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Single-cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis
Single-cell RNA sequencing is a powerful technique that continues to expand across various biological applications. However, incomplete 3′-UTR annotations can impede single-cell analysis resulting in genes that are partially or completely uncounted. Performing single-cell RNA sequencing with incompl...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8893252/ https://www.ncbi.nlm.nih.gov/pubmed/35143654 http://dx.doi.org/10.1093/genetics/iyac017 |
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author | Healey, Hope M Bassham, Susan Cresko, William A |
author_facet | Healey, Hope M Bassham, Susan Cresko, William A |
author_sort | Healey, Hope M |
collection | PubMed |
description | Single-cell RNA sequencing is a powerful technique that continues to expand across various biological applications. However, incomplete 3′-UTR annotations can impede single-cell analysis resulting in genes that are partially or completely uncounted. Performing single-cell RNA sequencing with incomplete 3′-UTR annotations can hinder the identification of cell identities and gene expression patterns and lead to erroneous biological inferences. We demonstrate that performing single-cell isoform sequencing in tandem with single-cell RNA sequencing can rapidly improve 3′-UTR annotations. Using threespine stickleback fish (Gasterosteus aculeatus), we show that gene models resulting from a minimal embryonic single-cell isoform sequencing dataset retained 26.1% greater single-cell RNA sequencing reads than gene models from Ensembl alone. Furthermore, pooling our single-cell sequencing isoforms with a previously published adult bulk Iso-Seq dataset from stickleback, and merging the annotation with the Ensembl gene models, resulted in a marginal improvement (+0.8%) over the single-cell isoform sequencing only dataset. In addition, isoforms identified by single-cell isoform sequencing included thousands of new splicing variants. The improved gene models obtained using single-cell isoform sequencing led to successful identification of cell types and increased the reads identified of many genes in our single-cell RNA sequencing stickleback dataset. Our work illuminates single-cell isoform sequencing as a cost-effective and efficient mechanism to rapidly annotate genomes for single-cell RNA sequencing. |
format | Online Article Text |
id | pubmed-8893252 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-88932522022-03-21 Single-cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis Healey, Hope M Bassham, Susan Cresko, William A Genetics Investigation Single-cell RNA sequencing is a powerful technique that continues to expand across various biological applications. However, incomplete 3′-UTR annotations can impede single-cell analysis resulting in genes that are partially or completely uncounted. Performing single-cell RNA sequencing with incomplete 3′-UTR annotations can hinder the identification of cell identities and gene expression patterns and lead to erroneous biological inferences. We demonstrate that performing single-cell isoform sequencing in tandem with single-cell RNA sequencing can rapidly improve 3′-UTR annotations. Using threespine stickleback fish (Gasterosteus aculeatus), we show that gene models resulting from a minimal embryonic single-cell isoform sequencing dataset retained 26.1% greater single-cell RNA sequencing reads than gene models from Ensembl alone. Furthermore, pooling our single-cell sequencing isoforms with a previously published adult bulk Iso-Seq dataset from stickleback, and merging the annotation with the Ensembl gene models, resulted in a marginal improvement (+0.8%) over the single-cell isoform sequencing only dataset. In addition, isoforms identified by single-cell isoform sequencing included thousands of new splicing variants. The improved gene models obtained using single-cell isoform sequencing led to successful identification of cell types and increased the reads identified of many genes in our single-cell RNA sequencing stickleback dataset. Our work illuminates single-cell isoform sequencing as a cost-effective and efficient mechanism to rapidly annotate genomes for single-cell RNA sequencing. Oxford University Press 2022-02-10 /pmc/articles/PMC8893252/ /pubmed/35143654 http://dx.doi.org/10.1093/genetics/iyac017 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Investigation Healey, Hope M Bassham, Susan Cresko, William A Single-cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis |
title | Single-cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis |
title_full | Single-cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis |
title_fullStr | Single-cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis |
title_full_unstemmed | Single-cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis |
title_short | Single-cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis |
title_sort | single-cell iso-sequencing enables rapid genome annotation for scrnaseq analysis |
topic | Investigation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8893252/ https://www.ncbi.nlm.nih.gov/pubmed/35143654 http://dx.doi.org/10.1093/genetics/iyac017 |
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