Diversity and complexity in DNA recognition by transcription factors

DeepD2V: A Novel Deep Learning-Based Framework for Predicting Transcription Factor Binding Sites from Combined DNA Sequence

Predicting in vivo protein-DNA binding sites is a challenging but pressing task in a variety of fields like drug design and development. Most promoters contain a number of transcription factor (TF) binding sites, but only a small minority has been identified by biochemical experiments that are time-consuming and laborious. To tackle this challenge, many computational methods have been proposed to predict TF binding sites from DNA sequence. Although previous methods have achieved remarkable performance in the prediction of protein-DNA interactions, there is still considerable room for improvement. In this paper, we present a hybrid deep learning framework, termed DeepD2V, for transcription factor binding sites prediction. First, we construct the input matrix with an original DNA sequence and its three kinds of variant sequences, including its inverse, complementary, and complementary inverse sequence. A sliding window of size k with a specific stride is used to obtain its k-mer representation of input sequences. Next, we use word2vec to obtain a pre-trained k-mer word distributed representation model. Finally, the probability of protein-DNA binding is predicted by using the recurrent and convolutional neural network. The experiment results on 50 public ChIP-seq benchmark datasets demonstrate the superior performance and robustness of DeepD2V. Moreover, we verify that the performance of DeepD2V using word2vec-based k-mer distributed representation is better than one-hot encoding, and the integrated framework of both convolutional neural network (CNN) and bidirectional LSTM (bi-LSTM) outperforms CNN or the bi-LSTM model when used alone. The source code of DeepD2V is available at the github repository.

G-quadruplexes are transcription factor binding hubs in human chromatin

BACKGROUND

The binding of transcription factors (TF) to genomic targets is critical in the regulation of gene expression. Short, double-stranded DNA sequence motifs are routinely implicated in TF recruitment, but many questions remain on how binding site specificity is governed.

RESULTS

Herein, we reveal a previously unappreciated role for DNA secondary structures as key features for TF recruitment. In a systematic, genome-wide study, we discover that endogenous G-quadruplex secondary structures (G4s) are prevalent TF binding sites in human chromatin. Certain TFs bind G4s with affinities comparable to double-stranded DNA targets. We demonstrate that, in a chromatin context, this binding interaction is competed out with a small molecule. Notably, endogenous G4s are prominent binding sites for a large number of TFs, particularly at promoters of highly expressed genes.

CONCLUSIONS

Our results reveal a novel non-canonical mechanism for TF binding whereby G4s operate as common binding hubs for many different TFs to promote increased transcription.

Logic and lineage impacts on functional transcription factor deployment for T-cell fate commitment

Transcription factors are the major agents that read the regulatory sequence information in the genome to initiate changes in expression of specific genes, both in development and in physiological activation responses. Their actions depend on site-specific DNA binding and are largely guided by their individual DNA target sequence specificities. However, their action is far more conditional in a real developmental context than would be expected for simple reading of local genomic DNA sequence, which is common to all cells in the organism. They are constrained by slow-changing chromatin states and by interactions with other transcription factors, which affect their occupancy patterns of potential sites across the genome. These mechanisms lead to emergent discontinuities in function even for transcription factors with minimally changing expression. This is well revealed by diverse lineages of blood cells developing throughout life from hematopoietic stem cells, which use overlapping combinations of transcription factors to drive strongly divergent gene regulation programs. Here, using development of T lymphocytes from hematopoietic multipotent progenitor cells as a focus, recent evidence is reviewed on how binding specificity and dynamics, transcription factor cooperativity, and chromatin state changes impact the effective regulatory functions of key transcription factors including PU.1, Runx1, Notch-RBPJ, and Bcl11b.

A Bit Stickier, a Bit Slower, a Lot Stiffer: Specific vs. Nonspecific Binding of Gal4 to DNA

Transcription factors regulate gene activity by binding specific regions of genomic DNA thanks to a subtle interplay of specific and nonspecific interactions that is challenging to quantify. Here, we exploit Reflective Phantom Interface (RPI), a label-free biosensor based on optical reflectivity, to investigate the binding of the N-terminal domain of Gal4, a well-known gene regulator, to double-stranded DNA fragments containing or not its consensus sequence. The analysis of RPI-binding curves provides interaction strength and kinetics and their dependence on temperature and ionic strength. We found that the binding of Gal4 to its cognate site is stronger, as expected, but also markedly slower. We performed a combined analysis of specific and nonspecific binding—equilibrium and kinetics—by means of a simple model based on nested potential wells and found that the free energy gap between specific and nonspecific binding is of the order of one kcal/mol only. We investigated the origin of such a small value by performing all-atom molecular dynamics simulations of Gal4–DNA interactions. We found a strong enthalpy–entropy compensation, by which the binding of Gal4 to its cognate sequence entails a DNA bending and a striking conformational freezing, which could be instrumental in the biological function of Gal4.

Stepwise chromatin and transcriptional acquisition of an intraepithelial lymphocyte program

Mesenteric lymph node (mLN) T cells undergo tissue adaptation upon migrating to intestinal lamina propria and epithelium, ensuring appropriate balance between tolerance and resistance. By combining mouse genetics with single-cell and chromatin analyses, we uncovered the molecular imprinting of gut epithelium on T cells. Transcriptionally, conventional and regulatory (Treg) CD4+ T cells from mLN, lamina propria and intestinal epithelium segregate based on the gut layer they occupy; trajectory analysis suggests a stepwise loss of CD4 programming and acquisition of an intraepithelial profile. Treg cell fate mapping coupled with RNA sequencing and assay for transposase-accessible chromatin followed by sequencing revealed that the Treg cell program shuts down before an intraepithelial program becomes fully accessible at the epithelium. Ablation of CD4-lineage-defining transcription factor ThPOK results in premature acquisition of an intraepithelial lymphocyte profile by mLN Treg cells, partially recapitulating epithelium imprinting. Thus, coordinated replacement of the circulating lymphocyte program with site-specific transcriptional and chromatin changes is necessary for tissue imprinting.

