In partial fulfillment of the requirements for the degree of

Doctor of Philosophy in Bioinformatics
in the School of Biological Sciences

Emily Greenwood

Defends her thesis:
Assessing Regulatory Function of Rare and Common Variants using Expression CROPseq

Tuesday, January 6, 2025
11:00am Eastern

Room: CHOA EBB building

Zoom link: https://gatech.zoom.us/j/94645588850

 
Thesis Advisor:

Dr. Greg Gibson, School of Biological Sciences, Georgia Institute of Technology, USA

Committee Members:

Dr. Joe Lachance, School of Biological Sciences, Georgia Institute of Technology, USA

Dr. Abigail Lind, School of Biological Sciences, Georgia Institute of Technology, USA

Dr. Francesca Storici, School of Biological Sciences, Georgia Institute of Technology, USA

Dr. Ciaran Lee, School of Biochemistry and Cell Biology, University College Cork, Ireland

Abstract:

Genome-wide association studies typically identify hundreds to thousands of loci, many of which harbor multiple independent peaks, each parsimoniously assumed to be due to the activity of a single causal variant.  Fine-mapping of such variants has become a priority and since most associations are located within regulatory regions, it is also assumed that they colocalize with regulatory variants that influence the expression of nearby genes.  Here we examine these assumptions by using a moderate throughput expression CROPseq protocol in which Cas9 nuclease is used to induce small insertions and deletions across the credible set of SNPs that may account for expression quantitative trait loci (eQTL) for genes associated with inflammatory bowel disease (IBD).  Of the 4,382 SNPs targeted in 87 loci (an average of 50 per locus), 439 were significant and further examined for validation. From these, 99 significantly altered target gene expression in HL-60 myeloid cell line, 64 in induced macrophages from these HL-60 cells, and 82 in induced neutrophils for a total of 202 validated effects (46%), 38 of which were observed in at least two of the cell types. Considering the observed sensitivity and specificity of the controls, we estimate that there are at least 150 true positives per cell type, an average of almost 2.3 for each of the 66 eQTL for which putative causal variants have been fine-mapped.  This implies that haplotype effects are likely to explain many of the associations.  We also demonstrate that the same approach can be used to investigate the activity of very rare variants in regulatory regions for 89 genes, providing a rapid strategy for establishing clinical relevance of non-coding mutations.