CloneRetriever: retrieval of rare clones from heterogeneous cell populations

Abstract

AbstractBackgroundMany biological processes, such as cancer metastasis, organismal development, and development of resistance to cytotoxic therapy, rely on the emergence of rare sub-clones from a larger population. Understanding how the genetic and epigenetic features of diverse clones affect clonal fitness provides insight into molecular mechanisms underlying selective processes. However, identifying causal drivers of clonal fitness remains challenging. Population-level analysis has limited resolution to characterize clones prior to selection, while high-resolution single-cell methods are destructive and challenging to scale across large populations, limiting further functional analysis of relevant clones.ResultsHere, we develop CloneRetriever, a methodology for tracking and retrieving rare clones throughout their response to selection. CloneRetriever utilizes a CRISPR sgRNA-barcode library that allows isolation of viable cells from specific clones within the barcoded population using a sequence-specific retrieval reporter. We demonstrated that CloneRetriever can measure clonal fitness of cancer cell modelsin vitroand retrieve targeted clones at abundance as low as 1 in 1,883 in a heterogeneous cell population.ConclusionsCloneRetriever provides a means to track and access specific and rare clones of interest across dynamic changes in population structure to comprehensively explore the basis of these changes.