Zhang, Michael Q.

Permanent URI for this collectionhttps://hdl.handle.net/10735.1/3154

Professor Michael Q. Zhang holds the Cecil H. and Ida Green Chair of Systems Biology Science. He also serves as director of the Center for Systems Biology. He is considered a leading scientist in computational biology and genomic research. Computational biology bridges the life sciences and quantitative sciences – mathematics, statistics and computer science – to understand living systems. His long-term research goal has been to use mathematical and statistical methods to identify functional elements in eucaryotic genomes, especially the genes and their control and regulatory elements.

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    Integrating Hi-C and FISH Data for Modeling of the 3D Organization of Chromosomes
    (Nature Publishing Group, 2019-05-03) Abbas, A.; He, X.; Niu, J.; Zhou, B.; Zhu, G.; Ma, T.; Song, J.; Gao, J.; Zhang, Michael Q.; Zeng, J.; Zhang, Michael Q.
    The new advances in various experimental techniques that provide complementary information about the spatial conformations of chromosomes have inspired researchers to develop computational methods to fully exploit the merits of individual data sources and combine them to improve the modeling of chromosome structure. Here we propose GEM-FISH, a method for reconstructing the 3D models of chromosomes through systematically integrating both Hi-C and FISH data with the prior biophysical knowledge of a polymer model. Comprehensive tests on a set of chromosomes, for which both Hi-C and FISH data are available, demonstrate that GEM-FISH can outperform previous chromosome structure modeling methods and accurately capture the higher order spatial features of chromosome conformations. Moreover, our reconstructed 3D models of chromosomes revealed interesting patterns of spatial distributions of super-enhancers which can provide useful insights into understanding the functional roles of these super-enhancers in gene regulation. © 2019, The Author(s).
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    Inhibiting the Integrated Stress Response Pathway Prevents Aberrant Chondrocyte Differentiation Thereby Alleviating Chondrodysplasia
    (eLife Sciences Publications Ltd) Wang, C.; Tan, Z.; Niu, B.; Tsang, K. Y.; Tai, A.; Chan, W. C. W.; Lo, R. L. K.; Leung, K. K. H.; Dung, N. W. F.; Itoh, N.; Zhang, Michael Q.; Chan, D.; Cheah, K. S. E.; 0000-0002-7408-1830 (Zhang, MQ); 161723084 (Zhang, MQ); Zhang, Michael Q.
    The integrated stress response (ISR) is activated by diverse forms of cellular stress, including endoplasmic reticulum (ER) stress, and is associated with diseases. However, the molecular mechanism(s) whereby the ISR impacts on differentiation is incompletely understood. Here, we exploited a mouse model of Metaphyseal Chondrodysplasia type Schmid (MCDS) to provide insight into the impact of the ISR on cell fate. We show the protein kinase RNA-like ER kinase (PERK) pathway that mediates preferential synthesis of ATF4 and CHOP, dominates in causing dysplasia by reverting chondrocyte differentiation via ATF4-directed transactivation of Sox9. Chondrocyte survival is enabled, cell autonomously, by CHOP and dual CHOP-ATF4 transactivation of Fgf21. Treatment of mutant mice with a chemical inhibitor of PERK signaling prevents the differentiation defects and ameliorates chondrodysplasia. By preventing aberrant differentiation, titrated inhibition of the ISR emerges as a rationale therapeutic strategy for stress-induced skeletal disorders. © Wang et al.
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    Alterations of Specific Chromatin Conformation Affect ATRA-Induced Leukemia Cell Differentiation
    (Nature Publishing Group) Li, Yanjian; He, Yi; Liang, Zhengyu; Wang, Yang; Chen, Fengling; Djekidel, Mohamed Nadhir; Li, Guipeng; Zhang, Xu; Xiang, Shuqin; Wang, Zejun; Gao, Juntao; Zhang, Michael Q.; Chen, Yang; 0000 0001 1707 1372 (Zhang, MQ); Zhang, Michael Q.
