Fine-mapping within eQTL credible intervals by expression CROP-seq.

Area of Science:

• Genomics
• Molecular Biology
• Genetics

Background:

• Genome-wide association studies (GWAS) often identify single nucleotide polymorphisms (SNPs) in noncoding regions, implicating them in disease risk and phenotypes through gene expression modulation.
• Fine-mapping causal variants within GWAS credible intervals, which frequently contain numerous statistically similar variants, requires experimental validation.

Purpose of the Study:

• To introduce and validate a moderate-throughput method, expression CROP-seq, for identifying regulatory GWAS variants.
• To demonstrate the utility of expression CROP-seq in pinpointing causal variants affecting gene expression and disease association.

Main Methods:

• Expression CROP-seq integrates multiplex CRISPR-Cas9 genome editing with single-cell RNA sequencing (scRNA-seq) to quantify transcript abundance changes following targeted mutations.
• Mutations were introduced near 57 SNPs in three genes within the HL60/S4 myeloid cell line.
• scRNA-seq was used to measure the impact of these mutations on gene expression.

Main Results:

• Expression CROP-seq successfully identified regulatory variants, with significant alterations in CISD1 and PARK7 expression linked to specific SNPs (rs2251039 and rs35675666).
• These findings were robustly replicated and validated in single-cell clones.
• The identified causal variants overlap with chromatin accessibility peaks and are implicated in inflammatory bowel disease.

Conclusions:

• Expression CROP-seq is an effective, relatively inexpensive, and scalable approach for identifying regulatory GWAS variants.
• This method facilitates the fine-mapping of causal variants and can be applied to individual genes or broader genomic surveys.
• The study validates specific variants in CISD1 and PARK7 as causal for inflammatory bowel disease.