Homotypic clusters of transcription factor binding sites: A model system for understanding the physical mechanics of gene expression

Evolution and Comparative Genomics of the Transforming Growth Factor-β-Related Proteins in Nile Tilapia

The members of the transforming growth factor β (TGF-β) family of cell signaling polypeptides have garnered a great deal of interest due to its capacity from nematodes to mammals to regulate cell-based activities which control the growth of embryos and sustain tissue homeostasis. The current study designed a computational analysis of the TGF-β protein family for understanding these proteins at the molecular level. This study determined the genomic structure of TGF-β gene family in Nile tilapia for the first time. We chose 33 TGF-β genes for identification and divided them into two subgroups, TGF-like and BMP-like. Moreover, the subcellular localization of the Nile tilapia TGF-β proteins have showed that majority of the members of TGF-β proteins family are present into extracellular matrix and plasma except BMP6, BMP7, and INHAC. All TGF-β proteins were thermostable excluding BMP1. Each protein exhibited basic nature, excluding of BMP1, BMP2, BMP7, BMP10, GDF2, GDF8, GDF11, AMH, INHA, INHBB, and NODAL M. All proteins gave impression of being unstable depending on the instability index, having values exceeding 40 excluding BMP1 and BMP2. Each TGF-β protein was found to be hydrophobic with lowered values of GRAVY. Moreover, every single one of the discovered TGF-β genes had a consistent evolutionary pattern. The TGF-β gene family had eight segmental duplications, and the Ka/Ks ratio demonstrated that purifying selection had an impact on the duplicated gene pairs which have experienced selection pressure. This study highlights important functionality of TGF-β and depicts the demand for further investigation to better understand the role and mechanism of transforming growth factor β in fishes and other species.

Genome-wide mapping of DNase I hypersensitive sites revealed differential chromatin accessibility and regulatory DNA elements under drought stress in rice cultivars

Drought stress (DS) is one of the major constraints limiting yield in crop plants including rice. Gene regulation under DS is largely governed by accessibility of the transcription factors (TFs) to their cognate cis-regulatory elements (CREs). In this study, we used DNase I hypersensitive assays followed by sequencing to identify the accessible chromatin regions under DS in a drought-sensitive (IR64) and a drought-tolerant (N22) rice cultivar. Our results indicated that DNase I hypersensitive sites (DHSs) were highly enriched at transcription start sites (TSSs) and numerous DHSs were detected in the promoter regions. DHSs were concurrent with epigenetic marks and the genes harboring DHSs in their TSS and promoter regions were highly expressed. In addition, DS induced changes in DHSs (∆DHSs) in TSS and promoter regions were positively correlated with upregulation of several genes involved in drought/abiotic stress response, those encoding TFs and located within drought-associated quantitative trait loci, much preferentially in the drought-tolerant cultivar. The CREs representing the binding sites of TFs involved in DS response were detected within the ∆DHSs, suggesting differential accessibility of TFs to their cognate sites under DS in different rice cultivars, which may be further deployed for enhancing drought tolerance in rice.

Identification of functional enhancer variants associated with type I diabetes in CD4+ T cells

Type I diabetes is an autoimmune disease mediated by T-cell destruction of β cells in pancreatic islets. Currently, there is no known cure, and treatment consists of daily insulin injections. Genome-wide association studies and twin studies have indicated a strong genetic heritability for type I diabetes and implicated several genes. As most strongly associated variants are noncoding, there is still a lack of identification of functional and, therefore, likely causal variants. Given that many of these genetic variants reside in enhancer elements, we have tested 121 CD4+ T-cell enhancer variants associated with T1D. We found four to be functional through massively parallel reporter assays. Three of the enhancer variants weaken activity, while the fourth strengthens activity. We link these to their cognate genes using 3D genome architecture or eQTL data and validate them using CRISPR editing. Validated target genes include CLEC16A and SOCS1. While these genes have been previously implicated in type 1 diabetes and other autoimmune diseases, we show that enhancers controlling their expression harbor functional variants. These variants, therefore, may act as causal type 1 diabetic variants.

Less-is-more: selecting transcription factor binding regions informative for motif inference

Numerous statistical methods have emerged for inferring DNA motifs for transcription factors (TFs) from genomic regions. However, the process of selecting informative regions for motif inference remains understudied. Current approaches select regions with strong ChIP-seq signal for a given TF, assuming that such strong signal primarily results from specific interactions between the TF and its motif. Additionally, these selection approaches do not account for non-target motifs, i.e. motifs of other TFs; they presume the occurrence of these non-target motifs infrequent compared to that of the target motif, and thus assume these have minimal interference with the identification of the target. Leveraging extensive ChIP-seq datasets, we introduced the concept of TF signal 'crowdedness', referred to as C-score, for each genomic region. The C-score helps in highlighting TF signals arising from non-specific interactions. Moreover, by considering the C-score (and adjusting for the length of genomic regions), we can effectively mitigate interference of non-target motifs. Using these tools, we find that in many instances, strong ChIP-seq signal stems mainly from non-specific interactions, and the occurrence of non-target motifs significantly impacts the accurate inference of the target motif. Prioritizing genomic regions with reduced crowdedness and short length markedly improves motif inference. This 'less-is-more' effect suggests that ChIP-seq region selection warrants more attention.

MORA and EnsembleTFpredictor: An ensemble approach to reveal functional transcription factor regulatory networks

MOTIVATION

Our study aimed to identify biologically relevant transcription factors (TFs) that control the expression of a set of co-expressed or co-regulated genes.

RESULTS

We developed a fully automated pipeline, Motif Over Representation Analysis (MORA), to detect enrichment of known TF binding motifs in any query sequences. MORA performed better than or comparable to five other TF-prediction tools as evaluated using hundreds of differentially expressed gene sets and ChIP-seq datasets derived from known TFs. Additionally, we developed EnsembleTFpredictor to harness the power of multiple TF-prediction tools to provide a list of functional TFs ranked by prediction confidence. When applied to the test datasets, EnsembleTFpredictor not only identified the target TF but also revealed many TFs known to cooperate with the target TF in the corresponding biological systems. MORA and EnsembleTFpredictor have been used in two publications, demonstrating their power in guiding experimental design and in revealing novel biological insights.

