Delving into Eukaryotic Origins of Replication Using DNA Structural Features

Yella, Venkata Rajesh; Vanaja, Akkinepally; Kulandaivelu, Umasankar; Kumar, Aditya

doi:10.1021/acsomega.0c00441

Cited by 11 publications

(10 citation statements)

References 66 publications

(149 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Embedding layer can realize the conversions from trinucleotides to corresponding pre-training feature vectors. In convolution blocks with an activation function of ReLu, convolutional kernels are set as [2,3,4] respectively, and the number of kernels for each size is set to be 128. L2 regularization is adopted to avoid over-fitting, which can ensure the availability of the proposed architecture.…”

Section: • the Embedding Training Modementioning

confidence: 99%

“…Since the theory of DNA replication was proposed, the bioscience has been undergoing profound changes, which greatly motivates various studies based on the DNA replication, including cell growth and cell division. As a rigorous biological process starting at 'ORI' (origin of replication), DNA replication can generate two identical daughter strands by unwinding the parental template strands with the semiconservative replication strategy [1][2][3][4] . To keep normal cell functions and inherit a complete set of genomic information, DNA replication is activated only once per cell cycle 5 .…”

mentioning

confidence: 99%

See 1 more Smart Citation

A deep learning framework combined with word embedding to identify DNA replication origins

Zhang

2021

Sci Rep

View full text Add to dashboard Cite

The DNA replication influences the inheritance of genetic information in the DNA life cycle. As the distribution of replication origins (ORIs) is the major determinant to precisely regulate the replication process, the correct identification of ORIs is significant in giving an insightful understanding of DNA replication mechanisms and the regulatory mechanisms of genetic expressions. For eukaryotes in particular, multiple ORIs exist in each of their gene sequences to complete the replication in a reasonable period of time. To simplify the identification process of eukaryote’s ORIs, most of existing methods are developed by traditional machine learning algorithms, and target to the gene sequences with a fixed length. Consequently, the identification results are not satisfying, i.e. there is still great room for improvement. To break through the limitations in previous studies, this paper develops sequence segmentation methods, and employs the word embedding technique, ‘Word2vec’, to convert gene sequences into word vectors, thereby grasping the inner correlations of gene sequences with different lengths. Then, a deep learning framework to perform the ORI identification task is constructed by a convolutional neural network with an embedding layer. On the basis of the analysis of similarity reduction dimensionality diagram, Word2vec can effectively transform the inner relationship among words into numerical feature. For four species in this study, the best models are obtained with the overall accuracy of 0.975, 0.765, 0.885, 0.967, the Matthew’s correlation coefficient of 0.940, 0.530, 0.771, 0.934, and the AUC of 0.975, 0.800, 0.888, 0.981, which indicate that the proposed predictor has a stable ability and provide a high confidence coefficient to classify both of ORIs and non-ORIs. Compared with state-of-the-art methods, the proposed predictor can achieve ORI identification with significant improvement. It is therefore reasonable to anticipate that the proposed method will make a useful high throughput tool for genome analysis.

show abstract

Section: • the Embedding Training Modementioning

confidence: 99%

mentioning

confidence: 99%

A deep learning framework combined with word embedding to identify DNA replication origins

Zhang

2021

Sci Rep

View full text Add to dashboard Cite

show abstract

“…It may completely polymorph from its double-helical structure to non-double-helical forms such as G-quadruplexes, intercalated motifs, cruciform DNA, triple helices, hairpins, and slipped structures. , Non-B-DNA structures have been revealed to be key modulators of several physiological mechanisms. − Within a double-helical form, DNA can conform to the B or Z forms. Furthermore, perturbations in rotational and translational dinucleotide parameters of B-DNA account for several DNA structural features such as intrinsic curvature, flexibility, duplex stability, and groove shape. , Investigations on these signature features have been carried out to understand DNA transcription factor recognition, − characterize origins of replication in eukaryotes, − predict promoter regions in several lineages spanning from yeast to mammals, − and reveal associations among the DNA structure and gene expression variability. , In a recent study, we used DNA duplex stability, bendability, and curvature to delineate TATA-containing and TATA-less promoters in six eukaryotes . Another study also reported the bendability characteristics of TATA-less promoters .…”

Section: Introductionmentioning

confidence: 99%

Delineation of the DNA Structural Features of Eukaryotic Core Promoter Classes

Vanaja

Yella

2022

ACS Omega

Self Cite

View full text Add to dashboard Cite

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.

show abstract

“…Several of these functions, rely on the fact that these telomere-like sequences have repeating nucleotide patterns, and as terminal inverted repeats, are predicted to fold into complex structures occluding free ssDNA ends from host exonuclease activity while providing duplexed binding sites for endogenous and host factors. Additionally, the wtITR sequence is inherently GC rich, which is a feature of human replication origins and perhaps consequently transcriptionally active regions (12, 16). The repeating pattern of precisely spaced G nucleotides on ssDNA exhibited by the wtITR is predicted to adopt a G-quadruplex formation, which are common amongst viruses and are also features of replication origins and human telomeres (17, 18).…”

Section: Introductionmentioning

confidence: 99%

AAV Vector Transduction Restriction and Attenuated Toxicity in hESCs via a Rationally Designed Inverted Terminal Repeat

Song

Brown

Bower

et al. 2022

Preprint

View full text Add to dashboard Cite

Recombinant adeno-associated virus (rAAV) inverted terminal repeats (ITRs) induce p53-dependent apoptosis in human embryonic stem cells (hESCs). To interrogate this phenomenon, a rationally designed ITR (SynITR), deleted for p53 binding sites was evaluated for vector production and gene delivery. While SynITR genomes were decreased for transgenic genome replication compared to wtITRs, similar production titers indicated that replication is not rate-limiting. Packaged in the AAV2 capsid, wtITR and SynITR vectors demonstrated similar transduction efficiencies of human cell lines with no differences in reporter kinetics. Following rAAV2-wtITR infection of hESCs, rapid apoptosis was observed, in contrast, rAAV2-SynITR infection resulted in attenuated hESC toxicity with cells retaining their differentiation potential. While hESC particle entry and double stranded circular episomes was similar for the ITR contexts, reporter expression was significantly inhibited from transduced SynITR genomes. Infection of hESCs induced gamma H2AX in an ITR-independent manner, however, canonical activation of p53 alpha; was uncoupled using rAAV-SynITR. Further hESC investigations revealed 2 additional novel findings: i) p53 beta is uniquely and constitutively active, and ii) rAAV infection, independent of the ITR sequence, induces activation of p53 psi. The data herein reveal an ITR-dependent rAAV transduction restriction specific to hESCs and manipulation of the DNA damage response via ITR engineering.

show abstract

Delving into Eukaryotic Origins of Replication Using DNA Structural Features

Cited by 11 publications

References 66 publications

A deep learning framework combined with word embedding to identify DNA replication origins

A deep learning framework combined with word embedding to identify DNA replication origins

Delineation of the DNA Structural Features of Eukaryotic Core Promoter Classes

AAV Vector Transduction Restriction and Attenuated Toxicity in hESCs via a Rationally Designed Inverted Terminal Repeat

Contact Info

Product

Resources

About