    Chromatin conformation plays a key role in regulating gene expression and controlling cell differentiation. However, the whole-genome chromatin conformation changes that occur during leukemia cell differentiation are poorly understood. Here, we characterized the changes in chromatin conformation, histone states, chromatin accessibility, and gene expression using an all-trans retinoic acid (ATRA)-induced HL-60 cell differentiation model. The results showed that the boundaries of topological associated domains (TADs) were stable during differentiation; however, the chromatin conformations within several specific TADs were obviously changed. By combining H3K4me3, H3K27ac, and Hi-C signals, we annotated the differential gene- regulatory chromatin interactions upon ATRA induction. The gains and losses of the gene-regulatory chromatin interactions are significantly correlated with gene expression and chromatin accessibility. Finally, we found that the loss of GATA2 expression and DNA binding are crucial for the differentiation process, and changes in the chromatin structure around the GATA2 regulate its expression upon ATRA induction. This study provided both statistical insights and experimental details regarding the relationship between chromatin conformation changes and transcription regulation during leukemia cell differentiation, and the results suggested that the chromatin conformation is a new type of potential drug target for cancer therapy.
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    FIND: DifFerential Chromatin INteractions Detection Using a Spatial Poisson Process
    (Cold Spring Harbor Lab Press, Publications Dept) Djekidel, Mohamed Nadhir; Chen, Yang; Zhang, Michael Q.; 0000 0001 1707 1372 (Zhang, MQ); Zhang, Michael Q.
    Polymer-based simulations and experimental studies indicate the existence of a spatial dependency between the adjacent DNA fibers involved in the formation of chromatin loops. However, the existing strategies for detecting differential chromatin interactions assume that the interacting segments are spatially independent from the other segments nearby. To resolve this issue, we developed a new computational method, FIND, which considers the local spatial dependency between interacting loci. FIND uses a spatial Poisson process to detect differential chromatin interactions that show a significant difference in their interaction frequency and the interaction frequency of their neighbors. Simulation and biological data analysis show that FIND outperforms the widely used count-based methods and has a better signal-to-noise ratio.
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    Relaxation Rates of Gene Expression Kinetics Reveal the Feedback Signs of Autoregulatory Gene Networks
    (American Institute of Physics Inc) Jia, Chen; Qian, Hong; Chen, Min; Zhang, Michael Q.; 0000 0001 1707 1372 (Zhang, MQ); Jia, Chen; Chen, Min; Zhang, Michael Q.
    The transient response to a stimulus and subsequent recovery to a steady state are the fundamental characteristics of a living organism. Here we study the relaxation kinetics of autoregulatory gene networks based on the chemical master equation model of single-cell stochastic gene expression with nonlinear feedback regulation. We report a novel relation between the rate of relaxation, characterized by the spectral gap of the Markov model, and the feedback sign of the underlying gene circuit. When a network has no feedback, the relaxation rate is exactly the decaying rate of the protein. We further show that positive feedback always slows down the relaxation kinetics while negative feedback always speeds it up. Numerical simulations demonstrate that this relation provides a possible method to infer the feedback topology of autoregulatory gene networks by using time-series data of gene expression. © 2018 Author(s).
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    Web3DMol: Interactive Protein Structure Visualization Based on WebGL
    (Oxford University Press, 2017-05-08) Shi, M.; Gao, J.; Zhang, Michael Q.; Zhang, Michael Q.
    A growing number of web-based databases and tools for protein research are being developed. There is now a widespread need for visualization tools to present the three-dimensional (3D) structure of proteins in web browsers. Here, we introduce our 3D modeling program--Web3DMol--a web application focusing on protein structure visualization in modern web browsers. Users submit a PDB identification code or select a PDB archive from their local disk, and Web3DMol will display and allow interactive manipulation of the 3D structure. Featured functions, such as sequence plot, fragment segmentation, measure tool and meta-information display, are offered for users to gain a better understanding of protein structure. Easy-to-use APIs are available for developers to reuse and extend Web3DMol. Web3DMol can be freely accessed at http://web3dmol.duapp.com/, and the source code is distributed under the MIT license.
