Poster AGBT 2022

The ResolveOME platform: integrated whole genome and whole transcriptome profiling from a single cell to unlock drug resistance mechanisms

Tatiana V. Morozova, Jeff G. Blackinton, Isai Salas-González, Viren R. Amin, Victor J. Weigman, Jon S. Zawistowski, Gary L. Harton and Jay A. A. West

BioSkryb Genomics, Inc., Durham, NC.
To elucidate drug resistance mechanisms in cancer and to deconvolve the molecular basis of variability in treatment responses, it is paramount to apply approaches that integrate multi-omics data. Existing methodologies aiming to couple genomic and transcriptomic information are limited in that the genomic information is based on a targeted approach, providing insight into only a small fraction of the genome. We have developed a novel, true multi-omic platform, ResolveOME, that combines whole genome amplification with transcriptome profiling from the same single cell. The platform unifies template-switching single-cell RNAseq chemistry with modified ResolveDNA™ whole genome amplification (WGA) technology based on Primary Template-directed Amplification (PTA). The workflow then relies on affinity purification of first-strand cDNA and subsequent separation of the RNA/DNA fractions to allow for independent library preparation of the fractions followed by ResolveDNA™ library preparation and sequencing. To demonstrate the validity of this platform we generated GM12878 cell data using the ResolveOME chemistry and compared it to data from the ResolveDNA™ WGA kit and to bulk RNA sequencing. Products from the DNA and RNA arms of the protocol demonstrated comparable product sizes and consistent yields to the bulk RNAseq and standard ResolveDNA™ chemistry. Low-pass sequencing of the DNA arm of the ResolveOME workflow showed robust performance, including high genomic coverage and high library diversity. Gene expression analysis of the RNA arm of ResolveOME revealed the ability to detect ~ 10K expressed genes in bulk RNA samples and ~ 8K expressed genes in the single cells, concordant with published data for GM12878 cells. Our next focus is to extend the ResolveOME platform to established cancer drug resistant models in cell lines to identify SNVs, differentially expressed transcripts, and CNV contributing to drug resistance, as well as to primary patient samples. We have demonstrated here that the ResolveOME platform provides unprecedented, and non-targeted multi-omics data from individual single cells. The utility of ResolveOME extends to all applications which require both whole genome and transcriptome data from a single cell and/or samples with limited biological material.