Low-Affinity Binding Sites and the Transcription Factor Specificity Paradox in Eukaryotes.

Eukaryotic transcription factors (TFs) from the same structural family tend to bind similar DNA sequences, despite the ability of these TFs to execute distinct functions in vivo. The cell partly resolves this specificity paradox through combinatorial strategies and the use of low-affinity binding sites, which are better able to distinguish between similar TFs. However, because these sites have low affinity, it is challenging to understand how TFs recognize them in vivo. Here, we summarize recent findings and technological advancements that allow for the quantification and mechanistic interpretation of TF recognition across a wide range of affinities. We propose a model that integrates insights from the fields of genetics and cell biology to provide further conceptual understanding of TF binding specificity. We argue that in eukaryotes, target specificity is driven by an inhomogeneous 3D nuclear distribution of TFs and by variation in DNA binding affinity such that locally elevated TF concentration allows low-affinity binding sites to be functional.

The Importance of Timing.

Building a nervous system requires a precise sequence of genetic transitions, mediated in part by the temporal and spatial regulation of transcription factors. Quan et al. add to our understanding of this regulation by describing an evolutionarily conserved post-translational mechanism that rapidly extinguishes proneural protein activity in neural precursors.

Deconvolving the recognition of DNA shape from sequence.

Protein-DNA binding is mediated by the recognition of the chemical signatures of the DNA bases and the 3D shape of the DNA molecule. Because DNA shape is a consequence of sequence, it is difficult to dissociate these modes of recognition. Here, we tease them apart in the context of Hox-DNA binding by mutating residues that, in a co-crystal structure, only recognize DNA shape. Complexes made with these mutants lose the preference to bind sequences with specific DNA shape features. Introducing shape-recognizing residues from one Hox protein to another swapped binding specificities in vitro and gene regulation in vivo. Statistical machine learning revealed that the accuracy of binding specificity predictions improves by adding shape features to a model that only depends on sequence, and feature selection identified shape features important for recognition. Thus, shape readout is a direct and independent component of binding site selection by Hox proteins.

Low affinity binding site clusters confer hox specificity and regulatory robustness.

In animals, Hox transcription factors define regional identity in distinct anatomical domains. How Hox genes encode this specificity is a paradox, because different Hox proteins bind with high affinity in vitro to similar DNA sequences. Here, we demonstrate that the Hox protein Ultrabithorax (Ubx) in complex with its cofactor Extradenticle (Exd) bound specifically to clusters of very low affinity sites in enhancers of the shavenbaby gene of Drosophila. These low affinity sites conferred specificity for Ubx binding in vivo, but multiple clustered sites were required for robust expression when embryos developed in variable environments. Although most individual Ubx binding sites are not evolutionarily conserved, the overall enhancer architecture-clusters of low affinity binding sites-is maintained and required for enhancer function. Natural selection therefore works at the level of the enhancer, requiring a particular density of low affinity Ubx sites to confer both specific and robust expression.

Context-Dependent Gene Regulation by Homeodomain Transcription Factor Complexes Revealed by Shape-Readout Deficient Proteins.

Eukaryotic transcription factors (TFs) form complexes with various partner proteins to recognize their genomic target sites. Yet, how the DNA sequence determines which TF complex forms at any given site is poorly understood. Here, we demonstrate that high-throughput in vitro DNA binding assays coupled with unbiased computational analysis provide unprecedented insight into how different DNA sequences select distinct compositions and configurations of homeodomain TF complexes. Using inferred knowledge about minor groove width readout, we design targeted protein mutations that destabilize homeodomain binding both in vitro and in vivo in a complex-specific manner. By performing parallel systematic evolution of ligands by exponential enrichment sequencing (SELEX-seq), chromatin immunoprecipitation sequencing (ChIP-seq), RNA sequencing (RNA-seq), and Hi-C assays, we not only classify the majority of in vivo binding events in terms of complex composition but also infer complex-specific functions by perturbing the gene regulatory network controlled by a single complex.

