DISSERTATION RESEARCH: Stochastic modeling approaches to evaluate the evolution of chromosome number and genome size in plants

University Of Florida, Gainesville FL

Investigators

Abstract

DNA provides the genetic instructions for life, yet very little is known about why the amount of DNA in a genome varies tremendously across species. In flowering plants, the size and composition of genomes can change drastically through whole genome duplications, which are associated with ecological adaptation and shifts in species diversification rates. This project takes an interdisciplinary approach, combining insights and approaches from disparate fields, such as Botany, Genetics, and Statistics, to examine the role of whole genome duplication in generating and maintaining variation in genome size and chromosome number among species. Specifically, this project will develop and implement new mathematical models to measure the effect of different evolutionary mechanisms associated with duplications on genome size variation in flowering plants. The software and methods developed by this project will help scientists test many questions in genome evolution in a statistically rigorous manner, and the project also will provide interdisciplinary training to graduate students. Whole genome duplication (WGD) is a recurrent genomic process in angiosperms that has been linked to genetic innovation, ecological adaptation, and shifts in diversification rates. However, the role of WGD in generating and maintaining variation in genome size and chromosome number among species is still largely unknown. The goal of this project is to develop new stochastic models of chromosome number and genome size change that will enable scientists to infer the speed of evolutionary mechanisms responsible for the variation in genome size as well as an inferential procedure that will allow estimation of the frequency of such evolutionary processes. Specifically, this project will (1) estimate the relative influence of genome downsizing and constraints against WGD using a formal simulation approach; (2) propose a new stochastic model for ploidy change that includes diploidization; and (3) propose a new stochastic model for genome size change that includes genome downsizing and selection against WGD for taxa with large genomes. The project will also provide new methods and open source software for the scientific community and will provide interdisciplinary training for graduate students.