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Transcription factors contain a DNA-binding domain ensuring specific recognition of DNA target sequences. The family of forkhead (FOX) transcription factors is composed of dozens of paralogs in mammals. The forkhead domain (FHD) is a segment of about 100 amino acids that binds an A-rich DNA sequence. Using DNA and RNA PCR-SELEX, we show that recombinant FOXL2 proteins, either wild-type or carrying the oncogenic variant C134W, recognize similar DNA-binding sites. This suggests that the oncogenic variant does not alter the intrinsic sequence-specificity of FOXL2. Most importantly, we show that FOXL2 binds G2-rich RNA sequences whereas it virtually fails to bind similar sequences in DNA chemistry. Interestingly, a statistically significant subset of genes responding to the knock-down of FOXL2/Foxl2 harbor such G2-rich sequences and are involved in crucial signaling pathways and cellular processes. In addition, we show that FOXA1, FOXO3a and chimeric FOXL2 proteins containing the FHD of the former are also able to interact with some of the preferred FOXL2-binding sequences. Our results point to an unexpected and novel characteristic of the forkhead domain, the biological relevance of which remains to be explored., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Proteins often regulate their activities via allostery-or action at a distance-in which the binding of a ligand at one binding site influences the affinity for another ligand at a distal site. Although less studied than in proteins, allosteric effects have been observed in experiments with DNA as well. In these experiments two or more proteins bind at distinct DNA sites and interact indirectly with each other, via a mechanism mediated by the linker DNA molecule. We develop a mechanical model of DNA/protein interactions which predicts three distinct mechanisms of allostery. Two of these involve an enthalpy-mediated allostery, while a third mechanism is entropy driven. We analyze experiments of DNA allostery and highlight the distinctive signatures allowing one to identify which of the proposed mechanisms best fits the data.

GCLiPP is a global RNA interactome capture method that detects RNA-binding protein (RBP) occupancy transcriptome-wide. GCLiPP maps RBP-occupied sites at a higher resolution than phase separation-based techniques. GCLiPP sequence tags correspond with known RBP binding sites and are enriched for sites detected by RBP-specific crosslinking immunoprecipitation (CLIP) for abundant cytosolic RBPs. Comparison of human Jurkat T cells and mouse primary T cells uncovers shared peaks of GCLiPP signal across homologous regions of human and mouse 3' UTRs, including a conserved mRNA-destabilizing cis-regulatory element. GCLiPP signal overlapping with immune-related SNPs uncovers stabilizing cis-regulatory regions in CD5, STAT6, and IKZF1., (© 2023. The Author(s).)

Transcription factor binding across the genome is regulated by DNA sequence and chromatin features. However, it is not yet possible to quantify the impact of chromatin context on transcription factor binding affinities. Here, we report a method called binding affinities to native chromatin by sequencing (BANC-seq) to determine absolute apparent binding affinities of transcription factors to native DNA across the genome. In BANC-seq, a concentration range of a tagged transcription factor is added to isolated nuclei. Concentration-dependent binding is then measured per sample to quantify apparent binding affinities across the genome. BANC-seq adds a quantitative dimension to transcription factor biology, which enables stratification of genomic targets based on transcription factor concentration and prediction of transcription factor binding sites under non-physiological conditions, such as disease-associated overexpression of (onco)genes. Notably, whereas consensus DNA binding motifs for transcription factors are important to establish high-affinity binding sites, these motifs are not always strictly required to generate nanomolar-affinity interactions in the genome., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Enhancers activate their cognate promoters over huge distances but how enhancer/promoter interactions become established is not completely understood. There is strong evidence that cohesin-mediated loop extrusion is involved but this does not appear to be a universal mechanism. Here, we identify an element within the mouse immunoglobulin lambda (Igλ) light chain locus, HSCλ1, that has characteristics of active regulatory elements but lacks intrinsic enhancer or promoter activity. Remarkably, knock-out of the YY1 binding site from HSCλ1 reduces Igλ transcription significantly and disrupts enhancer/promoter interactions, even though these elements are >10 kb from HSCλ1. Genome-wide analyses of mouse embryonic stem cells identified 2671 similar YY1-bound, putative genome organizing elements that lie within CTCF/cohesin loop boundaries but that lack intrinsic enhancer activity. We suggest that such elements play a fundamental role in locus folding and in facilitating enhancer/promoter interactions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

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., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Activating Transcription Factor 4 (ATF4) is an important regulator of gene expression in stress responses and developmental processes in many cell types. Here, we catalogued ATF4 binding sites in the human genome and identified overlaps with trait-associated genetic variants. We probed these genetic variants for allelic regulatory activity using a massively parallel reporter assay (MPRA) in HepG2 hepatoma cells exposed to tunicamycin to induce endoplasmic reticulum stress and ATF4 upregulation. The results revealed that in the majority of cases, the MPRA allelic activity of these SNPs was in agreement with the nucleotide preference seen in the ATF4 binding motif from ChIP-Seq. Luciferase and electrophoretic mobility shift assays in additional cellular models further confirmed ATF4-dependent regulatory effects for the SNPs rs532446 (GADD45A intronic; linked to hematological parameters), rs7011846 (LPL upstream; myocardial infarction), rs2718215 (diastolic blood pressure), rs281758 (psychiatric disorders) and rs6491544 (educational attainment). CRISPR-Cas9 disruption and/or deletion of the regulatory elements harboring rs532446 and rs7011846 led to the downregulation of GADD45A and LPL, respectively. Thus, these SNPs could represent examples of GWAS genetic variants that affect gene expression by altering ATF4-mediated transcriptional activation., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Örd et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

RNA-binding proteins play crucial roles in the regulation of gene expression, and understanding the interactions between RNAs and RBPs in distinct cellular conditions forms the basis for comprehending the underlying RNA function. However, current computational methods pose challenges to the cross-prediction of RNA-protein binding events across diverse cell lines and tissue contexts. Here, we develop HDRNet, an end-to-end deep learning-based framework to precisely predict dynamic RBP binding events under diverse cellular conditions. Our results demonstrate that HDRNet can accurately and efficiently identify binding sites, particularly for dynamic prediction, outperforming other state-of-the-art models on 261 linear RNA datasets from both eCLIP and CLIP-seq, supplemented with additional tissue data. Moreover, we conduct motif and interpretation analyses to provide fresh insights into the pathological mechanisms underlying RNA-RBP interactions from various perspectives. Our functional genomic analysis further explores the gene-human disease associations, uncovering previously uncharacterized observations for a broad range of genetic disorders., (© 2023. The Author(s).)

