|Goetze, Erica||University of Hawaii at Manoa (SOEST)||Principal Investigator|
|Ake, Hannah||Woods Hole Oceanographic Institution (WHOI BCO-DMO)||BCO-DMO Data Manager|
These microsatellite data derive from individual copepods collected on Atlantic Meridional Transect cruise 22 (AMT22) in 2012 (RRS James Cook).
These data are reported on in Goetze, E., Andrews, K., Peijnenburg, K. T. C. A., Portner, E., Norton, E. L. (2015) Temporal Stability of Genetic Structure in a Mesopelagic Copepod. PLoS One 10(8): e0136087. doi:10.1371/journal.pone.0136087
These microsatellite data are also available under supporting information S1 File.csv at PLoS One.
Mitochondrial cytochrome c oxidase subunit II (mtCOII) sequence data from this study are available at NCBI under accession numbers KR872026-KR872295 and KC713636-KC713781. Oceanographic data from the Atlantic Meridional Transect cruises are available through the British Oceanographic Data Center.
Abstract: Although stochasticity in oceanographic conditions is known to be an important driver of temporal genetic change in many marine species, little is known about whether genetically distinct plankton populations can persist in open ocean habitats. A prior study demonstrated significant population genetic structure among oceanic gyres in the mesopelagic copepod Haloptilus longicornis in both the Atlantic and Pacific Oceans, and we hypothesized that populations within each gyre represent distinct gene pools that persist over time. We tested this expectation through basin-scale sampling across the Atlantic Ocean in 2010 and 2012. Using both mitochondrial (mtCOII) and microsatellite markers (7 loci), we show that the genetic composition of populations was stable across two years in both the northern and southern subtropical gyres. Genetic variation in this species was partitioned among ocean gyres (FCT = 0.285, P < 0.0001 for mtCOII, FCT = 0.013, P < 0.0001 for microsatellites), suggesting strong spatial population structure, but no significant partitioning was found among sampling years. This temporal persistence of population structure across a large geographic scale was coupled with chaotic genetic patchiness at smaller spatial scales, but the magnitude of genetic differentiation was an order of magnitude lower at these smaller scales. Our results demonstrate that genetically distinct plankton populations persist over time in highly-dispersive open ocean habitats, and this is the first study to rigorously test for temporal stability of large-scale population structure in the plankton.
Refer to the following publication for complete methodology details:
Goetze, E., Andrews, K., Peijnenburg, K. T. C. A., Portner, E., Norton, E. L. (2015) Temporal Stability of Genetic Structure in a Mesopelagic Copepod. PLoS One 10(8): e0136087. doi:10.1371/journal.pone.0136087
In summary (excerpted from above):
For H. longicornis species 1, deviations from Hardy-Weinberg equilibrium (HWE) and linkage disequilibrium were examined using ARLEQUIN v220.127.116.11 and GENEPOP v4.2 for all microsatellite loci [36–38]. We tested for the presence of null alleles in microsatellite data using MICROCHECKER v2.2.3 , and estimated null allele frequencies and calculated population pairwise FST values with correction for null alleles in FreeNA . Microsatellite genetic diversity indices of observed and expected heterozygosity, average alleles per locus, and allele richness were calculated in GENETIX v4.05 and FSTAT [35,41]. Pairwise FST values were calculated among all sample sites using both microsatellite and mtCOII data, as a measure of population subdivision across samples (ARLEQUIN v18.104.22.168, ). Significance was assessed following correction for multiple comparisons using the false discovery rate (FDR, [42,43]). Pairwise ΦST values also were calculated for the mtCOII data. We identified the nucleotide substitution model that best fit our mtCOII data using the Akaike Information Criterion, as implemented in jModelTest v2.1.4 , and the K81 or three-parameter model was selected as the best model (TPM3uf+G). The Tamura and Nei substitution model, which was the closest available model in Arlequin, was used to calculate pairwise and global ΦST values, and to estimate genetic diversity at each site. Hierarchical Analyses of Molecular Variance (AMOVA) based on FST were carried out to partition the genetic variance across both space (ocean gyres) and time (sampling years), for both marker types. In these analyses, we tested for population structure under the following groupings: with samples stratified by (1) northern and southern subtropical gyres (2 gyres), and (2) across two sampling years (2010, 2012). Global FST values were estimated using non-hierarchical AMOVAs among all samples, as well as among subsets of the data across ocean gyres and sampling years. Significance was tested with 10,000 permutations of genotypes or haplotypes among populations. Principal coordinate analysis (PCA) plots of linearized pairwise FST values based on both mtCOII and microsatellite data were used to visualize spatial and temporal genetic differentiation among samples. Population structure was further examined using a Bayesian clustering method implemented in STRUCTURE [45,46] for microsatellite loci. We used admixture and correlated allele frequency models, with a burn-in of 105 steps followed by 106 steps, with and without using sampling location as a prior. We ran these analyses for each of the 2010 and 2012 datasets using K = 1 to K = 10, and for the dataset of combined years using K = 1 to K = 20. We ran three separate replicates for each K to investigate consistency of Pr(X|K). The true K was evaluated by visual inspection of barplots and comparing Pr(X|K) across K values.
