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NeoHunter:Flexible software for systematically detecting neoantigens from sequencing data

Quantitative Biology 2024年第1期12卷 70-84页

作者： Tianxing Ma Zetong Zhao Haochen Li Lei Wei Xuegong Zhang MOE Key Lab of Bioinformatics Bioinformatics Division of BNRIST and Department of AutomationTsinghua UniversityBeijingChina School of Medicine Tsinghua UniversityBeijingChina School of Life Sciences Tsinghua UniversityBeijingChina

Complicated molecular alterations in tumors generate various mutant *** of these mutant peptides can be presented to the cell surface and then elicit immune responses,and such mutant peptides are called *** detection of neoantigens could help to design personalized cancer *** some computational frameworks for neoantigen detection have been proposed,most of them can only detect SNV-and indel-derived *** addition,current frameworks adopt oversimplified neoantigen prioritization *** factors hinder the comprehensive and effective detection of *** developed NeoHunter,flexible software to systematically detect and prioritize neoantigens from sequencing data in different *** can detect not only SNV-and indel-derived neoantigens but also gene fusion-and aberrant splicing-derived *** supports both direct and indirect immunogenicity evaluation strategies to prioritize candidate *** strategies utilize binding characteristics,existing biological big data,and T-cell receptor specificity to ensure accurate detection and *** applied NeoHunter to the TESLA dataset,cohorts of melanoma and non-small cell lung cancer *** achieved high performance across the TESLA cancer patients and detected 79%(27 out of 34)of validated neoantigens in ***-and indel-derived neoantigens accounted for 90%of the top 100 candidate neoantigens while neoantigens from aberrant splicing accounted for 9%.Gene fusion-derived neoantigens were detected in one *** is a powerful tool to‘catch all’neoantigens and is available for free academic use on Github(Xuegonglab/NeoHunter).

关键词： cancer vaccine molecular alteration neoantigen neoantigen prioritization

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Toward a unified information framework for cell atlas assembly

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National Science Review 2022年第3期9卷 7-10页

作者： Sijie Chen Yanting Luo Haoxiang Gao Fanhong Li Jiaqi Li Yixin Chen Renke You Hairong Lv Kui Hua Rui Jiang Xuegong Zhang Bioinformatics Division of BNRIST and Department of Automation MOE Key Lab of BioinformaticsTsinghua University Fuzhou Institute of Data Technology School of Medicine Tsinghua University School of Life Sciences Center for Synthetic and Systems Biology Tsinghua University

Cells are the basic structural and functional unit of the human body. Virtually all cells of a human body possess the same genome, but they exhibit colorful heterogeneities in phenotypes and *** heterogeneities includ...

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Building digital life systems for future biology and medicine

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Quantitative Biology 2023年第3期11卷 207-213页

作者： Xuegong Zhang Lei Wei Rui Jiang Xiaowo Wang Jin Gu Zhen Xie Hairong Lv MOE Key Lab of Bioinformatics and Bioinformatics Division of BNRIST Department of AutomationTsinghua UniversityBeijing 100084China Center of Synthetic and Systems Biology Tsinghua UniversityBeijing 100084China School of Life Sciences and School of Medicine Tsinghua UniversityBeijing 100084China

The rapid development of biological technology (BT) and information technology (IT) especially of genomics and artificial intelligence (AI) is bringing great potential for revolutionizing future medicine. We propose the concept and framework of Digital Life Systems or dLife as a new paradigm to unleash this potential. It includes the multi-scale and multi-granule measure and representation of life in the digital space, the mathematical and/or computational modeling of the biology behind physiological and pathological processes, and ultimately cyber twins of healthy or diseased human body in the virtual space that can be used to simulate complex biological processes and deduce effects of medical treatments. We advocate that dLife is the route toward future AI precision medicine and should be the new paradigm for future biological and medical research.

