25CRISPR-Cas9-based gene editing is a powerful tool to reveal genotype-phenotype 26 relationships, but identifying cell clones carrying desired edits remains challenging. To 27 address this issue we developed GenEditID, a flexible, open-access platform for sample 28 tracking, analysis and integration of multiplexed deep sequencing and proteomic data, and 29 intuitive plate-based data visualisation to facilitate gene edited clone identification. To 30 demonstrate the scalability and sensitivity of this method, we identified KO clones in parallel 31 from multiplexed targeting experiments, and optimised conditions for single base editing 32 using homology directed repair. GenEditID enables non-specialist groups to expand their 33 gene targeting efforts, facilitating the study of genetically complex human disease. 34 35 KEYWORDS 36 CRISPR-Cas9; gene editing; GWAS; Illumina sequencing; multiplexed; pluripotent stem cell, 37 LIMS, In-Cell Western 38 39 BACKGROUND 40In the last decade, there has been an explosion of data from the sequencing of human 41 populations, including genome-wide association studies (GWAS) based on DNA microarrays 42 and increasingly also whole exomes and whole genomes (1). These studies have revealed 43 thousands of replicable genetic associations for complex diseases such as diabetes, obesity,
44Alzheimer's Disease and breast cancer (2-4). However, mechanistically determining how 45 these genetic associations contribute to disease remains challenging. Causal evidence 46 requires careful functional follow-up experiments in model cellular systems, organisms and 47 eventually in humans, but the traditional approach of characterising one gene at a time 48 cannot keep pace with the rate of genetic discovery. Furthermore, many associated variants 49 are non-coding, so the genetic elements responsible for conferring disease risk are often 50 unclear (5, 6). This issue is exemplified by the fat mass and obesity associated (FTO) locus, 51 3 in which intronic SNPs are strongly associated with obesity, largely due to increased food 52 intake (7-10) irrespective of gender, age or ethnicity (11, 12). Despite intense study, the 53 identify of the genetic elements that mediate SNP-associated phenotypes remains 54 controversial. Some studies suggest that effect on appetite might not be driven by the FTO 55 gene itself as initially thought, but instead by the nearby genes retinitis pigmentosa GTPase 56 regulator-interacting protein-1 like (RPGRIP1L) (13-15), or by iroquois homeobox 3 (IRX3) 57 and iroquois homeobox 5 (IRX5) (16, 17). Two powerful tools have recently emerged to help 58 meet the challenge of uncovering disease mechanisms from the translating the growing 59 wealth of genetic data: human pluripotent stem cells (hPSCs) and the CRISPR-Cas9 system 60 (18, 19).
62hPSCs facilitate human disease modelling since they can be indefinitely maintained in a 63 pluripotent state and can theoretically be differentiated into any cell type in the body,
64including disease-relevant cell populations (20, 21). For ex...