Cis-regulatory code for determining the action of Foxd as both an activator and a repressor in ascidian embryos

In early embryos of Ciona, an invertebrate chordate, the animal-vegetal axis is established by the combinatorial actions of maternal factors. One target of these maternal factors, Foxd, is specifically expressed in the vegetal hemisphere and stabilizes the animal-vegetal axis by activating vegetal hemisphere-specific genes and repressing animal hemisphere-specific genes. This dual functionality is essential for the embryogenesis of early ascidian embryos; however, the mechanism by which Foxd can act as both a repressor and an activator is unknown. Here, we identify a Foxd binding site upstream of Lhx3/4, which is activated by Foxd, and compare it with a repressive Foxd binding site upstream of Dmrt.a. We found that activating sites bind Foxd with low affinity while repressive sites bind Foxd with high affinity. Reporter assays confirm that this qualitative difference between activating and repressive Foxd binding sites is sufficient to change Foxd functionality. We therefore conclude that the outcome of Foxd transcriptional regulation is encoded in cis-regulatory elements.

Fast decoding cell type-specific transcription factor binding landscape at single-nucleotide resolution

Decoding the cell type-specific transcription factor (TF) binding landscape at single-nucleotide resolution is crucial for understanding the regulatory mechanisms underlying many fundamental biological processes and human diseases. However, limits on time and resources restrict the high-resolution experimental measurements of TF binding profiles of all possible TF-cell type combinations. Previous computational approaches either cannot distinguish the cell context-dependent TF binding profiles across diverse cell types or can only provide a relatively low-resolution prediction. Here we present a novel deep learning approach, Leopard, for predicting TF binding sites at single-nucleotide resolution, achieving the average area under receiver operating characteristic curve (AUROC) of 0.982 and the average area under precision recall curve (AUPRC) of 0.208. Our method substantially outperformed the state-of-the-art methods Anchor and FactorNet, improving the predictive AUPRC by 19% and 27%, respectively, when evaluated at 200-bp resolution. Meanwhile, by leveraging a many-to-many neural network architecture, Leopard features a hundredfold to thousandfold speedup compared with current many-to-one machine learning methods.

The role of SOX family transcription factors in gastric cancer

Gastric cancer (GC) is a leading cause of death worldwide. GC is the third-most common cause of cancer-related death after lung and colorectal cancer. It is also the fifth-most commonly diagnosed cancer. Accumulating evidence has revealed the role of signaling networks in GC progression. Identification of these molecular pathways can provide new insight into therapeutic approaches for GC. Several molecular factors involved in GC can play both onco-suppressor and oncogene roles. Sex-determining region Y (Sry)-box-containing (SOX) family members are transcription factors with a well-known role in cancer. SOX proteins can bind to DNA to regulate cellular pathways via a highly conserved domain known as high mobility group (HMG). In the present review, the roles of SOX proteins in the progression and/or inhibition of GC are discussed. The dual role of SOX proteins as tumor-promoting and tumor-suppressing factors is highlighted. SOX members can affect upstream mediators (microRNAs, long non-coding RNAs and NF-κB) and down-stream mediators (FAK, HIF-1α, CDX2 and PTEN) in GC. The possible role of anti-tumor compounds to target SOX pathway members in GC therapy is described. Moreover, SOX proteins may be used as diagnostic or prognostic biomarkers in GC.

REL Domain of NFATc2 Binding to Five Types of DNA Using Protein Binding Microarrays

NFATc2 is a DNA binding protein in the Rel family transcription factors, which binds a CGGAA motif better when both cytosines in the CG dinucleotide are methylated. Using protein binding microarrays (PBMs), we examined the DNA binding of NFATc2 to three additional types of DNA: single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) with either 5-methylcytosine (5mC, M) or 5-hydroxymethylcytosine (5hmC, H) in one strand and a cytosine in the second strand. ATTTCCAC, the complement of the core GGAA motif, is better bound as ssDNA compared to dsDNA. dsDNA containing the 5-mer CGGAA with either 5mC or 5hmC in one DNA strand is bound stronger than CGGAA. In contrast, the reverse complement TTCCG is bound weaker when it contains 5mC. Analysis of the available NFATc2:dsDNA complexes rationalizes these PBM data.

Long non-coding RNA PCA3 inhibits lipid accumulation and atherosclerosis through the miR-140-5p/RFX7/ABCA1 axis

OBJECTIVE

The purpose of this study was to explore the role of long noncoding RNA (lncRNA) prostate cancer antigen 3 (PCA3) in atherosclerosis and the underlying mechanism.

METHODS

The Gene Expression Omnibus (GEO) datasets were used to divide differentially expressed lncRNAs, microRNAs (miRNAs), and mRNAs. The expression of PCA3, miR-140-5p, RFX7 and ABCA1 were determined by qPCR or Western blot in ox-LDL-treated macrophages. Macrophage lipid accumulation s was evaluated using the Oil Red O staining and high-performance liquid chromatography. Target relationships among PCA3, miR-140-5p, RFX7, and ABCA1 promoter area were validated via dual-luciferase reporter gene assay or chromatin immunoprecipitation assay. The apoE^-/- mouse model in vivo was designed to evaluate the effect of PCA3 on the reverse cholesterol transport (RCT) and atherosclerosis.