关键词： digital life systems digital twin aritificial intelligence precision medicine

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SpaGRA:Graph augmentation facilitates domain identification for spatially resolved transcriptomics

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Journal of Genetics and Genomics 2025年第1期52卷 93-104页

作者： Xue Sun Wei Zhang Wenrui Li Na Yu Daoliang Zhang Qi Zou Qiongye Dong Xianglin Zhang Zhiping Liu Zhiyuan Yuan Rui Gao Center of Intelligent Medicine School of Control Science and EngineeringShandong UniversityJinanShandong 250061China MOE Key Lab of Bioinformatics and Bioinformatics Division of BNRIST Department of AutomationTsinghua UniversityBeijing 100084China Institute of Precision Medicine Peking University Shenzhen HospitalShenzhenGuangdong 518036China Department of Clinical Laboratory The Second HospitalCheeloo College of MedicineShandong UniversityJinanShandong 250033China Institute of Science and Technology for Brain-Inspired Intelligence Center for Medical Research and InnovationShanghai Pudong HospitalFudan University Pudong Medical CenterFudan UniversityShanghai 200433China

Recent advances in spatially resolved transcriptomics(SRT)have provided new opportunities for characterizing spatial structures of various ***-based geometric deep learning has gained widespread adoption for spatial domain identification ***,most methods define adjacency relation between cells or spots by their spatial distance in SRT data,which overlooks key biological interactions like gene expression similarities,and leads to inaccuracies in spatial domain *** tackle this challenge,we propose a novel method,SpaGRA(https://***/sunxue-yy/SpaGRA),for automatic multi-relationship construction based on graph *** uses spatial distance as prior knowledge and dynamically adjusts edge weights with multi-head graph attention networks(GATs).This helps SpaGRA to uncover diverse node relationships and enhance message passing in geometric contrastive ***,SpaGRA uses these multi-view relationships to construct negative samples,addressing sampling bias posed by random *** results show that SpaGRA presents superior domain identification performance on multiple datasets generated from different *** SpaGRA,we analyze the functional regions in the mouse hypothalamus,identify key genes related to heart development in mouse embryos,and observe cancer-associated fibroblasts enveloping cancer cells in the latest Visium HD ***,SpaGRA can effectively characterize spatial structures across diverse SRT datasets.

关键词： Spatial domain identification Spatially resolved transcriptomics Multi-head graph attention networks Graph augmentation Geometric contrastive learning

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Featured articles dedicated to the 20th anniversary of the human genome

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Quantitative Biology 2021年第1期9卷 1-3页

作者： Xuegong Zhang MOE Key Lab of Bioinformatics and Bioinformatics Division BNRISTDepartment of AutomationTsinghua UniversityBeijing 100084China

The year 2021 is the 20th anniversary of the publication of the draft human genome[1,2].The sequencing of the human genome has brought life sciences into a new era,the era to understand the information systems of life in a quantitative *** understanding lights up the bright future of individualized precision medicine,and enables the rational design of synthetic biological systems that can benefit mankind in broad aspects from industry,agriculture to environment and *** the human genome sequence as a basic reference has becoming a routine practice in current biological and medical *** is so common that people almost take the existence of the reference genome as *** the launching and completion of the Human Genome Project(HGP)was far from a routine *** was revolutionary in the history of science in the scientific vision,technological advancement,as well as in the joint efforts of multiple disciplines to accomplish the big scientific goal,in starting the culture and building the infrastructure of data sharing,and in the effective international multi-center collaboration.

关键词： starting rational routine

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Ultrasound-driven BaTiO_(3) nanorobots patching immunologic barrier to cure chronic rheumatoid arthritis

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Journal of Advanced Ceramics 2023年第5期12卷 1105-1117页

作者： Le Jiang Yifan Wang Chunlin Liu Nan Xu Wenshuo Li Lei Wang Yixian Wu Jingyun Wang Zhijun He Fengbo Sun Lingyun Zhao Qiong Wu Xiumei Wang Huihui Yuan Xiaohui Wang Xiaodan Sun State Key Laboratory of New Ceramics and Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China Key Laboratory of Advanced Materials of Ministry of Education of China School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China MOE Key Lab.Bioinformatics School of Life SciencesTsinghua UniversityBeijing 100084China Department of Immunology School of Basic Medical SciencesCapital Medical UniversityBeijing 100069China