High-throughput data and modeling reveal insights into the mechanisms of cooperative DNA-binding by transcription factor proteins

Cooperative DNA-binding by transcription factor (TF) proteins is critical for eukaryotic gene regulation. In the human genome, many regulatory regions contain TF-binding sites in close proximity to each other, which can facilitate cooperative interactions. However, binding site proximity does not necessarily imply cooperative binding, as TFs can also bind independently to each of their neighboring target sites. Currently, the rules that drive cooperative TF binding are not well understood. In addition, it is oftentimes difficult to infer direct TF-TF cooperativity from existing DNA-binding data. Here, we show that in vitro binding assays using DNA libraries of a few thousand genomic sequences with putative cooperative TF-binding events can be used to develop accurate models of cooperativity and to gain insights into cooperative binding mechanisms. Using factors ETS1 and RUNX1 as our case study, we show that the distance and orientation between ETS1 sites are critical determinants of cooperative ETS1-ETS1 binding, while cooperative ETS1-RUNX1 interactions show more flexibility in distance and orientation and can be accurately predicted based on the affinity and sequence/shape features of the binding sites. The approach described here, combining custom experimental design with machine-learning modeling, can be easily applied to study the cooperative DNA-binding patterns of any TFs.

Identifying the Gene Regulatory Network of the Starvation-Induced Transcriptional Activator Nla28

Myxococcus xanthus copes with starvation by producing fruiting bodies filled with dormant and stress-resistant spores. Here, we aimed to better define the gene regulatory network associated with Nla28, a transcriptional activator/enhancer binding protein (EBP) and a key regulator of the early starvation response. Previous work showed that Nla28 directly regulates EBP genes that are important for fruiting body development. However, the Nla28 regulatory network is likely to be much larger because hundreds of starvation-induced genes are downregulated in a nla28 mutant strain. To identify candidates for direct Nla28-mediated transcription, we analyzed the downregulated genes using a bioinformatics approach. Nine potential Nla28 target promoters (29 genes) were discovered. The results of in vitro promoter binding assays, coupled with in vitro and in vivo mutational analyses, suggested that the nine promoters along with three previously identified EBP gene promoters were indeed in vivo targets of Nla28. These results also suggested that Nla28 used tandem, imperfect repeats of an 8-bp sequence for promoter binding. Interestingly, eight of the new Nla28 target promoters were predicted to be intragenic. Based on mutational analyses, the newly identified Nla28 target loci contained at least one gene that was important for starvation-induced development. Most of these loci contained genes predicted to be involved in metabolic or defense-related functions. Using the consensus Nla28 binding sequence, bioinformatics, and expression profiling, 58 additional promoters and 102 genes were tagged as potential Nla28 targets. Among these putative Nla28 targets, functions, such as regulatory, metabolic, and cell envelope biogenesis, were assigned to many genes. IMPORTANCE In bacteria, starvation leads to profound changes in behavior and physiology. Some of these changes have economic and health implications because the starvation response has been linked to the formation of biofilms, virulence, and antibiotic resistance. To better understand how starvation contributes to changes in bacterial physiology and resistance, we identified the putative starvation-induced gene regulatory network associated with Nla28, a transcriptional activator from the bacterium Myxoccocus xanthus. We determined the mechanism by which starvation-responsive genes were activated by Nla28 and showed that several of the genes were important for the formation of a highly resistant cell type.

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

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

FOXL2 and FOXA1 cooperatively assemble on the TP53 promoter in alternative dimer configurations

Although both the p53 and forkhead box (FOX) family proteins are key transcription factors associated with cancer progression, their direct relationship is unknown. Here, we found that FOX family proteins bind to the non-canonical homotypic cluster of the p53 promoter region (TP53). Analysis of crystal structures of FOX proteins (FOXL2 and FOXA1) bound to the p53 homotypic cluster indicated that they interact with a 2:1 stoichiometry accommodated by FOX-induced DNA allostery. In particular, FOX proteins exhibited distinct dimerization patterns in recognition of the same p53-DNA; dimer formation of FOXA1 involved protein–protein interaction, but FOXL2 did not. Biochemical and biological functional analyses confirmed the cooperative binding of FOX proteins to the TP53 promoter for the transcriptional activation of TP53. In addition, up-regulation of TP53 was necessary for FOX proteins to exhibit anti-proliferative activity in cancer cells. These analyses reveal the presence of a discrete characteristic within FOX family proteins in which FOX proteins regulate the transcription activity of the p53 tumor suppressor via cooperative binding to the TP53 promoter in alternative dimer configurations.

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

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

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

TFEB Regulates ATP7B Expression to Promote Platinum Chemoresistance in Human Ovarian Cancer Cells

ATP7B is a hepato-specific Golgi-located ATPase, which plays a key role in the regulation of copper (Cu) homeostasis and signaling. In response to elevated Cu levels, ATP7B traffics from the Golgi to endo-lysosomal structures, where it sequesters excess copper and further promotes its excretion to the bile at the apical surface of hepatocytes. In addition to liver, high ATP7B expression has been reported in tumors with elevated resistance to platinum (Pt)-based chemotherapy. Chemoresistance to Pt drugs represents the current major obstacle for the treatment of large cohorts of cancer patients. Although the mechanisms underlying Pt-tolerance are still ambiguous, accumulating evidence suggests that lysosomal sequestration of Pt drugs by ion transporters (including ATP7B) might significantly contribute to drug resistance development. In this context, signaling mechanisms regulating the expression of transporters such as ATP7B are of great importance. Considering this notion, we investigated whether ATP7B expression in Pt-resistant cells might be driven by transcription factor EB (TFEB), a master regulator of lysosomal gene transcription. Using resistant ovarian cancer IGROV-CP20 cells, we found that TFEB directly binds to the predicted coordinated lysosomal expression and regulation (CLEAR) sites in the proximal promoter and first intron region of ATP7B upon Pt exposure. This binding accelerates transcription of luciferase reporters containing ATP7B CLEAR regions, while suppression of TFEB inhibits ATP7B expression and stimulates cisplatin toxicity in resistant cells. Thus, these data have uncovered a Pt-dependent transcriptional mechanism that contributes to cancer chemoresistance and might be further explored for therapeutic purposes.