Muscleblind-like splicing regulators (MBNLs) activate or repress the inclusion of alternative splicing (AS) events, enabling the developmental transition of fetal mRNA splicing isoforms to their adult forms. Herein, we sought to elaborate the mechanism by which MBNLs mediate AS related to biological processes. We evaluated the functional role of DEAD-box (DDX) RNA helicases, DDX5 and DDX17 in MBNL-dependent AS regulation. Whole-transcriptome analysis and validation approaches revealed a handful of MBNLs-dependent AS events to be affected by DDX5 and DDX17 in mostly an opposite manner. The opposite expression patterns of these two groups of factors during muscle development and coordination of fetal-to-adult splicing transition indicate the importance of these proteins at early stages of development. The identified pathways of how the helicases modulate MBNL splicing activity include DDX5 and DDX17-dependent changes in the ratio of MBNL splicing isoforms and most likely changes in accessibility of MBNL-binding sites. Another pathway involves the mode of action of the helicases independent of MBNL activity. These findings lead to a deeper understanding of the network of interdependencies between RNA-binding proteins and constitute a valuable element in the discussion on developmental homeostasis and pathological states in which the studied protein factors play a significant role., (© 2023. The Author(s).)

Background: Transcription factors (TF) play a crucial role in the regulation of gene transcription; alterations of their activity and binding to DNA areas are strongly involved in cancer and other disease onset and development. For proper biomedical investigation, it is hence essential to correctly trace TF dense DNA areas, having multiple bindings of distinct factors, and select DNA high occupancy target (HOT) zones, showing the highest accumulation of such bindings. Indeed, systematic and replicable analysis of HOT zones in a large variety of cells and tissues would allow further understanding of their characteristics and could clarify their functional role., Results: Here, we propose, thoroughly explain and discuss a full computational procedure to study in-depth DNA dense areas of transcription factor accumulation and identify HOT zones. This methodology, developed as a computationally efficient parametric algorithm implemented in an R/Bioconductor package, uses a systematic approach with two alternative methods to examine transcription factor bindings and provide comparative and fully-reproducible assessments. It offers different resolutions by introducing three distinct types of accumulation, which can analyze DNA from single-base to region-oriented levels, and a moving window, which can estimate the influence of the neighborhood for each DNA base under exam., Conclusions: We quantitatively assessed the full procedure by using our implemented software package, named TFHAZ, in two example applications of biological interest, proving its full reliability and relevance., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Transcription factors (TFs) exhibit heterogeneous DNA-binding specificities in individual cells and whole organisms under natural conditions, and de novo motif discovery usually provides multiple motifs, even from a single chromatin immunoprecipitation-sequencing (ChIP-seq) sample. Despite the accumulation of ChIP-seq data and ChIP-seq-derived motifs, the diversity of DNA-binding specificities across different TFs and cell types remains largely unexplored., Results: Here, we applied MOCCS2, our k-mer-based motif discovery method, to a collection of human TF ChIP-seq samples across diverse TFs and cell types, and systematically computed profiles of TF-binding specificity scores for all k-mers. After quality control, we compiled a set of TF-binding specificity score profiles for 2,976 high-quality ChIP-seq samples, comprising 473 TFs and 398 cell types. Using these high-quality samples, we confirmed that the k-mer-based TF-binding specificity profiles reflected TF- or TF-family dependent DNA-binding specificities. We then compared the binding specificity scores of ChIP-seq samples with the same TFs but with different cell type classes and found that half of the analyzed TFs exhibited differences in DNA-binding specificities across cell type classes. Additionally, we devised a method to detect differentially bound k-mers between two ChIP-seq samples and detected k-mers exhibiting statistically significant differences in binding specificity scores. Moreover, we demonstrated that differences in the binding specificity scores between k-mers on the reference and alternative alleles could be used to predict the effect of variants on TF binding, as validated by in vitro and in vivo assay datasets. Finally, we demonstrated that binding specificity score differences can be used to interpret disease-associated non-coding single-nucleotide polymorphisms (SNPs) as TF-affecting SNPs and provide candidates responsible for TFs and cell types., Conclusions: Our study provides a basis for investigating the regulation of gene expression in a TF-, TF family-, or cell-type-dependent manner. Furthermore, our differential analysis of binding-specificity scores highlights noncoding disease-associated variants in humans., (© 2023. BioMed Central Ltd., part of Springer Nature.)

The Wolfram syndrome 1 gene ( WFS1) is the main causative locus for Wolfram syndrome, an inherited condition characterized by childhood-onset diabetes mellitus, optic atrophy, and deafness. Global genome-wide association studies have listed at least 19 WFS1 variants that are associated with type 2 diabetes (T2D) and metabolic traits. It has been suggested that miRNA binding sites on WFS1 play a critical role in the regulation of the wolframin protein, and loss of WFS1 function may lead to the pathogenesis of diabetes. In the Hungarian population, it was observed that a 3' UTR variant from WFS1 , namely rs1046322, influenced the affinity of miR-668 to WFS1 mRNA, and showed a strong association with T2D. In this study, we genotyped a large cohort of 2067 individuals of different ethnicities residing in Kuwait for the WFS1 rs1046322 polymorphism. The cohort included 362 Southeast Asians (SEA), 1045 Arabs, and 660 South Asians (SA). Upon performing genetic association tests, we observed significant associations between the rs1046322 SNP and obesity traits in the SEA population, but not in the Arab or SA populations. The associated traits in SEA cohort were body mass index, BMI (β=1.562, P-value=0.0035, P emp =0.0072 ), waist circumference, WC (β=3.163, P-value=0.0197, P emp =0.0388 ) and triglyceride, TGL (β=0.224, P-value=0.0340). The association with BMI remained statistically significant even after multiple testing correction. Among the SEA individuals, carriers of the effect allele at the SNP had significantly higher BMI [mean of 27.63 (3.6) Kg/m 2 ], WC [mean of 89.9 (8.1) cm], and TGL levels [mean of 1.672 (0.8) mmol/l] than non-carriers of the effect allele. Our findings suggest a role for WFS1 in obesity, which is a risk factor for diabetes. The study also emphasizes the significant role the ethnic background may play in determining the effect of genetic variants on susceptibility to metabolic diseases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Hammad, Abu-Farha, Hebbar, Anoop, Chandy, Melhem, Channanath, Al-Mulla, Thanaraj and Abubaker.)

