Role of DNA sequence based structural features of promoters in transcription initiation and gene expression

GraphPro: An interpretable graph neural network-based model for identifying promoters in multiple species

Promoters are DNA sequences that bind with RNA polymerase to initiate transcription, regulating this process through interactions with transcription factors. Accurate identification of promoters is crucial for understanding gene expression regulation mechanisms and developing therapeutic approaches for various diseases. However, experimental techniques for promoter identification are often expensive, time-consuming, and inefficient, necessitating the development of accurate and efficient computational models for this task. Enhancing the model's ability to recognize promoters across multiple species and improving its interpretability pose significant challenges. In this study, we introduce a novel interpretable model based on graph neural networks, named GraphPro, for multi-species promoter identification. Initially, we encode the sequences using k-tuple nucleotide frequency pattern, dinucleotide physicochemical properties, and dna2vec. Subsequently, we construct two feature extraction modules based on convolutional neural networks and graph neural networks. These modules aim to extract specific motifs from the promoters, learn their dependencies, and capture the underlying structural features of the promoters, providing a more comprehensive representation. Finally, a fully connected neural network predicts whether the input sequence is a promoter. We conducted extensive experiments on promoter datasets from eight species, including Human, Mouse, and Escherichia coli. The experimental results show that the average Sn, Sp, Acc and MCC values of GraphPro are 0.9123, 0.9482, 0.8840 and 0.7984, respectively. Compared with previous promoter identification methods, GraphPro not only achieves better recognition accuracy on multiple species, but also outperforms all previous methods in cross-species prediction ability. Furthermore, by visualizing GraphPro's decision process and analyzing the sequences matching the transcription factor binding motifs captured by the model, we validate its significant advantages in biological interpretability. The source code for GraphPro is available at https://github.com/liuliwei1980/GraphPro.

Discerning the Role of DNA Sequence, Shape, and Flexibility in Recognition by Drosophila Transcription Factors

The precise spatial and temporal orchestration of gene expression is crucial for the ontogeny of an organism and is mainly governed by transcription factors (TFs). The mechanism of recognition of cognate sites amid millions of base pairs in the genome by TFs is still incompletely understood. In this study, we focus on DNA sequence composition, shape, and flexibility preferences of 28 quintessential TFs from Drosophila melanogaster that are critical to development and body patterning mechanisms. Our study finds that TFs exhibit distinct predilections for DNA shape, flexibility, and sequence compositions in the proximity of transcription factor binding sites (TFBSs). Notably, certain zinc finger proteins prefer GC-rich areas with less negative propeller twist, while homeodomains mainly seek AT-rich regions with a more negative propeller twist at their sites. Intriguingly, while numerous cofactors share similar binding site preferences and bind closer to each other in the genome, some cofactors that have different preferences bind farther apart. These findings shed light on TF DNA recognition and provide novel insights into possible cofactor binding and transcriptional regulation mechanisms.

DNA structural features and variability of complete MHC locus sequences

The major histocompatibility (MHC) locus, also known as the Human Leukocyte Antigen (HLA) genes, is located on the short arm of chromosome 6, and contains three regions (Class I, Class II and Class III). This 5 Mbp locus is one of the most variable regions of the human genome, yet it also encodes a set of highly conserved and important proteins related to immunological response. Genetic variations in this region are responsible for more diseases than in the entire rest of the human genome. However, information on local structural features of the DNA is largely ignored. With recent advances in long-read sequencing technology, it is now becoming possible to sequence the entire 5 Mbp MHC locus, producing complete diploid haplotypes of the whole region. Here, we describe structural maps based on the complete sequences from six different homozygous HLA cell lines. We find long-range structural variability in the different sequences for DNA stacking energy, position preference and curvature, variation in repeats, as well as more local changes in regions forming open chromatin structures, likely to influence gene expression levels. These structural maps can be useful in visualizing large scale structural variation across HLA types, in particular when this can be complemented with epigenetic signals.

MLDSPP: Bacterial Promoter Prediction Tool Using DNA Structural Properties with Machine Learning and Explainable AI

Bacterial promoters play a crucial role in gene expression by serving as docking sites for the transcription initiation machinery. However, accurately identifying promoter regions in bacterial genomes remains a challenge due to their diverse architecture and variations. In this study, we propose MLDSPP (Machine Learning and Duplex Stability based Promoter prediction in Prokaryotes), a machine learning-based promoter prediction tool, to comprehensively screen bacterial promoter regions in 12 diverse genomes. We leveraged biologically relevant and informative DNA structural properties, such as DNA duplex stability and base stacking, and state-of-the-art machine learning (ML) strategies to gain insights into promoter characteristics. We evaluated several machine learning models, including Support Vector Machines, Random Forests, and XGBoost, and assessed their performance using accuracy, precision, recall, specificity, F1 score, and MCC metrics. Our findings reveal that XGBoost outperformed other models and current state-of-the-art promoter prediction tools, namely Sigma70pred and iPromoter2L, achieving F1-scores >95% in most systems. Significantly, the use of one-hot encoding for representing nucleotide sequences complements these structural features, enhancing our XGBoost model's predictive capabilities. To address the challenge of model interpretability, we incorporated explainable AI techniques using Shapley values. This enhancement allows for a better understanding and interpretation of the predictions of our model. In conclusion, our study presents MLDSPP as a novel, generic tool for predicting promoter regions in bacteria, utilizing original downstream sequences as nonpromoter controls. This tool has the potential to significantly advance the field of bacterial genomics and contribute to our understanding of gene regulation in diverse bacterial systems.

Structural and dynamical aspect of DNA motif sequence specific binding of AP-1 transcription factor

Activator protein-1 (AP-1) comprises one of the largest and most evolutionary conserved families of ubiquitous eukaryotic transcription factors that act as a pioneer factor. Diversity in DNA binding interaction of AP-1 through a conserved basic-zipper (bZIP) domain directs in-depth understanding of how AP-1 achieves its DNA binding selectivity and consequently gene regulation specificity. Here, we address the structural and dynamical aspects of the DNA target recognition process of AP-1 using microsecond-long atomistic simulations based on the structure of the human AP-1 FosB/JunD bZIP-DNA complex. Our results show the unique role of DNA shape features in selective base specific interactions, characteristic ion population, and solvation properties of DNA grooves to form the motif sequence specific AP-1-DNA complex. The TpG step at the two terminals of the AP-1 site plays an important role in the structural adjustment of DNA by modifying the helical twist in the AP-1 bound state. We addressed the role of intrinsic motion of the bZIP domain in terms of opening and closing gripper motions of DNA binding helices, in target site recognition and binding of AP-1 factors. Our observations suggest that binding to the cognate motif in DNA is mainly accompanied with the precise adjustment of closing gripper motion of DNA binding helices of the bZIP domain.

