@article {Andor445932, author = {Noemi Andor and Billy T. Lau and Claudia Catalanotti and Vijay Kumar and Anuja Sathe and Kamila Belhocine and Tobias D. Wheeler and Andrew D. Price and Maengseok Song and David Stafford and Zachary Bent and Laura DeMare and Lance Hepler and Susana Jett and Bill Kengli Lin and Shamoni Maheshwari and Anthony J. Makarewicz and Mohammad Rahimi and Sanjam S. Sawhney and Martin Sauzade and Joe Shuga and Katrina Sullivan-Bibee and Adam Weinstein and Wei Yang and Yifeng Yin and Matthew A. Kubit and Jiamin Chen and Susan M. Grimes and Carlos Jose Suarez and George A. Poultsides and Michael Schnall-Levin and Rajiv Bharadwaj and Hanlee P. Ji}, title = {Joint single cell DNA-Seq and RNA-Seq of gastric cancer reveals subclonal signatures of genomic instability and gene expression}, elocation-id = {445932}, year = {2018}, doi = {10.1101/445932}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Sequencing the genomes of individual cancer cells provides the highest resolution of intratumoral heterogeneity. To enable high throughput single cell DNA-Seq across thousands of individual cells per sample, we developed a droplet-based, automated partitioning technology for whole genome sequencing. We applied this approach on a set of gastric cancer cell lines and a primary gastric tumor. In parallel, we conducted a separate single cell RNA-Seq analysis on these same cancers and used copy number to compare results. This joint study, covering thousands of single cell genomes and transcriptomes, revealed extensive cellular diversity based on distinct copy number changes, numerous subclonal populations and in the case of the primary tumor, subclonal gene expression signatures. We found genomic evidence of positive selection {\textendash} where the percentage of replicating cells per clone is higher than expected {\textendash} indicating ongoing tumor evolution. Our study demonstrates that joining single cell genomic DNA and transcriptomic features provides novel insights into cancer heterogeneity and biology.}, URL = {https://www.biorxiv.org/content/early/2018/10/17/445932.1}, eprint = {https://www.biorxiv.org/content/early/2018/10/17/445932.1.full.pdf}, journal = {bioRxiv} }