Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Related Publications
• Related Datasets
• Parameters
• Instruments
• Project Information
• Funding

In this study, we examined the phenotypic and molecular responses in the extrapallial fluid in the adult eastern oyster (Crassostrea virginica) exposed to experimental ocean acidification (OA) over 80 days. The collection and culturing of C. virginica specimens are detailed in Downey-Wall, A.M., L.P. Cameron, B.M. Ford, E.M. McNally, Y.R. Venkataraman, S.B. Roberts, J.B. Ries, and K.E. Lotterhos. 2020. Ocean acidification induces subtle shifts in gene expression and DNA methylation in the mantle tissue of the Eastern oyster (Crassostrea virginica). Frontiers in Marine Science doi: 10.3389/fmars.2020.566419.

Elemental analysis
Extrapallial fluid, seawater, and shell samples were analyzed for trace and minor elements by inductively coupled plasma mass spectrometry (ICPMS). Liquid samples (i.e., EPF, seawater) were diluted to less than 0.05 percent total dissolved solid content with ultra-pure deionized water in 15 mL polypropylene centrifuge tubes leached in the same manner as those for shell samples. The samples were acidified with ultra-pure nitric acid (Fisher TraceMetal Grade Nitric Acid UN2031). Shell samples were also acidified with ultra-pure nitric acid for analysis.

Extrapallial fluid, seawater, and shell samples were analyzed for a suite of 57 elements (including Ca) by ActLabs, Ontario, Canada. In addition to the common suite of elements, liquid samples were analyzed for Si and shell samples were analyzed for S, P, Au, B, and Re. Liquid samples were analyzed using the ActLabs ICPMS method. Shell samples were analyzed using the ActLabs ICPMS Ultratrace 4 method:
https://actlabs.com/geochemistry/exploration-geochemistry/4-acid-near-total-digestion/

This dataset represents molar ratio data that were processed using R (v. 4.0.3; R Core Team 2020) using the graphical interface RStudio (v. 1.0.1073) and then converted to molar ratios to calcium.  For each sample type (EPF, seawater, shell), values were identified as outliers if the E/Ca ratio deviated by more than 103 from the mean E/Ca ratio for that element. This approach to identifying outliers removes those caused by sampling or equipment error but is more conservative than Tukey's method to identify and remove outliers.

Molar ratio data were processed using R (v. 4.0.3; R Core Team 2020) and the graphical interface RStudio (v. 1.0.1073).

NSF Award Abstract:
Marine ecosystems worldwide are threatened by ocean acidification, a process caused by the unprecedented rate at which carbon dioxide is increasing in the atmosphere. Since ocean change is predicted to be rapid, extreme, and widespread, marine species may face an "adapt-or-die" scenario. However, modifications to the DNA sequence may be induced in response to a stress like ocean acidification and then inherited. Such "epigenetic" modifications may hold the key to population viability under global climate change, but they have been understudied. The aim of this research is to characterize the role of DNA methylation, a heritable epigenetic system, in the response of Eastern oysters (Crassostrea virginica) to ocean acidification. The intellectual merit lies in the integrative approach, which will characterize the role of DNA methylation in the intergenerational response of oysters to ocean acidification. These interdisciplinary data, spanning from molecular to organismal levels, will provide insight into mechanisms that underlie the capacity of marine invertebrates to respond to ocean acidification and lay the foundation for future transgenerational studies. Ocean acidification currently threatens marine species worldwide and has already caused significant losses in aquaculture, especially in Crassostrea species. This research has broader impacts for breeding, aquaculture, and the economy. Under the investigators' "Epigenetics to Ocean" (E2O) training program, the investigators will build STEM talent in bioinformatics and biogeochemistry, expose girls in low-income school districts to careers in genomics, and advance the field through open science and reproducibility.

This research will specifically test if intermittent exposure to low pH induces a methylation response with downstream beneficial effects for biomineralization. These methylation states could be inherited and confer a fitness advantage to larvae that possess them. Phase 1 of the project will use an exposure experiment to determine the degree to which DNA methylation is altered and regulates the response to OA. Data from this experiment will be used to test the hypotheses that (i) DNA methylation, induced in the tissue of shell formation (i.e., mantle tissue), is correlated with changes in transcription and regulation of pallial fluid pH (calcifying fluid pH, measured by microelectrode), and (ii) that methylation changes induced in the mantle tissue are also induced in the germline --indicating that such changes are potentially heritable. Phase 2 of the project will use a pair-mated cross experiment to test the hypothesis that parental exposure to OA alters larval traits (calcification rate, shell structure, and polymorph mineralogy). Larvae will be generated from parents exposed to OA or control seawater, and then raised under control or OA conditions. Results will be used to (i) characterize inheritance of induced methylation states, (ii) estimate the variance in larval traits explained by genotype, non-genetic maternal/paternal effects, adult OA exposure, larval OA exposure, and parental methylome, and (iii) test the hypothesis that adult exposure alters the heritability (a quantity that predicts evolutionary response) of larval traits. Since the effects of epigenetic phenomena on estimates of heritability are highly debated, the results would advance understanding of this important issue. Because the investigators could discover that DNA methylation is a mechanism for heritable plastic responses to OA, knowledge of this mechanism would significantly improve and potentially transform predictive models for how organisms respond to global change.