Nirmatrelvir is a specific antiviral drug that targets the main protease (M pro ) of SARS-CoV-2 and has been approved to treat COVID-19 1,2 . As an RNA virus characterized by high mutation rates, whether SARS-CoV-2 will develop resistance to nirmatrelvir is a question of concern. Our previous studies have shown that several mutational pathways confer resistance to nirmatrelvir, but some result in a loss of viral replicative fitness, which is then compensated for by additional alterations 3 . The molecular mechanisms for this observed resistance are unknown. Here we combined biochemical and structural methods to demonstrate that alterations at the substrate-binding pocket of M pro can allow SARS-CoV-2 to develop resistance to nirmatrelvir in two distinct ways. Comprehensive studies of the structures of 14 M pro mutants in complex with drugs or substrate revealed that alterations at the S1 and S4 subsites substantially decreased the level of inhibitor binding, whereas alterations at the S2 and S4' subsites unexpectedly increased protease activity. Both mechanisms contributed to nirmatrelvir resistance, with the latter compensating for the loss in enzymatic activity of the former, which in turn accounted for the restoration of viral replicative fitness, as observed previously 3 . Such a profile was also observed for ensitrelvir, another clinically relevant M pro inhibitor. These results shed light on the mechanisms by which SARS-CoV-2 evolves to develop resistance to the current generation of protease inhibitors and provide the basis for the design of next-generation M pro inhibitors., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Antibiotic binding sites are located in important domains of essential enzymes and have been extensively studied in the context of resistance mutations; however, their study is limited by positive selection. Using multiplex genome engineering 1 to overcome this constraint, we generate and characterize a collection of 760 single-residue mutants encompassing the entire rifampicin binding site of Escherichia coli RNA polymerase (RNAP). By genetically mapping drug-enzyme interactions, we identify an alpha helix where mutations considerably enhance or disrupt rifampicin binding. We find mutations in this region that prolong antibiotic binding, converting rifampicin from a bacteriostatic to bactericidal drug by inducing lethal DNA breaks. The latter are replication dependent, indicating that rifampicin kills by causing detrimental transcription-replication conflicts at promoters. We also identify additional binding site mutations that greatly increase the speed of RNAP.Fast RNAP depletes the cell of nucleotides, alters cell sensitivity to different antibiotics and provides a cold growth advantage. Finally, by mapping natural rpoB sequence diversity, we discover that functional rifampicin binding site mutations that alter RNAP properties or confer drug resistance occur frequently in nature., (© 2023. The Author(s).)

Transcription factors (TFs) are proteins that affect gene expression by binding to regulatory regions of DNA in a sequence specific manner. The binding of TFs to DNA is controlled by many factors, including the DNA sequence, concentration of TF, chromatin accessibility and co-factors. Here, we systematically investigated the binding mechanism of hundreds of TFs by analysing ChIP-seq data with our explainable statistical model, ChIPanalyser. This tool uses as inputs the DNA sequence binding motif; the capacity to distinguish between strong and weak binding sites; the concentration of TF; and chromatin accessibility. We found that approximately one third of TFs are predicted to bind the genome in a DNA accessibility independent fashion, which includes TFs that can open the chromatin, their co-factors and TFs with similar motifs. Our model predicted this to be the case when the TF binds to its strongest binding regions in the genome, and only a small number of TFs have the capacity to bind dense chromatin at their weakest binding regions, such as CTCF, USF2 and CEBPB. Our study demonstrated that the binding of hundreds of human and mouse TFs is predicted by ChIPanalyser with high accuracy and showed that many TFs can bind dense chromatin., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Prostate cancer (PrCa) is the second most common cancer worldwide in males. While strongly warranted, the prediction of mortality risk due to PrCa, especially before its development, is challenging. Here, we address this issue by maximizing the statistical power of genetic data with multi-ancestry meta-analysis and focusing on binding sites of the androgen receptor (AR), which has a critical role in PrCa. Taking advantage of large Japanese samples ever, a multi-ancestry meta-analysis comprising more than 300,000 subjects in total identifies 9 unreported loci including ZFHX3, a tumor suppressor gene, and successfully narrows down the statistically finemapped variants compared to European-only studies, and these variants strongly enrich in AR binding sites. A polygenic risk scores (PRS) analysis restricting to statistically finemapped variants in AR binding sites shows among cancer-free subjects, individuals with a PRS in the top 10% have a strongly higher risk of the future death of PrCa (HR: 5.57, P = 4.2 × 10 -10 ). Our findings demonstrate the potential utility of leveraging large-scale genetic data and advanced analytical methods in predicting the mortality of PrCa., (© 2023. Springer Nature Limited.)

Mammalian genomes are extensively transcribed, producing a large number of coding and non-coding transcripts. A large fraction of the nuclear RNAs is physically associated with chromatin, functioning in gene activation and silencing, shaping higher-order genome organisation, such as involvement in long-range enhancer-promoter interactions, transcription hubs, heterochromatin, nuclear bodies and phase transitions. Different mechanisms allow the tethering of these chromatin-associated RNAs (caRNA) to chromosomes, including RNA binding proteins, the RNA polymerases and R-loops. In this review, we focus on the sequence-specific targeting of RNA to DNA by forming triple helical structures and describe its interplay with chromatin. It turns out that nucleosome positioning at triple helix target sites and the nucleosome itself are essential factors in determining the formation and stability of triple helices. The histone H3-tail plays a critical role in triple helix stabilisation, and the role of its epigenetic modifications in this process is discussed., (© 2023 the author(s), published by De Gruyter, Berlin/Boston.)

RNA-binding proteins (RBPs) control RNA metabolism to orchestrate gene expression and, when dysfunctional, underlie human diseases. Proteome-wide discovery efforts predict thousands of RBP candidates, many of which lack canonical RNA-binding domains (RBDs). Here, we present a hybrid ensemble RBP classifier (HydRA), which leverages information from both intermolecular protein interactions and internal protein sequence patterns to predict RNA-binding capacity with unparalleled specificity and sensitivity using support vector machines (SVMs), convolutional neural networks (CNNs), and Transformer-based protein language models. Occlusion mapping by HydRA robustly detects known RBDs and predicts hundreds of uncharacterized RNA-binding associated domains. Enhanced CLIP (eCLIP) for HydRA-predicted RBP candidates reveals transcriptome-wide RNA targets and confirms RNA-binding activity for HydRA-predicted RNA-binding associated domains. HydRA accelerates construction of a comprehensive RBP catalog and expands the diversity of RNA-binding associated domains., Competing Interests: Declaration of interests G.W.Y. is a co-founder, member of the Board of Directors, on the SAB, equity holder, and paid consultant for Locanabio and Eclipse BioInnovations. G.W.Y. is a visiting professor at the National University of Singapore. G.W.Y.’s interests have been reviewed and approved by the University of California, San Diego in accordance with its conflict-of-interest policies., (Copyright © 2023 University of California San Diego. Published by Elsevier Inc. All rights reserved.)

Human nuclear receptors (NRs) are a superfamily of ligand-responsive transcription factors that have central roles in cellular function. Their malfunction is linked to numerous diseases, and the ability to modulate their activity with synthetic ligands has yielded 16% of all FDA-approved drugs. NRs regulate distinct gene networks, however they often function from genomic sites that lack known binding motifs. Here, to annotate genomic binding sites of known and unexamined NRs more accurately, we use high-throughput SELEX to comprehensively map DNA binding site preferences of all full-length human NRs, in complex with their ligands. Furthermore, to identify non-obvious binding sites buried in DNA-protein interactomes, we develop MinSeq Find, a search algorithm based on the MinTerm concept from electrical engineering and digital systems design. The resulting MinTerm sequence set (MinSeqs) reveal a constellation of binding sites that more effectively annotate NR-binding profiles in cells. MinSeqs also unmask binding sites created or disrupted by 52,106 single-nucleotide polymorphisms associated with human diseases. By implicating druggable NRs as hidden drivers of multiple human diseases, our results not only reveal new biological roles of NRs, but they also provide a resource for drug-repurposing and precision medicine., (© 2023. The Author(s).)

