Single cell Iso-Sequencing enables rapid genome annotation for scRNAseq analysis

Single cell RNA sequencing (scRNAseq) 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 scRNAseq 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
(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.