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Zhao Z, Chen Y, Zou X, Lin L, Zhou X, Cheng X, Yang G, Xu Q, Gong L, Li L, Ni T. Pan-cancer transcriptome analysis reveals widespread regulation through alternative tandem transcription initiation. SCIENCE ADVANCES 2024; 10:eadl5606. [PMID: 38985880 PMCID: PMC11235174 DOI: 10.1126/sciadv.adl5606] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 06/05/2024] [Indexed: 07/12/2024]
Abstract
Abnormal transcription initiation from alternative first exon has been reported to promote tumorigenesis. However, the prevalence and impact of gene expression regulation mediated by alternative tandem transcription initiation were mostly unknown in cancer. Here, we developed a robust computational method to analyze alternative tandem transcription start site (TSS) usage from standard RNA sequencing data. Applying this method to pan-cancer RNA sequencing datasets, we observed widespread dysregulation of tandem TSS usage in tumors, many of which were independent of changes in overall expression level or alternative first exon usage. We showed that the dynamics of tandem TSS usage was associated with epigenomic modulation. We found that significant 5' untranslated region shortening of gene TIMM13 contributed to increased protein production, and up-regulation of TIMM13 by CRISPR-mediated transcriptional activation promoted proliferation and migration of lung cancer cells. Our findings suggest that dysregulated tandem TSS usage represents an addtional layer of cancer-associated transcriptome alterations.
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Affiliation(s)
- Zhaozhao Zhao
- State Key Laboratory of Genetic Engineering, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, Center for Evolutionary Biology, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai 200438, China
- MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Yu Chen
- State Key Laboratory of Genetic Engineering, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, Center for Evolutionary Biology, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Xudong Zou
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | - Limin Lin
- State Key Laboratory of Genetic Engineering, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, Center for Evolutionary Biology, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Xiaolan Zhou
- State Key Laboratory of Genetic Engineering, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, Center for Evolutionary Biology, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Xiaomeng Cheng
- State Key Laboratory of Genetic Engineering, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, Center for Evolutionary Biology, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Guangrui Yang
- State Key Laboratory of Genetic Engineering, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, Center for Evolutionary Biology, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Qiushi Xu
- State Key Laboratory of Genetic Engineering, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, Center for Evolutionary Biology, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Lihai Gong
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | - Lei Li
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518055, China
| | - Ting Ni
- State Key Laboratory of Genetic Engineering, National Clinical Research Center for Aging and Medicine, Huashan Hospital, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, Center for Evolutionary Biology, Shanghai Engineering Research Center of Industrial Microorganisms, School of Life Sciences, Fudan University, Shanghai 200438, China
- State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, Institutes of Biomedical Sciences, School of Life Sciences, Inner Mongolia University, Hohhot 010070, China
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Xia J, Li Y, Zhu H, Xue F, Shi F, Li N. A Bayesian Change Point Model for Dynamic Alternative Transcription Start Site Usage During Cellular Differentiation. J Comput Biol 2024; 31:445-457. [PMID: 38752891 DOI: 10.1089/cmb.2023.0174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/23/2024] Open
Abstract
ABSTRACT An alternative transcription start site (ATSS) is a major driving force for increasing the complexity of transcripts in human tissues. As a transcriptional regulatory mechanism, ATSS has biological significance. Many studies have confirmed that ATSS plays an important role in diseases and cell development and differentiation. However, exploration of its dynamic mechanisms remains insufficient. Identifying ATSS change points during cell differentiation is critical for elucidating potential dynamic mechanisms. For relative ATSS usage as percentage data, the existing methods lack sensitivity to detect the change point for ATSS longitudinal data. In addition, some methods have strict requirements for data distribution and cannot be applied to deal with this problem. In this study, the Bayesian change point detection model was first constructed using reparameterization techniques for two parameters of a beta distribution for the percentage data type, and the posterior distributions of parameters and change points were obtained using Markov Chain Monte Carlo (MCMC) sampling. With comprehensive simulation studies, the performance of the Bayesian change point detection model is found to be consistently powerful and robust across most scenarios with different sample sizes and beta distributions. Second, differential ATSS events in the real data, whose change points were identified using our method, were clustered according to their change points. Last, for each change point, pathway and transcription factor motif analyses were performed on its differential ATSS events. The results of our analyses demonstrated the effectiveness of the Bayesian change point detection model and provided biological insights into cell differentiation.