CDBProm: the Comprehensive Directory of Bacterial Promoters

The decreasing cost of whole genome sequencing has produced high volumes of genomic information that require annotation. The experimental identification of promoter sequences, pivotal for regulating gene expression, is a laborious and cost-prohibitive task. To expedite this, we introduce the Comprehensive Directory of Bacterial Promoters (CDBProm), a directory of in-silico predicted bacterial promoter sequences. We first identified that an Extreme Gradient Boosting (XGBoost) algorithm would distinguish promoters from random downstream regions with an accuracy of 87%. To capture distinctive promoter signals, we generated a second XGBoost classifier trained on the instances misclassified in our first classifier. The predictor of CDBProm is then fed with over 55 million upstream regions from more than 6000 bacterial genomes. Upon finding potential promoter sequences in upstream regions, each promoter is mapped to the genomic data of the organism, linking the predicted promoter with its coding DNA sequence, and identifying the function of the gene regulated by the promoter. The collection of bacterial promoters available in CDBProm enables the quantitative analysis of a plethora of bacterial promoters. Our collection with over 24 million promoters is publicly available at https://aw.iimas.unam.mx/cdbprom/.

Flanking AT base pairs affect the localization of monovalent cations in DNA A-tracts

Capillary electrophoresis has been used to measure the free solution mobilities of a series of 26-base pair (bp) DNA oligomers containing two phased A4T1in-tracts embedded in flanking sequences containing 0 to 11 additional AT bps. A random-sequence 26-bp oligomer with 12 isolated AT bps was used as the reference. Mobility ratios (A-tract/reference) were measured in background electrolytes (BGEs) containing mixtures of small monovalent cations and tetrabutylammonium (TBA+ ) or tetrapropylammonium (TPA+ ) ions. The mobility ratios observed in 0.3 M TBA+ were >1.00, suggesting that the TBA+ ions had formed electrostatic contact pairs with the AT bp in the reference and in the A-tract flanking sequences, decreasing the mobilities of both oligomers. The TBA-AT pairing interactions could be eliminated by increasing the concentration of small monovalent cations in the BGE. In 0.3 M TPA+ , electrostatic contact pairs were formed with the AT bps in the flanking sequences and in the A-tracts. Interestingly, the shapes of the mobility ratio profiles observed for the A4T1in-tract oligomers depended on the total number of A + T residues in the oligomer.

Towards a rational approach to promoter engineering: understanding the complexity of transcription initiation in prokaryotes

Promoter sequences are important genetic control elements. Through their interaction with RNA polymerase they determine transcription strength and specificity, thereby regulating the first step in gene expression. Consequently, they can be targeted as elements to control predictability and tuneability of a genetic circuit, which is essential in applications such as the development of robust microbial cell factories. This review considers the promoter elements implicated in the three stages of transcription initiation, detailing the complex interplay of sequence-specific interactions that are involved, and highlighting that DNA sequence features beyond the core promoter elements work in a combinatorial manner to determine transcriptional strength. In particular, we emphasize that, aside from promoter recognition, transcription initiation is also defined by the kinetics of open complex formation and promoter escape, which are also known to be highly sequence specific. Significantly, we focus on how insights into these interactions can be manipulated to lay the foundation for a more rational approach to promoter engineering.

Predicting DNA structure using a deep learning method

Understanding the mechanisms of protein-DNA binding is critical in comprehending gene regulation. Three-dimensional DNA structure, also described as DNA shape, plays a key role in these mechanisms. In this study, we present a deep learning-based method, Deep DNAshape, that fundamentally changes the current k-mer based high-throughput prediction of DNA shape features by accurately accounting for the influence of extended flanking regions, without the need for extensive molecular simulations or structural biology experiments. By using the Deep DNAshape method, DNA structural features can be predicted for any length and number of DNA sequences in a high-throughput manner, providing an understanding of the effects of flanking regions on DNA structure in a target region of a sequence. The Deep DNAshape method provides access to the influence of distant flanking regions on a region of interest. Our findings reveal that DNA shape readout mechanisms of a core target are quantitatively affected by flanking regions, including extended flanking regions, providing valuable insights into the detailed structural readout mechanisms of protein-DNA binding. Furthermore, when incorporated in machine learning models, the features generated by Deep DNAshape improve the model prediction accuracy. Collectively, Deep DNAshape can serve as versatile and powerful tool for diverse DNA structure-related studies.

A Comprehensive Analysis of Auxin Response Factor Gene Family in Melastoma dodecandrum Genome

Auxin Response Factors (ARFs) mediate auxin signaling and govern diverse biological processes. However, a comprehensive analysis of the ARF gene family and identification of their key regulatory functions have not been conducted in Melastoma dodecandrum, leading to a weak understanding of further use and development for this functional shrub. In this study, we successfully identified a total of 27 members of the ARF gene family in M. dodecandrum and classified them into Class I-III. Class II-III showed more significant gene duplication than Class I, especially for MedARF16s. According to the prediction of cis-regulatory elements, the AP2/ERF, BHLH, and bZIP transcription factor families may serve as regulatory factors controlling the transcriptional pre-initiation expression of MedARF. Analysis of miRNA editing sites reveals that miR160 may play a regulatory role in the post-transcriptional expression of MeARF. Expression profiles revealed that more than half of the MedARFs exhibited high expression levels in the stem compared to other organs. While there are some specific genes expressed only in flowers, it is noteworthy that MedARF16s, MedARF7A, and MedARF9B, which are highly expressed in stems, also demonstrate high expressions in other organs of M. dodecandrum. Further hormone treatment experiments revealed that these MedARFs were sensitive to auxin changes, with MedARF6C and MedARF7A showing significant and rapid changes in expression upon increasing exogenous auxin. In brief, our findings suggest a crucial role in regulating plant growth and development in M. dodecandrum by responding to changes in auxin. These results can provide a theoretical basis for future molecular breeding in Myrtaceae.

Three new LmbU targets outside lmb cluster inhibit lincomycin biosynthesis in Streptomyces lincolnensis

BACKGROUND

Antibiotics biosynthesis is usually regulated by the cluster-situated regulatory gene(s) (CSRG(s)), which directly regulate the genes within the corresponding biosynthetic gene cluster (BGC). Previously, we have demonstrated that LmbU functions as a cluster-situated regulator (CSR) of lincomycin. And it has been found that LmbU regulates twenty non-lmb genes through comparative transcriptomic analysis. However, the regulatory mode of CSRs' targets outside the BGC remains unknown.

RESULTS

We screened the targets of LmbU in the whole genome of Streptomyces lincolnensis and found fourteen candidate targets, among which, eight targets can bind to LmbU by electrophoretic mobility shift assays (EMSA). Reporter assays in vivo revealed that LmbU repressed the transcription of SLINC_0469 and SLINC_1037 while activating the transcription of SLINC_8097. In addition, disruptions of SLINC_0469, SLINC_1037, and SLINC_8097 promoted the production of lincomycin, and qRT-PCR showed that SLINC_0469, SLINC_1037, and SLINC_8097 inhibited transcription of the lmb genes, indicating that all the three regulators can negatively regulate lincomycin biosynthesis.

CONCLUSIONS

LmbU can directly regulate genes outside the lmb cluster, and these genes can affect both lincomycin biosynthesis and the transcription of lmb genes. Our results first erected the cascade regulatory circuit of LmbU and regulators outside lmb cluster, which provides the theoretical basis for the functional research of LmbU family proteins.