Eukaryotic genomes contain several types of recurrent sequence motifs, e.g. transcription factor motifs, miRNA binding sites, repetitive elements. CRISPR/Cas9 can facilitate identification and study of crucial motifs. We present transCRISPR, the first online tool dedicated to search for sequence motifs in the user-provided genomic regions and design optimal sgRNAs targeting them. Users can obtain sgRNAs for chosen motifs, for up to tens of thousands of target regions in 30 genomes, either for the Cas9 or dCas9 system. TransCRISPR provides user-friendly tables and visualizations, summarizing features of identified motifs and designed sgRNAs such as genomic localization, quality scores, closest transcription start sites and others. Experimental validation of sgRNAs for MYC binding sites designed with transCRISPR confirmed efficient disruption of the targeted motifs and effect on expression of MYC-regulated genes. TransCRISPR is available from https://transcrispr.igcz.poznan.pl/transcrispr/., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Measuring the relative effect that any two sequence positions have on each other may improve protein design or help better interpret coding variants. Current approaches use statistics and machine learning but rarely consider phylogenetic divergences which, as shown by Evolutionary Trace studies, provide insight into the functional impact of sequence perturbations. Here, we reframe covariation analyses in the Evolutionary Trace framework to measure the relative tolerance to perturbation of each residue pair during evolution. This approach (CovET) systematically accounts for phylogenetic divergences: at each divergence event, we penalize covariation patterns that belie evolutionary coupling. We find that while CovET approximates the performance of existing methods to predict individual structural contacts, it performs significantly better at finding structural clusters of coupled residues and ligand binding sites. For example, CovET found more functionally critical residues when we examined the RNA recognition motif and WW domains. It correlates better with large-scale epistasis screen data. In the dopamine D2 receptor, top CovET residue pairs recovered accurately the allosteric activation pathway characterized for Class A G protein-coupled receptors. These data suggest that CovET ranks highest the sequence position pairs that play critical functional roles through epistatic and allosteric interactions in evolutionarily relevant structure-function motifs. CovET complements current methods and may shed light on fundamental molecular mechanisms of protein structure and function., Competing Interests: Conflict of interest The authors declare no conflict of interest with the contents of this article., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

During development, Hox genes are temporally activated according to their relative positions on their clusters, contributing to the proper identities of structures along the rostrocaudal axis. To understand the mechanism underlying this Hox timer, we used mouse embryonic stem cell-derived stembryos. Following Wnt signaling, the process involves transcriptional initiation at the anterior part of the cluster and a concomitant loading of cohesin complexes enriched on the transcribed DNA segments, that is, with an asymmetric distribution favoring the anterior part of the cluster. Chromatin extrusion then occurs with successively more posterior CTCF sites acting as transient insulators, thus generating a progressive time delay in the activation of more posterior-located genes due to long-range contacts with a flanking topologically associating domain. Mutant stembryos support this model and reveal that the presence of evolutionary conserved and regularly spaced intergenic CTCF sites controls the precision and the pace of this temporal mechanism., (© 2023. The Author(s).)

Transcription factors (TF) recognize specific motifs in the genome that are typically 6-12 bp long to regulate various aspects of the cellular machinery. Presence of binding motifs and favorable genome accessibility are key drivers for a consistent TF-DNA interaction. Although these pre-requisites may occur thousands of times in the genome, there seems to be a high degree of selectivity for the sites that are actually bound. Here, we present a deep-learning framework that identifies and characterizes the upstream and downstream genetic elements to the binding motif, for their role in enforcing the mentioned selectivity. The proposed framework is based on an interpretable recurrent neural network architecture that enables for the relative analysis of sequence context features. We apply the framework to model twenty-six transcription factors and score the TF-DNA binding at a base-pair resolution. We find significant differences in activations of DNA context features for bound and unbound sequences. In addition to standardized evaluation protocols, we offer outstanding interpretability that enables us to identify and annotate DNA sequence with possible elements that modulate TF-DNA binding. Also, differences in data processing have a huge influence on the overall model performance. Overall, the proposed framework allows for novel insights on the non-coding genetic elements and their role in facilitating a stable TF-DNA interaction., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

RNA-binding proteins (RBPs) are essential for gene regulation, but it remains a challenge to identify their RNA targets across cell types. Here we present PIE-Seq to investigate Protein-RNA Interaction with dual-deaminase Editing and Sequencing by conjugating C-to-U and A-to-I base editors to RBPs. We benchmark PIE-Seq and demonstrate its sensitivity in single cells, its application in the developing brain, and its scalability with 25 human RBPs. Bulk PIE-Seq identifies canonical binding features for RBPs such as PUM2 and NOVA1, and nominates additional target genes for most tested RBPs such as SRSF1 and TDP-43/TARDBP. Homologous RBPs frequently edit similar sequences and gene sets in PIE-Seq while different RBP families show distinct targets. Single-cell PIE-PUM2 uncovers comparable targets to bulk samples and applying PIE-PUM2 to the developing mouse neocortex identifies neural-progenitor- and neuron-specific target genes such as App. In summary, PIE-Seq provides an orthogonal approach and resource to uncover RBP targets in mice and human cells., (© 2023. The Author(s).)

The maturation of RNA from its nascent transcription to ultimate utilization (e.g., translation, miR-mediated RNA silencing, etc.) involves an intricately coordinated series of biochemical reactions regulated by RNA-binding proteins (RBPs). Over the past several decades, there has been extensive effort to elucidate the biological factors that control specificity and selectivity of RNA target binding and downstream function. Polypyrimidine tract binding protein 1 (PTBP1) is an RBP that is involved in all steps of RNA maturation and serves as a key regulator of alternative splicing, and therefore, understanding its regulation is of critical biologic importance. While several mechanisms of RBP specificity have been proposed (e.g., cell-specific expression of RBPs and secondary structure of target RNA), recently, protein-protein interactions with individual domains of RBPs have been suggested to be important determinants of downstream function. Here, we demonstrate a novel binding interaction between the first RNA recognition motif 1 (RRM1) of PTBP1 and the prosurvival protein myeloid cell leukemia-1 (MCL1). Using both in silico and in vitro analyses, we demonstrate that MCL1 binds a novel regulatory sequence on RRM1. NMR spectroscopy reveals that this interaction allosterically perturbs key residues in the RNA-binding interface of RRM1 and negatively impacts RRM1 association with target RNA. Furthermore, pulldown of MCL1 by endogenous PTBP1 verifies that these proteins interact in an endogenous cellular environment, establishing the biological relevance of this binding event. Overall, our findings suggest a novel mechanism of regulation of PTBP1 in which a protein-protein interaction with a single RRM can impact RNA association., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

