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Gupta P, O’Neill H, Wolvetang E, Chatterjee A, Gupta I. Advances in single-cell long-read sequencing technologies. NAR Genom Bioinform 2024; 6:lqae047. [PMID: 38774511 PMCID: PMC11106032 DOI: 10.1093/nargab/lqae047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 04/18/2024] [Accepted: 04/29/2024] [Indexed: 05/24/2024] Open
Abstract
With an increase in accuracy and throughput of long-read sequencing technologies, they are rapidly being assimilated into the single-cell sequencing pipelines. For transcriptome sequencing, these techniques provide RNA isoform-level information in addition to the gene expression profiles. Long-read sequencing technologies not only help in uncovering complex patterns of cell-type specific splicing, but also offer unprecedented insights into the origin of cellular complexity and thus potentially new avenues for drug development. Additionally, single-cell long-read DNA sequencing enables high-quality assemblies, structural variant detection, haplotype phasing, resolving high-complexity regions, and characterization of epigenetic modifications. Given that significant progress has primarily occurred in single-cell RNA isoform sequencing (scRiso-seq), this review will delve into these advancements in depth and highlight the practical considerations and operational challenges, particularly pertaining to downstream analysis. We also aim to offer a concise introduction to complementary technologies for single-cell sequencing of the genome, epigenome and epitranscriptome. We conclude by identifying certain key areas of innovation that may drive these technologies further and foster more widespread application in biomedical science.
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Affiliation(s)
- Pallavi Gupta
- University of Queensland – IIT Delhi Research Academy, Hauz Khas, New Delhi 110016, India
- Australian Institute of Bioengineering and Nanotechnology (AIBN), The University of Queensland, St Lucia, QLD 4072, Australia
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
| | - Hannah O’Neill
- Department of Pathology, Dunedin School of Medicine, University of Otago, 58 Hanover Street, Dunedin 9054, New Zealand
| | - Ernst J Wolvetang
- Australian Institute of Bioengineering and Nanotechnology (AIBN), The University of Queensland, St Lucia, QLD 4072, Australia
| | - Aniruddha Chatterjee
- Department of Pathology, Dunedin School of Medicine, University of Otago, 58 Hanover Street, Dunedin 9054, New Zealand
| | - Ishaan Gupta
- Department of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India
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2
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Kumari P, Kaur M, Dindhoria K, Ashford B, Amarasinghe SL, Thind AS. Advances in long-read single-cell transcriptomics. Hum Genet 2024:10.1007/s00439-024-02678-x. [PMID: 38787419 DOI: 10.1007/s00439-024-02678-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 05/07/2024] [Indexed: 05/25/2024]
Abstract
Long-read single-cell transcriptomics (scRNA-Seq) is revolutionizing the way we profile heterogeneity in disease. Traditional short-read scRNA-Seq methods are limited in their ability to provide complete transcript coverage, resolve isoforms, and identify novel transcripts. The scRNA-Seq protocols developed for long-read sequencing platforms overcome these limitations by enabling the characterization of full-length transcripts. Long-read scRNA-Seq techniques initially suffered from comparatively poor accuracy compared to short read scRNA-Seq. However, with improvements in accuracy, accessibility, and cost efficiency, long-reads are gaining popularity in the field of scRNA-Seq. This review details the advances in long-read scRNA-Seq, with an emphasis on library preparation protocols and downstream bioinformatics analysis tools.
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Affiliation(s)
- Pallawi Kumari
- Institute of Microbial Technology, Council of Scientific and Industrial Research, Chandigarh, India
| | - Manmeet Kaur
- Institute of Microbial Technology, Council of Scientific and Industrial Research, Chandigarh, India
| | - Kiran Dindhoria
- Institute of Microbial Technology, Council of Scientific and Industrial Research, Chandigarh, India
| | - Bruce Ashford
- Illawarra Shoalhaven Local Health District (ISLHD), NSW Health, Wollongong, NSW, Australia
| | - Shanika L Amarasinghe
- Monash Biomedical Discovery Institute, Monash University, Clayton, VIC, 3800, Australia
- Walter and Eliza Hall Institute of Medical Research, 1G, Royal Parade, Parkville, VIC, 3025, Australia
| | - Amarinder Singh Thind
- Illawarra Shoalhaven Local Health District (ISLHD), NSW Health, Wollongong, NSW, Australia.
