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Modeling the causal regulatory network by integrating chromatin accessibility and transcriptome data

National Science Review 2016年第2期3卷 240-251页

作者： Yong Wang Rui Jiang wing hung wong Department of Statistics Department of Biomedical Data ScienceBio-X ProgramStanford University Academy of Mathematics and Systems Science National Center for Mathematics and Interdisciplinary SciencesChinese Academy of Sciences MOE Key Laboratory of Bioinformatics Bioinformatics Division and Center for Synthetic and Systems BiologyTNLISTDepartment of AutomationTsinghua University

Cell packs a lot of genetic and regulatory information through a structure known as chromatin,*** is wrapped around histone proteins and is tightly packed in a remarkable *** express a gene in a specific coding region,the chromatin would open up and DNA loop may be formed by interacting enhancers and ***,the mediator and cohesion complexes,sequence-specific transcription factors,and RNA polymerase Ⅱ are recruited and work together to elaborately regulate the expression *** is in pressing need to understand how the information,about when,where,and to what degree genes should be expressed,is embedded into chromatin structure and gene regulatory *** to large consortia such as Encyclopedia of DNA Elements(ENCODE) and Roadmap Epigenomic projects,extensive data on chromatin accessibility and transcript abundance are available across many tissues and cell *** rich data offer an exciting opportunity to model the causal regulatory ***,we will review the current experimental approaches,foundational data,computational problems,interpretive frameworks,and integrative models that will enable the accurate interpretation of regulatory ***,we will discuss the efforts to organize,analyze,model,and integrate the DNA accessibility data,transcriptional data,and functional genomic regions *** believe that these efforts will eventually help us understand the information flow within the cell and will influence research directions across many fields.

关键词： gene regulatory network open chromatin DNA accessibility transcription factor colocalization statistical model data integration

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DeepCAGE:Incorporating Transcription Factors in Genome-wide Prediction of Chromatin Accessibility

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Genomics, Proteomics & Bioinformatics 2022年第3期20卷 496-507页

作者： Qiao Liu Kui Hua Xuegong Zhang wing hung wong Rui Jiang Ministry of Education Key Laboratory of Bioinformatics Bioinformatics DivisionBeijing National Research Center for Information Science and TechnologyCenter for Synthetic and Systems BiologyDepartment of AutomationTsinghua UniversityBeijing 100084China Department of Statistics Stanford UniversityStanfordCA 94305USA

Although computational approaches have been complementing high-throughput biological experiments for the identification of functional regions in the human genome,it remains a great challenge to systematically decipher interactions between transcription factors(TFs)and regulatory elements to achieve interpretable annotations of chromatin accessibility across diverse cellular *** solve this problem,we propose DeepCAGE,a deep learning framework that integrates sequence information and binding statuses of TFs,for the accurate prediction of chromatin accessible regions at a genome-wide scale in a variety of cell *** takes advantage of a densely connected deep convolutional neural network architecture to automatically learn sequence signatures of known chromatin accessible regions and then incorporates such features with expression levels and binding activities of human core TFs to predict novel chromatin accessible *** a series of systematic comparisons with existing methods,DeepCAGE exhibits superior performance in not only the classification but also the regression of chromatin accessibility *** a detailed analysis of TF activities,DeepCAGE successfully extracts novel binding motifs and measures the contribution of a TF to the regulation with respect to a specific locus in a certain cell *** applied to whole-genome sequencing data analysis,our method successfully prioritizes putative deleterious variants underlying a human complex trait and thus provides insights into the understanding of disease-associated genetic *** can be downloaded from https://***/kimmo1019/DeepCAGE.

关键词： Chromatin accessibility Deep learning Transcription factor Gene expression

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Simultaneous inference of phenotype-associated genes and relevant tissues from GWAS data via Bayesian integration of multiple tissue-specific gene networks

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Journal of Molecular Cell Biology 2017年第6期9卷 436-452页

作者： Mengmeng Wu Zhixiang Lin Shining Ma Ting Chen Rui Jiang wing hung wong Department of Computer Science Tsinghua University Beijing 100084 China Ministry of Education Key Laboratory of Bioinformatics and Bioinformatics Division Tsinghua National Laboratory for Information Science and Technology Beijing 100084 China Department of Statistics Stanford University CA 94305 USA Department of Automation Tsinghua University Beijing 100084 China

