Single Cell Analysis of Non-coding Distal Autoimmune Loci

Genome-wide association studies (GWAS) have discovered thousands of genetic variants linked to autoimmune disease, and yet the molecular pathways underlying autoimmunity have remained elusive. A key challenge is that >90% of identified GWAS risk loci are in non-coding genomic regions making it difficult to predict their relevance to disease. Here, we have curated fine-mapped non-coding risk variants from over 30 different autoimmune traits including common conditions such as systemic lupus erythematosus (SLE), Crohn’s disease, and multiple sclerosis, and reveal shared genetic signatures between diverse autoimmune diseases. Here, we performed a high-throughput single-cell multi-omic CRISPR activation screen targeting 763 autoimmune risk loci in primary human B cells (a highly relevant cell type to autoimmune diseases) and discover 524 cis-regulatory target gene effects for 378 risk loci, with many risk loci regulating multiple gene targets. This Single Cell Analysis of Non-coding Distal Autoimmune Loci (SCANDAL) provides a powerful experimental resource linking non-coding risk loci to many disease-relevant genes, including lowly-expressed cytokines and transcription factors that can be difficult to quantify perturbation effects with other CRISPR-based strategies. This dataset reflects single-cell expression matrices for gene expression, antobody-derived tags and sgRNA for two independent experiments on two biological donors (four samples total over seven libraries). Single-cell capture with the Chromium GEM-X Single Cell 5' Reagent Kit v3 (10X Genomics) and sequenced on the Illumina NovaSeq X Plus with 150bp paired-end reads. Following demultiplexing and quality control After quality control and data integration, we retained data for 256,790 cells, with 201,191 cells having an assigned sgRNA, with a median of 116 cells per sgRNA and on average 1.4 unique sgRNAs detected per cell. We used SCEPTRE (v0.10.0) to test for differentially expressed genes and cell surface proteins in response to CRISPR-SAM activation of autoimmune risk loci. GEX and ADT count matrixes were generated from the integrated final Seurat object with DropletUtils (v1.26.0). SCEPTRE differential gene expression analysis was performed for all genes (GEX) or cell surface proteins encoded by genes (ADT) within ±500 kb of each targeted locus with high MOI settings, combining cells that contained any of the 3 sgRNAs per target locus and using cells with non-targeting sgRNAs as the control group. We found no major difference in the number of cis-regulatory targets identified for high- or low-MOI settings (data not shown). Following this pooled analysis, we quantified the effects from individual sgRNAs for each locus by repeating SCEPTRE analysis with a singleton sgRNA strategy. We then retained only results that were significant and concordant for ≥2 sgRNAs (SCEPTRE p < 0.05).