Stafford, D. | Search bioRxiv

bioRxiv2018

Joint single cell DNA-Seq and RNA-Seq of gastric cancer reveals subclonal signatures of genomic instability and gene expression

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 - where the percentage of replicating cells per clone is higher than expected - indicating ongoing tumor evolution. Our study demonstrates that joining single cell genomic DNA and transcriptomic features provides novel insights into cancer heterogeneity and biology. SIGNIFICANCEWe conducted a massively parallel DNA sequencing analysis on a set of gastric cancer cell lines and a primary gastric tumor in combination with a joint single cell RNA-Seq analysis. 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 where the percentage of replicating cells per clone is higher than expected indicating ongoing tumor evolution. Our study demonstrates that combining single cell genomic DNA and transcriptomic features provides novel insights into cancer heterogeneity and biology.

genomics↗

bioRxiv2017

Linked-Read sequencing resolves complex structural variants

Large genomic structural variants (>50bp) are important contributors to disease, yet they remain one of the most difficult types of variation to accurately ascertain, in part because they tend to cluster in duplicated and repetitive regions, but also because the various signals for these events can be challenging to detect with short reads. Clinically, aCGH and karyotype remain the most commonly used assays for genome-wide structural variant (SV) detection, though there is clear potential benefit to an NGS-based assay that accurately detects both SVs and single nucleotide variants. Linked-Read sequencing is a relatively simple, fast, and cost-effective method that is applicable to both genome and targeted assays. Linked-Reads are generated by performing haplotype-level dilution of long input DNA molecules into >1 million barcoded partitions, generating barcoded short reads within those partitions, and then performing short read sequencing in bulk. We performed 30x Linked-Read genome sequencing on a set of 23 samples with known balanced or unbalanced SVs. Twenty-seven of the 29 known events were detected and another event was called as a candidate. Sequence downsampling was performed on a subset to determine the lowest sequence depth required to detect variations. Copy-number variants can be called with as little as 1-2x sequencing depth (5-10Gb) while balanced events require on the order of 10x coverage for variant calls to be made, although specific signal is clearly present at 1-2x sequencing depth. In addition to detecting a full spectrum of variant types with a single test, Linked-Read sequencing provides base-level resolution of breakpoints, enabling complete resolution of even the most complex chromosomal rearrangements.

genomics↗