Magnitude and predictability of pH fluctuations shape plastic responses to ocean acidification

• Main Authors: Bitter, Mark, Kapsenberg, Lydia, Silliman, Katherine, Gattuso, Jean-Pierre, Pfister, Catherine
• Format: Other/Unknown Material
• Language: unknown
• Published: Zenodo 2020
• Subjects: mussels; population transcriptomics; Ocean acidification
• Online Access: https://doi.org/10.5061/dryad.tqjq2bvxc

Phenotypic plasticity is expected to facilitate the persistence of natural populations as global change progresses. The attributes of fluctuating environments that favor the evolution of plasticity have received extensive theoretical investigation, yet empirical validation of these findings is still in its infancy. Here, we combine high-resolution environmental data with a laboratory-based experiment to explore the influence of habitat pH fluctuation dynamics on the plasticity of gene expression in two populations of the Mediterranean mussel, Mytilus galloprovincialis . We linked differences in the magnitude and predictability of pH fluctuations in two habitats to population-specific gene expression profiles in ambient and stressful pH treatments. The results presented demonstrate population-based differentiation in gene expression plasticity, whereby mussels native to a habitat exhibiting a large magnitude of pH fluctuations with low predictability display reduced phenotypic plasticity between experimentally imposed pH treatments. This work validates recent theoretical findings on evolution in fluctuating environments using an ecologically important marine bivalve, and suggests that populations inhabiting regions exposed to unpredictably fluctuating selection pressures may exhibit reduced plasticity as global change progresses. TranscriptCounts.csv – Transcript count data for all coastal and lagoon mussels reared in either benign or stressful pH conditions. Each row corresponds to a gene, while each column corresponds to the observed transcript count for each individual at that gene. Transcript counts were computed from the sequencing data using custom Perl script written by Misha Matz (available at https://github.com/z0on/tag-based_RNAseq). CountsID.csv – Identifying information for the individuals in the transcript counts matrix. Specifically, each row contains pertinent information for corresponding column of the transcript counts file, including source population and treatment information. ...