Although genome-wide association studies （GWAS） have successfully identified thousands of genomic loci associated with hun- dreds of complex traits in the past decade, the debate about such problems as missing heritabiUty and weak interpretability has been appealing for effective computational methods to facilitate the advanced analysis of the vast volume of existing and antici- pated genetic data. Towards this goal, gene-tevel integrative GWAS analysis with the assumption that genes associated with a phenotype tend to be enriched in biological gene sets or gene networks has recently attracted much attention, due to such advan- tages as straightforward interpretation, tess multiple testing burdens, and robustness across studies. However, existing methods in this category usually exploit non-tissue-specific gene networks and thus lack the ability to utilize informative tissue-specific characteristics. To overcome this limitation, we proposed a Bayesian approach called SIGNET （Simultaneously Inference of GeNEs and Tissues） to integrate GWAS data and multiple tissue-specific gene networks for the simultaneous inference of phenotype- associated genes and relevant tissues. Through extensive simulation studies, we showed the effectiveness of our method in find- ing both associated genes and relevant tissues for a phenotype. In applications to real GWAS data of 14 complex phenotypes, we demonstrated the power of our method in both deciphering genetic basis and discovering biological insights of a phenotype. With this understanding, we expect to see SIGNET as a valuable tool for integrative GWAS analysis, thereby boosting the preven- tion, diagnosis, and treatment of human inherited diseases and eventually facilitating precision medicine.

关键词： GWAS tissue-specific gene networks Markov random field

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Modeling stochastic noise in gene regulatory systems

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Frontiers of Electrical and Electronic Engineering in China 2014年第1期9卷 1-29页

作者： Arwen Meister Chao Du Ye Henry Li wing hung wong Computational Biology Lab Bio-X Program Stanford University Stanford CA 94305 USA

The Master equation is considered the gold standard for modeling the stochastic mechanisms of gene regulation in molecular detail, but it is too complex to solve exactly in most cases, so approximation and simulation methods are essential. However, there is still a lack of consensus about the best way to carry these out. To help clarify the situation, we review Master equation models of gene regulation, theoretical approximations based on an expansion method due to N.G. van Kampen and R. Kubo, and simulation algorithms due to D.T. Gillespie and P. Langevin. Expansion of the Master equation shows that for systems with a single stable steady-state, the stochastic model reduces to a deterministic model in a first-order approximation. Additional theory, also due to van Kampen, describes the asymptotic behavior of multistable systems. To support and illustrate the theory and provide further insight into the complex behavior of multistable systems, we perform a detailed simulation study comparing the various approximation and simulation methods applied to synthetic gene regulatory systems with various qualitative characteristics. The simulation studies show that for large stochastic systems with a single steady-state, deterministic models are quite accurate, since the probability distribution of the solution has a single peak tracking the deterministic trajectory whose variance is inversely proportional to the system size. In multistable stochastic systems, large fluctuations can cause individual trajectories to escape from the domain of attraction of one steady-state and be attracted to another, so the system eventually reaches a multimodal probability distribution in which all stable steady- states are represented proportional to their relative stability. However, since the escape time scales exponentially with system size, this process can take a very long time in large systems.

关键词： gene regulation stochastic modeling simulation Master equation Gillespie algorithm Langevin equation

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CNEReg Interprets Ruminant-specific Conserved Non-coding Elements by Developmental Gene Regulatory Network

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Genomics, Proteomics & Bioinformatics 2023年第3期21卷 632-648页

作者： Xiangyu Pan Zhaoxia Ma Xinqi Sun Hui Li Tingting Zhang Chen Zhao Nini Wang Rasmus Heller wing hung wong Wen Wang Yu Jiang Yong Wang Key Laboratory of Animal Genetics Breeding and Reproduction of Shaanxi ProvinceCollege of Animal Science and TechnologyNorthwest A&F UniversityYangling 712100China Department of Medical Research Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China Guangdong Cardiovascular Institute Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China School of Mathematics University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources College of Animal Science and TechnologyGuangxi UniversityNanning 530005China Section for Computational and RNA Biology Department of BiologyUniversity of CopenhagenCopenhagen DK-2100Denmark Department of Statistics Department of Biomedical Data ScienceBio-X ProgramStanford UniversityStanfordCA 94305USA Center for Ecological and Environmental Sciences Northwestern Polytechnical UniversityXi’an 710072China State Key Laboratory of Genetic Resources and Evolution Kunming Institute of ZoologyChinese Academy of SciencesKunming 650223China Center for Excellence in Animal Evolution and Genetics Chinese Academy of SciencesKunming 650223China Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China

