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Subcellular RNA distribution and its change during human embryonic stem cell differentiation

STEM CELL REPORTS 2024年第1期19卷 126-140页

作者： Zhou, Fanqi tan, puwen Liu, Siqi Chang, Le Yang, Jiabin Sun, Mengyao Guo, Yuehong Si, Yanmin Wang, Dong Yu, Jia Ma, Yanni Chinese Acad Med Sci Peking Union Med Coll Inst Basic Med Sci Key Lab RNA & Hematopoiet RegulatState Key Lab Co Beijing Peoples R China Southern Med Univ Sch Basic Med Sci Dept Bioinformat Guangzhou Peoples R China Chinese Acad Med Sci Inst Blood Transfus Chengdu Sichuan Peoples R China Chinese Acad Med Sci & Peking Union Med Coll Inst Hematol & Blood Dis Hosp State Key Lab Expt Hematol Natl Clin Res Ctr Blood Dis Tianjin Peoples R China

The spatial localization of RNA within cells is closely related to its function and also involved in cell fate determination. However, the atlas of RNA distribution within cells and dynamic changes during the developmental process are largely unknown. In this study, five subcellular components, including cytoplasmic extract, membrane extract, soluble nuclear extract, chromatin -bound nuclear extract, and cytoskeletal extract, were isolated and the rules of subcellular RNA distribution in human embryonic stem cells (hESCs) and its change during hESC differentiation are summarized for the first time. The overall distribution patterns of coding and non -coding RNAs are revealed. Interestingly, some developmental genes are found to be transcribed but confined to the chromatin in undifferentiated hESC. Unexpectedly, alternative splicing and polyadenylation endow spatial heterogeneity among different isoforms of the same gene. Finally, the dynamic pattern of RNA distribution during hESC differentiation is characterized, which provides new clues for a comprehensive understanding hESC pluripotency and differentiation.

关键词： RNA localization hESC subcellular fraction hESC differentiation

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LncReader: identification of dual functional long noncoding RNAs using a multi -head self-attention mechanism

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BRIEFINGS IN BIOINFORMATICS 2023年第1期24卷 bbac579-bbac579页

作者： Liu, Tianyuan Zou, Bohao He, Manman Hu, Yongfei Dou, Yiying Cui, Tianyu tan, puwen Li, Shaobin Rao, Shuan Huang, Yan Liu, Sixi Cai, Kaican Wang, Dong Southern Med Univ Guangzhou Peoples R China Univ Calif Davis Davis CA USA CAMS & Peking Union Med Coll Union NJ USA Southern Med Univ Nanfang Hosp Dept Thorac Surg Guangzhou Peoples R China Shenzhen Childrens Hosp Dept Hematol & Oncol Shenzhen Peoples R China Southern Med Univ Dept Bioinformat Guangzhou Peoples R China

Long noncoding ribonucleic acids (RNAs;LncRNAs) endowed with both protein -coding and noncoding functions are referred to as 'dual functional lncRNAs'. Recently, dual functional lncRNAs have been intensively studied and identified as involved in various fundamental cellular processes. However, apart from time-consuming and cell -type -specific experiments, there is virtually no in silico method for predicting the identity of dual functional lncRNAs. Here, we developed a deep -learning model with a multi -head self-attention mechanism, LncReader, to identify dual functional lncRNAs. Our data demonstrated that LncReader showed multiple advantages compared to various classical machine learning methods using benchmark datasets from our previously reported cncRNAdb project. Moreover, to obtain independent in-house datasets for robust testing, mass spectrometry proteomics combined with RNA-seq and Ribo-seq were applied in four leukaemia cell lines, which further confirmed that LncReader achieved the best performance compared to other tools. Therefore, LncReader provides an accurate and practical tool that enables fast dual functional lncRNA identification.