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Affiliation(s)
- Juan Xia
- Department of Mathematics, College of Informatics, Huazhong Agricultural University, Wuhan, P.R. China
| | - Yuxia Li
- Department of Mathematics, College of Informatics, Huazhong Agricultural University, Wuhan, P.R. China
| | - Haotian Zhu
- College of Informatics, Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural University, Wuhan, P.R. China
| | - Feiyang Xue
- College of Informatics, Hubei Key Laboratory of Agricultural Bioinformatics, Huazhong Agricultural University, Wuhan, P.R. China
| | - Feng Shi
- Department of Mathematics, College of Informatics, Huazhong Agricultural University, Wuhan, P.R. China
| | - Nana Li
- Department of Mathematics, College of Informatics, Huazhong Agricultural University, Wuhan, P.R. China
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Zhang G, Song C, Fan S, Yin M, Wang X, Zhang Y, Huang X, Li Y, Shang D, Li C, Wang Q. LncSEA 2.0: an updated platform for long non-coding RNA related sets and enrichment analysis. Nucleic Acids Res 2024; 52:D919-D928. [PMID: 37986229 PMCID: PMC10767924 DOI: 10.1093/nar/gkad1008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/12/2023] [Accepted: 10/19/2023] [Indexed: 11/22/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) possess a wide range of biological functions, and research has demonstrated their significance in regulating major biological processes such as development, differentiation, and immune response. The accelerating accumulation of lncRNA research has greatly expanded our understanding of lncRNA functions. Here, we introduce LncSEA 2.0 (http://bio.liclab.net/LncSEA/index.php), aiming to provide a more comprehensive set of functional lncRNAs and enhanced enrichment analysis capabilities. Compared with LncSEA 1.0, we have made the following improvements: (i) We updated the lncRNA sets for 11 categories and extremely expanded the lncRNA scopes for each set. (ii) We newly introduced 15 functional lncRNA categories from multiple resources. This update not only included a significant amount of downstream regulatory data for lncRNAs, but also covered numerous epigenetic regulatory data sets, including lncRNA-related transcription co-factor binding, chromatin regulator binding, and chromatin interaction data. (iii) We incorporated two new lncRNA set enrichment analysis functions based on GSEA and GSVA. (iv) We adopted the snakemake analysis pipeline to track data processing and analysis. In summary, LncSEA 2.0 offers a more comprehensive collection of lncRNA sets and a greater variety of enrichment analysis modules, assisting researchers in a more comprehensive study of the functional mechanisms of lncRNAs.
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Affiliation(s)
- Guorui Zhang
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Chao Song
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Shifan Fan
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
| | - Mingxue Yin
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Xinyue Wang
- School of Medical Informatics, Daqing Campus, Harbin Medical University. Daqing, 163319, China
| | - Yuexin Zhang
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Xuemei Huang
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
| | - Ye Li
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
| | - Desi Shang
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
| | - Chunquan Li
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
- MOE Key Lab of Rare Pediatric Diseases, University of South China, Hengyang, Hunan 421001, China
| | - Qiuyu Wang
- The First Affiliated Hospital & National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- School of Computer, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
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Xie Y, Chan LY, Cheung MY, Li MW, Lam HM. Current technical advancements in plant epitranscriptomic studies. THE PLANT GENOME 2023; 16:e20316. [PMID: 36890704 DOI: 10.1002/tpg2.20316] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 02/05/2023] [Indexed: 06/18/2023]
Abstract
The growth and development of plants are the result of the interplay between the internal developmental programming and plant-environment interactions. Gene expression regulations in plants are made up of multi-level networks. In the past few years, many studies were carried out on co- and post-transcriptional RNA modifications, which, together with the RNA community, are collectively known as the "epitranscriptome." The epitranscriptomic machineries were identified and their functional impacts characterized in a broad range of physiological processes in diverse plant species. There is mounting evidence to suggest that the epitranscriptome provides an additional layer in the gene regulatory network for plant development and stress responses. In the present review, we summarized the epitranscriptomic modifications found so far in plants, including chemical modifications, RNA editing, and transcript isoforms. The various approaches to RNA modification detection were described, with special emphasis on the recent development and application potential of third-generation sequencing. The roles of epitranscriptomic changes in gene regulation during plant-environment interactions were discussed in case studies. This review aims to highlight the importance of epitranscriptomics in the study of gene regulatory networks in plants and to encourage multi-omics investigations using the recent technical advancements.
