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• W3204193819 abstract "Single cell RNA sequencing (scRNAseq) is a powerful technique that continues to expand across various biological applications. However, incomplete 3 UTR annotations in less developed or non-model systems can impede single cell analysis resulting in genes that are partially or completely uncounted. Performing scRNAseq with incomplete 3 UTR annotations can impede the identification of cell identities and gene expression patterns and lead to erroneous biological inferences. We demonstrate that performing single cell isoform sequencing (ScISOr-Seq) in tandem with scRNAseq can rapidly improve 3 UTR annotations. Using threespine stickleback fish (Gasterosteus aculeatus), we show that gene models resulting from a minimal embryonic ScISOr-Seq dataset retained 26.1% greater scRNAseq reads than gene models from Ensembl alone. Furthermore, pooling our ScISOr-Seq 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 ScISOr-Seq only dataset. In addition, isoforms identified by ScISOr-Seq included thousands of new splicing variants. The improved gene models obtained using ScISOr-Seq lead to successful identification of cell types and increased the reads identified of many genes in our scRNAseq stickleback dataset. Our work illuminates ScISOr-Seq as a cost-effective and efficient mechanism to rapidly annotate genomes for scRNAseq." @default.
• W3204193819 created "2021-10-11" @default.
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• W3204193819 date "2021-09-28" @default.
• W3204193819 modified "2023-10-15" @default.
• W3204193819 title "Single cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis" @default.
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• W3204193819 doi "https://doi.org/10.1101/2021.09.27.461747" @default.
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