A framework for evaluating edited cell libraries created by massively parallel genome engineering

Author:

Cawley SimonORCID,Abbate Eric,Abraham Christopher G.,Alvarez Steven,Barber MathewORCID,Bolte ScottORCID,Bruand JocelyneORCID,Church Deanna M.ORCID,Davis Clint,Estes MatthewORCID,Federowicz Stephen,Fox Richard,Gander Miles W.,Garst Andrew D.ORCID,Gencer GozdeORCID,Halweg-Edwards Andrea L.ORCID,Hardenbol Paul,Hraha ThomasORCID,Jain SurbhiORCID,Johnson Charlie,Juneau Kara,Krishnamurthy NandiniORCID,Lambert Shea,Leland Bryan,Pearson Francesca,Ray J. Christian J.ORCID,Sanada Chad D.,Shaver Timothy M.ORCID,Shepherd Tyson R.ORCID,Shorenstein JoshuaORCID,Spindler Eileen C.,Struble Craig A.ORCID,Swat Maciej H.ORCID,Tanner StephenORCID,Tian Tian,Wishart Ken,Graige Michael S.

Abstract

AbstractGenome engineering methodologies are transforming biological research and discovery. Approaches based on CRISPR technology have been broadly adopted and there is growing interest in the generation of massively parallel edited cell libraries. Comparing the libraries generated by these varying approaches is challenging and researchers lack a common framework for defining and assessing the characteristics of these libraries. Here we describe a framework for evaluating massively parallel libraries of edited genomes based on established methods for sampling complex populations. We define specific attributes and metrics that are informative for describing a complex cell library and provide examples for estimating these values. We also connect this analysis to generic phenotyping approaches, using either pooled (typically via a selection assay) or isolate (often referred to as screening) phenotyping approaches. We approach this from the context of creating massively parallel, precisely edited libraries with one edit per cell, though the approach holds for other types of modifications, including libraries containing multiple edits per cell (combinatorial editing). This framework is a critical component for evaluating and comparing new technologies as well as understanding how a massively parallel edited cell library will perform in a given phenotyping approach.

Publisher

Cold Spring Harbor Laboratory

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