Differentially methylated cytosines and methylation patterns
We first assessed differentially methylated cytosines (DMCs) between parental environments (enriched vs poor), using logistic regression on quantitated normalised data with q-value < 0.01 after multiple testing correction and >20% minimal CpG methylation difference (|ΔM|), using methylKit. To test whether the number of DMCs between environments were different from the expected by random, we generated with 4,000 random combinations of 16 parental individuals and tested for the number of DMCs for each combination following the same parameters as the ones described for the original grouping.
We then analysed whether the DNA methylation patterns (hypomethylated or hypermethylated) in the parents were maintained in the offspring. For this, we classified DMCs in two categories (i) environmentally-induced (differences in methylation patterns between the parents changed in the offspring depending on the offspring rearing environment) and (ii) intergenerational (differences in methylation patterns between parental environments were maintained in the offspring regardless of their rearing environment) (Fig. S3). We set up a threshold of ±10% average methylation score value in the offspring relatively to its parents to consider whether an individual epiallele methylation pattern maintained the parental methylation state. For DMCs classified as intergenerational we identified the genomic location (within gene body, promoter region (≤2 kb upstream of the transcription start site (TSS)), or intergenic region (≥2kb upstream of TSS or downstream the gene bodies).
To test whether the methylation patterns of the offspring on the DMCs classified as potentially intergenerational were significantly influenced by the parental environment, we analysed the methylation score of the offspring for each DMC (as a proportion index) as a function of the parental environment (enriched or poor), the offspring environment and their interactions using a generalized linear model with a binomial link, with multiple testing correction.
The annotated regions affected by these DMCs were used for the gene ontology enrichment analysis using zebrafish (Danio rerio ) gene orthologs in PANTHER v. 11 (Mi et al. 2016). We searched for enrichments across biological process and pathways ontologies curated for zebrafish. Only genes which matched with the genes names annotated for zebrafish were included in the gene ontology analysis.