Student Exit Seminar: A scalable computing framework for whole-body mouse cell lineage reconstruction

Student Exit Seminar: A scalable computing framework for whole-body mouse cell lineage reconstruction
 
 
 
 
Join Session:

 
Seminar abstract:
The advent of CRISPR-Cas9 genome editing technologies has spurred the development of high-resolution cell lineage tracing systems. These experimental systems utilize genome editing tools to introduce random mutations to chromosome-embedded, synthetic DNA barcode arrays. As these barcodes are continuously mutated and inherited from mother to daughter cells, the lineage of cells sacrificed at the time of observation can be reconstructed from the mutation patterns in their barcodes, akin to phylogeny estimation in evolutionary biology. Recent advances in single-cell sequencing technologies has facilitated large-scale applications of cell lineage tracing systems, which has highlighted major limitations with respect to information decoding capacity. To that end, the Yachie lab recently proposed a theoretical framework capable of reconstructing the phylogeny of hundreds of millions of sequences—a task that far surpasses the capabilities of existing software. A major remaining challenge is to overcome technical biases, noise, and sparsity typically associated with barcode sequence readouts derived from large-scale sequencing experiments. My project focused on the development of a rejection sampling method along with a bootstrapping strategy based on orthogonal tree agreement. Together, they provided a relatively unbiased estimate of confidence for proposed tree branches, which could be leveraged to significantly improve tree reconstruction accuracy. Developing a scalable lineage reconstruction method is paramount to realizing the overarching goal of the Yachie lab to resolve the whole-body mapping of the mouse developmental lineage, a resource that would revolutionize our understanding of mammalian development.
 
Speaker: Brett Kiyota