CRISPR single base editing, neuronal disease modelling and functional genomics for genetic variant analysis: pipeline validation using Kleefstra syndrome EHMT1 haploinsufficiency

Background Over 400 million people worldwide are living with a rare disease. Next Generation Sequencing (NGS) identifies potential disease causative genetic variants. However, many are identified as variants of uncertain significance (VUS) and require functional laboratory validation to determine pathogenicity, and this creates major diagnostic delays. Methods In this study we test a rapid genetic variant assessment pipeline using CRISPR homology directed repair to introduce single nucleotide variants into inducible pluripotent stem cells (iPSCs), followed by neuronal disease modelling, and functional genomics on amplicon and RNA sequencing, to determine cellular changes to support patient diagnosis and identify disease mechanism. Results As proof-of-principle, we investigated an EHMT1 (Euchromatin histone methyltransferase 1; EHMT1 c.3430C > T; p.Gln1144*) genetic variant pathogenic for Kleefstra syndrome and determined changes in gene expression during neuronal progenitor cell differentiation. This pipeline rapidly identified Kleefstra syndrome in genetic variant cells compared to healthy cells, and revealed novel findings potentially implicating the key transcription factors REST and SP1 in disease pathogenesis. Conclusion The study pipeline is a rapid, robust method for genetic variant assessment that will support rare diseases patient diagnosis. The results also provide valuable information on genome wide perturbations key to disease mechanism that can be targeted for drug treatments.

Automated summary

This study proposes a rapid genetic variant assessment pipeline utilizing CRISPR technology and functional genomics to support rare disease diagnosis and identify key disease mechanisms. The results demonstrate the effectiveness of the pipeline in identifying specific genetic variants associated with Kleefstra syndrome and revealing potential transcription factors relevant to disease pathogenesis.