Oct 30, 2018

Genetic Heterogeneity Profiling by Single Cell RNA Sequencing

BioRxiv : the Preprint Server for Biology
Zilu ZhouAndy J Minn

Abstract

Detection of genetically distinct subclones and profiling the transcriptomic differences between them is important for studying the evolutionary dynamics of tumors, as well as for accurate prognosis and effective treatment of cancer in the clinic. For the profiling of intra-tumor transcriptional heterogeneity, single cell RNA-sequencing (scRNA-seq) is now ubiquitously adopted in ongoing and planned cancer studies. Detection of somatic DNA mutations and inference of clonal membership from scRNA-seq, however, is currently unreliable. We propose DENDRO, an analysis method for scRNA-seq data that detects genetically distinct subclones, assigns each single cell to a subclone, and reconstructs the phylogenetic tree describing the tumor's evolutionary history. DENDRO utilizes information from single nucleotide mutations in transcribed regions and accounts for technical noise and expression stochasticity at the single cell level. The accuracy of DENDRO was benchmarked on spike-in datasets and on scRNA-seq data with known subpopulation structure. We applied DENDRO to delineate subclonal expansion in a mouse melanoma model in response to immunotherapy, highlighting the role of neoantigens in treatment response. We also applied DENDRO to ...Continue Reading

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Mentioned in this Paper

Study
Clinic
Trees (plant)
Sequence Determinations, RNA
Transcription, Genetic
Neoplasms
Sequence Determinations
Profile (Lab Procedure)
Clone
Sequencing

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