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    Super-Resolution Imaging of a 2.5 Kb Non-Repetitive DNA in situ in the Nuclear Genome Using Molecular Beacon Probes
    (2018-08-31) Ni, Yanxiang; Cao, Bo; Ma, Tszshan; Niu, Gang; Huo, Yingdong; Huang, Jiandong; Chen, Danni; Liu, Yi; Yu, Bin; Zhang, Michael Q.; Niu, Hanben; 0000-0002-7408-1830 (Zhang, MQ); Zhang, Michael Q.
    High-resolution visualization of short non-repetitive DNA in situ in the nuclear genome is essential for studying looping interactions and chromatin organization in single cells. Recent advances in fluorescence in situ hybridization (FISH) using Oligopaint probes have enabled super resolution imaging of genomic domains with a resolution limit of 4.9 kb. To target shorter elements, we developed a simple FISH method that uses molecular beacon (MB) probes to facilitate the probe-target binding, while minimizing non-specific fluorescence. We used three-dimensional stochastic optical reconstruction microscopy (3D-STORM) with optimized imaging conditions to efficiently distinguish sparsely distributed Alexa-647 from background cellular autofluorescence. Utilizing 3D-STORM and only 29-34 individual MB probes, we observed 3D fine scale nanostructures of 2.5 kb integrated or endogenous unique DNA in situ in human or mouse genome, respectively. We demonstrated our MB-based FISH method was capable of visualizing the so far shortest non-repetitive genomic sequence in 3D at super-resolution.
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    Reconstructing Cell Cycle Pseudo Time-Series Via Single-Cell Transcriptome Data
    (Nature Publishing Group, 2018-08-24) Liu, Zehua; Lou, Huazhe; Xie, Kaikun; Wang, Hao; Chen, Ning; Aparicio, Oscar M.; Zhang, Michael Q.; Jiang, Rui; Chen, Ting; Zhang, Michael Q.
    Single-cell mRNA sequencing, which permits whole transcriptional profiling of individual cells, has been widely applied to study growth and development of tissues and tumors. Resolving cell cycle for such groups of cells is significant, but may not be adequately achieved by commonly used approaches. Here we develop a traveling salesman problem and hidden Markov model-based computational method named reCAT, to recover cell cycle along time for unsynchronized single-cell transcriptome data. We independently test reCAT for accuracy and reliability using several data sets. We find that cell cycle genes cluster into two major waves of expression, which correspond to the two well-known checkpoints, G1 and G2. Moreover, we leverage reCAT to exhibit methylation variation along the recovered cell cycle. Thus, reCAT shows the potential to elucidate diverse profiles of cell cycle, as well as other cyclic or circadian processes (e.g., in liver), on single-cell resolution.
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    ChIA-PET2: A Versatile and Flexible Pipeline for ChIA-PET Data Analysis
    (Oxford University Press, 2016-09-12) Li, G.; Chen, Y.; Snyder, M. P.; Zhang, Michael Q.; Zhang, Michael Q.
    ChIA-PET2 is a versatile and flexible pipeline for analyzing different types of ChIA-PET data from raw sequencing reads to chromatin loops. ChIA-PET2 integrates all steps required for ChIA-PET data analysis, including linker trimming, read alignment, duplicate removal, peak calling and chromatin loop calling. It supports different kinds of ChIA-PET data generated from different ChIA-PET protocols and also provides quality controls for different steps of ChIA-PET analysis. In addition, ChIA-PET2 can use phased genotype data to call allele-specific chromatin interactions. We applied ChIA-PET2 to different ChIA-PET datasets, demonstrating its significantly improved performance as well as its ability to easily process ChIA-PET raw data. ChIA-PET2 is available at https://github.com/GuipengLi/ChIA-PET2. © The Author(s) 2016.
