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The phase separation of SGS3 regulates antiviral immunity and fertility in Arabidopsis

Science China(Life Sciences) 2023年第8期66卷 1938-1941页

作者： Yujie Han Xiaolin Zhang Ran Du Xiaoyi Shan Daoxin Xie MOE Laboratory of Bioinformatics Tsinghua-Peking Center for Life SciencesSchool of Life SciencesTsinghua UniversityBeijing 100084China Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program School of Life SciencesTsinghua UniversityBeijing 100084China Shenzhen Branch of Guangdong Laboratory for Lingnan Modern Agriculture Genome Analysis Laboratory of the Ministry of AgricultureAgricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhen 518124China

Dear Editor,As a conserved mechanism among eukaryotic organisms,RNA silencing is vital for suppressing gene expression at the transcriptional or posttranscriptional level to regulate multiple biological *** interfering RNAs(si RNAs)generated by Dicer proteins integrate with Argonaute(AGO)to form an RNA-induced silencing complex(RISC),in which RNA/DNA could be degraded/methylated through a sequence-specific manner(Ding et al.,2004).

关键词： immunity separation

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HCCDB v2.0:Decompose Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC

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Genomics, Proteomics & bioinformatics 2024年第1期22卷 131-142页

作者： Ziming Jiang Yanhong Wu Yuxin Miao Kaige Deng Fan Yang Shuhuan Xu Yupeng Wang Renke You Lei Zhang Yuhan Fan Wenbo Guo Qiuyu Lian Lei Chen Xuegong Zhang Yongchang Zheng Jin Gu Eight-Year Program of Clinical Medicine Peking Union Medical College HospitalChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100006China MOE Key Laboratory of Bioinformatics BNRIST Bioinformatics DivisionInstitute for Precision Medicine&Department of AutomationTsinghua UniversityBeijing 100084China Department of Liver Surgery Peking Union Medical College HospitalChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China Fuzhou Institute for Data Technology Fuzhou 350207China University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong UniversityShanghai 200240China Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China International Cooperation Laboratory on Signal Transduction Eastern Hepatobiliary Surgery InstituteSecond Military Medical UniversityShanghai 200438China National Center for Liver Cancer Shanghai 201805China

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma(HCC).Integrated 15 transcriptomic datasets of HCC clinical samples,the first version of HCC database(HCCDB v1.0)was released in *** the meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets,it provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and *** four years having passed,the database now needs integration of recently published ***,the latest single-cell and spatial transcriptomics have provided a great opportunity to decipher complex gene expression variations at the cellular level with spatial ***,we present HCCDB v2.0,an updated version that combines bulk,single-cell,and spatial transcriptomic data of HCC clinical *** dramatically expands the bulk sample size by adding 1656 new samples from 11 datasets to the existing 3917 samples,thereby enhancing the reliability of transcriptomic meta-analysis.A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections,respectively.A novel single-cell level and 2-dimension(sc-2D)metric is proposed as well to summarize cell type-specific and dysregulated gene expression *** are all graphically visualized in our online portal,allowing users to easily retrieve data through a user-friendly interface and navigate between different *** extensive clinical phenotypes and transcriptomic data in the database,we show two applications for identifying prognosis-associated cells and tumor *** v2.0 is available at http://***/database/hccdb2.

关键词： Hepatocellular carcinoma Database Integrative analysis Single-cell RNA sequencing Spatial transcriptomics

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Jasmonate perception: Ligand-receptor interaction, regulation, and evolution

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Molecular Plant 2023年第1期16卷 23-42页

作者： Shuai Hu Kaiming Yu Jianbin Yan Xiaoyi Shan Daoxin Xie MOE Laboratory of Bioinformatics Tsinghua-Peking Center for Life SciencesSchool of Life SciencesTsinghua UniversityBeijing 100084China Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program School of Life SciencesTsinghua UniversityBeijing 100084China Shenzhen Branch Guangdong Laboratory of Lingnan Modern AgricultureKey Laboratory of Synthetic BiologyMinistry of Agriculture and Rural AffairsAgricultural Genomics Institute at ShenzhenChinese Academy of Agricultural SciencesShenzhen 518124China Kunpeng Institute of Modern Agriculture at Foshan Chinese Academy of Agricultural SciencesFoshan 528200China

Phytohormones integrate external environmental and developmental signals with internal cellular responses for plant survival and multiplication in changing ***(JA),which might originate from prokaryotes and benefit plant terrestrial adaptation,is a vital phytohormone that regulates diverse developmental processes and defense responses against various environmental *** this review,we first provide an overview of ligand-receptor binding techniques used for the characterization of phytohormone-receptor interactions,then introduce the identification of the receptor COI1 and active JA molecules,and finally summarize recent advances on the regulation of JA perception and its evolution.