CRISPR-associated transposases (CASTs) direct DNA integration downstream of target sites using the RNA-guided DNA binding activity of nuclease-deficient CRISPR-Cas systems. Transposition relies on several key protein-protein and protein-DNA interactions, but little is known about the explicit sequence requirements governing efficient transposon DNA integration activity. Here, we exploit pooled library screening and high-throughput sequencing to reveal novel sequence determinants during transposition by the Type I-F Vibrio cholerae CAST system (VchCAST). On the donor DNA, large transposon end libraries revealed binding site nucleotide preferences for the TnsB transposase, as well as an additional conserved region that encoded a consensus binding site for integration host factor (IHF). Remarkably, we found that VchCAST requires IHF for efficient transposition, thus revealing a novel cellular factor involved in CRISPR-associated transpososome assembly. On the target DNA, we uncovered preferred sequence motifs at the integration site that explained previously observed heterogeneity with single-base pair resolution. Finally, we exploited our library data to design modified transposon variants that enable in-frame protein tagging. Collectively, our results provide new clues about the assembly and architecture of the paired-end complex formed between TnsB and the transposon DNA, and inform the design of custom payload sequences for genome engineering applications with CAST systems., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

As a master regulator in cells, RNA-binding protein (RBP) plays critical roles in organismal development, metabolism and various diseases. It regulates gene expression at various levels mostly by specific recognition of target RNA. The traditional CLIP-seq method to detect transcriptome-wide RNA targets of RBP is less efficient in yeast due to the low UV transmissivity of their cell walls. Here, we established an efficient HyperTRIBE (Targets of RNA-binding proteins Identified By Editing) in yeast, by fusing an RBP to the hyper-active catalytic domain of human RNA editing enzyme ADAR2 and expressing the fusion protein in yeast cells. The target transcripts of RBP were marked with new RNA editing events and identified by high-throughput sequencing. We successfully applied HyperTRIBE to identifying the RNA targets of two yeast RBPs, KHD1 and BFR1. The antibody-free HyperTRIBE has competitive advantages including a low background, high sensitivity and reproducibility, as well as a simple library preparation procedure, providing a reliable strategy for RBP target identification in Saccharomyces cerevisiae .

Cyclic AMP receptor proteins (CRPs) are important transcription regulators in many species. The prediction of CRP-binding sites was mainly based on position-weighted matrixes (PWMs). Traditional prediction methods only considered known binding motifs, and their ability to discover inflexible binding patterns was limited. Thus, a novel CRP-binding site prediction model called CRPBSFinder was developed in this research, which combined the hidden Markov model, knowledge-based PWMs and structure-based binding affinity matrixes. We trained this model using validated CRP-binding data from Escherichia coli and evaluated it with computational and experimental methods. The result shows that the model not only can provide higher prediction performance than a classic method but also quantitatively indicates the binding affinity of transcription factor binding sites by prediction scores. The prediction result included not only the most knowns regulated genes but also 1089 novel CRP-regulated genes. The major regulatory roles of CRPs were divided into four classes: carbohydrate metabolism, organic acid metabolism, nitrogen compound metabolism and cellular transport. Several novel functions were also discovered, including heterocycle metabolic and response to stimulus. Based on the functional similarity of homologous CRPs, we applied the model to 35 other species. The prediction tool and the prediction results are online and are available at: https://awi.cuhk.edu.cn/∼CRPBSFinder., (© The Author(s) 2023. Published by Oxford University Press.)

The gene regulatory code and grammar remain largely unknown, precluding our ability to link phenotype to genotype in regulatory sequences. Here, using a massively parallel reporter assay (MPRA) of 209,440 sequences, we examine all possible pair and triplet combinations, permutations and orientations of eighteen liver-associated transcription factor binding sites (TFBS). We find that TFBS orientation and order have a major effect on gene regulatory activity. Corroborating these results with genomic analyses, we find clear human promoter TFBS orientation biases and similar TFBS orientation and order transcriptional effects in an MPRA that tested 164,307 liver candidate regulatory elements. Additionally, by adding TFBS orientation to a model that predicts expression from sequence we improve performance by 7.7%. Collectively, our results show that TFBS orientation and order have a significant effect on gene regulatory activity and need to be considered when analyzing the functional effect of variants on the activity of these sequences., (© 2023. The Author(s).)

We present RCRUNCH, an end-to-end solution to CLIP data analysis for identification of binding sites and sequence specificity of RNA-binding proteins. RCRUNCH can analyze not only reads that map uniquely to the genome but also those that map to multiple genome locations or across splice boundaries and can consider various types of background in the estimation of read enrichment. By applying RCRUNCH to the eCLIP data from the ENCODE project, we have constructed a comprehensive and homogeneous resource of in-vivo-bound RBP sequence motifs. RCRUNCH automates the reproducible analysis of CLIP data, enabling studies of post-transcriptional control of gene expression., (© 2023. The Author(s).)

It has been recently suggested that a significant fraction of homomer protein-protein interfaces evolve neutrally, without contributing to function, due to a hydrophobic bias in missense mutations. However, the fraction of such gratuitous complexes is currently unknown. Here, we quantified the fraction of homodimers where multimerization is unlikely to contribute to their biochemical function. We show that: 1) ligand binding-site structure predicts whether a homomer is functional or not; the vast majority of homodimers with multichain binding-sites (MBS) are likely to be functional, while in homodimers with single-chain binding-sites (SBS) and small to medium interfaces, quaternary structure is unlikely to be functional in a significant fraction-35%, even up to 42%-of complexes; 2) the hydrophobicity of interfaces changes little with the strength of selection, and the amino acid composition of interfaces is shaped by the "hydrophobic ratchet" in both types, but they are not in a strict equilibrium with mutations; particularly cysteines are much more abundant in mutations than in interfaces or surfaces; 3) in MBS homomers, the interfaces are conserved, while in a high fraction of SBS homomers, the interface is not more conserved than the solvent-accessible surface; and 4) MBS homomer interfaces coevolve more strongly with ligand binding sites than the interfaces of SBS homomers, and MBS complexes have higher capacity to transfer information from ligands across the interfaces than SBS homomers, explaining the enrichment of allostery in the former., (© The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