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    Emergent Lévy Behavior In Single-cell Stochastic Gene Expression
    (American Physical Society, 2018-08-20) Jia, Chen; Zhang, Michael Q.; Qian, H.; Jia, Chen; Zhang, Michael Q.
    Single-cell gene expression is inherently stochastic; its emergent behavior can be defined in terms of the chemical master equation describing the evolution of the mRNA and protein copy numbers as the latter tends to infinity. We establish two types of "macroscopic limits": the Kurtz limit is consistent with the classical chemical kinetics, while the Lévy limit provides a theoretical foundation for an empirical equation proposed in N. Friedman et al., Phys. Rev. Lett. 97, 168302 (2006). Furthermore, we clarify the biochemical implications and ranges of applicability for various macroscopic limits and calculate a comprehensive analytic expression for the protein concentration distribution in autoregulatory gene networks. The relationship between our work and modern population genetics is discussed.
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    De Novo Deciphering Three-Dimensional Chromatin Interaction and Topological Domains by Wavelet Transformation of Epigenetic Profiles
    (Oxford University Press, 2016-04-07) Chen, Yong; Wang, Yunfei; Xuan, Zhenyu; Chen, Min; Zhang, Michael Q.; 0000 0001 1707 1372 (Zhang, MQ); 0000-0002-4029-8716 (Chen, M); Chen, Yong; Wang, Yunfei; Xuan, Zhenyu; Chen, Min; Zhang, Michael Q.
    Defining chromatin interaction frequencies and topological domains is a great challenge for the annotations of genome structures. Although the chromosome conformation capture (3C) and its derivative methods have been developed for exploring the global interactome, they are limited by high experimental complexity and costs. Here we describe a novel computational method, called CITD, for de novo prediction of the chromatin interaction map by integrating histone modification data. We used the public epigenomic data from human fibroblast IMR90 cell and embryonic stem cell (H1) to develop and test CITD, which can not only successfully reconstruct the chromatin interaction frequencies discovered by the Hi-C technology, but also provide additional novel details of chromosomal organizations. We predicted the chromatin interaction frequencies, topological domains and their states (e.g. active or repressive) for 98 additional cell types from Roadmap Epigenomics and ENCODE projects. A total of 131 protein-coding genes located near 78 preserved boundaries among 100 cell types are found to be significantly enriched in functional categories of the nucleosome organization and chromatin assembly. CITD and its predicted results can be used for complementing the topological domains derived from limited Hi-C data and facilitating the understanding of spatial principles underlying the chromosomal organization.
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    Chip-Array 2: Integrating Multiple Omics Data to Construct Gene Regulatory Networks
    (2015-04-27) Wang, Panwen; Qin, Jing; Qin, Yiming; Zhu, Yun; Wang, Lily Yan; Li, Mulin Jun; Zhang, Michael Q.; Wang, Junwen; 0000 0001 1707 1372 (Zhang, MQ); Zhang, Michael Q.
    Transcription factors (TFs) play an important role in gene regulation. The interconnections among TFs, chromatin interactions, epigenetic marks and cisregulatory elements form a complex gene transcription apparatus. Our previous work, ChIP-Array, combined TF binding and transcriptome data to construct gene regulatory networks (GRNs). Here we present an enhanced version, ChIP-Array 2, to integrate additional types of omics data including long-range chromatin interaction, open chromatin region and histone modification data to dissect more comprehensive GRNs involving diverse regulatory components. Moreover, we substantially extended our motif database for human, mouse, rat, fruit fly, worm, yeast and Arabidopsis, and curated large amount of omics data for users to select as input or backend support. With ChIP-Array 2, we compiled a library containing regulatory networks of 18 TFs/chromatin modifiers in mouse embryonic stem cell (mESC). The web server and the mESC library are publicly free and accessible at http://jjwanglab.org/chip-array.
