A renewable barcoding system for high-resolution lineage tracking in laboratory yeast
This event is part of the Physics Department Colloquia Series.
In the past few years, whole-genome sequencing studies of evolving microbial populations have shown that the dynamics of adaptation can be remarkably complex. However, these whole-genome sequencing approaches have a very limited resolution due to practical limitations on sequencing depth: typically we can only identify mutations when they reach frequencies of at least a few percent. This is a critical limitation in large microbial populations, where the fates of mutations are often determined over long timescales by competition and hitchhiking among rare high-fitness lineages, and the vast majority of driver mutations never reach detectable frequencies. I will describe a renewable high-efficiency barcoding approach which makes it possible to periodically add barcodes to an evolving yeast population. New barcodes are integrated immediately downstream of existing barcodes, so that each cell contains a string of barcodes that encodes its ancestry. By sequencing the barcode locus, we can then track the frequencies of all the lineages and sublineages in the population for an indefinite period of time and trace the ancestry of all the individuals in the population. I will explain what we saw when we used this system to observe evolutionary dynamics at high resolution in two laboratory yeast populations.