| With the rapid development of high-throughput sequencing and chip technology,genomics research has entered the post-genomic era gradually.Epigenetics includes DNA methylations,RNA modification,histone modifications,chromatin structure remodeling,etc.,is becoming a hot research topic in gene regulation.DNA methylation is the earliest discovered epigenetic mechanism.With the accumulation of massive amounts of data,it has been possible to study the interaction between methylated DNA-binding transcription factors and gene regulation function.However,how to integrate massive and multi-omics data effectively and deeply study the biological function of DNA methylation is still an important issue with needs to be solved urgently.The biological functions of the connection between the DNA methylation and transcription factors are of great significance to figure out the DNA methylation role in specific genetic diseases and discovering new disease biomarkers and new drug targets.This article focuses on the interaction between DNA methylation and transcription factors and reveals the rules and biological functions of this interaction.By using the open-source data and self-developed technologies,a variety of biological information analysis methods have been constructed for high-throughput DNA methylation data and transcription factor binding information.The main contents include the following four aspects:First,for DNA methylation chip data,currently fixed thresholds are mainly used to judge DNA methylation status.However,due to the heterogeneity of cells,the overall methylation level of different cells is different,and it is unreasonable to directly use a fixed threshold to divide the methylation status.To solve this problem,based on the characteristics of the DNA chip data,combined with the overall methylation level distribution of the cell,a hidden Markov model is used to construct an algorithm which can dynamically and accurately identify the methylation status of single nucleotide sites and DNA regions.Second,with the deepening of research,it has been discovered that transcription factors can bind to methylated DNA regions.In order to systematically study the interaction between transcription factors and DNA methylation,the whole-genome bisulfite sequencing data is used to construct an algorithm which can identify transcription factor binding motifs under different DNA methylation states.By using this algorithm,the first large-scale and systematic study of the interaction between DNA methylation and transcription factors,and the first database on the interaction between DNA methylation and transcription factors is built based on open-source data.Third,to study the biological function of DNA methylation,the DNA methylation level and gene expression level are used innovatively to construct an active enhancer prediction algorithm.At the same time,deep learning algorithms are used to construct enhancer prediction algorithms based on DNA sequences.To avoid the dependence of enhancer prediction on multi-omics data,both algorithms rely on the simplest data.Fourth,in response to the current lack of all-to-all high-throughput technology for the interaction of DNA and transcription factors,the technology named ’DAPPL’is developed independently which can simultaneously detect the interaction of multiple epigenetic modifications and multiple transcription factors.With this technology,a series of bioinformatics analysis algorithms have been constructed independently.Aiming at the features of DAPPL with high noise and large sequences,we innovatively construct data preprocessing algorithm,6-mer-based denoising algorithm and transcription factor binding motif recognition algorithms.At the same time,DAPPL is used to systematically study the interaction between 1534 transcription factors and DNA methylation and three DNA methylation oxides for the first time.Then we analyzed the influence of different modification forms on the interaction between transcription factors and DNA.The research results are helpful to understand the biological regulation function of the dynamic changes of DNA methylation,and lay the foundation for the study of the relationship between DNA methylation changes and diseases.Besides,this technology also provides a technical reference for subsequent research on other DNA or RNA modifications. |