- The School of Chemistry and Molecular Bioscience (SCMB), University of Wollongong, Loftus St, Wollongong, NSW, 2500, Australia.
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3
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Wang C, Qiu J, Liu M, Wang Y, Yu Y, Liu H, Zhang Y, Han L. Microfluidic Biochips for Single-Cell Isolation and Single-Cell Analysis of Multiomics and Exosomes. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2401263. [PMID: 38767182 DOI: 10.1002/advs.202401263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 04/26/2024] [Indexed: 05/22/2024]
Abstract
Single-cell multiomic and exosome analyses are potent tools in various fields, such as cancer research, immunology, neuroscience, microbiology, and drug development. They facilitate the in-depth exploration of biological systems, providing insights into disease mechanisms and aiding in treatment. Single-cell isolation, which is crucial for single-cell analysis, ensures reliable cell isolation and quality control for further downstream analyses. Microfluidic chips are small lightweight systems that facilitate efficient and high-throughput single-cell isolation and real-time single-cell analysis on- or off-chip. Therefore, most current single-cell isolation and analysis technologies are based on the single-cell microfluidic technology. This review offers comprehensive guidance to researchers across different fields on the selection of appropriate microfluidic chip technologies for single-cell isolation and analysis. This review describes the design principles, separation mechanisms, chip characteristics, and cellular effects of various microfluidic chips available for single-cell isolation. Moreover, this review highlights the implications of using this technology for subsequent analyses, including single-cell multiomic and exosome analyses. Finally, the current challenges and future prospects of microfluidic chip technology are outlined for multiplex single-cell isolation and multiomic and exosome analyses.
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Affiliation(s)
- Chao Wang
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
| | - Jiaoyan Qiu
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
| | - Mengqi Liu
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
| | - Yihe Wang
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
| | - Yang Yu
- Department of Periodontology, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University, Jinan, 250100, China
| | - Hong Liu
- State Key Laboratory of Crystal Materials, Shandong University, Jinan, 250100, China
| | - Yu Zhang
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
| | - Lin Han
- Institute of Marine Science and Technology, Shandong University, Qingdao, 266237, China
- Shandong Engineering Research Center of Biomarker and Artificial Intelligence Application, Jinan, 250100, China
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4
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Xu Z, Qu HQ, Chan J, Kao C, Hakonarson H, Wang K. Single-Cell Omics for Transcriptome CHaracterization (SCOTCH): isoform-level characterization of gene expression through long-read single-cell RNA sequencing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.29.590597. [PMID: 38746128 PMCID: PMC11092450 DOI: 10.1101/2024.04.29.590597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
The advent of long-read single-cell transcriptome sequencing (lr-scRNA-Seq) represents a significant leap forward in single-cell genomics. With the recent introduction of R10 flowcells by Oxford Nanopore, we propose that previous computational methods designed to handle high sequencing error rates are no longer relevant, and that the prevailing approach using short reads to compile "barcode space" (candidate barcode list) to de-multiplex long reads are no longer necessary. Instead, computational methods should now shift focus on harnessing the unique benefits of long reads to analyze transcriptome complexity. In this context, we introduce a comprehensive suite of computational methods named Single-Cell Omics for Transcriptome CHaracterization (SCOTCH). Our method is compatible with the single-cell library preparation platform from both 10X Genomics and Parse Biosciences, facilitating the analysis of special cell populations, such as neurons, hepatocytes and developing cardiomyocytes. We specifically re-formulated the transcript mapping problem with a compatibility matrix and addressed the multiple-mapping issue using probabilistic inference, which allows the discovery of novel isoforms as well as the detection of differential isoform usage between cell populations. We evaluated SCOTCH through analysis of real data across different combinations of single-cell libraries and sequencing technologies (10X + Illumina, Parse + Illumina, 10X + Nanopore_R9, 10X + Nanopore_R10, Parse + Nanopore_R10), and showed its ability to infer novel biological insights on cell type-specific isoform expression. These datasets enhance the availability of publicly available data for continued development of computational approaches. In summary, SCOTCH allows extraction of more biological insights from the new advancements in single-cell library construction and sequencing technologies, facilitating the examination of transcriptome complexity at the single-cell level.
