Pair DNA Sequence Research Articles

Crispr-SGRU: Prediction of CRISPR/Cas9 Off-Target Activities with Mismatches and Indels Using Stacked BiGRU

CRISPR/Cas9 is a popular genome editing technology, yet its clinical application is hindered by off-target effects. Many deep learning-based methods are available for off-target prediction. However, few can predict off-target activities with insertions or deletions (indels) between single guide RNA and DNA sequence pairs. Additionally, the analysis of off-target data is challenged due to a data imbalance issue. Moreover, the prediction accuracy and interpretability remain to be improved. Here, we introduce a deep learning-based framework, named Crispr-SGRU, to predict off-target activities with mismatches and indels. This model is based on Inception and stacked BiGRU. It adopts a dice loss function to solve the inherent imbalance issue. Experimental results show our model outperforms existing methods for off-target prediction in terms of accuracy and robustness. Finally, we study the interpretability of this model through Deep SHAP and teacher–student-based knowledge distillation, and find it can provide meaningful explanations for sequence patterns regarding off-target activity.

Fluorescence assay for aflatoxin B1 based on aptamer-binding triggered DNAzyme activity.

As a kind of mycotoxin, aflatoxin B1 (AFB1), which is often found in agricultural products, poses a threat to human health. Developing asimple sensitive method for AFB1 detection is in great demand. Here, we reported an aptamer-based fluorescence assay for AFB1 detection by using DNAzyme to generate and amplify asignal. We redesigned a pair of DNA sequences, which originated from the anti-AFB1 aptamer and RNA-cleaving DNAzyme 10-23. In the absence of AFB1, the aptamer hybridized with the region of thesubstrate-binding arm of the DNAzyme, inhibiting the activity of theDNAzyme. In the presence of AFB1, the binding of AFB1 to theaptamer led to the displacement of theDNAzyme from theaptamer. The substrate-binding arm was unblocked, and the activity of theDNAzyme was restored for the hydrolysis of thefluorophore and quencher-labeled substrate, causing asignificant fluorescence increase. This assay could detect AFB1 in the dynamic range from 0.98 to 2000nmol/L with high selectivity, and the detection limit was 0.98nmol/L. Moreover, the assay was able to detect AFB1 in acomplex sample matrix. This work provides a useful tool for the analysis of AFB1.

ANALYSIS OF THE CRYPTOSPORIDIUM SPP GP60 GENE VARIABILITY APPLYING INFORMATION THEORY

In this paper we used statistical methods to understand the genetic information of DNA considered as a statistical system. The alphabet of a DNA sequence is defined by the four nucleotides: adenine, cytosine, guanine, and thymine. The order of nucleotides along the DNA sequences encodes the genetic information. We have analyzed three Cryptosporidium DNA sequences: one DNA sequence isolated and analyzed in our laboratory and two DNA reference sequences from the public database GenBank. Each DNA sequence is considered as a statistical system and is represented by a random variable and an associate probability distribution. The Shannon entropy, Renyi entropy, Onicescu informational energy and square deviation from uniform distribution are used in order to measure the degree of randomness for the three statistical systems. The similarity and difference between the three DNA sequences of the two Cryptosporidium species (Cryptosporidium hominis and Cryptosporidium parvum) were assessed by calculating the statistical distance between the probability distributions associated with each pair of DNA sequences. Each of the three DNA sequences pairs with one of the other two sequences and forms three pairs of sequences. Using the associated probability distributions, the statistical distance between them can be calculated. Bhattacharyya distance measures similarity degree between the two probability distributions. The Kullback-Leiber and the resistor-average distances measure the difference between the two distributions.

Binding modes of a flexible ruthenium polypyridyl complex to DNA.

Ruthenium(II) polypyridyl complexes are attractive binders to DNA. Modifying the hydrophobicity, shape, or size of the ancillary ligands around the central ruthenium atom can induce changes in the binding mode to the DNA double helix. In this paper, we investigate the binding modes of [Ru(2,2'-bipyridine)2 (5-{4-[(pyren-1-yl)methyl]-1H-1,2,3-triazol-4-yl}-1,10-phenanthroline)]2+ (RuPy for short), a metal complex featuring a flexible pyrene moiety known for its intercalative properties. Classical molecular dynamics simulations are employed to gain insight into the non-covalent binding interactions of RuPy with two different 20 base pair DNA sequences, poly(dA)poly(dT) (AT) and poly(dC)poly(dG) (CG). In addition to examining the intercalation of the pyrene moiety from the major groove, the stability of RuPy-DNA adducts is investigated when the metal complex interacts externally with the DNA and with the major and minor groove pockets. The results indicate that external interaction and major groove binding are not stable, whereas intercalation consistently forms stable adducts. Minor groove binding showed less stability than intercalation and more variability, with some trajectories transitioning to intercalation, involving either the pyrene moiety or a bipyridine ligand. Pyrene intercalation, especially from the minor groove, was the most stable, while bipyridine intercalation was less favorable and associated with higher binding free energies.