关键词： jasmonate COI1 hormone perception ligand-receptor interaction ligand-receptor binding techniques evolution

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Lateral transfer of mRNA and protein by migrasomes modifies the recipient cells

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细胞研究（英文版） 2021年第2期31卷 237-240页

作者： Mingli Zhu Qin Zou Rongyao Huang Ying Li Xudong Xing Jianhuo Fang Liang Ma Lifei Li Xuerui Yang Li Yu State Key Laboratory of Membrane Biology Tsinghua University-Peking University Joint Center for Life Sciences Beijing Frontier Research Center for Biological Structure School of Life ScienceTsinghua University Beijing 100084 China Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Science Tsinghua University Beijing 100084 China Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Science Tsinghua University Beijing 100084 China MOE Key Laboratory of Bioinformatics Tsinghua University Center for Synthetic & Systems Biology Tsinghua University School of Life Science Beijing 100084China State Key Laboratory of Membrane Biology Tsinghua University-Peking University Joint Center for Life Sciences Beijing Frontier Research Center for Biological Structure School of Life ScienceTsinghua University Beijing 100084 China MOE Key Laboratory of Bioinformatics Tsinghua University Center for Synthetic & Systems Biology Tsinghua University School of Life Science Beijing 100084China

Dear Editor,Migrasomes are recently discovered vesicular organelles which form on the retraction fibers(RFs)of migrating cells.1 Once detached from cells,migrasomes can rupture and release their luminal contents1 in a process named ***,migrasomes have been shown to play an important role in zebrafish organ morphogenesis by releasing chemokine signals to defined regions of the embryo.2 Thus,migracytosis is considered as a major mechanism for migrasomes to carry out their *** has been frequently observed that intact migrasomes can be engulfed by surrounding cells,1 and this has been proposed as a potential mechanism for lateral transfer of cellular contents between ***,it is not clear whether the lateral transfer of cellular contents by migrasomes has functional consequences for the recipient cells.

关键词： Extracellular signalling molecules Organelles

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Mutual dependency between lncRNA LETN and protein NPM1 in controlling the nucleolar structure and functions sustaining cell proliferation

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细胞研究（英文版） 2021年第6期31卷 664-683页

作者： Xianteng Wang Xiaolin Hu Wanlu Song Hui Xu Zhengtao Xiao Rongyao Huang Qingran Bai Fan Zhang Yongzhen Chen Yu Liu Jianhuo Fang Xin Li Qin Shen Haitao Zhao Xuerui Yang MOE Key Laboratory of Bioinformatics Tsinghua UniversityBeijing 100084China Center for Synthetic & Systems Biology Tsinghua UniversityBeijing 100084China School of Life Sciences Tsinghua UniversityBeijing 100084China MOE Key Laboratory of Bioinformatics Tsinghua UniversityBeijing 100084China Center for Synthetic & Systems Biology Tsinghua UniversityBeijing 100084China School of Life Sciences Tsinghua UniversityBeijing 100084China Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Science Beijing 100084China Brain and Spinal Cord Innovative Research Center of Tongji Hospital School of Life Sciences and TechnologyTongji University and Frontier Science Research Center for Stem Cells of Ministry of EducationShanghai 200092China Department of Liver Surgery Peking Union Medical College HospitalChinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC)Beijing 100730China

Fundamental processes such as ribosomal RNA synthesis and chromatin remodeling take place in the nucleolus,which is hyperactive in fast-proliferating *** sophisticated regulatory mechanism underlying the dynamic nucleolar structure and functions is yet to be fully *** present study uncovers the mutual functional dependency between a previously uncharacterized human long non-coding RNA,which we renamed LETN,and a key nucleolar protein,***,being upregulated in multiple types of cancer,LETN resides in the nucleolus via direct binding with *** plays a critical role in facilitating the formation of NPM1 pentamers,which are essential building blocks of the nucleolar granular component and control the nucleolar *** of LETN or NPM1 led to similar and profound changes of the nucleolar morphology and arrest of the nucleolar functions,which led to proliferation inhibition of human cancer cells and neural progenitor ***,this inter-dependency between LETN and NPM1 is associated with the evolutionarily new variations of NPM1 and the coincidental emergence of LETN in higher *** propose that this human-specific protein-lncRNA axis renders an additional yet critical layer of regulation with high physiological relevance in both cancerous and normal developmental processes that require hyperactive nucleoli.

关键词： Cell division Long non-coding RNAs

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Development of a respiratory sound labeling software for training a deep learning-based respiratory sound analysis model

Development of a respiratory sound labeling software for tra...