- modified parameter names to conform with BCO-DMO naming conventions
- "0" missing value code changed to "nd"
|sample_id||PI issued sample ID number||unitless|
|station||Station number where sampling occurred||unitless|
|diploidGenotype1_HALOMS175||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype2_HALOMS175||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype1_HALOMS27||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype2_HALOMS27||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype1_HALOMS32||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype2_HALOMS32||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype1_HALOMS86||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype2_HALOMS86||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype1_HALOM264||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype2_HALOM264||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype1_HALOMS91||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype2_HALOMS91||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype1_HALOMX66||Diploid genotypes reported for each locus and individual||count|
|diploidGenotype2_HALOMX66||Diploid genotypes reported for each locus and individual||count|
|Dataset-specific Instrument Name|| |
ABI3730 Genetic Analyzer
|Generic Instrument Name|| |
PCR Thermal Cycler
|Dataset-specific Description|| |
PCR products were genotyped
|Generic Instrument Description|| |
General term for a laboratory apparatus commonly used for performing polymerase chain reaction (PCR). The device has a thermal block with holes where tubes with the PCR reaction mixtures can be inserted. The cycler then raises and lowers the temperature of the block in discrete, pre-programmed steps. (adapted from http://serc.carleton.edu/microbelife/research_methods/genomics/pcr.html)
RRS James Cook
|Start Date|| |
|End Date|| |
The AMT22 cruise set sail from Southampton in the UK on 10 October 2012 and arrived in Punta Arenas, Chile on 24 November 2012. The final cruise report and other cruise information, including all science components, can be found online at the Atlantic Meridional Transect webpage (http://www.amt-uk.org/Cruises), or through the British Oceanographic Data Centre (BODC) (http://www.bodc.ac.uk/projects/uk/amt/). Zooplankton ecology data from the project "Does habitat specialization drive population genetic structure of oceanic zooplankton?" (NSF OCE-1029478) were collected on this cruise.
RRS James Cook
|Start Date|| |
|End Date|| |
From: https://www.bodc.ac.uk/resources/inventories/cruise_inventory/report/9969/ AMT20 (JC053) is the third cruise of the third phase of the Atlantic Meridional Transect (AMT) programme. The programme is hosted by Plymouth Marine Laboratory in collaboration with the National Oceanography Centre, Southampton, provides an exceptional opportunity for nationally and internationally driven collaborative research, and provides a platform for excellent multi-disciplinary oceanographic research. As an in situ observation system, AMT informs on changes in biodiversity and function of the Atlantic ecosystem during this period of rapid change to our climate and biosphere. The aims of the AMT programme [www.amt-uk.org] are to quantify the nature and causes of ecological and biogeochemical variability in the planktonic ecosystems of the Atlantic Ocean, and to assess the effects of this variability on biological carbon cycling and air-sea exchange of radiatively active gases and aerosols. Between 1995 and 2005 marine and atmospheric data were collected twice a year along a 13,500 km transect in the Atlantic Ocean. The cruise track enabled biogeochemical measurements to be made within the poorly studied North and South Atlantic oligotrophic gyres as well as within equatorial and coastal upwelling regions. The range of ecosystems sampled has facilitated the calibration and validation of newly developed techniques, provided a testbed for comparative ecology and enabled the development of atmospheric and oceanographic models. The unique AMT dataset continues to be deposited and made available to the wider community through the British Oceanographic Data Centre.
|NSF Division of Ocean Sciences (NSF OCE)|
|NSF Division of Ocean Sciences (NSF OCE)|