In pursuit of design principles of regulatory sequences

Targeting and silencing of rhodopsin by ectopic expression of the transcription factor KLF15

The genome-wide activity of transcription factors (TFs) on multiple regulatory elements precludes their use as gene-specific regulators. Here we show that ectopic expression of a TF in a cell-specific context can be used to silence the expression of a specific gene as a therapeutic approach to regulate gene expression in human disease. We selected the TF Krüppel-like factor 15 (KLF15) based on its putative ability to recognize a specific DNA sequence motif present in the rhodopsin (RHO) promoter and its lack of expression in terminally differentiated rod photoreceptors (the RHO-expressing cells). Adeno-associated virus (AAV) vector-mediated ectopic expression of KLF15 in rod photoreceptors of pigs enables Rho silencing with limited genome-wide transcriptional perturbations. Suppression of a RHO mutant allele by KLF15 corrects the phenotype of a mouse model of retinitis pigmentosa with no observed toxicity. Cell-specific-context conditioning of TF activity may prove a novel mode for somatic gene-targeted manipulation.

GeneHancer: genome-wide integration of enhancers and target genes in GeneCards

A major challenge in understanding gene regulation is the unequivocal identification of enhancer elements and uncovering their connections to genes. We present GeneHancer, a novel database of human enhancers and their inferred target genes, in the framework of GeneCards. First, we integrated a total of 434 000 reported enhancers from four different genome-wide databases: the Encyclopedia of DNA Elements (ENCODE), the Ensembl regulatory build, the functional annotation of the mammalian genome (FANTOM) project and the VISTA Enhancer Browser. Employing an integration algorithm that aims to remove redundancy, GeneHancer portrays 285 000 integrated candidate enhancers (covering 12.4% of the genome), 94 000 of which are derived from more than one source, and each assigned an annotation-derived confidence score. GeneHancer subsequently links enhancers to genes, using: tissue co-expression correlation between genes and enhancer RNAs, as well as enhancer-targeted transcription factor genes; expression quantitative trait loci for variants within enhancers; and capture Hi-C, a promoter-specific genome conformation assay. The individual scores based on each of these four methods, along with gene–enhancer genomic distances, form the basis for GeneHancer’s combinatorial likelihood-based scores for enhancer–gene pairing. Finally, we define ‘elite’ enhancer–gene relations reflecting both a high-likelihood enhancer definition and a strong enhancer–gene association.

GeneHancer predictions are fully integrated in the widely used GeneCards Suite, whereby candidate enhancers and their annotations are displayed on every relevant GeneCard. This assists in the mapping of non-coding variants to enhancers, and via the linked genes, forms a basis for variant–phenotype interpretation of whole-genome sequences in health and disease.

Database URL:http://www.genecards.org/

A Simple Grammar Defines Activating and Repressing cis-Regulatory Elements in Photoreceptors

Transcription factors often activate and repress different target genes in the same cell. How activation and repression are encoded by different arrangements of transcription factor binding sites in cis-regulatory elements is poorly understood. We investigated how sites for the transcription factor CRX encode both activation and repression in photoreceptors by assaying thousands of genomic and synthetic cis-regulatory elements in wild-type and Crx^-/- retinas. We found that sequences with high affinity for CRX repress transcription, whereas sequences with lower affinity activate. This rule is modified by a cooperative interaction between CRX sites and sites for the transcription factor NRL, which overrides the repressive effect of high affinity for CRX. Our results show how simple rearrangements of transcription factor binding sites encode qualitatively different responses to a single transcription factor and explain how CRX plays multiple cis-regulatory roles in the same cell.

Cis-regulatory landscapes of four cell types of the retina

The retina is composed of ∼50 cell-types with specific functions for the process of vision. Identification of the cis-regulatory elements active in retinal cell-types is key to elucidate the networks controlling this diversity. Here, we combined transcriptome and epigenome profiling to map the regulatory landscape of four cell-types isolated from mouse retinas including rod and cone photoreceptors as well as rare inter-neuron populations such as horizontal and starburst amacrine cells. Integration of this information reveals sequence determinants and candidate transcription factors for controlling cellular specialization. Additionally, we refined parallel reporter assays to enable studying the transcriptional activity of large collection of sequences in individual cell-types isolated from a tissue. We provide proof of concept for this approach and its scalability by characterizing the transcriptional capacity of several hundred putative regulatory sequences within individual retinal cell-types. This generates a catalogue of cis-regulatory regions active in retinal cell types and we further demonstrate their utility as potential resource for cellular tagging and manipulation.

IL-12 stimulates CTLs to secrete exosomes capable of activating bystander CD8+ T cells

An effective cytotoxic T lymphocyte (CTL) response against intracellular pathogens is generally accomplished by immense CTL expansion and activation, which can destroy infected cells. Vigorous immune responses can lead to activation of bystander CD8⁺ T cells, but the contribution from antigen-specific CTLs is not well understood. We found that CTLs secrete extracellular vesicles following antigen stimulation. These CTL-derived vesicles contain CTL proteins and exhibit markers and size profiles consistent with exosomes. Interestingly, further stimulation of CTLs with IL-12 impacts exosome size and leads to selective enrichment of certain exosomal proteins. More important, exosomes from IL-12-stimulated CTLs directly activated bystander naïve CD8⁺ T cells to produce interferon-γ (IFNγ) and granzyme B (GZB) in the absence of antigens, whereas control exosomes derived from antigen-stimulated CTLs did not. In addition, IL-12 induced exosomes are able to strengthen the effects of weak antigen stimulation on CTLs. Proteomic analysis demonstrates that IL-12 stimulation alters catalytic and binding activities of proteins in CTL exosomes. Our findings indicate that the biological function and morphology of exosomes secreted by CTLs can be influenced by the type of stimulation CTLs receive. Thus, a fully functional, ongoing, antigen-specific CTL response may influence bystander CD8⁺ T cells through secretion of exosomes.