Computational analysis on the dissemination of non-B DNA structural motifs in promoter regions of 1180 cellular genomes

The promoter regions of gene regulation are under evolutionary constraints and earlier studies uncovered that they are characterized by enrichment of functional non-B DNA structural signatures like curved DNA, cruciform DNA, G-quadruplex, triple-helical DNA, slipped DNA structures, and Z-DNA. However, these studies are restricted to a few model organisms, single non-B DNA motif types, or whole genomic sequences, and their comparative accumulation in promoter regions of different domains of life has not been reported comprehensively. In this study, for the first time, we investigated the preponderance of non-B DNA-prone motifs in promoter regions in 1180 genomes belonging to 28 taxonomic groups using the non-B DNA Motif Search Tool (nBMST). The trends suggest that they are predominant in promoters compared to the upstream and downstream regions of all three domains of life and variably linked to taxonomic groups. Cruciform DNA motif is the most abundant form of non-B DNA, spanning from archaea to lower eukaryotes. Curved DNA motifs are prominent in host-associated bacteria, and suppressed in mammals. Triplex-DNA and slipped DNA structure repeats are discretely dispersed in all lineages. G-quadruplex motifs are significantly enriched in mammals. We also observed that the unique enrichment of non-B DNA in promoters is strongly linked to genome GC, size, evolutionary time divergence, and ecological adaptations. Overall, our work systematically reports the unique non-B DNA structural landscape of cellular organisms from the perspective of the cis-regulatory code of genomes.

Deep DNAshape: Predicting DNA shape considering extended flanking regions using a deep learning method

Understanding the mechanisms of protein-DNA binding is critical in comprehending gene regulation. Three-dimensional DNA shape plays a key role in these mechanisms. In this study, we present a deep learning-based method, Deep DNAshape, that fundamentally changes the current k -mer based high-throughput prediction of DNA shape features by accurately accounting for the influence of extended flanking regions, without the need for extensive molecular simulations or structural biology experiments. By using the Deep DNAshape method, refined DNA shape features can be predicted for any length and number of DNA sequences in a high-throughput manner, providing a deeper understanding of the effects of flanking regions on DNA shape in a target region of a sequence. Deep DNAshape method provides access to the influence of distant flanking regions on a region of interest. Our findings reveal that DNA shape readout mechanisms of a core target are quantitatively affected by flanking regions, including extended flanking regions, providing valuable insights into the detailed structural readout mechanisms of protein-DNA binding. Furthermore, when incorporated in machine learning models, the features generated by Deep DNAshape improve the model prediction accuracy. Collectively, Deep DNAshape can serve as a versatile and powerful tool for diverse DNA structure-related studies.

Monovalent cation localization in DNA A-tracts with different sequences

The free solution mobilities of 26-base pair (bp) DNA oligomers containing A-tracts with and without internal ApT steps have been measured by capillary electrophoresis, using the mobility of a 26-bp random-sequence oligomer as a reference. The background electrolytes (BGEs) contained mixtures of Li+ and tetrapropylammonium (TPA+ ) ions, keeping the total cation concentration constant at 0.3 M. The mobility ratios equaled 1.00 in 0.3 M TPA+ , indicating that the A-tract and reference oligomers had the same B-form conformation in this BGE. With increasing [Li+ ], the mobility ratio decreased as Li+ ions became localized in the A-tract minor groove, suggesting that the A-tract was now in the B* conformation. If the A-tract contained an internal ApT step and the oligomer contained less than ∼50% A + T, the mobility ratio reached a reduced plateau value that remained constant as the [Li+ ] increased to 0.3 M. However, for A-tracts without an internal ApT step and for A-tracts embedded in oligomers containing more than 50% A + T, the mobility ratios increased again at high [Li+ ], eventually reaching a plateau value of 1.00. Hence, DNA A-tracts in solution appear to exist as mixtures of the B and B* conformations, with the fractional concentration of each conformer depending on the [Li+ ], the A-tract sequence, and the total A + T content of the oligomer.

Promoter editing for the genetic improvement of crops

Gene expression plays a fundamental role in the regulation of agronomically important traits in crop plants. The genetic manipulation of plant promoters through genome editing has emerged as an effective strategy to create favorable traits in crops by altering the expression pattern of the pertinent genes. Promoter editing can be applied in a directed manner, where nucleotide sequences associated with favorable traits are precisely generated. Alternatively, promoter editing can also be exploited as a random mutagenic approach to generate novel genetic variations within a designated promoter, from which elite alleles are selected based on their phenotypic effects. Pioneering studies have demonstrated the potential of promoter editing in engineering agronomically important traits as well as in mining novel promoter alleles valuable for plant breeding. In this review, we provide an update on the application of promoter editing in crops for increased yield, enhanced tolerance to biotic and abiotic stresses, and improved quality. We also discuss several remaining technical bottlenecks and how this strategy may be better employed for the genetic improvement of crops in the future.

DNA structural properties of DNA binding sites for 21 transcription factors in the mycobacterial genome

Mycobacterium tuberculosis, the causative agent of tuberculosis, has evolved over time into a multidrug resistance strain that poses a serious global pandemic health threat. The ability to survive and remain dormant within the host macrophage relies on multiple transcription factors contributing to virulence. To date, very limited structural insights from crystallographic and NMR studies are available for TFs and TF-DNA binding events. Understanding the role of DNA structure in TF binding is critical to deciphering MTB pathogenicity and has yet to be resolved at the genome scale. In this work, we analyzed the compositional and conformational preference of 21 mycobacterial TFs, evident at their DNA binding sites, in local and global scales. Results suggest that most TFs prefer binding to genomic regions characterized by unique DNA structural signatures, namely, high electrostatic potential, narrow minor grooves, high propeller twist, helical twist, intrinsic curvature, and DNA rigidity compared to the flanking sequences. Additionally, preference for specific trinucleotide motifs, with clear periodic signals of tetranucleotide motifs, are observed in the vicinity of the TF-DNA interactions. Altogether, our study reports nuanced DNA shape and structural preferences of 21 TFs.

DeePromClass: Delineator for Eukaryotic Core Promoters Employing Deep Neural Networks

Computational promoter identification in eukaryotes is a classical biological problem that should be refurbished with the availability of an avalanche of experimental data and emerging deep learning technologies. The current knowledge indicates that eukaryotic core promoters display multifarious signals such as TATA-Box, Inr element, TCT, and Pause-button, etc., and structural motifs such as G-quadruplexes. In the present study, we combined the power of deep learning with a plethora of promoter motifs to delineate promoter and non-promoters gleaned from the statistical properties of DNA sequence arrangement. To this end, we implemented convolutional neural network (CNN) and long short-term memory (LSTM) recurrent neural network architecture for five model systems with [-100 to +50] segments relative to the transcription start site being the core promoter. Unlike previous state-of-the-art tools, which furnish a binary decision of promoter or non-promoter, we classify a chunk of 151mer sequence into a promoter along with the consensus signal type or a non-promoter. The combined CNN-LSTM model; we call "DeePromClass", achieved testing accuracy of 90.6%, 93.6%, 91.8%, 86.5%, and 84.0% for S. cerevisiae, C. elegans, D. melanogaster, Mus musculus, and Homo sapiens respectively. In total, our tool provides an insightful update on next-generation promoter prediction tools for promoter biologists.

