title: Reconstructing the ancestral germ line methylation state of young repeats.
abstract: One of the key objectives of comparative genomics is the characterization of the forces that shape genomes over the course of evolution. In the last decades, evidence has been accumulated that for vertebrate genomes also epigenetic modifications have to be considered in this context. Especially, the elevated mutation frequency of 5-methylcytosine (5mC) is assumed to facilitate the depletion of CpG dinucleotides in species that exhibit global DNA methylation. For instance, the underrepresentation of CpG dinucleotides in many mammalian genomes is attributed to this effect, which is only neutralized in so-called CpG islands (CGIs) that are preferentially unmethylated and thus partially protected from rapid CpG decay. For primate-specific CpG-rich transposable elements from the ALU family, it is unclear whether their elevated CpG frequency is caused by their small age or by the absence of DNA methylation. In consequence, these elements are often misclassified in CGI annotations. We present a method for the estimation of germ line methylation from pairwise ancestral-descendant alignments. The approach is validated in a simulation study and tested on DNA repeats from the AluSx family. We conclude that a predicted unmethylated state in the germ line is highly correlated with epigenetic activity of the respective genomic region. Thus, CpG-rich repeats can be facilitated as in silico probes for the epigenetic potential of their genomic neighborhood.
authors.affiliation: Computational Biology and Applied Algorithmics, Max Planck Institute für Informatik, Saarbrücken, Germany. lfbach@mpi-inf.mpg.de
authors.forename: Lars
authors.initials: L
authors.lastname: Feuerbach
authors.forename: Rune B
authors.initials: RB
authors.lastname: Lyngsø
authors.forename: Thomas
authors.initials: T
authors.lastname: Lengauer
authors.forename: Jotun
authors.initials: J
authors.lastname: Hein
mesh_terms: D020087:Alu Elements / Q000235:genetics; D001773:Blood Cells / Q000378:metabolism; D003198:Computer Simulation; D018899:CpG Islands / Q000235:genetics; D019175:DNA Methylation / Q000235:genetics*; D057890:Epigenomics; D005854:Germ Cells / Q000378:metabolism*; D006801:Humans; D008957:Models, Genetic; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity