Coalescing Singlecell Genomes And Transcriptomesto Decode Breast Cancer Progression Kaile Wang Rui Ye Shanshan Bai Zhenna Xiao Lei Yang Jianzhuo Li Chenling Tang Emi Sei Jinyu Peng Anna K Casasent Steven H Lin Chandandeep Nagi Alastair M Thompson Savitri Krishnamurthy Nicholas E Navin by Kaile Wang & Rui Ye & Shanshan Bai & Zhenna Xiao & Lei Yang & Jianzhuo Li & Chenling Tang & Emi Sei & Jinyu Peng & Anna K. Casasent & Steven H. Lin & Chandandeep Nagi & Alastair M. Thompson & Savitri Krishnamurthy & Nicholas E. Navin instant download after payment.

Cell, Corrected proof. SUMMARY - Understanding epithelial lineages of breast cancer and genotype-phenotype relationships requires directmeasurements of the genome and transcriptome of the same single cells at scale. To achieve this, we developed wellDR-seq, a high-genomic-resolution, high-throughput method to simultaneously profile the genomeand transcriptome of thousands of single cells. We profiled 33,646 single cells from 12 estrogen-receptorpositive breast cancers and identified ancestral subclones in multiple patients that showed a luminal hormone-responsive lineage, indicating a potential cell of origin. In contrast to bulk studies, wellDR-seq enabledthe study of subclone-level gene-dosage relationships, which showed near-linear correlations in large chromosomal segments and extensive variation at the single-gene level. We identified dosage-sensitive anddosage-insensitive genes, including many breast cancer genes as well as sporadic copy-number aberrationsin non-cancer cells. Overall, these data reveal complex relationships between copy number and gene expression in single cells, improving our understanding of breast cancer progression.