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Mateman, C.

Publications and source records attributed to Mateman, C..

3 recordsLinked to original sources

Fishing pressure induces changes in DNA methylation in genetically homogeneous marine metapopulations

Trait-selective harvesting by fisheries can impose strong selective pressures on fish populations, driving changes in life history traits affecting fisheries productivity and ecosystem functioning. While the genetic consequences of harvesting have been extensively studied, the extent to which phenotypic variation reflects genomic evolution versus environmentally-induced plasticity remains unclear. Epigenetic mechanisms, such as DNA methylation, may mediate between these processes, serving as a rapid and reversible response to the selective pressures imposed by harvesting. In this study, we implemented an improved laboratory and bioinformatics protocol, epiGBS3, to examine genomic variation and DNA methylation patterns in the marine fish Xyrichtys novacula. The study spanned three replicated geographical areas each comprising two adjacent locations: an intensively exploited fishery and a no-take Marine Protected Area (ntMPA). A nested analysis design across the three areas revealed strong gene flow and no evidence of genetic structure. Nevertheless, nucleotide diversity was significantly reduced in fisheries relative to ntMPAs. We also found that DNA methylation levels differed between protected and exploited sites after controlling for age, suggesting that fishing may influence epigenetic changes independently of fisheries-induced age-truncation effects. This represents one of the first lines of evidence that fisheries can potentially shape epigenetic variation, supporting DNA methylation as contributor to local adaptation under high gene flow and strong anthropogenic selection.

molecular biology↗

DNA methylation associates with sex-specific effects of experimentally increased yolk testosterone in wild nestlings

Maternal hormones can profoundly impact offspring physiology and behaviour in sex-dependent ways. Yet little is known on the molecular mechanisms linking these maternal effects to offspring phenotypes. DNA methylation, an epigenetic mechanism, is suggested to facilitate maternal androgens effects. To assess whether phenotypic changes induced by maternal androgens associate with DNA methylation changes, we experimentally manipulated yolk testosterone levels in wild great tit eggs (Parus major) and quantified phenotypic and DNA methylation changes in the hatched offspring. Increased yolk testosterone levels decreased the begging probability, emphasised sex-differences in fledging mass and affected methylation at 763 CpG sites, but always in a sex-specific way. These sites associated with genes involved in growth, oxidative stress and reproduction, suggesting sex-specific trade-offs to balance the costs and benefits of exposure to high yolk testosterone levels. Future studies should assess if these effects extend beyond the nestling stage and impact fitness.

molecular biology↗

epiGBS2: an improved protocol and automated snakemake workflow for highly multiplexed reduced representation bisulfite sequencing

epiGBS is an existing reduced representation bisulfite sequencing method to determine cytosine methylation and genetic polymorphisms de novo. Here, we present epiGBS2, an improved epiGBS laboratory protocol and user-friendly bioinformatics pipeline for a wide range of species with or without reference genome. epiGBS2 decreases costs and time investment and increases user-friendliness and reproducibility. The library protocol was adjusted to allow for a flexible choice of restriction enzymes and a double digest. Instead of fully methylated adapters, semi-methylated adapters are now used. The bioinformatics pipeline was improved in speed and integrated in the snakemake workflow management system, which now makes the pipeline easy to execute, modular, and parameter settings flexible. We also provide a detailed description of the laboratory protocol, an extensive manual of the bioinformatics pipeline, which is publicly accessible on github (https://github.com/nioo-knaw/epiGBS2) and zenodo (https://doi.org/10.5281/zenodo.3819996), and example output.

bioinformatics↗