- Time:
Human genetics provides perhaps the single best opportunity to innovate and improve clinical success rates, through the identification of novel drug targets for complex disease. Even as correlation identifies multiple genetic variants associated with disease, it is challenging to conduct requisite functional studies to identify the causal variants, especially since most association signals map to non-coding regions of the genome.
Genetic editing technologies, such as CRISPR, have enabled the modeling of associated variants at their native loci, including non-coding loci, empowering the identification of underlying biological mechanisms of disease with potential causal genes. However, genome editing is largely manual today severely limiting scale, and forcing the use of rational filters to prioritize which variants to investigate functionally.
In this GEN webinar, we will discuss several strategies enabling large-scale functional investigation of disease-associated variants in a cost- and time-effective manner, including different types of pooled CRISPR-based screens and the development of a fully automated genome engineering platform. We will also review how optimization of genome engineering on this platform enables the engineering of disease-associated variants at scale in pluripotent cells.
A live Q&A session followed the presentation, offering a chance to pose questions to our expert panelist.
Produced with support from:
Martin Kampmann, PhD
Associate Professor, UCSF
Investigator, Chan
Zuckerberg Biohub
Kevin Holden, PhD
Head of Science
Synthego