关键词： noncoding RNA system biology deep learning

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Single-cell architecture and functional requirement of alternative splicing during hematopoietic stem cell formation

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SCIENCE ADVANCES 2022年第1期8卷 000-000页

作者： Wang, Fang tan, puwen Zhang, Pengcheng Ren, Yue Zhou, Jie Li, Yunqiao Hou, Siyuan Li, Shuaili Zhang, Linlin Ma, Yanni Wang, Chaojie tang, Wanbo Wang, Xiaoshuang Huo, Yue Hu, Yongfei Cui, Tianyu Niu, Chao Wang, Dong Liu, Bing Lan, Yu Yu, Jia Chinese Acad Med Sci Sch Basic Med Inst Basic Med SciPeking Union Med Coll Dept Biochem & Mol BiolState Key Lab Med Mol Bio Beijing 100005 Peoples R China Chinese Acad Med Sci Key Lab RNA & Hematopoiet Regulat Beijing 100005 Peoples R China Southern Med Univ Sch Basic Med Sci Dept Bioinformat Guangzhou 510515 Peoples R China Chinese Peoples Liberat Army Gen Hosp State Key Lab Expt Hematol Med Ctr 5 Beijing 100071 Peoples R China Tianjin Inst Environm & Operat Med Dept Environm Med Tianjin 300050 Peoples R China Jinan Univ Sch Med Inst Hematol Key Lab Regenerat MedMinist Educ Guangzhou 510632 Peoples R China Jinan Univ Integrated Chinese & Western Med Postdoctoral Res Guangzhou 510632 Peoples R China

Single-cell transcriptional profiling has rapidly advanced our understanding of the embryonic hematopoiesis;however, whether and what role RNA alternative splicing (AS) plays remains an enigma. This is important for understanding the mechanisms underlying splicing-associated hematopoietic diseases and for the derivation of therapeutic stem cells. Here, we used single- cell full-length transcriptome data to construct an isoform-based transcriptional atlas of the murine endothelial-to-hematopoietic stem cell (HSC) transition, which enables the identification of hemogenic signature isoforms and stage-specific AS events. We showed that the inclusion of these hemogenic-specific AS events was essential for hemogenic function in vitro. Expression data and knockout mouse studies highlighted the critical role of Srsf2: Early Srsf2 deficiency from endothelial cells affected the splicing pattern of several master hematopoietic regulators and significantly impaired HSC generation. These results redefine our understanding of the dynamic HSC developmental transcriptome and demonstrate that elaborately controlled RNA splicing governs cell fate in HSC formation.

关键词： Stem cells

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CellCall: integrating paired ligand-receptor and transcription factor activities for cell-cell communication

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NUCLEIC ACIDS RESEARCH 2021年第15期49卷 8520-8534页

作者： Zhang, Yang Liu, Tianyuan Hu, Xuesong Wang, Mei Wang, Jing Zou, Bohao tan, puwen Cui, Tianyu Dou, Yiying Ning, Lin Huang, Yan Rao, Shuan Wang, Dong Zhao, Xiaoyang Southern Med Univ Sch Basic Med Sci Dept Bioinformat Guangzhou 510515 Peoples R China Southern Med Univ Sch Basic Med Sci Dept Dev Biol State Key Lab Organ Failure Res Guangzhou 510515 Peoples R China Univ Calif Davis Dept Stat Davis CA 95616 USA Southern Med Univ Nanfang Hosp Dept Thorac Surg Guangzhou 510515 Peoples R China Southern Med Univ Guangdong Key Lab Construct & Detect Tissue Engn Guangzhou 510515 Peoples R China Southern Med Univ Zhujiang Hosp Dept Gynecol Guangzhou 510280 Peoples R China

With the dramatic development of single-cell RNA sequencing (scRNA-seq) technologies, the systematic decoding of cell-cell communication has received great research interest. To date, several in-silico methods have been developed, but most of them lack the ability to predict the communication pathways connecting the insides and outsides of cells. Here, we developed CellCall, a toolkit to infer inter- and intracellular communication pathways by integrating paired ligand-receptor and transcription factor (TF) activity. Moreover, CellCall uses an embedded pathway activity analysis method to identify the significantly activated pathways involved in intercellular crosstalk between certain cell types. Additionally, CellCall offers a rich suite of visualization options (Circos plot, Sankey plot, bubble plot, ridge plot, etc.) to present the analysis results. Case studies on scRNA-seq datasets of human testicular cells and the tumor immune microenvironment demonstrated the reliable and unique functionality of CellCall in intercellular communication analysis and internal TF activity exploration, which were further validated experimentally. Comparative analysis of CellCall and other tools indicated that CellCall was more accurate and offered more functions. In summary, CellCall provides a sophisticated and practical tool allowing researchers to decipher intercellular communication and related internal regulatory signals based on scRNA-seq data.