Prediction of CRISPR-Cas9 off-target activities with mismatches and indels based on hybrid neural network

The CRISPR/Cas9 system has significantly advanced the field of gene editing, yet its clinical application is constrained by the considerable challenge of off-target effects. Although numerous deep learning models for off-target prediction have been proposed, most struggle to effectively extract the nuanced features of guide RNA (gRNA) and DNA sequence pairs and to mitigate information loss during data transmission within the model. To address these limitations, we introduce a novel Hybrid Neural Network (HNN) model that employs a parallelized network structure to fully extract pertinent features from different positions and types of bases in the sequence to minimize information loss. Notably, this study marks the first application of word embedding techniques to extract information from sequence pairs that contain insertions and deletions (Indels). Comprehensive evaluation across diverse datasets indicates that our proposed model outperforms existing state-of-the-art prediction methods in off-target prediction. The datasets and source codes supporting this study can be found at https://github.com/Yang-k955/CRISPR-HW.

Labeling approaches for DNA-PAINT super-resolution imaging.

Super-resolution imaging is becoming a commonly employed tool to visualize biological targets in unprecedented detail. DNA-PAINT is one of the single-molecule localization microscopy-based super-resolution imaging modalities allowing the ultra-high-resolution imaging with superior multiplexing capabilities. We discuss the importance of patterned DNA nanostructures in demonstrating the capabilities of DNA-PAINT and the design of various combinations of imager-docking strand pairs for imaging. Central to the implementation of DNA-PAINT imaging in a biological context is the generation of docking strand-conjugated binders against the target molecules. Several researchers have developed a variety of labelling probes for improving resolution while also providing multiplexing capabilities for the broader application of DNA-PAINT. This review provides a comprehensive summary of the repertoire of labelling probes used for DNA-PAINT in cells and the strategies implemented to chemically modify them with a docking strand.

Deciphering the mechanism of p73 recognition of p53 response elements using the crystal structure of p73-DNA complexes and computational studies

p73 belongs to p53 family transcription factor activating more than 50% of cell fate p53 target genes involved in cell cycle, apoptosis, DNA damage response alongside neuronal system development and differentiation by binding to 20-bp response elements (REs) having sequence motif (PPPC-A/T-T/A-GYYY) where P-purines and Y-pyrimidines with each 10-bp separated by minimum 0 to 13-bp spacer. The promiscuous nature of recognizing both cell fate and development genes and the underlying RE selectivity mechanism by p73 is not well understood. Here, we report the molecular details of p73 recognizing the REs using the crystal structure of p73 DNA binding domain (DBD) in complex with 12 base pair DNA sequence 5'-cAGGCATGCCTg-3′ and molecular dynamics simulations with six different p53 natural promoter sequences. Each 20-base pair natural promoter forms a different major/minor groove due to the presence of nucleotides A/T, A/C, G/G, T/T and G/T at positions 3, 8, 13, 18 uniquely recognized by p73 key residues Lys138 and Arg268. The loops L1 and L3 bearing these residues influence inter-and intra-dimer interfaces interactions and hence p73 forms a unique tetramer with each natural promoter sequence. Structural features of the DNA and the spacing between half-sites influence p73 tetramerization and its transactivation function.

Inference of gene flow in the process of speciation: Efficient maximum-likelihood implementation of a generalised isolation-with-migration model

The ‘isolation with migration’ (IM) model has been extensively used in the literature to detect gene flow during the process of speciation. In this model, an ancestral population split into two or more descendant populations which subsequently exchanged migrants at a constant rate until the present. Of course, the assumption of constant gene flow until the present is often over-simplistic in the context of speciation. In this paper, we consider a ‘generalised IM’ (GIM) model: a two-population IM model in which migration rates and population sizes are allowed to change at some point in the past. By developing a maximum-likelihood implementation of this model, we enable inference on both historical and contemporary rates of gene flow between two closely related populations or species. The GIM model encompasses both the standard two-population IM model and the ‘isolation with initial migration’ (IIM) model as special cases, as well as a model of secondary contact. We examine for simulated data how our method can be used, by means of likelihood ratio tests or AIC scores, to distinguish between the following scenarios of population divergence: (a) divergence in complete isolation; (b) divergence with a period of gene flow followed by isolation; (c) divergence with a period of isolation followed by secondary contact; (d) divergence with ongoing gene flow. Our method is based on the coalescent and is suitable for data sets consisting of the number of nucleotide differences between one pair of DNA sequences at each of a large number of independent loci. As our method relies on an explicit expression for the likelihood, it is computationally very fast.