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    Quantitative Combination of Natural Anti-Oxidants Prevents Metabolic Syndrome by Reducing Oxidative Stress
    (2015-06-26) Gao, Mingjing; Zhao, Zhen; Lv, Pengyu; Li, YuFang; Gao, Juntao; Zhang, Michael Q.; Zhao, Baolu; 0000 0001 1707 1372 (Zhang, MQ); Zhang, Michael Q.
    Insulin resistance and abdominal obesity are present in the majority of people with the metabolic syndrome. Antioxidant therapy might be a useful strategy for type 2 diabetes and other insulin-resistant states. The combination of vitamin C (Vc) and vitamin E has synthetic scavenging effect on free radicals and inhibition effect on lipid peroxidation. However, there are few studies about how to define the best combination of more than three anti-oxidants as it is difficult or impossible to test the anti-oxidant effect of the combination of every concentration of each ingredient experimentally. Here we present a math model, which is based on the classical Hill equation to determine the best combination, called Fixed Dose Combination (FDC), of several natural anti-oxidants, including Vc, green tea polyphenols (GTP) and grape seed extract proanthocyanidin (GSEP). Then we investigated the effects of FDC on oxidative stress, blood glucose and serum lipid levels in cultured 3T3-L1 adipocytes, high fat diet (HFD)-fed rats which serve as obesity model, and KK-ay mice as diabetic model. The level of serum malondialdehyde (MDA) in the treated rats was studied and Hematoxylin-Eosin (HE) staining or Oil red slices of liver and adipose tissue in the rats were examined as well. FDC shows excellent antioxidant and anti-glycation activity by attenuating lipid peroxidation. FDC determined in this investigation can become a potential solution to reduce obesity, to improve insulin sensitivity and be beneficial for the treatment of fat and diabetic patients. It is the first time to use the math model to determine the best ratio of three anti-oxidants, which can save much more time and chemical materials than traditional experimental method. This quantitative method represents a potentially new and useful strategy to screen all possible combinations of many natural anti-oxidants, therefore may help develop novel therapeutics with the potential to ameliorate the worldwide metabolic abnormalities.
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    3CPET: Finding Co-Factor Complexes from ChIA-Pet Data Using a Hierarchical Dirichlet Process
    (BioMed Central Ltd, 2015-12-22) Djekidel, Mohamed Nadhir; Liang, Zhengyu; Wang, Qi; Hu, Zhirui; Li, Guipeng; Chen, Yang; Zhang, Michael Q.; 0000 0001 1707 1372 (Zhang, MQ); Zhang, Michael Q.
    Various efforts have been made to elucidate the cooperating proteins involved in maintaining chromatin interactions; however, many are still unknown. Here, we present 3CPET, a tool based on a non-parametric Bayesian approach, to infer the set of the most probable protein complexes involved in maintaining chromatin interactions and the regions that they may control, making it a valuable downstream analysis tool in chromatin conformation studies. 3CPET does so by combining data from ChIA-PET, transcription factor binding sites, and protein interactions. 3CPET results show biologically significant and accurate predictions when validated against experimental and simulation data.
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    Histone Deacetylases Positively Regulate Transcription Through the Elongation Machinery
    (Elsevier B.V., 2015-11-17) Greer, Celeste B.; Tanaka, Yoshiaki; Kim, Yoon Jung; Xie, Peng; Zhang, Michael Q.; Park, In-Hyun; Kim, Tae Hoon; 0000 0001 1707 1372 (Zhang, MQ); Kim, Yoon Jung; Xie, Peng; Zhang, Michael Q.; Park, In-Hyun
    Transcription elongation regulates the expression of many genes, including oncogenes. Histone deacetylase (HDAC) inhibitors (HDACIs) block elongation, suggesting that HDACs are involved in gene activation. To understand this, we analyzed nascent transcription and elongation factor binding genome-wide after perturbation of elongation with small molecule inhibitors. We found that HDACI-mediated repression requires heat shock protein 90 (HSP90) activity. HDACIs promote the association of RNA polymerase II (RNAP2) and negative elongation factor (NELF), a complex stabilized by HSP90, at the same genomic sites. Additionally, HDACIs redistribute bromodomain-containing protein 4 (BRD4), a key elongation factor involved in enhancer activity. BRD4 binds to newly acetylated sites, and its occupancy at promoters and enhancers is reduced. Furthermore, HDACIs reduce enhancer activity, as measured by enhancer RNA production. Therefore, HDACs are required for limiting acetylation in gene bodies and intergenic regions. This facilitates the binding of elongation factors to properly acetylated promoters and enhancers for efficient elongation.; Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
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    Fast Dimension Reduction and Integrative Clustering of Multi-Omics Data Using Low-Rank Approximation: Application to Cancer Molecular Classification
    (BioMed Central, 2015-12-01) Wu, Dingming; Wang, Dongfang; Zhang, Michael Q.; Gu, Jin; 0000 0001 1707 1372 (Zhang, MQ); Zhang, Michael Q.
