Evolutionary genetics and quantitative genetics across populations for plant breeding applications in cool-season grasses

My project is an innovative research project in quantitative genetics applied to crop species (wheat and barley) as well as model species (Brachypodium). I will address fundamental limitations in quantitative genetics, by combining different types of genetic data: phylogenetic data (evolution of DNA sequences across species), omics data at different levels of biological organization (RNA expression, metabolism, etc.), and field data (plant morphology and agronomic traits).

Quantitative genetics relies on associations between DNA polymorphisms and observed differences at agronomic traits. These associations are useful to predict plants’ performance, but they are only correlations and cannot detect the exact causal mutations responsible for observed differences, within blocks of millions of DNA bases inherited together by recombination during mating. The goal of the PhD project will be to break away from this current paradigm in quantitative genetics, by
(1) identifying causal mutations based on evolutionary conservation across species, rather than statistical associations within species,
(2) characterizing the intermediate effects of causal mutations on gene expression, metabolism, morphology, etc., rather than modeling their direct effects on agronomic traits, and
(3) depicting genetic variability by descriptions of gene activity, rather than DNA polymorphisms that are often specific to plant populations.