Pitfalls in Single Clone CRISPR-Cas9 Mutagenesis to Fine-Map Regulatory Intervals

Abstract

The majority of genetic variants affecting complex traits map to regulatory regions of genes, and typically lie in credible intervals of 100 or more SNPs. Fine mapping of the causal variant(s) at a locus depends on assays that are able to discriminate the effects of polymorphisms or mutations on gene expression. Here, we evaluated a moderate-throughput CRISPR-Cas9 mutagenesis approach, based on replicated measurement of transcript abundance in single-cell clones, by deleting candidate regulatory SNPs, affecting four genes known to be affected by large-effect expression Quantitative Trait Loci (eQTL) in leukocytes, and using Fluidigm qRT-PCR to monitor gene expression in HL60 pro-myeloid human cells. We concluded that there were multiple constraints that rendered the approach generally infeasible for fine mapping. These included the non-targetability of many regulatory SNPs, clonal variability of single-cell derivatives, and expense. Power calculations based on the measured variance attributable to major sources of experimental error indicated that typical eQTL explaining 10% of the variation in expression of a gene would usually require at least eight biological replicates of each clone. Scanning across credible intervals with this approach is not recommended.

Acis-regulatory element regulatesERAP2expression through autoimmune disease risk SNPs

“…We did not observe any of such unfavourable events. This confirmed that our editing strategy did not induce widespread genomic changes (43). While THP-1 cells are characterised by genomic alterations, including large regions of copy number neutral loss of heterozygosity of chromosome 5 (including 5q15 ) (44, 45) ( Supplemental Figure 3 ), the results confirmed that single-cell clones from the unedited ‘wild-type’ (WT, rs2248374-GG) THP-1 cells and "edited" THP-1 (rs2248374-AA) were genetically identical at 5q15 , which justifies their comparison ( Figure 1C ).…”

“…Since allelic replacement would provide a more physiological relevant approach, we next aimed to specifically alter the SNP alleles and evaluate the impact on ERAP2 expression. The large size of the region containing all the “independent” ERAP2 eQTLs prevents efficient HDR (43), so we decided to prioritise a regulatory interval with ERAP2 eQTLs. Genetic variation in non-coding enhancer sequences near genes can influence gene expression by interacting with the gene promoter (49).…”

“…The large size of the region containing all the "independent" ERAP2 eQTLs prevents efficient HDR (43), so we decided to prioritise a regulatory interval with ERAP2 eQTLs. Genetic variation in non-coding enhancer sequences near genes can influence gene expression by interacting with the gene promoter (49).…”

Leveraging supervised learning for functionally-informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs

“…Reporter assays have been powerful tools to test variant effects in cellular contexts, but typical high-throughput massive parallel reporter assays (MPRAs) 11,12 do not represent the native chromatin context in the human genome. Direct introduction of single base pair variants in the native genome are still low-throughput 13 . RNAseq studies combined with genotyping or whole-genome sequencing have highlighted loci that are associated with gene expression in humans (eQTLs) [14][15][16] .…”

Computational Methods for the Analysis of Genomic Data and Biological Processes

“…The work by Tian et al [ 9 ] addresses the effect that deleting single-nucleotide polymorphisms (SNPs) of genes affected by large-effect expression Quantitative Trait Loci (eQTL) may have on gene expression. To this end, CRISPR-Cas9 mutagenesis was used to delete SNPs, obtaining single-cell clones.…”