Blue Mussel (Genus Mytilus) Transcriptome Response to Simulated Climate Change in the Gulf of Maine

Abstract

The biogeochemistry of the Gulf of Maine (GOM) is rapidly changing in response to the changing climate, including rising temperatures, acidification, and declining primary productivity. These impacts are projected to worsen over the next 100 y and will apply selective pressure on populations of marine calcifiers. This study investigates the transcriptome expression response to these changes in ecologically and economically important marine calcifiers, blue mussels. Wild mussels (Mytilus edulis and Mytilus trossulus) were sampled from sites spanning the GOM and exposed to two different biogeochemical water conditions: (1) present-day conditions in the GOM and (2) simulated future conditions, which included elevated temperature, increased acidity, and decreased food supply. Patterns of gene expression were measured using RNA sequencing from 24 mussel samples and contrasted between ambient and future conditions. The net calcification rate, a trait predicted to be under climate-induced stress, was measured for each individual over a 2-wk exposure period and used as a covariate along with gene expression patterns. Generalized linear models, with and without the calcification rate, were used to identify differentially expressed transcripts between ambient and future conditions. The comparison revealed transcripts that likely comprise a core stress response characterized by the induction of molecular chaperones, genes involved in aerobic metabolism, and indicators of cellular stress. Furthermore, the model contrasts revealed transcripts that may be associated with individual variation in calcification rate and suggest possible biological processes that may have downstream effects on calcification phenotypes, such as zinc-ion binding and protein degradation. Overall, these findings contribute to the understanding of blue mussel adaptive responses to imminent climate change and suggest metabolic pathways are resilient in variable environments.