RESULTS

PCA3 was down-regulated in foam cells, whereas miR-140-5p was highly expressed. Overexpression of PCA3 promoted ABCA1-mediated cholesterol efflux and reduced lipid accumulation in macrophages. Besides, RFX7 bound to the ABCA1 promoter and increased ABCA1 expression. Targeted relationships and interactions on the expression between miR-140-5p and PCA3 or RFX7 were elucidated. PCA3 up-regulated ABCA1 expression by binding to miR-140-5p to up-regulate RFX7 and ABCA1 expression in macrophages. PCA3 promoted RCT and impeded the progression of atherosclerosis by sponging miR-140-5p in apoE^-/- mice. Meanwhile, miR-140-5p also inhibit ABCA1 expression via downregulation of RFX7 to impede RCT and aggravate atherosclerosis.

CONCLUSIONS

lncRNA PCA3 promotes ABCA1-mediated cholesterol efflux to inhibit atherosclerosis through sponging miR-140-5p and up-regulating RFX7.

An all-to-all approach to the identification of sequence-specific readers for epigenetic DNA modifications on cytosine

Epigenetic modifications of DNA play important roles in many biological processes. Identifying readers of these epigenetic marks is a critical step towards understanding the underlying mechanisms. Here, we present an all-to-all approach, dubbed digital affinity profiling via proximity ligation (DAPPL), to simultaneously profile human TF-DNA interactions using mixtures of random DNA libraries carrying different epigenetic modifications (i.e., 5-methylcytosine, 5-hydroxymethylcytosine, 5-formylcytosine, and 5-carboxylcytosine) on CpG dinucleotides. Many proteins that recognize consensus sequences carrying these modifications in symmetric and/or hemi-modified forms are identified. We further demonstrate that the modifications in different sequence contexts could either enhance or suppress TF binding activity. Moreover, many modifications can affect TF binding specificity. Furthermore, symmetric modifications show a stronger effect in either enhancing or suppressing TF-DNA interactions than hemi-modifications. Finally, in vivo evidence suggests that USF1 and USF2 might regulate transcription via hydroxymethylcytosine-binding activity in weak enhancers in human embryonic stem cells.

Identifying readers of epigenetic marks is a critical step for understanding the role of epigenetic marks in biology. Here, the authors applied DAPPL, an all-to-all approach to profile the interactions between TFs and epigenetic modified DNA libraries.

Speed-Specificity Trade-Offs in the Transcription Factors Search for Their Genomic Binding Sites

Transcription factors (TFs) regulate gene expression by binding DNA sequences recognized by their DNA-binding domains (DBDs). DBD-recognized motifs are short and highly abundant in genomes. The ability of TFs to bind a specific subset of motif-containing sites, and to do so rapidly upon activation, is fundamental for gene expression in all eukaryotes. Despite extensive interest, our understanding of the TF-target search process is fragmented; although binding specificity and detection speed are two facets of this same process, trade-offs between them are rarely addressed. In this opinion article, we discuss potential speed-specificity trade-offs in the context of existing models. We further discuss the recently described 'distributed specificity' paradigm, suggesting that intrinsically disordered regions (IDRs) promote specificity while reducing the TF-target search time.

High-Throughput Analysis of the Cell and DNA Site-Specific Binding of Native NF-κB Dimers Using Nuclear Extract Protein-Binding Microarrays (NextPBMs)

Nuclear factor-kappa B (NF-κB) transcription factors coordinate gene expression in response to a broad array of cellular signals. In vertebrates, there are five NF-κB proteins (c-Rel, RelA/p65, RelB, p50, and p52) that can form various dimeric combinations exhibiting both common and dimer-specific DNA-binding specificity. In this chapter, we describe the use of the nuclear extract protein-binding microarray (nextPBM), a high-throughput method to characterize the DNA binding of transcription factors present in cell nuclear extracts. NextPBMs allow for sensitive analysis of the DNA binding of NF-κB dimers and their interactions with cell-specific cofactors.

Of numbers and movement - understanding transcription factor pathogenesis by advanced microscopy

Transcription factors (TFs) are life-sustaining and, therefore, the subject of intensive research. By regulating gene expression, TFs control a plethora of developmental and physiological processes, and their abnormal function commonly leads to various developmental defects and diseases in humans. Normal TF function often depends on gene dosage, which can be altered by copy-number variation or loss-of-function mutations. This explains why TF haploinsufficiency (HI) can lead to disease. Since aberrant TF numbers frequently result in pathogenic abnormalities of gene expression, quantitative analyses of TFs are a priority in the field. In vitro single-molecule methodologies have significantly aided the identification of links between TF gene dosage and transcriptional outcomes. Additionally, advances in quantitative microscopy have contributed mechanistic insights into normal and aberrant TF function. However, to understand TF biology, TF-chromatin interactions must be characterised in vivo, in a tissue-specific manner and in the context of both normal and altered TF numbers. Here, we summarise the advanced microscopy methodologies most frequently used to link TF abundance to function and dissect the molecular mechanisms underlying TF HIs. Increased application of advanced single-molecule and super-resolution microscopy modalities will improve our understanding of how TF HIs drive disease.

Phenotypic Mapping of Pathologic Cross-Talk between Glioblastoma and Innate Immune Cells by Synthetic Genetic Tracing

Glioblastoma is a lethal brain tumor that exhibits heterogeneity and resistance to therapy. Our understanding of tumor homeostasis is limited by a lack of genetic tools to selectively identify tumor states and fate transitions. Here, we use glioblastoma subtype signatures to construct synthetic genetic tracing cassettes and investigate tumor heterogeneity at cellular and molecular levels, in vitro and in vivo. Through synthetic locus control regions, we demonstrate that proneural glioblastoma is a hardwired identity, whereas mesenchymal glioblastoma is an adaptive and metastable cell state driven by proinflammatory and differentiation cues and DNA damage, but not hypoxia. Importantly, we discovered that innate immune cells divert glioblastoma cells to a proneural-to-mesenchymal transition that confers therapeutic resistance. Our synthetic genetic tracing methodology is simple, scalable, and widely applicable to study homeostasis in development and diseases. In glioblastoma, the method causally links distinct (micro)environmental, genetic, and pharmacologic perturbations and mesenchymal commitment. SIGNIFICANCE: Glioblastoma is heterogeneous and incurable. Here, we designed synthetic reporters to reflect the transcriptional output of tumor cell states and signaling pathways' activity. This method is generally applicable to study homeostasis in normal tissues and diseases. In glioblastoma, synthetic genetic tracing causally connects cellular and molecular heterogeneity to therapeutic responses.This article is highlighted in the In This Issue feature, p. 521.

