The Soft Touch: Low-Affinity Transcription Factor Binding Sites in Development and Evolution

Single Effective Complex Loading into Zero-Mode Waveguides Optimized with Fluorescence Evaluation at Quenching and Accumulation Checkpoints

Single-molecule detection with high accuracy and specialty plays an important role in biomedical diagnosis and screening. Zero-mode waveguides (ZMWs) enable the possibility of single biological molecule detection in real time. Nevertheless, the absence of a reliable assessment for single effective complex loading has constrained further applications of ZMWs in complex interaction. Both the quantity and activity of the complex loaded into ZMWs have a critical effect on the efficiency of detection. Herein, a fluorescence evaluation at quenching and accumulation checkpoints was established to assess and optimize single effective complex loading into ZMWs. A primer-template-enzyme ternary complex was designed, and then an evaluation for quantity statistics at the quenching checkpoint and functional activity at the accumulation checkpoint was used to validate the effectiveness of complexes loaded into ZMWs. By optimizing the parameters such as loading time, procedures, and enzyme amount, the single-molecule effective occupancy was increased to 25.48%, achieving 68.86% of the theoretical maximum value (37%) according to Poisson statistics. It is of great significance to provide effective complex-loading validation for improving the sample-loading efficiency of single-molecule assays or sequencing in the future.

PRA-Pred: Structure-based prediction of protein-RNA binding affinity

Understanding crucial factors that affect the binding affinity of protein-RNA complexes is vital for comprehending their recognition mechanisms. This study involved compiling experimentally measured binding affinity (ΔG) values of 217 protein-RNA complexes and extracting numerous structure-based features, considering RNA, protein, and interactions between protein and RNA. Our findings indicate the significance of RNA base-step parameters, interaction energies, number of atomic contacts in the complex, hydrogen bonds, and contact potentials in understanding the binding affinity. Further, we observed that these factors are influenced by the type of RNA strand and the function of the protein in a protein-RNA complex. Multiple regression equations were developed for different classes of complexes to perform the prediction of the binding affinity between the protein and RNA. We evaluated the models using the jack-knife test and achieved an overall correlation 0.77 between the experimental and predicted binding affinities with a mean absolute error of 1.02 kcal/mol. Furthermore, we introduced a web server, PRA-Pred, intended for the prediction of protein-RNA binding affinity, and it is freely accessible through https://web.iitm.ac.in/bioinfo2/prapred/. We propose that our approach could function as a potential resource for investigating protein-RNA recognitions and developing therapeutic strategies.

Homeodomain complex formation and biomolecular condensates in Hox gene regulation

Hox genes are a family of homeodomain transcription factors that regulate specialized morphological structures along the anterior-posterior axis of metazoans. Over the past few decades, researchers have focused on defining how Hox factors with similar in vitro DNA binding activities achieve sufficient target specificity to regulate distinct cell fates in vivo. In this review, we highlight how protein interactions with other transcription factors, many of which are also homeodomain proteins, result in the formation of transcription factor complexes with enhanced DNA binding specificity. These findings suggest that Hox-regulated enhancers utilize distinct combinations of homeodomain binding sites, many of which are low-affinity, to recruit specific Hox complexes. However, low-affinity sites can only yield reproducible responses with high transcription factor concentrations. To overcome this limitation, recent studies revealed how transcription factors, including Hox factors, use intrinsically disordered domains (IDRs) to form biomolecular condensates that increase protein concentrations. Moreover, Hox factors with altered IDRs have been associated with altered transcriptional activity and human disease states, demonstrating the importance of IDRs in mediating essential Hox output. Collectively, these studies highlight how Hox factors use their DNA binding domains, protein-protein interaction domains, and IDRs to form specific transcription factor complexes that yield accurate gene expression.

Single-nucleotide variants within heart enhancers increase binding affinity and disrupt heart development

Transcriptional enhancers direct precise gene expression patterns during development and harbor the majority of variants associated with phenotypic diversity, evolutionary adaptations, and disease. Pinpointing which enhancer variants contribute to changes in gene expression and phenotypes is a major challenge. Here, we find that suboptimal or low-affinity binding sites are necessary for precise gene expression during heart development. Single-nucleotide variants (SNVs) can optimize the affinity of ETS binding sites, causing gain-of-function (GOF) gene expression, cell migration defects, and phenotypes as severe as extra beating hearts in the marine chordate Ciona robusta. In human induced pluripotent stem cell (iPSC)-derived cardiomyocytes, a SNV within a human GATA4 enhancer increases ETS binding affinity and causes GOF enhancer activity. The prevalence of suboptimal-affinity sites within enhancers creates a vulnerability whereby affinity-optimizing SNVs can lead to GOF gene expression, changes in cellular identity, and organismal-level phenotypes that could contribute to the evolution of novel traits or diseases.

O’Brien T, Perucca P, Ge Z, Anderson A. Applications for Deep Learning in Epilepsy Genetic Research

Epilepsy is a group of brain disorders characterised by an enduring predisposition to generate unprovoked seizures. Fuelled by advances in sequencing technologies and computational approaches, more than 900 genes have now been implicated in epilepsy. The development and optimisation of tools and methods for analysing the vast quantity of genomic data is a rapidly evolving area of research. Deep learning (DL) is a subset of machine learning (ML) that brings opportunity for novel investigative strategies that can be harnessed to gain new insights into the genomic risk of people with epilepsy. DL is being harnessed to address limitations in accuracy of long-read sequencing technologies, which improve on short-read methods. Tools that predict the functional consequence of genetic variation can represent breaking ground in addressing critical knowledge gaps, while methods that integrate independent but complimentary data enhance the predictive power of genetic data. We provide an overview of these DL tools and discuss how they may be applied to the analysis of genetic data for epilepsy research.

Negatively charged, intrinsically disordered regions can accelerate target search by DNA-binding proteins

In eukaryotes, many DNA/RNA-binding proteins possess intrinsically disordered regions (IDRs) with large negative charge, some of which involve a consecutive sequence of aspartate (D) or glutamate (E) residues. We refer to them as D/E repeats. The functional role of D/E repeats is not well understood, though some of them are known to cause autoinhibition through intramolecular electrostatic interaction with functional domains. In this work, we investigated the impacts of D/E repeats on the target DNA search kinetics for the high-mobility group box 1 (HMGB1) protein and the artificial protein constructs of the Antp homeodomain fused with D/E repeats of varied lengths. Our experimental data showed that D/E repeats of particular lengths can accelerate the target association in the overwhelming presence of non-functional high-affinity ligands ('decoys'). Our coarse-grained molecular dynamics (CGMD) simulations showed that the autoinhibited proteins can bind to DNA and transition into the uninhibited complex with DNA through an electrostatically driven induced-fit process. In conjunction with the CGMD simulations, our kinetic model can explain how D/E repeats can accelerate the target association process in the presence of decoys. This study illuminates an unprecedented role of the negatively charged IDRs in the target search process.