Transcription Factor Dynamics

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

Mechanisms of Binding Specificity among bHLH Transcription Factors

The transcriptome of every cell is orchestrated by the complex network of interaction between transcription factors (TFs) and their binding sites on DNA. Disruption of this network can result in many forms of organism malfunction but also can be the substrate of positive natural selection. However, understanding the specific determinants of each of these individual TF-DNA interactions is a challenging task as it requires integrating the multiple possible mechanisms by which a given TF ends up interacting with a specific genomic region. These mechanisms include DNA motif preferences, which can be determined by nucleotide sequence but also by DNA’s shape; post-translational modifications of the TF, such as phosphorylation; and dimerization partners and co-factors, which can mediate multiple forms of direct or indirect cooperative binding. Binding can also be affected by epigenetic modifications of putative target regions, including DNA methylation and nucleosome occupancy. In this review, we describe how all these mechanisms have a role and crosstalk in one specific family of TFs, the basic helix-loop-helix (bHLH), with a very conserved DNA binding domain and a similar DNA preferred motif, the E-box. Here, we compile and discuss a rich catalog of strategies used by bHLH to acquire TF-specific genome-wide landscapes of binding sites.

ZNF410 represses fetal globin by singular control of CHD4

Known fetal hemoglobin (HbF) silencers have potential on-target liabilities for rational β-hemoglobinopathy therapeutic inhibition. Here, through transcription factor (TF) CRISPR screening, we identify zinc-finger protein (ZNF) 410 as an HbF repressor. ZNF410 does not bind directly to the genes encoding γ-globins, but rather its chromatin occupancy is concentrated solely at CHD4, encoding the NuRD nucleosome remodeler, which is itself required for HbF repression. CHD4 has two ZNF410-bound regulatory elements with 27 combined ZNF410 binding motifs constituting unparalleled genomic clusters. These elements completely account for the effects of ZNF410 on fetal globin repression. Knockout of ZNF410 or its mouse homolog Zfp410 reduces CHD4 levels by 60%, enough to substantially de-repress HbF while eluding cellular or organismal toxicity. These studies suggest a potential target for HbF induction for β-hemoglobin disorders with a wide therapeutic index. More broadly, ZNF410 represents a special class of gene regulator, a conserved TF with singular devotion to regulation of a chromatin subcomplex.

Carbon Catabolite Repression Governs Diverse Physiological Processes and Development in Aspergillus nidulans

Carbon catabolite repression (CCR) is a common phenomenon of microorganisms that enable efficient utilization of carbon nutrients, critical for the fitness of microorganisms in the wild and for pathogenic species to cause infection. In most filamentous fungal species, the conserved transcription factor CreA/Cre1 mediates CCR. Previous studies demonstrated a primary function for CreA/Cre1 in carbon metabolism; however, the phenotype of creA/cre1 mutants indicated broader roles. The global function and regulatory mechanism of this wide-domain transcription factor has remained elusive. Here, we applied two powerful genomics methods (transcriptome sequencing and chromatin immunoprecipitation sequencing) to delineate the direct and indirect roles of Aspergillus nidulans CreA across diverse physiological processes, including secondary metabolism, iron homeostasis, oxidative stress response, development, N-glycan biosynthesis, unfolded protein response, and nutrient and ion transport. The results indicate intricate connections between the regulation of carbon metabolism and diverse cellular functions. Moreover, our work also provides key mechanistic insights into CreA regulation and identifies CreA as a master regulator controlling many transcription factors of different regulatory networks. The discoveries for this highly conserved transcriptional regulator in a model fungus have important implications for CCR in related pathogenic and industrial species. IMPORTANCE The ability to scavenge and use a wide range of nutrients for growth is crucial for microorganisms' survival in the wild. Carbon catabolite repression (CCR) is a transcriptional regulatory phenomenon of both bacteria and fungi to coordinate the expression of genes required for preferential utilization of carbon sources. Since carbon metabolism is essential for growth, CCR is central to the fitness of microorganisms. In filamentous fungi, CCR is mediated by the conserved transcription factor CreA/Cre1, whose function in carbon metabolism has been well established. However, the global roles and regulatory mechanism of CreA/Cre1 are poorly defined. This study uncovers the direct and indirect functions of CreA in the model organism Aspergillus nidulans over diverse physiological processes and development and provides mechanistic insights into how CreA controls different regulatory networks. The work also reveals an interesting functional divergence between filamentous fungal and yeast CreA/Cre1 orthologues.

Evidence of widespread, independent sequence signature for transcription factor cobinding

Transcription factors (TFs) are the vocabulary that genomes use to regulate gene expression and phenotypes. The interactions among TFs enrich this vocabulary and orchestrate diverse biological processes. Although simple models identify open chromatin and the presence of TF motifs as the two major contributors to TF binding patterns, it remains elusive what contributes to the in vivo TF cobinding landscape. In this study, we developed a machine learning algorithm to explore the contributors of the cobinding patterns. The algorithm substantially outperforms the state-of-the-field models for TF cobinding prediction. Game theory-based feature importance analysis reveals that, for most of the TF pairs we studied, independent motif sequences contribute one or more of the two TFs under investigation to their cobinding patterns. Such independent motif sequences include, but are not limited to, transcription initiation-related proteins and known TF complexes. We found the motif sequence signatures and the TFs are rarely mutual, corroborating a hierarchical and directional organization of the regulatory network and refuting the possibility of artifacts caused by shared sequence similarity with the TFs under investigation. We modeled such regulatory language with directed graphs, which reveal shared, global factors that are related to many binding and cobinding patterns.

Regulation of Cell Type-Specific Immunity Networks in Arabidopsis Roots

While root diseases are among the most devastating stresses in global crop production, our understanding of root immunity is still limited relative to our knowledge of immune responses in leaves. Considering that root performance is based on the concerted functions of its different cell types, we undertook a cell type-specific transcriptome analysis to identify gene networks activated in epidermis, cortex, and pericycle cells of Arabidopsis (Arabidopsis thaliana) roots challenged with two immunity elicitors, the bacterial flagellin-derived flg22 and the endogenous Pep1 peptide. Our analyses revealed distinct immunity gene networks in each cell type. To further substantiate our understanding of regulatory patterns underlying these cell type-specific immunity networks, we developed a tool to analyze paired transcription factor binding motifs in the promoters of cell type-specific genes. Our study points toward a connection between cell identity and cell type-specific immunity networks that might guide cell types in launching immune response according to the functional capabilities of each cell type.