DeepLncPro: an interpretable convolutional neural network model for identifying long non-coding RNA promoters

Long non-coding RNA (lncRNA) plays important roles in a series of biological processes. The transcription of lncRNA is regulated by its promoter. Hence, accurate identification of lncRNA promoter will be helpful to understand its regulatory mechanisms. Since experimental techniques remain time consuming for gnome-wide promoter identification, developing computational tools to identify promoters are necessary. However, only few computational methods have been proposed for lncRNA promoter prediction and their performances still have room to be improved. In the present work, a convolutional neural network based model, called DeepLncPro, was proposed to identify lncRNA promoters in human and mouse. Comparative results demonstrated that DeepLncPro was superior to both state-of-the-art machine learning methods and existing models for identifying lncRNA promoters. Furthermore, DeepLncPro has the ability to extract and analyze transcription factor binding motifs from lncRNAs, which made it become an interpretable model. These results indicate that the DeepLncPro can server as a powerful tool for identifying lncRNA promoters. An open-source tool for DeepLncPro was provided at https://github.com/zhangtian-yang/DeepLncPro.

Sequence-Specific Structural Features and Solvation Properties of Transcription Factor Binding DNA Motifs: Insights from Molecular Dynamics Simulation

Sequence-specific recognition of transcription factor (TF) binding motifs in the target site of DNA over the vast amount of non-target DNA is of primary importance for the transcriptional regulation of gene expression by the TFs. Binding of TFs to the target site of DNA relies not only on the direct contact formation but also on the structural and conformational features of DNA. Recognition of DNA structural features or shape readout by proteins is an important factor in the context of TF-DNA interaction. Based on the atomistic molecular simulation, here we report the sequence-dependent unique structural features, solvation, and ion-binding properties of biologically relevant AT- and GC-rich human TF binding motifs in DNA. Counterion and water distribution around the motif is found to be sensitive to the motif sequence, which is accompanied with the DNA shape features. The motif sequence affects the electrostatic potential along the grooves, and cytosine methylation alters the DNA shape features. Characteristic solvation properties of TF binding motif DNA fragments infer that an ionic environment and hydration influences are essential to describe TF-DNA interactions.

Flexibility of flanking DNA is a key determinant of transcription factor affinity for the core motif

Selective gene regulation is mediated by recognition of specific DNA sequences by transcription factors (TFs). The extremely challenging task of searching out specific cognate DNA binding sites among several million putative sites within the eukaryotic genome is achieved by complex molecular recognition mechanisms. Elements of this recognition code include the core binding sequence, the flanking sequence context, and the shape and conformational flexibility of the composite binding site. To unravel the extent to which DNA flexibility modulates TF binding, in this study, we employed experimentally guided molecular dynamics simulations of ternary complex of closely related Hox heterodimers Exd-Ubx and Exd-Scr with DNA. Results demonstrate that flexibility signatures embedded in the flanking sequences impact TF binding at the cognate binding site. A DNA sequence has intrinsic shape and flexibility features. While shape features are localized, our analyses reveal that flexibility features of the flanking sequences percolate several basepairs and allosterically modulate TF binding at the core. We also show that lack of flexibility in the motif context can render the cognate site resistant to protein-induced shape changes and subsequently lower TF binding affinity. Overall, this study suggests that flexibility-guided DNA shape, and not merely the static shape, is a key unexplored component of the complex DNA-TF recognition code.

Simple and accurate transcriptional start site identification using Smar2C2 and examination of conserved promoter features

The precise and accurate identification and quantification of transcriptional start sites (TSSs) is key to understanding the control of transcription. The core promoter consists of the TSS and proximal non-coding sequences, which are critical in transcriptional regulation. Therefore, the accurate identification of TSSs is important for understanding the molecular regulation of transcription. Existing protocols for TSS identification are challenging and expensive, leaving high-quality data available for a small subset of organisms. This sparsity of data impairs study of TSS usage across tissues or in an evolutionary context. To address these shortcomings, we developed Smart-Seq2 Rolling Circle to Concatemeric Consensus (Smar2C2), which identifies and quantifies TSSs and transcription termination sites. Smar2C2 incorporates unique molecular identifiers that allowed for the identification of as many as 70 million sites, with no known upper limit. We have also generated TSS data sets from as little as 40 pg of total RNA, which was the smallest input tested. In this study, we used Smar2C2 to identify TSSs in Glycine max (soybean), Oryza sativa (rice), Sorghum bicolor (sorghum), Triticum aestivum (wheat) and Zea mays (maize) across multiple tissues. This wide panel of plant TSSs facilitated the identification of evolutionarily conserved features, such as novel patterns in the dinucleotides that compose the initiator element (Inr), that correlated with promoter expression levels across all species examined. We also discovered sequence variations in known promoter motifs that are positioned reliably close to the TSS, such as differences in the TATA box and in the Inr that may prove significant to our understanding and control of transcription initiation. Smar2C2 allows for the easy study of these critical sequences, providing a tool to facilitate discovery.

PredPromoter-MF(2L): A Novel Approach of Promoter Prediction Based on Multi-source Feature Fusion and Deep Forest

Promoters short DNA sequences play vital roles in initiating gene transcription. However, it remains a challenge to identify promoters using conventional experiment techniques in a high-throughput manner. To this end, several computational predictors based on machine learning models have been developed, while their performance is unsatisfactory. In this study, we proposed a novel two-layer predictor, called PredPromoter-MF(2L), based on multi-source feature fusion and ensemble learning. PredPromoter-MF(2L) was developed based on various deep features learned by a pre-trained deep learning network model and sequence-derived features. Feature selection based on XGBoost was applied to reduce fused features dimensions, and a cascade deep forest model was trained on the selected feature subset for promoter prediction. The results both fivefold cross-validation and independent test demonstrated that PredPromoter-MF(2L) outperformed state-of-the-art methods.

Systematic Identification and Expression Analysis of the Auxin Response Factor (ARF) Gene Family in Ginkgo biloba L

Auxin participates in various physiological and molecular response-related developmental processes and is a pivotal hormone that regulates phenotypic formation in plants. Auxin response factors (ARFs) are vital transcription factors that mediate downstream auxin signaling by explicitly binding to auxin-responsive genes' promoters. Here, to investigate the possible developmental regulatory functions of ARFs in Ginkgo biloba, through employing comprehensive bioinformatics, we recognized 15 putative GbARF members. Conserved domains and motifs, gene and protein structure, gene duplication, GO enrichment, transcriptome expression profiles, and qRT-PCR all showed that Group I and III members were highly conserved. Among them, GbARF10b and GbARF10a were revealed as transcriptional activators in the auxin response for the development of Ginkgo male flowers through sequences alignment, cis-elements analysis and GO annotation; the results were corroborated for the treatment of exogenous SA. Moreover, the GbARFs expansion occurred predominantly by segmental duplication, and most GbARFs have undergone purifying selection. The Ka/Ks ratio test identified the functional consistence of GbARF2a and GbARF2c, GbARF10b, and GbARF10a in tissue expression profiles and male flower development. In summary, our study established a new research basis for exploring Ginkgo GbARF members' roles in floral organ development and hormone response.

dCas9 fusion to computer-designed PRC2 inhibitor reveals functional TATA box in distal promoter region

Bifurcation of cellular fates, a critical process in development, requires histone 3 lysine 27 methylation (H3K27me3) marks propagated by the polycomb repressive complex 2 (PRC2). However, precise chromatin loci of functional H3K27me3 marks are not yet known. Here, we identify critical PRC2 functional sites at high resolution. We fused a computationally designed protein, EED binder (EB), which competes with EZH2 and thereby inhibits PRC2 function, to dCas9 (EBdCas9) to allow for PRC2 inhibition at a precise locus using gRNA. Targeting EBdCas9 to four different genes (TBX18, p16, CDX2, and GATA3) results in precise H3K27me3 and EZH2 reduction, gene activation, and functional outcomes in the cell cycle (p16) or trophoblast transdifferentiation (CDX2 and GATA3). In the case of TBX18, we identify a PRC2-controlled, functional TATA box >500 bp upstream of the TBX18 transcription start site (TSS) using EBdCas9. Deletion of this TATA box eliminates EBdCas9-dependent TATA binding protein (TBP) recruitment and transcriptional activation. EBdCas9 technology may provide a broadly applicable tool for epigenomic control of gene regulation.