PDA-Pred: Predicting the binding affinity of protein-DNA complexes using machine learning techniques and structural features

Protein-DNA interactions play an important role in various biological processes such as gene expression, replication, and transcription. Understanding the important features that dictate the binding affinity of protein-DNA complexes and predicting their affinities is important for elucidating their recognition mechanisms. In this work, we have collected the experimental binding free energy (ΔG) for a set of 391 Protein-DNA complexes and derived several structure-based features such as interaction energy, contact potentials, volume and surface area of binding site residues, base step parameters of the DNA and contacts between different types of atoms. Our analysis on relationship between binding affinity and structural features revealed that the important factors mainly depend on the number of DNA strands as well as functional and structural classes of proteins. Specifically, binding site properties such as number of atom contacts between the DNA and protein, volume of protein binding sites and interaction-based features such as interaction energies and contact potentials are important to understand the binding affinity. Further, we developed multiple regression equations for predicting the binding affinity of protein-DNA complexes belonging to different structural and functional classes. Our method showed an average correlation and mean absolute error of 0.78 and 0.98 kcal/mol, respectively, between the experimental and predicted binding affinities on a jack-knife test. We have developed a webserver, PDA-PreD (Protein-DNA Binding affinity predictor), for predicting the affinity of protein-DNA complexes and it is freely available at https://web.iitm.ac.in/bioinfo2/pdapred/.

CRISPR/Cas9 and FLP-FRT mediated regulatory dissection of the BX-C of Drosophila melanogaster

The homeotic genes or Hox define the anterior-posterior (AP) body axis formation in bilaterians and are often present on the chromosome in an order collinear to their function across the AP axis. However, there are many cases wherein the Hox are not collinear, but their expression pattern is conserved across the AP axis. The expression pattern of Hox is attributed to the cis-regulatory modules (CRMs) consisting of enhancers, initiators, or repressor elements that regulate the genes in a segment-specific manner. In the Drosophila melanogaster Hox complex, the bithorax complex (BX-C) and even the CRMs are organized in an order that is collinear to their function in the thoracic and abdominal segments. In the present study, the regulatorily inert regions were targeted using CRISPR/Cas9 to generate a series of transgenic lines with the insertion of FRT sequences. These FRT lines are repurposed to shuffle the CRMs associated with Abd-B to generate modular deletion, duplication, or inversion of multiple CRMs. The rearrangements yielded entirely novel phenotypes in the fly suggesting the requirement of such complex manipulations to address the significance of higher order arrangement of the CRMs. The functional map and the transgenic flies generated in this study are important resources to decipher the collective ability of multiple regulatory elements in the eukaryotic genome to function as complex modules.

Enhancer architecture and chromatin accessibility constrain phenotypic space during Drosophila development

Developmental enhancers bind transcription factors and dictate patterns of gene expression during development. Their molecular evolution can underlie phenotypical evolution, but the contributions of the evolutionary pathways involved remain little understood. Here, using mutation libraries in Drosophila melanogaster embryos, we observed that most point mutations in developmental enhancers led to changes in gene expression levels but rarely resulted in novel expression outside of the native pattern. In contrast, random sequences, often acting as developmental enhancers, drove expression across a range of cell types; random sequences including motifs for transcription factors with pioneer activity acted as enhancers even more frequently. Our findings suggest that the phenotypic landscapes of developmental enhancers are constrained by enhancer architecture and chromatin accessibility. We propose that the evolution of existing enhancers is limited in its capacity to generate novel phenotypes, whereas the activity of de novo elements is a primary source of phenotypic novelty.

Limited conservation in cross-species comparison of GLK transcription factor binding suggested wide-spread cistrome divergence

Non-coding cis-regulatory variants in animal genomes are an important driving force in the evolution of transcription regulation and phenotype diversity. However, cistrome dynamics in plants remain largely underexplored. Here, we compare the binding of GOLDEN2-LIKE (GLK) transcription factors in tomato, tobacco, Arabidopsis, maize and rice. Although the function of GLKs is conserved, most of their binding sites are species-specific. Conserved binding sites are often found near photosynthetic genes dependent on GLK for expression, but sites near non-differentially expressed genes in the glk mutant are nevertheless under purifying selection. The binding sites' regulatory potential can be predicted by machine learning model using quantitative genome features and TF co-binding information. Our study show that genome cis-variation caused wide-spread TF binding divergence, and most of the TF binding sites are genetically redundant. This poses a major challenge for interpreting the effect of individual sites and highlights the importance of quantitatively measuring TF occupancy.

Structural basis for cell type specific DNA binding of C/EBPβ: The case of cell cycle inhibitor p15INK4b promoter

C/EBPβ is a key regulator of numerous cellular processes, but it can also contribute to tumorigenesis and viral diseases. It binds to specific DNA sequences (C/EBP sites) and interacts with other transcription factors to control expression of multiple eukaryotic genes in a tissue and cell-type dependent manner. A body of evidence has established that cell-type-specific regulatory information is contained in the local DNA sequence of the binding motif. In human epithelial cells, C/EBPβ is an essential cofactor for TGFβ signaling in the case of Smad2/3/4 and FoxO-dependent induction of the cell cycle inhibitor, p15INK4b. In the TGFβ-responsive region 2 of the p15INK4b promoter, the Smad binding site is flanked by a C/EBP site, CTTAA•GAAAG, which differs from the canonical, palindromic ATTGC•GCAAT motif. The X-ray crystal structure of C/EBPβ bound to the p15INK4b promoter fragment shows how GCGC-to-AAGA substitution generates changes in the intermolecular interactions in the protein-DNA interface that enhances C/EBPβ binding specificity, limits possible epigenetic regulation of the promoter, and generates a DNA element with a unique pattern of methyl groups in the major groove. Significantly, CT/GA dinucleotides located at the 5'ends of the double stranded element maintain local narrowing of the DNA minor groove width that is necessary for DNA recognition. Our results suggest that C/EBPβ would accept all forms of modified cytosine in the context of the CpT site. This contrasts with the effect on the consensus motif, where C/EBPβ binding is modestly increased by cytosine methylation, but substantially decreased by hydroxymethylation.

A Synthetic Biosensor for Detecting Putrescine in Beef Samples

Biogenic amines (BAs) are toxicological risks present in many food products. Putrescine is the most common foodborne BA and is frequently used as a quality control marker. Currently, there is a lack of regulation concerning safe putrescine limits in food as well as outdated food handling practices leading to unnecessary putrescine intake. Conventional methods used to evaluate BAs in food are generally time-consuming and resource-heavy with few options for on-site analysis. In response to this challenge, we have developed a transcription factor-based biosensor for the quantification of putrescine in beef samples. In this work, we use a naturally occurring putrescine responsive repressor-operator pair (PuuR-puuO) native to Escherichia coli. Moreover, we demonstrate the use of the cell-free putrescine biosensor on a paper-based device that enables rapid low-cost detection of putrescine in beef samples stored at different temperatures. The results presented demonstrate the potential role of using paper-based biosensors for on-site testing, particularly as an index for determining meat product stability and quality.