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RNAInter in 2020: RNA interactome repository with increased coverage and annotation

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NUCLEIC ACIDS RESEARCH 2020年第D1期48卷 D189-D197页

作者： Lin, Yunqing Liu, Tianyuan Cui, Tianyu Wang, Zhao Zhang, Yuncong tan, puwen Huang, Yan Yu, Jia Wang, Dong Southern Med Univ Sch Basic Med Sci Dept Bioinformat Guangzhou 510515 Peoples R China Harbin Med Univ Coll Bioinformat Sci & Technol Harbin 150081 Peoples R China Southern Med Univ Peoples Hosp Shunde 1 Shunde Hosp Foshan 528308 Peoples R China Chinese Acad Med Sci CAMS & Peking Union Med Coll State Key Lab Med Mol Biol Dept Biochem & Mol Biol Inst Basic Med Sci Beijing 100730 Peoples R China Southern Med Univ Dermatol Hosp Guangzhou 510091 Peoples R China Univ Elect Sci & Technol China Ctr Informat Biol Chengdu 611731 Peoples R China

Research on RNA-associated interactions has exploded in recent years, and increasing numbers of studies are not limited to RNA-RNA and RNA-protein interactions but also include RNA-DNA/compound interactions. To facilitate the development of the interactome and promote understanding of the biological functions and molecular mechanisms of RNA, we updated RAID v2.0 to RNAInter (RNA Interactome Database), a repository for RNA-associated interactions that is freely accessible at http://***/rnainter/ or http://***/raid/.Compared to RAID v2.0, new features in RNAInter include (i) 8-fold more interaction data and 94 additional species;(ii) more definite annotations organized, including RNA editing/localization/modification/structure and homology interaction;(iii) advanced functions including fuzzy/batch search, interaction network and RNA dynamic expression and (iv) four embedded RNA interactome tools: RIscoper, IntaRNA, PRIdictor and DeepBind. Consequently, RNAInter contains>41 million RNA-associated interaction entries, involving more than 450 thousand unique molecules, including RNA, protein, DNA and compound. Overall, RNAInter provides a comprehensive RNA interactome resource for researchers and paves the way to investigate the regulatory landscape of cellular RNAs.

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RNALocate v2.0: an updated resource for RNA subcellular localization with increased coverage and annotation

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NUCLEIC ACIDS RESEARCH 2022年第D1期50卷 D333-D339页

作者： Cui, Tianyu Dou, Yiying tan, puwen Ni, Zhen Liu, Tianyuan Wang, DuoLin Huang, Yan Cai, Kaican Zhao, Xiaoyang Xu, Dong Lin, Hao Wang, Dong Southern Med Univ Sch Basic Med Sci Dept Bioinformat Guangzhou 510515 Peoples R China Southern Med Univ Nanfang Hosp Dept Thorac Surg Guangzhou 510515 Peoples R China Univ Missouri Dept Elect Engn & Comp Sci Bond Life Sci Ctr Columbia MO 65211 USA Southern Med Univ Peoples Hosp Shunde Foshan 1 Shunde Hosp Foshan 528308 Peoples R China Southern Med Univ Sch Basic Med Sci Dept Dev Biol State Key Lab Organ Failure Res Guangzhou 510515 Peoples R China Univ Elect Sci & Technol China Ctr Informat Biol Chengdu 611731 Peoples R China Southern Med Univ Dermatol Hosp Guangzhou 510091 Peoples R China

Resolving the spatial distribution of the transcriptome at a subcellular level can increase our understanding of biology and diseases. To facilitate studies of biological functions and molecular mechanisms in the transcriptome, we updated RNALocate, a resource for RNA subcellular localization analysis that is freely accessible at http://***/or littp://***/. Compared to RNALocate v1.0, the new features in version 2.0 include (i) expansion of the data sources and the coverage of species;(ii) incorporation and integration of RNA-seq datasets containing information about subcellular localization;(iii) addition and reorganization of RNA information (RNA subcellular localization conditions and descriptive figures for method, RNA homology information, RNA interaction and ncRNA disease information) and (iv) three additional prediction tools: DM3Loc, iLoc-lncRNA and iLoc-mRNA. Overall, RNALocate v2.0 provides a comprehensive RNA subcellular localization resource for researchers to deconvolute the highly complex architecture of the cell.

