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Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq
The rise in throughput and quality of long-read sequencing should allow unambiguous identification of full-length transcript isoforms. 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), whic...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495978/ https://www.ncbi.nlm.nih.gov/pubmed/34620214 http://dx.doi.org/10.1186/s13059-021-02505-w |
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author | Rebboah, Elisabeth Reese, Fairlie Williams, Katherine Balderrama-Gutierrez, Gabriela McGill, Cassandra Trout, Diane Rodriguez, Isaryhia Liang, Heidi Wold, Barbara J. Mortazavi, Ali |
author_facet | Rebboah, Elisabeth Reese, Fairlie Williams, Katherine Balderrama-Gutierrez, Gabriela McGill, Cassandra Trout, Diane Rodriguez, Isaryhia Liang, Heidi Wold, Barbara J. Mortazavi, Ali |
author_sort | Rebboah, Elisabeth |
collection | PubMed |
description | The rise in throughput and quality of long-read sequencing should allow unambiguous identification of full-length transcript isoforms. 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 combinatorial barcoding to sequence single cells with long reads. Applied to the C2C12 myogenic system, LR-split-seq associates isoforms to cell types with relative economy and design flexibility. We find widespread evidence of changing isoform expression during differentiation including alternative transcription start sites (TSS) and/or alternative internal exon usage. LR-Split-seq provides an affordable method for identifying cluster-specific isoforms in single cells. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02505-w. |
format | Online Article Text |
id | pubmed-8495978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-84959782021-10-07 Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq Rebboah, Elisabeth Reese, Fairlie Williams, Katherine Balderrama-Gutierrez, Gabriela McGill, Cassandra Trout, Diane Rodriguez, Isaryhia Liang, Heidi Wold, Barbara J. Mortazavi, Ali Genome Biol Method The rise in throughput and quality of long-read sequencing should allow unambiguous identification of full-length transcript isoforms. 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 combinatorial barcoding to sequence single cells with long reads. Applied to the C2C12 myogenic system, LR-split-seq associates isoforms to cell types with relative economy and design flexibility. We find widespread evidence of changing isoform expression during differentiation including alternative transcription start sites (TSS) and/or alternative internal exon usage. LR-Split-seq provides an affordable method for identifying cluster-specific isoforms in single cells. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-021-02505-w. BioMed Central 2021-10-07 /pmc/articles/PMC8495978/ /pubmed/34620214 http://dx.doi.org/10.1186/s13059-021-02505-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Method Rebboah, Elisabeth Reese, Fairlie Williams, Katherine Balderrama-Gutierrez, Gabriela McGill, Cassandra Trout, Diane Rodriguez, Isaryhia Liang, Heidi Wold, Barbara J. Mortazavi, Ali Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq |
title | Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq |
title_full | Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq |
title_fullStr | Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq |
title_full_unstemmed | Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq |
title_short | Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq |
title_sort | mapping and modeling the genomic basis of differential rna isoform expression at single-cell resolution with lr-split-seq |
topic | Method |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495978/ https://www.ncbi.nlm.nih.gov/pubmed/34620214 http://dx.doi.org/10.1186/s13059-021-02505-w |
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