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MathBio Seminar

Tuesday, February 15, 2022 - 4:00pm

Michal Hledik

IST Austria


University of Pennsylvania

via Zoom

The talk will be held online: Meeting ID: 967 6263 0263 Passcode: 095803

Selection guides stochastically evolving populations towards fit genotypes and phenotypes, which would be highly unlikely under neutrality. A perspective dating back to Kimura 1961 is that this constitutes accumulation of information in the genome, and that such information is costly. But defining this information and quantifying its cost has been challenging. We propose a framework to to this, which leads to intuitive and very general results. The central quantity is the Kullback-Leibler divergence between the distributions of genotype frequencies with and without selection. First, we show that this population-level information sets an upper bound on the information at the level of the genotype and the phenotype, limiting how precisely they can be specified by selection. Then we ask how much information can be accumulated and maintained at a given cost, measured as variation in fitness. We find links with control theory, and that information is cheapest when it is distributed among many loci.