MachMe-in-Time: Evolution of DNA Methylation Machinery and Function across Time

The basal unit of biological information is the DNA sequence. Furthermore, DNA nucleotides can be methylated, impacting genome structure and readout.

DNA methylation can be epigenetically inherited over many generations, is crucial for plant and animal development, and its mis-regulation underlies several human diseases.

Despite its importance, our understanding of DNA methylation is far from complete, partly because it is absent from the most common genetic model organisms.

To overcome this challenge, I propose a large-scale systematization of the available genomic and epigenomic data to uncover the evolution of DNA methylation in the form of catalytic modules regulating methylation homeostasis.

In year one, I will identify in sequenced genomes the enzymes regulating DNA methylation and reconstruct minimum functional modules using sequence conservation analyses and phylogenomics.

In year two, the robustness and functionality of the modules will be evaluated by comparative analyses of the corresponding epigenomes.

In the third year, detailed information of the configuration and regulatory scope of the catalytic modules will be used along Bayesian models to predict new, undescribed members and configurations of the DNA methylation machinery, thereby overcoming limitations of classical genetic approaches to expand our knowledge of the methylation system.

The results from the present proposal will expand our understanding of DNA methylation and its role driving life complexity.