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Affiliation(s)
- Yichun Xie
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Long-Yiu Chan
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Ming-Yan Cheung
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Man-Wah Li
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
| | - Hon-Ming Lam
- School of Life Sciences and Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China
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Carrion SA, Michal JJ, Jiang Z. Alternative Transcripts Diversify Genome Function for Phenome Relevance to Health and Diseases. Genes (Basel) 2023; 14:2051. [PMID: 38002994 PMCID: PMC10671453 DOI: 10.3390/genes14112051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 11/06/2023] [Accepted: 11/07/2023] [Indexed: 11/26/2023] Open
Abstract
Manipulation using alternative exon splicing (AES), alternative transcription start (ATS), and alternative polyadenylation (APA) sites are key to transcript diversity underlying health and disease. All three are pervasive in organisms, present in at least 50% of human protein-coding genes. In fact, ATS and APA site use has the highest impact on protein identity, with their ability to alter which first and last exons are utilized as well as impacting stability and translation efficiency. These RNA variants have been shown to be highly specific, both in tissue type and stage, with demonstrated importance to cell proliferation, differentiation and the transition from fetal to adult cells. While alternative exon splicing has a limited effect on protein identity, its ubiquity highlights the importance of these minor alterations, which can alter other features such as localization. The three processes are also highly interwoven, with overlapping, complementary, and competing factors, RNA polymerase II and its CTD (C-terminal domain) chief among them. Their role in development means dysregulation leads to a wide variety of disorders and cancers, with some forms of disease disproportionately affected by specific mechanisms (AES, ATS, or APA). Challenges associated with the genome-wide profiling of RNA variants and their potential solutions are also discussed in this review.
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Affiliation(s)
| | | | - Zhihua Jiang
- Department of Animal Sciences and Center for Reproductive Biology, Washington State University, Pullman, WA 99164-7620, USA; (S.A.C.); (J.J.M.)
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6
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de Mendoza A, Nguyen TV, Ford E, Poppe D, Buckberry S, Pflueger J, Grimmer MR, Stolzenburg S, Bogdanovic O, Oshlack A, Farnham PJ, Blancafort P, Lister R. Large-scale manipulation of promoter DNA methylation reveals context-specific transcriptional responses and stability. Genome Biol 2022; 23:163. [PMID: 35883107 PMCID: PMC9316731 DOI: 10.1186/s13059-022-02728-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Accepted: 07/06/2022] [Indexed: 12/22/2022] Open
Abstract
Background Cytosine DNA methylation is widely described as a transcriptional repressive mark with the capacity to silence promoters. Epigenome engineering techniques enable direct testing of the effect of induced DNA methylation on endogenous promoters; however, the downstream effects have not yet been comprehensively assessed. Results Here, we simultaneously induce methylation at thousands of promoters in human cells using an engineered zinc finger-DNMT3A fusion protein, enabling us to test the effect of forced DNA methylation upon transcription, chromatin accessibility, histone modifications, and DNA methylation persistence after the removal of the fusion protein. We find that transcriptional responses to DNA methylation are highly context-specific, including lack of repression, as well as cases of increased gene expression, which appears to be driven by the eviction of methyl-sensitive transcriptional repressors. Furthermore, we find that some regulatory networks can override DNA methylation and that promoter methylation can cause alternative promoter usage. DNA methylation deposited at promoter and distal regulatory regions is rapidly erased after removal of the zinc finger-DNMT3A fusion protein, in a process combining passive and TET-mediated demethylation. Finally, we demonstrate that induced DNA methylation can exist simultaneously on promoter nucleosomes that possess the active histone modification H3K4me3, or DNA bound by the initiated form of RNA polymerase II. Conclusions These findings have important implications for epigenome engineering and demonstrate that the response of promoters to DNA methylation is more complex than previously appreciated. Supplementary Information The online version contains supplementary material available at 10.1186/s13059-022-02728-5.
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Affiliation(s)
- Alex de Mendoza
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, WA, 6009, Australia. .,Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia. .,School of Biological and Behavioural Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS, UK.
| | - Trung Viet Nguyen
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, WA, 6009, Australia.,Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia
| | - Ethan Ford
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, WA, 6009, Australia.,Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia
| | - Daniel Poppe
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, WA, 6009, Australia.,Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia
| | - Sam Buckberry
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, WA, 6009, Australia.,Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia
| | - Jahnvi Pflueger
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, WA, 6009, Australia.,Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia
| | - Matthew R Grimmer
- Department of Biochemistry and Molecular Medicine, University of Southern California, 1450 Biggy St, Los Angeles, CA, 90089, USA.,Integrated Genetics and Genomics, University of California, Davis, 451 Health Sciences Dr, Davis, CA, 95616, USA.,Department of Neurological Surgery, University of California, 1450 3rd St, San Francisco, CA, 94158, USA
| | - Sabine Stolzenburg
- School of Anatomy, Physiology and Human Biology, The University of Western Australia, 35 Stirling Hwy, Crawley, WA, 6009, Australia
| | - Ozren Bogdanovic
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, WA, 6009, Australia.,Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney, New South Wales, Australia.,School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, 2052, Australia
| | - Alicia Oshlack
- The Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, VIC, 3000, Australia.,School of BioScience, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Peggy J Farnham
- Department of Biochemistry and Molecular Medicine, University of Southern California, 1450 Biggy St, Los Angeles, CA, 90089, USA
| | - Pilar Blancafort
- Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia.,School of Anatomy, Physiology and Human Biology, The University of Western Australia, 35 Stirling Hwy, Crawley, WA, 6009, Australia.,The Greehey Children's Cancer Research Institute, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Ryan Lister
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, WA, 6009, Australia. .,Harry Perkins Institute of Medical Research, QEII Medical Centre and Centre for Medical Research, The University of Western Australia, Perth, WA, 6009, Australia.