Information Theory Can Help Quantify the Potential of New Phenotypes to Originate as Exaptations

Exaptations are adaptive traits that do not originate de novo but from other adaptive traits. They include complex macroscopic traits, such as the middle ear bones of mammals, which originated from reptile jaw bones, but also molecular traits, such as new binding sites of transcriptional regulators. What determines whether a trait originates de novo or as an exaptation is unknown. I here use simple information theoretic concepts to quantify a molecular phenotype’s potential to give rise to new phenotypes. These quantities rely on the amount of genetic information needed to encode a phenotype. I use these quantities to estimate the propensity of new transcription factor binding phenotypes to emerge de novo or exaptively, and do so for 187 mouse transcription factors. I also use them to quantify whether an organism’s viability in one of 10 different chemical environment is likely to arise exaptively. I show that informationally expensive traits are more likely to originate exaptively. Exaptive evolution is only sometimes favored for new transcription factor binding, but it is always favored for the informationally complex metabolic phenotypes I consider. As our ability to genotype evolving populations increases, so will our ability to understand how phenotypes of ever-increasing informational complexity originate in evolution.

Genome-wide analysis of the AREB/ABF gene lineage in land plants and functional analysis of TaABF3 in Arabidopsis

BACKGROUND

Previous studies have shown that ABFs (abscisic acid-responsive transcription factors) are important ABA-signaling components that participate in abiotic stress response. However, little is known about the function of ABFs in Triticum aestivum. In addition, although various ABFs have been identified in other species, the phylogenetic relationship between ABF transcription factors has not been systemically investigated in land plants.

RESULTS

In this study, we systemically collected ABFs from land plants and analyzed the phylogenetic relationship of these ABF genes. The ABF genes are present in all the land plants we investigated, including moss, lycophyte, monocots, and eudicots. Furthermore, these ABF genes are phylogenetically divided into seven subgroups, differentiations that are supported by variation in the gene structure, protein properties, and motif patterns. We further demonstrated that the expression of ABF genes varies among different tissues and developmental stages, and are induced by one or more environmental stresses. Furthermore, we found that three wheat ABFs (TaABF1, TaABF2, and TaABF3) were significantly induced by drought stress. Compared with wild-type (WT) plants, transgenic Arabidopsis plants overexpressing TaABF3 displayed enhanced drought tolerance.

CONCLUSIONS

These results provide important ground work for understanding the phylogenetic relationships between plant ABF genes. Our results also indicate that TaABFs may participate in regulating plant response to abiotic stresses.

Post-translational modification of SOX family proteins: Key biochemical targets in cancer?

Sox proteins are a family of lineage-associated transcription factors. They regulate expression of genes involved in control of self-renewal and multipotency in both developmental and adult stem cells. Overexpression of Sox proteins is frequently observed in many different human cancers. Despite their importance as therapeutic targets, Sox proteins are difficult to 'drug' using structure-based design. However, Sox protein localisation, activity and interaction partners are regulated by a plethora of post-translational modifications (PTMs), such as: phosphorylation, acetylation, sumoylation, methylation, and ubiquitylation. Here we review the various reported post-translational modifications of Sox proteins and their potential functional importance in guiding cell fate processes. The enzymes that regulate these PTMs could be useful targets for anti-cancer drug discovery.

Common variants in signaling transcription-factor-binding sites drive phenotypic variability in red blood cell traits

Genome-wide association studies identify genomic variants associated with human traits and diseases. Most trait-associated variants are located within cell-type-specific enhancers, but the molecular mechanisms governing phenotypic variation are less well understood. Here, we show that many enhancer variants associated with red blood cell (RBC) traits map to enhancers that are co-bound by lineage-specific master transcription factors (MTFs) and signaling transcription factors (STFs) responsive to extracellular signals. The majority of enhancer variants reside on STF and not MTF motifs, perturbing DNA binding by various STFs (BMP/TGF-β-directed SMADs or WNT-induced TCFs) and affecting target gene expression. Analyses of engineered human blood cells and expression quantitative trait loci verify that disrupted STF binding leads to altered gene expression. Our results propose that the majority of the RBC-trait-associated variants that reside on transcription-factor-binding sequences fall in STF target sequences, suggesting that the phenotypic variation of RBC traits could stem from altered responsiveness to extracellular stimuli.

Quantum aspects of evolution: a contribution towards evolutionary explorations of genotype networks via quantum walks

Quantum biology seeks to explain biological phenomena via quantum mechanisms, such as enzyme reaction rates via tunnelling and photosynthesis energy efficiency via coherent superposition of states. However, less effort has been devoted to study the role of quantum mechanisms in biological evolution. In this paper, we used transcription factor networks with two and four different phenotypes, and used classical random walks (CRW) and quantum walks (QW) to compare network search behaviour and efficiency at finding novel phenotypes between CRW and QW. In the network with two phenotypes, at temporal scales comparable to decoherence time TD, QW are as efficient as CRW at finding new phenotypes. In the case of the network with four phenotypes, the QW had a higher probability of mutating to a novel phenotype than the CRW, regardless of the number of mutational steps (i.e. 1, 2 or 3) away from the new phenotype. Before quantum decoherence, the QW probabilities become higher turning the QW effectively more efficient than CRW at finding novel phenotypes under different starting conditions. Thus, our results warrant further exploration of the QW under more realistic network scenarios (i.e. larger genotype networks) in both closed and open systems (e.g. by considering Lindblad terms).

