|Document Type:||Journal Article|
|Title:||Migratory phenotypic divergence is associated with epigenetic modifications in rainbow trout|
|Author:||Melinda Baerwald, Molly Stephens, Mariah Meek, Raman Nagarajan, A. Goodbla, Katharine Tomalty, Gary H. Thorgaard, Bernie May, Krista M. Nichols|
Migration is essential for the reproduction and survival of many animals, yet little is understood about its underlying molecular mechanisms. We used the salmonid Oncorhynchus mykiss to gain mechanistic insight into smoltification, which is a morphological, physiological and behavioural transition undertaken by juveniles in preparation for seaward migration. O. mykiss is experimentally tractable and displays intra- and interpopulation variation in migration propensity. Migratory individuals can produce nonmigratory progeny and vice versa, indicating a high degree of phenotypic plasticity. One potential way that phenotypic plasticity might be linked to variation in migration-related life history tactics is through epigenetic regulation of gene expression. To explore this, we quantitatively measured genome-scale DNA methylation in fin tissue using reduced representation bisulphite sequencing of F2 siblings produced from a cross between steelhead (migratory) and rainbow trout (nonmigratory) lines. We identified 57 differentially methylated regions (DMRs) between smolt and resident O. mykiss juveniles. DMRs were high in magnitude, with up to 62% differential methylation between life history types, and over half of the gene-associated DMRs were in transcriptional regulatory regions. Many of the DMRs encode proteins with activity relevant to migration-related transitions (e.g. circadian rhythm pathway, nervous system development, protein kinase activity). This study provides the first evidence of a relationship between epigenetic variation and life history divergence associated with migration-related traits in any species.
|Theme:||Recovery and rebuilding of marine and coastal species|
Characterize the population biology of species, and develop and improve methods for predicting the status of populations.
Develop methods to use physiological, biological and behavioral information to predict population-level processes.