Philipp Hummer

27.06.2023

What can trait covariances tell us about the underlying developmental processes?

MSc Student
Advisor: Mihaela Pavlicev

Unit for Theoretical  Biology, Department of Evolutionary Biology
University of Vienna

Abstract

Pleiotropy – the phenomenon of a gene having an effect on more than just one trait – is an important feature of genotype-phenotype mappings and thus, a central concept of both genetics and developmental biology, as well as important for predicting the evolvability of traits. The B-matrix (Wagner 1989) can be a useful and intuitive model to understand pleiotropic structures, but it is also purely an abstract construct and not empirically measurable. It is thus my goal to come up with a mathematical model that will allow us to arrive at estimations of B-matrices from empirical mutational effect covariance (M-)matrices. I will attempt to do this by using a probability density function on the contributions of eigenvalues on the M-matrix from Wagner (1984) with a maximum likelihood approach. This model will then be used on already published data to construct B-matrices for these specific systems, which allows for their re-interpretation and might potentially reveal new insights into the pleiotropic structures of the analyzed traits. From these analyses I hope to synthesize and evaluate the broader value of using estimated B-matrices over trait variances and covariance for understanding the variational pleiotropic structure of various study systems.