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International Forum on Medical Imaging in Asia 2021, IFMIA 2021

作者： Hsu, Fu-Shun Huang, Chao-Jung Kuo, Chen-Yi Huang, Shang-Ran Cheng, Yuan-Ren Wang, Jia-Horng Wu, Yi-Lin Tzeng, Tzu-Ling Lai, Feipei Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Heroic Faith Medical Science Corporation Limited New Taipei Taiwan National Taiwan University-Stanford Joint Program Office of AI in Biotechnology Ministry of Science and Technology Joint Research Center for Artificial Intelligence Technology and All Vista Healthcare Taipei Taiwan Department of Life Science College of Life Science National Taiwan University Taipei Taiwan Institute of Biomedical Sciences Academia Sinica Taipei Taiwan Department of Critical Care Far Eastern Memorial Hospital New Taipei City Taiwan

ISBN: (数字)9781510644212

ISBN: (纸本)9781510644205

Respiratory auscultation can help healthcare professionals detect abnormal respiratory conditions if adventitious lung sounds are heard. The state-of-the-art artificial intelligence technologies based on deep learning show great potential in the development of automated respiratory sound analysis. To train a deep learning-based model, a huge number of accurate labels of normal breath sounds and adventitious sounds are needed. In this paper, we demonstrate the work of developing a respiratory sound labeling software to help annotators identify and label the inhalation, exhalation, and adventitious respiratory sound more accurately and quickly. Our labeling software integrates six features from MATLAB Audio Labeler, and one commercial audio editor, RX7. As of October, 2019, we have labeled 9,765 15- second-long audio files of breathing lung sounds, and accrued 34,095 inhalation labels,18,349 exhalation labels, 13,883 continuous adventitious sounds (CASs) labels and 15,606 discontinuous adventitious sounds (DASs) labels, which are significantly larger than previously published studies. The trained convolutional recurrent neural networks based on these labels showed good performance with F1-scores of 86.0% on inhalation event detection, 51.6% on CASs event detection and 71.4% on DASs event detection. In conclusion, our results show that our proposed respiratory sound labeling software could easily pre-define a label, perform one-click labeling, and overall facilitate the process of accurately labeling. This software helps develop deep learning-based models that require a huge amount of labeled acoustic data. © 2021 SPIE.

关键词： Recurrent neural networks

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Uncovering chromatin accessibility and cancer diagnostic potential via cell-free DNA utilization

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Science Bulletin 2024年第19期69卷 2987-2992页

作者： Jie Li Jiahui Chen Xin Sun Heli Yang Keyong Sun Chang Liu Yongwang Wang Mengyue Xu Xin Ji Ji Zhang Xiaojiang Wu Anqiang Wang Biao Fan Xiaolu Zhang Yue Wu Peilin Cui Junya Peng Yupei Zhao Wenming Wu Honghao Yu Zhaode Bu Jiafu Ji Xun Lan Department of Basic Medical Sciences School of MedicineTsinghua UniversityBeijing 100084China Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing) Center of Gastrointestinal CancerPeking University Cancer Hospital&InstituteBeijing 100142China Guangxi Key Laboratory of Drug Discovery and Optimization Guilin Medical UniversityGuilin 541001China Department of General Surgery Peking Union Medical College HospitalPeking Union Medical CollegeBeijing 100730China Department of Internal Medicine International Medical Services(IMS)Beijing Tiantan Hospital of Capital Medical UniversityBeijing 100070China Institute of Clinical Medicine Peking Union Medical College HospitalChinese Academy of Medical Science and Peking Union Medical CollegeBeijing 100730China Academy of Biomedical Engineering Kunming Medical UniversityKunming 650500China MOE Key Laboratory of Bioinformatics Tsinghua UniversityBeijing 100084China Peking-Tsinghua-NIBS Joint Graduate Program Tsinghua UniversityBeijing 100084China Tsinghua-Peking Joint Center for Life Sciences Tsinghua UniversityBeijing 100084China Department of Anesthesiology Affiliated Hospital of Guilin Medical UniversityGuilin 541000China Key Laboratory of Medical Biotechnology and Translational Medicine Guilin Medical UniversityGuilin 541001China State Key Laboratory of Complex Severe and Rare Diseases Peking Union Medical College HospitalChinese Academy of Medical Science and Peking Union Medical CollegeBeijing 100730China Department of Gastric Surgery Zhejiang Cancer HospitalHangzhou Institute of Medicine(HIM)Chinese Academy of SciencesHangzhou 310022China The Islands Healthcare Complex-Macao Medical Center of Peking Union Medical College Hospital Macao 999078China

Gene expression patterns of tumor cells can be inferred from features of circulating cell-free DNA(cfDNA),such as histone modifications and fragmentation patterns at ***,the direct relationship between cfDNA patterns and tumor-specific chromatin accessibility has not yet been experimentally established,limiting its current application to cancer diagnosis alone.