Multiple ER-to-nucleus stress signaling pathways are activated during Plantago asiatica mosaic virus and Turnip mosaic virus infection in Arabidopsis thaliana

Pathogens and other adverse environmental conditions can trigger endoplasmic reticulum (ER) stress. ER stress signaling increases the expression of cytoprotective ER-chaperones. The inositol-requiring enzyme (IRE1) is one ER stress sensor that is activated to splice the bZIP60 mRNA that produces a truncated transcription factor that activates gene expression in the nucleus. The IRE1/bZIP60 pathway is associated with restricting potyvirus and potexvirus infection. This study shows that the Plantago asiatica mosaic virus (PlAMV) triple gene block 3 (TGB3) and the Turnip mosaic virus (TuMV) 6K2 proteins activate alternative transcription pathways involving the bZIP17, bZIP28, BAG7, NAC089 and NAC103 factors in Arabidopsis thaliana. Using the corresponding knockout mutant lines, we show that bZIP17, bZIP60, BAG7 and NAC089 are factors in reducing PlAMV infection, whereas bZIP28 and bZIP60 are factors in reducing TuMV infection. We propose a model in which bZIP60 and bZIP17 synergistically induce genes restricting PlAMV infection, while bZIP60 and bZIP28 independently induce genes supporting PlAMV infection. Regarding TuMV-green fluorescent protein (GFP) infection, bZIP60 and bZIP28 serve to repress local and systemic infection. Finally, tauroursodeoxycholic acid treatments were used to demonstrate that the protein folding capacity significantly influences PlAMV accumulation.

Co-option of the lineage-specific LAVA retrotransposon in the gibbon genome

Co-option of transposable elements (TEs) to become part of existing or new enhancers is an important mechanism for evolution of gene regulation. However, contributions of lineage-specific TE insertions to recent regulatory adaptations remain poorly understood. Gibbons present a suitable model to study these contributions as they have evolved a lineage-specific TE called LAVA (LINE-AluSz-VNTR-Alu _LIKE), which is still active in the gibbon genome. The LAVA retrotransposon is thought to have played a role in the emergence of the highly rearranged structure of the gibbon genome by disrupting transcription of cell cycle genes. In this study, we investigated whether LAVA may have also contributed to the evolution of gene regulation by adopting enhancer function. We characterized fixed and polymorphic LAVA insertions across multiple gibbons and found 96 LAVA elements overlapping enhancer chromatin states. Moreover, LAVA was enriched in multiple transcription factor binding motifs, was bound by an important transcription factor (PU.1), and was associated with higher levels of gene expression in cis We found gibbon-specific signatures of purifying/positive selection at 27 LAVA insertions. Two of these insertions were fixed in the gibbon lineage and overlapped with enhancer chromatin states, representing putative co-opted LAVA enhancers. These putative enhancers were located within genes encoding SETD2 and RAD9A, two proteins that facilitate accurate repair of DNA double-strand breaks and prevent chromosomal rearrangement mutations. Co-option of LAVA in these genes may have influenced regulation of processes that preserve genome integrity. Our findings highlight the importance of considering lineage-specific TEs in studying evolution of gene regulatory elements.

ICGEC: a comparative method for measuring epigenetic conservation of genes via the integrated signal from multiple histone modifications between cell types

Background

Histone post-translational modifications play crucial roles in epigenetic regulation of gene expression and are known to be associated with the phenotypic differences of different cell types. Therefore, it is of fundamental importance to dissect the genes and pathways involved in such a phenotypic variation at the level of epigenetics. However, the existing comparative approaches are largely based on the differences, especially the absolute difference in the levels of individual histone modifications of genes under contrasting conditions. Thus, a method for measuring the overall change in the epigenetic circumstance of each gene underpinned by multiple types of histone modifications between cell types is lacking.

Results

To address this challenge, we developed ICGEC, a new method for estimating the degree of epigenetic conservation of genes between two cell lines. Different from existing comparative methods, ICGEC provides a reliable score for measuring the relative change in the epigenetic context of corresponding gene between two conditions and simultaneously produces a score for each histone mark. The application of ICGEC to the human embryonic stem cell line H1 and four H1-derived cell lines with available epigenomic data for the same 16 types of histone modifications indicated high robustness and reliability of ICGEC. Furthermore, the analysis of the epigenetically dynamic and conserved genes which were defined based on the ICGEC output results demonstrated that ICGEC can deepen our understanding of the biological processes of cell differentiation to overcome the limitations of traditional expression analysis. Specifically, the ICGEC-derived differentiation-direction-specific genes were shown to have putative functions that are well-matched with cell identity. Additionally, H3K79me1 and H3K27ac were found to be the main histone marks accounting for whether an epigenetically dynamic gene was differentially expressed between two cell lines.

Conclusions

The use of ICGEC creates a convenient and robust way to measure the overall epigenetic conservation of individual genes and marks between two conditions. Thus, it provides a basis for exploring the epigenotype-phenotype relationship. ICGEC can be deemed a state-of-the-art method tailored for comparative epigenomic analysis of changes in cell dynamics.