Collective behavior from surprise minimization.

Collective motion is ubiquitous in nature; groups of animals, such as fish, birds, and ungulates appear to move as a whole, exhibiting a rich behavioral repertoire that ranges from directed movement to milling to disordered swarming. Typically, such macroscopic patterns arise from decentralized, local interactions among constituent components (e.g., individual fish in a school). Preeminent models of this process describe individuals as self-propelled particles, subject to self-generated motion and "social forces" such as short-range repulsion and long-range attraction or alignment. However, organisms are not particles; they are probabilistic decision-makers. Here, we introduce an approach to modeling collective behavior based on active inference. This cognitive framework casts behavior as the consequence of a single imperative: to minimize surprise. We demonstrate that many empirically observed collective phenomena, including cohesion, milling, and directed motion, emerge naturally when considering behavior as driven by active Bayesian inference-without explicitly building behavioral rules or goals into individual agents. Furthermore, we show that active inference can recover and generalize the classical notion of social forces as agents attempt to suppress prediction errors that conflict with their expectations. By exploring the parameter space of the belief-based model, we reveal nontrivial relationships between the individual beliefs and group properties like polarization and the tendency to visit different collective states. We also explore how individual beliefs about uncertainty determine collective decision-making accuracy. Finally, we show how agents can update their generative model over time, resulting in groups that are collectively more sensitive to external fluctuations and encode information more robustly.

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

Members of transcription factor families typically have similar DNA binding specificities yet execute unique functions in vivo. Transcription factors often bind DNA as multiprotein complexes, raising the possibility that complex formation might modify their DNA binding specificities. To test this hypothesis, we developed an experimental and computational platform, SELEX-seq, that can be used to determine the relative affinities to any DNA sequence for any transcription factor complex. Applying this method to all eight Drosophila Hox proteins, we show that they obtain novel recognition properties when they bind DNA with the dimeric cofactor Extradenticle-Homothorax (Exd). Exd-Hox specificities group into three main classes that obey Hox gene collinearity rules and DNA structure predictions suggest that anterior and posterior Hox proteins prefer DNA sequences with distinct minor groove topographies. Together, these data suggest that emergent DNA recognition properties revealed by interactions with cofactors contribute to transcription factor specificities in vivo.

Dense and pleiotropic regulatory information in a developmental enhancer.

Changes in gene regulation underlie much of phenotypic evolution1. However, our understanding of the potential for regulatory evolution is biased, because most evidence comes from either natural variation or limited experimental perturbations2. Using an automated robotics pipeline, we surveyed an unbiased mutation library for a developmental enhancer in Drosophila melanogaster. We found that almost all mutations altered gene expression and that parameters of gene expression-levels, location, and state-were convolved. The widespread pleiotropic effects of most mutations may constrain the evolvability of developmental enhancers. Consistent with these observations, comparisons of diverse Drosophila larvae revealed apparent biases in the phenotypes influenced by the enhancer. Developmental enhancers may encode a higher density of regulatory information than has been appreciated previously, imposing constraints on regulatory evolution.

Origins of specificity in protein-DNA recognition.

Specific interactions between proteins and DNA are fundamental to many biological processes. In this review, we provide a revised view of protein-DNA interactions that emphasizes the importance of the three-dimensional structures of both macromolecules. We divide protein-DNA interactions into two categories: those when the protein recognizes the unique chemical signatures of the DNA bases (base readout) and those when the protein recognizes a sequence-dependent DNA shape (shape readout). We further divide base readout into those interactions that occur in the major groove from those that occur in the minor groove. Analogously, the readout of the DNA shape is subdivided into global shape recognition (for example, when the DNA helix exhibits an overall bend) and local shape recognition (for example, when a base pair step is kinked or a region of the minor groove is narrow). Based on the >1500 structures of protein-DNA complexes now available in the Protein Data Bank, we argue that individual DNA-binding proteins combine multiple readout mechanisms to achieve DNA-binding specificity. Specificity that distinguishes between families frequently involves base readout in the major groove, whereas shape readout is often exploited for higher resolution specificity, to distinguish between members within the same DNA-binding protein family.