Identification and functional prediction of stress responsive AP2/ERF transcription factors in Brassica napus by genome-wide analysis

Using homology and domain authentication, 321 putative AP2/ERF transcription factors were identified in Brassica napus, called BnAP2/ERF TFs. BnAP2/ERF TFs were classified into five major subfamilies, including DREB, ERF, AP2, RAV, and BnSoloist. This classification is based on phylogenetic analysis, motif identification, gene structure analysis, and physiochemical characterization. These TFs were annotated based on phylogenetic relationship with Brassica rapa. BnAP2/ERF TFs were located on 19 chromosomes of B. napus. Orthologs and paralogs were identified using synteny-based methods Ks calculation within B. napus genome and between B. napus with other species such as B. rapa, Brassica oleracea, and Arabidopsis thaliana indicated that BnAP2/ERF TFs were formed through duplication events occurred before B. napus formation. Kn/Ks values were between 0 and 1, suggesting the purifying selection among BnAP2/ERF TFs. Gene ontology annotation, cis-regulatory elements and functional interaction networks suggested that BnAP2/ERF TFs participate in response to stressors, including drought, high salinity, heat and cold as well as developmental processes particularly organ specification and embryogenesis. The identified cis-regulatory elements in the upstream of BnAP2/ERF TFs were responsive to abscisic acid. Analysis of the expression data derived from Illumina Hiseq 2000 RNA sequencing revealed that BnAP2/ERF genes were highly expressed in the roots comparing to flower buds, leaves, and stems. Also, the ERF subfamily was over-expressed under salt and fungal treatments. BnERF039 and BnERF245 are candidates for salt-tolerant B. napus. BnERF253-256 and BnERF260-277 are potential cytokinin response factors. BnERF227, BnERF228, BnERF234, BnERF134, BnERF132, BnERF176, and BnERF235 were suggested for resistance against Leptosphaeria maculan and Leptosphaeria biglobosa.

Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints

In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding. Sasquatch performs a comprehensive k-mer-based analysis of DNase footprints to determine any k-mer's potential for protein binding in a specific cell type and how this may be changed by sequence variants. Therefore, Sasquatch uses an unbiased approach, independent of known transcription factor binding sites and motifs. Sasquatch only requires a single DNase-seq data set per cell type, from any genotype, and produces consistent predictions from data generated by different experimental procedures and at different sequence depths. Here we demonstrate the effectiveness of Sasquatch using previously validated functional SNPs and benchmark its performance against existing approaches. Sasquatch is available as a versatile webtool incorporating publicly available data, including the human ENCODE collection. Thus, Sasquatch provides a powerful tool and repository for prioritizing likely regulatory SNPs in the noncoding genome.

A Knockout Screen of ApiAP2 Genes Reveals Networks of Interacting Transcriptional Regulators Controlling the Plasmodium Life Cycle

A family of apicomplexa-specific proteins containing AP2 DNA-binding domains (ApiAP2s) was identified in malaria parasites. This family includes sequence-specific transcription factors that are key regulators of development. However, functions for the majority of ApiAP2 genes remain unknown. Here, a systematic knockout screen in Plasmodium berghei identified ten ApiAP2 genes that were essential for mosquito transmission: four were critical for the formation of infectious ookinetes, and three were required for sporogony. We describe non-essential functions for AP2-O and AP2-SP proteins in blood stages, and identify AP2-G2 as a repressor active in both asexual and sexual stages. Comparative transcriptomics across mutants and developmental stages revealed clusters of co-regulated genes with shared cis promoter elements, whose expression can be controlled positively or negatively by different ApiAP2 factors. We propose that stage-specific interactions between ApiAP2 proteins on partly overlapping sets of target genes generate the complex transcriptional network that controls the Plasmodium life cycle.

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Mutants in 11 of 26 apiAP2 genes reveal gene functions in mosquito transmission

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Co-expression clustering across mutants and stages reveals molecular phenotypes

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Multifunctional apiAP2 genes create complex regulatory networks in Plasmodium

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Ap2-g2 is a transcriptional repressor in both asexual and sexual blood stages

Functional regulatory evolution outside of the minimal even-skipped stripe 2 enhancer

Transcriptional enhancers are regions of DNA that drive precise patterns of gene expression. Although many studies have elucidated how individual enhancers can evolve, most of this work has focused on what are called 'minimal' enhancers, the smallest DNA regions that drive expression that approximates an aspect of native gene expression. Here, we explore how the Drosophila erecta even-skipped (eve) locus has evolved by testing its activity in the divergent D. melanogaster genome. We found, as has been reported previously, that the D. erecta eve stripe 2 enhancer (eveS2) fails to drive appreciable expression in D. melanogaster However, we found that a large transgene carrying the entire D. erecta eve locus drives normal eve expression, including in stripe 2. We performed a functional dissection of the region upstream of the D. erecta eveS2 region and found multiple Zelda motifs that are required for normal expression. Our results illustrate how sequences outside of minimal enhancer regions can evolve functionally through mechanisms other than changes in transcription factor-binding sites that drive patterning.

Identification and characterization of a FOXA2-regulated transcriptional enhancer at a type 2 diabetes intronic locus that controls GCKR expression in liver cells

BACKGROUND

Genome-wide association studies (GWAS) have identified more than 100 genetic loci associated with type 2 diabetes (T2D). However, the underlying biological mechanisms for many of these associations remain unknown. GWAS signals close to the glucokinase regulatory protein gene (GCKR) have been reported for lipid and glucose metabolism traits and the risk of T2D. We investigated the regulatory function of an intronic locus at GCKR represented by the lead single nucleotide polymorphism (SNP) rs780094.

METHODS

We used ENCODE project histone modification and transcription factor binding data to determine the regulatory features of a GCKR intronic locus formed by the high linkage disequilibrium rs780094(C/T), rs780095(G/A), and rs780096(G/C) SNPs. Characterization of the transcriptional activity of this region was assessed by luciferase reporter assays in HepG2 cells and mouse primary hepatocytes. ChIP-qPCR was used to determine the levels of haplotype specific transcription factor binding and histone marks. A CRISPR-dCas9 transcriptional activator system and qPCR were used to activate the locus and measure GCKR expression, respectively. Differential haplotype expression was measured from human liver biopsies.