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Affiliation(s)
- Zhuoran Xu
- Graduate Group in Genomics and Computational Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Hui-Qi Qu
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - Joe Chan
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Charlly Kao
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
| | - Hakon Hakonarson
- The Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, 19104, USA
- Department of Pediatrics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA
| | - Kai Wang
- Raymond G. Perelman Center for Cellular and Molecular Therapeutics, Children’s Hospital of Philadelphia, Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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5
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Yuan CU, Quah FX, Hemberg M. Single-cell and spatial transcriptomics: Bridging current technologies with long-read sequencing. Mol Aspects Med 2024; 96:101255. [PMID: 38368637 DOI: 10.1016/j.mam.2024.101255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/30/2024] [Accepted: 02/07/2024] [Indexed: 02/20/2024]
Abstract
Single-cell technologies have transformed biomedical research over the last decade, opening up new possibilities for understanding cellular heterogeneity, both at the genomic and transcriptomic level. In addition, more recent developments of spatial transcriptomics technologies have made it possible to profile cells in their tissue context. In parallel, there have been substantial advances in sequencing technologies, and the third generation of methods are able to produce reads that are tens of kilobases long, with error rates matching the second generation short reads. Long reads technologies make it possible to better map large genome rearrangements and quantify isoform specific abundances. This further improves our ability to characterize functionally relevant heterogeneity. Here, we show how researchers have begun to combine single-cell, spatial transcriptomics, and long-read technologies, and how this is resulting in powerful new approaches to profiling both the genome and the transcriptome. We discuss the achievements so far, and we highlight remaining challenges and opportunities.
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Affiliation(s)
- Chengwei Ulrika Yuan
- Department of Biochemistry, University of Cambridge, Cambridge, UK; Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Fu Xiang Quah
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Martin Hemberg
- Gene Lay Institute, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
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6
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Beletskiy A, Zolotar A, Fortygina P, Chesnokova E, Uroshlev L, Balaban P, Kolosov P. Downregulation of Ribosomal Protein Genes Is Revealed in a Model of Rat Hippocampal Neuronal Culture Activation with GABA(A)R/GlyRa2 Antagonist Picrotoxin. Cells 2024; 13:383. [PMID: 38474347 DOI: 10.3390/cells13050383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 02/13/2024] [Accepted: 02/20/2024] [Indexed: 03/14/2024] Open
Abstract
Long-read transcriptome sequencing provides us with a convenient tool for the thorough study of biological processes such as neuronal plasticity. Here, we aimed to perform transcriptional profiling of rat hippocampal primary neuron cultures after stimulation with picrotoxin (PTX) to further understand molecular mechanisms of neuronal activation. To overcome the limitations of short-read RNA-Seq approaches, we performed an Oxford Nanopore Technologies MinION-based long-read sequencing and transcriptome assembly of rat primary hippocampal culture mRNA at three time points after the PTX activation. We used a specific approach to exclude uncapped mRNAs during sample preparation. Overall, we found 23,652 novel transcripts in comparison to reference annotations, out of which ~6000 were entirely novel and mostly transposon-derived loci. Analysis of differentially expressed genes (DEG) showed that 3046 genes were differentially expressed, of which 2037 were upregulated and 1009 were downregulated at 30 min after the PTX application, with only 446 and 13 genes differentially expressed at 1 h and 5 h time points, respectively. Most notably, multiple genes encoding ribosomal proteins, with a high basal expression level, were downregulated after 30 min incubation with PTX; we suggest that this indicates redistribution of transcriptional resources towards activity-induced genes. Novel loci and isoforms observed in this study may help us further understand the functional mRNA repertoire in neuronal plasticity processes. Together with other NGS techniques, differential gene expression analysis of sequencing data obtained using MinION platform might provide a simple method to optimize further study of neuronal plasticity.