Neutral components show a hierarchical community structure in the genotype-phenotype map of RNA secondary structure

Genotype-phenotype (GP) maps describe the relationship between biological sequences and structural or functional outcomes. They can be represented as networks in which genotypes are the nodes, and one-point mutations between them are the edges. The genotypes that map to the same phenotype form subnetworks consisting of one or multiple disjoint connected components-so-called neutral components (NCs). For the GP map of RNA secondary structure, the NCs have been found to exhibit distinctive network features that can affect the dynamical processes taking place on them. Here, we focus on the community structure of RNA secondary structure NCs. Building on previous findings, we introduce a method to reveal the hierarchical community structure solely from the sequence constraints and composition of the genotypes that form a given NC. Thereby, we obtain modularity values similar to common community detection algorithms, which are much more complex. From this knowledge, we endorse a sampling method that allows a fast exploration of the different communities of a given NC. Furthermore, we introduce a way to estimate the community structure from genotype samples, which is useful when an exhaustive analysis of the NC is not feasible, as is the case for longer sequence lengths.

Multiple Developmental Defects in sox11a Mutant Zebrafish with Features of Coffin-Siris Syndrome

A previous study suggested that human Coffin-Siris syndrome is related to the mutation of SOX11. Since the homozygous SOX11 mutant mice died soon after birth, no suitable model was available for the study of the pathogenic mechanism of Coffin-Siris syndrome. To solve this problem, we generated two viable homozygous zebrafish mutants, sox11a^m/m and sox11b^m/m. We found that the sox11a^m/m mutant possessed Coffin-Siris syndrome features. The sox11a^m/m mutants exhibited growth deficiency from 3.3 hpf embryos to adulthood. Furthermore, the sox11a^m/m mutant also displayed microcephaly, narrow pupillary distance, achondroplasia, and bone deformity in adults. Growth deficiency could be rescued by the injection of sox11a mRNA at the one-cell stage. In addition, the expression levels of genes related to cartilage and bone were downregulated in the sox11a^m/m mutant, indicating that sox11a mainly affected the growth and development of zebrafish by regulating the expression of genes related to skeletal development. Our results indicate that sox11a^m/m mutant zebrafish offered a potential model system to help with the search for pathogenic mechanisms of human Coffin-Siris syndrome.

A compendium of DNA-binding specificities of transcription factors in Pseudomonas syringae

Pseudomonas syringae is a Gram-negative and model pathogenic bacterium that causes plant diseases worldwide. Here, we set out to identify binding motifs for all 301 annotated transcription factors (TFs) of P. syringae using HT-SELEX. We successfully identify binding motifs for 100 TFs. We map functional interactions between the TFs and their targets in virulence-associated pathways, and validate many of these interactions and functions using additional methods such as ChIP-seq, electrophoretic mobility shift assay (EMSA), RT-qPCR, and reporter assays. Our work identifies 25 virulence-associated master regulators, 14 of which had not been characterized as TFs before.

The authors set out to identify binding motifs for all 301 transcription factors of a plant pathogenic bacterium, Pseudomonas syringae, using HT-SELEX. They successfully identify binding motifs for 100 transcription factors, infer their binding sites on the genome, and validate the predicted interactions and functions.

bZIP Dimers CREB1, ATF2, Zta, ATF3|cJun, and cFos|cJun Prefer to Bind to Some Double-Stranded DNA Sequences Containing 5-Formylcytosine and 5-Carboxylcytosine

In mammalian cells, 5-methylcytosine (5mC) occurs in genomic double-stranded DNA (dsDNA) and is enzymatically oxidized to 5-hydroxymethylcytosine (5hmC), then to 5-formylcytosine (5fC), and finally to 5-carboxylcytosine (5caC). These cytosine modifications are enriched in regulatory regions of the genome. The effect of these oxidative products on five bZIP dimers (CREB1, ATF2, Zta, ATF3|cJun, and cFos|cJun) binding to five types of dsDNA was measured using protein binding microarrays. The five dsDNAs contain either cytosine in both DNA strands or cytosine in one strand and either 5mC, 5hmC, 5fC, or 5caC in the second strand. Some sequences containing the CEBP half-site GCAA are bound more strongly by all five bZIP domains when dsDNA contains 5mC, 5hmC, or 5fC. dsDNA containing 5caC in some TRE (AP-1)-like sequences, e.g., TGACTAA, is better bound by Zta, ATF3|cJun, and cFos|cJun.

Mutation bias interacts with composition bias to influence adaptive evolution

Mutation is a biased stochastic process, with some types of mutations occurring more frequently than others. Previous work has used synthetic genotype-phenotype landscapes to study how such mutation bias affects adaptive evolution. Here, we consider 746 empirical genotype-phenotype landscapes, each of which describes the binding affinity of target DNA sequences to a transcription factor, to study the influence of mutation bias on adaptive evolution of increased binding affinity. By using empirical genotype-phenotype landscapes, we need to make only few assumptions about landscape topography and about the DNA sequences that each landscape contains. The latter is particularly important because the set of sequences that a landscape contains determines the types of mutations that can occur along a mutational path to an adaptive peak. That is, landscapes can exhibit a composition bias—a statistical enrichment of a particular type of mutation relative to a null expectation, throughout an entire landscape or along particular mutational paths—that is independent of any bias in the mutation process. Our results reveal the way in which composition bias interacts with biases in the mutation process under different population genetic conditions, and how such interaction impacts fundamental properties of adaptive evolution, such as its predictability, as well as the evolution of genetic diversity and mutational robustness.

