Analysis of the Epigenetic Signature of Cell Reprogramming by Computational DNA Methylation Profiles

Zuo, Yongchun; Song, Ming; Li, Hanshuang; Chen, Xing; Cao, Pengbo; Zheng, Lei; Cao, Guifang

doi:10.2174/1574893614666190919103752

Cited by 25 publications

(11 citation statements)

References 51 publications

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“…In conclusion, we identified incomplete activation of transcription pathways and massive dysregulation of genes related to transcription pathway in NTA embryos. Then, the GRNs indicated that crucial factors responsible for transcription play a coordinated role in epigenome erasure and pluripotency regulation during normal embryo development [ 44 , 45 , 46 , 47 ]. However, in NTA embryos, predicted target genes of transcription pathways were varying in degrees of inhibition and showed a defect in synergy.…”

Section: Discussionmentioning

confidence: 99%

Nuclear Transfer Arrest Embryos Show Massive Dysregulation of Genes Involved in Transcription Pathways

Long

et al. 2021

IJMS

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Somatic cell nuclear transfer (SCNT) technology can reprogram terminally differentiated cell nuclei into a totipotent state. However, the underlying molecular barriers of SCNT embryo development remain incompletely elucidated. Here, we observed that transcription-related pathways were incompletely activated in nuclear transfer arrest (NTA) embryos compared to normal SCNT embryos and in vivo fertilized (WT) embryos, which hinders the development of SCNT embryos. We further revealed the transcription pathway associated gene regulatory networks (GRNs) and found the aberrant transcription pathways can lead to the massive dysregulation of genes in NTA embryos. The predicted target genes of transcription pathways contain a series of crucial factors in WT embryos, which play an important role in catabolic process, pluripotency regulation, epigenetic modification and signal transduction. In NTA embryos, however, these genes were varying degrees of inhibition and show a defect in synergy. Overall, our research found that the incomplete activation of transcription pathways is another potential molecular barrier for SCNT embryos besides the incomplete reprogramming of epigenetic modifications, broadening the understanding of molecular mechanism of SCNT embryonic development.

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Section: Discussionmentioning

confidence: 99%

Nuclear Transfer Arrest Embryos Show Massive Dysregulation of Genes Involved in Transcription Pathways

Long

et al. 2021

IJMS

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“…Considering the performance, most of the existing predictors are evaluated by cross validation test, which might produce performance bias; we here randomly split the datasets into ( Zuo et al, 2020 ) training set for model training and evaluation and ( Liu et al, 2019 ) independent test set for model robustness validation. Thus, we randomly divided the dataset into training set and testing set with the ratio of 8:2, resulting in 16,000 samples in the training set and 4,000 samples in the testing set.…”

Section: Methodsmentioning

confidence: 99%

“…Epigenetics refers to the reversible and heritable changes in gene function when there is no change in the nuclear DNA sequence ( Zuo et al, 2020 ). Epigenetic phenomena include DNA methylation, RNA interference, histone modification, etc.…”

Section: Introductionmentioning

confidence: 99%

4mCPred-MTL: Accurate Identification of DNA 4mC Sites in Multiple Species Using Multi-Task Deep Learning Based on Multi-Head Attention Mechanism

Zeng

Cheng

Liao

2021

Front. Cell Dev. Biol.

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DNA methylation is one of the most extensive epigenetic modifications. DNA 4mC modification plays a key role in regulating chromatin structure and gene expression. In this study, we proposed a generic 4mC computational predictor, namely, 4mCPred-MTL using multi-task learning coupled with Transformer to predict 4mC sites in multiple species. In this predictor, we utilize a multi-task learning framework, in which each task is to train species-specific data based on Transformer. Extensive experimental results show that our multi-task predictive model can significantly improve the performance of the model based on single task and outperform existing methods on benchmarking comparison. Moreover, we found that our model can sufficiently capture better characteristics of 4mC sites as compared to existing commonly used feature descriptors, demonstrating the strong feature learning ability of our model. Therefore, based on the above results, it can be expected that our 4mCPred-MTL can be a useful tool for research communities of interest.

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“…Due to its importance, DNA methylation is one of the most widely studied epigenetic modifications (Bergman and Cedar, 2013;Smith and Meissner, 2013). Currently, four out of the DNA modifications, such as N4-methylcytosine (4mC), N6-methyladenine (6mA), 5-methylcytosine (5mC), and 5-hydroxymethylcytosine (5hmC), have been extensively studied (Cheng and Baldi, 2006;Guohua et al, 2017;He et al, 2019;Luo et al, 2020;Zuo et al, 2020c). Schweizer (2008) proposed that 4mC has the effect of protecting the host DNA from degradation by restriction enzymes and belongs to restriction-modification (RM) systems.…”

Section: Introductionmentioning

confidence: 99%

iDNA-MT: Identification DNA Modification Sites in Multiple Species by Using Multi-Task Learning Based a Neural Network Tool

Yang

et al. 2021

Front. Genet.

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MotivationDNA N4-methylcytosine (4mC) and N6-methyladenine (6mA) are two important DNA modifications and play crucial roles in a variety of biological processes. Accurate identification of the modifications is essential to better understand their biological functions and mechanisms. However, existing methods to identify 4mA or 6mC sites are all single tasks, which demonstrates that they can identify only a certain modification in one species. Therefore, it is desirable to develop a novel computational method to identify the modification sites in multiple species simultaneously.ResultsIn this study, we proposed a computational method, called iDNA-MT, to identify 4mC sites and 6mA sites in multiple species, respectively. The proposed iDNA-MT mainly employed multi-task learning coupled with the bidirectional gated recurrent units (BGRU) to capture the sharing information among different species directly from DNA primary sequences. Experimental comparative results on two benchmark datasets, containing different species respectively, show that either for identifying 4mA or for 6mC site in multiple species, the proposed iDNA-MT outperforms other state-of-the-art single-task methods. The promising results have demonstrated that iDNA-MT has great potential to be a powerful and practically useful tool to accurately identify DNA modifications.

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Analysis of the Epigenetic Signature of Cell Reprogramming by Computational DNA Methylation Profiles

Cited by 25 publications

References 51 publications

Nuclear Transfer Arrest Embryos Show Massive Dysregulation of Genes Involved in Transcription Pathways

Nuclear Transfer Arrest Embryos Show Massive Dysregulation of Genes Involved in Transcription Pathways

4mCPred-MTL: Accurate Identification of DNA 4mC Sites in Multiple Species Using Multi-Task Deep Learning Based on Multi-Head Attention Mechanism

iDNA-MT: Identification DNA Modification Sites in Multiple Species by Using Multi-Task Learning Based a Neural Network Tool

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