    Background: One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data.; Results: In this study, we proposed a novel low-rank approximation based integrative probabilistic model to fast find the shared principal subspace across multiple data types: the convexity of the low-rank regularized likelihood function of the probabilistic model ensures efficient and stable model fitting. Candidate molecular subtypes can be identified by unsupervised clustering hundreds of cancer samples in the reduced low-dimensional subspace. On testing datasets, our method LRAcluster (low-rank approximation based multi-omics data clustering) runs much faster with better clustering performances than the existing method. Then, we applied LRAcluster on large-scale cancer multi-omics data from TCGA. The pan-cancer analysis results show that the cancers of different tissue origins are generally grouped as independent clusters, except squamous-like carcinomas. While the single cancer type analysis suggests that the omics data have different subtyping abilities for different cancer types.; Conclusions: LRAcluster is a very useful method for fast dimension reduction and unsupervised clustering of large-scale multi-omics data. LRAcluster is implemented in R and freely available via http://bioinfo.au.tsinghua.edu.cn/software/lracluster/
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    Distinct and Predictive Histone Lysine Acetylation Patterns at Promoters, Enhancers, and Gene Bodies
    (Genetics Society America, 2014-11-01) Rajagopal, Nisha; Ernst, Jason; Ray, Pradipta; Wu, Jie; Zhang, Michael Q.; Kellis, Manolis; Ren, Bing; 0000 0001 1707 1372 (Zhang, MQ); 99086074‏ (Zhang, MQ); Zhang, Michael Q.
    In eukaryotic cells, histone lysines are frequently acetylated. However, unlike modifications such as methylations, histone acetylation modifications are often considered redundant. As such, the functional roles of distinct histone acetylations are largely unexplored. We previously developed an algorithm RFECS to discover the most informative modifications associated with the classification or prediction of mammalian enhancers. Here, we used this tool to identify the modifications most predictive of promoters, enhancers, and gene bodies. Unexpectedly, we found that histone acetylation alone performs well in distinguishing these unique genomic regions. Further, we found the association of characteristic acetylation patterns with genic regions and association of chromatin state with splicing. Taken together, our work underscores the diverse functional roles of histone acetylation in gene regulation and provides several testable hypotheses to dissect these roles.
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    Genome Wide Mapping of Foxo1 Binding-Sites in Murine T Lymphocytes
    (Elsevier Inc, 2014-08-01) Liao, Will; Ouyang, Weiming; Zhang, Michael Q.; Li, Ming O.; Zhang, Michael Q.