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7
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Fiszbein A, McGurk M, Calvo-Roitberg E, Kim G, Burge CB, Pai AA. Widespread occurrence of hybrid internal-terminal exons in human transcriptomes. SCIENCE ADVANCES 2022; 8:eabk1752. [PMID: 35044812 PMCID: PMC8769537 DOI: 10.1126/sciadv.abk1752] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2021] [Accepted: 11/23/2021] [Indexed: 06/12/2023]
Abstract
Messenger RNA isoform differences are predominantly driven by alternative first, internal, and last exons. Despite the importance of classifying exons to understand isoform structure, few tools examine isoform-specific exon usage. We recently observed that alternative transcription start sites often arise near internal exons, often creating “hybrid” first/internal exons. To systematically detect hybrid exons, we built the hybrid-internal-terminal (HIT) pipeline to classify exons depending on their isoform-specific usage. On the basis of splice junction reads in RNA sequencing data and probabilistic modeling, the HIT index identified thousands of previously misclassified hybrid first-internal and internal-last exons. Hybrid exons are enriched in long genes and genes involved in RNA splicing and have longer flanking introns and strong splice sites. Their usage varies considerably across human tissues. By developing the first method to classify exons according to isoform contexts, our findings document the occurrence of hybrid exons, a common quirk of the human transcriptome.
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Affiliation(s)
- Ana Fiszbein
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Biology, Boston University, Boston, MA, USA
| | - Michael McGurk
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - GyeungYun Kim
- Department of Biology, Boston University, Boston, MA, USA
| | - Christopher B. Burge
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Athma A. Pai
- RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA, USA
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8
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Robinson EK, Jagannatha P, Covarrubias S, Cattle M, Smaliy V, Safavi R, Shapleigh B, Abu-Shumays R, Jain M, Cloonan SM, Akeson M, Brooks AN, Carpenter S. Inflammation drives alternative first exon usage to regulate immune genes including a novel iron-regulated isoform of Aim2. eLife 2021; 10:69431. [PMID: 34047695 PMCID: PMC8260223 DOI: 10.7554/elife.69431] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 05/21/2021] [Indexed: 12/11/2022] Open
Abstract
Determining the layers of gene regulation within the innate immune response is critical to our understanding of the cellular responses to infection and dysregulation in disease. We identified a conserved mechanism of gene regulation in human and mouse via changes in alternative first exon (AFE) usage following inflammation, resulting in changes to the isoforms produced. Of these AFE events, we identified 95 unannotated transcription start sites in mice using a de novo transcriptome generated by long-read native RNA-sequencing, one of which is in the cytosolic receptor for dsDNA and known inflammatory inducible gene, Aim2. We show that this unannotated AFE isoform of Aim2 is the predominant isoform expressed during inflammation and contains an iron-responsive element in its 5′UTR enabling mRNA translation to be regulated by iron levels. This work highlights the importance of examining alternative isoform changes and translational regulation in the innate immune response and uncovers novel regulatory mechanisms of Aim2.
