10.5061/DRYAD.TQJQ2BVXC
Bitter, Mark
0000-0001-7607-2375
Stanford University
Kapsenberg, Lydia
Institut de Ciències del Mar
Silliman, Katherine
0000-0001-5964-3965
Auburn University
Gattuso, Jean-Pierre
0000-0002-4533-4114
Villefranche Oceanographic Laboratory
Pfister, Catherine
0000-0003-0892-637X
University of Chicago
Magnitude and predictability of pH fluctuations shape plastic responses to
ocean acidification
Dryad
dataset
2020
Mussels
population transcriptomics
France and Chicago Collaborating in the Sciences program*
France and Chicago Collaborating in the Sciences program
2020-10-08T00:00:00Z
2020-10-08T00:00:00Z
en
https://doi.org/10.1186/s12864-015-1817-5
https://doi.org/10.1186/s13059-014-0550-8
https://github.com/z0on/tag-based_RNAseq
15165285 bytes
3
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
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.
For a full description of the methods, please see the associated
manuscript for this Dryad submission. Breifly, one year of high-frequency
pH and temperature monitoring was conducted at a coastal and lagoon
habitat in the Northwest Mediterranean Sea (the Bay of
Villefranche: 43.682oN, 7.319o E and Thau Lagoon: 43.4158oN, 3.6888oE).
Resident mussels at each site were collected and reared in labortory
common garden conditions for six weeks, after which a 5 day acclimation to
two pH treatments (benign pH - 8.1; stressful pH - 7.75) was conducted. At
the end of the acclimation peirod, total RNA was extracted from gill
tissue samples, and gene expression profiling was carried out using 3’
mRNA sequencing. All resulting raw and processed data files are included
here.
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.
SupplementaryFile1.csv – File containing gene expression data for the
coastal population’s response to stressful pH conditions. Columns
correspond to: reference contig ID (as identified in reference
transcriptome provided by Moreira et al. 2015), transcript ID
(corresponding to row number of counts matrix), log2-fold change, and raw
p-value for each gene. Log2-fold-change values were computed using the
DeSEQ2 software developed by Love et al. (2015)
(doi:10.1186/s13059-014-0550-8). SupplementaryFile2.csv – File containing
gene expression data for the lagoon population’s response to stressful pH
conditions. Columns correspond to: reference contig ID (as identified in
reference transcriptome provided by Moreira et al. 2015), transcript ID
(corresponding to row number of counts matrix), log2-fold change, and raw
p-value for each gene. Log2-fold-change values were computed using the
DeSEQ2 software developed by Love et al. (2015)
(doi:10.1186/s13059-014-0550-8). SupplementaryFile3.csv – File containing
gene expression data for population differentiation in the benign pH
treatment. Columns correspond to: reference contig ID (as identified in
reference transcriptome provided by Moreira et al. 2015), transcript ID
(corresponding to row number of counts matrix), log2-fold change, and raw
p-value for each gene. Log2-fold-change values were computed using the
DeSEQ2 software developed by Love et al. (2015)
(doi:10.1186/s13059-014-0550-8). SupplementaryFile4.csv – File containing
gene expression data for population differentiation in the stressful pH
treatment. Columns correspond to: reference contig ID (as identified in
reference transcriptome provided by Moreira et al. 2015), transcript ID
(corresponding to row number of counts matrix), log2-fold change, and raw
p-value for each gene. Log2-fold-change values were computed using the
DeSEQ2 software developed by Love et al. (2015)
(doi:10.1186/s13059-014-0550-8). SupplementaryFile5.csv – File containing
temperature and pH data as measured by SeaFET pH sensor at hourly
intervals from the coastal habitat. SupplementaryFile6.csv – File
containing raw SeaFET pH sensor readings, as well as sensor-collected pH
and temperature data at 20 minute intervals from the lagoon habitat.