The disruption and reconstruction of the TREM2^(+) tissue resident macrophage(TRM)barrier on the surface of synovial lining play a key role in the activation and"remission"of rheumatoid arthritis(RA),which engender the prediction of this immunologic barrier as a potential driver for the achievement of"cure"in ***,strategies to promote the reconstruction of this barrier have not been reported,and the effect of patching this barrier remains *** the other hand,appropriate piezoelectric stimulation can reprogram macrophages,which has never been exerted on this barrier TRM ***,we design piezoelectric tetragonal BaTiO_(3)(BTO)ultrasound-driven nanorobots(USNRs)by the solvothermal synthesis method,which demonstrates satisfactory electro-mechanical conversion effects,paving the way to generate controllable electrical stimulation under ultrasound to reprogram the barrier TRM by minimally invasive injection into joint *** is demonstrated that the immunologic barrier could be patched by this USNR effectively,thereby eliminating the hyperplasia of vessels and nerves(HVN)and ***,TREM2 deficiency serum-transfected arthritis(STA)mice models are applied and proved the indispensable role of TREM2 in RA curing mediated by *** all,our work is an interesting and important exploration to expand the classical tetragonal BTO nanoparticles in the treatment of autoimmune diseases,providing a new idea and direction for the biomedical application of piezoelectric ceramics.

关键词： ultrasound-driven BaTiO_(3)nanorobots(BTO NRs) immunologic barrier upstream driver rheumatoid arthritis(RA)

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scDiffusion: conditional generation of high-quality single-cell data using diffusion model

arXiv

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arXiv 2024年

作者： Luo, Erpai Hao, Minsheng Wei, Lei Zhang, Xuegong MOE Key Lab of Bioinformatics and Bioinformatics Division of BNRIST Department of Automation Tsinghua University Beijing100084 China School of Life Sciences School of Medicine Tsinghua University Beijing100084 China

Single-cell RNA sequencing (scRNA-seq) data are important for studying the laws of life at single-cell level. However, it is still challenging to obtain enough high-quality scRNA-seq data. To mitigate the limited availability of data, generative models have been proposed to computationally generate synthetic scRNA-seq data. Nevertheless, the data generated with current models are not very realistic yet, especially when we need to generate data with controlled conditions. In the meantime, the Diffusion models have shown their power in generating data at high fidelity, providing a new opportunity for scRNA-seq generation. In this study, we developed scDiffusion, a generative model combining diffusion model and foundation model to generate high-quality scRNA-seq data with controlled conditions. We designed multiple classifiers to guide the diffusion process simultaneously, enabling scDiffusion to generate data under multiple condition combinations. We also proposed a new control strategy called Gradient Interpolation. This strategy allows the model to generate continuous trajectories of cell development from a given cell state. Experiments showed that scDiffusion can generate single-cell gene expression data closely resembling real scRNA-seq data. Also, scDiffusion can conditionally produce data on specific cell types including rare cell types. Furthermore, we could use the multiple-condition generation of scDiffusion to generate cell type that was out of the training data. Leveraging the Gradient Interpolation strategy, we generated a continuous developmental trajectory of mouse embryonic cells. These experiments demonstrate that scDiffusion is a powerful tool for augmenting the real scRNA-seq data and can provide insights into cell fate research. © 2024, CC BY-NC-ND.

关键词： Cytology

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Single-cell genomic profile-based analysis of tissue differentiation in colorectal cancer

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Science China(Life Sciences) 2021年第8期64卷 1311-1325页

作者： Hao Jiang Hongquan Zhang Xuegong Zhang MOE Key Lab of Bioinformatics and Bioinformatics Division BNRISTDepartment of AutomationTsinghua-Peking Joint Center for Life SciencesCenter for Synthetic and Systems BiologyTsinghua UniversityBeijing 100084China MOE Key Laboratory of Carcinogenesis and Translational Research Department of Human AnatomyHistology and EmbryologyState Key Laboratory of Natural and Biomimetic DrugsPeking University Health Science CenterBeijing 100191China