On the incongruence of genotype-phenotype and fitness landscapes

The mapping from genotype to phenotype to fitness typically involves multiple nonlinearities that can transform the effects of mutations. For example, mutations may contribute additively to a phenotype, but their effects on fitness may combine non-additively because selection favors a low or intermediate value of that phenotype. This can cause incongruence between the topographical properties of a fitness landscape and its underlying genotype-phenotype landscape. Yet, genotype-phenotype landscapes are often used as a proxy for fitness landscapes to study the dynamics and predictability of evolution. Here, we use theoretical models and empirical data on transcription factor-DNA interactions to systematically study the incongruence of genotype-phenotype and fitness landscapes when selection favors a low or intermediate phenotypic value. Using the theoretical models, we prove a number of fundamental results. For example, selection for low or intermediate phenotypic values does not change simple sign epistasis into reciprocal sign epistasis, implying that genotype-phenotype landscapes with only simple sign epistasis motifs will always give rise to single-peaked fitness landscapes under such selection. More broadly, we show that such selection tends to create fitness landscapes that are more rugged than the underlying genotype-phenotype landscape, but this increased ruggedness typically does not frustrate adaptive evolution because the local adaptive peaks in the fitness landscape tend to be nearly as tall as the global peak. Many of these results carry forward to the empirical genotype-phenotype landscapes, which may help to explain why low- and intermediate-affinity transcription factor-DNA interactions are so prevalent in eukaryotic gene regulation.

How do mutations change phenotypic traits and organismal fitness? This question is often addressed in the context of a classic metaphor of evolutionary theory—the fitness landscape. A fitness landscape is akin to a physical landscape, in which genotypes define spatial coordinates, and fitness defines the elevation of each coordinate. Evolution then acts like a hill-climbing process, in which populations ascend fitness peaks as a consequence of mutation and selection. It is becoming increasingly common to construct such landscapes using experimental data from high-throughput sequencing technologies and phenotypic assays, in systems such as macromolecules and gene regulatory circuits. Although these landscapes are typically defined by molecular phenotypes, and are therefore more appropriately referred to as genotype-phenotype landscapes, they are often used to study evolutionary dynamics. This requires the assumption that the molecular phenotype is a reasonable proxy for fitness, which need not be the case. For example, selection may favor a low or intermediate phenotypic value, causing incongruence between a fitness landscape and its underlying genotype-phenotype landscape. Here, we study such incongruence using a diversity of theoretical models and experimental data from gene regulatory systems. We regularly find incongruence, in that fitness landscapes tend to comprise more peaks than their underlying genotype-phenotype landscapes. However, using evolutionary simulations, we show that this increased ruggedness need not impede adaptation.

Systematic analysis of low-affinity transcription factor binding site clusters in vitro and in vivo establishes their functional relevance

Binding to binding site clusters has yet to be characterized in depth, and the functional relevance of low-affinity clusters remains uncertain. We characterized transcription factor binding to low-affinity clusters in vitro and found that transcription factors can bind concurrently to overlapping sites, challenging the notion of binding exclusivity. Furthermore, small clusters with binding sites an order of magnitude lower in affinity give rise to high mean occupancies at physiologically-relevant transcription factor concentrations. To assess whether the observed in vitro occupancies translate to transcriptional activation in vivo, we tested low-affinity binding site clusters in a synthetic and native gene regulatory network in S. cerevisiae. In both systems, clusters of low-affinity binding sites generated transcriptional output comparable to single or even multiple consensus sites. This systematic characterization demonstrates that clusters of low-affinity binding sites achieve substantial occupancies, and that this occupancy can drive expression in eukaryotic promoters.

Multi-layered transcriptional control of cranial neural crest development

The neural crest (NC) is an emblematic population of embryonic stem-like cells with remarkable migratory ability. These distinctive attributes have inspired the curiosity of developmental biologists for over 150 years, however only recently the regulatory mechanisms controlling the complex features of the NC have started to become elucidated at genomic scales. Regulatory control of NC development is achieved through combinatorial transcription factor binding and recruitment of associated transcriptional complexes to distal cis-regulatory elements. Together, they regulate when, where and to what extent transcriptional programmes are actively deployed, ultimately shaping ontogenetic processes. Here, we discuss how transcriptional networks control NC ontogeny, with a special emphasis on the molecular mechanisms underlying specification of the cephalic NC. We also cover emerging properties of transcriptional regulation revealed in diverse developmental systems, such as the role of three-dimensional conformation of chromatin, and how they are involved in the regulation of NC ontogeny. Finally, we highlight how advances in deciphering the NC transcriptional network have afforded new insights into the molecular basis of human diseases.

Elucidating the biology of transcription factor-DNA interaction for accurate identification of cis-regulatory elements

Transcription factors (TFs) play a critical role in determining cell fate decisions by integrating developmental and environmental signals through binding to specific cis-regulatory modules and regulating spatio-temporal specificity of gene expression patterns. Precise identification of functional TF binding sites in time and space not only will revolutionize our understanding of regulatory networks governing cell fate decisions but is also instrumental to uncover how genetic variations cause morphological diversity or disease. In this review, we discuss recent advances in mapping TF binding sites and characterizing the various parameters underlying the complexity of binding site recognition by TFs.

Evolution of transcription factor binding through sequence variations and turnover of binding sites

Variations in noncoding regulatory sequences play a central role in evolution. Interpreting such variations, however, remains difficult even in the context of defined attributes such as transcription factor (TF) binding sites. Here, we systematically link variations in cis-regulatory sequences to TF binding by profiling the allele-specific binding of 27 TFs expressed in a yeast hybrid, in which two related genomes are present within the same nucleus. TFs localize preferentially to sites containing their known consensus motifs but occupy only a small fraction of the motif-containing sites available within the genomes. Differential binding of TFs to the orthologous alleles was well explained by variations that alter motif sequence, whereas differences in chromatin accessibility between alleles were of little apparent effect. Motif variations that abolished binding when present in only one allele were still bound when present in both alleles, suggesting evolutionary compensation, with a potential role for sequence conservation at the motif's vicinity. At the level of the full promoter, we identify cases of binding-site turnover, in which binding sites are reciprocally gained and lost, yet most interspecific differences remained uncompensated. Our results show the flexibility of TFs to bind imprecise motifs and the fast evolution of TF binding sites between related species.

A synthetic synthesis to explore animal evolution and development

Identifying the general principles by which genotypes are converted into phenotypes remains a challenge in the post-genomic era. We still lack a predictive understanding of how genes shape interactions among cells and tissues in response to signalling and environmental cues, and hence how regulatory networks generate the phenotypic variation required for adaptive evolution. Here, we discuss how techniques borrowed from synthetic biology may facilitate a systematic exploration of evolvability across biological scales. Synthetic approaches permit controlled manipulation of both endogenous and fully engineered systems, providing a flexible platform for investigating causal mechanisms in vivo. Combining synthetic approaches with multi-level phenotyping (phenomics) will supply a detailed, quantitative characterization of how internal and external stimuli shape the morphology and behaviour of living organisms. We advocate integrating high-throughput experimental data with mathematical and computational techniques from a variety of disciplines in order to pursue a comprehensive theory of evolution.

