Browsing by Author "He, Jianlin"
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- EGR1 recruits TET1 to shape the brain methylome during development and upon neuronal activitySun, 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.
- Epigenetic regulation of neuronal cell specification inferred with single cell “Omics” dataYin, Liduo; Banerjee, Sharmi; Fan, Jiayi; He, Jianlin; Lu, Xuemei; Xie, Hehuang (Elsevier, 2020-01-01)The brain is a highly complex organ consisting of numerous types of cells with ample diversity at the epigenetic level to achieve distinct gene expression profiles. During neuronal cell specification, transcription factors (TFs) form regulatory modules with chromatin remodeling proteins to initiate the cascade of epigenetic changes. Currently, little is known about brain epigenetic regulatory modules and how they regulate gene expression in a cell-type specific manner. To infer TFs involved in neuronal specification, we applied a recursive motif search approach on the differentially methylated regions identified from single-cell methylomes. The epigenetic transcription regulatory modules (ETRM), including EGR1 and MEF2C, were predicted and the co-expression of TFs in ETRMs were examined with RNA-seq data from single or sorted brain cells using a conditional probability matrix. Lastly, computational predications were validated with EGR1 ChIP-seq data. In addition, methylome and RNA-seq data generated from Egr1 knockout mice supported the essential role of EGR1 in brain epigenome programming, in particular for excitatory neurons. In summary, we demonstrated that brain single cell methylome and RNA-seq data can be integrated to gain a better understanding of how ETRMs control cell specification. The analytical pipeline implemented in this study is freely accessible in the Github repository (https://github.com/Gavin-Yinld/brain_TF).
- Integrative single-cell omics analyses reveal epigenetic heterogeneity in mouse embryonic stem cellsLuo, 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.
- Retinal-input-induced epigenetic dynamics in the developing mouse dorsal lateral geniculate nucleusHe, Jianlin; Xu, Xiguang; Monavarfeshani, Aboozar; Banerjee, Sharmi; Fox, Michael A.; Xie, Hehuang David (2019-02-14)DNA methylation plays important roles in the regulation of nervous system development and in cellular responses to environmental stimuli such as light-derived signals. Despite great efforts in understanding the maturation and refinement of visual circuits, we lack a clear understanding of how changes in DNA methylation correlate with visual activity in the developing subcortical visual system, such as in the dorsal lateral geniculate nucleus (dLGN), the main retino-recipient region in the dorsal thalamus. Here, we explored epigenetic dynamics underlying dLGN development at ages before and after eye opening in wild-type mice and mutant mice in which retinal ganglion cells fail to form. We observed that development-related epigenetic changes tend to co-localize together on functional genomic regions critical for regulating gene expression, while retinal-input-induced epigenetic changes are enriched on repetitive elements. Enhancers identified in neurons are prone to methylation dynamics during development, and activity-induced enhancers are associated with retinal-input-induced epigenetic changes. Intriguingly, the binding motifs of activity-dependent transcription factors, including EGR1 and members of MEF2 family, are enriched in the genomic regions with epigenetic aberrations in dLGN tissues of mutant mice lacking retinal inputs. Overall, our study sheds new light on the epigenetic regulatory mechanisms underlying the role of retinal inputs on the development of mouse dLGN.
- Risk Assessment in Chinese Hospitalized Patients Comparing the Padua and Caprini Scoring AlgorithmsChen, Xiaolan; Pan, Lei; Deng, Hui; Zhang, Jingyuan; Tong, Xinjie; Huang, He; Zhang, Min; He, Jianlin; Caprini, Joseph A.; Wang, Yong (2018-12)The current venous thromboembolism (VTE) guidelines recommend all patients to be assessed for the risk of VTE using risk assessment models (RAMs). The study was to evaluate the performance of the Caprini and Padua RAMs among Chinese hospitalized patients. We reviewed data from 189 patients with deep venous thrombosis (DVT) and 201 non-DVT patients. Deep venous thrombosis risk factors were obtained from all patients. The sensitivity and specificity of the Caprini and Padua scores for all patients were calculated. The receiver operating curve (ROC) and the area under the ROC curve (AUC) were used to evaluate the performance of each score. We documented that age, acute infection, prothrombin time (PT), D-dimer, erythrocyte sedimentation rate, blood platelets, and anticoagulation were significantly associated with the occurrence of DVT (P < .05). These results were true for all medical and surgical patients group (G1), as well as the analysis of medical versus surgical patients (G2). Finally, analysis of the scores in patients with and without cancer was also done (G3). The Caprini has a higher sensitivity but a lower specificity than the Padua (P < .05). Caprini has a better predictive ability for the first 2 groups (P < .05). We found Caprini and Padua scores have a similar predictive value for patients with cancer (P > .05), while Caprini has a higher predictive ability for no cancer patients in G3 than Padua (P < .05). For Chinese hospitalized patients, Caprini has a higher sensitivity but a lower specificity than Padua. Overall, Caprini RAM has a better predictive ability than Padua RAM.