The Role of Chromatin Accessibility in cis-Regulatory Evolution

Transcription factor (TF) binding is determined by sequence as well as chromatin accessibility. Although the role of accessibility in shaping TF-binding landscapes is well recorded, its role in evolutionary divergence of TF binding, which in turn can alter cis-regulatory activities, is not well understood. In this work, we studied the evolution of genome-wide binding landscapes of five major TFs in the core network of mesoderm specification, between Drosophila melanogaster and Drosophila virilis, and examined its relationship to accessibility and sequence-level changes. We generated chromatin accessibility data from three important stages of embryogenesis in both Drosophila melanogaster and Drosophila virilis and recorded conservation and divergence patterns. We then used multivariable models to correlate accessibility and sequence changes to TF-binding divergence. We found that accessibility changes can in some cases, for example, for the master regulator Twist and for earlier developmental stages, more accurately predict binding change than is possible using TF-binding motif changes between orthologous enhancers. Accessibility changes also explain a significant portion of the codivergence of TF pairs. We noted that accessibility and motif changes offer complementary views of the evolution of TF binding and developed a combined model that captures the evolutionary data much more accurately than either view alone. Finally, we trained machine learning models to predict enhancer activity from TF binding and used these functional models to argue that motif and accessibility-based predictors of TF-binding change can substitute for experimentally measured binding change, for the purpose of predicting evolutionary changes in enhancer activity.

Cis-Regulatory Code for Predicting Plant Cell-Type Transcriptional Response to High Salinity

Multicellular organisms have diverse cell types with distinct roles in development and responses to the environment. At the transcriptional level, the differences in the environmental response between cell types are due to differences in regulatory programs. In plants, although cell-type environmental responses have been examined, it is unclear how these responses are regulated. Here, we identify a set of putative cis-regulatory elements (pCREs) enriched in the promoters of genes responsive to high-salinity stress in six Arabidopsis (Arabidopsis thaliana) root cell types. We then use these pCREs to establish cis-regulatory codes (i.e. models predicting whether a gene is responsive to high salinity for each cell type with machine learning). These pCRE-based models outperform models using in vitro binding data of 758 Arabidopsis transcription factors. Surprisingly, organ pCREs identified based on the whole-root high-salinity response can predict cell-type responses as well as pCREs derived from cell-type data, because organ and cell-type pCREs predict complementary subsets of high-salinity response genes. Our findings not only advance our understanding of the regulatory mechanisms of the plant spatial transcriptional response through cis-regulatory codes but also suggest broad applicability of the approach to any species, particularly those with little or no trans-regulatory data.

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

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

The lncRNA MIR2052HG regulates ERα levels and aromatase inhibitor resistance through LMTK3 by recruiting EGR1

Background

Our previous genome-wide association study using the MA.27 aromatase inhibitors adjuvant trial identified SNPs in the long noncoding RNA MIR2052HG associated with breast cancer-free interval. MIR2052HG maintained ERα both by promoting AKT/FOXO3-mediated ESR1 transcription and by limiting ubiquitin-mediated ERα degradation. Our goal was to further elucidate MIR2052HG’s mechanism of action.

Methods

RNA-binding protein immunoprecipitation assays were performed to demonstrate that the transcription factor, early growth response protein 1 (EGR1), worked together with MIR2052HG to regulate that lemur tyrosine kinase-3 (LMTK3) transcription in MCF7/AC1 and CAMA-1 cells. The location of EGR1 on the LMTK3 gene locus was mapped using chromatin immunoprecipitation assays. The co-localization of MIR2052HG RNA and the LMTK3 gene locus was determined using RNA-DNA dual fluorescent in situ hybridization. Single-nucleotide polymorphisms (SNP) effects were evaluated using a panel of human lymphoblastoid cell lines.

Results

MIR2052HG depletion in breast cancer cells results in a decrease in LMTK3 expression and cell growth. Mechanistically, MIR2052HG interacts with EGR1 and facilitates its recruitment to the LMTK3 promoter. LMTK3 sustains ERα levels by reducing protein kinase C (PKC) activity, resulting in increased ESR1 transcription mediated through AKT/FOXO3 and reduced ERα degradation mediated by the PKC/MEK/ERK/RSK1 pathway. MIR2052HG regulated LMTK3 in a SNP- and aromatase inhibitor-dependent fashion: the variant SNP increased EGR1 binding to LMTK3 promoter in response to androstenedione, relative to wild-type genotype, a pattern that can be reversed by aromatase inhibitor treatment. Finally, LMTK3 overexpression abolished the effect of MIR2052HG on PKC activity and ERα levels.

Conclusions

Our findings support a model in which the MIR2052HG regulates LMTK3 via EGR1, and LMTK3 regulates ERα stability via the PKC/MEK/ERK/RSK1 axis. These results reveal a direct role of MIR2052HG in LMTK3 regulation and raise the possibilities of targeting MIR2052HG or LMTK3 in ERα-positive breast cancer.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1130-3) contains supplementary material, which is available to authorized users.

Evolution and Diversification of FRUITFULL Genes in Solanaceae

Ecologically and economically important fleshy edible fruits have evolved from dry fruit numerous times during angiosperm diversification. However, the molecular mechanisms that underlie these shifts are unknown. In the Solanaceae there has been a major shift to fleshy fruits in the subfamily Solanoideae. Evidence suggests that an ortholog of FRUITFULL (FUL), a transcription factor that regulates cell proliferation and limits the dehiscence zone in the silique of Arabidopsis, plays a similar role in dry-fruited Solanaceae. However, studies have shown that FUL orthologs have taken on new functions in fleshy fruit development, including regulating elements of tomato ripening such as pigment accumulation. FUL belongs to the core eudicot euFUL clade of the angiosperm AP1/FUL gene lineage. The euFUL genes fall into two paralogous clades, euFULI and euFULII. While most core eudicots have one gene in each clade, Solanaceae have two: FUL1 and FUL2 in the former, and MBP10 and MBP20 in the latter. We characterized the evolution of the euFUL genes to identify changes that might be correlated with the origin of fleshy fruit in Solanaceae. Our analyses revealed that the Solanaceae FUL1 and FUL2 clades probably originated through an early whole genome multiplication event. By contrast, the data suggest that the MBP10 and MBP20 clades are the result of a later tandem duplication event. MBP10 is expressed at weak to moderate levels, and its atypical short first intron lacks putative transcription factor binding sites, indicating possible pseudogenization. Consistent with this, our analyses show that MBP10 is evolving at a faster rate compared to MBP20. Our analyses found that Solanaceae euFUL gene duplications, evolutionary rates, and changes in protein residues and expression patterns are not correlated with the shift in fruit type. This suggests deeper analyses are needed to identify the mechanism underlying the change in FUL ortholog function.