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Affiliation(s)
- Elektra K Robinson
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, United States
| | - Pratibha Jagannatha
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, United States.,Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, United States
| | - Sergio Covarrubias
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, United States
| | - Matthew Cattle
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, United States
| | - Valeriya Smaliy
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, United States
| | - Rojin Safavi
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, United States
| | - Barbara Shapleigh
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, United States
| | - Robin Abu-Shumays
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, United States
| | - Miten Jain
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, United States
| | - Suzanne M Cloonan
- Division of Pulmonary and Critical Care Medicine, Joan and Sanford I. Weill Department of Medicine, Weill Cornell Medicine, New York, United States
| | - Mark Akeson
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, United States
| | - Angela N Brooks
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, United States
| | - Susan Carpenter
- Department of Molecular, Cell and Developmental Biology, University of California Santa Cruz, Santa Cruz, United States
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9
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Lanjanian H, Moazzam-Jazi M, Hedayati M, Akbarzadeh M, Guity K, Sedaghati-Khayat B, Azizi F, Daneshpour MS. SARS-CoV-2 infection susceptibility influenced by ACE2 genetic polymorphisms: insights from Tehran Cardio-Metabolic Genetic Study. Sci Rep 2021; 11:1529. [PMID: 33452303 PMCID: PMC7810897 DOI: 10.1038/s41598-020-80325-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Accepted: 12/16/2020] [Indexed: 01/29/2023] Open
Abstract
The genetic variations among individuals are one of the notable factors determining disease severity and drug response. Nowadays, COVID-19 pandemic has been adversely affecting many aspects of human life. We used the Tehran Cardio-Metabolic Genetic Study (TCGS) data that is an ongoing genetic study including the whole-genome sequencing of 1200 individuals and chip genotyping of more than 15,000 participants. Here, the effect of ACE2 variations by focusing on the receptor-binding site of SARS-CoV-2 and ACE2 cleavage by TMPRSS2 protease were investigated through simulations study. After analyzing TCGS data, 570 genetic variations on the ACE2 gene, including single nucleotide polymorphisms (SNP) and insertion/deletion (INDEL) were detected. Interestingly, two observed missense variants, K26R and S331F, which only the first one was previously reported, can reduce the receptor affinity for the viral Spike protein. Moreover, our bioinformatics simulation of 3D structures and docking of proteins explains important details of ACE2-Spike and ACE2-TMPRSS2 interactions, especially the critical role of Arg652 of ACE2 for protease function of TMPRSS2 was uncovered. As our results show that the genetic variation of ACE2 can at least influence the affinity of this receptor to its partners, we need to consider the genetic variations on ACE2 as well as other genes in the pathways that contribute to the pathogenesis of COVID-19 for designing efficient drugs and vaccines.
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Affiliation(s)
- Hossein Lanjanian
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran
| | - Maryam Moazzam-Jazi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran
| | - Mehdi Hedayati
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran
| | - Mahdi Akbarzadeh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran
| | - Kamran Guity
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran
| | - Bahareh Sedaghati-Khayat
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam S Daneshpour
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, POBox: 19195-4763, Tehran, Iran.
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10
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Single-cell RNA cap and tail sequencing (scRCAT-seq) reveals subtype-specific isoforms differing in transcript demarcation. Nat Commun 2020; 11:5148. [PMID: 33051455 PMCID: PMC7555861 DOI: 10.1038/s41467-020-18976-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2019] [Accepted: 09/15/2020] [Indexed: 01/31/2023] Open
Abstract
The differences in transcription start sites (TSS) and transcription end sites (TES) among gene isoforms can affect the stability, localization, and translation efficiency of mRNA. Gene isoforms allow a single gene diverse functions across different cell types, and isoform dynamics allow different functions over time. However, methods to efficiently identify and quantify RNA isoforms genome-wide in single cells are still lacking. Here, we introduce single cell RNA Cap And Tail sequencing (scRCAT-seq), a method to demarcate the boundaries of isoforms based on short-read sequencing, with higher efficiency and lower cost than existing long-read sequencing methods. In conjunction with machine learning algorithms, scRCAT-seq demarcates RNA transcripts with unprecedented accuracy. We identified hundreds of previously uncharacterized transcripts and thousands of alternative transcripts for known genes, revealed cell-type specific isoforms for various cell types across different species, and generated a cell atlas of isoform dynamics during the development of retinal cones.
