Browsing by Author "Sun, Ming-an"

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    EGR1 recruits TET1 to shape the brain methylome during development and upon neuronal activity
    Sun, Zhixiong; Xu, Xiguang; He, Jianlin; Murray, Alexander; Sun, Ming-an; Wei, Xiaoran; Wang, Xia; McCoig, Emmarose; Xie, Evan; Jiang, Xi; Li, Liwu; Zhu, Jinsong; Chen, Jianjun; Morozov, Alexei; Pickrell, Alicia M.; Theus, Michelle H.; Xie, Hehuang David (2019-08-29)
    Life experience can leave lasting marks, such as epigenetic changes, in the brain. How life experience is translated into storable epigenetic information remains largely unknown. With unbiased data-driven approaches, we predicted that Egr1, a transcription factor important for memory formation, plays an essential role in brain epigenetic programming. We performed EGR1 ChIP-seq and validated thousands of EGR1 binding sites with methylation patterns established during postnatal brain development. More specifically, these EGR1 binding sites become hypomethylated in mature neurons but remain heavily methylated in glia. We further demonstrated that EGR1 recruits a DNA demethylase TET1 to remove the methylation marks and activate downstream genes. The frontal cortices from the knockout mice lacking Egr1 or Tet1 share strikingly similar profiles in both gene expression and DNA methylation. In summary, our study reveals EGR1 programs the brain methylome together with TET1 providing new insight into how life experience may shape the brain methylome.
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    HBS-Tools for Hairpin Bisulfite Sequencing Data Processing and Analysis
    Sun, Ming-an; Velmurugan, Karthik Raja; Keimig, David; Xie, Hehuang David (Hindawi, 2015-12-20)
    The emerging genome-wide hairpin bisulfite sequencing (hairpin-BS-Seq) technique enables the determination of the methylation pattern for DNA double strands simultaneously. Compared with traditional bisulfite sequencing (BS-Seq) techniques, hairpin-BS-Seq can determine methylation fidelity and increase mapping efficiency. However, no computational tool has been designed for the analysis of hairpin-BS-Seq data yet. Here we present HBS-tools, a set of command line based tools for the preprocessing, mapping, methylation calling, and summarizing of genome-wide hairpin-BS-Seq data. It accepts paired-end hairpin-BS-Seq reads to recover the original (pre-bisulfite-converted) sequences using global alignment and then calls the methylation statuses for cytosines on both DNA strands after mapping the original sequences to the reference genome. After applying to hairpin-BS-Seq datasets, we found that HBS-tools have a reduced mapping time and improved mapping efficiency compared with state-of-the-art mapping tools. The HBS-tools source scripts, along with user guide and testing data, are freely available for download.
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    Integrative single-cell omics analyses reveal epigenetic heterogeneity in mouse embryonic stem cells
    Luo, Yanting; He, Jianlin; Xu, Xiguang; Sun, Ming-an; Wu, Xiaowei; Lu, Xuemei; Xie, Hehuang David (PLOS, 2018-03)
    Embryonic stem cells (ESCs) consist of a population of self-renewing cells displaying extensive phenotypic and functional heterogeneity. Research towards the understanding of the epigenetic mechanisms underlying the heterogeneity among ESCs is still in its initial stage. Key issues, such as how to identify cell-subset specifically methylated loci and how to interpret the biological meanings of methylation variations remain largely unexplored. To fill in the research gap, we implemented a computational pipeline to analyze single-cell methylome and to perform an integrative analysis with single-cell transcriptome data. According to the origins of variation in DNA methylation, we determined the genomic loci associated with allelic-specific methylation or asymmetric DNA methylation, and explored a beta mixture model to infer the genomic loci exhibiting cell-subset specific methylation (CSM). We observed that the putative CSM loci in ESCs are significantly enriched in CpG island (CGI) shelves and regions with histone marks for promoter and enhancer, and the genes hosting putative CSM loci show wide-ranging expression among ESCs. More interestingly, the putative CSM loci may be clustered into co-methylated modules enriching the binding motifs of distinct sets of transcription factors. Taken together, our study provided a novel tool to explore single-cell methylome and transcriptome to reveal the underlying transcriptional regulatory networks associated with epigenetic heterogeneity of ESCs.
