Enhancement of erythropoietic output by Cas9-mediated insertion of a natural variant in haematopoietic stem and progenitor cells.

Some gene polymorphisms can lead to monogenic diseases, whereas other polymorphisms may confer beneficial traits. A well-characterized example is congenital erythrocytosis-the non-pathogenic hyper-production of red blood cells-that is caused by a truncated erythropoietin receptor. Here we show that Cas9-mediated genome editing in CD34+ human haematopoietic stem and progenitor cells (HSPCs) can recreate the truncated form of the erythropoietin receptor, leading to substantial increases in erythropoietic output. We also show that combining the expression of the cDNA of a truncated erythropoietin receptor with a previously reported genome-editing strategy to fully replace the HBA1 gene with an HBB transgene in HSPCs (to restore normal haemoglobin production in cells with a ß-thalassaemia phenotype) gives the edited HSPCs and the healthy red blood cell phenotype a proliferative advantage. Combining knowledge of human genetics with precise genome editing to insert natural human variants into therapeutic cells may facilitate safer and more effective genome-editing therapies for patients with genetic diseases.

Comparative analysis of CRISPR off-target discovery tools following ex vivo editing of CD34+ hematopoietic stem and progenitor cells.

While a number of methods exist to investigate CRISPR off-target (OT) editing, few have been compared head-to-head in primary cells after clinically relevant editing processes. Therefore, we compared in silico tools (COSMID, CCTop, and Cas-OFFinder) and empirical methods (CHANGE-Seq, CIRCLE-Seq, DISCOVER-Seq, GUIDE-Seq, and SITE-Seq) after ex vivo hematopoietic stem and progenitor cell (HSPC) editing. We performed editing using 11 different gRNAs complexed with Cas9 protein (high-fidelity [HiFi] or wild-type versions), then performed targeted next-generation sequencing of nominated OT sites identified by in silico and empirical methods. We identified an average of less than one OT site per guide RNA (gRNA) and all OT sites generated using HiFi Cas9 and a 20-nt gRNA were identified by all OT detection methods with the exception of SITE-seq. This resulted in high sensitivity for the majority of OT nomination tools and COSMID, DISCOVER-Seq, and GUIDE-Seq attained the highest positive predictive value (PPV). We found that empirical methods did not identify OT sites that were not also identified by bioinformatic methods. This study supports that refined bioinformatic algorithms could be developed that maintain both high sensitivity and PPV, thereby enabling more efficient identification of potential OT sites without compromising a thorough examination for any given gRNA.