mC-EVOLVE · The evolutionary biology of crop plant DNA methylation

In this project, mC-EVOLVE, I aim to decipher the evolutionary principles governing crop plant methylation diversity. This newfound knowledge will unlock investigations into an underexplored source of functional variation. The project employs a multidisciplinary approach that encompasses mathematical modeling, population genetics, and epigenetics. It is structured around three main objectives:Objective 1 - Separation of Evolutionary and Environmental Forces on Methylomes: I will develop an innovative inference tool to disentangle neutral, selective, and environmental influences on methylation variants. This will be achieved by inferring the genealogy along the methylome and evaluating the local correlations between genetic and methylation variants.Objective 2 - Assessment of Transgenerational Stability of Methylation Alleles following Genomic Shock: Given that introgressive hybridization is a recurring phenomenon in crop plant enhancement, resulting in genomic shock and subsequent methylome remodeling, I will analyze introgression lines derived from crosses between wild and domesticated sunflowers to identify methylation patterns stable across multiple generations.Objective 3 - Inference of Evolutionary Parameters in Crop Plants with Varied Methylation Patterns: I will analyze publicly accessible datasets containing genomes and methylomes from nine crop plants and their wild relatives to quantify the evolutionary forces affecting plant DNA methylation. This analysis aims to determine the variation in methylation rates across the phylogeny, facilitated by comparisons to the model plant Arabidopsis.Through the development of a pioneering evolutionary inference approach for methylomes, the identification of the optimal marker class of crop plant methylation analysis, and the analysis of multiple open access crop plant methylomes, mC-EVOLVE is dedicated to advancing our comprehension of the evolutionary dynamics underlying crop plant DNA methylation.