关键词： rna messenger rna primary visual cortex datasets rna-seq

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RNAInter v4.0: RNA interactome repository with redefined confidence scoring system and improved accessibility

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NUCLEIC ACIDS RESEARCH 2022年第D1期50卷 D326-D332页

作者： Kang, Juanjuan tang, Qiang He, Jun Li, Le Yang, Nianling Yu, Shuiyan Wang, Mengyao Zhang, Yuchen Lin, Jiahao Cui, Tianyu Hu, Yongfei tan, puwen Cheng, Jun Zheng, Hailong Wang, Dong Su, Xi Chen, Wei Huang, Yan Southern Med Univ Foshan Matern & Child Healthcare Hosp Affiliated Foshan Matern & Child Healthcare Hosp Foshan 528000 Peoples R China Southern Med Univ Sch Basic Med Sci Dept Bioinformat Guangzhou 510515 Peoples R China Chengdu Univ Tradit Chinese Med Sch Basic Med Sci Chengdu 611137 Peoples R China Chengdu Univ Tradit Chinese Med Innovat Inst Chinese Med & Pharm Chengdu 611730 Peoples R China Fujian Med Univ Sch Med Technol & Engn Dept Bioinformat Fujian Key Lab Med Bioinformat Fuzhou 350122 Peoples R China Guangzhou Med Univ Affiliated Hosp 6 Qingyuan Peoples Hosp Qingyuan 511518 Peoples R China Southern Med Univ Canc Res Inst Sch Basic Med Sci Guangzhou 510515 Peoples R China Southern Med Univ Peoples Hosp Shunde 1 Shunde Hosp Foshan 528308 Peoples R China

Establishing an RNA-associated interaction repository facilitates the system-level understanding of RNA functions. However, as these interactions are distributed throughout various resources, an essential prerequisite for effectively applying these data requires that they are deposited together and annotated with confidence scores. Hence, we have updated the RNA-associated interaction database RNAInter (RNA Interactome Database) to version 4.0, which is freely accessible at http://***. org or http://***/rnainteri. Compared with previous versions, the current RNAInter not only contains an enlarged data set, but also an updated confidence scoring system. The merits of this 4.0 version can be summarized in the following points: (i) a redefined confidence scoring system as achieved by integrating the trust of experimental evidence, the trust of the scientific community and the types of tissues/cells, (ii) a redesigned fully functional database that enables for a more rapid retrieval and browsing of interactions via an upgraded user- friendly interface and (iii) an update of entries to >47 million by manually mining the literature and integrating six database resources with evidence from experimental and computational sources. Overall, RNAInter will provide a more comprehensive and readily accessible RNA interactome platform to investigate the regulatory landscape of cellular RNAs.

关键词： mining rna community datasets

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Dissecting dynamic expression of autophagy-related genes during human fetal digestive tract development via single-cell RNA sequencing

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AUTOPHAGY 2019年第11期15卷 2019-2021页

作者： tan, puwen Ren, Yue Zhang, Yuncong Lin, Yunqing Cui, Tianyu Huang, Yan Zhang, Yang Ning, Lin Yu, Jia Gao, Shuai Wang, Dong Huang, He Chongqing Med Univ Affiliated Hosp 2 Dept Anesthesiol Chongqing Peoples R China Southern Med Univ Sch Basic Med Sci Dept Bioinformat Guangzhou Guangdong Peoples R China Chinese Acad Med Sci Inst Basic Med Sci Dept Biochem & Mol Biol State Key Lab Med Mol Biol Beijing Peoples R China Peking Union Med Coll Beijing Peoples R China Harbin Med Univ Coll Bioinformat Sci & Technol Harbin Heilongjiang Peoples R China Southern Med Univ Peoples Hosp Shunde 1 Shunde Hosp Foshan Peoples R China Southern Med Univ Dermatol Hosp Guangzhou Guangdong Peoples R China China Agr Univ Coll Anim Sci & Technol Key Lab Anim Genet Breeding & Reprod MARA Natl Engn Lab Anim Breeding Beijing Peoples R China Peking Univ Hosp 3 Beijing Adv Innovat Ctr Genom Dept Obstet & GynecolColl Life Sci Beijing Peoples R China

Macroautophagy/autophagy has been demonstrated to play an essential role in embryonic development. However, the role of autophagy during human fetal digestive tract development has not been investigated. Here, by using over 5,000 human embryonic digestive tract cells ranging from 6 weeks to 25 weeks, we explored the dynamic expression of autophagy-related genes at single-cell resolution, and found that the transcriptional activity of autophagy-related genes boosted remarkably and specifically in the early (between 6 and 9 weeks) stages. Interestingly, the small intestine cells at 9 weeks showed the most significant enrichment of autophagy-related genes than any other stages. In summary, our results for the first time revealed that autophagy may play an essential role in the development of the digestive tract, especially for the small intestine, in early human embryos.