RESULTS

The ENCODE data suggest the existence of a liver-specific intragenic enhancer at the locus represented by s780094. We observed that FOXA2 increased the transcriptional activity of this region in a haplotype specific way (CGG > TAC; rs780094, rs780095, and rs780096). In addition, the CGG haplotype showed higher binding to FOXA2 and higher levels of the H3K27Ac histone mark. The epigenetic activation of this locus increased the expression of endogenous GCKR in HepG2 cells, confirming that GCKR is the direct target gene of the enhancer. Finally, we confirmed that the CGG haplotype exhibits higher levels of transcription in human liver.

CONCLUSIONS

Our results demonstrate the existence of a liver-specific FOXA2-regulated transcriptional enhancer at an intronic T2D locus represented by rs780094, rs780095, and rs780096 SNPs that increases GCKR expression. Differential haplotype regulation suggests the existence of cis regulatory effects that may contribute to the associated traits at this locus.

On the mechanistic nature of epistasis in a canonical cis-regulatory element

Understanding the relation between genotype and phenotype remains a major challenge. The difficulty of predicting individual mutation effects, and particularly the interactions between them, has prevented the development of a comprehensive theory that links genotypic changes to their phenotypic effects. We show that a general thermodynamic framework for gene regulation, based on a biophysical understanding of protein-DNA binding, accurately predicts the sign of epistasis in a canonical cis-regulatory element consisting of overlapping RNA polymerase and repressor binding sites. Sign and magnitude of individual mutation effects are sufficient to predict the sign of epistasis and its environmental dependence. Thus, the thermodynamic model offers the correct null prediction for epistasis between mutations across DNA-binding sites. Our results indicate that a predictive theory for the effects of cis-regulatory mutations is possible from first principles, as long as the essential molecular mechanisms and the constraints these impose on a biological system are accounted for.

DOI:http://dx.doi.org/10.7554/eLife.25192.001

Mutations are changes to DNA that provide the raw material upon which evolution can act. Therefore, to understand evolution, we need to know the effects of mutations, and how those mutations interact with each other (a phenomenon referred to as epistasis). So far, few mathematical models allow scientists to predict the effects of mutations, and even fewer are able to predict epistasis.

Biological systems are complex and consist of many proteins and other molecules. Genes are the sections of DNA that provide the instructions needed to produce these molecules, and some genes encode proteins that can bind to DNA to control whether other genes are switched on or off. Lagator, Paixão et al. have now used mathematical models and experiments to understand how the environment inside the cells of a bacterium known as E. coli, specifically the amount of particular proteins, affects epistasis.

These mathematical models are able to predict interactions between mutations in the most abundant class of DNA-binding sites in proteins. This approach found that the nature of the interaction between mutations can be explained through biophysical laws, combined with the basic knowledge of the logic of how genes regulate each other’s activities. Furthermore, the models allow Lagator, Paixão et al. to predict interactions between mutations in several different environments, such as the presence of a new food source or a toxin, defined by the amounts of relevant DNA-binding proteins in cells.

By providing new ways of understanding how genes are regulated in bacteria, and how gene regulation is affected by mutations, these findings contribute to our understanding of how organisms evolve. In addition, this work may help us to build artificial networks of genes that interact with each other to produce a desired response, such as more efficient production of fuel from ethanol or the break down of hazardous chemicals.

DOI:http://dx.doi.org/10.7554/eLife.25192.002

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

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

New Repeat Polymorphism in the AKT1 Gene Predicts Striatal Dopamine D2/D3 Receptor Availability and Stimulant-Induced Dopamine Release in the Healthy Human Brain

The role of the protein kinase Akt1 in dopamine neurotransmission is well recognized and has been implicated in schizophrenia and psychosis. However, the extent to which variants in the AKT1 gene influence dopamine neurotransmission is not well understood. Here we investigated the effect of a newly characterized variant number tandem repeat (VNTR) polymorphism in AKT1 [major alleles: L- (eight repeats) and H- (nine repeats)] on striatal dopamine D2/D3 receptor (DRD2) availability and on dopamine release in healthy volunteers. We used PET and [¹¹C]raclopride to assess baseline DRD2 availability in 91 participants. In 54 of these participants, we also measured intravenous methylphenidate-induced dopamine release to measure dopamine release. Dopamine release was quantified as the difference in specific binding of [¹¹C]raclopride (nondisplaceable binding potential) between baseline values and values following methylphenidate injection. There was an effect of AKT1 genotype on DRD2 availability at baseline for the caudate (F_(2,90) = 8.2, p = 0.001) and putamen (F_(2,90) = 6.6, p = 0.002), but not the ventral striatum (p = 0.3). For the caudate and putamen, LL showed higher DRD2 availability than HH; HL were in between. There was also a significant effect of AKT1 genotype on dopamine increases in the ventral striatum (F_(2,53) = 5.3, p = 0.009), with increases being stronger in HH > HL > LL. However, no dopamine increases were observed in the caudate (p = 0.1) or putamen (p = 0.8) following methylphenidate injection. Our results provide evidence that the AKT1 gene modulates both striatal DRD2 availability and dopamine release in the human brain, which could account for its association with schizophrenia and psychosis. The clinical relevance of the newly characterized AKT1 VNTR merits investigation.SIGNIFICANCE STATEMENT The AKT1 gene has been implicated in schizophrenia and psychosis. This association is likely to reflect modulation of dopamine signaling by Akt1 kinase since striatal dopamine hyperstimulation is associated with psychosis and schizophrenia. Here, using PET with [¹¹C]raclopride, we identified in the AKT1 gene a new variable number tandem repeat (VNTR) marker associated with baseline striatal dopamine D2/D3 receptor availability and with methylphenidate-induced striatal dopamine increases in healthy volunteers. Our results confirm the involvement of the AKT1 gene in modulating striatal dopamine signaling in the human brain. Future studies are needed to assess the association of this new VNTR AKT1 variant in schizophrenia and drug-induced psychoses.

Can We Predict Gene Expression by Understanding Proximal Promoter Architecture?

