The methylation landscape and its role in domestication and gene regulation in the chicken

Abstract

Domestication is one of the strongest examples of artificial selection, and has produced some of the most extreme within-species phenotypic variation known. In the case of the chicken, it has been hypothesised that DNA methylation may play a mechanistic role in the domestication response. By inter-crossing wild-derived Red Junglefowl with domestic chickens we mapped Quantitative Trait Loci for hypothalamic methylation (methQTL), gene expression (eQTL) and behaviour. We find large, stable methylation differences, with 6179 cis and 2973 trans methQTL identified. Over 46% of the trans effects were genotypically controlled by five loci, mainly associated with increased methylation in the Junglefowl genotype. In a third of eQTL we find that there is a correlation between gene expression and methylation, whilst statistical causality analysis reveals multiple instances where methylation is driving gene expression, as well as the reverse. We also show that methylation is correlated to some aspects of behavioural variation in the intercross. In conclusion, our data suggest a role of methylation in the regulation of gene expression underlying the domesticated phenotype of the chicken.

Heritability of DNA methylation in threespine stickleback (Gasterosteus aculeatus)

“…46-2 (Broman et al 2003) with default settings, except for rescaling the basepair positions of SNPs by multiplying by a constant of 3.11 x 10 -6 due to the genome-wide recombination rate of 3.11cM/Mb in stickleback (Roesti et al 2013). We calculated genomewide logarithm of the odds (LOD) thresholds through 1,000 permutations, using the n.perm function in the R package R/qtl and set the 95 th percentile LOD score as the significance threshold (Hoglund et al 2020).…”

Rapid changes in DNA methylation associated with the initiation of reproduction in a small songbird

“…In chicken ovaries, MYLK is up‐regulated during egg laying (Liu et al, 2018 ), a pattern consistent with the observed decrease in methylation at CpG sites within the promoter region of LOC107215054 ( MYLK ‐like) in the weeks prior to laying. A recent study on the methylation landscape of chicken found that DNA methylation of MYLK putatively controls MYLK gene expression (Höglund et al, 2020 ), further supporting the idea that identified changes in DNA methylation at the promoter region of this gene can have a regulatory function by mediating gene expression. Whether both genes function as myosin light chain kinases, however, remains to be established.…”

“…On question is also to what degree the observed changes in DNA methylation are dependent on the DNA sequence. Recent studies have demonstrated that genetic variants can underly local and distant variation in DNA methylation in a variety of species: Arabidopsis thaliana (Dubin et al, 2015 ), maize (Xu et al, 2019 ), reef‐building corals (Liew et al, 2020 ), inter‐crosses between wild derived junglefowl and domestic chickens (Höglund et al, 2020 ), and humans (Heyn et al, 2013 ). While we controlled for relatedness among individuals in our differential methylation analysis using single nucleotide polymorphism (SNP) genotype data, the number of females sampled is too small to detect any genome‐wide significant effects of SNPs on local or distant variation in DNA methylation.…”

Heritability of DNA methylation in threespine stickleback (Gasterosteus aculeatus)

“…In addition to performing the meQTL analyses using MatrixEQTL as described above, we also validated meQTL results within each hybrid line using the R package R/qtl v.1.46-2 (Broman et al 2003) with default settings, except for rescaling the basepair positions of SNPs by multiplying by a constant of 3.11 x 10 -6 due to the genome-wide recombination rate of 3.11cM/Mb in stickleback (Roesti et al 2013). We calculated genomewide logarithm of the odds (LOD) thresholds through 1,000 permutations, using the n.perm function in the R package R/qtl and set the 95 th percentile LOD score as the significance threshold (Hoglund et al 2020).…”