    The Forkhead box O (Foxo) family of transcription factors has a critical role in controlling the development, differentiation, and function of T cells. However, the direct target genes of Foxo transcription factors in T cells have not been well characterized. In this study, we focused on mapping the genome wide Foxo1-binding sites in naïve CD4(+) T cells, CD8(+) T cells, and Foxp3(+) regulatory T (Treg) cells. By using chromatin immunoprecipitation coupled with deep sequencing (ChIP-Seq), we identified Foxo1 binding sites that were shared among or specific to the three T cell populations. Here we describe the experiments, quality controls, as well as the deep sequencing data. Part of the data analysis has been published by Ouyang W et al. in Nature 20121] and Kim MV et al. in Immunity 20132], and the associated data set were uploaded to NCBI Gene Expression Omnibus.;
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    Hsa-miR-1246, Hsa-miR-320a and Hsa-miR-196b-5p Inhibitors can Reduce the Cytotoxicity of Ebola Virus Glycoprotein in Vitro
    (Science Press, 2014-09-12) Sheng, MiaoMiao; Ying, Zhong; Yang,Chen; Du, JianChao; Ju, XiangWu; Chen, Zhao; GuiGen, Zhang; LiFang,Zhang; Liu, KangTai; Yang, Ning; Xie, Peng; Li, DangSheng; Zhang, Michael Q.; Jiang, ChengYu; ATLAS Collaboration; 0000 0001 1707 1372 (Zhang, MQ); 99086074‏ (Zhang, MQ); Zhang, Michael Q.
    Ebola virus (EBOV) causes a highly lethal hemorrhagic fever syndrome in humans and has been associated with mortality rates of up to 91% in Zaire, the most lethal strain. Though the viral envelope glycoprotein (GP) mediates widespread inflammation and cellular damage, these changes have mainly focused on alterations at the protein level, the role of microRNAs (miRNAs) in the molecular pathogenesis underlying this lethal disease is not fully understood. Here, we report that the miRNAs hsa-miR-1246, hsa-miR-320a and hsa-miR-196b-5p were induced in human umbilical vein endothelial cells (HUVECs) following expression of EBOV GP. Among the proteins encoded by predicted targets of these miRNAs, the adhesion-related molecules tissue factor pathway inhibitor (TFPI), dystroglycan1 (DAG1) and the caspase 8 and FADD-like apoptosis regulator (CFLAR) were significantly downregulated in EBOV GP-expressing HUVECs. Moreover, inhibition of hsa-miR-1246, hsa-miR-320a and hsa-miR-196b-5p, or overexpression of TFPI, DAG1 and CFLAR rescued the cell viability that was induced by EBOV GP. Our results provide a novel molecular basis for EBOV pathogenesis and may contribute to the development of strategies to protect against future EBOV pandemics.
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    Activity-Dependent FUS Dysregulation Disrupts Synaptic Homeostasis
    (Natl Acad Sciences, 2014-10-16) Sephton, Chantelle F.; Tang, Amy A.; Kulkarni, Ashwinikumar; West, James; Brooks, Mieu; Stubblefield, Jeremy J.; Liu, Yun; Zhang, Michael Q.; Green, Carla B.; Huber, Kimberly M.; Huang, Eric J.; Herz, Joachim; Yu, Gang; 0000 0001 1707 1372 (Zhang, MQ); 99086074‏ (Zhang, MQ); Zhang, Michael Q.
    The RNA-binding protein fused-in-sarcoma (FUS) has been associated with amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD), two neurodegenerative disorders that share similar clinical and pathological features. Both missense mutations and overexpression of wild-type FUS protein can be pathogenic in human patients. To study the molecular and cellular basis by which FUS mutations and overexpression cause disease, we generated novel transgenic mice globally expressing low levels of human wild-type protein (FUSWT) and a pathological mutation (FUSR521G). FUSWT and FUSR521G mice that develop severe motor deficits also show neuroinflammation, denervated neuromuscular junctions, and premature death, phenocopying the human diseases. A portion of FUSR521G mice escape early lethality; these escapers have modest motor impairments and altered sociability, which correspond with a reduction of dendritic arbors and mature spines. Remarkably, only FUSR521G mice show dendritic defects; FUSWT mice do not. Activation of metabotropic glutamate receptors 1/5 in neocortical slices and isolated synaptoneurosomes increases endogenous mouse FUS and FUSWT protein levels but decreases the FUSR521G protein, providing a potential biochemical basis for the dendritic spine differences between FUSWT and FUSR521G mice.

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