We review computational predictions of expression from the promoter architecture - the set of transcription factors that can bind the proximal promoter. We focus on spatial expression patterns in animals with complex body plans and many distinct tissue types. This field is ripe for change as functional genomics datasets accumulate for both expression and protein-DNA interactions. While there has been some success in predicting the breadth of expression (i.e., the fraction of tissue types a gene is expressed in), predicting tissue specificity remains challenging. We discuss how progress can be achieved through either machine learning or complementary combinatorial data mining. The likely impact of single-cell expression data is considered. Finally, we discuss the design of artificial promoters as a practical application.

Quality of TCR signaling determined by differential affinities of enhancers for the composite BATF-IRF4 transcription factor complex

Variable strengths of T cell receptor (TCR) signaling can produce divergent outcomes, but the mechanism remains obscure. The abundance of the transcription factor IRF4 increases with TCR signal strength, but how this would induce distinct types of responses is unclear. We compared T_H2 gene expression with BATF/IRF4 enhancer occupancy at varying strengths of TCR stimulation. BATF/IRF4-dependent genes clustered into distinct TCR-sensitivities. Enhancers exhibited a spectrum of occupancy by BATF/IRF4 ternary complex that correlated with TCR-sensitivity of gene expression. DNA sequences immediately flanking the previously defined AICE motif controlled the affinity for BATF/IRF4 for direct binding to DNA. ChIP-exo analysis allowed identification of a novel high-affinity AICE2 motif at a human SNP of CTLA4 associated with resistance to autoimmunity. Thus, the affinity of different enhancers for the BATF-IRF4 complex may underlie divergent signaling outcomes in response to various strengths of TCR signaling.

A CRISPR view of gene regulation

Due to plummeting costs, whole genome sequencing of patients and cancers will soon become routine medical practice; however, we cannot currently predict how non-coding genotype affects cellular gene expression. Gene regulation research has recently been dominated by observational approaches that correlate chromatin state with regulatory function. These approaches are limited to the available genotypes and cannot scratch the surface of possible sequence combinations, and thus there is a need for perturbation-based approaches to better understand how DNA encodes gene regulatory functions. CRISPR/Cas9 genome editing has revolutionized our ability to alter genome sequence, and CRISPR/Cas9-based assays have already begun to contribute to new paradigms of gene regulation. We discuss the variety of arenas in which current and future CRISPR-based technologies will aid in developing predictive understanding of how genome sequence leads to gene regulatory function.

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

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

Identifying Cell Type-Specific Transcription Factors by Integrating ChIP-seq and eQTL Data-Application to Monocyte Gene Regulation

We describe a novel computational approach to identify transcription factors (TFs) that are candidate regulators in a human cell type of interest. Our approach involves integrating cell type-specific expression quantitative trait locus (eQTL) data and TF data from chromatin immunoprecipitation-to-tag-sequencing (ChIP-seq) experiments in cell lines. To test the method, we used eQTL data from human monocytes in order to screen for TFs. Using a list of known monocyte-regulating TFs, we tested the hypothesis that the binding sites of cell type-specific TF regulators would be concentrated in the vicinity of monocyte eQTLs. For each of 397 ChIP-seq data sets, we obtained an enrichment ratio for the number of ChIP-seq peaks that are located within monocyte eQTLs. We ranked ChIP-seq data sets according to their statistical significances for eQTL overlap, and from this ranking, we observed that monocyte-regulating TFs are more highly ranked than would be expected by chance. We identified 27 TFs that had significant monocyte enrichment scores and mapped them into a protein interaction network. Our analysis uncovered two novel candidate monocyte-regulating TFs, BCLAF1 and SIN3A. Our approach is an efficient method to identify candidate TFs that can be used for any cell/tissue type for which eQTL data are available.

Effect of sequence-dependent rigidity on plectoneme localization in dsDNA

We use Monte-Carlo simulations to study the effect of variable rigidity on plectoneme formation and localization in supercoiled double-stranded DNA. We show that the presence of soft sequences increases the number of plectoneme branches and that the edges of the branches tend to be localized at these sequences. We propose an experimental approach to test our results in vitro, and discuss the possible role played by plectoneme localization in the search process of transcription factors for their targets (promoter regions) on the bacterial genome.

The Genetics of Transcription Factor DNA Binding Variation

Most complex trait-associated variants are located in non-coding regulatory regions of the genome, where they have been shown to disrupt transcription factor (TF)-DNA binding motifs. Variable TF-DNA interactions are therefore increasingly considered as key drivers of phenotypic variation. However, recent genome-wide studies revealed that the majority of variable TF-DNA binding events are not driven by sequence alterations in the motif of the studied TF. This observation implies that the molecular mechanisms underlying TF-DNA binding variation and, by extrapolation, inter-individual phenotypic variation are more complex than originally anticipated. Here, we summarize the findings that led to this important paradigm shift and review proposed mechanisms for local, proximal, or distal genetic variation-driven variable TF-DNA binding. In addition, we discuss the biomedical implications of these findings for our ability to dissect the molecular role(s) of non-coding genetic variants in complex traits, including disease susceptibility.

Cistrome and Epicistrome Features Shape the Regulatory DNA Landscape

The cistrome is the complete set of transcription factor (TF) binding sites (cis-elements) in an organism, while an epicistrome incorporates tissue-specific DNA chemical modifications and TF-specific chemical sensitivities into these binding profiles. Robust methods to construct comprehensive cistrome and epicistrome maps are critical for elucidating complex transcriptional networks that underlie growth, behavior, and disease. Here, we describe DNA affinity purification sequencing (DAP-seq), a high-throughput TF binding site discovery method that interrogates genomic DNA with in-vitro-expressed TFs. Using DAP-seq, we defined the Arabidopsis cistrome by resolving motifs and peaks for 529 TFs. Because genomic DNA used in DAP-seq retains 5-methylcytosines, we determined that >75% (248/327) of Arabidopsis TFs surveyed were methylation sensitive, a property that strongly impacts the epicistrome landscape. DAP-seq datasets also yielded insight into the biology and binding site architecture of numerous TFs, demonstrating the value of DAP-seq for cost-effective cistromic and epicistromic annotation in any organism.