Delineation of the DNA Structural Features of Eukaryotic Core Promoter Classes

The eukaryotic transcription is orchestrated from a chunk of the DNA region stated as the core promoter. Multifarious and punctilious core promoter signals, viz., TATA-box, Inr, BREs, and Pause Button, are associated with a subset of genes and regulate their spatiotemporal expression. However, the core promoter architecture linked with these signals has not been investigated exhaustively for several species. In this study, we attempted to envisage the adaptive binding landscape of the transcription initiation machinery as a function of DNA structure. To this end, we deployed a set of k-mer based DNA structural estimates and regular expression models derived from experiments, molecular dynamic simulations, and theoretical frameworks, and high-throughout promoter data sets retrieved from the eukaryotic promoter database. We categorized protein-coding gene core promoters based on characteristic motifs at precise locations and analyzed the B-DNA structural properties and non-B-DNA structural motifs for 15 different eukaryotic genomes. We observed that Inr, BREd, and no-motif classes display common patterns of DNA sequence and structural environment. TATA-containing, BREu, and Pause Button classes show a deviant behavior with the TATA class displaying varied axial and twisting flexibility while BREu and Pause Button leaned toward G-quadruplex motif enrichment. Intriguingly, DNA meltability and shape signals are conserved irrespective of the presence or absence of distinct core promoter motifs in the majority of species. Altogether, here we delineated the conserved DNA structural signals associated with several promoter classes that may contribute to the chromatin configuration, orchestration of transcription machinery, and DNA duplex melting during the transcription process.

In silico identification of variations in microRNAs with a potential impact on dairy traits using whole ruminant genome SNP datasets

MicroRNAs are small noncoding RNAs that have important roles in the lactation process and milk biosynthesis. Some polymorphisms have been studied in various livestock species from the perspective of pathology or production traits. To target variants that could be the causal variants of dairy traits, genetic variants of microRNAs expressed in the mammary gland or present in milk and localized in dairy quantitative trait loci (QTLs) were investigated in bovine, caprine, and ovine species. In this study, a total of 59,124 (out of 28 millions), 13,427 (out of 87 millions), and 4761 (out of 38 millions) genetic variants in microRNAs expressed in the mammary gland or present in milk were identified in bovine, caprine, and ovine species, respectively. A total of 4679 of these detected bovine genetic variants are located in dairy QTLs. In caprine species, 127 genetic variants are localized in dairy QTLs. In ovine species, no genetic variant was identified in dairy QTLs. This study leads to the detection of microRNA genetic variants of interest in the context of dairy production, taking advantage of whole genome data to identify microRNA genetic variants expressed in the mammary gland and localized in dairy QTLs.

Analysis of nucleoid-associated protein-binding regions reveals DNA structural features influencing genome organization in Mycobacterium tuberculosis

Nucleoid-associated proteins (NAPs) maintain bacterial nucleoid configuration through their architectural properties of DNA bending, wrapping, and bridging. However, the contribution of DNA structural alterations to DNA-NAP recognition at the genomic scale remains unresolved. Present work dissects the DNA sequence, shape and altered structural preferences at a genomic scale for six NAPs in Mycobacterium tuberculosis. Results suggest narrower minor groove width (MGW) and higher DNA rigidity are marked for the binding sites of EspR and Lsr2, while mIHF, MtHU and NapM have heterogeneous DNA structural predilections. In contrast, WhiB4-DNA-binding sites were characterized by wider MGW, highly deformable and less curved DNA. This work provides systematic insight into NAP-mediated genome organization as a function of DNA structural features.

Characterization of promoters in archaeal genomes based on DNA structural parameters

The transcription machinery of archaea can be roughly classified as a simplified version of eukaryotic organisms. The basal transcription factor machinery binds to the TATA box found around 28 nucleotides upstream of the transcription start site; however, some transcription units lack a clear TATA box and still have TBP/TFB binding over them. This apparent absence of conserved sequences could be a consequence of sequence divergence associated with the upstream region, operon, and gene organization. Furthermore, earlier studies have found that a structural analysis gains more information compared with a simple sequence inspection. In this work, we evaluated and coded 3630 archaeal promoter sequences of three organisms, Haloferax volcanii, Thermococcus kodakarensis, and Sulfolobus solfataricus into DNA duplex stability, enthalpy, curvature, and bendability parameters. We also split our dataset into conserved TATA and degenerated TATA promoters to identify differences among these two classes of promoters. The structural analysis reveals variations in archaeal promoter architecture, that is, a distinctive signal is observed in the TFB, TBP, and TFE binding sites independently of these being TATA-conserved or TATA-degenerated. In addition, the promoter encountering method was validated with upstream regions of 13 other archaea, suggesting that there might be promoter sequences among them. Therefore, we suggest a novel method for locating promoters within the genome of archaea based on DNA energetic/structural features.

Symphony of the DNA flexibility and sequence environment orchestrates p53 binding to its responsive elements

The p53 tumor suppressor protein maintains the genome fidelity and integrity by modulating several cellular activities. It regulates these events by interacting with a heterogeneous set of response elements (REs) of regulatory genes in the background of chromatin configuration. At the p53-RE interface, both the base readout and torsional-flexibility of DNA account for high-affinity binding. However, DNA structure is an entanglement of a multitude of physicochemical features, both local and global structure should be considered for dealing with DNA-protein interactions. The goal of current research work is to conceptualize and abstract basic principles of p53-RE binding affinity as a function of structural alterations in DNA such as bending, twisting, and stretching flexibility and shape. For this purpose, we have exploited high throughput in-vitro relative affinity information of responsive elements and genome binding events of p53 from HT-Selex and ChIP-Seq experiments respectively. Our results confirm the role of torsional flexibility in p53 binding, and further, we reveal that DNA axial bending, stretching stiffness, propeller twist, and wedge angles are intimately linked to p53 binding affinity when compared to homeodomain, bZIP, and bHLH proteins. Besides, a similar DNA structural environment is observed in the distal sequences encompassing the actual binding sites of p53 cistrome genes. Additionally, we revealed that p53 cistrome target genes have unique promoter architecture, and the DNA flexibility of genomic sequences around REs in cancer and normal cell types display major differences. Altogether, our work provides a keynote on DNA structural features of REs that shape up the in-vitro and in-vivo high-affinity binding of the p53 transcription factor.

