Doctoral defence: Nurlan Kerimov “Building a catalogue of molecular quantitative trait loci to interpret complex trait associations“

On 13. November at 2.15 pm Nurlan Kerimov will defend His doctoral thesis "Building a catalogue of molecular quantitative trait loci to interpret complex trait associations" for obtaining the degree of Doctor of Philosophy (Computer Science).

Supervisor:
lecturer Kaur Alasoo, University of Tartu.

Opponents:
Prof. Gregory C. Gibson, Georgia Institute of Technology (United States of America);
Dr. Emma Davenport, Wellcome Sanger Institute (United Kingdom).

Summary
Picture this: you're in a room with a single ceiling lamp and a wall adorned with 100 mystery switches. Their wires are concealed, and their specific functions remain a puzzle. You decide to experiment, flipping various combinations of switches, and suddenly, the lamp flickers on. As you test different combinations, you note a variance in the lamp's brightness. With some combinations, the light glows radiantly, while with others, it dimly illuminates the room. After some tinkering, you start to understand which switch combinations affect the lamp's brightness the most. Yet, your ultimate goal is to accurately control the lamp's brightness at will. It's apparent the switches don't create the electricity powering the lamp. Rather, they must trigger unseen power generators. The enigma now is figuring out the connections between specific switches and specific generators that enable the lamp to glow.

In this metaphor, I aimed to provide a simplified understanding of quantitative trait locus (QTL) analysis. Here, the switches represent genetic variants, the lamp symbolises a complex trait (like a disease), the power GENErators stand for genes, and the room represents a specific cell type. Moreover, each QTL can be seen as the impact of a particular switch on a given generator. However, the complexity far exceeds a mere 100 switches. In reality, we're dealing with millions. And although the switches (genetic variants) are identical in each different room (cell type), the wiring blueprint connecting switches to generators (genes) differs significantly from one room to the next.

We've built an extensive Catalogue of QTLs, covering 127 human cell types, and have developed a tool to visualise these QTLs for a better interpretation. The eQTL Catalogue has shown its worth in multiple research initiatives, enhancing our understanding of the genetic underpinnings of complex traits. Additionally, its well-designed infrastructure allows for swift re-analysis when new research approaches emerge, underscoring the Catalogue's versatility and resilience in the realm of genomic research.