Single-cell isoform RNA sequencing (ScISOr-Seq) across thousands of cells reveals isoforms of cerebellar cell types

Gupta, Ishaan; Collier, Paul; Haase, Bettina; Mahfouz, Ahmed; Joglekar, Anoushka; Floyd, Taylor; Koopmans, Frank; Barres, Ben A.; Smit, August B.; Sloan, Steven A.; Luo, Wenjie; Fédrigo, Olivier; Ross, M. Elizabeth; Tilgner, Hagen

doi:10.1101/364950

Cited by 6 publications

(12 citation statements)

References 42 publications

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“…This is better than previously published approaches, but not ideal [27,31]. Increasing accuracy to the level of PacBio Iso-Seq [23,24,42] could increase this number significantly. Paired with the higher throughput we can achieve by optimizing raw read to consensus read conversion as we have previously shown [43], future experiments could only retain UMIs which were observed more than once, similar to how we analyze Illumina data (see the "Methods" section).…”

Section: Discussionmentioning

confidence: 87%

“…Instead of sequencing transcript fragments, long-read sequencing methods in the form of Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) are now capable of sequencing comprehensive full-length transcriptomes [16][17][18][19]. These methods have now been used to analyze single-cell cDNA pools generated by different methods, both well- [20][21][22] and droplet-based [23][24][25][26][27], enriching the information we can extract from single-cell experiments. However, for the analysis of high-throughput droplet-based experiments with long reads, short-read data are still required for interpreting experimental data [27,28] or enabling the identification of cellular and molecular identifiers in low-accuracy ONT reads [27].…”

Section: Introductionmentioning

confidence: 99%

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Single-cell isoform analysis in human immune cells

Volden

Vollmers

2022

Genome Biol

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High-throughput single-cell analysis today is facilitated by protocols like the 10X Genomics platform or Drop-Seq which generate cDNA pools in which the origin of a transcript is encoded at its 5′ or 3′ end. Here, we used R2C2 to sequence and demultiplex 12 million full-length cDNA molecules generated by the 10X Genomics platform from ~3000 peripheral blood mononuclear cells. We use these reads, independent from Illumina data, to identify B cell, T cell, and monocyte clusters and generate isoform-level transcriptomes for cells and cell types. Finally, we extract paired adaptive immune receptor sequences unique to each T and B cell.

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Section: Discussionmentioning

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Single-cell isoform analysis in human immune cells

Volden

Vollmers

2022

Genome Biol

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“…Instead of sequencing transcript fragments, long-read sequencing methods in the form of Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) are now capable of sequencing comprehensive full-length transcriptomes [16][17][18][19]. These methods have now been used to analyze single cell cDNA pools generated by different methods, both well- [20][21][22] and droplet-based [23][24][25], enriching the information we can extract from single cells experiments. However, for the analysis of high-throughput droplet-based experiments with long reads, short-read data are still required for interpreting experimental data [26] or enabling the identification of cellular and molecular identifiers in low-accuracy ONT reads [24].…”

Section: Introductionmentioning

confidence: 99%

Highly Multiplexed Single-Cell Full-Length cDNA Sequencing of human immune cells with 10X Genomics and R2C2

Volden

Vollmers

2020

Preprint

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Single cell transcriptome analysis elucidates facets of cell biology that have been previously out of reach. However, the high-throughput analysis of thousands of single cell transcriptomes has been limited by sample preparation and sequencing technology. High-throughput single cell analysis today is facilitated by protocols like the 10X Genomics platform or Drop-Seq which generate cDNA pools in which the origin of a transcript is encoded at its 5' or 3' end. These cDNA pools are currently analyzed by short read Illumina sequencing which can identify the cellular origin of a transcript and what gene it was transcribed from. However, these methods fail to retrieve isoform information. In principle, cDNA pools prepared using these approaches can be analyzed with Pacific Biosciences and Oxford Nanopore long-read sequencers to retrieve isoform information but all current implementations rely heavily on Illumina short-reads for the analysis in addition to long reads. Here, we used R2C2 to sequence and demultiplex 9 million full-length cDNA molecules generated by the 10X Chromium platform from ~3000 peripheral blood mononuclear cells (PBMCs). We used these reads to -independent from Illumina data -cluster cells into B cells, T cells, and Monocytes and generate isoform-level transcriptomes for these cell-types. We also generated isoform-level transcriptomes for all single cells and used this information to identify a wide range of isoform diversity between genes. Finally, we also designed a computational workflow to extract paired adaptive immune receptor -T cell receptor and B cell receptor (TCR and BCR)sequences unique to each T and B cell. This work represents a new, simple, and powerful approach thatusing a single sequencing method -can extract an unprecedented amount of information from thousands of single cells./

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“…In recent years, long-read RNA sequencing technologies have emerged as a powerful alternative for transcript-level identification and quantification by going beyond the level of exon-usage to simultaneously identify novel isoforms with alternative TSSs, TESs, and exon combinations. Furthermore, long-read RNA-seq has been adapted to single-cell sequencing using high-throughput microfluidics-based methods (1,2,3,4). Some of these studies sequenced the same cells with both PacBio and Illumina technologies and relied on short-read gene quantification to cluster and characterize cell types, while using the long reads to identify full-length isoforms (2,4).…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, long-read RNA-seq has been adapted to single-cell sequencing using high-throughput microfluidics-based methods (1,2,3,4). Some of these studies sequenced the same cells with both PacBio and Illumina technologies and relied on short-read gene quantification to cluster and characterize cell types, while using the long reads to identify full-length isoforms (2,4). However, these prior approaches used expensive equipment, such as microfluidics platforms, and/or applied very high amounts of long-read sequencing whose expense limits routine and extensive application.…”

Section: Introductionmentioning

confidence: 99%

Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq

Rebboah

Reese

Williams

et al. 2021

Preprint

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Alternative RNA isoforms are defined by promoter choice, alternative splicing, and polyA site selection. Although differential isoform expression is known to play a large regulatory role in eukaryotes, it has proved challenging to study with standard short-read RNA-seq because of the uncertainties it leaves about the full-length structure and precise termini of transcripts. The rise in throughput and quality of long-read sequencing now makes it possible, in principle, to unambiguously identify most transcript isoforms from beginning to end. However, its application to single-cell RNA-seq has been limited by throughput and expense. Here, we develop and characterize long-read Split-seq (LR-Split-seq), which uses a combinatorial barcoding-based method for sequencing single cells and nuclei with long reads. We show that LR-Split-seq can associate isoforms with cell types with relative economy and design flexibility. We characterize LR-Split-seq for whole cells and nuclei by using the well-studied mouse C2C12 system in which mononucleated myoblast cells differentiate and fuse into multinucleated myotubes. We show that the overall results are reproducible when comparing long- and short-read data from the same cell or nucleus. We find substantial evidence of differential isoform expression during differentiation including alternative transcription start site (TSS) usage. We integrate the resulting isoform expression dynamics with snATAC-seq chromatin accessibility to validate TSS-driven isoform choices. LR-Split-seq provides an affordable method for identifying cluster-specific isoforms in single cells that can be further quantified with companion deep short-read scRNA-seq from the same cell populations.

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Single-cell isoform RNA sequencing (ScISOr-Seq) across thousands of cells reveals isoforms of cerebellar cell types

Cited by 6 publications

References 42 publications

Single-cell isoform analysis in human immune cells

Single-cell isoform analysis in human immune cells

Highly Multiplexed Single-Cell Full-Length cDNA Sequencing of human immune cells with 10X Genomics and R2C2

Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq

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