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Affiliation(s)
- Alexander Beletskiy
- Institute of Higher Nervous Activity and Neurophysiology, The Russian Academy of Sciences, 117485 Moscow, Russia
| | - Anastasia Zolotar
- Institute of Higher Nervous Activity and Neurophysiology, The Russian Academy of Sciences, 117485 Moscow, Russia
| | - Polina Fortygina
- Institute of Higher Nervous Activity and Neurophysiology, The Russian Academy of Sciences, 117485 Moscow, Russia
| | - Ekaterina Chesnokova
- Institute of Higher Nervous Activity and Neurophysiology, The Russian Academy of Sciences, 117485 Moscow, Russia
| | - Leonid Uroshlev
- Institute of Higher Nervous Activity and Neurophysiology, The Russian Academy of Sciences, 117485 Moscow, Russia
| | - Pavel Balaban
- Institute of Higher Nervous Activity and Neurophysiology, The Russian Academy of Sciences, 117485 Moscow, Russia
| | - Peter Kolosov
- Institute of Higher Nervous Activity and Neurophysiology, The Russian Academy of Sciences, 117485 Moscow, Russia
- Engelhardt Institute of Molecular Biology, The Russian Academy of Sciences, 119991 Moscow, Russia
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7
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Shiau CK, Lu L, Kieser R, Fukumura K, Pan T, Lin HY, Yang J, Tong EL, Lee G, Yan Y, Huse JT, Gao R. High throughput single cell long-read sequencing analyses of same-cell genotypes and phenotypes in human tumors. Nat Commun 2023; 14:4124. [PMID: 37433798 PMCID: PMC10336110 DOI: 10.1038/s41467-023-39813-7] [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: 10/19/2022] [Accepted: 06/27/2023] [Indexed: 07/13/2023] Open
Abstract
Single-cell nanopore sequencing of full-length mRNAs transforms single-cell multi-omics studies. However, challenges include high sequencing errors and dependence on short-reads and/or barcode whitelists. To address these, we develop scNanoGPS to calculate same-cell genotypes (mutations) and phenotypes (gene/isoform expressions) without short-read nor whitelist guidance. We apply scNanoGPS onto 23,587 long-read transcriptomes from 4 tumors and 2 cell-lines. Standalone, scNanoGPS deconvolutes error-prone long-reads into single-cells and single-molecules, and simultaneously accesses both phenotypes and genotypes of individual cells. Our analyses reveal that tumor and stroma/immune cells express distinct combination of isoforms (DCIs). In a kidney tumor, we identify 924 DCI genes involved in cell-type-specific functions such as PDE10A in tumor cells and CCL3 in lymphocytes. Transcriptome-wide mutation analyses identify many cell-type-specific mutations including VEGFA mutations in tumor cells and HLA-A mutations in immune cells, highlighting the critical roles of different mutant populations in tumors. Together, scNanoGPS facilitates applications of single-cell long-read sequencing technologies.
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Affiliation(s)
- Cheng-Kai Shiau
- Department of Biochemistry and Molecular Genetics, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Cancer Genomics, Robert H. Lurie Cancer Center, Northwestern University, Chicago, IL, 60611, USA
| | - Lina Lu
- Department of Biochemistry and Molecular Genetics, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Cancer Genomics, Robert H. Lurie Cancer Center, Northwestern University, Chicago, IL, 60611, USA
| | - Rachel Kieser
- Center for RNA Therapeutics, Houston Methodist Research Institute, Houston, TX, 77030, USA
| | - Kazutaka Fukumura
- Department of Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Timothy Pan
- Department of Biochemistry and Molecular Genetics, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Cancer Genomics, Robert H. Lurie Cancer Center, Northwestern University, Chicago, IL, 60611, USA
- The Driskill Graduate Program, Northwestern University, Chicago, IL, 60611, USA
| | - Hsiao-Yun Lin
- Department of Biochemistry and Molecular Genetics, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Cancer Genomics, Robert H. Lurie Cancer Center, Northwestern University, Chicago, IL, 60611, USA
| | - Jie Yang
- Department of Radiation Oncology, New York University Langone School of Medicine, New York, NY, 100167, USA
| | - Eric L Tong
- School of Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - GaHyun Lee
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Yuanqing Yan
- Department of Surgery, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Jason T Huse
- Department of Pathology and Translational Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Ruli Gao
- Department of Biochemistry and Molecular Genetics, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
- Center for Cancer Genomics, Robert H. Lurie Cancer Center, Northwestern University, Chicago, IL, 60611, USA.
- The Driskill Graduate Program, Northwestern University, Chicago, IL, 60611, USA.
