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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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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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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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Shi W, Tang J, Xiang J. Therapeutic strategies for aberrant splicing in cancer and genetic disorders. Clin Genet 2024; 105:345-354. [PMID: 38165092 DOI: 10.1111/cge.14478] [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: 09/21/2023] [Revised: 12/12/2023] [Accepted: 12/21/2023] [Indexed: 01/03/2024]
Abstract
Accurate pre-mRNA splicing is essential for proper protein translation; however, aberrant splicing is commonly observed in the context of cancer and genetic disorders. Notably, in genetic diseases, these splicing abnormalities often play a pivotal role. Substantial challenges persist in accurately identifying and classifying disease-induced aberrant splicing, as well as in development of targeted therapeutic strategies. In this review, we examine prevalent forms of aberrant splicing and explore potential therapeutic approaches aimed at addressing these splicing-related diseases. This summary contributes to a deeper understanding of the complexities about aberrant splicing and provide a foundation for the development of effective therapeutic interventions in the field of genetic disorders and cancer.
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Affiliation(s)
- Wenhua Shi
- Cancer Research Institute, School of Basic Medical Science, Central South University, Changsha, Hunan, China
- Hunan Key laboratory of Early Diagnosis and Precise Treatment of Lung Cancer, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- NHC Key Laboratory of Carcinogenesis and the Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Jingqun Tang
- Hunan Key laboratory of Early Diagnosis and Precise Treatment of Lung Cancer, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Thoracic Surgery, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Juanjuan Xiang
- Cancer Research Institute, School of Basic Medical Science, Central South University, Changsha, Hunan, China
- Hunan Key laboratory of Early Diagnosis and Precise Treatment of Lung Cancer, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
- NHC Key Laboratory of Carcinogenesis and the Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Xiangya Hospital, Central South University, Changsha, Hunan, China
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Jones EF, Howton TC, Flanary VL, Clark AD, Lasseigne BN. Long-read RNA sequencing identifies region- and sex-specific C57BL/6J mouse brain mRNA isoform expression and usage. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.11.575219. [PMID: 38260631 PMCID: PMC10802568 DOI: 10.1101/2024.01.11.575219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Alternative splicing (AS) contributes to the biological heterogeneity between species, sexes, tissues, and cell types. Many diseases are either caused by alterations in AS or by alterations to AS. Therefore, measuring AS accurately and efficiently is critical for assessing molecular phenotypes, including those associated with disease. Long-read sequencing enables more accurate quantification of differentially spliced isoform expression than short-read sequencing approaches, and third-generation platforms facilitate high-throughput experiments. To assess differences in AS across the cerebellum, cortex, hippocampus, and striatum by sex, we generated and analyzed Oxford Nanopore Technologies (ONT) long-read RNA sequencing (lrRNA-Seq) C57BL/6J mouse brain cDNA libraries. From >85 million reads that passed quality control metrics, we calculated differential gene expression (DGE), differential transcript expression (DTE), and differential transcript usage (DTU) across brain regions and by sex. We found significant DGE, DTE, and DTU across brain regions and that the cerebellum had the most differences compared to the other three regions. Additionally, we found region-specific differential splicing between sexes, with the most sex differences in DTU in the cortex and no DTU in the hippocampus. We also report on two distinct patterns of sex DTU we observed, sex-divergent and sex-specific, that could potentially help explain sex differences in the prevalence and prognosis of various neurological and psychiatric disorders in future studies. Finally, we built a Shiny web application for researchers to explore the data further. Our study provides a resource for the community; it underscores the importance of AS in biological heterogeneity and the utility of long-read sequencing to better understand AS in the brain.
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Affiliation(s)
- Emma F. Jones
- Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Timothy C. Howton
- Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Victoria L. Flanary
- Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Amanda D. Clark
- Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, United States of America
| | - Brittany N. Lasseigne
- Department of Cell, Developmental and Integrative Biology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, United States of America
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Saglam-Metiner P, Yildirim E, Dincer C, Basak O, Yesil-Celiktas O. Humanized brain organoids-on-chip integrated with sensors for screening neuronal activity and neurotoxicity. Mikrochim Acta 2024; 191:71. [PMID: 38168828 DOI: 10.1007/s00604-023-06165-4] [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: 10/10/2023] [Accepted: 12/21/2023] [Indexed: 01/05/2024]
Abstract
The complex structure and function of the human central nervous system that develops from the neural tube made in vitro modeling quite challenging until the discovery of brain organoids. Human-induced pluripotent stem cells-derived brain organoids offer recapitulation of the features of early human neurodevelopment in vitro, including the generation, proliferation, and differentiation into mature neurons and micro-macroglial cells, as well as the complex interactions among these diverse cell types of the developing brain. Recent advancements in brain organoids, microfluidic systems, real-time sensing technologies, and their cutting-edge integrated use provide excellent models and tools for emulation of fundamental neurodevelopmental processes, the pathology of neurological disorders, personalized transplantation therapy, and high-throughput neurotoxicity testing by bridging the gap between two-dimensional models and the complex three-dimensional environment in vivo. In this review, we summarize how bioengineering approaches are applied to mitigate the limitations of brain organoids for biomedical and clinical research. We further provide an extensive overview and future perspectives of the humanized brain organoids-on-chip platforms with integrated sensors toward brain organoid intelligence and biocomputing studies. Such approaches might pave the way for increasing approvable clinical applications by solving their current limitations.
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Affiliation(s)
- Pelin Saglam-Metiner
- Department of Bioengineering, Faculty of Engineering, Ege University, Izmir, Turkey
- Department of Translational Neuroscience, Division of Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Ender Yildirim
- Department of Mechanical Engineering, Middle East Technical University, Ankara, Turkey
- ODTÜ MEMS Center, Ankara, Turkey
| | - Can Dincer
- Department of Microsystems Engineering (IMTEK), University of Freiburg, Freiburg, Germany
- FIT Freiburg Center for Interactive Materials and Bioinspired Technologies, University of Freiburg, Freiburg, Germany
| | - Onur Basak
- Department of Translational Neuroscience, Division of Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Ozlem Yesil-Celiktas
- Department of Bioengineering, Faculty of Engineering, Ege University, Izmir, Turkey.
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