Germline methylation patterns determine the distribution of recombination events in the dog genome

Abstract

The positive-regulatory domain containing nine gene, PRDM9, which strongly associates with the location of recombination events in several vertebrates, is inferred to be inactive in the dog genome. Here, we address several questions regarding the control of recombination and its influence on genome evolution in dogs. First, we address whether the association between CpG islands (CGIs) and recombination hotspots is generated by lack of methylation, GC-biased gene conversion (gBGC), or both. Using a genome-wide dog single nucleotide polymorphism data set and comparisons of the dog genome with related species, we show that recombination-associated CGIs have low CpG mutation rates, and that CpG mutation rate is negatively correlated with recombination rate genome wide, indicating that nonmethylation attracts the recombination machinery. We next use a neighbor-dependent model of nucleotide substitution to disentangle the effects of CpG mutability and gBGC and analyze the effects that loss of PRDM9 has on these rates. We infer that methylation patterns have been stable during canid genome evolution, but that dog CGIs have experienced a drastic increase in substitution rate due to gBGC, consistent with increased levels of recombination in these regions. We also show that gBGC is likely to have generated many new CGIs in the dog genome, but these mostly occur away from genes, whereas the number of CGIs in gene promoter regions has not increased greatly in recent evolutionary history. Recombination has a major impact on the distribution of CGIs that are detected in the dog genome due to the interaction between methylation and gBGC. The results indicate that germline methylation patterns are the main determinant of recombination rates in the absence of PRDM9.

Keywords: CpG island; biased gene conversion; dog genome; methylation; recombination.

Fig. 1.—

Patterns of mutation inferred from SNPs observed in dog resequencing data in different genomic regions and their intersections.

Fig. 2.—

CpG mutability in regions of different recombination rate. Error bars represent 95% confidence intervals from bootstrapping.

Fig. 3.—

Patterns of nucleotide substitution in dog (blue) and panda (red) lineages inferred from dog–panda–cat alignments. Error bars represent 95% confidence intervals from bootstrapping. (a) Substitution frequencies in (i) dog and (ii) panda. (b) Mean substitution frequencies in dog and panda. (c) Current and stationary GC-content (GC*) in (i) dog an (ii) panda.