Nucleotide Binding Site - Leucine Rich Repeat (NBS-LRR) genes play a significant role in plant defense against biotic stresses and are an integral part of signal transduction pathways. Vat gene has been well reported for their role in resistance to Aphis gossypii and viruses transmitted by them. Despite their importance, Vat like NBS-LRR resistance genes have not yet been identified and studied in cotton species. This study report hundreds of orthologous Vat like NBS-LRR genes from the genomes of 18 cotton species through homology searches and the distribution of those identified genes were tend to be clustered on different chromosome. Especially, in a majority of the cases, Vat like genes were located on chromosome number 13 and they all shared two conserved NBS-LRR domains, one disease resistant domain and several repeats of LRR on the investigated cotton Vat like proteins. Gene ontology study on Vat like NBS-LRR genes revealed the molecular functions viz., ADP and protein binding. Phylogenetic analysis also revealed that Vat like sequences of two diploid species, viz., G. arboreum and G. anomalum, were closely related to the sequences of the tetraploids than all other diploids. The Vat like genes of G. aridum and G. schwendimanii were distantly related among diploids and tetraploids species. Various hormones and defense related cis-acting regulatory elements were identified from the 2 kb upstream sequences of the Vat like genes implying their defensive response towards the biotic stresses. Interestingly, G. arboreum and G. trilobum were found to have more regulatory elements than larger genomes of tetraploid cotton species. Thus, the present study provides the evidence for the evolution of Vat like genes in defense mechanisms against aphids infestation in cotton genomes and allows further characterization of candidate genes for developing aphid and aphid transmitted viruses resistant crops through cotton breeding., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The human papillomavirus (HPV) E2 protein is essential for regulating the initiation of viral DNA replication as well as the regulation of transcription of certain HPV-encoded genes. Its ability to recognize and bind to its four recognition sequences in the viral origin is a key step in the initiation of HPV DNA replication. Thus, understanding the mechanism of DNA binding by E2 protein and the unique roles played by individual DNA sequence elements of the replication origin is essential. We have purified the recombinant full-length HPV type 11 E2 protein. Quantitative DNA binding analysis indicated E2 protein bound all four DNA binding sites with reasonably high affinities but with distinct preferences. It bound its cognate binding sites 1, 2, and 4 with higher affinities, but bound binding site 3 with lower affinity. Analysis of binding to these sites unraveled multiple sequence elements that appeared to influence E2 binding affinity and target discrimination, including the sequence of spacer region, flanking sequences, and proximity of E2 binding sites. Thermodynamic analysis indicated hydrophobic interaction in the protein-DNA complex formation. Our studies indicate a large multi-protein complex formation on the HPV-origin DNA, likely due to reasonably high binding affinities as well as intrinsic oligomerization propensity of E2 dimers.

Background: Genome-wide association studies (GWAS) have highlighted over 200 autosomal variants associated with multiple sclerosis (MS). However, variants in non-coding regions such as those encoding microRNAs have not been explored thoroughly, despite strong evidence of microRNA dysregulation in MS patients and model organisms. This study explores the effect of microRNA-associated variants in MS, through the largest publicly available GWAS, which involved 47,429 MS cases and 68,374 controls., Methods: We identified SNPs within the coordinates of microRNAs, ± 5-kb microRNA flanking regions and predicted 3'UTR target-binding sites using miRBase v22, TargetScan 7.0 RNA22 v2.0 and dbSNP v151. We established the subset of microRNA-associated SNPs which were tested in the summary statistics of the largest MS GWAS by intersecting these datasets. Next, we prioritised those microRNA-associated SNPs which are among known MS susceptibility SNPs, are in strong linkage disequilibrium with the former or meet a microRNA-specific Bonferroni-corrected threshold. Finally, we predicted the effects of those prioritised SNPs on their microRNAs and 3'UTR target-binding sites using TargetScan v7.0, miRVaS and ADmiRE., Results: We have identified 30 candidate microRNA-associated variants which meet at least one of our prioritisation criteria. Among these, we highlighted one microRNA variant rs1414273 (MIR548AC) and four 3'UTR microRNA-binding site variants within SLC2A4RG (rs6742), CD27 (rs1059501), MMEL1 (rs881640) and BCL2L13 (rs2587100). We determined changes to the predicted microRNA stability and binding site recognition of these microRNA and target sites., Conclusions: We have systematically examined the functional, structural and regulatory effects of candidate MS variants among microRNAs and 3'UTR targets. This analysis allowed us to identify candidate microRNA-associated MS SNPs and highlights the value of prioritising non-coding RNA variation in GWAS. These candidate SNPs could influence microRNA regulation in MS patients. Our study is the first thorough investigation of both microRNA and 3'UTR target-binding site variation in multiple sclerosis using GWAS summary statistics., (© 2023. The Author(s).)

Despite the vast phenotypic differences observed across primates, their protein products are largely similar to each other at the sequence level. We hypothesized that, since proteins accomplish all their functions via interactions with other molecules, alterations in the sites that participate in these interactions may be of critical importance. To uncover the extent to which these sites evolve across primates, we built a structurally-derived dataset of ~4,200 one-to-one orthologous sequence groups across 18 primate species, consisting of ~68,000 ligand-binding sites that interact with DNA, RNA, small molecules, ions, or peptides. Using this dataset, we identify functionally important patterns of conservation and variation within the amino acid residues that facilitate protein-ligand interactions across the primate phylogeny. We uncover that interaction sites are significantly more conserved than other sites, and that sites binding DNA and RNA further exhibit the lowest levels of variation. We also show that the subset of ligand-binding sites that do vary are enriched in components of gene regulatory pathways and uncover several instances of human-specific ligand-binding site changes within transcription factors. Altogether, our results suggest that ligand-binding sites have experienced selective pressure in primates and propose that variation in these sites may have an outsized effect on phenotypic variation in primates through pleiotropic effects on gene regulation., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 King, Singh. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Somatic mutations are highly enriched at transcription factor (TF) binding sites, with the strongest trend being observed for ultraviolet light (UV)-induced mutations in melanomas. One of the main mechanisms proposed for this hypermutation pattern is the inefficient repair of UV lesions within TF-binding sites, caused by competition between TFs bound to these lesions and the DNA repair proteins that must recognize the lesions to initiate repair. However, TF binding to UV-irradiated DNA is poorly characterized, and it is unclear whether TFs maintain specificity for their DNA sites after UV exposure. We developed UV-Bind, a high-throughput approach to investigate the impact of UV irradiation on protein-DNA binding specificity. We applied UV-Bind to ten TFs from eight structural families, and found that UV lesions significantly altered the DNA-binding preferences of all the TFs tested. The main effect was a decrease in binding specificity, but the precise effects and their magnitude differ across factors. Importantly, we found that despite the overall reduction in DNA-binding specificity in the presence of UV lesions, TFs can still compete with repair proteins for lesion recognition, in a manner consistent with their specificity for UV-irradiated DNA. In addition, for a subset of TFs, we identified a surprising but reproducible effect at certain nonconsensus DNA sequences, where UV irradiation leads to a high increase in the level of TF binding. These changes in DNA-binding specificity after UV irradiation, at both consensus and nonconsensus sites, have important implications for the regulatory and mutagenic roles of TFs in the cell.