This article is part of the theme issue ‘Genetic basis of adaptation and speciation: from loci to causative mutations’.

DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers

Enhancer sequences control gene expression and comprise binding sites (motifs) for different transcription factors (TFs). Despite extensive genetic and computational studies, the relationship between DNA sequence and regulatory activity is poorly understood, and de novo enhancer design has been challenging. Here, we built a deep-learning model, DeepSTARR, to quantitatively predict the activities of thousands of developmental and housekeeping enhancers directly from DNA sequence in Drosophila melanogaster S2 cells. The model learned relevant TF motifs and higher-order syntax rules, including functionally nonequivalent instances of the same TF motif that are determined by motif-flanking sequence and intermotif distances. We validated these rules experimentally and demonstrated that they can be generalized to humans by testing more than 40,000 wildtype and mutant Drosophila and human enhancers. Finally, we designed and functionally validated synthetic enhancers with desired activities de novo.

Notch-dependent DNA cis-regulatory elements and their dose-dependent control of C. elegans stem cell self-renewal

A long-standing biological question is how DNA cis-regulatory elements shape transcriptional patterns during metazoan development. Reporter constructs, cell culture assays and computational modeling have made major contributions to answering this question, but analysis of elements in their natural context is an important complement. Here, we mutate Notch-dependent LAG-1 binding sites (LBSs) in the endogenous Caenorhabditis elegans sygl-1 gene, which encodes a key stem cell regulator, and analyze the consequences on sygl-1 expression (nascent transcripts, mRNA, protein) and stem cell maintenance. Mutation of one LBS in a three-element cluster approximately halved both expression and stem cell pool size, whereas mutation of two LBSs essentially abolished them. Heterozygous LBS mutant clusters provided intermediate values. Our results lead to two major conclusions. First, both LBS number and configuration impact cluster activity: LBSs act additively in trans and synergistically in cis. Second, the SYGL-1 gradient promotes self-renewal above its functional threshold and triggers differentiation below the threshold. Our approach of coupling CRISPR/Cas9 LBS mutations with effects on both molecular and biological readouts establishes a powerful model for in vivo analyses of DNA cis-regulatory elements.

Summary: Notch-dependent DNA cis-regulatory elements work together in their developmental context in C. elegans to shape a transcriptional gradient, control stem cell pool size, and govern differentiation onset.

The power of the (imperfect) palindrome: Sequence-specific roles of palindromic motifs in gene regulation

In human languages, a palindrome reads the same forward as backward (e.g., 'madam'). In regulatory DNA, a palindrome is an inverted sequence repeat that allows a transcription factor to bind as a homodimer or as a heterodimer with another type of transcription factor. Regulatory palindromes are typically imperfect, that is, the repeated sequences differ in at least one base pair, but the functional significance of this asymmetry remains poorly understood. Here, we review the use of imperfect palindromes in Drosophila photoreceptor differentiation and mammalian steroid receptor signaling. Moreover, we discuss mechanistic explanations for the predominance of imperfect palindromes over perfect palindromes in these two gene regulatory contexts. Lastly, we propose to elucidate whether specific imperfectly palindromic variants have specific regulatory functions in steroid receptor signaling and whether such variants can help predict transcriptional outcomes as well as the response of individual patients to drug treatments.

Delilah, prospero, and D-Pax2 constitute a gene regulatory network essential for the development of functional proprioceptors

Coordinated animal locomotion depends on the development of functional proprioceptors. While early cell-fate determination processes are well characterized, little is known about the terminal differentiation of cells within the proprioceptive lineage and the genetic networks that control them. In this work we describe a gene regulatory network consisting of three transcription factors–Prospero (Pros), D-Pax2, and Delilah (Dei)–that dictates two alternative differentiation programs within the proprioceptive lineage in Drosophila. We show that D-Pax2 and Pros control the differentiation of cap versus scolopale cells in the chordotonal organ lineage by, respectively, activating and repressing the transcription of dei. Normally, D-Pax2 activates the expression of dei in the cap cell but is unable to do so in the scolopale cell where Pros is co-expressed. We further show that D-Pax2 and Pros exert their effects on dei transcription via a 262 bp chordotonal-specific enhancer in which two D-Pax2- and three Pros-binding sites were identified experimentally. When this enhancer was removed from the fly genome, the cap- and ligament-specific expression of dei was lost, resulting in loss of chordotonal organ functionality and defective larval locomotion. Thus, coordinated larval locomotion depends on the activity of a dei enhancer that integrates both activating and repressive inputs for the generation of a functional proprioceptive organ.

Methods of massive parallel reporter assays for investigation of enhancers

The correct deployment of genetic programs for development and differentiation relies on finely coordinated regulation of specific gene sets. Genomic regulatory elements play an exceptional role in this process. There are few types of gene regulatory elements, including promoters, enhancers, insulators and silencers. Alterations of gene regulatory elements may cause various pathologies, including cancer, congenital disorders and autoimmune diseases. The development of high-throughput genomic assays has made it possible to significantly accelerate the accumulation of information about the characteristic epigenetic properties of regulatory elements. In combination with high-throughput studies focused on the genome-wide distribution of epigenetic marks, regulatory proteins and the spatial structure of chromatin, this significantly expands the understanding of the principles of epigenetic regulation of genes and allows potential regulatory elements to be searched for in silico. However, common experimental approaches used to study the local characteristics of chromatin have a number of technical limitations that may reduce the reliability of computational identification of genomic regulatory sequences. Taking into account the variability of the functions of epigenetic determinants and complex multicomponent regulation of genomic elements activity, their functional verification is often required. A plethora of methods have been developed to study the functional role of regulatory elements on the genome scale. Common experimental approaches for in silico identification of regulatory elements and their inherent technical limitations will be described. The present review is focused on original high-throughput methods of enhancer activity reporter analysis that are currently used to validate predicted regulatory elements and to perform de novo searches. The methods described allow assessing the functional role of the nucleotide sequence of a regulatory element, to determine its exact boundaries and to assess the influence of the local state of chromatin on the activity of enhancers and gene expression. These approaches have contributed substantially to the understanding of the fundamental principles of gene regulation.

Transcription Factor Dynamics

To predict transcription, one needs a mechanistic understanding of how the numerous required transcription factors (TFs) explore the nuclear space to find their target genes, assemble, cooperate, and compete with one another. Advances in fluorescence microscopy have made it possible to visualize real-time TF dynamics in living cells, leading to two intriguing observations: first, most TFs contact chromatin only transiently; and second, TFs can assemble into clusters through their intrinsically disordered regions. These findings suggest that highly dynamic events and spatially structured nuclear microenvironments might play key roles in transcription regulation that are not yet fully understood. The emerging model is that while some promoters directly convert TF-binding events into on/off cycles of transcription, many others apply complex regulatory layers that ultimately lead to diverse phenotypic outputs. Cracking this kinetic code is an ongoing and challenging task that is made possible by combining innovative imaging approaches with biophysical models.

