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Opportunities and challenges of next-generation sequencing applications in ecological epigenetics
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 ). Recently, the pot...
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Published in: | Molecular ecology 2015-08, Vol.24 (15), p.3799-3801 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | 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 ). Recently, the potential role of epigenetic mechanisms in the process of adaptive evolution has been the subject of much debate (Pigliucci & Finkelman ). 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. ). 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. ). 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. |
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ISSN: | 0962-1083 1365-294X |
DOI: | 10.1111/mec.13277 |