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11
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Deng Y, Luo H, Yang Z, Liu L. LncAS2Cancer: a comprehensive database for alternative splicing of lncRNAs across human cancers. Brief Bioinform 2020; 22:5895039. [PMID: 32820322 DOI: 10.1093/bib/bbaa179] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 07/10/2020] [Accepted: 07/13/2020] [Indexed: 02/05/2023] Open
Abstract
Accumulating studies demonstrated that the roles of lncRNAs for tumorigenesis were isoform-dependent and their aberrant splicing patterns in cancers contributed to function specificity. However, there is no existing database focusing on cancer-related alternative splicing of lncRNAs. Here, we developed a comprehensive database called LncAS2Cancer, which collected 5335 bulk RNA sequencing and 1826 single-cell RNA sequencing samples, covering over 30 cancer types. By applying six state-of-the-art splicing algorithms, 50 859 alternative splicing events for 8 splicing types were identified and deposited in the database. In addition, the database contained the following information: (i) splicing patterns of lncRNAs under seven different conditions, such as gene interference, which facilitated to infer potential regulators; (ii) annotation information derived from eight sources and manual curation, to understand the functional impact of affected sequences; (iii) survival analysis to explore potential biomarkers; as well as (iv) a suite of tools to browse, search, visualize and download interesting information. LncAS2Cancer could not only confirm the known cancer-associated lncRNA isoforms but also indicate novel ones. Using the data deposited in LncAS2Cancer, we compared gene model and transcript overlap between lncRNAs and protein-coding genes and discusses how these factors, along with sequencing depth, affected the interpretation of splicing signals. Based on recurrent signals and potential confounders, we proposed a reliable score to prioritize splicing events for further elucidation. Together, with the broad collection of lncRNA splicing patterns and annotation, LncAS2Cancer will provide important new insights into the diverse functional roles of lncRNA isoforms in human cancers. LncAS2Cancer is freely available at https://lncrna2as.cd120.com/.
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Affiliation(s)
- Yulan Deng
- Department of Thoracic Surgery, West China Hospital, Sichuan University
| | - Hao Luo
- Department of Thoracic Surgery, West China Hospital, Sichuan University
| | - Zhenyu Yang
- Department of Thoracic Surgery, West China Hospital, Sichuan University
| | - Lunxu Liu
- Department of Thoracic Surgery, West China Hospital, Sichuan University
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12
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Kanodia P, Prasanth KR, Roa-Linares VC, Bradrick SS, Garcia-Blanco MA, Miller WA. A rapid and simple quantitative method for specific detection of smaller coterminal RNA by PCR (DeSCo-PCR): application to the detection of viral subgenomic RNAs. RNA (NEW YORK, N.Y.) 2020; 26:888-901. [PMID: 32238481 PMCID: PMC7297113 DOI: 10.1261/rna.074963.120] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 03/26/2020] [Indexed: 05/10/2023]
Abstract
RNAs that are 5'-truncated versions of a longer RNA but share the same 3' terminus can be generated by alternative promoters in transcription of cellular mRNAs or by replicating RNA viruses. These truncated RNAs cannot be distinguished from the longer RNA by a simple two-primer RT-PCR because primers that anneal to the cDNA from the smaller RNA also anneal to-and amplify-the longer RNA-derived cDNA. Thus, laborious methods, such as northern blot hybridization, are used to distinguish shorter from longer RNAs. For rapid, low-cost, and specific detection of these truncated RNAs, we report detection of smaller coterminal RNA by PCR (DeSCo-PCR). DeSCo-PCR uses a nonextendable blocking primer (BP), which outcompetes a forward primer (FP) for annealing to longer RNA-derived cDNA, while FP outcompetes BP for annealing to shorter RNA-derived cDNA. In the presence of BP, FP, and the reverse primer, only cDNA from the shorter RNA is amplified in a single-tube reaction containing both RNAs. Many positive strand RNA viruses generate 5'-truncated forms of the genomic RNA (gRNA) called subgenomic RNAs (sgRNA), which play key roles in viral gene expression and pathogenicity. We demonstrate that DeSCo-PCR is easily optimized to selectively detect relative quantities of sgRNAs of red clover necrotic mosaic virus from plants and Zika virus from human cells, each infected with viral strains that generate different amounts of sgRNA. This technique should be readily adaptable to other sgRNA-producing viruses, and for quantitative detection of any truncated or alternatively spliced RNA.