Computational inference of gene regulatory networks: Approaches, limitations and opportunities

Gene regulatory networks lie at the core of cell function control. In E. coli and S. cerevisiae, the study of gene regulatory networks has led to the discovery of regulatory mechanisms responsible for the control of cell growth, differentiation and responses to environmental stimuli. In plants, computational rendering of gene regulatory networks is gaining momentum, thanks to the recent availability of high-quality genomes and transcriptomes and development of computational network inference approaches. Here, we review current techniques, challenges and trends in gene regulatory network inference and highlight challenges and opportunities for plant science. We provide plant-specific application examples to guide researchers in selecting methodologies that suit their particular research questions. Given the interdisciplinary nature of gene regulatory network inference, we tried to cater to both biologists and computer scientists to help them engage in a dialogue about concepts and caveats in network inference. Specifically, we discuss problems and opportunities in heterogeneous data integration for eukaryotic organisms and common caveats to be considered during network model evaluation. This article is part of a Special Issue entitled: Plant Gene Regulatory Mechanisms and Networks, edited by Dr. Erich Grotewold and Dr. Nathan Springer.

Sequences flanking the core-binding site modulate glucocorticoid receptor structure and activity

The glucocorticoid receptor (GR) binds as a homodimer to genomic response elements, which have particular sequence and shape characteristics. Here we show that the nucleotides directly flanking the core-binding site, differ depending on the strength of GR-dependent activation of nearby genes. Our study indicates that these flanking nucleotides change the three-dimensional structure of the DNA-binding site, the DNA-binding domain of GR and the quaternary structure of the dimeric complex. Functional studies in a defined genomic context show that sequence-induced changes in GR activity cannot be explained by differences in GR occupancy. Rather, mutating the dimerization interface mitigates DNA-induced changes in both activity and structure, arguing for a role of DNA-induced structural changes in modulating GR activity. Together, our study shows that DNA sequence identity of genomic binding sites modulates GR activity downstream of binding, which may play a role in achieving regulatory specificity towards individual target genes.

Spatiotemporal regulation of enhancers during cardiogenesis

With the advance in chromatin immunoprecipitation followed by high-throughput sequencing, there has been a dramatic increase in our understanding of distal enhancer function. In the developing heart, the identification and characterisation of such enhancers have deepened our knowledge of the mechanisms of transcriptional regulation that drives cardiac differentiation. With next-generation sequencing techniques becoming widely accessible, the quantity of data describing the genome-wide distribution of cardiac-specific transcription factor and chromatin modifiers has rapidly increased and it is now becoming clear that the usage of enhancers is highly dynamic and complex, both during the development and in the adult. The identification of those enhancers has revealed new insights into the transcriptional mechanisms of how tissue-specific gene expression patterns are established, maintained, and change dynamically during development and upon physiological stress.

The role of enhancers in cancer

Enhancer elements function as the logic gates of the genetic regulatory circuitry. One of their most important functions is the integration of extracellular signals with intracellular cell fate information to generate cell type-specific transcriptional responses. Mutations occurring in cancer often misregulate enhancers that normally control the signal-dependent expression of growth-related genes. This misregulation can result from trans-acting mechanisms, such as activation of the transcription factors or epigenetic regulators that control enhancer activity, or can be caused in cis by direct mutations that alter the activity of the enhancer or its target gene specificity. These processes can generate tumour type-specific super-enhancers and establish a 'locked' gene regulatory state that drives the uncontrolled proliferation of cancer cells. Here, we review the role of enhancers in cancer, and their potential as therapeutic targets.

Gene activation by metazoan enhancers: Diverse mechanisms stimulate distinct steps of transcription

Enhancers can stimulate transcription by a number of different mechanisms which control different stages of the transcription cycle of their target genes, from recruitment of the transcription machinery to elongation by RNA polymerase. These mechanisms may not be mutually exclusive, as a single enhancer may act through different pathways by binding multiple transcription factors. Multiple enhancers may also work together to regulate transcription of a shared target gene. Most of the evidence supporting different enhancer mechanisms comes from the study of single genes, but new high-throughput experimental frameworks offer the opportunity to integrate and generalize disparate mechanisms identified at single genes. This effort is especially important if we are to fully understand how sequence variation within enhancers contributes to human disease.

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

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

Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks

The complex language of eukaryotic gene expression remains incompletely understood. Despite the importance suggested by many noncoding variants statistically associated with human disease, nearly all such variants have unknown mechanisms. Here, we address this challenge using an approach based on a recent machine learning advance-deep convolutional neural networks (CNNs). We introduce the open source package Basset to apply CNNs to learn the functional activity of DNA sequences from genomics data. We trained Basset on a compendium of accessible genomic sites mapped in 164 cell types by DNase-seq, and demonstrate greater predictive accuracy than previous methods. Basset predictions for the change in accessibility between variant alleles were far greater for Genome-wide association study (GWAS) SNPs that are likely to be causal relative to nearby SNPs in linkage disequilibrium with them. With Basset, a researcher can perform a single sequencing assay in their cell type of interest and simultaneously learn that cell's chromatin accessibility code and annotate every mutation in the genome with its influence on present accessibility and latent potential for accessibility. Thus, Basset offers a powerful computational approach to annotate and interpret the noncoding genome.

Pooled ChIP-Seq Links Variation in Transcription Factor Binding to Complex Disease Risk

Cis-regulatory elements such as transcription factor (TF) binding sites can be identified genome-wide, but it remains far more challenging to pinpoint genetic variants affecting TF binding. Here, we introduce a pooling-based approach to mapping quantitative trait loci (QTLs) for molecular-level traits. Applying this to five TFs and a histone modification, we mapped thousands of cis-acting QTLs, with over 25-fold lower cost compared to standard QTL mapping. We found that single genetic variants frequently affect binding of multiple TFs, and CTCF can recruit all five TFs to its binding sites. These QTLs often affect local chromatin and transcription but can also influence long-range chromosomal contacts, demonstrating a role for natural genetic variation in chromosomal architecture. Thousands of these QTLs have been implicated in genome-wide association studies, providing candidate molecular mechanisms for many disease risk loci and suggesting that TF binding variation may underlie a large fraction of human phenotypic variation.