Transcription factor binding site clusters identify target genes with similar tissue-wide expression and buffer against mutations

Background: The distribution and composition of cis-regulatory modules composed of transcription factor (TF) binding site (TFBS) clusters in promoters substantially determine gene expression patterns and TF targets. TF knockdown experiments have revealed that TF binding profiles and gene expression levels are correlated. We use TFBS features within accessible promoter intervals to predict genes with similar tissue-wide expression patterns and TF targets. Methods: Genes with correlated expression patterns across 53 tissues and TF targets were respectively identified from Bray-Curtis Similarity and TF knockdown experiments. Corresponding promoter sequences were reduced to DNase I-accessible intervals; TFBSs were then identified within these intervals using information theory-based position weight matrices for each TF (iPWMs) and clustered. Features from information-dense TFBS clusters predicted these genes with machine learning classifiers, which were evaluated for accuracy, specificity and sensitivity. Mutations in TFBSs were analyzed to in silico examine their impact on cluster densities and the regulatory states of target genes. Results:  We initially chose the glucocorticoid receptor gene ( NR3C1), whose regulation has been extensively studied, to test this approach. SLC25A32 and TANK were found to exhibit the most similar expression patterns to NR3C1. A Decision Tree classifier exhibited the largest area under the Receiver Operating Characteristic (ROC) curve in detecting such genes. Target gene prediction was confirmed using siRNA knockdown of TFs, which was found to be more accurate than those predicted after CRISPR/CAS9 inactivation. In-silico mutation analyses of TFBSs also revealed that one or more information-dense TFBS clusters in promoters are required for accurate target gene prediction.  Conclusions: Machine learning based on TFBS information density, organization, and chromatin accessibility accurately identifies gene targets with comparable tissue-wide expression patterns. Multiple information-dense TFBS clusters in promoters appear to protect promoters from effects of deleterious binding site mutations in a single TFBS that would otherwise alter regulation of these genes.

Transcription factor binding site clusters identify target genes with similar tissue-wide expression and buffer against mutations

Background: The distribution and composition of cis-regulatory modules composed of transcription factor (TF) binding site (TFBS) clusters in promoters substantially determine gene expression patterns and TF targets. TF knockdown experiments have revealed that TF binding profiles and gene expression levels are correlated. We use TFBS features within accessible promoter intervals to predict genes with similar tissue-wide expression patterns and TF targets using Machine Learning (ML). Methods: Bray-Curtis Similarity was used to identify genes with correlated expression patterns across 53 tissues. TF targets from knockdown experiments were also analyzed by this approach to set up the ML framework. TFBSs were selected within DNase I-accessible intervals of corresponding promoter sequences using information theory-based position weight matrices (iPWMs) for each TF. Features from information-dense clusters of TFBSs were input to ML classifiers which predict these gene targets along with their accuracy, specificity and sensitivity. Mutations in TFBSs were analyzed in silico to examine their impact on TFBS clustering and predict changes in gene regulation. Results: The glucocorticoid receptor gene ( NR3C1), whose regulation has been extensively studied, was selected to test this approach. SLC25A32 and TANK exhibited the most similar expression patterns to NR3C1. A Decision Tree classifier exhibited the best performance in detecting such genes, based on Area Under the Receiver Operating Characteristic curve (ROC). TF target gene prediction was confirmed using siRNA knockdown, which was more accurate than CRISPR/CAS9 inactivation. TFBS mutation analyses revealed that accurate target gene prediction required  at least 1  information-dense TFBS cluster.  Conclusions: ML based on TFBS information density, organization, and chromatin accessibility accurately identifies gene targets with comparable tissue-wide expression patterns. Multiple information-dense TFBS clusters in promoters appear to protect promoters from effects of deleterious binding site mutations in a single TFBS that would otherwise alter regulation of these genes.

Derivation and molecular characterization of pancreatic differentiated MODY1-iPSCs

Maturity onset diabetes of the young (MODY) is a hereditary form of diabetes mellitus presenting at childhood or adolescence, which eventually leads to pancreatic β-cells dysfunction. The underlying genetic basis of MODY disorders is haploinsufficiency, where loss-of-function mutations in a single allele cause the diabetic phenotype in heterozygous patients. MODY1 is a type of MODY disorder resulting from a mutation in the transcription factor hepatocyte nuclear factor 4 alpha (HNF4α). In order to establish a human based model to study MODY1, we generated patient-derived induced pluripotent stem cells (iPSCs). Differentiation of these pluripotent cells towards the pancreatic lineage enabled to evaluate the effects of the MODY1 mutation and its impact on endodermal and pancreatic cells. Analyzing the gene expression profiles of differentiated MODY1 cells, revealed the outcome of HNF4α haploinsufficiency on its targets. This molecular analysis suggests that the differential expression of HNF4α target genes in MODY1 is affected by the number of HNF4α binding sites, their distance from the transcription start site, and the number of other transcription factor binding sites. These features may help explain the molecular manifestations of haploinsufficiency in MODY1 disease.

Control of species-dependent cortico-motoneuronal connections underlying manual dexterity

Superior manual dexterity in higher primates emerged together with the appearance of cortico-motoneuronal (CM) connections during the evolution of the mammalian corticospinal (CS) system. Previously thought to be specific to higher primates, we identified transient CM connections in early postnatal mice, which are eventually eliminated by Sema6D-PlexA1 signaling. PlexA1 mutant mice maintain CM connections into adulthood and exhibit superior manual dexterity as compared with that of controls. Last, differing PlexA1 expression in layer 5 of the motor cortex, which is strong in wild-type mice but weak in humans, may be explained by FEZF2-mediated cis-regulatory elements that are found only in higher primates. Thus, species-dependent regulation of PlexA1 expression may have been crucial in the evolution of mammalian CS systems that improved fine motor control in higher primates.

