Refer to the following publication for complete methodology details:
\nGoetze, E.,\u00a0Andrews, K., Peijnenburg, K. T. C. A., Portner, E., Norton, E. L. (2015) Temporal Stability of Genetic Structure in a Mesopelagic Copepod.\u00a0\u00a0PLoS One\u00a010(8): e0136087.\u00a0doi:10.1371/journal.pone.0136087
\nIn summary (excerpted from above):
\nFor\u00a0H.\u00a0longicornis species 1, deviations from Hardy-Weinberg equilibrium (HWE) and linkage disequilibrium were examined using ARLEQUIN v3.5.1.3 and GENEPOP v4.2 for all microsatellite loci [36\u201338]. We tested for the presence of null alleles in microsatellite data using MICROCHECKER v2.2.3 [39], and estimated null allele frequencies and calculated population pairwise\u00a0FST\u00a0values with correction for null alleles in FreeNA [40]. 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\u00a0FST\u00a0values were calculated among all sample sites using both microsatellite and mtCOII data, as a measure of population subdivision across samples (ARLEQUIN v3.5.1.3, [38]). Significance was assessed following correction for multiple comparisons using the false discovery rate (FDR, [42,43]). Pairwise \u03a6ST\u00a0values 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 [44], 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 \u03a6ST\u00a0values, and to estimate genetic diversity at each site. Hierarchical Analyses of Molecular Variance (AMOVA) based on\u00a0FST\u00a0were 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\u00a0FST\u00a0values 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\u00a0FST\u00a0values 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\u00a0steps followed by 106\u00a0steps, with and without using sampling location as a prior. We ran these analyses for each of the 2010 and 2012 datasets using\u00a0K\u00a0= 1 to\u00a0K\u00a0= 10, and for the dataset of combined years using\u00a0K\u00a0= 1 to\u00a0K\u00a0= 20. We ran three separate replicates for each K to investigate consistency of Pr(X|K). The true\u00a0K\u00a0was evaluated by visual inspection of barplots and comparing Pr(X|K) across\u00a0K\u00a0values.
These microsatellite data derive from individual copepods collected on Atlantic Meridional Transect cruise 22 (AMT22) in 2012 (RRS James Cook).\u00a0
\nThese data are reported on in Goetze, E.,\u00a0Andrews, K., Peijnenburg, K. T. C. A., Portner, E., Norton, E. L. (2015) Temporal Stability of Genetic Structure in a Mesopelagic Copepod.\u00a0\u00a0PLoS One\u00a010(8): e0136087.\u00a0doi:10.1371/journal.pone.0136087
\nThese microsatellite data are also available under supporting information S1 File.csv at PLoS One.
\nMitochondrial cytochrome c oxidase subunit II (mtCOII) sequence data from this study\u00a0are available at NCBI under accession numbers\u00a0KR872026-KR872295 and KC713636-KC713781. Oceanographic data from\u00a0the Atlantic Meridional Transect cruises are\u00a0available through the British Oceanographic Data\u00a0Center.
\nAbstract:\u00a0Although 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.\u00a0
BCO-DMO Processing:
\n- modified parameter names to conform with BCO-DMO naming conventions
\n- \"0\" missing value code changed to \"nd\"