Droevendaalsesteeg 10
6708 PB Wageningen
The Netherlands
The aim of my PhD project is to identify genetic and environmental control mechanism underlying genome-wide DNA methylation and possible functional consequences of gene methylation for natural variation in great tit personality.
Bernice Sepers (1991) studied Biology (Bachelor of Science) and Environmental Biology (specialisation programme Behavioural Ecology, Master of Science) at Utrecht University. During her major internship at Stichting AAP, she studied the effect of intervention on the abnormal behaviour of ex-laboratory chimpanzees. In her final year she visited the Nova Scotia Department of Natural Resources in Canada to study the environmental conditions that influenced snowmobile trail use by coyotes within lynx home ranges at Cape Breton Island (Nova Scotia, Canada). Her master thesis consisted of an extensive literature review on the effect of epigenetic changes on the behaviour of animals in natural populations (NIOO-KNAW). Bernice graduated in 2016, after which she was funded by a Startersbeurs to study the effect of experimental brood size manipulation on DNA methylation and exploratory behaviour in the great tit at the NIOO-KNAW. After this, she worked as a soil consultant and ecologist at Antea Group (the Netherlands) before starting her PhD at the NIOO-KNAW in 2018. This PhD project focuses on the epigenetics of animal personality, in particular DNA methylation and its influence on exploratory behaviour in great tits. By using established selection lines of fast and slow exploratory birds and several long-term natural populations, this projects aims to identify genetic and environmental control mechanism underlying genome-wide DNA methylation and possible functional consequences of gene methylation for natural variation in great tit personality.
The field of molecular biology is advancing fast with new powerful technologies, sequencing methods and analysis software being developed constantly. Commonly used tools originally developed for research on humans and model species are now regularly used in ecological and evolutionary research. There is also a growing interest in the causes and consequences of epigenetic variation in natural populations. Studying ecological epigenetics is currently challenging, especially for vertebrate systems, because of the required technical expertise, complications with analyses and interpretation, and limitations in acquiring sufficiently high sample sizes. Importantly, neglecting the limitations of the experimental setup, technology and analyses may affect the reliability and reproducibility, and the extent to which unbiased conclusions can be drawn from these studies. Here, we provide a practical guide for researchers aiming to study DNA methylation variation in wild vertebrates. We review the technical aspects of epigenetic research, concentrating on DNA methylation using bisulfite sequencing, discuss the limitations and possible pitfalls, and how to overcome them through rigid and reproducible data analysis. This review provides a solid foundation for the proper design of epigenetic studies, a clear roadmap on the best practices for correct data analysis and a realistic view on the limitations for studying ecological epigenetics in vertebrates. This review will help researchers studying the ecological and evolutionary implications of epigenetic variation in wild populations.
Several reduced-representation bisulfite sequencing methods have been developed in recent years to determine cytosine methylation de novo in nonmodel species. Here, we present epiGBS2, a laboratory protocol based on epiGBS with a revised and user-friendly bioinformatics pipeline for a wide range of species with or without a reference genome. epiGBS2 is cost- and time-efficient and the computational workflow is designed in a user-friendly and reproducible manner. The library protocol allows a flexible choice of restriction enzymes and a double digest. The bioinformatics pipeline was integrated in the Snakemake workflow management system, which makes the pipeline easy to execute and modular, and parameter settings for important computational steps flexible. We implemented bismark for alignment and methylation analysis and we preprocessed alignment files by double masking to enable single nucleotide polymorphism calling with Freebayes (epiFreebayes). The performance of several critical steps in epiGBS2 was evaluated against baseline data sets from Arabidopsis thaliana and great tit (Parus major), which confirmed its overall good performance. We provide a detailed description of the laboratory protocol and 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.4764652).