Sort-seq under the hood: implications of design choices on large-scale characterization of sequence-function relations

Background

Sort-seq is an effective approach for simultaneous activity measurements in a large-scale library, combining flow cytometry, deep sequencing, and statistical inference. Such assays enable the characterization of functional landscapes at unprecedented scale for a wide-reaching array of biological molecules and functionalities in vivo. Applications of sort-seq range from footprinting to establishing quantitative models of biological systems and rational design of synthetic genetic elements. Nearly as diverse are implementations of this technique, reflecting key design choices with extensive impact on the scope and accuracy the results. Yet how to make these choices remains unclear. Here we investigate the effects of alternative sort-seq designs and inference methods on the information output using mathematical formulation and simulations.

Results

We identify key intrinsic properties of any system of interest with practical implications for sort-seq assays, depending on the experimental goals. The fluorescence range and cell-to-cell variability specify the number of sorted populations needed for quantitative measurements that are precise and unbiased. These factors also indicate cases where an enrichment-based approach that uses a single sorted population can offer satisfactory results. These predications of our model are corroborated using re-analysis of published data. We explore implications of these results for quantitative modeling and library design.

Conclusions

Sort-seq assays can be streamlined by reducing the number of sorted populations, saving considerable resources. Simple preliminary experiments can guide optimal experiment design, minimizing cost while maintaining the maximal information output and avoiding latent biases. These insights can facilitate future applications of this highly adaptable technique.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2533-5) contains supplementary material, which is available to authorized users.

The analysis of novel distal Cebpa enhancers and silencers using a transcriptional model reveals the complex regulatory logic of hematopoietic lineage specification

C/EBPα plays an instructive role in the macrophage-neutrophil cell-fate decision and its expression is necessary for neutrophil development. How Cebpa itself is regulated in the myeloid lineage is not known. We decoded the cis-regulatory logic of Cebpa, and two other myeloid transcription factors, Egr1 and Egr2, using a combined experimental-computational approach. With a reporter design capable of detecting both distal enhancers and silencers, we analyzed 46 putative cis-regulatory modules (CRMs) in cells representing myeloid progenitors, and derived early macrophages or neutrophils. In addition to novel enhancers, this analysis revealed a surprisingly large number of silencers. We determined the regulatory roles of 15 potential transcriptional regulators by testing 32,768 alternative sequence-based transcriptional models against CRM activity data. This comprehensive analysis allowed us to infer the cis-regulatory logic for most of the CRMs. Silencer-mediated repression of Cebpa was found to be effected mainly by TFs expressed in non-myeloid lineages, highlighting a previously unappreciated contribution of long-distance silencing to hematopoietic lineage resolution. The repression of Cebpa by multiple factors expressed in alternative lineages suggests that hematopoietic genes are organized into densely interconnected repressive networks instead of hierarchies of mutually repressive pairs of pivotal TFs. More generally, our results demonstrate that de novo cis-regulatory dissection is feasible on a large scale with the aid of transcriptional modeling. Current address: Department of Biology, University of North Dakota, 10 Cornell Street, Stop 9019, Grand Forks, ND 58202-9019, USA.

Complex Interdependence Regulates Heterotypic Transcription Factor Distribution and Coordinates Cardiogenesis

Transcription factors (TFs) are thought to function with partners to achieve specificity and precise quantitative outputs. In the developing heart, heterotypic TF interactions, such as between the T-box TF TBX5 and the homeodomain TF NKX2-5, have been proposed as a mechanism for human congenital heart defects. We report extensive and complex interdependent genomic occupancy of TBX5, NKX2-5, and the zinc finger TF GATA4 coordinately controlling cardiac gene expression, differentiation, and morphogenesis. Interdependent binding serves not only to co-regulate gene expression but also to prevent TFs from distributing to ectopic loci and activate lineage-inappropriate genes. We define preferential motif arrangements for TBX5 and NKX2-5 cooperative binding sites, supported at the atomic level by their co-crystal structure bound to DNA, revealing a direct interaction between the two factors and induced DNA bending. Complex interdependent binding mechanisms reveal tightly regulated TF genomic distribution and define a combinatorial logic for heterotypic TF regulation of differentiation.

Using synthetic bacterial enhancers to reveal a looping-based mechanism for quenching-like repression

We explore a model for 'quenching-like' repression by studying synthetic bacterial enhancers, each characterized by a different binding site architecture. To do so, we take a three-pronged approach: first, we compute the probability that a protein-bound dsDNA molecule will loop. Second, we use hundreds of synthetic enhancers to test the model's predictions in bacteria. Finally, we verify the mechanism bioinformatically in native genomes. Here we show that excluded volume effects generated by DNA-bound proteins can generate substantial quenching. Moreover, the type and extent of the regulatory effect depend strongly on the relative arrangement of the binding sites. The implications of these results are that enhancers should be insensitive to 10-11 bp insertions or deletions (INDELs) and sensitive to 5-6 bp INDELs. We test this prediction on 61 σ(54)-regulated qrr genes from the Vibrio genus and confirm the tolerance of these enhancers' sequences to the DNA's helical repeat.

Incorporating chromatin accessibility data into sequence-to-expression modeling

Prediction of gene expression levels from regulatory sequences is one of the major challenges of genomic biology today. A particularly promising approach to this problem is that taken by thermodynamics-based models that interpret an enhancer sequence in a given cellular context specified by transcription factor concentration levels and predict precise expression levels driven by that enhancer. Such models have so far not accounted for the effect of chromatin accessibility on interactions between transcription factor and DNA and consequently on gene-expression levels. Here, we extend a thermodynamics-based model of gene expression, called GEMSTAT (Gene Expression Modeling Based on Statistical Thermodynamics), to incorporate chromatin accessibility data and quantify its effect on accuracy of expression prediction. In the new model, called GEMSTAT-A, accessibility at a binding site is assumed to affect the transcription factor's binding strength at the site, whereas all other aspects are identical to the GEMSTAT model. We show that this modification results in significantly better fits in a data set of over 30 enhancers regulating spatial expression patterns in the blastoderm-stage Drosophila embryo. It is important to note that the improved fits result not from an overall elevated accessibility in active enhancers but from the variation of accessibility levels within an enhancer. With whole-genome DNA accessibility measurements becoming increasingly popular, our work demonstrates how such data may be useful for sequence-to-expression models. It also calls for future advances in modeling accessibility levels from sequence and the transregulatory context, so as to predict accurately the effect of cis and trans perturbations on gene expression.

