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Transcription factors (TFs) control gene expression by binding to genomic DNA in a sequence-specific manner. Mutations in TF binding sites are increasingly found to be associated with human disease, yet we currently lack robust methods to predict these sites. Here, we developed a versatile maximum likelihood framework named No Read Left Behind (NRLB) that infers a biophysical model of protein-DNA recognition across the full affinity range from a library of in vitro selected DNA binding sites. NRLB predicts human Max homodimer binding in near-perfect agreement with existing low-throughput measurements. It can capture the specificity of the p53 tetramer and distinguish multiple binding modes within a single sample. Additionally, we confirm that newly identified low-affinity enhancer binding sites are functional in vivo, and that their contribution to gene expression matches their predicted affinity. Our results establish a powerful paradigm for identifying protein binding sites and interpreting gene regulatory sequences in eukaryotic genomes.

Expression divergence caused by genetic variation and crosstalks among subgenomes of the allohexaploid bread wheat ( Triticum aestivum. L., BBAADD) is hypothesized to increase its adaptability and/or plasticity. However, the molecular basis of expression divergence remains unclear. Squamosa promoter-binding protein-like (SPL) transcription factors are critical for a wide array of biological processes. In this study, we constructed expression regulatory networks by combining DAP-seq for 40 SPLs, ATAC-seq, and RNA-seq. Our findings indicate that a group of low-affinity SPL binding regions (SBRs) were targeted by diverse SPLs and caused different sequence preferences around the core GTAC motif. The SBRs including the low-affinity ones are evolutionarily conserved, enriched GWAS signals related to important agricultural traits. However, those SBRs are highly diversified among the cis -regulatory regions (CREs) of syntenic genes, with less than 8% SBRs coexisting in triad genes, suggesting that CRE variations are critical for subgenome differentiations. Knocking out of TaSPL7A/B/D and TaSPL15A/B/D subfamily further proved that both high- and low-affinity SBRs played critical roles in the differential expression of genes regulating tiller number and spike sizes. Our results have provided baseline data for downstream networks of SPLs and wheat improvements and revealed that CRE variations are critical sources for subgenome divergence in the allohexaploid wheat.

The HMG-box protein Capicua (Cic) is a conserved transcriptional repressor that functions downstream of receptor tyrosine kinase (RTK) signaling pathways in a relatively simple switch: In the absence of signaling, Cic represses RTK-responsive genes by binding to nearly invariant sites in DNA, whereas activation of RTK signaling down-regulates Cic activity, leading to derepression of its targets. This mechanism controls gene expression in both Drosophila and mammals, but whether Cic can also function via other regulatory mechanisms remains unknown. Here, we characterize an RTK-independent role of Cic in regulating spatially restricted expression of Toll/IL-1 signaling targets in Drosophila embryogenesis. We show that Cic represses those targets by binding to suboptimal DNA sites of lower affinity than its known consensus sites. This binding depends on Dorsal/NF-κB, which translocates into the nucleus upon Toll activation and binds next to the Cic sites. As a result, Cic binds to and represses Toll targets only in regions with nuclear Dorsal. These results reveal a mode of Cic regulation unrelated to the well-established RTK/Cic depression axis and implicate cooperative binding in conjunction with low-affinity binding sites as an important mechanism of enhancer regulation. Given that Cic plays a role in many developmental and pathological processes in mammals, our results raise the possibility that some of these Cic functions are independent of RTK regulation and may depend on cofactor-assisted DNA binding.

Despite a common understanding that Gli TFs are utilized to convey a Hh morphogen gradient, genetic analyses suggest craniofacial development does not completely fit this paradigm. Using the mouse model ( Mus musculus ), we demonstrated that rather than being driven by a Hh threshold, robust Gli3 transcriptional activity during skeletal and glossal development required interaction with the basic helix-loop-helix TF Hand2. Not only did genetic and expression data support a co-factorial relationship, but genomic analysis revealed that Gli3 and Hand2 were enriched at regulatory elements for genes essential for mandibular patterning and development. Interestingly, motif analysis at sites co-occupied by Gli3 and Hand2 uncovered mandibular-specific, low-affinity, ‘divergent’ Gli-binding motifs ( d GBMs). Functional validation revealed these d GBMs conveyed synergistic activation of Gli targets essential for mandibular patterning and development. In summary, this work elucidates a novel, sequence-dependent mechanism for Gli transcriptional activity within the craniofacial complex that is independent of a graded Hh signal.