Identity: rapid alignment-free prediction of sequence alignment identity scores using self-supervised general linear models.

Pairwise global alignment is a fundamental step in sequence analysis. Optimal alignment algorithms are quadratic—slow especially on long sequences. In many applications that involve large sequence datasets, all what is needed is calculating the identity scores (percentage of identical nucleotides in an optimal alignment—including gaps—of two sequences); there is no need for visualizing how every two sequences are aligned. For these applications, we propose Identity, which produces global identity scores for a large number of pairs of DNA sequences using alignment-free methods and self-supervised general linear models. For the first time, the new tool can predict pairwise identity scores in linear time and space. On two large-scale sequence databases, Identity provided the best compromise between sensitivity and precision while being faster than BLAST, Mash, MUMmer4 and USEARCH by 2–80 times. Identity was the best performing tool when searching for low-identity matches. While constructing phylogenetic trees from about 6000 transcripts, the tree due to the scores reported by Identity was the closest to the reference tree (in contrast to andi, FSWM and Mash). Identity is capable of producing pairwise identity scores of millions-of-nucleotides-long bacterial genomes; this task cannot be accomplished by any global-alignment-based tool. Availability: https://github.com/BioinformaticsToolsmith/Identity.

Small Sequence-Sensitive Compounds for Specific Recognition of the G⋅C Base Pair in DNA Minor Groove.

A series of small diamidines with thiophene and modified N-alkylbenzimidazole σ-hole module represent specific binding to single G⋅C base pair (bp) DNA sequence. The variation of N-alkyl or aromatic rings were sensitive to microstructures of the DNA minor groove. Thirteen new compounds were synthesized to test their binding affinity and selectivity. The dicyanobenzimidazoles needed to synthesize the target diamidines were made via condensation/cyclization reactions of different aldehydes with different 3-amino-4-(alkyl- or phenyl-amino) benzonitriles. The final diamidines were synthesized using lithium bis-trimethylsilylamide (LiN[Si(CH3 )3 ]2 ) or Pinner methods. The newly synthesized compounds showed strong binding and selectivity to AAAGTTT compared to similar sequences AAATTT and AAAGCTTT investigated by several biophysical methods including biosensor-SPR, fluorescence spectroscopy, DNA thermal melting, ESI-MS spectrometry, circular dichroism, and molecular dynamics. The binding affinity results determined by fluorescence spectroscopy are in accordance with those obtained by biosensor-SPR. These small size single G⋅C bp highly specific binders extend the compound database for future biological applications.

Identification of SNP markers correlated with the tolerance of low-salinity challenge in swimming crab (Portunus trituberculatus)

Water salinity condition is an important factor for artificial propagation of the swimming crab (Portunus trituberculatus). Low salinity (LS)-resistant strains are preferred by crab industries. Single nucleotide polymorphism (SNP), the third generation of molecular markers, can be utilized in the breeding of LS-resistant species of P. trituberculatus. Our earlier study identified 615 genes differentially expressed in low-salinity stress compared to the controls. Although thousands of SNP loci have been found, it is hard to identify a SNP marker in correlation with a desired trait. In this study, time-of-flight mass spectrometry (TOF-MS), as an efficient method to select SNPs for the tolerance of LS challenge, was utilized for SNP typing. Fifty gene segments were amplified based on comparative transcriptomics in our earlier study, a total of 18 511 bp DNA fragments were amplified, and eighty-five SNP markers were found. The frequency of the SNPs was estimated to be 0.46 per 100 base pairs of DNA sequences. The rate of the conversion mutation was 81%, while the transversion mutation was 19%. The mutation rate of the G/T (C/A), A/T and G/C was 26%, 12% and 7%, respectively. Eight SNP markers were found to significantly correlate with the adaption of low salinity. Of the eight SNP markers, three linked-SNPs were found in the cuticle proportion gene, and another three SNPs were found in three new genes, and the rest two were found in aquaporin gene and chloride channel gene. The development of these SNP markers found in our study could be primarily used for breeding LS-resistant strains of P. trituberculatus.

