Insights into the Link between the Organization of DNA Replication and the Mutational Landscape

Gaboriaud, Julia; Wu, Pei-Yun Jenny

doi:10.3390/genes10040252

Cited by 16 publications

(14 citation statements)

References 96 publications

(120 reference statements)

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“…Increased mutation rates are correlated with these late-replicating regions [ 56 ]. For an in-depth review of the mutational landscape of replication timing, see [ 57 ].…”

Section: Dna Sequences Prone To Mutationmentioning

confidence: 99%

“…Late-replicating regions contain a two- and sixfold increase in transition and transversion SNV mutations, respectively, compared with early-replicating loci [ 58 ]. Factors contributing to increased mutations in late-replicating regions include replication fork stress and induction of DNA damage response pathways [ 57 ]. Other mutation types are correlated with differences in replication timing.…”

Section: Dna Sequences Prone To Mutationmentioning

confidence: 99%

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Hotspots of Human Mutation

2021

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Mutation of the human genome results in three classes of genomic variation: single nucleotide variants; short insertions or deletions; and large structural variants (SVs). Some mutations occur during normal processes, such as meiotic recombination or B cell development, and others result from DNA replication or aberrant repair of breaks in sequence-specific contexts. Regardless of mechanism, mutations are subject to selection, and some hotspots can manifest in disease. Here, we discuss genomic regions prone to mutation, mechanisms contributing to mutation susceptibility, and the processes leading to their accumulation in normal and somatic genomes. With further, more accurate human genome sequencing, additional mutation hotspots, mechanistic details of their formation, and the relevance of hotspots to evolution and disease are likely to be discovered. HighlightsGenetic mutations are influenced by sequence context, structure, and genomic features.Mechanisms responsible for many mutational hotspots have been identified.Hotspots are largely related to loci prone to mutation during replication or DNA repair.Selection leads to recurrent mutations in somatic tissues that can be exploited for therapeutic purposes.

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“…Increased mutation rates are correlated with these late-replicating regions [ 56 ]. For an in-depth review of the mutational landscape of replication timing, see [ 57 ].…”

Section: Dna Sequences Prone To Mutationmentioning

confidence: 99%

Section: Dna Sequences Prone To Mutationmentioning

confidence: 99%

Hotspots of Human Mutation

2021

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“…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%

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

Zhang

2021

Sci Rep

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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.

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“…(D) We propose a model where Yap would ensure the proper orchestration of the RT program during early development. The schematic representation of the replication program was adapted from Gaboriaud J. and Wu PJ (Gaboriaud and Wu, 2019). Based on our assays in vitro in egg extracts and in vivo in early embryos, we propose that following Yap depletion (bottom panel), the number of firing origins is increased and S-phase length is reduced compared to a wild-type situation (top panel).…”

Section: Yapmentioning

confidence: 99%

A non-transcriptional function of Yap orchestrates the DNA replication program

Garcia

Haccard

Chesneau

et al. 2021

Preprint

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In multicellular eukaryotic organisms, the initiation of DNA replication occurs asynchronously throughout S-phase according to a regulated replication timing program. Here, using Xenopus egg extracts, we showed that Yap (Yes-associated protein 1), a downstream effector of the Hippo signaling pathway, is required for the control of DNA replication dynamics. We found that Yap is recruited to chromatin at the start of DNA replication and that Yap depletion accelerates DNA replication dynamics by increasing the number of activated replication origins. Furthermore, we identified Rif1, a major regulator of the DNA replication timing program, as a novel Yap binding protein. In Xenopus embryos, using a Trim-Away approach during cleavage stages devoid of transcription, we found that both Yap and Rif1 depletion trigger an acceleration of cell divisions, suggesting a shorter S-phase by alterations of the replication program. Finally, our data show that Rif1 knockdown leads to defects in the partitioning of early versus late replication foci in retinal stem cells, as we previously showed for Yap. Altogether, our findings unveil a non-transcriptional role for Yap in regulating replication dynamics. We propose that Yap and Rif1 function as breaks to control the DNA replication program in early embryos and post-embryonic stem cells.HighlightsYap is recruited to chromatin during DNA replication dependent on pre-replicative complex assembly.Yap controls DNA replication dynamics by limiting origin firing.The replication timing regulatory factor 1, Rif1, is a novel Yap binding-partner.Both Yap and Rif1 regulate the length of the first embryonic cell cycles.Like Yap, Rif1 controls retinal stem cell DNA replication timing.

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Insights into the Link between the Organization of DNA Replication and the Mutational Landscape

Cited by 16 publications

References 96 publications

Hotspots of Human Mutation

Hotspots of Human Mutation

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

A non-transcriptional function of Yap orchestrates the DNA replication program

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