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8
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Joglekar A, Foord C, Jarroux J, Pollard S, Tilgner HU. From words to complete phrases: insight into single-cell isoforms using short and long reads. Transcription 2023; 14:92-104. [PMID: 37314295 PMCID: PMC10807471 DOI: 10.1080/21541264.2023.2213514] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Revised: 04/24/2023] [Accepted: 05/07/2023] [Indexed: 06/15/2023] Open
Abstract
The profiling of gene expression patterns to glean biological insights from single cells has become commonplace over the last few years. However, this approach overlooks the transcript contents that can differ between individual cells and cell populations. In this review, we describe early work in the field of single-cell short-read sequencing as well as full-length isoforms from single cells. We then describe recent work in single-cell long-read sequencing wherein some transcript elements have been observed to work in tandem. Based on earlier work in bulk tissue, we motivate the study of combination patterns of other RNA variables. Given that we are still blind to some aspects of isoform biology, we suggest possible future avenues such as CRISPR screens which can further illuminate the function of RNA variables in distinct cell populations.
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Affiliation(s)
- Anoushka Joglekar
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Careen Foord
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Julien Jarroux
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Shaun Pollard
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
| | - Hagen U Tilgner
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
- Center for Neurogenetics, Weill Cornell Medicine, New York, NY, USA
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9
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You Y, Prawer YDJ, De Paoli-Iseppi R, Hunt CPJ, Parish CL, Shim H, Clark MB. Identification of cell barcodes from long-read single-cell RNA-seq with BLAZE. Genome Biol 2023; 24:66. [PMID: 37024980 PMCID: PMC10077662 DOI: 10.1186/s13059-023-02907-y] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 03/23/2023] [Indexed: 04/08/2023] Open
Abstract
Long-read single-cell RNA sequencing (scRNA-seq) enables the quantification of RNA isoforms in individual cells. However, long-read scRNA-seq using the Oxford Nanopore platform has largely relied upon matched short-read data to identify cell barcodes. We introduce BLAZE, which accurately and efficiently identifies 10x cell barcodes using only nanopore long-read scRNA-seq data. BLAZE outperforms the existing tools and provides an accurate representation of the cells present in long-read scRNA-seq when compared to matched short reads. BLAZE simplifies long-read scRNA-seq while improving the results, is compatible with downstream tools accepting a cell barcode file, and is available at https://github.com/shimlab/BLAZE .
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Affiliation(s)
- Yupei You
- School of Mathematics and Statistics/Melbourne Integrative Genomics, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Yair D J Prawer
- Centre for Stem Cell Systems, Department of Anatomy and Physiology, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Ricardo De Paoli-Iseppi
- Centre for Stem Cell Systems, Department of Anatomy and Physiology, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Cameron P J Hunt
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Clare L Parish
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3010, Australia
| | - Heejung Shim
- School of Mathematics and Statistics/Melbourne Integrative Genomics, The University of Melbourne, Parkville, VIC, 3010, Australia.
| | - Michael B Clark
- Centre for Stem Cell Systems, Department of Anatomy and Physiology, The University of Melbourne, Parkville, VIC, 3010, Australia.
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10
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Spatial transcriptomics reveals niche-specific enrichment and vulnerabilities of radial glial stem-like cells in malignant gliomas. Nat Commun 2023; 14:1028. [PMID: 36823172 PMCID: PMC9950149 DOI: 10.1038/s41467-023-36707-6] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 02/14/2023] [Indexed: 02/25/2023] Open
Abstract
Diffuse midline glioma-H3K27M mutant (DMG) and glioblastoma (GBM) are the most lethal brain tumors that primarily occur in pediatric and adult patients, respectively. Both tumors exhibit significant heterogeneity, shaped by distinct genetic/epigenetic drivers, transcriptional programs including RNA splicing, and microenvironmental cues in glioma niches. However, the spatial organization of cellular states and niche-specific regulatory programs remain to be investigated. Here, we perform a spatial profiling of DMG and GBM combining short- and long-read spatial transcriptomics, and single-cell transcriptomic datasets. We identify clinically relevant transcriptional programs, RNA isoform diversity, and multi-cellular ecosystems across different glioma niches. We find that while the tumor core enriches for oligodendrocyte precursor-like cells, radial glial stem-like (RG-like) cells are enriched in the neuron-rich invasive niche in both DMG and GBM. Further, we identify niche-specific regulatory programs for RG-like cells, and functionally confirm that FAM20C mediates invasive growth of RG-like cells in a neuron-rich microenvironment in a human neural stem cell derived orthotopic DMG model. Together, our results provide a blueprint for understanding the spatial architecture and niche-specific vulnerabilities of DMG and GBM.