关键词： diagnosis cancer alone

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Development of a respiratory sound labeling software for training a deep learning-based respiratory sound analysis model

arXiv

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arXiv 2021年

作者： Hsu, Fu-Shun Huang, Chao-Jung Kuo, Chen-Yi Huang, Shang-Ran Cheng, Yuan-Ren Wang, Jia-Horng Wu, Yi-Lin Huang, Chien-Wen Tzeng, Tzu-Ling Lai, Feipei Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Heroic Faith Medical Science Corporation Limited New Taipei Taiwan National Taiwan University Stanford Joint Program Office of AI in Biotechnology Ministry of Science and Technology Joint Research Center for Artificial Intelligence Technology All Vista Healthcare Taipei Taiwan Department of Life Science College of Life Science National Taiwan University Taipei Taiwan Institute of Biomedical Sciences Academia Sinica Taipei Taiwan Department of Critical Care Far Eastern Memorial Hospital New Taipei City Taiwan

Respiratory auscultation can help healthcare professionals detect abnormal respiratory conditions if adventitious lung sounds are heard. The state-of-the-art artificial intelligence technologies based on deep learning show great potential in the development of automated respiratory sound analysis. To train a deep learning-based model, a huge number of accurate labels of normal breath sounds and adventitious sounds are needed. In this paper, we demonstrate the work of developing a respiratory sound labeling software to help annotators identify and label the inhalation, exhalation, and adventitious respiratory sound more accurately and quickly. Our labeling software integrates six features from MATLAB Audio Labeler, and one commercial audio editor, RX7. As of October, 2019, we have labeled 9,765 15-second-long audio files of breathing lung sounds, and accrued 34,095 inhalation labels,18,349 exhalation labels, 13,883 continuous adventitious sounds (CASs) labels and 15,606 discontinuous adventitious sounds (DASs) labels, which are significantly larger than previously published studies. The trained convolutional recurrent neural networks based on these labels showed good performance with F1-scores of 86.0% on inhalation event detection, 51.6% on CASs event detection and 71.4% on DASs event detection. In conclusion, our results show that our proposed respiratory sound labeling software could easily pre-define a label, perform one-click labeling, and overall facilitate the process of accurately labeling. This software helps develop deep learning-based models that require a huge amount of labeled acoustic data. Copyright © 2021, The Authors. All rights reserved.

关键词： Software design

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IDH1 fine-tunes cap-dependent translation initiation

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Journal of Molecular Cell Biology 2019年第10期11卷 816-828页

作者： Lichao Liu JYuyang Lu Fajin Li Xudong Xing Tong Li Xuerui Yang Xiaohua Shen Tsinghua-Peking Center for Life Sciences School of Medicine and School of Life SciencesTsinghua UniversityBeijing 100084China MOE Key Laboratory of Bioinformatics Center for Synthetic Systems BiologySchool of Life SciencesTsinghua UniversityBeijing 100084China Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program School of Life SciencesTsinghua UniversityBeijing 100084China

The metabolic enzyme isocitrate dehydrogenase 1(IDH1)catalyzes the oxidative decarboxylation of isocitrate to a-ketoglutarate(a-KG).Its mutation often leads to aberrant gene expression in ***1 was reported to bind thousands of RNA transcripts in a sequence-dependent manner;yet,the functional significance of this RNA-binding activity remains ***,we report that IDH1 promotes mRNA translation via direct associations with polysome mRNA and translation *** proteomic analysis in embryonic stem cells(ESCs)revealed strikingenrichmentof ribosomal proteins and translation regulators in IDH1-bound protein *** performed ribosomal profiling and analyzed mRNA transcripts that are associated with actively translating ***,knockout of IDH1 in ESCs led to significant downregulation of polysome-bound mRNA in IDH1 targets and subtle upregulation of ribosome densities at the start codon,indicating inefficient translation initiation upon loss of *** IDH1 to a luciferase mRNA via the MS2-MBP system promotes luciferase translation,independently of the catalytic activity of ***,IDH1 fails to enhance luciferase translation driven by an internal ribosome entry ***,these results reveal an unforeseen role of IDH1 in fine-tuning cap-dependent translation via the initiation step.

关键词： IDH1 proteomic interactome translation regulation RNA-binding protein

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Biomedical data and AI

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Science China Life Sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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