关键词： Autophagy digestive tract dynamic expression human embryos single cells

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Improving gene isoform quantification with miniQuant

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Nature biotechnology 2025年 2025 Jun 3页

作者： Haoran Li Dingjie Wang Qi Gao puwen tan Yunhao Wang Xiaoyu Cai Aifu Li Yue Zhao Andrew L Thurman Seyed Amir Malekpour Ying Zhang Roberta Sala Andrea Cipriano Chia-Lin Wei Vittorio Sebastiano Chi Song Nancy R Zhang Kin Fai Au Gilbert S. Omenn Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. Department of Biomedical Informatics The Ohio State University Columbus OH USA. Department of Internal Medicine University of Iowa Iowa City IA USA. Department of Obstetrics and Gynecology Stanford University Stanford CA USA. Institute for Stem Cell Biology and Regenerative Medicine Stanford University Stanford CA USA. The Jackson Laboratory for Genomic Medicine Farmington CT USA. Division of Biostatistics College of Public Health The Ohio State University Columbus OH USA. Department of Statistics and Data Science The Wharton School University of Pennsylvania Philadelphia PA USA. Gilbert S. Omenn Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. kinfai@umich.edu. Department of Biomedical Informatics The Ohio State University Columbus OH USA. kinfai@umich.edu. Department of Internal Medicine University of Iowa Iowa City IA USA. kinfai@umich.edu.

RNA sequencing has been widely applied for gene isoform quantification, but limitations exist in quantifying isoforms of complex genes accurately, especially for short reads. Here we identify genes that are difficult to quantify accurately with short reads and illustrate the information benefit of using long reads to quantify these regions. We present miniQuant, which ranks genes with quantification errors caused by the ambiguity of read alignments and integrates the complementary strengths of long reads and short reads with optimal combination in a gene- and data-specific manner to achieve more accurate quantification. These results are supported by rigorous mathematical proofs, validated with a wide range of simulation data, experimental validations and more than 17,000 public datasets from GTEx, TCGA and ENCODE consortia. We demonstrate miniQuant can uncover isoform switches during the differentiation of human embryonic stem cells to pharyngeal endoderm and primordial germ cell-like cells.

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Transcriptomic insights into temporal expression pattern of autophagy genes during monocytic and granulocytic differentiation

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AUTOPHAGY 2018年第3期14卷 558-559页

作者： Huang, Yan tan, puwen Wang, Xiaoshuang Yi, Ying Hu, Yongfei Wang, Dong Wang, Fang Harbin Med Univ Coll Bioinformat Sci & Technol 157 Baojian Rd Harbin Heilongjiang Peoples R China Chinese Acad Med Sci Inst Basic Med Sci Dept Biochem & Mol Biol State Key Lab Med Mol Biol Beijing Peoples R China Peking Union Med Coll Beijing Peoples R China Univ Elect Sci & Technol China Ctr Informat Biol Chengdu Sichuan Peoples R China

Macroautophagy/autophagy plays an essential role in hematopoietic stem cell (HSC) differentiation. However, the role of autophagy during monocytic and granulocytic differentiation remains poorly understood. Hence, we first represented global transcriptomic analysis for temporal expression of autophagy genes during monocytic and granulocytic differentiation by combining RNA-Seq data with monocytic and granulocytic induction in CD34(+) hematopoietic stem and progenitor cells. According to a self-organizing map (SOM) algorithm, our results show temporal expression patterns of autophagy genes during monocytic and granulocytic differentiation. More importantly, 22 autophagy genes present significantly divergent roles during monocytic and granulocytic differentiation, indicating these autophagy genes could be important factors involved in the differentiation of myeloid progenitors into monocytes and granulocytes.

关键词： autophagy hematopoietic stem cell monocytic and granulocytic differentiation temporal expression pattern transcriptomic analysis

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