The genetic information coded in DNA leads to trait innovation via a gene regulatory network(GRN)in ***,we developed a conserved non-coding element interpretation method to integrate multi-omics data into gene regulatory network(CNEReg)to investigate the ruminant multi-chambered stomach *** generated paired expression and chromatin accessibility data during rumen and esophagus development in sheep,and revealed 1601 active ruminantspecific conserved non-coding elements(active-RSCNEs).To interpret the function of these activeRSCNEs,we defined toolkit transcription factors(TTFs)and modeled their regulation on rumenspecific genes via batteries of active-RSCNEs during *** developmental GRN revealed 18 TTFs and 313 active-RSCNEs regulating 7 rumen functional ***,6 TTFs(OTX1,SOX21,HOXC8,SOX2,TP63,and PPARG),as well as 16 active-RSCNEs,functionally distinguished the rumen from the *** study provides a systematic approach to understanding how gene regulation evolves and shapes complex traits by putting evo-devo concepts into practice with developmental multi-omics data.

关键词： Trait innovation Gene regulatory network Conserved non-coding element Toolkit transcription factor Ruminant

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Effects of length alteration of OPE-containing mono- and dinuclear alkynylplatinum(II) terpyridine complexes on photophysical, structural and morphological properties

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Nano Research 2024年第10期17卷 8893-8903页

作者： Jason Koon-Lam Poon Sammual Yu-Lut Leung Eric Ka-Ho wong Vivian wing-Wah Yam Institute of Molecular Functional Materials State Key Laboratory of Synthetic Chemistry and Department of ChemistryThe University of Hong KongHong Kong 999077China

A series of mononuclear complexes and unsymmetric dinuclear alkynylplatinum(II)terpyridine complexes with oligo(paraphenylene ethynylene)(OPE)-derived backbone with a variation of the lengths of alkoxy chains and OPE backbones was *** morphological properties,packing lattice and gelation behaviors of the mononuclear complexes were systematically studied,and the thermodynamic parameters and packing lattices of the dinuclear complexes were also investigated,providing further insights into the roles of the non-covalent interactions and their delicate balance in constructing sophisticated supramolecular *** and nanotube formation have been observed upon a delicate control of the intermolecular interactions by altering the lengths and structural dimensions of the complexes.

关键词： supramolecular chemistry self-assembled nanostructures platinum(II)complexes metallogel

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An Overview of Chemical Constituents, Medicinal Properties, Clinical Trials, and Patents of Twigs of Morus alba(Ramulus Mori)

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World Journal of Traditional Chinese Medicine 2024年第2期10卷 149-158页

作者： Eric Wei Chiang Chan hung Tuck Chan Siu Kuin wong Department of Food Science and Nutrition Faculty of Applied SciencesUCSI UniversityCherasKuala LumpurMalaysia Secretariat of International Society for Mangrove Ecosystems Faculty of AgricultureUniversity of the RyukyusOkinawaJapan School of Foundation Studies Xiamen University MalaysiaSepangSelangorMalaysia

The rich chemical constituents and diverse pharmacological properties of Ramulus Mori(RM) or the twig of Morus alba with evidence supported by clinical trials and patents are reviewed. Known as Sangzhi in Chinese, RM is widely used in traditional Chinese medicine to treat gout, arthritis, and rheumatism. Chemical constituents include flavonoids, benzofurans, alkaloids, stilbenes, chalcones, phenolic acids, and coumarins. Bioactivities of RM include antidiabetic, anti-obesity, anti-inflammatory, antityrosinase, neuroprotective, antioxidant, hepatoprotective, cytoprotective, renoprotective, antihyperuricemic, analgesic, antifungal, DNA protective, anticancer, gastroprotective, cardioprotective, anti-hair aging, anti-arthritic, and antiplatelet aggregation properties. The most active compounds from RM are mulberrin, oxyresveratrol, and mulberroside A. All four clinical trials on RM are focused on the treatment of diabetes. The patents entail using RM extracts as cosmetics for skin whitening and as agents for hypoglycemia. Topics for further research on RM are suggested.

关键词： Clinical trials mulberrin mulberroside A oxyresveratrol patents Sangzhi

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Chemical biology investigation of a triple-action,smart-decomposition antimicrobial booster based-combination therapy against“ESKAPE”pathogens

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Science China Chemistry 2024年第9期67卷 3071-3082页