ProNAB: database for binding affinities of protein-nucleic acid complexes and their mutants

Protein–nucleic acid interactions are involved in various biological processes such as gene expression, replication, transcription, translation and packaging. The binding affinities of protein–DNA and protein–RNA complexes are important for elucidating the mechanism of protein–nucleic acid recognition. Although experimental data on binding affinity are reported abundantly in the literature, no well-curated database is currently available for protein–nucleic acid binding affinity. We have developed a database, ProNAB, which contains more than 20 000 experimental data for the binding affinities of protein–DNA and protein–RNA complexes. Each entry provides comprehensive information on sequence and structural features of a protein, nucleic acid and its complex, experimental conditions, thermodynamic parameters such as dissociation constant (K_d), binding free energy (ΔG) and change in binding free energy upon mutation (ΔΔG), and literature information. ProNAB is cross-linked with GenBank, UniProt, PDB, ProThermDB, PROSITE, DisProt and Pubmed. It provides a user-friendly web interface with options for search, display, sorting, visualization, download and upload the data. ProNAB is freely available at https://web.iitm.ac.in/bioinfo2/pronab/ and it has potential applications such as understanding the factors influencing the affinity, development of prediction tools, binding affinity change upon mutation and design complexes with the desired affinity.

p53-Dependent Repression: DREAM or Reality?

Simple Summary

The tumor suppressor p53 is a complex cell signaling hub encompassing multiple transcription programs and governs a vast repertoire of biological responses. However, despite several decades of research, how p53 selects one program over another is still elusive. Recent attempts have used meta-analyses of p53 ChIP-seq data to determine the core p53 transcriptional program, conserved across different models and stimuli. This review highlights the complexity of the multiple layers of p53 regulation and the context specificity of p53 target genes. More specifically, we discuss the controversy over the mechanisms of p53-dependent transcriptional repression and its potential role in the flexibility of p53 response.

Abstract

p53 is a major tumor suppressor that integrates diverse types of signaling in mammalian cells. In response to a broad range of intra- or extra-cellular stimuli, p53 controls the expression of multiple target genes and elicits a vast repertoire of biological responses. The exact code by which p53 integrates the various stresses and translates them into an appropriate transcriptional response is still obscure. p53 is tightly regulated at multiple levels, leading to a wide diversity in p53 complexes on its target promoters and providing adaptability to its transcriptional program. As p53-targeted therapies are making their way into clinics, we need to understand how to direct p53 towards the desired outcome (i.e., cell death, senescence or other) selectively in cancer cells without affecting normal tissues or the immune system. While the core p53 transcriptional program has been proposed, the mechanisms conferring a cell type- and stimuli-dependent transcriptional outcome by p53 require further investigations. The mechanism by which p53 localizes to repressed promoters and manages its co-repressor interactions is controversial and remains an important gap in our understanding of the p53 cistrome. We hope that our review of the recent literature will help to stimulate the appreciation and investigation of largely unexplored p53-mediated repression.

LncRNA LINC00520 aggravates cell proliferation and migration in lung adenocarcinoma via a positive feedback loop

Background

Lung adenocarcinoma (LUAD) is the most common histological subtype of primary lung cancer. To identify the biomarker of diagnosis for LUAD is of great significance. Long non-coding RNAs (lncRNAs) were previously revealed to exert vital effects in numerous cancers. LncRNA long intergenic non-protein coding RNA 520 (LINC00520) served as an oncogene in various cancers. Therefore, our study was specially designed to probe the role of LINC00520 in LUAD.

Results

LINC00520 expression was detected by RT-qPCR. Next, function of LINC00520 in LUAD was verified by in vitro loss-of-function experiments. DNA pull down, ChIP, RIP, and luciferase reporter assays were conducted to reveal the regulatory mechanism of LINC00520. We found that LINC00520 was upregulated in LUAD. Additionally, LINC00520 upregulation is associated with the poor prognosis for patients with LUAD. Furthermore, LINC00520 downregulation suppressed LUAD cell proliferation and migration and induced cell apoptosis. Forkhead box P3 (FOXP3) is identified as the transcription factor to transcriptionally activate LINC00520. Moreover, LINC00520 positively upregulated FOXP3 expression via sponging miR-3611 in LUAD cells. Subsequently, rescue experiments delineated that miR-3611 downregulation or FOXP3 overexpression reversed the effects of silenced LINC00520 on proliferative and migratory capabilities in LUAD cells.

Conclusion

This study innovatively indicated that lncRNA LINC00520 facilitated cell proliferative and migratory abilities in LUAD through interacting with miR-3611 and targeting FOXP3, which may provide a potential novel insight for treatment of LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-021-01657-6.

Adaptive gene misregulation

Because gene expression is important for evolutionary adaptation, its misregulation is an important cause of maladaptation. A misregulated gene can be incorrectly silent ("off") when a transcription factor (TF) that is required for its activation does not binds its regulatory region. Conversely, a misregulated gene can be incorrectly active ("on") when a TF not normally involved in its activation binds its regulatory region, a phenomenon also known as regulatory crosstalk. DNA mutations that destroy or create TF binding sites on DNA are an important source of misregulation and crosstalk. Although misregulation reduces fitness in an environment to which an organism is well-adapted, it may become adaptive in a new environment. Here, I derive simple yet general mathematical expressions that delimit the conditions under which misregulation can be adaptive. These expressions depend on the strength of selection against misregulation, on the fraction of DNA sequence space filled with TF binding sites, and on the fraction of genes that must be expressed for optimal adaptation. I then use empirical data from RNA sequencing, protein-binding microarrays, and genome evolution, together with population genetic simulations to ask when these conditions are likely to be met. I show that they can be met under realistic circumstances, but these circumstances may vary among organisms and environments. My analysis provides a framework in which improved theory and data collection can help us demonstrate the role of misregulation in adaptation. It also shows that misregulation, like DNA mutation, is one of life's many imperfections that can help propel Darwinian evolution.

Developmental Robustness: The Haltere Case in Drosophila

Developmental processes have to be robust but also flexible enough to respond to genetic and environmental variations. Different mechanisms have been described to explain the apparent antagonistic nature of developmental robustness and plasticity. Here, we present a “self-sufficient” molecular model to explain the development of a particular flight organ that is under the control of the Hox gene Ultrabithorax (Ubx) in the fruit fly Drosophila melanogaster. Our model is based on a candidate RNAi screen and additional genetic analyses that all converge to an autonomous and cofactor-independent mode of action for Ubx. We postulate that this self-sufficient molecular mechanism is possible due to an unusually high expression level of the Hox protein. We propose that high dosage could constitute a so far poorly investigated molecular strategy for allowing Hox proteins to both innovate and stabilize new forms during evolution.