Chiral DNA sequences as commutable controls for clinical genomics

Chirality is a property describing any object that is inequivalent to its mirror image. Due to its 5′–3′ directionality, a DNA sequence is distinct from a mirrored sequence arranged in reverse nucleotide-order, and is therefore chiral. A given sequence and its opposing chiral partner sequence share many properties, such as nucleotide composition and sequence entropy. Here we demonstrate that chiral DNA sequence pairs also perform equivalently during molecular and bioinformatic techniques that underpin genetic analysis, including PCR amplification, hybridization, whole-genome, target-enriched and nanopore sequencing, sequence alignment and variant detection. Given these shared properties, synthetic DNA sequences mirroring clinically relevant or analytically challenging regions of the human genome are ideal controls for clinical genomics. The addition of synthetic chiral sequences (sequins) to patient tumor samples can prevent false-positive and false-negative mutation detection to improve diagnosis. Accordingly, we propose that sequins can fulfill the need for commutable internal controls in precision medicine.

Optimal Pair DNA Sequence Alignment based on Matching Regions and Multi-Zone Genetic Algorithm

DNA sequence alignment is an important and challenging task in Bioinformatics, which is used for finding the optimal arrangement between two sequences. In this paper, two methods are proposed in two stages to solve the pairwise sequence alignment problem. The first method is Matching Regions(MR) concerns on splitting the DNA into regions with adaptive interleaving windows to isolate the DNA tape into matched and non-matched regions. Additionally, a Multi-Zone Genetic Algorithm (MZGA) is proposed as an improved method in the second stage. It consists of segmenting a large non-matched region into smaller search space. Then, the MZGA is implemented in parallel to save time. Genetic Algorithm can be applied as an optimization toolto produce multiple solutions. Furthermore, the improvement focuses on the enhancement of Simple GA operators. In the selection, the population is divided into three Zones according to the fitness score. A new crossover approach is proposed depending on cut-points and location of gaps. The proposed method guarantees that the value of fitness tends to improvement or convergence in each successive generation. Thus, the offspring of populations will have better fitness value. The system has been applied to the real-world dataset of DNA with variable lengths which are ranged from 66 bases up to 26037 bases. As a result, the proposed technique satisfied the best alignment score of the DNA sequences. Finally, it is worth mentioning that the proposed system proved to be generalizable.

Bound Compound, Interfacial Water, and Phenyl Ring Rotation Dynamics of a Compound in the DNA Minor Groove.

DB2277, a heterocyclic diamidine, is a successful design for mixed base pair (bp) DNA sequence recognition. The compound has a central aza-benzimidazole group that forms two H-bonds with a GC bp that has flanking AT bps. The nuclear magnetic resonance structure of the DB2277-DNA complex with an AAGATA recognition site sequence was determined, and here we report extended molecular dynamics (MD) simulations of the structure. DB2277 has two terminal phenyl-amidine groups, one of which is directly linked to the DB2277 heterocyclic core and the other through a flexible -OCH2- group. The flexibly linked phenyl is too far from the minor groove floor to make direct H-bonds but is linked to an AT bp through water-mediated H-bonds. The flexibly linked phenyl-amidine with water-mediated H-bonds to the bases at the floor of the minor groove suggested that it might rotate in time spans accessible in MD. To test this idea, we conducted multimicrosecond MD simulations to determine if these phenyl rotations could be observed for a bound compound. In a 3 μs simulation, highly dynamic torsional motions were observed for the -OCH2-linked phenyl but not for the other phenyl. The dynamics periodically reached a level to allow 180° rotation of the phenyl while it was still bound in the minor groove. This is the first observation of rotation of a phenyl bound to DNA, and the results provide mechanistic details about how a rotation can occur as well as how mixed bp recognition can occur for monomer compounds bound to the minor groove.

Inference of Gene Flow in the Process of Speciation: An Efficient Maximum-Likelihood Method for the Isolation-with-Initial-Migration Model.

The isolation-with-migration (IM) model is commonly used to make inferences about gene flow during speciation, using polymorphism data. However, it has been reported that the parameter estimates obtained by fitting the IM model are very sensitive to the model’s assumptions—including the assumption of constant gene flow until the present. This article is concerned with the isolation-with-initial-migration (IIM) model, which drops precisely this assumption. In the IIM model, one ancestral population divides into two descendant subpopulations, between which there is an initial period of gene flow and a subsequent period of isolation. We derive a very fast method of fitting an extended version of the IIM model, which also allows for asymmetric gene flow and unequal population sizes. This is a maximum-likelihood method, applicable to data on the number of segregating sites between pairs of DNA sequences from a large number of independent loci. In addition to obtaining parameter estimates, our method can also be used, by means of likelihood-ratio tests, to distinguish between alternative models representing the following divergence scenarios: (a) divergence with potentially asymmetric gene flow until the present, (b) divergence with potentially asymmetric gene flow until some point in the past and in isolation since then, and (c) divergence in complete isolation. We illustrate the procedure on pairs of Drosophila sequences from ∼30,000 loci. The computing time needed to fit the most complex version of the model to this data set is only a couple of minutes. The R code to fit the IIM model can be found in the supplementary files of this article.