Mutation is often depicted as a random process due its unpredictable nature. However, such randomness does not imply uniformly distributed outcomes, because some DNA sequence changes happen more frequently than others. Mutation bias can be an orienting factor in adaptive evolution, influencing the mutational trajectories populations follow toward higher-fitness genotypes. Because these trajectories are typically just a small subset of all possible mutational trajectories, they can exhibit composition bias—an enrichment of a particular kind of DNA sequence change, such as transition or transversion mutations. Here, we use empirical data from eukaryotic transcriptional regulation to study how mutation bias and composition bias interact to influence adaptive evolution.

A High-Throughput Genome-Integrated Assay Reveals Spatial Dependencies Governing Tcf7l2 Binding

Predicting where transcription factors bind in the genome from their in vitro DNA-binding affinity is confounded by the large number of possible interactions with nearby transcription factors. To characterize the in vivo binding logic for the Wnt effector Tcf7l2, we developed a high-throughput screening platform in which thousands of synthesized DNA phrases are inserted into a specific genomic locus, followed by measurement of Tcf7l2 binding by DamID. Using this platform at two genomic loci in mouse embryonic stem cells, we show that while the binding of Tcf7l2 closely follows the in vitro motif-binding strength and is influenced by local chromatin accessibility, it is also strongly affected by the surrounding 99 bp of sequence. Through controlled sequence perturbation, we show that Oct4 and Klf4 motifs promote Tcf7l2 binding, particularly in the adjacent ∼50 bp and oscillating with a 10.8-bp phasing relative to these cofactor motifs, which matches the turn of a DNA helix.

Transcriptional enhancers: from prediction to functional assessment on a genome-wide scale

Enhancers are cis-regulatory sequences located distally to target genes. These sequences consolidate developmental and environmental cues to coordinate gene expression in a tissue-specific manner. Enhancer function and tissue specificity depend on the expressed set of transcription factors, which recognize binding sites and recruit cofactors that regulate local chromatin organization and gene transcription. Unlike other genomic elements, enhancers are challenging to identify because they function independently of orientation, are often distant from their promoters, have poorly defined boundaries, and display no reading frame. In addition, there are no defined genetic or epigenetic features that are unambiguously associated with enhancer activity. Over recent years there have been developments in both empirical assays and computational methods for enhancer prediction. We review genome-wide tools, CRISPR advancements, and high-throughput screening approaches that have improved our ability to both observe and manipulate enhancers in vitro at the level of primary genetic sequences, chromatin states, and spatial interactions. We also highlight contemporary animal models and their importance to enhancer validation. Together, these experimental systems and techniques complement one another and broaden our understanding of enhancer function in development, evolution, and disease.

Chromatin Environment and Cellular Context Specify Compensatory Activity of Paralogous MEF2 Transcription Factors

Compensation among paralogous transcription factors (TFs) confers genetic robustness of cellular processes, but how TFs dynamically respond to paralog depletion on a genome-wide scale in vivo remains incompletely understood. Using single and double conditional knockout of myocyte enhancer factor 2 (MEF2) family TFs in granule neurons of the mouse cerebellum, we find that MEF2A and MEF2D play functionally redundant roles in cerebellar-dependent motor learning. Although both TFs are highly expressed in granule neurons, transcriptomic analyses show MEF2D is the predominant genomic regulator of gene expression in vivo. Strikingly, genome-wide occupancy analyses reveal upon depletion of MEF2D, MEF2A occupancy robustly increases at a subset of sites normally bound to MEF2D. Importantly, sites experiencing compensatory MEF2A occupancy are concentrated within open chromatin and undergo functional compensation for genomic activation and gene expression. Finally, motor activity induces a switch from non-compensatory to compensatory MEF2-dependent gene regulation. These studies uncover genome-wide functional interdependency between paralogous TFs in the brain.

Majidi et al. study how transcription factors respond to paralog depletion by conditionally depleting MEF2A and MEF2D in mouse cerebellum. Depletion of MEF2D induces functionally compensatory genomic occupancy by MEF2A. Compensation occurs within accessible chromatin in a context-dependent manner. This study explores the interdependency between paralogous transcription factors.

SOX2 and squamous cancers

SOX2 is a pleiotropic nuclear transcription factor with major roles in stem cell biology and in development. Over the last 10 years SOX2 has also been implicated as a lineage-specific oncogene, notably in squamous carcinomas but also neurological tumours, particularly glioblastoma. Squamous carcinomas (SQCs) comprise a common group of malignancies for which there are no targeted therapeutic interventions. In this article we review the molecular epidemiological and laboratory evidence linking SOX2 with squamous carcinogenesis, explore in detail the multifaceted impact of SOX2 in SQC, describe areas of uncertainty and highlight areas for potential future research.

Sox17 and β-catenin co-occupy Wnt-responsive enhancers to govern the endoderm gene regulatory network

Lineage specification is governed by gene regulatory networks (GRNs) that integrate the activity of signaling effectors and transcription factors (TFs) on enhancers. Sox17 is a key transcriptional regulator of definitive endoderm development, and yet, its genomic targets remain largely uncharacterized. Here, using genomic approaches and epistasis experiments, we define the Sox17-governed endoderm GRN in Xenopus gastrulae. We show that Sox17 functionally interacts with the canonical Wnt pathway to specify and pattern the endoderm while repressing alternative mesectoderm fates. Sox17 and β-catenin co-occupy hundreds of key enhancers. In some cases, Sox17 and β-catenin synergistically activate transcription apparently independent of Tcfs, whereas on other enhancers, Sox17 represses β-catenin/Tcf-mediated transcription to spatially restrict gene expression domains. Our findings establish Sox17 as a tissue-specific modifier of Wnt responses and point to a novel paradigm where genomic specificity of Wnt/β-catenin transcription is determined through functional interactions between lineage-specific Sox TFs and β-catenin/Tcf transcriptional complexes. Given the ubiquitous nature of Sox TFs and Wnt signaling, this mechanism has important implications across a diverse range of developmental and disease contexts.