The binding of DNA sequences to cell type-specific transcription factors is essential for regulating gene expression in all organisms. Many variants occurring in these binding regions play crucial roles in human disease by disrupting the cis-regulation of gene expression. We first implemented a sequence-based deep learning model called deepBICS to quantify the intensity of transcription factors-DNA binding. The experimental results not only showed the superiority of deepBICS on ChIP-seq data sets but also suggested deepBICS as a language model could help the classification of disease-related and neutral variants. We then built a language model-based method called deepBICS4SNV to predict the pathogenicity of single nucleotide variants. The good performance of deepBICS4SNV on 2 tests related to Mendelian disorders and viral diseases shows the sequence contextual information derived from language models can improve prediction accuracy and generalization capability.

Our sense of smell enables us to navigate a vast space of chemically diverse odour molecules. This task is accomplished by the combinatorial activation of approximately 400 odorant G protein-coupled receptors encoded in the human genome 1-3 . How odorants are recognized by odorant receptors remains unclear. Here we provide mechanistic insight into how an odorant binds to a human odorant receptor. Using cryo-electron microscopy, we determined the structure of the active human odorant receptor OR51E2 bound to the fatty acid propionate. Propionate is bound within an occluded pocket in OR51E2 and makes specific contacts critical to receptor activation. Mutation of the odorant-binding pocket in OR51E2 alters the recognition spectrum for fatty acids of varying chain length, suggesting that odorant selectivity is controlled by tight packing interactions between an odorant and an odorant receptor. Molecular dynamics simulations demonstrate that propionate-induced conformational changes in extracellular loop 3 activate OR51E2. Together, our studies provide a high-resolution view of chemical recognition of an odorant by a vertebrate odorant receptor, providing insight into how this large family of G protein-coupled receptors enables our olfactory sense., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

The Fms-like tyrosine kinase-1 (FLT1) gene is expressed in various types of cells, including vascular endothelial cells and placental trophoblasts, and regulates angiogenesis, inflammation, and pregnancy. However, the basal transcriptional machinery of FLT1 is still not well understood. In this study, we first examined FLT1 promoter activity in three different types of cells, that is, trophoblast-derived cells, vascular endothelial-related cells, and HEK293 cells, using plasmid-based luciferase reporter assays, and showed that a cAMP-response element (CRE) and an ETS-binding site (EBS) are important for FLT1 expression in all cell types. To further examine the importance of these sites at the chromosomal level using HEK293 cells, we introduced CRISPR/Cas9-mediated mutations in these sites on the genomic DNA. HEK293 cells carrying these mutations clearly showed a significant decrease in endogenous FLT1 gene expression. These results suggest that CRE and EBS transcription regulatory elements are crucial for FLT1 gene expression in human tissues., Competing Interests: Declaration of competing interest All authors state no conflict of interest for this research., (Copyright © 2023. Published by Elsevier Inc.)

The limitations associated with natural enzyme catalysis have triggered the rise of the field of protein engineering. Traditional rational design was based on the analysis of protein structural information and catalytic mechanisms to identify key active sites or ligand binding sites to reshape the substrate pocket. The role and significance of functional sites in the active center have been studied extensively. With a deeper understanding of the structure-catalysis relationship map, the entire protein molecule can be filled with residues that play a substantial role in its structure and function. However, the catalytic mechanism underlying distal mutations remains unclear. The aim of this review was to highlight the criticality of the distal site in enzyme engineering based on the following three aspects: What can distal mutations exert on function from mutability landscape? How do distal sites influence enzyme function? How to predict and design distal mutations? This review provides insights into the catalytic mechanism of enzymes from the global interaction network, knowledge from sequence-structure-dynamics-function relationships, and strategies for distal mutation-based protein engineering., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Chromatin-binding proteins are critical regulators of cell state in haematopoiesis 1,2 . Acute leukaemias driven by rearrangement of the mixed lineage leukaemia 1 gene (KMT2Ar) or mutation of the nucleophosmin gene (NPM1) require the chromatin adapter protein menin, encoded by the MEN1 gene, to sustain aberrant leukaemogenic gene expression programs 3-5 . In a phase 1 first-in-human clinical trial, the menin inhibitor revumenib, which is designed to disrupt the menin-MLL1 interaction, induced clinical responses in patients with leukaemia with KMT2Ar or mutated NPM1 (ref. 6 ). Here we identified somatic mutations in MEN1 at the revumenib-menin interface in patients with acquired resistance to menin inhibition. Consistent with the genetic data in patients, inhibitor-menin interface mutations represent a conserved mechanism of therapeutic resistance in xenograft models and in an unbiased base-editor screen. These mutants attenuate drug-target binding by generating structural perturbations that impact small-molecule binding but not the interaction with the natural ligand MLL1, and prevent inhibitor-induced eviction of menin and MLL1 from chromatin. To our knowledge, this study is the first to demonstrate that a chromatin-targeting therapeutic drug exerts sufficient selection pressure in patients to drive the evolution of escape mutants that lead to sustained chromatin occupancy, suggesting a common mechanism of therapeutic resistance., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Although >90% of somatic mutations reside in non-coding regions, few have been reported as cancer drivers. To predict driver non-coding variants (NCVs), we present a transcription factor (TF)-aware burden test based on a model of coherent TF function in promoters. We apply this test to NCVs from the Pan-Cancer Analysis of Whole Genomes cohort and predict 2555 driver NCVs in the promoters of 813 genes across 20 cancer types. These genes are enriched in cancer-related gene ontologies, essential genes, and genes associated with cancer prognosis. We find that 765 candidate driver NCVs alter transcriptional activity, 510 lead to differential binding of TF-cofactor regulatory complexes, and that they primarily impact the binding of ETS factors. Finally, we show that different NCVs within a promoter often affect transcriptional activity through shared mechanisms. Our integrated computational and experimental approach shows that cancer NCVs are widespread and that ETS factors are commonly disrupted., (© 2023. The Author(s).)

Recent comparative genomic studies have identified many human accelerated elements (HARs) with elevated substitution rates in the human lineage. However, it remains unknown to what extent transcription factor binding sites (TFBSs) are under accelerated evolution in humans and other primates. Here, we introduce two pooling-based phylogenetic methods with dramatically enhanced sensitivity to examine accelerated evolution in TFBSs. Using these new methods, we show that more than 6000 TFBSs annotated in the human genome have experienced accelerated evolution in Hominini, apes, and Old World monkeys. Although these TFBSs individually show relatively weak signals of accelerated evolution, they collectively are more abundant than HARs. Also, we show that accelerated evolution in Pol III binding sites may be driven by lineage-specific positive selection, whereas accelerated evolution in other TFBSs might be driven by nonadaptive evolutionary forces. Finally, the accelerated TFBSs are enriched around developmental genes, suggesting that accelerated evolution in TFBSs may drive the divergence of developmental processes between primates., (© 2023. The Author(s).)

