Elsevier, Journal of Experimental Marine Biology and Ecology, (420-421), p. 56-64, 2012
DOI: 10.1016/j.jembe.2012.03.024
Full text: Download
Marine ecosystems involve relationships between genomic interactions of marine populations with shared biogeographic ranges and the environmental conditions. These relationships, studied mainly through neutral DNA markers, are not always consistent with actual biogeographic patterns or the evolutionary history of marine species. In addition, increased information at functional genomic level from non-model species allows the study of adaptive responses in marine populations. This work reports local transcriptomic patterns in populations of the mussel Mytilus chilensis and their correspondence with oceanographic variability in southern Chile. Analysis of gene expression patterns was conducted through qPCR of seven candidate genes involved in the response to environmental stress (HSP70, HSP90), iron metabolism (Ferritin), pathogens (Mytilin B, Defensin) and oxidative stress (SOD-CuZn, Catalase) in at five study sites located in southern Chile, from Valdivia (39°56′S–73°36′W) to Melinka (43°52′S–73°44′W). Multivariate and correlation analyses were used to assess the relationship between levels of individual gene expression and site features characterized using satellite data on surface temperature, chlorophyll concentration and total suspended sediments. Two main groups of sites with differential patterns of gene expression were identified. Individuals exposed to higher temperatures showed an overexpression of HSP70, HSP90 and Ferritin genes. The expression of SOD-CuZn and Catalase was correlated with local chlorophyll-a (i.e. food availability for mussels), although with opposite correlations. In addition, Mytilin B showed higher levels of expression in areas with higher freshwater influence. Patterns of gene expression across the region of interest suggest that spatial variability in environmental conditions induce phenotypic changes in different populations of the same mussel species. In addition, the analysis of expression patterns in candidate genes can reveal local patterns in populations where other molecular markers show no genetic structure.