Protein-Controlled Actuation of Dynamic Nucleic Acid Networks by Using Synthetic DNA Translators*

Integrating dynamic DNA nanotechnology with protein-controlled actuation will expand our ability to process molecular information. We have developed a strategy to actuate strand displacement reactions using DNA-binding proteins by engineering synthetic DNA translators that convert specific protein-binding events into trigger inputs through a programmed conformational change. We have constructed synthetic DNA networks responsive to two different DNA-binding proteins, TATA-binding protein and Myc-Max, and demonstrated multi-input activation of strand displacement reactions. We achieved protein-controlled regulation of a synthetic RNA and of an enzyme through artificial DNA-based communication, showing the potential of our molecular system in performing further programmable tasks.

Cancer and SOX proteins: New insight into their role in ovarian cancer progression/inhibition

Transcription factors are potential targets in disease therapy, particularly in cancer. This is due to the fact that transcription factors regulate a variety of cellular events, and their modulation has opened a new window in cancer therapy. Sex-determining region Y (SRY)-related high-mobility group (HMG) box (SOX) proteins are potential transcription factors that are involved in developmental processes such as embryogenesis. It has been reported that abnormal expression of SOX proteins is associated with development of different cancers, particularly ovarian cancer (OC). In the present review, our aim is to provide a mechanistic review of involvement of SOX members in OC. SOX members may suppress and/or promote aggressiveness and proliferation of OC cells. Clinical studies have also confirmed the potential of transcription factors as diagnostic and prognostic factors in OC. Notably, studies have demonstrated the relationship between SOX members and other molecular pathways such as ST6Ga1-I, PI3K, ERK and so on, leading to more complexity. Furthermore, SOX members can be affected by upstream mediators such as microRNAs, long non-coding RNAs, and so on. It is worth mentioning that the expression of each member of SOX proteins is corelated with different stages of OC. Furthermore, their expression determines the response of OC cells to chemotherapy. These topics are discussed in this review to shed some light on role of SOX transcription factors in OC.

Systematized reporter assays reveal ZIC protein regulatory abilities are Subclass-specific and dependent upon transcription factor binding site context

The ZIC proteins are a family of transcription regulators with a well-defined zinc finger DNA-binding domain and there is evidence that they elicit functional DNA binding at a ZIC DNA binding site. Little is known, however, regarding domains within ZIC proteins that confer trans-activation or -repression. To address this question, a new cell-based trans-activation assay system suitable for ZIC proteins in HEK293T cells was constructed. This identified two previously unannotated evolutionarily conserved regions of ZIC3 that are necessary for trans-activation. These domains are found in all Subclass A ZIC proteins, but not in the Subclass B proteins. Additionally, the Subclass B proteins fail to elicit functional binding at a multimerised ZIC DNA binding site. All ZIC proteins, however, exhibit functional binding when the ZIC DNA binding site is embedded in a multiple transcription factor locus derived from ZIC target genes in the mouse genome. This ability is due to several domains, some of which are found in all ZIC proteins, that exhibit context dependent trans-activation or -repression activity. This knowledge is valuable for assessing the likely pathogenicity of variant ZIC proteins associated with human disorders and for determining factors that influence functional transcription factor binding.

ZIC3 Controls the Transition from Naive to Primed Pluripotency

Embryonic stem cells (ESCs) must transition through a series of intermediate cell states before becoming terminally differentiated. Here, we investigated the early events in this transition by determining the changes in the open chromatin landscape as naive mouse ESCs transition to epiblast-like cells (EpiLCs). Motif enrichment analysis of the newly opening regions coupled with expression analysis identified ZIC3 as a potential regulator of this cell fate transition. Chromatin binding and genome-wide transcriptional profiling following Zic3 depletion confirmed ZIC3 as an important regulatory transcription factor, and among its targets are genes encoding a number of transcription factors. Among these is GRHL2, which acts through enhancer switching to maintain the expression of a subset of genes from the ESC state. Our data therefore place ZIC3 upstream of a set of pro-differentiation transcriptional regulators and provide an important advance in our understanding of the regulatory factors governing the early steps in ESC differentiation.

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Transcription factor ZIC3 regulates gene expression during the ESC to EpiLC transition

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Extensive changes occur in the open chromatin landscape as ESCs progress to EpiLCs

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ZIC3 activates the expression of a network of transcription factors

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ZIC3-activated genes in EpiLCs are upregulated in the post-implantation epiblast

Custom G4 Microarrays Reveal Selective G-Quadruplex Recognition of Small Molecule BMVC: A Large-Scale Assessment of Ligand Binding Selectivity

G-quadruplexes (G4) are considered new drug targets for human diseases such as cancer. More than 10,000 G4s have been discovered in human chromatin, posing challenges for assessing the selectivity of a G4-interactive ligand. 3,6-bis(1-Methyl-4-vinylpyridinium) carbazole diiodide (BMVC) is the first fluorescent small molecule for G4 detection in vivo. Our previous structural study shows that BMVC binds to the MYC promoter G4 (MycG4) with high specificity. Here, we utilize high-throughput, large-scale custom DNA G4 microarrays to analyze the G4-binding selectivity of BMVC. BMVC preferentially binds to the parallel MycG4 and selectively recognizes flanking sequences of parallel G4s, especially the 3′-flanking thymine. Importantly, the microarray results are confirmed by orthogonal NMR and fluorescence binding analyses. Our study demonstrates the potential of custom G4 microarrays as a platform to broadly and unbiasedly assess the binding selectivity of G4-interactive ligands, and to help understand the properties that govern molecular recognition.