Predicting the impact of promoter variability on regulatory outputs

The increased availability of whole genome sequences calls for quantitative models of global gene expression, yet predicting gene expression patterns directly from genome sequence remains a challenge. We examine the contributions of an individual regulator, the ferrous iron-responsive regulatory element, BqsR, on global patterns of gene expression in Pseudomonas aeruginosa. The position weight matrix (PWM) derived for BqsR uncovered hundreds of likely binding sites throughout the genome. Only a subset of these potential binding sites had a regulatory consequence, suggesting that BqsR/DNA interactions were not captured within the PWM or that the broader regulatory context at each promoter played a greater role in setting promoter outputs. The architecture of the BqsR operator was systematically varied to understand how binding site parameters influence expression. We found that BqsR operator affinity was predicted by the PWM well. At many promoters the surrounding regulatory context, including overlapping operators of BqsR or the presence of RhlR binding sites, were influential in setting promoter outputs. These results indicate more comprehensive models that include local regulatory contexts are needed to develop a predictive understanding of global regulatory outputs.

Epistatic Interactions in the Arabinose Cis-Regulatory Element

Changes in gene expression are an important mode of evolution; however, the proximate mechanism of these changes is poorly understood. In particular, little is known about the effects of mutations within cis binding sites for transcription factors, or the nature of epistatic interactions between these mutations. Here, we tested the effects of single and double mutants in two cis binding sites involved in the transcriptional regulation of the Escherichia coli araBAD operon, a component of arabinose metabolism, using a synthetic system. This system decouples transcriptional control from any posttranslational effects on fitness, allowing a precise estimate of the effect of single and double mutations, and hence epistasis, on gene expression. We found that epistatic interactions between mutations in the araBAD cis-regulatory element are common, and that the predominant form of epistasis is negative. The magnitude of the interactions depended on whether the mutations are located in the same or in different operator sites. Importantly, these epistatic interactions were dependent on the presence of arabinose, a native inducer of the araBAD operon in vivo, with some interactions changing in sign (e.g., from negative to positive) in its presence. This study thus reveals that mutations in even relatively simple cis-regulatory elements interact in complex ways such that selection on the level of gene expression in one environment might perturb regulation in the other environment in an unpredictable and uncorrelated manner.

Massively parallel cis-regulatory analysis in the mammalian central nervous system

Cis-regulatory elements (CREs, e.g., promoters and enhancers) regulate gene expression, and variants within CREs can modulate disease risk. Next-generation sequencing has enabled the rapid generation of genomic data that predict the locations of CREs, but a bottleneck lies in functionally interpreting these data. To address this issue, massively parallel reporter assays (MPRAs) have emerged, in which barcoded reporter libraries are introduced into cells, and the resulting barcoded transcripts are quantified by next-generation sequencing. Thus far, MPRAs have been largely restricted to assaying short CREs in a limited repertoire of cultured cell types. Here, we present two advances that extend the biological relevance and applicability of MPRAs. First, we adapt exome capture technology to instead capture candidate CREs, thereby tiling across the targeted regions and markedly increasing the length of CREs that can be readily assayed. Second, we package the library into adeno-associated virus (AAV), thereby allowing delivery to target organs in vivo. As a proof of concept, we introduce a capture library of about 46,000 constructs, corresponding to roughly 3500 DNase I hypersensitive (DHS) sites, into the mouse retina by ex vivo plasmid electroporation and into the mouse cerebral cortex by in vivo AAV injection. We demonstrate tissue-specific cis-regulatory activity of DHSs and provide examples of high-resolution truncation mutation analysis for multiplex parsing of CREs. Our approach should enable massively parallel functional analysis of a wide range of CREs in any organ or species that can be infected by AAV, such as nonhuman primates and human stem cell–derived organoids.

Predicting functional regulatory SNPs in the human antimicrobial peptide genes DEFB1 and CAMP in tuberculosis and HIV/AIDS

Single nucleotide polymorphisms (SNPs) in transcription factor binding sites (TFBSs) within gene promoter region or enhancers can modify the transcription rate of genes related to complex diseases. These SNPs can be called regulatory SNPs (rSNPs). Data compiled from recent projects, such as the 1000 Genomes Project and ENCODE, has revealed essential information used to perform in silico prediction of the molecular and biological repercussions of SNPs within TFBS. However, most of these studies are very limited, as they only analyze SNPs in coding regions or when applied to promoters, and do not integrate essential biological data like TFBSs, expression profiles, pathway analysis, homotypic redundancy (number of TFBSs for the same TF in a region), chromatin accessibility and others, which could lead to a more accurate prediction. Our aim was to integrate different data in a biologically coherent method to analyze the proximal promoter regions of two antimicrobial peptide genes, DEFB1 and CAMP, that are associated with tuberculosis (TB) and HIV/AIDS. We predicted SNPs within the promoter regions that are more likely to interact with transcription factors (TFs). We also assessed the impact of homotypic redundancy using a novel approach called the homotypic redundancy weight factor (HWF). Our results identified 10 SNPs, which putatively modify the binding affinity of 24 TFs previously identified as related to TB and HIV/AIDS expression profiles (e.g. KLF5, CEBPA and NFKB1 for TB; FOXP2, BRCA1, CEBPB, CREB1, EBF1 and ZNF354C for HIV/AIDS; and RUNX2, HIF1A, JUN/AP-1, NR4A2, EGR1 for both diseases). Validating with the OregAnno database and cell-specific functional/non functional SNPs from additional 13 genes, our algorithm performed 53% sensitivity and 84.6% specificity to detect functional rSNPs using the DNAseI-HUP database. We are proposing our algorithm as a novel in silico method to detect true functional rSNPs in antimicrobial peptide genes. With further improvement, this novel method could be applied to other promoters in order to design probes and to discover new drug targets for complex diseases.

cis Determinants of Promoter Threshold and Activation Timescale

Although the relationship between DNA cis-regulatory sequences and gene expression has been extensively studied at steady state, how cis-regulatory sequences affect the dynamics of gene induction is not known. The dynamics of gene induction can be described by the promoter activation timescale (AcTime) and amplitude threshold (AmpThr). Combining high-throughput microfluidics with quantitative time-lapse microscopy, we control the activation dynamics of the budding yeast transcription factor, Msn2, and reveal how cis-regulatory motifs in 20 promoter variants of the Msn2-target-gene SIP18 affect AcTime and AmpThr. By modulating Msn2 binding sites, we can decouple AmpThr from AcTime and switch the SIP18 promoter class from high AmpThr and slow AcTime to low AmpThr and either fast or slow AcTime. We present a model that quantitatively explains gene-induction dynamics on the basis of the Msn2-binding-site number, TATA box location, and promoter nucleosome organization. Overall, we elucidate the cis-regulatory logic underlying promoter decoding of TF dynamics.