作者： Min Wang Huangsheng Pu Yangfan Xu Chenxuan Wu Yuanxin Gu Qingyun Cai Guoxing Yin Peng Yin Chunhui Zhang wing-Leung wong Muyang Wan Yugang Bai Xinxin Feng State Key Laboratory of Chem-/Bio-Sensing and Chemometrics Hunan Provincial Key Laboratory of Biomacromolecular Chemical Biologyand School of Chemistry and Chemical EngineeringHunan UniversityChangsha 410082China College of Biology Hunan UniversityChangsha 410082China College of Advanced Interdisciplinary Studies&Hunan Provincial Key Laboratory of Novel Nano Optoelectronic Information Materials and Devices National University of Defense TechnologyChangsha 410073China Nanhu Laser Laboratory National University of Defense TechnologyChangsha 410073China Key Laboratory of Chemical Biology and Traditional Chinese Medicine Research(Ministry of Education) College of Chemistry and Chemical EngineeringHunan Normal UniversityChangsha 410081China State Key Laboratory of Chemical Biology and Drug Discovery Department of Applied Biology and Chemical TechnologyThe Hong Kong Polytechnic UniversityHong Kong SAR 999077China Hunan Provincial Key Laboratory of Anti-Resistance Microbial Drugs The Third Hospital of Changsha(The Affiliated Changsha Hospital of Hunan University)Changsha 410015China

The global antibiotic resistance crisis necessitates urgent *** innovative approach involves potentiating antibiotics and non-antibiotic drugs with adjuvants or boosters.A major drawback of these membrane-active boosters is their limited biocompatibility,as they struggle to differentiate between prokaryotic and eukaryotic *** study reports the chemical biology investigation of a dual-action oligoamidine(OA1)booster with a glutathione-triggered decomposition ***1,when combined with other antimicrobial molecules,exhibits a triple-targeting mechanism including cell membrane disruption,DNA targeting,and intracellular enzyme *** multi-targeting mechanism not only enhances the in vitro and in vivo eradication of antibiotic-resistant“ESKAPE”pathogens,but also suppresses the development of bacterial ***,OA1 maintains its activity in bacterial cells by creating an oxidative environment,while it quickly decomposes in mammalian cells due to high glutathione *** mechanistic insights and design principles may provide a feasible approach to develop novel antimicrobial agents and effective anti-resistance combination therapies.

关键词： antimicrobial booster oligoamidine membrane disruption DNA targeting triggered degradation anti-resistance

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Solitary extraovarian primary peritoneal carcinoma with direct invasion into the liver,diaphragm and lung without peritoneal dissemination or distant metastasis

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Hepatobiliary & Pancreatic Diseases International 2024年第3期23卷 322-325页

作者： Billy Ho hung Cheung wong Hoi She Siu Lun Ho Albert Chi Yan Chan Chung Mau Lo Tan To Cheung Department of Surgery The University of Hong KongHong KongChina Department of Pathology The University of Hong KongHong KongChina

To the Editor:Extraovarian primary peritoneal carcinoma(EOPPC)is an uncommon malignancy with many similarities to epithelial ovarian carcinoma in histological,clinical,and etiological aspects[1].This phenomenon is explained by their common embryonal origin,in which both develop from the coelomic epithelium in the early embryological *** their similarities,the incidence of EOPPC is significantly lower than that of epithelial ovarian carcinoma(6.78 cases per million vs.120.5 cases per million)[1].

关键词： peritoneal invasion metastasis

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IgG4 Coronary Arteritis Presenting as a Cardiac Pseudo-Tumour

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Case Reports in Clinical Medicine 2024年第9期13卷 345-352页

作者： Elaine Mo-Chee Chau Catherine Yuet-hung wong Raymond Hin-Suen Liang Cardiology Centre Hong Kong Sanatorium & Hospital Hong Kong SAR China Nuclear Medicine Department Hong Kong Sanatorium & Hospital Hong Kong SAR China Comprehensive Oncology Centre Hong Kong Sanatorium & Hospital Hong Kong SAR China

We report on an unusual case presenting with a cardiac pseudo-tumour on echocardiogram, which corresponded to a large soft tissue mural thickening around the mid-right coronary artery. There were similar but not as thick mural lesions around other parts of the coronary arteries. The so-called “pigs-in-a-blanket” sign on computed tomography (CT) scan was pathognomonic of IgG4 coronary arteritis. The IgG4 level was grossly elevated at more than 10 times the upper limit of normal. Positron emission tomography (PET)-CT scans with 18F-fluoro-deoxy-glucose (FDG) and 68Ga-Fibroblast Activation Protein Inhibitor (FAPI) were performed to assess the extent of organ involvement of the IgG4-related disease. The patient was treated with 8 injections of rituximab with good serological response. However, the coronary arteritis findings on CT scan remained unchanged.

关键词： IgG4-Related Disease Coronary Arteritis Cardiac Pseudo-Tumour “Pigs-in-a-Blanket” Sign

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