A combinatorial cis-regulatory logic restricts color-sensing Rhodopsins to specific photoreceptor subsets in Drosophila

Color vision in Drosophila melanogaster is based on the expression of five different color-sensing Rhodopsin proteins in distinct subtypes of photoreceptor neurons. Promoter regions of less than 300 base pairs are sufficient to reproduce the unique, photoreceptor subtype-specific rhodopsin expression patterns. The underlying cis-regulatory logic remains poorly understood, but it has been proposed that the rhodopsin promoters have a bipartite structure: the distal promoter region directs the highly restricted expression in a specific photoreceptor subtype, while the proximal core promoter region provides general activation in all photoreceptors. Here, we investigate whether the rhodopsin promoters exhibit a strict specialization of their distal (subtype specificity) and proximal (general activation) promoter regions, or if both promoter regions contribute to generating the photoreceptor subtype-specific expression pattern. To distinguish between these two models, we analyze the expression patterns of a set of hybrid promoters that combine the distal promoter region of one rhodopsin with the proximal core promoter region of another rhodopsin. We find that the function of the proximal core promoter regions extends beyond providing general activation: these regions play a previously underappreciated role in generating the non-overlapping expression patterns of the different rhodopsins. Therefore, cis-regulatory motifs in both the distal and the proximal core promoter regions recruit transcription factors that generate the unique rhodopsin patterns in a combinatorial manner. We compare this combinatorial regulatory logic to the regulatory logic of olfactory receptor genes and discuss potential implications for the evolution of rhodopsins.

Each type of sensory receptor neuron in our body expresses a specific sensory receptor protein, which allows us to detect and discriminate a variety of environmental stimuli. The regulatory logic that controls this spatially precise and highly restricted expression of sensory receptor proteins remains poorly understood. As a model system, we study the mechanisms that control the expression of different color-sensing Rhodopsin proteins in distinct subtypes of Drosophila photoreceptors, which is the basis for color vision. Compact promoter regions of less than 300 base pairs are sufficient to reproduce the non-overlapping rhodopsin patterns. However, the regulatory logic that underlies the combination (sometimes called ‘grammar’) of the cis-regulatory motifs (sometimes called ‘vocabulary’) within the rhodopsin promoters remains poorly understood. Here, we find that specific combinations of cis-regulatory motifs in the distal and the proximal core promoter regions of each rhodopsin direct its unique expression pattern.

Regulatory SNPs: Altered Transcription Factor Binding Sites Implicated in Complex Traits and Diseases

The vast majority of the genetic variants (mainly SNPs) associated with various human traits and diseases map to a noncoding part of the genome and are enriched in its regulatory compartment, suggesting that many causal variants may affect gene expression. The leading mechanism of action of these SNPs consists in the alterations in the transcription factor binding via creation or disruption of transcription factor binding sites (TFBSs) or some change in the affinity of these regulatory proteins to their cognate sites. In this review, we first focus on the history of the discovery of regulatory SNPs (rSNPs) and systematized description of the existing methodical approaches to their study. Then, we brief the recent comprehensive examples of rSNPs studied from the discovery of the changes in the TFBS sequence as a result of a nucleotide substitution to identification of its effect on the target gene expression and, eventually, to phenotype. We also describe state-of-the-art genome-wide approaches to identification of regulatory variants, including both making molecular sense of genome-wide association studies (GWAS) and the alternative approaches the primary goal of which is to determine the functionality of genetic variants. Among these approaches, special attention is paid to expression quantitative trait loci (eQTLs) analysis and the search for allele-specific events in RNA-seq (ASE events) as well as in ChIP-seq, DNase-seq, and ATAC-seq (ASB events) data.

Bayesian Markov models improve the prediction of binding motifs beyond first order

Transcription factors (TFs) regulate gene expression by binding to specific DNA motifs. Accurate models for predicting binding affinities are crucial for quantitatively understanding of transcriptional regulation. Motifs are commonly described by position weight matrices, which assume that each position contributes independently to the binding energy. Models that can learn dependencies between positions, for instance, induced by DNA structure preferences, have yielded markedly improved predictions for most TFs on in vivo data. However, they are more prone to overfit the data and to learn patterns merely correlated with rather than directly involved in TF binding. We present an improved, faster version of our Bayesian Markov model software, BaMMmotif2. We tested it with state-of-the-art motif discovery tools on a large collection of ChIP-seq and HT-SELEX datasets. BaMMmotif2 models of fifth-order achieved a median false-discovery-rate-averaged recall 13.6% and 12.2% higher than the next best tool on 427 ChIP-seq datasets and 164 HT-SELEX datasets, respectively, while being 8 to 1000 times faster. BaMMmotif2 models showed no signs of overtraining in cross-cell line and cross-platform tests, with similar improvements on the next-best tool. These results demonstrate that dependencies beyond first order clearly improve binding models for most TFs.

An open-source semi-automated robotics pipeline for embryo immunohistochemistry

A significant challenge for developmental systems biology is balancing throughput with controlled conditions that minimize experimental artifacts. Large-scale developmental screens such as unbiased mutagenesis surveys have been limited in their applicability to embryonic systems, as the technologies for quantifying precise expression patterns in whole animals has not kept pace with other sequencing-based technologies. Here, we outline an open-source semi-automated pipeline to chemically fixate, stain, and 3D-image Drosophila embryos. Central to this pipeline is a liquid handling robot, Flyspresso, which automates the steps of classical embryo fixation and staining. We provide the schematics and an overview of the technology for an engineer or someone equivalently trained to reproduce and further improve upon Flyspresso, and highlight the Drosophila embryo fixation and colorimetric or antibody staining protocols. Additionally, we provide a detailed overview and stepwise protocol for our adaptive-feedback pipeline for automated embryo imaging on confocal microscopes. We demonstrate the efficiency of this pipeline compared to classical techniques, and how it can be repurposed or scaled to other protocols and biological systems. We hope our pipeline will serve as a platform for future research, allowing a broader community of users to build, execute, and share similar experiments.

Posttranslational Modifications in Conserved Transcription Factors: A Survey of the TALE-Homeodomain Superclass in Human and Mouse

Transcription factors (TFs) guide effector proteins like chromatin-modifying or -remodeling enzymes to distinct sites in the genome and thereby fulfill important early steps in translating the genome’s sequence information into the production of proteins or functional RNAs. TFs of the same family are often highly conserved in evolution, raising the question of how proteins with seemingly similar structure and DNA-binding properties can exert physiologically distinct functions or respond to context-specific extracellular cues. A good example is the TALE superclass of homeodomain-containing proteins. All TALE-homeodomain proteins share a characteristic, 63-amino acid long homeodomain and bind to similar sequence motifs. Yet, they frequently fulfill non-redundant functions even in domains of co-expression and are subject to regulation by different signaling pathways. Here we provide an overview of posttranslational modifications that are associated with murine and human TALE-homeodomain proteins and discuss their possible importance for the biology of these TFs.

Enhancer grammar in development, evolution, and disease: dependencies and interplay

Each language has standard books describing that language's grammatical rules. Biologists have searched for similar, albeit more complex, principles relating enhancer sequence to gene expression. Here, we review the literature on enhancer grammar. We introduce dependency grammar, a model where enhancers encode information based on dependencies between enhancer features shaped by mechanistic, evolutionary, and biological constraints. Classifying enhancers based on the types of dependencies may identify unifying principles relating enhancer sequence to gene expression. Such rules would allow us to read the instructions for development within genomes and pinpoint causal enhancer variants underlying disease and evolutionary changes.

