Liya Mooradian

Liya Mooradian

Liya Mooradian is a senior studying Genetics and Science Communication at Iowa State University of Science and Technology.

Non-coding genomic regions harbor 90% of disease-associated genetic variants. This makes it incredibly challenging to determine which gene is impacted compared to genetic variants that directly change the coding sequence.Internships offer a valuable glimpse into your future career. While you may not have all the answers at the outset, you gain a clearer sense of the questions you need to explore. My internship at the Broad provided just this experience. I learned rapidly, refined my research interests, and gained an even stronger motivation to pursue graduate education. Engaging in leadership series, an intensive science communication course, and seminars by leading faculty, while conducting impactful research, was an indispensable opportunity for both personal and professional growth. I thoroughly enjoyed my time at the Broad and look forward to applying these skills in my future academic and professional endeavors.

One way to link non-coding variants to their related genes is through fine-mapped expression Quantitative Trait Loci (eQTL) studies. These studies examine many individuals in a population to test the association of each variant to a particular trait. Our group identified 32,081 genomic variants that are associated with 1,914 genes’ expression changes in human induced pluripotent stem cells (iPSCs). Even after statistical analysis to predict causal variants, there’s still doubt due to linkage disequilibrium.

To evaluate the confidence of these predictions and obtain direct evidence of a causal variant, we selected variants that not only are most strongly associated with a change in gene expression but are also associated with a change in the binding of key transcription factors. We use an Adenine-Base-Editing protein, ABE8e-NG, coupled with a CRISPR-Cas9 enzyme that introduces adenine-to-guanine conversions when complexed to a guide-RNA. This allows us to test whether making this single nucleotide change in an iPSC line has the same impact on a gene’s expression level as observed for the original eQTL. With this approach, we can validate the variant as causal while simultaneously gaining information about the variant’s mechanism of action.

We hope to use this approach to interpret the function of many more variants in the genome, thus accelerating the understanding of the functional role of disease-associated variants.

 

Project: Using Base Editor Protein ABE8e-NG for eQTL Validation

Mentors: Elisa Donnard and Alexia Sweet, Eric Lander Lab