA structures derived from all-atom Monte Carlo simulations. We validated this approach, which only requires nucleotide sequence as input, based on direct comparison with NLPB calculations for available crystal structures. Using statistical machine-learning approaches, we showed that adding EP as a biophysical feature can improve the predictive power of quantitative binding specificity models across 27 transcription factor families. High-throughput prediction of EP offers a novel way to integrate biophysical and genomic studies of protein–DNA binding.

SelexGLM differentiates androgen and glucocorticoid receptor DNA-binding preference over an extended binding site

The DNA-binding interfaces of the androgen (AR) and glucocorticoid (GR) receptors are virtually identical, yet these transcription factors share only about a third of their genomic binding sites and regulate similarly distinct sets of target genes. To address this paradox, we determined the intrinsic specificities of the AR and GR DNA-binding domains using a refined version of SELEX-seq. We developed an algorithm, SelexGLM, that quantifies binding specificity over a large (31-bp) binding site by iteratively fitting a feature-based generalized linear model to SELEX probe counts. This analysis revealed that the DNA-binding preferences of AR and GR homodimers differ significantly, both within and outside the 15-bp core binding site. The relative preference between the two factors can be tuned over a wide range by changing the DNA sequence, with AR more sensitive to sequence changes than GR. The specificity of AR extends to the regions flanking the core 15-bp site, where isothermal calorimetry measurements reveal that affinity is augmented by enthalpy-driven readout of poly(A) sequences associated with narrowed minor groove width. We conclude that the increased specificity of AR is correlated with more enthalpy-driven binding than GR. The binding models help explain differences in AR and GR genomic binding and provide a biophysical rationale for how promiscuous binding by GR allows functional substitution for AR in some castration-resistant prostate cancers.

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.