A genome-wide CRISPR screen identifies CALCOCO2 as a regulator of beta cell function influencing type 2 diabetes risk

Antje K Rottner, Yingying Ye, Elena Navarro-Guerrero, Varsha Rajesh, Alina Pollner, Romina J Bevacqua, Jing Yang, Aliya F Spigelman, Roberta Baronio, Austin Bautista, Soren K Thomsen, James Lyon, Sameena Nawaz, Nancy Smith, Agata Wesolowska-Andersen, Jocelyn E Manning Fox, Han Sun, Seung K Kim, Daniel Ebner, Patrick E MacDonald, Anna L Gloyn.
Nat Genet. 2022-12-21;55(1):54-65.
Identification of the genes and processes mediating genetic association signals for complex diseases represents a major challenge. As many of the genetic signals for type 2 diabetes (T2D) exert their effects through pancreatic islet-cell dysfunction, we performed a genome-wide pooled CRISPR loss-of-function screen in a human pancreatic beta cell line. We assessed the regulation of insulin content as a disease-relevant readout of beta cell function and identified 580 genes influencing this phenotype. Integration with genetic and genomic data provided experimental support for 20 candidate T2D effector transcripts including the autophagy receptor CALCOCO2. Loss of CALCOCO2 was associated with distorted mitochondria, less proinsulin-containing immature granules and accumulation of autophagosomes upon inhibition of late-stage autophagy. Carriers of T2D-associated variants at the CALCOCO2 locus further displayed altered insulin secretion. Our study highlights how cellular screens can augment existing multi-omic efforts to support mechanistic understanding and provide evidence for causal effects at genome-wide association studies loci.
Consortium data used in this publication
Fastq sequencing files from the CRISPR screen have been deposited in the European Nucleotide Archive (ENA) at EMBL-EBI under accession number PRJEB44712. Fastq sequencing files from RNA-Sequencing experiments for siCALCOCO2 samples have been deposited in the European Genome-phenome Archive (EGA) under study number EGAS00001006127 and EndoC-βh1 expression data from a previously published study can be accessed under PRJEB15283 (ENA)71. The data are freely available to download while the processed counts can be found in Supplementary Dataset 1. RNA-seq data were aligned to the human genome reference GRCh38 (ftp://ftp.ensembl.org/pub/release-101/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz) and counted with the gene annotation (ftp://ftp.ensembl.org/pub/release-101/gtf/homo_sapiens/Homo_sapiens.GRCh38.101.gtf.gz) downloaded from Ensembl database. Source data of unprocessed blots and Extended Data can be accessed online. Source data are provided with this paper. The source code of MAGeCK is freely available at http://liulab.dfci.harvard.edu/Mageck and differential gene expression analysis was performed using the DESeq2 R package. Respective code is available at 10.5281/zenodo.7226348.

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Pancreatic beta cell function and type 2 diabetes predicted effector genes (Rottner AK et al., 2023)