Specificity of RNA-binding proteins for target sequences varies considerably. Yet, it is not understood how certain few proteins achieve markedly higher sequence specificity than most others. Here we show that the RNA Recognition Motif of RbFox accomplishes extraordinary sequence specificity by employing functionally and structurally distinct binding modes. Affinity measurements of RbFox for all binding site variants reveal the existence of two distinct binding modes. The first exclusively accommodates cognate and closely related RNAs with high affinity. The second mode accommodates all other RNAs with reduced affinity by imposing large thermodynamic penalties on non-cognate sequences. NMR studies indicate marked structural differences between the two binding modes, including large conformational rearrangements distant from the RNA-binding site. Distinct binding modes by a single RNA-binding module explain extraordinary sequence selectivity and reveal an unknown layer of functional diversity, cross talk and regulation in RNA-protein interactions., (© 2023. The Author(s).)

Here we describe a competitive genome editing method that measures the effect of mutations on molecular functions, based on precision CRISPR editing using template libraries with either the original or altered sequence, and a sequence tag, enabling direct comparison between original and mutated cells. Using the example of the MYC oncogene, we identify important transcriptional targets and show that E-box mutations at MYC target gene promoters reduce cellular fitness., (© 2022. The Author(s).)

Pseudomonas stutzeri phosphite dehydrogenase (PTDH) catalyzes the oxidation of phosphite to phosphate in the presence of NAD, resulting in the formation of NADH. The regeneration of NADH by PTDH is greater than any other enzyme due to the substantial change in the free energy of reaction (G°' = - 63.3 kJ/mol). Presently, improving the stability of PTDH is for a great importance to ensure an economically viable reaction process to produce phosphite as a byproduct for agronomic applications. The binding site of NAD + with PTDH includes thirty-four residues; eight of which have been previously mutated and characterized for their roles in catalysis. In the present study, the unexplored twenty-six key residues involved in the binding of NAD + were subjected to in silico mutagenesis based on the physicochemical properties of the amino acids. The effects of these mutations on the structure, stability, activity, and interaction of PTDH with NAD + were investigated using molecular docking, molecular dynamics simulations, free energy calculations, and secondary structure analysis. We identified seven novel mutations, A155I, G157I, L217I, P235A, V262I, I293A, and I293L, that reduce the compactness of the protein while improving PTDH stability and binding to NAD + ., (© 2023. The Author(s).)

Transcription factors are an integral component of the cellular machinery responsible for regulating many biological processes, and they recognize distinct DNA sequence patterns as well as internal/external signals to mediate target gene expression. The functional roles of an individual transcription factor can be traced back to the functions of its target genes. While such functional associations can be inferred through the use of binding evidence from high-throughput sequencing technologies available today, including chromatin immunoprecipitation sequencing, such experiments can be resource-consuming. On the other hand, exploratory analysis driven by computational techniques can alleviate this burden by narrowing the search scope, but the results are often deemed low-quality or non-specific by biologists. In this paper, we introduce a data-driven, statistics-based strategy to predict novel functional associations for transcription factors in the model plant Arabidopsis thaliana . To achieve this, we leverage one of the largest available gene expression compendia to build a genome-wide transcriptional regulatory network and infer regulatory relationships among transcription factors and their targets. We then use this network to build a pool of likely downstream targets for each transcription factor and query each target pool for functionally enriched gene ontology terms. The results exhibited sufficient statistical significance to annotate most of the transcription factors in Arabidopsis with highly specific biological processes. We also perform DNA binding motif discovery for transcription factors based on their target pool. We show that the predicted functions and motifs strongly agree with curated databases constructed from experimental evidence. In addition, statistical analysis of the network revealed interesting patterns and connections between network topology and system-level transcriptional regulation properties. We believe that the methods demonstrated in this work can be extended to other species to improve the annotation of transcription factors and understand transcriptional regulation on a system level.

Motivation: Cell-type-specific gene expression is maintained in large part by transcription factors (TFs) selectively binding to distinct sets of sites in different cell types. Recent research works have provided evidence that such cell-type-specific binding is determined by TF's intrinsic sequence preferences, cooperative interactions with co-factors, cell-type-specific chromatin landscapes and 3D chromatin interactions. However, computational prediction and characterization of cell-type-specific and shared binding sites is rarely studied., Results: In this article, we propose two computational approaches for predicting and characterizing cell-type-specific and shared binding sites by integrating multiple types of features, in which one is based on XGBoost and another is based on convolutional neural network (CNN). To validate the performance of our proposed approaches, ChIP-seq datasets of 10 binding factors were collected from the GM12878 (lymphoblastoid) and K562 (erythroleukemic) human hematopoietic cell lines, each of which was further categorized into cell-type-specific (GM12878- and K562-specific) and shared binding sites. Then, multiple types of features for these binding sites were integrated to train the XGBoost- and CNN-based models. Experimental results show that our proposed approaches significantly outperform other competing methods on three classification tasks. Moreover, we identified independent feature contributions for cell-type-specific and shared sites through SHAP values and explored the ability of the CNN-based model to predict cell-type-specific and shared binding sites by excluding or including DNase signals. Furthermore, we investigated the generalization ability of our proposed approaches to different binding factors in the same cellular environment., Availability and Implementation: The source code is available at: https://github.com/turningpoint1988/CSSBS., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press.)

Most of the currently available disease resistance (R) genes have NBS (nucleotide-binding site) and LRR (leucine-rich-repeat) domain which belongs to the NBS-LRR gene family. The whole genome sequencing of Broussonetia papyrifera provides an important bioinformatics database for the study of the NBS-LRR gene family. In this study, 328 NBS-LRR family genes were identified and classified in B. papyrifera according to different classification schemes, where there are 92 N types, 47 CN type, 54 CNL type, 29 NL types, 55 TN type, and 51 TNL type. Subsequently, we conducted bioinformatics analysis of the NBS-LRR gene family. Classification, motif analysis of protein sequences, and phylogenetic tree studies of the NBS-LRR genes in B. papyrifera provide important basis for the functional study of NBS-LRR family genes. Additionally, we performed structural analysis of the chromosomal location, physicochemical properties, and sequences identified by genetic characterization. In addition, through the analysis of GO enrichment, it was found that NBS-LRR genes were involved in defense responses and were significantly enriched in biological stimulation, immune response, and abiotic stress. In addition, we found that Bp06g0955 was the most sensitive to low temperature and encoded the RPM1 protein by analyzing the low temperature transcriptome data of B. papyrifera. Quantitative results of gene expression after 48 h of Fusarium infection showed that Bp01g3293 increased 14 times after infection, which encodes RPM1 protein. The potential of NBS-LRR gene responsive to biotic and abiotic stresses can be exploited to improve the resistance of B. papyrifera., (© 2022. The Author(s), under exclusive licence to Springer Nature B.V.)