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    Investigating bisulfite short-read mapping failure with hairpin bisulfite sequencing data
    Porter, Jacob; Sun, Ming-an; Xie, Hehuang David; Zhang, Liqing (BMC, 2015-11-10)
    Background: DNA methylation is an important epigenetic mark relevant to normal development and disease genesis. A common approach to characterizing genome-wide DNA methylation is using Next Generation Sequencing technology to sequence bisulfite treated DNA. The short sequence reads are mapped to the reference genome to determine the methylation statuses of Cs. However, despite intense effort, a much smaller proportion of the reads derived from bisulfite treated DNA (usually about 40-80%) can be mapped than regular short reads mapping (> 90%), and it is unclear what factors lead to this low mapping efficiency. Results: To address this issue, we used the hairpin bisulfite sequencing technology to determine sequences of both DNA double strands simultaneously. This enabled the recovery of the original non-bisulfite-converted sequences. We used Bismark for bisulfite read mapping and Bowtie2 for recovered read mapping. We found that recovering the reads improved unique mapping efficiency by 9-10% compared to the bisulfite reads. Such improvement in mapping efficiency is related to sequence entropy. Conclusions: The hairpin recovery technique improves mapping efficiency, and sequence entropy relates to mapping efficiency.
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    Nonparametric Bayesian clustering to detect bipolar methylated genomic loci
    Wu, Xiaowei; Sun, Ming-an; Zhu, Hongxiao; Xie, Hehuang (Biomed Central, 2015-01-16)
    Background: With recent development in sequencing technology, a large number of genome-wide DNA methylation studies have generated massive amounts of bisulfite sequencing data. The analysis of DNA methylation patterns helps researchers understand epigenetic regulatory mechanisms. Highly variable methylation patterns reflect stochastic fluctuations in DNA methylation, whereas well-structured methylation patterns imply deterministic methylation events. Among these methylation patterns, bipolar patterns are important as they may originate from allele-specific methylation (ASM) or cell-specific methylation (CSM). Results: Utilizing nonparametric Bayesian clustering followed by hypothesis testing, we have developed a novel statistical approach to identify bipolar methylated genomic regions in bisulfite sequencing data. Simulation studies demonstrate that the proposed method achieves good performance in terms of specificity and sensitivity. We used the method to analyze data from mouse brain and human blood methylomes. The bipolar methylated segments detected are found highly consistent with the differentially methylated regions identified by using purified cell subsets. Conclusions: Bipolar DNA methylation often indicates epigenetic heterogeneity caused by ASM or CSM. With allele-specific events filtered out or appropriately taken into account, our proposed approach sheds light on the identification of cell-specific genes/pathways under strong epigenetic control in a heterogeneous cell population.
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    Objective and Comprehensive Evaluation of Bisulfite Short Read Mapping Tools
    Tran, Hong T.; Porter, Jacob; Sun, Ming-an; Xie, Hehuang David; Zhang, Liqing (Hindawi, 2014-04-15)
    Background. Large-scale bisulfite treatment and short reads sequencing technology allow comprehensive estimation of methylation states of Cs in the genomes of different tissues, cell types, and developmental stages. Accurate characterization of DNA methylation is essential for understanding genotype phenotype association, gene and environment interaction, diseases, and cancer. Aligning bisulfite short reads to a reference genome has been a challenging task. We compared five bisulfite short read mapping tools, BSMAP, Bismark, BS-Seeker, BiSS, and BRAT-BW, representing two classes of mapping algorithms (hash table and suffix/prefix tries). We examined their mapping efficiency (i.e., the percentage of reads that can be mapped to the genomes), usability, running time, and effects of changing default parameter settings using both real and simulated reads. We also investigated how preprocessing data might affect mapping efficiency. Conclusion. Among the five programs compared, in terms of mapping efficiency, Bismark performs the best on the real data, followed by BiSS, BSMAP, and finally BRAT-BW and BS-Seeker with very similar performance. If CPU time is not a constraint, Bismark is a good choice of program for mapping bisulfite treated short reads. Data quality impacts a great deal mapping efficiency. Although increasing the number of mismatches allowed can increase mapping efficiency, it not only significantly slows down the program, but also runs the risk of having increased false positives. Therefore, users should carefully set the related parameters depending on the quality of their sequencing data.