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11
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Boileau E, Li X, Naarmann-de Vries IS, Becker C, Casper R, Altmüller J, Leuschner F, Dieterich C. Full-Length Spatial Transcriptomics Reveals the Unexplored Isoform Diversity of the Myocardium Post-MI. Front Genet 2022; 13:912572. [PMID: 35937994 PMCID: PMC9354982 DOI: 10.3389/fgene.2022.912572] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 06/23/2022] [Indexed: 11/13/2022] Open
Abstract
We introduce Single-cell Nanopore Spatial Transcriptomics (scNaST), a software suite to facilitate the analysis of spatial gene expression from second- and third-generation sequencing, allowing to generate a full-length near-single-cell transcriptional landscape of the tissue microenvironment. Taking advantage of the Visium Spatial platform, we adapted a strategy recently developed to assign barcodes to long-read single-cell sequencing data for spatial capture technology. Here, we demonstrate our workflow using four short axis sections of the mouse heart following myocardial infarction. We constructed a de novo transcriptome using long-read data, and successfully assigned 19,794 transcript isoforms in total, including clinically-relevant, but yet uncharacterized modes of transcription, such as intron retention or antisense overlapping transcription. We showed a higher transcriptome complexity in the healthy regions, and identified intron retention as a mode of transcription associated with the infarct area. Our data revealed a clear regional isoform switching among differentially used transcripts for genes involved in cardiac muscle contraction and tissue morphogenesis. Molecular signatures involved in cardiac remodeling integrated with morphological context may support the development of new therapeutics towards the treatment of heart failure and the reduction of cardiac complications.
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Affiliation(s)
- Etienne Boileau
- Section of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology, Heidelberg, Germany
- Department of Internal Medicine III (Cardiology, Angiology, and Pneumology), University Hospital Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research) Partner Site Heidelberg/Mannheim, Heidelberg, Germany
| | - Xue Li
- Department of Internal Medicine III (Cardiology, Angiology, and Pneumology), University Hospital Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research) Partner Site Heidelberg/Mannheim, Heidelberg, Germany
| | - Isabel S Naarmann-de Vries
- Section of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology, Heidelberg, Germany
- Department of Internal Medicine III (Cardiology, Angiology, and Pneumology), University Hospital Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research) Partner Site Heidelberg/Mannheim, Heidelberg, Germany
| | - Christian Becker
- Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany
| | - Ramona Casper
- Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany
| | - Janine Altmüller
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Max Delbrück Center for Molecular Medicine, Berlin, Germany
| | - Florian Leuschner
- Department of Internal Medicine III (Cardiology, Angiology, and Pneumology), University Hospital Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research) Partner Site Heidelberg/Mannheim, Heidelberg, Germany
| | - Christoph Dieterich
- Section of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology, Heidelberg, Germany
- Department of Internal Medicine III (Cardiology, Angiology, and Pneumology), University Hospital Heidelberg, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research) Partner Site Heidelberg/Mannheim, Heidelberg, Germany
- *Correspondence: Christoph Dieterich,
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Conrad T, Altmüller J. Single cell- and spatial 'Omics revolutionize physiology. Acta Physiol (Oxf) 2022; 235:e13848. [PMID: 35656634 DOI: 10.1111/apha.13848] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Revised: 04/24/2022] [Accepted: 05/27/2022] [Indexed: 11/29/2022]
Abstract
Single cell multi- 'Omics and Spatial Transcriptomics are prominent technological highlights of recent years, and both fields still witness a ceaseless firework of novel approaches for high resolution profiling of additional omics layers. As all life processes in organs and organisms are based on the functions of their fundamental building blocks, the individual cells and their interactions, these methods are of utmost worth for the study of physiology in health and disease. Recent discoveries on embryonic development, tumor immunology, the detailed cellular composition and function of complex tissues like for example the kidney or the brain, different roles of the same cell type in different organs, the oncogenic program of individual tumor entities, or the architecture of immunopathology in infected tissue are based on single cell and spatial transcriptomics experiments. In this review, we will give a broad overview of technological concepts for single cell and spatial analysis, showing both advantages and limitations, and illustrate their impact with some particularly impressive case studies.