Conserved regulatory logic at accessible and inaccessible chromatin during the acute inflammatory response in mammals

The regulatory elements controlling gene expression during acute inflammation are not fully elucidated. Here we report the identification of a set of NF-κB-bound elements and common chromatin landscapes underlying the acute inflammatory response across cell-types and mammalian species. Using primary vascular endothelial cells (human/mouse/bovine) treated with the pro-inflammatory cytokine, Tumor Necrosis Factor-α, we identify extensive (~30%) conserved orthologous binding of NF-κB to accessible, as well as nucleosome-occluded chromatin. Regions with the highest NF-κB occupancy pre-stimulation show dramatic increases in NF-κB binding and chromatin accessibility post-stimulation. These 'pre-bound' regions are typically conserved (~56%), contain multiple NF-κB motifs, are utilized by diverse cell types, and overlap rare non-coding mutations and common genetic variation associated with both inflammatory and cardiovascular phenotypes. Genetic ablation of conserved, 'pre-bound' NF-κB regions within the super-enhancer associated with the chemokine-encoding CCL2 gene and elsewhere supports the functional relevance of these elements.

Conformational Plasticity and DNA-Binding Specificity of the Eukaryotic Transcription Factor Pax5

The eukaryotic transcription factor Pax5 has a DNA-binding Paired domain composed of two independent helical bundle subdomains joined by a flexible linker. Previously, we showed distinct biophysical properties of the N-terminal (NTD) and C-terminal (CTD) subdomains, with implications for how these two regions cooperate to distinguish nonspecific and cognate DNA sites [Perez-Borrajero, C., et al. (2016) J. Mol. Biol. 428, 2372-2391]. In this study, we combined experimental methods and molecular dynamics (MD) simulations to dissect the mechanisms underlying the functional differences between the Pax5 subdomains. Both subdomains showed a similar dependence of DNA-binding affinity on ionic strength. However, due to a greater contribution of non-ionic interactions, the NTD bound its cognate DNA half-site with an affinity approximately 10-fold higher than that of the CTD with its half-site. These interactions involve base-mediated contacts as evidenced by nuclear magnetic resonance spectroscopy-monitored chemical shift perturbations. Isothermal titration calorimetry revealed that favorable enthalpic and compensating unfavorable entropic changes were substantially larger for DNA binding by the NTD than by the CTD. Complementary MD simulations indicated that the DNA recognition helix H3 of the NTD is particularly flexible in the absence of DNA and undergoes the largest changes in conformational dynamics upon binding. Overall, these data suggest that the differences observed for the subdomains of Pax5 are due to the coupling of DNA binding with dampening of motions in the NTD required for specific base contacts. Thus, the conformational plasticity of the Pax5 Paired domain underpins the differing roles of its subdomains in association with nonspecific versus cognate DNA sites.

High-Throughput Affinity Measurements of Transcription Factor and DNA Mutations Reveal Affinity and Specificity Determinants

Transcription factors (TFs) bind regulatory DNA to control gene expression, and mutations to either TFs or DNA can alter binding affinities to rewire regulatory networks and drive phenotypic variation. While studies have profiled energetic effects of DNA mutations extensively, we lack similar information for TF variants. Here, we present STAMMP (simultaneous transcription factor affinity measurements via microfluidic protein arrays), a high-throughput microfluidic platform enabling quantitative characterization of hundreds of TF variants simultaneously. Measured affinities for ∼210 mutants of a model yeast TF (Pho4) interacting with 9 oligonucleotides (>1,800 K_ds) reveal that many combinations of mutations to poorly conserved TF residues and nucleotides flanking the core binding site alter but preserve physiological binding, providing a mechanism by which combinations of mutations in cis and trans could modulate TF binding to tune occupancies during evolution. Moreover, biochemical double-mutant cycles across the TF-DNA interface reveal molecular mechanisms driving recognition, linking sequence to function. A record of this paper's Transparent Peer Review process is included in the Supplemental Information.

Discrete-state stochastic kinetic models for target DNA search by proteins: Theory and experimental applications

To perform their functions, transcription factors and DNA-repair/modifying enzymes randomly search DNA in order to locate their specific targets on DNA. Discrete-state stochastic kinetic models have been developed to explain how the efficiency of the search process is influenced by the molecular properties of proteins and DNA as well as by other factors such as molecular crowding. These theoretical models not only offer explanations on the relation of microscopic processes to macroscopic behavior of proteins, but also facilitate the analysis and interpretation of experimental data. In this review article, we provide an overview on discrete-state stochastic kinetic models and explain how these models can be applied to experimental investigations using stopped-flow, single-molecule, nuclear magnetic resonance (NMR), and other biophysical and biochemical methods.

Synthetic protein-binding DNA sponge as a tool to tune gene expression and mitigate protein toxicity

Versatile tools for gene expression regulation are vital for engineering gene networks of increasing scales and complexity with bespoke responses. Here, we investigate and repurpose a ubiquitous, indirect gene regulation mechanism from nature, which uses decoy protein-binding DNA sites, named DNA sponge, to modulate target gene expression in Escherichia coli. We show that synthetic DNA sponges can be designed to reshape the response profiles of gene circuits, lending multifaceted tuning capacities including reducing basal leakage by >20-fold, increasing system output amplitude by >130-fold and dynamic range by >70-fold, and mitigating host growth inhibition by >20%. Further, multi-layer DNA sponges for decoying multiple regulatory proteins provide an additive tuning effect on the responses of layered circuits compared to single-layer sponges. Our work shows synthetic DNA sponges offer a simple yet generalizable route to systematically engineer the performance of synthetic gene circuits, expanding the current toolkit for gene regulation with broad potential applications.

Decoy binding sites are natural regulators of gene expression. Here the authors design synthetic DNA sponges that fine tune the performance of synthetic gene circuits in a simple yet systematic manner, expanding the synthetic biology toolkit for gene regulation.

A low affinity cis-regulatory BMP response element restricts target gene activation to subsets of Drosophila neurons

Retrograde BMP signaling and canonical pMad/Medea-mediated transcription regulate diverse target genes across subsets of Drosophila efferent neurons, to differentiate neuropeptidergic neurons and promote motor neuron terminal maturation. How a common BMP signal regulates diverse target genes across many neuronal subsets remains largely unresolved, although available evidence implicates subset-specific transcription factor codes rather than differences in BMP signaling. Here we examine the cis-regulatory mechanisms restricting BMP-induced FMRFa neuropeptide expression to Tv4-neurons. We find that pMad/Medea bind at an atypical, low affinity motif in the FMRFa enhancer. Converting this motif to high affinity caused ectopic enhancer activity and eliminated Tv4-neuron expression. In silico searches identified additional motif instances functional in other efferent neurons, implicating broader functions for this motif in BMP-dependent enhancer activity. Thus, differential interpretation of a common BMP signal, conferred by low affinity pMad/Medea binding motifs, can contribute to the specification of BMP target genes in efferent neuron subsets.