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

Position weight matrix (PWM) is the traditional motif model representing the transcription factor (TF) binding sites. It proposes that the positions contribute independently to TFs binding affinity, although this hypothesis does not fit the data perfectly. This explains why PWM hits are missing in a substantial fraction of ChIP-seq peaks. To study various modes of the direct binding of plant TFs, we compiled the benchmark collection of 111 ChIP-seq datasets for Arabidopsis thaliana , and applied the traditional PWM, and two alternative motif models BaMM and SiteGA, proposing the dependencies of the positions. The variation in the stringency of the recognition thresholds for the models proposed that the hits of PWM, BaMM, and SiteGA models are associated with the sites of high/medium, any, and low affinity, respectively. At the medium recognition threshold, about 60% of ChIP-seq peaks contain PWM hits consisting of conserved core consensuses, while BaMM and SiteGA provide hits for an additional 15% of peaks in which a weaker core consensus is compensated through intra-motif dependencies. The presence/absence of these dependencies in the motifs of alternative/traditional models was confirmed by the dependency logo DepLogo visualizing the position-wise partitioning of the alignments of predicted sites. We exemplify the detailed analysis of ChIP-seq profiles for plant TFs CCA1, MYC2, and SEP3. Gene ontology (GO) enrichment analysis revealed that among the three motif models, the SiteGA had the highest portions of genes with the significantly enriched GO terms among all predicted genes. We showed that both alternative motif models provide for traditional PWM greater extensions in predicted sites for TFs MYC2/SEP3 with condition/tissue specific functions, compared to those for TF CCA1 with housekeeping functions. Overall, the combined application of standard and alternative motif models is beneficial to detect various modes of the direct TF-DNA interactions in the maximal portion of ChIP-seq loci.

Combination of low concentration, low binding affinity and small solution volume is increasingly more common in calorimetric studies of host-guest interaction, but it leads to very small enthalpy and entropy effects, which are difficult to measure accurately. The aim of this study was to evaluate the reliability of enthalpy determination under such conditions using isothermal titration calorimetry (ITC) with a small-volume microcalorimeter and to evaluate the expected accuracy (expressed as measurement uncertainty) on the example of a simple 1:1 binding reaction of 18-crown-6-ether with K+ cation. The investigation focused on whether or not it is possible to get meaningful results from experiments on such a system with low binding constant, low concentration (logK ≈ 2), low Wiseman “c” parameter values (c < 1) and low total heat released in the studied system. A thorough estimation of measurement uncertainty was performed using the component-by-component (the “classical” GUM) approach to estimate the uncertainties of experimentally determined heat effects at individual titration points and applying those uncertainties to data fitting to obtain the K and ΔH values for the studied reaction. We found that it was possible to determine the reaction enthalpy ΔH of -26.6 kJ/mol with standard uncertainty of 1.1 kJ/mol. If we assume similar uncertainties for the other authors, the ΔH value found in this work is in good agreement with the majority of the literature ΔH values and those are in general in agreement with each other.

This chapter contains sections titled: Gel Retardation Analysis

Heat shock protein 90 (Hsp90) is an ATP-dependent molecular chaperone which is essential in eukaryotes. It is required for the activation and stabilization of a wide variety of client proteins and many of them are involved in important cellular pathways. Since Hsp90 affects numerous physiological processes such as signal transduction, intracellular transport, and protein degradation, it became an interesting target for cancer therapy. Structurally, Hsp90 is a flexible dimeric protein composed of three different domains which adopt structurally distinct conformations. ATP binding triggers directionality in these conformational changes and leads to a more compact state. To achieve its function, Hsp90 works together with a large group of cofactors, termed co-chaperones. Co-chaperones form defined binary or ternary complexes with Hsp90, which facilitate the maturation of client proteins. In addition, posttranslational modifications of Hsp90, such as phosphorylation and acetylation, provide another level of regulation. They influence the conformational cycle, co-chaperone interaction, and inter-domain communications. In this review, we discuss the recent progress made in understanding the Hsp90 machinery.

Sorghum bicolor (SB) is rich in protective phytoconstituents with health benefits and regarded as a promising source of natural anti-diabetic substance. However, its comprehensive bioactive compound(s) and mechanism(s) against type-2 diabetes mellitus (T2DM) have not been exposed. Hence, we implemented network pharmacology to identify its key compounds and mechanism(s) against T2DM. Compounds in SB were explored through GC-MS and screened by Lipinski's rule. Genes associated with the selected compounds or T2DM were extracted from public databases, and the overlapping genes between SB-compound related genes and T2DM target genes were identified using Venn diagram. Then, the networking between selected compounds and overlapping genes was constructed, visualized, and analyzed by RStudio. Finally, affinity between compounds and genes was evaluated via molecular docking. GC-MS analysis of SB detected a total of 20 compounds which were accepted by the Lipinski's rule. A total number of 16 compounds-related genes and T2DM-related genes (4,763) were identified, and 81 overlapping genes between them were selected. Gene set enrichment analysis exhibited that the mechanisms of SB against T2DM were associated with 12 signaling pathways, and the key mechanism might be to control blood glucose level by activating PPAR signaling pathway. Furthermore, the highest affinities were noted between four main compounds and six genes (FABP3-Propyleneglyco monoleate, FABP4-25-Oxo-27-norcholesterol, NR1H3-Campesterol, PPARA-β-sitosterol, PPARD-β-sitosterol, and PPARG-β-sitosterol). Our study overall suggests that the four key compounds detected in SB might ameliorate T2DM severity by activating the PPAR signaling pathway.