Published June 10, 2020 | Version v1
Dataset Open

Along-shelf connectivity and circumpolar gene flow in Antarctic silverfish (Pleuragramma antarctica)

  • 1. Alfred Wegener Institute for Polar and Marine Research
  • 2. University of Padua
  • 3. University of Koblenz and Landau
  • 4. Old Dominion University

Description

The Antarctic silverfish (Pleuragramma antarctica) is a critically important forage species with a circumpolar distribution and is unique among other notothenioid species for its wholly pelagic life cycle. Previous studies have provided mixed evidence of population structure over regional and circumpolar scales. The aim of the present study was to test the recent population hypothesis for Antarctic silverfish, which emphasizes the interplay between life history and hydrography in shaping connectivity. A total of 1067 individuals were collected over 25 years from different locations on a circumpolar scale. Samples were genotyped at fifteen microsatellites to assess population differentiation and genetic structuring using clustering methods, F-statistics, and hierarchical analysis of variance. A lack of differentiation was found between locations connected by the Antarctic Slope Front Current (ASF), indicative of high levels of gene flow. However, gene flow was significantly reduced at the South Orkney Islands and the western Antarctic Peninsula where the ASF is absent. This pattern of gene flow emphasized the relevance of large-scale circulation as a mechanism for circumpolar connectivity. Chaotic genetic patchiness characterized population structure over time, with varying patterns of differentiation observed between years, accompanied by heterogeneous standard length distributions. The present study supports a more nuanced version of the genetic panmixia hypothesis that reflects physical-biological interactions over the life history.

Notes

Pleuragramma2018_Genotypes_15loci_GENEPOP.txt

Text file containing the genotypes of all analyzed individuals at the 15 microsatellite loci considered in the final analysis. Data are divided by the 19 population divisions based on the 19 sampling provenances of samples. File prepared using CREATE ver 1.37 (Coombs et al. 2008) for compatibility with GENEPOP online (Rousset 2008), a common format for downstream bioinformatics analyses.

Coombs JA, Letcher BH, Nislow KH (2008) create: a software to create input files from diploid genotypic data for 52 genetic software programs. Molecular ecology resources 8:578-580
Rousset F (2008) GENEPOP'007: A complete re-implementation of the GENEPOP software for Windows and Linux. Molecular ecology resources 8:103-106
Pleuragramma2018_Genotypes_metadata.xlsx

Excel file containing all metadata associated with the genotypes produced in this study.

Metadata (columns A – U) headers are:

  • Study #: the ID number of the samples used in the present study. Samples without Study # (na) represent samples from a previous study (Agostini et al. 2015) - only the genotypes of these samples were used in the present study;
  • Extract-DNA box ID: the DNA extraction ID combined with the ID of the storage box where the genomic DNA was stored (na values refer to samples from Agostini et al. 2015);
  • BMR CODE: the ID given to sequences for samples produced by BMR (na values refer to samples from Agostini et al. 2015);
  • Age: life stage: adult, juvenile, larva (na values refer to samples from Agostini et al. 2015);
  • Tissue type: the type of tissue from which DNA was extracted: muscle, fin clip, fin/m (fin and muscle), whole (for larvae and juveniles) (na values refer to samples from Agostini et al. 2015);
  • Year: sampling year;
  • Geographic Origin: sampling area;
  • Comment: additional information related to the sample, where relevant;
  • Dataset: Cecilia (Agostini et al. 2015) or Jilda (present study);
  • Population: population labels corresponding to sampling areas, representing the 19 population divisions;
  • Pop specific: population labels corresponding to sampling location, further dividing the 19 population divisions into population subdivisions by sampling station within the 19 sampling areas;
  • study#_pop ID: individual sample IDs based on Study # and population ID for samples from the present study, and Agostini et al. 2015 sample ID and population ID for samples from Agostini et al. 2015;
  • study#_pop specific ID: individual sample IDs based on Study # and pop specific ID for samples from the present study, and Agostini et al. 2015 sample ID and pop specific ID for samples from Agostini et al. 2015;
  • Pop 6: population labels corresponding to the 6 population divisions based on sampling region;
  • station: sampling station information where available;
  • depth: sampling depth in m;
  • SL: standard length of sampled fish in cm where available;
  • Cruise: name of research cruise during which sample was collected;
  • n: total number of individuals in Pop specific group divisions;
  • Lat: latitude of sampling location, where available;
  • Long: longitude of sampling location, where available.

Genotype data (columns V – BA) correspond to the genotype information for samples at the 16 total microsatellite loci sequenced in this study. Only 15 loci were ultimately used in the analysis, as allele Ch11230, columns AP and AQ, was problematic due to stuttering and interference from other fluorophores used during sequencing. Genotype information is expressed as whole numbers based on the output derived from Flexibin 2 (Amos et al. 2007), which takes microsatellite size information in base pairs and groups these into discrete allele categories based on the repeat length of the microsatellite. In this spreadsheet, each locus has two columns of information, the first providing the genotype of the first allele for that locus for a given individual, the second providing the genotype for the second allele for that locus for a given individual.

Amos W, Hoffman JI, Frodsham A, Zhang L, Best S, Hill AVS (2007) Automated binning of microsatellite alleles: Problems and solutions. Molecular Ecology Notes 7:10-14

Funding provided by: Fondazione Cassa di Risparmio di Padova e Rovigo
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000706
Award Number: Cariparo Fellowship for foreign students

Funding provided by: Scientific Committee on Antarctic Research
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000706
Award Number: SCAR fellowship

Funding provided by: Antarctic Science International (ASI)*
Crossref Funder Registry ID:
Award Number: ASI Bursary

Funding provided by: Erasmus+
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100010790
Award Number: Student Traineeship

Funding provided by: Antarctic Science International (ASI)
Crossref Funder Registry ID:
Award Number: ASI Bursary

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