DNA structural and physical properties reveal peculiarities in promoter sequences of the bacterium Escherichia coli K-12

The gene transcription of bacteria starts with a promoter sequence being recognized by a transcription factor found in the RNAP enzyme, this process is assisted through the conservation of nucleotides as well as other factors governing these intergenic regions. Faced with this, the coding of genetic information into physical aspects of the DNA such as enthalpy, stability, and base-pair stacking could suggest promoter activity as well as protrude differentiation of promoter and non-promoter data. In this work, a total of 3131 promoter sequences associated to six different sigma factors in the bacterium E. coli were converted into numeric attributes, a strong set of control sequences referring to a shuffled version of the original sequences as well as coding regions is provided. Then, the parameterized genetic information was normalized, exhaustively analyzed through statistical tests. The results suggest that strong signals in the promoter sequences match the binding site of transcription factor proteins, indicating that promoter activity is well represented by its conversion into physical attributes. Moreover, the features tested in this report conveyed significant variances between promoter and control data, enabling these features to be employed in bacterial promoter classification. The results produced here may aid in bacterial promoter recognition by providing a robust set of biological inferences.

Learning the Regulatory Code of Gene Expression

Data-driven machine learning is the method of choice for predicting molecular phenotypes from nucleotide sequence, modeling gene expression events including protein-DNA binding, chromatin states as well as mRNA and protein levels. Deep neural networks automatically learn informative sequence representations and interpreting them enables us to improve our understanding of the regulatory code governing gene expression. Here, we review the latest developments that apply shallow or deep learning to quantify molecular phenotypes and decode the cis-regulatory grammar from prokaryotic and eukaryotic sequencing data. Our approach is to build from the ground up, first focusing on the initiating protein-DNA interactions, then specific coding and non-coding regions, and finally on advances that combine multiple parts of the gene and mRNA regulatory structures, achieving unprecedented performance. We thus provide a quantitative view of gene expression regulation from nucleotide sequence, concluding with an information-centric overview of the central dogma of molecular biology.

Long Noncoding RNA OIP5-AS1 Promotes Cell Apoptosis and Cataract Formation by Blocking POLG Expression Under Oxidative Stress

Purpose

Cataract, a clouding of the intraocular lens, is the leading cause of blindness. The lens-expressed long noncoding RNA OIP5-AS1 was upregulated in lens epithelial cells from patients with cataracts, suggesting its pathogenic role in cataracts. We investigated the regulatory role of OIP5-AS1 in the development of cataracts as well as potential RNA binding proteins, downstream target genes, and upstream transcription factors.

Methods

Clinical capsules and ex vivo and in vitro cataract models were used to test OIP5-AS1 expression. Cell apoptosis was detected using Western blots, JC-1 staining, and flow cytometry. Ribonucleoprotein immunoprecipitation-qPCR was performed to confirm the interaction of OIP5-AS1 and POLG. Chromatin immunoprecipitation-qPCR was used to determine the binding of TFAP2A and the OIP5-AS1 promoter region.

Results

OIP5-AS1 was upregulated in cataract lenses and B3 cells under oxidative stress. OIP5-AS1 knockdown protected B3 cells from H₂O₂-induced apoptosis and alleviated lens opacity in the ex vivo cataract model. HuR functioned as a scaffold carrying OIP5-AS1 and POLG mRNA and mediated the decay of POLG mRNA. POLG was downregulated in the cataract lens and oxidative-stressed B3 cells, and POLG depletion decreased the mtDNA copy number and MMP, increased reactive oxygen species production, and sensitized B3 cells to oxidative stress-induced apoptosis. POLG overexpression reversed these effects. TFAP2A bound the OIP5-AS1 promoter and contributed to OIP5-AS1 expression.

Conclusions

We demonstrated that OIP5-AS1, activated by TFAP2A, contributed to cataract formation by inhibiting POLG expression mediated by HuR, thus leading to increased apoptosis of lens epithelial cells and aggravated lens opacity, suggesting that OIP5-AS1 is a potential target for cataract treatment.

Evolution of Diverse Strategies for Promoter Regulation

DNA is fundamentally important for all cellular organisms due to its role as a store of hereditary genetic information. The precise and accurate regulation of gene transcription depends primarily on promoters, which vary significantly within and between genomes. Some promoters are rich in specific types of bases, while others have more varied, complex sequence characteristics. However, it is not only base sequence but also epigenetic modifications and altered DNA structure that regulate promoter activity. Significantly, many promoters across all organisms contain sequences that can form intrastrand hairpins (cruciforms) or four-stranded structures (G-quadruplex or i-motif). In this review we integrate recent studies on promoter regulation that highlight the importance of DNA structure in the evolutionary adaptation of promoter sequences.

Intron exon boundary junctions in human genome have in-built unique structural and energetic signals

Precise identification of correct exon–intron boundaries is a prerequisite to analyze the location and structure of genes. The existing framework for genomic signals, delineating exon and introns in a genomic segment, seems insufficient, predominantly due to poor sequence consensus as well as limitations of training on available experimental data sets. We present here a novel concept for characterizing exon–intron boundaries in genomic segments on the basis of structural and energetic properties. We analyzed boundary junctions on both sides of all the exons (3 28 368) of protein coding genes from human genome (GENCODE database) using 28 structural and three energy parameters. Study of sequence conservation at these sites shows very poor consensus. It is observed that DNA adopts a unique structural and energy state at the boundary junctions. Also, signals are somewhat different for housekeeping and tissue specific genes. Clustering of 31 parameters into four derived vectors gives some additional insights into the physical mechanisms involved in this biological process. Sites of structural and energy signals correlate well to the positions playing important roles in pre-mRNA splicing.

Intrinsic DNA topology as a prioritization metric in genomic fine-mapping studies

In genomic fine-mapping studies, some approaches leverage annotation data to prioritize likely functional polymorphisms. However, existing annotation resources can present challenges as many lack information for novel variants and/or may be uninformative for non-coding regions. We propose a novel annotation source, sequence-dependent DNA topology, as a prioritization metric for fine-mapping. DNA topology and function are well-intertwined, and as an intrinsic DNA property, it is readily applicable to any genomic region. Here, we constructed and applied Minor Groove Width (MGW) as a prioritization metric. Using an established MGW-prediction method, we generated a MGW census for 199 038 197 SNPs across the human genome. Summarizing a SNP's change in MGW (ΔMGW) as a Euclidean distance, ΔMGW exhibited a strongly right-skewed distribution, highlighting the infrequency of SNPs that generate dissimilar shape profiles. We hypothesized that phenotypically-associated SNPs can be prioritized by ΔMGW. We tested this hypothesis in 116 regions analyzed by a Massively Parallel Reporter Assay and observed enrichment of large ΔMGW for functional polymorphisms (P = 0.0007). To illustrate application in fine-mapping studies, we applied our MGW-prioritization approach to three non-coding regions associated with systemic lupus erythematosus. Together, this study presents the first usage of sequence-dependent DNA topology as a prioritization metric in genomic association studies.

