Mapping genetic modifiers of epimutation rates in Arabidopsis thaliana

• Applicant: Professor Dr. Frank Johannes
• Subject Area: Plant Genetics and Genomics ; General Genetics and Functional Genome Biology ; Bioinformatics and Theoretical Biology
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 460890770

Heritable gains or losses of cytosine methylation can arise stochastically in plant genomes independently of DNA sequence changes. These so-called ‘spontaneous epimutations’ appear to be a byproduct of imperfect DNA methylation maintenance and epigenome reinforcement events during development. There is continued interest in the plant epigenetics community in trying to understand the broader implications of these stochastic events, as some have been shown to induce heritable gene expression changes, shape patterns of methylation diversity within and among plant populations, and appear to be responsive to multi-generational environmental stressors. There has been major progress in recent years in quantifying the rate and spectrum of spontaneous epimutations using mutation accumulation (MA) lines of the model plant A. thaliana. However, these insights are currently limited to a single reference genotype. Solid preliminary data from our lab (see proposal) shows that epimutation rates can vary significantly across genetic backgrounds, with up to three orders of magnitude difference. These observations indicate that some genotypes are much more error-prone at maintaining cytosine methylation across mitotic and meiotic cell divisions than others. The general aim of this proposal is to exploit these genotypic differences as a tool to identify causal genetic loci that contribute to natural variation in epimutation rates, and to identify molecular pathways that contribute to the formation of spontaneous epimutations in A. thaliana. To this end, we will make use of a novel mutational accumulation mapping population (MAMP) created by my lab (see proposal). The MAMP consists of a large number of MA-pedigrees that differ in their genetic backgrounds. We will use this unique resource in combination with multi-generational DNA methylation measurements to infer genotype-specific epimutation rates. Treating inter-individual variation in these rates as quantitative molecular traits, we will employ classical quantitative trait locus (QTL) mapping strategies to elucidate its genetic basis. Integration of these QTL results with already existing transcriptome, metabolome and proteome data on the MAMP founder lines will provide unprecedented insights into the molecular pathways and genomic targets of spontaneous epimutations, and will advance our basic understanding of how genome and methylome diversity co-evolve over evolutionary- and agriculturally relevant time-scales.

• DFG Programme: Research Grants