In silico design of context-responsive mammalian promoters with user-defined functionality

Comprehensive de novo-design of complex mammalian promoters is restricted by unpredictable combinatorial interactions between constituent transcription factor regulatory elements (TFREs). In this study, we show that modular binding sites that do not function cooperatively can be identified by analyzing host cell transcription factor expression profiles, and subsequently testing cognate TFRE activities in varying homotypic and heterotypic promoter architectures. TFREs that displayed position-insensitive, additive function within a specific expression context could be rationally combined together in silico to create promoters with highly predictable activities. As TFRE order and spacing did not affect the performance of these TFRE-combinations, compositions could be specifically arranged to preclude the formation of undesirable sequence features. This facilitated simple in silico-design of promoters with context-required, user-defined functionalities. To demonstrate this, we de novo-created promoters for biopharmaceutical production in CHO cells that exhibited precisely designed activity dynamics and long-term expression-stability, without causing observable retroactive effects on cellular performance. The design process described can be utilized for applications requiring context-responsive, customizable promoter function, particularly where co-expression of synthetic TFs is not suitable. Although the synthetic promoter structure utilized does not closely resemble native mammalian architectures, our findings also provide additional support for a flexible billboard model of promoter regulation.

The G-Box Transcriptional Regulatory Code in Arabidopsis

Plants have significantly more transcription factor (TF) families than animals and fungi, and plant TF families tend to contain more genes; these expansions are linked to adaptation to environmental stressors. Many TF family members bind to similar or identical sequence motifs, such as G-boxes (CACGTG), so it is difficult to predict regulatory relationships. We determined that the flanking sequences near G-boxes help determine in vitro specificity but that this is insufficient to predict the transcription pattern of genes near G-boxes. Therefore, we constructed a gene regulatory network that identifies the set of bZIPs and bHLHs that are most predictive of the expression of genes downstream of perfect G-boxes. This network accurately predicts transcriptional patterns and reconstructs known regulatory subnetworks. Finally, we present Ara-BOX-cis (araboxcis.org), a Web site that provides interactive visualizations of the G-box regulatory network, a useful resource for generating predictions for gene regulatory relations.

Enhancers and chromatin structures: regulatory hubs in gene expression and diseases

Gene expression requires successful communication between enhancer and promoter regions, whose activities are regulated by a variety of factors and associated with distinct chromatin structures; in addition, functionally related genes and their regulatory repertoire tend to be arranged in the same subchromosomal regulatory domains. In this review, we discuss the importance of enhancers, especially clusters of enhancers (such as super-enhancers), as key regulatory hubs to integrate environmental cues and encode spatiotemporal instructions for genome expression, which are critical for a variety of biological processes governing mammalian development. Furthermore, we emphasize that the enhancer–promoter interaction landscape provides a critical context to understand the aetiologies and mechanisms behind numerous complex human diseases and provides new avenues for effective transcription-based interventions.

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.

Most of the tight positional conservation of transcription factor binding sites near the transcription start site reflects their co-localization within regulatory modules

Background

Transcription factors (TFs) form complexes that bind regulatory modules (RMs) within DNA, to control specific sets of genes. Some transcription factor binding sites (TFBSs) near the transcription start site (TSS) display tight positional preferences relative to the TSS. Furthermore, near the TSS, RMs can co-localize TFBSs with each other and the TSS. The proportion of TFBS positional preferences due to TFBS co-localization within RMs is unknown, however. ChIP experiments confirm co-localization of some TFBSs genome-wide, including near the TSS, but they typically examine only a few TFs at a time, using non-physiological conditions that can vary from lab to lab. In contrast, sequence analysis can examine many TFs uniformly and methodically, broadly surveying the co-localization of TFBSs with tight positional preferences relative to the TSS.

Results

Our statistics found 43 significant sets of human motifs in the JASPAR TF Database with positional preferences relative to the TSS, with 38 preferences tight (±5 bp). Each set of motifs corresponded to a gene group of 135 to 3304 genes, with 42/43 (98%) gene groups independently validated by DAVID, a gene ontology database, with FDR < 0.05. Motifs corresponding to two TFBSs in a RM should co-occur more than by chance alone, enriching the intersection of the gene groups corresponding to the two TFs. Thus, a gene-group intersection systematically enriched beyond chance alone provides evidence that the two TFs participate in an RM. Of the 903 = 43*42/2 intersections of the 43 significant gene groups, we found 768/903 (85%) pairs of gene groups with significantly enriched intersections, with 564/768 (73%) intersections independently validated by DAVID with FDR < 0.05. A user-friendly web site at http://go.usa.gov/3kjsH permits biologists to explore the interaction network of our TFBSs to identify candidate subunit RMs.

Conclusions

Gene duplication and convergent evolution within a genome provide obvious biological mechanisms for replicating an RM near the TSS that binds a particular TF subunit. Of all intersections of our 43 significant gene groups, 85% were significantly enriched, with 73% of the significant enrichments independently validated by gene ontology. The co-localization of TFBSs within RMs therefore likely explains much of the tight TFBS positional preferences near the TSS.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-1354-5) contains supplementary material, which is available to authorized users.

Assembly PCR synthesis of optimally designed, compact, multi-responsive promoters suited to gene therapy application

Gene therapy has the potential to provide innovative treatments for genetic and non-genetic diseases, with the ability to auto-regulate expression levels of therapeutic molecules so that they are produced locally and in direct response to disease activity. Generating disease responsive gene therapy vectors requires knowledge of the activation profile of transcription factors (TFs) during active disease, in order to assemble binding sites for these TFs into synthetic promoters, which can be appropriately activated by the disease process. In this study, we optimised a PCR random assembly approach to generate promoters with optimal spacing between TF binding sites (TFBSs) and their distance from the TATA box. In promoters with optimal spacing, it was possible to demonstrate activation by individual transcription pathways and either additive or synergistic promoter activation when transfected cells were treated with combined stimuli. The kinetics and sensitivity of promoter activation was further explored in transduced cells and when lentivirus was directly delivered to mouse paws a synthetic promoter demonstrated excellent activation by real-time imaging in response to local inflammation.

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.