SpyChIP identifies cell type-specific transcription factor occupancy from complex tissues.

Chromatin immunoprecipitation (ChIP) is an important technique for characterizing protein-DNA binding in vivo. One drawback of ChIP-based techniques is the lack of cell type-specificity when profiling complex tissues. To overcome this limitation, we developed SpyChIP to identify cell type-specific transcription factor (TF) binding sites in native physiological contexts without tissue dissociation or nuclei sorting. SpyChIP takes advantage of a specific covalent isopeptide bond that rapidly forms between the 15-amino acid SpyTag and the 17-kDa protein SpyCatcher. In SpyChIP, the target TF is fused with SpyTag by genome engineering, and an epitope tagged SpyCatcher is expressed in cell populations of interest, where it covalently binds to SpyTag-TF. Cell type-specific ChIP is obtained by immunoprecipitating chromatin prepared from whole tissues using antibodies directed against the epitope-tagged SpyCatcher. Using SpyChIP, we identified the genome-wide binding profiles of the Hox protein Ultrabithorax (Ubx) in two distinct cell types of the Drosophila haltere imaginal disc. Our results revealed extensive region-specific Ubx-DNA binding events, highlighting the significance of cell type-specific ChIP and the limitations of whole-tissue ChIP approaches. Analysis of Ubx::SpyChIP results provided insights into the relationship between chromatin accessibility and Ubx-DNA binding, as well as different mechanisms Ubx employs to regulate its downstream cis-regulatory modules. In addition to SpyChIP, we suggest that SpyTag-SpyCatcher technology, as well as other protein pairs that form covalent isopeptide bonds, will facilitate many additional in vivo applications that were previously impractical.

Two Notorious Nodes: a Critical Examination of Relaxed Molecular Clock Age Estimates of the Bilaterian Animals and Placental Mammals.

The popularity of relaxed clock Bayesian inference of clade origin timings has generated several recent publications with focal results considerably older than the fossils of the clades in question. Here we critically examine two such clades: the animals (with focus on the bilaterians); and the mammals (with focus on the placentals). Each example displays a set of characteristic pathologies which, although much commented on, are rarely corrected for. We conclude that in neither case does the molecular clock analysis provide any evidence for an origin of the clade deeper than what is suggested by the fossil record. In addition, both these clades have other features (including, in the case of the placental mammals, proximity to a large mass extinction) that allow us to generate precise expectations of the timings of their origins. Thus, in these instances the fossil record can provide a powerful test of molecular clock methodology, and why it goes astray; and we have every reason to think these problems are general.

Homothorax controls a binary Rhodopsin switch in Drosophila ocelli.

Visual perception of the environment is mediated by specialized photoreceptor (PR) neurons of the eye. Each PR expresses photosensitive opsins, which are activated by a particular wavelength of light. In most insects, the visual system comprises a pair of compound eyes that are mainly associated with motion, color or polarized light detection, and a triplet of ocelli that are thought to be critical during flight to detect horizon and movements. It is widely believed that the evolutionary diversification of compound eye and ocelli in insects occurred from an ancestral visual organ around 500 million years ago. Concurrently, opsin genes were also duplicated to provide distinct spectral sensitivities to different PRs of compound eye and ocelli. In the fruit fly Drosophila melanogaster, Rhodopsin1 (Rh1) and Rh2 are closely related opsins that originated from the duplication of a single ancestral gene. However, in the visual organs, Rh2 is uniquely expressed in ocelli whereas Rh1 is uniquely expressed in outer PRs of the compound eye. It is currently unknown how this differential expression of Rh1 and Rh2 in the two visual organs is controlled to provide unique spectral sensitivities to ocelli and compound eyes. Here, we show that Homothorax (Hth) is expressed in ocelli and confers proper rhodopsin expression. We find that Hth controls a binary Rhodopsin switch in ocelli to promote Rh2 expression and repress Rh1 expression. Genetic and molecular analysis of rh1 and rh2 supports that Hth acts through their promoters to regulate Rhodopsin expression in the ocelli. Finally, we also show that when ectopically expressed in the retina, hth is sufficient to induce Rh2 expression only at the outer PRs in a cell autonomous manner. We therefore propose that the diversification of rhodpsins in the ocelli and retinal outer PRs occurred by duplication of an ancestral gene, which is under the control of Homothorax.