Multiple plasmid origin-of-transfer regions might aid the spread of antimicrobial resistance to human pathogens

Antimicrobial resistance poses a great danger to humanity, in part due to the widespread horizontal gene transfer of plasmids via conjugation. Modeling of plasmid transfer is essential to uncovering the fundamentals of resistance transfer and for the development of predictive measures to limit the spread of resistance. However, a major limitation in the current understanding of plasmids is the incomplete characterization of the conjugative DNA transfer mechanisms, which conceals the actual potential for plasmid transfer in nature. Here, we consider that the plasmid-borne origin-of-transfer substrates encode specific DNA structural properties that can facilitate finding these regions in large datasets and develop a DNA structure-based alignment procedure for typing the transfer substrates that outperforms sequence-based approaches. Thousands of putative DNA transfer substrates are identified, showing that plasmid mobility can be twofold higher and span almost twofold more host species than is currently known. Over half of all putative mobile plasmids contain the means for mobilization by conjugation systems belonging to different mobility groups, which can hypothetically link previously confined host ranges across ecological habitats into a robust plasmid transfer network. This hypothetical network is found to facilitate the transfer of antimicrobial resistance from environmental genetic reservoirs to human pathogens, which might be an important driver of the observed rapid resistance development in humans and thus an important point of focus for future prevention measures.

iPromoter-BnCNN: a novel branched CNN-based predictor for identifying and classifying sigma promoters

Motivation

Promoter is a short region of DNA which is responsible for initiating transcription of specific genes. Development of computational tools for automatic identification of promoters is in high demand. According to the difference of functions, promoters can be of different types. Promoters may have both intra- and interclass variation and similarity in terms of consensus sequences. Accurate classification of various types of sigma promoters still remains a challenge.

Results

We present iPromoter-BnCNN for identification and accurate classification of six types of promoters—σ24,σ28,σ32,σ38,σ54,σ70. It is a CNN-based classifier which combines local features related to monomer nucleotide sequence, trimer nucleotide sequence, dimer structural properties and trimer structural properties through the use of parallel branching. We conducted experiments on a benchmark dataset and compared with six state-of-the-art tools to show our supremacy on 5-fold cross-validation. Moreover, we tested our classifier on an independent test dataset.

Availability and implementation

Our proposed tool iPromoter-BnCNN web server is freely available at http://103.109.52.8/iPromoter-BnCNN. The runnable source code can be found https://colab.research.google.com/drive/1yWWh7BXhsm8U4PODgPqlQRy23QGjF2DZ.

Supplementary information

Supplementary data are available at Bioinformatics online.

Delving into Eukaryotic Origins of Replication Using DNA Structural Features

DNA replication in eukaryotes is an intricate process, which is precisely synchronized by a set of regulatory proteins, and the replication fork emanates from discrete sites on chromatin called origins of replication (Oris). These spots are considered as the gateway to chromosomal replication and are stereotyped by sequence motifs. The cognate sequences are noticeable in a small group of entire origin regions or totally absent across different metazoans. Alternatively, the use of DNA secondary structural features can provide additional information compared to the primary sequence. In this article, we report the trends in DNA sequence-based structural properties of origin sequences in nine eukaryotic systems representing different families of life. Biologically relevant DNA secondary structural properties, namely, stability, propeller twist, flexibility, and minor groove shape were studied in the sequences flanking replication start sites. Results indicate that Oris in yeasts show lower stability, more rigidity, and narrow minor groove preferences compared to genomic sequences surrounding them. Yeast Oris also show preference for A-tracts and the promoter element TATA box in the vicinity of replication start sites. On the contrary, Drosophila melanogaster, humans, and Arabidopsis thaliana do not have such features in their Oris, and instead, they show high preponderance of G-rich sequence motifs such as putative G-quadruplexes or i-motifs and CpG islands. Our extensive study applies the DNA structural feature computation to delve into origins of replication across organisms ranging from yeasts to mammals and including a plant. Insights from this study would be significant in understanding origin architecture and help in designing new algorithms for predicting DNA trans-acting factor recognition events.

Local features determine Ty3 targeting frequency at RNA polymerase III transcription start sites

Retroelement integration into host genomes affects chromosome structure and function. A goal of a considerable number of investigations is to elucidate features influencing insertion site selection. The Saccharomyces cerevisiae Ty3 retrotransposon inserts proximal to the transcription start sites (TSS) of genes transcribed by RNA polymerase III (RNAP3). In this study, differential patterns of insertion were profiled genome-wide using a random barcode-tagged Ty3. Saturation transposition showed that tRNA genes (tDNAs) are targeted at widely different frequencies even within isoacceptor families. Ectopic expression of Ty3 integrase (IN) showed that it localized to targets independent of other Ty3 proteins and cDNA. IN, RNAP3, and transcription factor Brf1 were enriched at tDNA targets with high frequencies of transposition. To examine potential effects of cis-acting DNA features on transposition, targeting was tested on high-copy plasmids with restricted amounts of 5′ flanking sequence plus tDNA. Relative activity of targets was reconstituted in these constructions. Weighting of genomic insertions according to frequency identified an A/T-rich sequence followed by C as the dominant site of strand transfer. This site lies immediately adjacent to the adenines previously implicated in the RNAP3 TSS motif (CAA). In silico DNA structural analysis upstream of this motif showed that targets with elevated DNA curvature coincide with reduced integration. We propose that integration mediated by the Ty3 intasome complex (IN and cDNA) is subject to inputs from a combination of host factor occupancy and insertion site architecture, and that this results in the wide range of Ty3 targeting frequencies.

Crustacean hyperglycemic hormone of Portunus trituberculatus: evidence of alternative splicing and potential roles in osmoregulation

The crustacean hyperglycemic hormone (CHH) gene of Portunus trituberculatus (Pt-CHH) consists of four exons and three introns spanning 3849 bp in size and generating two mature mRNA, Pt-CHH1, and Pt-CHH2. The primary gene transcript produces a cDNA encoding for the putative Pt-CHH2 from exons 1, 2, 3, and 4 and an alternative transcript encodes for a putative Pt-CHH1 peptide from exons 1, 2, and 4. A promoter fragment of about 3 kb was obtained by genomic walking. The tissue-specific expression pattern is examined by reverse transcriptase chain reaction, and the results show that Pt-CHH1 is detected in the eyestalk, brain, muscle, and blood. However, Pt-CHH2 is detected in the ganglia thoracalis and gill. The results indicate that the expression of Pt-CHH2 in the gill might suggest a potential role in osmoregulation. The Pt-CHH transcript level in the gill increases when the crab is exposed to low salinity. The injection of dsRNA for Pt-CHH causes a significant reduction in Pt-CHH2 transcript level and the activity of Na+/K+-ATPase, and carbonic anhydrase (CA) show a serious decrease. In conclusion, this study provides molecular evidence to support the osmoregulatory function of Pt-CHH2.

