Oxford Global presents NextGen Omics US

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Abstract

RNA sequencing (RNA-seq) is a powerful way to investigate transcriptional highs and lows, allelic origins, and isoform preferences in the transcriptome that can underlie key biological states. One current limitation of single-cell RNA-seq methodologies is either the absence of unique molecular identifiers (UMIs), or the inability to maintain the yield, sensitivity, and reproducibility when UMIs are employed. To address these problems, we developed a new SMART-Seq method that includes the use of unique molecular identifiers (UMIs) for RNA counting to allow for allelic and transcript isoform resolution analysis. We benchmarked the new SMART-Seq method against the existing SMART-Seq v4 Ultra Low Input RNA Kit for Sequencing (SSv4) and the Smart-seq 2 (SS2) homebrew method. The inclusion of UMIs did not compromise data quality and led to superior sensitivity compared to the homebrew SS2 chemistry. In addition, we show that our new SMART-Seq method can enable RNA counting, and while optimized for low RNA input, is compatible with single-cell RNA-seq analysis. Finally, we show that our new SMART-Seq method is compatible with common automation platforms. Our data demonstrate that the new SMART-Seq method leveraging SMART technology with UMIs for cDNA generation and our unique library preparation protocol, combined with our Cogent NGS analysis software, is a complete, robust, and sensitive solution for full-length transcriptome studies.