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Affiliation(s)
- Pulkit Kanodia
- Interdepartmental Genetics and Genomics, Iowa State University, Ames, Iowa 50011, USA
- Plant Pathology and Microbiology Department, Iowa State University, Ames, Iowa 50011, USA
| | - K Reddisiva Prasanth
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas 77555, USA
| | - Vicky C Roa-Linares
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas 77555, USA
- Molecular and Translational Medicine Group, Institute of Medical Research, Faculty of Medicine University of Antioquia, Medellin 050010, Colombia
| | - Shelton S Bradrick
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas 77555, USA
| | - Mariano A Garcia-Blanco
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas 77555, USA
- Programme of Emerging Infectious Diseases, Duke-NUS Medical School, Singapore 169857, Singapore
- Institute of Human Infections and Immunity, University of Texas Medical Branch, Galveston, Texas 77555, USA
| | - W Allen Miller
- Interdepartmental Genetics and Genomics, Iowa State University, Ames, Iowa 50011, USA
- Plant Pathology and Microbiology Department, Iowa State University, Ames, Iowa 50011, USA
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13
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An integrated multi-omics approach identifies the landscape of interferon-α-mediated responses of human pancreatic beta cells. Nat Commun 2020; 11:2584. [PMID: 32444635 PMCID: PMC7244579 DOI: 10.1038/s41467-020-16327-0] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 04/23/2020] [Indexed: 12/12/2022] Open
Abstract
Interferon-α (IFNα), a type I interferon, is expressed in the islets of type 1 diabetic individuals, and its expression and signaling are regulated by T1D genetic risk variants and viral infections associated with T1D. We presently characterize human beta cell responses to IFNα by combining ATAC-seq, RNA-seq and proteomics assays. The initial response to IFNα is characterized by chromatin remodeling, followed by changes in transcriptional and translational regulation. IFNα induces changes in alternative splicing (AS) and first exon usage, increasing the diversity of transcripts expressed by the beta cells. This, combined with changes observed on protein modification/degradation, ER stress and MHC class I, may expand antigens presented by beta cells to the immune system. Beta cells also up-regulate the checkpoint proteins PDL1 and HLA-E that may exert a protective role against the autoimmune assault. Data mining of the present multi-omics analysis identifies two compound classes that antagonize IFNα effects on human beta cells. The cytokine IFNα is expressed in the islets of individuals with type 1 diabetes and contributes to local inflammation and destruction of beta cells. Here, the authors provide a global multiomics view of IFNα-induced changes in human beta cells at the level of chromatin, mRNA and protein expression.
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14
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de la Fuente L, Arzalluz-Luque Á, Tardáguila M, Del Risco H, Martí C, Tarazona S, Salguero P, Scott R, Lerma A, Alastrue-Agudo A, Bonilla P, Newman JRB, Kosugi S, McIntyre LM, Moreno-Manzano V, Conesa A. tappAS: a comprehensive computational framework for the analysis of the functional impact of differential splicing. Genome Biol 2020; 21:119. [PMID: 32423416 PMCID: PMC7236505 DOI: 10.1186/s13059-020-02028-w] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Accepted: 04/23/2020] [Indexed: 12/26/2022] Open
Abstract
Recent advances in long-read sequencing solve inaccuracies in alternative transcript identification of full-length transcripts in short-read RNA-Seq data, which encourages the development of methods for isoform-centered functional analysis. Here, we present tappAS, the first framework to enable a comprehensive Functional Iso-Transcriptomics (FIT) analysis, which is effective at revealing the functional impact of context-specific post-transcriptional regulation. tappAS uses isoform-resolved annotation of coding and non-coding functional domains, motifs, and sites, in combination with novel analysis methods to interrogate different aspects of the functional readout of transcript variants and isoform regulation. tappAS software and documentation are available at https://app.tappas.org.
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Affiliation(s)
- Lorena de la Fuente
- Genomics of Gene Expression Laboratory, Prince Felipe Research Center, Valencia, Spain
- Present Address: Bioinformatics Unit, IIS Fundación Jiménez Díaz, Madrid, Spain
| | - Ángeles Arzalluz-Luque
- Department of Statistics and Operational Research, Polytechnical University of Valencia, Valencia, Spain
| | - Manuel Tardáguila
- Department of Microbiology and Cell Science, Institute for Food and Agricultural Sciences, University of Florida, Gainesville, FL, USA
- Present Address: Human Genetics Department, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
| | - Héctor Del Risco
- Department of Microbiology and Cell Science, Institute for Food and Agricultural Sciences, University of Florida, Gainesville, FL, USA
| | - Cristina Martí
- Genomics of Gene Expression Laboratory, Prince Felipe Research Center, Valencia, Spain
| | - Sonia Tarazona
- Department of Statistics and Operational Research, Polytechnical University of Valencia, Valencia, Spain
| | - Pedro Salguero
- Genomics of Gene Expression Laboratory, Prince Felipe Research Center, Valencia, Spain
| | - Raymond Scott
- Department of Microbiology and Cell Science, Institute for Food and Agricultural Sciences, University of Florida, Gainesville, FL, USA
| | - Alberto Lerma
- Genomics of Gene Expression Laboratory, Prince Felipe Research Center, Valencia, Spain
| | - Ana Alastrue-Agudo
- Present Address: Human Genetics Department, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
| | - Pablo Bonilla
- Present Address: Human Genetics Department, Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK
| | - Jeremy R B Newman
- Genetics Institute, University of Florida, Gainesville, FL, USA
- Department of Pathology, University of Florida, Gainesville, FL, USA
| | - Shunichi Kosugi
- Genetics Institute, University of Florida, Gainesville, FL, USA
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Wako, Japan
| | - Lauren M McIntyre
- Genetics Institute, University of Florida, Gainesville, FL, USA
- Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL, USA
| | | | - Ana Conesa
- Department of Microbiology and Cell Science, Institute for Food and Agricultural Sciences, University of Florida, Gainesville, FL, USA.