SArKS: de novo discovery of gene expression regulatory motif sites and domains by suffix array kernel smoothing

MOTIVATION

We set out to develop an algorithm that can mine differential gene expression data to identify candidate cell type-specific DNA regulatory sequences. Differential expression is usually quantified as a continuous score-fold-change, test-statistic, P-value-comparing biological classes. Unlike existing approaches, our de novo strategy, termed SArKS, applies non-parametric kernel smoothing to uncover promoter motif sites that correlate with elevated differential expression scores. SArKS detects motif k-mers by smoothing sequence scores over sequence similarity. A second round of smoothing over spatial proximity reveals multi-motif domains (MMDs). Discovered motif sites can then be merged or extended based on adjacency within MMDs. False positive rates are estimated and controlled by permutation testing.

RESULTS

We applied SArKS to published gene expression data representing distinct neocortical neuron classes in Mus musculus and interneuron developmental states in Homo sapiens. When benchmarked against several existing algorithms using a cross-validation procedure, SArKS identified larger motif sets that formed the basis for regression models with higher correlative power.

AVAILABILITY AND IMPLEMENTATION

https://github.com/denniscwylie/sarks.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The geometric influence on the Cys2His2 zinc finger domain and functional plasticity

The Cys₂His₂ zinc finger is the most common DNA-binding domain expanding in metazoans since the fungi human split. A proposed catalyst for this expansion is an arms race to silence transposable elements yet it remains poorly understood how this domain is able to evolve the required specificities. Likewise, models of its DNA binding specificity remain error prone due to a lack of understanding of how adjacent fingers influence each other's binding specificity. Here, we use a synthetic approach to exhaustively investigate binding geometry, one of the dominant influences on adjacent finger function. By screening over 28 billion protein–DNA interactions in various geometric contexts we find the plasticity of the most common natural geometry enables more functional amino acid combinations across all targets. Further, residues that define this geometry are enriched in genomes where zinc fingers are prevalent and specificity transitions would be limited in alternative geometries. Finally, these results demonstrate an exhaustive synthetic screen can produce an accurate model of domain function while providing mechanistic insight that may have assisted in the domains expansion.

IGAP-integrative genome analysis pipeline reveals new gene regulatory model associated with nonspecific TF-DNA binding affinity

The human genome is regulated in a multi-dimensional way. While biophysical factors like Non-specific Transcription factor Binding Affinity (nTBA) act at DNA sequence level, other factors act above sequence levels such as histone modifications and 3-D chromosomal interactions. This multidimensionality of regulation requires many of these factors for a proper understanding of the regulatory landscape of the human genome. Here, we propose a new biophysical model for estimating nTBA. Integration of nTBA with chromatin modifications and chromosomal interactions, using a new Integrative Genome Analysis Pipeline (IGAP), reveals additive effects of nTBA to regulatory DNA sequences and identifies three types of genomic zones in the human genome (Inactive Genomic Zones, Poised Genomic Zones, and Active Genomic Zones). It also unveils a novel long distance gene regulatory model: chromosomal interactions reduce the physical distance between the high occupancy target (HOT) regions that results in high nTBA to DNA in the area, which in turn attract TFs to such regions with higher binding potential. These findings will help to elucidate the three-dimensional diffusion process that TFs use during their search for the right targets.

High throughput approaches to study RNA-protein interactions in vitro

To understand the regulation of gene expression it is critical to determine how proteins interact with and discriminate between different RNAs. In this review, we discuss experimental techniques that utilize high throughput approaches to characterize the interactions of proteins with large numbers of RNAs in vitro. We describe the underlying principles for the main methods, briefly discuss their scope and limitations, and outline how insight from the techniques contributes to our understanding of specificity for RNA-protein interactions.

Sequence and chromatin determinants of transcription factor binding and the establishment of cell type-specific binding patterns

Transcription factors (TFs) selectively bind distinct sets of sites in different cell types. Such cell type-specific binding specificity is expected to result from interplay between the TF's intrinsic sequence preferences, cooperative interactions with other regulatory proteins, and cell type-specific chromatin landscapes. Cell type-specific TF binding events are highly correlated with patterns of chromatin accessibility and active histone modifications in the same cell type. However, since concurrent chromatin may itself be a consequence of TF binding, chromatin landscapes measured prior to TF activation provide more useful insights into how cell type-specific TF binding events became established in the first place. Here, we review the various sequence and chromatin determinants of cell type-specific TF binding specificity. We identify the current challenges and opportunities associated with computational approaches to characterizing, imputing, and predicting cell type-specific TF binding patterns. We further focus on studies that characterize TF binding in dynamic regulatory settings, and we discuss how these studies are leading to a more complex and nuanced understanding of dynamic protein-DNA binding activities. We propose that TF binding activities at individual sites can be viewed along a two-dimensional continuum of local sequence and chromatin context. Under this view, cell type-specific TF binding activities may result from either strongly favorable sequence features or strongly favorable chromatin context.

The function of architecture and logic in developmental gene regulatory networks

An important contribution of systems biology is the insight that biological systems depend on the function of molecular interactions and not just on individual molecules. System level mechanisms are particularly important in the development of animals and plants which depends not just on transcription factors and signaling molecules, but also on regulatory circuits and gene regulatory networks (GRNs). However, since GRNs consist of transcription factors, it can be challenging to assess the function of regulatory circuits independently of the function of regulatory factors. The comparison of different GRNs offers a way to do so and leads to several observations. First, similar regulatory circuits operate in various developmental contexts and in different species, and frequently, these circuits are associated with similar developmental functions. Second, given regulatory circuits are often used at particular positions within the GRN hierarchy. Third, in some GRNs, regulatory circuits are organized in a particular order in respect to each other. And fourth, the evolution of GRNs occurs not just by co-option of regulatory genes but also by rewiring of regulatory linkages between conserved regulatory genes, indicating that the organization of interactions is important. Thus, even though in most instances the function of regulatory circuits remains to be discovered, it becomes evident that the architecture and logic of GRNs are functionally important for the control of genome activity and for the specification of the body plan.