Control of tissue morphogenesis by the HOX gene Ultrabithorax.

Mutations in the Ultrabithorax (Ubx) gene cause homeotic transformation of the normally two-winged Drosophila into a four-winged mutant fly. Ubx encodes a HOX family transcription factor that specifies segment identity, including transformation of the second set of wings into rudimentary halteres. Ubx is known to control the expression of many genes that regulate tissue growth and patterning, but how it regulates tissue morphogenesis to reshape the wing into a haltere is still unclear. Here, we show that Ubx acts by repressing the expression of two genes in the haltere, Stubble and Notopleural, both of which encode transmembrane proteases that remodel the apical extracellular matrix to promote wing morphogenesis. In addition, Ubx induces expression of the Tissue inhibitor of metalloproteases in the haltere, which prevents the basal extracellular matrix remodelling necessary for wing morphogenesis. Our results provide a long-awaited explanation for how Ubx controls morphogenetic transformation.

Evolutionary stability of social interaction rules in collective decision-making.

Social animals can use the choices made by other members of their groups as cues in decision making. Individuals must balance the private information they receive from their own sensory cues with the social information provided by observing what others have chosen. These two cues can be integrated using decision making rules, which specify the probability to select one or other options based on the quality and quantity of social and non-social information. Previous empirical work has investigated which decision making rules can replicate the observable features of collective decision making, while other theoretical research has derived forms for decision making rules based on normative assumptions about how rational agents should respond to the available information. Here we explore the performance of one commonly used decision making rule in terms of the expected decision accuracy of individuals employing it. We show that parameters of this model which have typically been treated as independent variables in empirical model-fitting studies obey necessary relationships under the assumption that animals are evolutionarily optimised to their environment. We further investigate whether this decision making model is appropriate to all animal groups by testing its evolutionary stability to invasion by alternative strategies that use social information differently, and show that the likely evolutionary equilibrium of these strategies depends sensitively on the precise nature of group identity among the wider population of animals it is embedded within.

A lexicon for homeodomain-DNA recognition.

Decoding the cis-regulatory logic of eukaryotic genomes requires knowledge of the DNA-binding specificities of all transcription factors. New work (Berger et al., 2008; Noyes et al., 2008) provides individual specificities for nearly all Drosophila and mouse homeodomains, key DNA-binding domains in many transcription factors. The data underscore the complexity of determining target specificities in vivo.

Collective decision-making by rational agents with differing preferences.

Collective decisions can emerge from individual-level interactions between members of a group. These interactions are often seen as social feedback rules, whereby individuals copy the decisions they observe others making, creating a coherent group decision. The benefit of these behavioral rules to the individual agent can be understood as a transfer of information, whereby a focal individual learns about the world by gaining access to the information possessed by others. Previous studies have analyzed this exchange of information by assuming that all agents share common goals. While differences in information and differences in preferences have often been conflated, little is known about how differences between agents' underlying preferences affect the use and efficacy of social information. In this paper, I develop a model of social information use by rational agents with differing preferences, and demonstrate that the resulting collective behavior is strongly dependent on the structure of preference sharing within the group, as well as the quality of information in the environment. In particular, I show that strong social responses are expected by individuals that are habituated to noisy, uncertain environments where private information about the world is relatively weak. Furthermore, by investigating heterogeneous group structures, I demonstrate a potential influence of cryptic minority subgroups that may illuminate the empirical link between personality and leadership.