- Genetics Institute, University of Florida, Gainesville, FL, USA.
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15
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Yang LF, Yang F, Zhang FL, Xie YF, Hu ZX, Huang SL, Shao ZM, Li DQ. Discrete functional and mechanistic roles of chromodomain Y-like 2 (CDYL2) transcript variants in breast cancer growth and metastasis. Am J Cancer Res 2020; 10:5242-5258. [PMID: 32373210 PMCID: PMC7196301 DOI: 10.7150/thno.43744] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 03/09/2020] [Indexed: 12/28/2022] Open
Abstract
Rationale: Chromodomain Y-like 2 (CDYL2) is a member of the CDY gene family involved in spermatogenesis, but its role in human cancer has not been reported. Analyses of publicly available databases demonstrate that CDYL2 is abundantly expressed in breast tumors. However, whether CDYL2 is involved in breast cancer progression remains unknown. Methods: Quantitative real-time PCR and immunoblotting assays were used to determine the expression levels of CDYL2 transcript variants in breast cancer cell lines and primary breast tumors. The effect of CDYL2 transcript variants on the malignant phenotypes of breast cancer cells was examined through in vitro and in vivo assays. Immunofluorescent staining, RNA-seq, ATAC-seq, and ChIP-qPCR were used to investigate the underlying mechanisms behind the aforementioned observations. Results: Here we show that CDYL2 generated four transcript variants, named CDYL2a-CDYL2d. CDYL2a and CDYL2b were the predominant variants expressed in breast cancer cell lines and breast tumors and exerted strikingly discrete functions in breast cancer growth and metastasis. CDYL2a was upregulated in the majority of the breast cancer cell lines and tumors, and promoted breast cancer cell proliferation, colony formation in vitro, and tumorigenesis in xenografts. In contrast, CDYL2b was mainly expressed in luminal- and HER2-positive types of breast cancer cell lines and tumors, and suppressed the migratory, invasive, and metastatic potential of breast cancer cells in vitro and in vivo. Mechanistically, CDYL2a partially localized to SC35-positive nuclear speckles and promoted alternative splicing of a subset of target genes, including FIP1L1, NKTR, and ADD3 by exon skipping. Elimination of full-length FIP1L1, NKTR, and ADD3 rescued the impaired cell proliferation through CDYL2a depletion. In contrast, CDYL2b localized to heterochromatin and transcriptionally repressed several metastasis-promoting genes, including HPSE, HLA-F, and SELL. Restoration of HPSE, HLA-F, or SELL expression in CDYL2b-overexpressing cells attenuated the ability of CDYL2b to suppress breast cancer cell migration and invasion. Conclusions: Collectively, these findings establish an isoform-specific function of CDYL2 in breast cancer development and progression and highlight that pharmacological inhibition of the CDYL2a, but not the CDYL2b, isoform may be an effective strategy for breast cancer therapy.
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16
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Li Y, McGrail DJ, Xu J, Mills GB, Sahni N, Yi S. Gene Regulatory Network Perturbation by Genetic and Epigenetic Variation. Trends Biochem Sci 2018; 43:576-592. [PMID: 29941230 DOI: 10.1016/j.tibs.2018.05.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2018] [Revised: 04/25/2018] [Accepted: 05/27/2018] [Indexed: 01/28/2023]
Abstract
Gene regulatory networks underlie biological function and cellular physiology. Alternative splicing (AS) is a fundamental step in gene regulatory networks and plays a key role in development and disease. In addition to the identification of aberrant AS events, an increasing number of studies are focusing on molecular determinants of AS, including genetic and epigenetic regulators. We review here recent efforts to identify various deregulated AS events as well as their molecular determinants that alter biological functions, and discuss clinical features of AS and their druggable potential.
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Affiliation(s)
- Yongsheng Li
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; College of Bioinformatics Science and Technology and Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Harbin 150081, China
| | - Daniel J McGrail
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Juan Xu
- College of Bioinformatics Science and Technology and Bio-Pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Harbin 150081, China
| | - Gordon B Mills
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Nidhi Sahni
- Department of Systems Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Program in Quantitative and Computational Biosciences (QCB), Baylor College of Medicine, Houston, TX 77030, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA; Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Smithville, TX 78957, USA.
| | - Song Yi
- Department of Oncology, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA; Department of Biomedical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX 78712, USA.
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