On DNA numerical representations for genomic similarity computation

Genomic signal processing (GSP) refers to the use of signal processing for the analysis of genomic data. GSP methods require the transformation or mapping of the genomic data to a numeric representation. To date, several DNA numeric representations (DNR) have been proposed; however, it is not clear what the properties of each DNR are and how the selection of one will affect the results when using a signal processing technique to analyze them. In this paper, we present an experimental study of the characteristics of nine of the most frequently-used DNR. The objective of this paper is to evaluate the behavior of each representation when used to measure the similarity of a given pair of DNA sequences.

Systematic synthetic and biophysical development of mixed sequence DNA binding agents.

It is now well established that, although only about 5% of the human genome codes for protein, most of the DNA has some function, such as synthesis of specific, functional RNAs and/or control of gene expression. These functional sequences open immense possibilities in both biotechnology and therapeutics for the use of cell-permeable, small molecules that can bind mixed-base pair sequences of DNA for regulation of genomic functions. Unfortunately very few types of modules have been designed to recognize mixed DNA sequences and for progress in targeting specific genes, it is essential to have additional classes of compounds. Compounds that can be rationally designed from established modules and which can bind strongly to mixed base pair DNA sequences are especially attractive. Based on extensive experience in design of minor-groove agents for AT recognition, a small library of compounds with two AT specific binding modules, connected through linkers which can recognize the G·C base pairs, were prepared. The compound-DNA interactions were evaluated with a powerful array of biophysical methods and the results show that some pyridyl-linked compounds bind with the target sequence with sub-nanomolar KD, with very slow dissociation kinetics and 200 times selectivity over the related sequence without a G·C base pair. Interestingly, a set of compounds with AT module connected by different linkers shows cooperative dimer recognition of related sequences. This type of design approach can be expanded to additional modules for recognition of a wide variety of sequences.

Proximity-Induced H-Aggregation of Cyanine Dyes on DNA-Duplexes.

A wide variety of organic dyes form, under certain conditions, clusters know as J- and H-aggregates. Cyanine dyes are such a class of molecules where the spatial proximity of several dyes leads to overlapping electron orbitals and thus to the creation of a new energy landscape compared to that of the individual units. In this work, we create artificial H-aggregates of exactly two Cyanine 3 (Cy3) dyes by covalently linking them to a DNA molecule with controlled subnanometer distances. The absorption spectra of these coupled systems exhibit a blue-shifted peak, whose intensity varies depending on the distance between the dyes and the rigidity of the DNA template. Simulated vibrational resolved spectra, based on molecular orbital theory, excellently reproduce the experimentally observed features. Circular dichroism spectroscopy additionally reveals distinct signals, which indicates a chiral arrangement of the dye molecules. Molecular dynamic simulations of a Cy3-Cy3 construct including a 14-base pair DNA sequence verified chiral stacking of the dye molecules.

A New Heuristic Approach for DNA Sequences Alignment

The problem of comparing DNA sequences is one of the most significant tasks in the field of computational biology. It helps locating the similarities and differences between pairs of DNA sequences. This task can be achieved by finding the longest common substrings between DNA sequences and consequently aligning them. The complexity of this task is due to the high computational power and huge space consuming. Comparing DNA sequences leads to infer the cause of a certain disease beside many significant biological applications. This paper introduces a new Heuristic Approach for DNA Sequences Alignment between two DNA sequences. The new approach is based on three processing phases: the first phase finds the multiple common substrings in the two sequences, the second one sorts the obtained common substrings descending according to their lengths, and the last phase generates the optimal two aligned sequences. The modules of the new approach have been implemented and tested in C# language under Windows platform. The obtained results manifest a reduction in both time of processing and memory requirements.

An alignment-free method to find and visualise rearrangements between pairs of DNA sequences.

Species evolution is indirectly registered in their genomic structure. The emergence and advances in sequencing technology provided a way to access genome information, namely to identify and study evolutionary macro-events, as well as chromosome alterations for clinical purposes. This paper describes a completely alignment-free computational method, based on a blind unsupervised approach, to detect large-scale and small-scale genomic rearrangements between pairs of DNA sequences. To illustrate the power and usefulness of the method we give complete chromosomal information maps for the pairs human-chimpanzee and human-orangutan. The tool by means of which these results were obtained has been made publicly available and is described in detail.