Evolution of heterogeneous perceptual limits and indifference in competitive foraging.

The collective behaviour of animal and human groups emerges from the individual decisions and actions of their constituent members. Recent research has revealed many ways in which the behaviour of groups can be influenced by differences amongst their constituent individuals. The existence of individual differences that have implications for collective behaviour raises important questions. How are these differences generated and maintained? Are individual differences driven by exogenous factors, or are they a response to the social dilemmas these groups face? Here I consider the classic case of patch selection by foraging agents under conditions of social competition. I introduce a multilevel model wherein the perceptual sensitivities of agents evolve in response to their foraging success or failure over repeated patch selections. This model reveals a bifurcation in the population, creating a class of agents with no perceptual sensitivity. These agents exploit the social environment to avoid the costs of accurate perception, relying on other agents to make fitness rewards insensitive to the choice of foraging patch. This provides a individual-based evolutionary basis for models incorporating perceptual limits that have been proposed to explain observed deviations from the Ideal Free Distribution (IFD) in empirical studies, while showing that the common assumption in such models that agents share identical sensory limits is likely false. Further analysis of the model shows how agents develop perceptual strategic niches in response to environmental variability. The emergence of agents insensitive to reward differences also has implications for societal resource allocation problems, including the use of financial and prediction markets as mechanisms for aggregating collective wisdom.

Low affinity binding sites in an activating CRM mediate negative autoregulation of the Drosophila Hox gene Ultrabithorax.

Specification of cell identity and the proper functioning of a mature cell depend on precise regulation of gene expression. Both binary ON/OFF regulation of transcription, as well as more fine-tuned control of transcription levels in the ON state, are required to define cell types. The Drosophila melanogaster Hox gene, Ultrabithorax (Ubx), exhibits both of these modes of control during development. While ON/OFF regulation is needed to specify the fate of the developing wing (Ubx OFF) and haltere (Ubx ON), the levels of Ubx within the haltere differ between compartments along the proximal-distal axis. Here, we identify and molecularly dissect the novel contribution of a previously identified Ubx cis-regulatory module (CRM), anterobithorax (abx), to a negative auto-regulatory loop that decreases Ubx expression in the proximal compartment of the haltere as compared to the distal compartment. We find that Ubx, in complex with the known Hox cofactors, Homothorax (Hth) and Extradenticle (Exd), acts through low-affinity Ubx-Exd binding sites to reduce the levels of Ubx transcription in the proximal compartment. Importantly, we also reveal that Ubx-Exd-binding site mutations sufficient to result in de-repression of abx activity in a transgenic context are not sufficient to de-repress Ubx expression when mutated at the endogenous locus, suggesting the presence of multiple mechanisms through which Ubx-mediated repression occurs. Our results underscore the complementary nature of CRM analysis through transgenic reporter assays and genome modification of the endogenous locus; but, they also highlight the increasing need to understand gene regulation within the native context to capture the potential input of multiple genomic elements on gene control.

Collective decision making by rational individuals.

The patterns and mechanisms of collective decision making in humans and animals have attracted both empirical and theoretical attention. Of particular interest has been the variety of social feedback rules and the extent to which these behavioral rules can be explained and predicted from theories of rational estimation and decision making. However, models that aim to model the full range of social information use have incorporated ad hoc departures from rational decision-making theory to explain the apparent stochasticity and variability of behavior. In this paper I develop a model of social information use and collective decision making by fully rational agents that reveals how a wide range of apparently stochastic social decision rules emerge from fundamental information asymmetries both between individuals and between the decision makers and the observer of those decisions. As well as showing that rational decision making is consistent with empirical observations of collective behavior, this model makes several testable predictions about how individuals make decisions in groups and offers a valuable perspective on how we view sources of variability in animal, and human, behavior.