A widespread role of the motif environment in transcription factor binding across diverse protein families

Transcriptional regulation requires the binding of transcription factors (TFs) to short sequence-specific DNA motifs, usually located at the gene regulatory regions. Interestingly, based on a vast amount of data accumulated from genomic assays, it has been shown that only a small fraction of all potential binding sites containing the consensus motif of a given TF actually bind the protein. Recent in vitro binding assays, which exclude the effects of the cellular environment, also demonstrate selective TF binding. An intriguing conjecture is that the surroundings of cognate binding sites have unique characteristics that distinguish them from other sequences containing a similar motif that are not bound by the TF. To test this hypothesis, we conducted a comprehensive analysis of the sequence and DNA shape features surrounding the core-binding sites of 239 and 56 TFs extracted from in vitro HT-SELEX binding assays and in vivo ChIP-seq data, respectively. Comparing the nucleotide content of the regions around the TF-bound sites to the counterpart unbound regions containing the same consensus motifs revealed significant differences that extend far beyond the core-binding site. Specifically, the environment of the bound motifs demonstrated unique sequence compositions, DNA shape features, and overall high similarity to the core-binding motif. Notably, the regions around the binding sites of TFs that belong to the same TF families exhibited similar features, with high agreement between the in vitro and in vivo data sets. We propose that these unique features assist in guiding TFs to their cognate binding sites.

TRIP through the chromatin: a high throughput exploration of enhancer regulatory landscapes

Enhancers are regulatory elements that promote gene expression in a spatio-temporal way and are involved in a wide range of developmental and disease processes. Both the identification and subsequent functional dissection of enhancers are key steps in understanding these processes. Several high-throughput approaches were recently developed for these purposes; however, in almost all cases enhancers are being tested outside their native chromatin context. Until recently, the analysis of enhancer activities at their native genomic locations was low throughput, laborious and time-consuming. Here, we discuss the potential of a powerful approach, TRIP, to study the functioning of enhancers in their native chromatin environments by introducing sensor constructs directly in the genome. TRIP allows for simultaneously analyzing the quantitative readout of numerous sensor constructs integrated at random locations in the genome. The high-throughput and flexible nature of TRIP opens up potential to study different aspects of enhancer biology at an unprecedented level.

Understanding how cis-regulatory function is encoded in DNA sequence using massively parallel reporter assays and designed sequences

Genome-scale methods have identified thousands of candidate cis-regulatory elements (CREs), but methods to directly assay the regulatory function of these elements on a comparably large scale have not been available. The inability to directly test and perturb the regulatory activity of large numbers of DNA sequences has hindered efforts to discover how cis-regulatory function is encoded in genomic sequence. Recently developed massively parallel reporter gene assays combine next generation sequencing with high-throughput oligonucleotide synthesis to offer the capacity to test and mutationally perturb thousands of specifically chosen or designed cis-regulatory sequences in a single experiment. These assays are the basis of recent studies that include large-scale functional validation of genomic CREs, exhaustive mutational analyses of individual regulatory sequences, and tests of large libraries of synthetic CREs. The results demonstrate how massively parallel reporter assays with libraries of designed sequences provide the statistical power required to address previously intractable questions about cis-regulatory function.

Temporal hierarchy of gene expression mediated by transcription factor binding affinity and activation dynamics

Understanding cellular responses to environmental stimuli requires not only the knowledge of specific regulatory components but also the quantitative characterization of the magnitude and timing of regulatory events. The two-component system is one of the major prokaryotic signaling schemes and is the focus of extensive interest in quantitative modeling and investigation of signaling dynamics. Here we report how the binding affinity of the PhoB two-component response regulator (RR) to target promoters impacts the level and timing of expression of PhoB-regulated genes. Information content has often been used to assess the degree of conservation for transcription factor (TF)-binding sites. We show that increasing the information content of PhoB-binding sites in designed phoA promoters increased the binding affinity and that the binding affinity and concentration of phosphorylated PhoB (PhoB~P) together dictate the level and timing of expression of phoA promoter variants. For various PhoB-regulated promoters with distinct promoter architectures, expression levels appear not to be correlated with TF-binding affinities, in contrast to the intuitive and oversimplified assumption that promoters with higher affinity for a TF tend to have higher expression levels. However, the expression timing of the core set of PhoB-regulated genes correlates well with the binding affinity of PhoB~P to individual promoters and the temporal hierarchy of gene expression appears to be related to the function of gene products during the phosphate starvation response. Modulation of the information content and binding affinity of TF-binding sites may be a common strategy for temporal programming of the expression profile of RR-regulated genes.

IMPORTANCE

A single TF often orchestrates the expression of multiple genes in response to environmental stimuli. It is not clear how different TF-binding sites within the regulon dictate the expression profile. Our studies of Escherichia coli PhoB, a response regulator that controls expression of a core set of phosphate assimilation genes in response to phosphate starvation, showed that expression levels of PhoB-regulated genes are under sophisticated control and do not follow a simple correlation with the binding affinity of PhoB~P to individual promoters. However, the expression timing correlates with the PhoB-binding affinity and gene functions. Genes involved in direct Pi uptake contain high-affinity sites and are transcribed earlier than genes involved in phosphorus scavenging. This illustrates an elaborate mechanism of temporally programmed gene expression, even for nondevelopmental pathways.