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Opportunities and challenges of next‐generation sequencing applications in ecological epigenetics
Author(s) -
Robertson Marta,
Richards Christina
Publication year - 2015
Publication title -
molecular ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.619
H-Index - 225
eISSN - 1365-294X
pISSN - 0962-1083
DOI - 10.1111/mec.13277
Subject(s) - biology , epigenetics , evolutionary biology , adaptation (eye) , genetic variation , amplified fragment length polymorphism , context (archaeology) , dna methylation , variation (astronomy) , ecological genetics , trait , genetics , natural selection , genetic architecture , evolutionary ecology , quantitative trait locus , selection (genetic algorithm) , population , genetic diversity , gene , paleontology , gene expression , demography , physics , neuroscience , artificial intelligence , sociology , astrophysics , computer science , programming language , host (biology)
Evolutionary theory posits that adaptation can result when populations harbour heritable phenotypic variation for traits that increase tolerance to local conditions. However, the actual mechanisms that underlie heritable phenotypic variation are not completely understood (Keller [Keller EF, 2014]). Recently, the potential role of epigenetic mechanisms in the process of adaptive evolution has been the subject of much debate (Pigliucci & Finkelman [Pigliucci M, 2014]). Studies of variation in DNA methylation in particular have shown that natural populations harbour high amounts of epigenetic variation, which can be inherited across generations and can cause heritable trait variation independently of genetic variation (Kilvitis et al . [Kilvitis HJ, 2014]). While we have made some progress addressing the importance of epigenetics in ecology and evolution using methylation‐sensitive AFLP ( MS ‐ AFLP ), this approach provides relatively few anonymous and dominant markers per individual. MS ‐ AFLP are difficult to link to functional genomic elements or phenotype and are difficult to compare directly to genetic variation, which has limited the insights drawn from studies of epigenetic variation in natural nonmodel populations (Schrey et al . [Schrey AW, 2013]). In this issue, Platt et al . provide an example of a promising approach to address this problem by applying a reduced representation bisulphite sequencing (RRBS) approach based on next‐generation sequencing methods in an ecological context.