Skip to main content
Premium Trial:

Request an Annual Quote

This Week in Genome Research: Aug 15, 2018

Researchers from Mission Bio and the University of Texas MD Anderson Cancer Center present findings from clonal evolution analyses done with targeted single-cell sequencing on tumor cells collected over time from individuals with acute myeloid leukemia. The team came up with a high-throughput, droplet microfluidics-based pipeline for barcoding and amplifying DNA from individual cells, before sorting the cells and sequencing 62 loci linked to AML progression. Based on genotypes for more than 16,000 individual cells analyzed from diagnosis through treatment and relapse in two men with AML, the authors tracked down complex clonal evolution and architecture clues that would have been missed by bulk tumor sequencing alone.

A University of Warwick-led team describes a computational pipeline called GrapeTree to tease out and view relationships between many bacterial pathogens based on core gene sequences. With the help of the visualization algorithm GrapeTree Layout and a minimum spanning tree method for teasing out genetic relationships, the authors explain, the software package "efficiently reconstructs and visualizes intricate minimum spanning trees together with detailed metadata." The researchers applied the approach to simulated bacterial data as well as authentic sequence data from hundreds of Salmonella enterica serovars, and note that it appears to be well suited for rapidly making sense of large bacterial datasets.

Finally, researchers from Cold Spring Harbor Laboratory, Stony Brook University, and elsewhere introduced a method called "single-cell RNA-seq analysis and klustering evaluation," or SAKE, for analyzing single-cell RNA sequence data. After demonstrating that the SAKE strategy compared favorably with other single-cell analytical approaches, the team applied it to single-cell RNA-seq data generated with Fluidigm or 10x Genomics technology for human melanoma cells that developed resistance to BRAF inhibitor treatment. "Data from both platforms indicate that BRAF inhibitor-resistant cells can emerge from rare populations already present before drug application," the authors report, "with SAKE identifying both novel and known markers of resistance."