Colorectal cancer(CRC) progression is associated with cancer cell dedifferentiation and stemness acquisition. Several methods have been developed to identify stemness signatures in CRCs. However, studies that directly measured the degree of dedifferentiation in CRC tissues are limited. It is unclear how the differentiation states change during CRC progression. To address this, we develop a method to analyze the tissue differentiation spectrum in colorectal cancer using normal gastrointestinal singlecell transcriptome data. Applying this method on 281 tumor samples from The Cancer Genome Atlas Colon Adenocarcinoma dataset, we identified three major CRC subtypes with distinct tissue differentiation pattern. We observed that differentiation states are closely correlated with anti-tumor immune response and patient outcomes in CRC. Highly dedifferentiated CRC samples escaped the immune surveillance and exhibited poor outcomes;mildly dedifferentiated CRC samples showed resistance to anti-tumor immune responses and had a worse survival rate;well-differentiated CRC samples showed sustained anti-tumor immune responses and had a good prognosis. Overall, the spectrum of tissue differentiation observed in CRCs can be used for future clinical risk stratification and subtype-based therapy selection.

关键词： colorectal cancer sustained

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Single-cell technologies: current and near future

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Science China(Life Sciences) 2025年第1期68卷 1-4页

作者： Chenfei Wang Qi Liu Xiaohui Fan Tieliu Shi KeyLaboratory of Spine and Spinal CordInjury Repairand Regeneration Ministry of EducationOrthopedics DepartmentTongji HospitalBioinformatics DepartmentSchoolofLifeSciencesandTechnologyTongji UniversityShanghai 200082China Frontier Science Center for Stem Cells School of Life Sciences and TechnologyTongji UniversityShanghai 200092China Translational Medical Center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji UniversityShanghai 200082China Research Institute of Intelligent Computing Zhejiang LabHangzhou 311121China Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang UniversityJiaxing 314103China Center for Bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal UniversityShanghai 200241China Key Laboratory of Advanced Theory and Application in Statistics and Data Science(MOE) School of StatisticsEast China Normal UniversityShanghai 200062China

Single-cell technologies enable the indepth exploration of multiple biological hierarchies at the scale of individual cells,which have deepened our knowledge of cellular diversity,tissue organization,and overall organism function(Sun et al.,2024).In 2009,single-cell RNA sequencing(scRNA-seq)was first developed as a powerful tool to dissect gene expression and uncover transcriptional *** the rapid advancement of technology,single-cell approaches have expanded to encompass other omics,such as genomics,epigenomics,proteomics,and ***,multimodal technologies including spatially resolved transcriptomics and clustered regularly interspaced short palindromic repeats(CRISPR)screening at the single-cell level further advanced our ability to comprehensively understand cellular ***-cell methods provide deeper insights into disease mechanisms across various conditions,including cancer,developmental disorders,and aging-associated *** this issue,we focus on topics related to single-cell methods,covering the following four aspects:(i)single-cell multi-omic sequencing technology;(ii)single-cell spatial technology;(iii)singlecell CRISPR screening technology;(iv)applications of single-cell technology.

关键词： expanded enable insight

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Current opinions on large cellular models

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Quantitative Biology 2024年第4期12卷 433-443页

作者： Minsheng Hao Lei Wei Fan Yang Jianhua Yao Christina V.Theodoris Bo Wang Xin Li Ge Yang Xuegong Zhang MOE Key Laboratory of Bioinformatics and Bioinformatics Division BNRISTDepartment of AutomationTsinghua UniversityBeijingChina AI Lab TencentShenzhenChina Gladstone Institutes and University of California San FranciscoCaliforniaUSA Department of Computer Science University of TorontoTorontoOntarioCanada State Key Laboratory of Stem Cell and Reproductive Biology Institute of ZoologyChinese Academy of SciencesBeijingChina State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Life Sciences and School of Medicine Center for Synthetic and Systems BiologyTsinghua UniversityBeijingChina

1|*** language models(LLMs)have made breakthroughs in natural language processing(NLP)and understanding,and have brought revolutions in many other fields[1-4].Inspired by those successes,several large cellular models(LCMs)adopting similar structures of LLMs have been developed for single-cell transcriptomics,including(but not limited to)scBERT[5],Geneformer[6],scGPT[7],scFoundation[8],and GeneCompass[9].The practices of these models have shown LCMs’power and potential in various biological tasks and illustrated the possibilities of revolutionizing future biological studies by LCMs.

关键词： large cellular models large language models scBERT Geneformer scGPT scFoundation GeneCompass single-cell transcriptomics

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