Variation of gene expression in plants is influenced by gene architecture and structural properties of promoters

In higher eukaryotes, gene architecture and structural properties of promoters have emerged as significant factors influencing variation in number of transcripts (expression level) and specificity of gene expression in a tissue (expression breadth), which eventually shape the phenotype. In this study, transcriptome data of different tissue types at various developmental stages of A. thaliana, O. sativa, S. bicolor and Z. mays have been used to understand the relationship between properties of gene components and its expression. Our findings indicate that in plants, among all gene architecture and structural properties of promoters, compactness of genes in terms of intron content is significantly linked to gene expression level and breadth, whereas in human an exactly opposite scenario is seen. In plants, for the first time we have carried out a quantitative estimation of effect of a particular trait on expression level and breadth, by using multiple regression analysis and it confirms that intron content of primary transcript (as %) is a powerful determinant of expression breadth. Similarly, further regression analysis revealed that among structural properties of the promoters, stability is negatively linked to expression breadth, while DNase1 sensitivity strongly governs gene expression breadth in monocots and gene expression level in dicots. In addition, promoter regions of tissue specific genes are found to be enriched with TATA box and Y-patch motifs. Finally, multi copy orthologous genes in plants are found to be longer, highly regulated and tissue specific.

Flexibility and structure of flanking DNA impact transcription factor affinity for its core motif

Spatial and temporal expression of genes is essential for maintaining phenotype integrity. Transcription factors (TFs) modulate expression patterns by binding to specific DNA sequences in the genome. Along with the core binding motif, the flanking sequence context can play a role in DNA-TF recognition. Here, we employ high-throughput in vitro and in silico analyses to understand the influence of sequences flanking the cognate sites in binding of three most prevalent eukaryotic TF families (zinc finger, homeodomain and bZIP). In vitro binding preferences of each TF toward the entire DNA sequence space were correlated with a wide range of DNA structural parameters, including DNA flexibility. Results demonstrate that conformational plasticity of flanking regions modulates binding affinity of certain TF families. DNA duplex stability and minor groove width also play an important role in DNA-TF recognition but differ in how exactly they influence the binding in each specific case. Our analyses further reveal that the structural features of preferred flanking sequences are not universal, as similar DNA-binding folds can employ distinct DNA recognition modes.

HMGB1 binds to the KRAS promoter G-quadruplex: a new player in oncogene transcriptional regulation?

This communication reports on a possible distinct role of HMGB1 protein. Biophysical studies revealed that HMGB1 binds and stabilizes the G-quadruplex of the KRAS promoter element that is responsible for most of the transcriptional activity. Biological data showed that inhibition of HMGB1 increases KRAS expression. These results suggest that HMGB1 could play a role in the gene transcriptional regulation via the functional recognition of the G-quadruplex.

Dynamics of physiologically relevant noncanonical DNA structures: an overview from experimental and theoretical studies

DNA is a complex molecule with phenomenal inherent plasticity and the ability to form different hydrogen bonding patterns of varying stabilities. These properties enable DNA to attain a variety of structural and conformational polymorphic forms. Structurally, DNA can exist in single-stranded form or as higher-order structures, which include the canonical double helix as well as the noncanonical duplex, triplex and quadruplex species. Each of these structural forms in turn encompasses an ensemble of dynamically heterogeneous conformers depending on the sequence composition and environmental context. In vivo, the widely populated canonical B-DNA attains these noncanonical polymorphs during important cellular processes. While several investigations have focused on the structure of these noncanonical DNA, studying their dynamics has remained nontrivial. Here, we outline findings from some recent advanced experimental and molecular simulation techniques that have significantly contributed toward understanding the complex dynamics of physiologically relevant noncanonical forms of DNA.

Human Enhancers Harboring Specific Sequence Composition, Activity, and Genome Organization Are Linked to the Immune Response

The FANTOM5 consortium recently characterized 65,423 human enhancers from 1829 cell and tissue samples using the Cap Analysis of Gene Expression technology. We showed that the guanine and cytosine content at enhancer regions distinguishes two classes of enhancers harboring distinct DNA structural properties at flanking regions. A functional analysis of their predicted gene targets highlighted one class of enhancers as significantly enriched for associations with immune response genes. Moreover, these enhancers were specifically enriched for regulatory motifs recognized by transcription factors involved in immune response. We observed that enhancers enriched for links to immune response genes were more cell-type specific, preferentially activated upon bacterial infection, and with specific response activity. Looking at chromatin capture data, we found that the two classes of enhancers were lying in distinct topologically associating domains and chromatin loops. Our results suggest that specific nucleotide compositions encode for classes of enhancers that are functionally distinct and specifically organized in the human genome.

Alternative DNA secondary structure formation affects RNA polymerase II promoter-proximal pausing in human

BACKGROUND

Alternative DNA secondary structures can arise from single-stranded DNA when duplex DNA is unwound during DNA processes such as transcription, resulting in the regulation or perturbation of these processes. We identify sites of high propensity to form stable DNA secondary structure across the human genome using Mfold and ViennaRNA programs with parameters for analyzing DNA.

RESULTS

The promoter-proximal regions of genes with paused transcription are significantly and energetically more favorable to form DNA secondary structure than non-paused genes or genes without RNA polymerase II (Pol II) binding. Using Pol II ChIP-seq, GRO-seq, NET-seq, and mNET-seq data, we arrive at a robust set of criteria for Pol II pausing, independent of annotation, and find that a highly stable secondary structure is likely to form about 10-50 nucleotides upstream of a Pol II pausing site. Structure probing data confirm the existence of DNA secondary structures enriched at the promoter-proximal regions of paused genes in human cells. Using an in vitro transcription assay, we demonstrate that Pol II pausing at HSPA1B, a human heat shock gene, is affected by manipulating DNA secondary structure upstream of the pausing site.

CONCLUSIONS

Our results indicate alternative DNA secondary structure formation as a mechanism for how GC-rich sequences regulate RNA Pol II promoter-proximal pausing genome-wide.

Heat shock cognate 70 gene in Haliotis diversicolor: responses to pathogen infection and environmental stresses and its transcriptional regulation analysis

Heat shock cognate 70 (HSC70) is a class of highly conserved proteins which functions as a molecular chaperon, participates in tolerance processes, and is involved in protein folding, degradation, targeting, translocation, and protein complex remodeling. In this study, the mRNA expression level of the Haliotis diversicolor HSC70 (HdHSC70) gene was detected by quantitative real-time PCR in different tissues and under different stresses. The results showed that the HdHSC70 gene was ubiquitously expressed in seven selected tissues. The highest expression level was detected in gills (P < 0.05). The expression level of the HdHSC70 gene was significantly upregulated by thermal stress, hypoxia stress, Vibrio parahaemolyticus infection, and combined thermal and hypoxia stress. The upregulation occurred at the early stage of stress. These results indicated that the HdHSC70 is an important component in the immune system of H. diversicolor and is involved in the early stress response. Meanwhile, 5'-flanking region sequence (2013 bp) of the HdHSC70 gene was cloned; it contains a putative core promoter region, heat shock element, CpG, and transcription elements including NF-1, Sp1, Oct-1, interferon consensus sequence binding protein (ICSBP), etc. In HEK 293T cells, the 5'-flanking region sequence is able to drive expression of the enhanced green fluorescent protein (EGFP), proving its promoter function. The promoter activity increased after high-temperature treatment, which may be the immediate reason why the expression of the HdHSC70 gene was significantly upregulated by thermal stress. After the ICSBP-binding site was mutated, we found the luciferase activity significantly reduced, which suggested that the ICSBP-binding site has a certain enhancement effect on the activity of the HdHSC70 promoter.