Seawater carbonate chemistry for the transgenerational experiment on synergistic genomic mechanisms of adaptation to ocean warming and acidification in a marine copepod

DOI

Metazoan adaptation to global change relies on selection of standing genetic variation. Determining the extent to which this variation exists in natural populations, particularly for responses to simultaneous stressors, is essential to make accurate predictions for persistence in future conditions. Here, we identified the genetic variation enabling the copepod Acartia tonsa to adapt to experimental ocean warming, acidification, and combined ocean warming and acidification (OWA) over 25 generations of continual selection. Replicate populations showed a consistent polygenic response to each condition, targeting an array of adaptive mechanisms including cellular homeostasis, development, and stress response. We used a genome-wide covariance approach to partition the allelic changes into three categories: selection, drift and replicate-specific selection, and laboratory adaptation responses. The majority of allele frequency change in warming (57%) and OWA (63%) was driven by shared selection pressures across replicates, but this effect was weaker under acidification alone (20%). OWA and warming shared 37% of their response to selection but OWA and acidification shared just 1%, indicating that warming is the dominant driver of selection in OWA. Despite the dominance of warming, the interaction with acidification was still critical as the OWA selection response was highly synergistic with 47% of the allelic selection response unique from either individual treatment. These results disentangle how genomic targets of selection differ between single and multiple stressors and demonstrate the complexity that nonadditive multiple stressors will contribute to predictions of adaptation to complex environmental shifts caused by global change.

In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2021) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2022-12-23.

Identifier
DOI https://doi.org/10.1594/PANGAEA.953111
Related Identifier https://doi.org/10.1073/pnas.2201521119
Related Identifier https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA590963
Related Identifier https://doi.org/10.5281/zenodo.5093796
Related Identifier https://cran.r-project.org/web/packages/seacarb/index.html
Metadata Access https://ws.pangaea.de/oai/provider?verb=GetRecord&metadataPrefix=datacite4&identifier=oai:pangaea.de:doi:10.1594/PANGAEA.953111
Provenance
Creator Brennan, Reid S (ORCID: 0000-0001-7678-564X); deMayo, James A; Dam, H G ORCID logo; Finiguerra, Michael B ORCID logo; Baumann, Hannes ORCID logo; Buffalo, Vince ORCID logo; Pespeni, Melissa H ORCID logo
Publisher PANGAEA
Contributor Yang, Yan
Publication Year 2022
Rights Creative Commons Attribution 4.0 International; https://creativecommons.org/licenses/by/4.0/
OpenAccess true
Representation
Resource Type Dataset
Format text/tab-separated-values
Size 576 data points
Discipline Earth System Research
Spatial Coverage (-72.002 LON, 41.321 LAT)
Temporal Coverage Begin 2016-06-01T00:00:00Z
Temporal Coverage End 2016-06-30T00:00:00Z