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Affiliation(s)
- Thomas Conrad
- Genomics Technology Platform Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) Berlin Germany
| | - Janine Altmüller
- Genomics Technology Platform Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) Berlin Germany
- Core Facility Genomics Berlin Institute of Health at Charité ‐ Universitätsmedizin Berlin Berlin Germany
- Center for Molecular Medicine Cologne (CMMC) Cologne Germany
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Tian L, Jabbari JS, Thijssen R, Gouil Q, Amarasinghe SL, Voogd O, Kariyawasam H, Du MRM, Schuster J, Wang C, Su S, Dong X, Law CW, Lucattini A, Prawer YDJ, Collar-Fernández C, Chung JD, Naim T, Chan A, Ly CH, Lynch GS, Ryall JG, Anttila CJA, Peng H, Anderson MA, Flensburg C, Majewski I, Roberts AW, Huang DCS, Clark MB, Ritchie ME. Comprehensive characterization of single-cell full-length isoforms in human and mouse with long-read sequencing. Genome Biol 2021; 22:310. [PMID: 34763716 PMCID: PMC8582192 DOI: 10.1186/s13059-021-02525-6] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 10/21/2021] [Indexed: 12/11/2022] Open
Abstract
A modified Chromium 10x droplet-based protocol that subsamples cells for both short-read and long-read (nanopore) sequencing together with a new computational pipeline (FLAMES) is developed to enable isoform discovery, splicing analysis, and mutation detection in single cells. We identify thousands of unannotated isoforms and find conserved functional modules that are enriched for alternative transcript usage in different cell types and species, including ribosome biogenesis and mRNA splicing. Analysis at the transcript level allows data integration with scATAC-seq on individual promoters, improved correlation with protein expression data, and linked mutations known to confer drug resistance to transcriptome heterogeneity.
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Affiliation(s)
- Luyi Tian
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia.
| | - Jafar S Jabbari
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Australian Genome Research Facility, Victorian Comprehensive Cancer Centre, Melbourne, VIC, Australia
| | - Rachel Thijssen
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
| | - Quentin Gouil
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
| | - Shanika L Amarasinghe
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
| | - Oliver Voogd
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Hasaru Kariyawasam
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Mei R M Du
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Jakob Schuster
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Changqing Wang
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Shian Su
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
| | - Xueyi Dong
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
| | - Charity W Law
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
| | - Alexis Lucattini
- Australian Genome Research Facility, Victorian Comprehensive Cancer Centre, Melbourne, VIC, Australia
| | - Yair David Joseph Prawer
- Centre for Stem Cell Systems, Department of Anatomy and Neuroscience, The University of Melbourne, Parkville, VIC, Australia
| | | | - Jin D Chung
- Centre for Muscle Research, Department of Physiology, The University of Melbourne, Melbourne, VIC, Australia
| | - Timur Naim
- Centre for Muscle Research, Department of Physiology, The University of Melbourne, Melbourne, VIC, Australia
| | - Audrey Chan
- Centre for Muscle Research, Department of Physiology, The University of Melbourne, Melbourne, VIC, Australia
| | - Chi Hai Ly
- Centre for Muscle Research, Department of Physiology, The University of Melbourne, Melbourne, VIC, Australia
- Present address: Department of Neurology, Stanford University, Stanford, CA, USA
| | - Gordon S Lynch
- Centre for Muscle Research, Department of Physiology, The University of Melbourne, Melbourne, VIC, Australia
| | - James G Ryall
- Centre for Muscle Research, Department of Physiology, The University of Melbourne, Melbourne, VIC, Australia
- Present address: VOW, North Parramatta, NSW, Australia
| | - Casey J A Anttila
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
| | - Hongke Peng
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
| | - Mary Ann Anderson
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
- Clinical Haematology, Peter MacCallum Cancer Centre and Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Christoffer Flensburg
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
| | - Ian Majewski
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
| | - Andrew W Roberts
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
- Clinical Haematology, Peter MacCallum Cancer Centre and Royal Melbourne Hospital, Melbourne, VIC, Australia
- Centre for Cancer Research, University of Melbourne, Melbourne, VIC, Australia
- Victorian Comprehensive Cancer Centre, Melbourne, VIC, Australia
| | - David C S Huang
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia
| | - Michael B Clark
- Centre for Stem Cell Systems, Department of Anatomy and Neuroscience, The University of Melbourne, Parkville, VIC, Australia
| | - Matthew E Ritchie
- The Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.
- Department of Medical Biology, The University of Melbourne, Parkville, VIC, Australia.
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