Robust and efficient gene regulation through localized nuclear microenvironments

Developmental enhancers drive gene expression in specific cell types during animal development. They integrate signals from many different sources mediated through the binding of transcription factors, producing specific responses in gene expression. Transcription factors often bind low-affinity sequences for only short durations. How brief, low-affinity interactions drive efficient transcription and robust gene expression is a central question in developmental biology. Localized high concentrations of transcription factors have been suggested as a possible mechanism by which to use these enhancer sites effectively. Here, we discuss the evidence for such transcriptional microenvironments, mechanisms for their formation and the biological consequences of such sub-nuclear compartmentalization for developmental decisions and evolution.

Architecture of DNA elements mediating ARF transcription factor binding and auxin-responsive gene expression in Arabidopsis

The hormone auxin controls many aspects of the plant life cycle by regulating the expression of thousands of genes. The transcriptional output of the nuclear auxin signaling pathway is determined by the activity of AUXIN RESPONSE transcription FACTORs (ARFs), through their binding to cis-regulatory elements in auxin-responsive genes. Crystal structures, in vitro, and heterologous studies have fueled a model in which ARF dimers bind with high affinity to distinctly spaced repeats of canonical AuxRE motifs. However, the relevance of this "caliper" model, and the mechanisms underlying the binding affinities in vivo, have remained elusive. Here we biochemically and functionally interrogate modes of ARF-DNA interaction. We show that a single additional hydrogen bond in Arabidopsis ARF1 confers high-affinity binding to individual DNA sites. We demonstrate the importance of AuxRE cooperativity within repeats in the Arabidopsis TMO5 and IAA11 promoters in vivo. Meta-analysis of transcriptomes further reveals strong genome-wide association of auxin response with both inverted (IR) and direct (DR) AuxRE repeats, which we experimentally validated. The association of these elements with auxin-induced up-regulation (DR and IR) or down-regulation (IR) was correlated with differential binding affinities of A-class and B-class ARFs, respectively, suggesting a mechanistic basis for the distinct activity of these repeats. Our results support the relevance of high-affinity binding of ARF transcription factors to uniquely spaced DNA elements in vivo, and suggest that differential binding affinities of ARF subfamilies underlie diversity in cis-element function.

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.

Functional genomic approaches to elucidate the role of enhancers during development

Successful development depends on the precise tissue-specific regulation of genes by enhancers, genetic elements that act as switches to control when and where genes are expressed. Because enhancers are critical for development, and the majority of disease-associated mutations reside within enhancers, it is essential to understand which sequences within enhancers are important for function. Advances in sequencing technology have enabled the rapid generation of genomic data that predict putative active enhancers, but functionally validating these sequences at scale remains a fundamental challenge. Herein, we discuss the power of genome-wide strategies used to identify candidate enhancers, and also highlight limitations and misconceptions that have arisen from these data. We discuss the use of massively parallel reporter assays to test enhancers for function at scale. We also review recent advances in our ability to study gene regulation during development, including CRISPR-based tools to manipulate genomes and single-cell transcriptomics to finely map gene expression. Finally, we look ahead to a synthesis of complementary genomic approaches that will advance our understanding of enhancer function during development. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Developmental Biology > Developmental Processes in Health and Disease Laboratory Methods and Technologies > Genetic/Genomic Methods.

The ROK like protein of Myxococcus xanthus DK1622 acts as a pleiotropic transcriptional regulator for secondary metabolism

Myxococcus xanthus DK1622 is known as a proficient producer of different kinds of secondary metabolites (SM) with various biological activities, including myxovirescin A, myxalamide A, myxochromide A and DKxanthene. Low production of SM in the wild type bacteria makes searching for production optimization methods highly desirable. Identification and induction of endogenous key molecular feature(s) regulating the production level of the metabolites remain promising, while heterologous expression of the biosynthetic genes is not always efficient because of various complicating factors including codon usage bias. This study established proteomic and molecular approaches to elucidate the regulatory roles of the ROK regulatory protein in the modification of secondary metabolite biosynthesis. Interestingly, the results revealed that rok inactivation significantly reduced the production of the SM and also changed the motility in the bacteria. Electrophoretic mobility shift assay using purified ROK protein indicated a direct enhancement of the promoters encoding transcription of the DKxanthene, myxochelin A, and myxalamide A biosynthesis machinery. Comparative proteomic analysis by two-dimensional fluorescence difference in-gel electrophoresis (2D-DIGE) was employed to identify the protein profiles of the wild type and rok mutant strains during early and late logarithmic growth phases of the bacterial culture. Resulting data demonstrated overall 130 differently altered proteins by the effect of the rok gene mutation, including putative proteins suspected to be involved in transcriptional regulation, carbohydrate metabolism, development, spore formation, and motility. Except for a slight induction seen in the production of myxovirescin A in a rok over-expression background, no changes were found in the formation of the other SM. From the outcome of our investigation, it is possible to conclude that ROK acts as a pleiotropic regulator of secondary metabolite formation and development in M. xanthus, while its direct effects still remain speculative. More experiments are required to elucidate in detail the variable regulation effects of the protein and to explore applicable approaches for generating valuable SM in this bacterium.

How to study enhancers in non-traditional insect models

Transcriptional enhancers are central to the function and evolution of genes and gene regulation. At the organismal level, enhancers play a crucial role in coordinating tissue- and context-dependent gene expression. At the population level, changes in enhancers are thought to be a major driving force that facilitates evolution of diverse traits. An amazing array of diverse traits seen in insect morphology, physiology and behavior has been the subject of research for centuries. Although enhancer studies in insects outside of Drosophila have been limited, recent advances in functional genomic approaches have begun to make such studies possible in an increasing selection of insect species. Here, instead of comprehensively reviewing currently available technologies for enhancer studies in established model organisms such as Drosophila, we focus on a subset of computational and experimental approaches that are likely applicable to non-Drosophila insects, and discuss the pros and cons of each approach. We discuss the importance of validating enhancer function and evaluate several possible validation methods, such as reporter assays and genome editing. Key points and potential pitfalls when establishing a reporter assay system in non-traditional insect models are also discussed. We close with a discussion of how to advance enhancer studies in insects, both by improving computational approaches and by expanding the genetic toolbox in various insects. Through these discussions, this Review provides a conceptual framework for studying the function and evolution of enhancers in non-traditional insect models.

Intrinsic DNA Shape Accounts for Affinity Differences between Hox-Cofactor Binding Sites

Transcription factors bind to their binding sites over a wide range of affinities, yet how differences in affinity are encoded in DNA sequences is not well understood. Here, we report X-ray crystal structures of four heterodimers of the Hox protein AbdominalB bound with its cofactor Extradenticle to four target DNA molecules that differ in affinity by up to ∼20-fold. Remarkably, despite large differences in affinity, the overall structures are very similar in all four complexes. In contrast, the predicted shapes of the DNA binding sites (i.e., the intrinsic DNA shape) in the absence of bound protein are strikingly different from each other and correlate with affinity: binding sites that must change conformations upon protein binding have lower affinities than binding sites that have more optimal conformations prior to binding. Together, these observations suggest that intrinsic differences in DNA shape provide a robust mechanism for modulating affinity without affecting other protein-DNA interactions.