Hill function-based models of transcriptional switches: impact of specific, nonspecific, functional and nonfunctional binding

We explore minimalist models of transcription in which we take into account that a cis-regulatory sequence is embedded in, and interacts with, a complex genome. The classical Hill equation is the simplest way to represent a transcriptional response. However, it may overlook the fact that a transcription factor (TF) establishes specific and nonspecific nonfunctional interactions with chromatin. Classical papers have shown that nonfunctional binding (not leading to transcription) may influence gene expression. We examine how the presence of additional binding sites for a TF, besides those on the gene(s) of interest, affect the shape and parameters of the transcriptional response. We consider two conditions: at equilibrium and at steady-state. In many cases the TF level is determined by the position of the cell within a spatial or temporal gradient. We show that such gradients can be adjusted by evolutionary selection to compensate for the alteration of the gene transcription response by the presence of nonfunctional binding sites. Finally, we analyse how the transcriptional response is affected by a decrease in TF concentration, as in cases of haploinsufficiency. We show that the nonlinearity of the transcriptional response as a function of [TF] exacerbates the effect of a decrease in the latter, at least for weakly expressed TFs. Although decades of work on TFs have led to the impression that almost everything is known about the control of gene expression, we show that even the simplest models of transcription control have not delivered all their secrets yet.

DNA-Binding Motif of the Imprinted Transcription Factor PEG3

Peg3 is an imprinted gene that is predicted to encode a DNA-binding zinc finger protein. This was previously demonstrated through Chromatin ImmunoPrecipitation-based Sequencing experiments. In the current study, we reanalyzed the previous ChIP-Seq results and further characterized the DNA-binding motif of PEG3. According to the results, PEG3 binds to the promoters and enhancers of a subset of genes that are closely associated with the known functions of Peg3. Some of these identified targets include Tufm, Mrpl45, Cry2, Per1, Slc25a29 and Slc38a2. With this set of targets, we derived a DNA-binding motif of PEG3, 5'-GTGGCAGT-3', which also provides a tabulated matrix that can be used for predicting other unknown genomic targets. Among the newly identified targets, we analyzed in detail the two loci, Slc38a2 and Slc38a4, which are known to be involved in neutral amino acid transport. The results indicated that PEG3 likely functions as a transcriptional repressor for these two loci. Overall, the current study provides a set of genomic targets and also redefines the DNA-binding motif for the imprinted transcription factor PEG3.

Mechanisms of mutational robustness in transcriptional regulation

Robustness is the invariance of a phenotype in the face of environmental or genetic change. The phenotypes produced by transcriptional regulatory circuits are gene expression patterns that are to some extent robust to mutations. Here we review several causes of this robustness. They include robustness of individual transcription factor binding sites, homotypic clusters of such sites, redundant enhancers, transcription factors, redundant transcription factors, and the wiring of transcriptional regulatory circuits. Such robustness can either be an adaptation by itself, a byproduct of other adaptations, or the result of biophysical principles and non-adaptive forces of genome evolution. The potential consequences of such robustness include complex regulatory network topologies that arise through neutral evolution, as well as cryptic variation, i.e., genotypic divergence without phenotypic divergence. On the longest evolutionary timescales, the robustness of transcriptional regulation has helped shape life as we know it, by facilitating evolutionary innovations that helped organisms such as flowering plants and vertebrates diversify.

Nonconsensus Protein Binding to Repetitive DNA Sequence Elements Significantly Affects Eukaryotic Genomes

Recent genome-wide experiments in different eukaryotic genomes provide an unprecedented view of transcription factor (TF) binding locations and of nucleosome occupancy. These experiments revealed that a large fraction of TF binding events occur in regions where only a small number of specific TF binding sites (TFBSs) have been detected. Furthermore, in vitro protein-DNA binding measurements performed for hundreds of TFs indicate that TFs are bound with wide range of affinities to different DNA sequences that lack known consensus motifs. These observations have thus challenged the classical picture of specific protein-DNA binding and strongly suggest the existence of additional recognition mechanisms that affect protein-DNA binding preferences. We have previously demonstrated that repetitive DNA sequence elements characterized by certain symmetries statistically affect protein-DNA binding preferences. We call this binding mechanism nonconsensus protein-DNA binding in order to emphasize the point that specific consensus TFBSs do not contribute to this effect. In this paper, using the simple statistical mechanics model developed previously, we calculate the nonconsensus protein-DNA binding free energy for the entire C. elegans and D. melanogaster genomes. Using the available chromatin immunoprecipitation followed by sequencing (ChIP-seq) results on TF-DNA binding preferences for ~100 TFs, we show that DNA sequences characterized by low predicted free energy of nonconsensus binding have statistically higher experimental TF occupancy and lower nucleosome occupancy than sequences characterized by high free energy of nonconsensus binding. This is in agreement with our previous analysis performed for the yeast genome. We suggest therefore that nonconsensus protein-DNA binding assists the formation of nucleosome-free regions, as TFs outcompete nucleosomes at genomic locations with enhanced nonconsensus binding. In addition, here we perform a new, large-scale analysis using in vitro TF-DNA preferences obtained from the universal protein binding microarrays (PBM) for ~90 eukaryotic TFs belonging to 22 different DNA-binding domain types. As a result of this new analysis, we conclude that nonconsensus protein-DNA binding is a widespread phenomenon that significantly affects protein-DNA binding preferences and need not require the presence of consensus (specific) TFBSs in order to achieve genome-wide TF-DNA binding specificity.

Interactions between proteins and DNA trigger many important biological processes. Therefore, to fully understand how the information encoded on the DNA transcribes into RNA, which in turn translates into proteins in the cell, we need to unravel the molecular design principles of protein-DNA interactions. It is known that many interactions occur when a protein is attracted to a specific short segment on the DNA called a specific protein-DNA binding motif. Strikingly, recent experiments revealed that many regulatory proteins reproducibly bind to different regions on the DNA lacking such specific motifs. This suggests that fundamental molecular mechanisms responsible for protein-DNA recognition specificity are not fully understood. Here, using high-throughput protein-DNA binding data obtained by two entirely different methods for ~100 TFs in each case, we show that DNA regions possessing certain repetitive sequence elements exert the statistical attractive potential on DNA-binding proteins, and as a result, such DNA regions are enriched in bound proteins. This is in agreement with our previous analysis performed for the yeast genome. We use the term nonconsensus protein-DNA binding in order to describe protein-DNA interactions that occur in the absence of specific protein-DNA binding motifs. Here we demonstrate that the identified nonconsensus effect is highly significant for a variety of organismal genomes and it affects protein-DNA binding preferences and nucleosome occupancy at the genome-wide level.

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.