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Supporting fisheries management with genomic tools: a case study of kingklip (Genypterus capensis) off southern Africa

Citation

Schulze, Melissa Jane; von der Heyden, Sophie; Henriques, Romina (2020), Supporting fisheries management with genomic tools: a case study of kingklip (Genypterus capensis) off southern Africa, Dryad, Dataset, https://doi.org/10.5061/dryad.2280gb5q1

Abstract

Kingklip, Genypterus capensis, is a valuable fish resource in southern African waters, with a wide geographic distribution spanning South Africa and Namibia. Previous studies have provided evidence for multiple stocks in South Africa, but the extent of stock structuring across the Southern African region remains unclear. In this study, we genotyped over 40 000 SNPs to characterise the spatial distribution of genomic variation for G. capensis throughout its core distribution. Results suggest that fish sampled at the northernmost range (off central Namibia) are characterised by lower genomic diversity, although the region exhibited the highest number of private SNPs, suggesting some degree of geographic isolation. Using neutral and putative outlier loci independently, we show that kingklip exhibits three population clusters, “northern Benguela”, “southern Benguela” and South African “South Coast”. Population differentiation was observed only using “outlier” loci, suggesting that local adaptation might be one of the main drivers of the observed differentiation. Overall, our research provides novel insights into the regional dynamics that can support the sustainable long-term exploitation of this valuable fisheries resource.

Usage Notes

ReadMe File:

Allele frequency file of biallelic SNPs, identified based on a minimum count of four, a minimum coverage of 20 and a maximum coverage of 500 reads > "MAA.420500.txt"

Input allele frequency files for corresponding "Full" (MAA.FULL.txt), "Neutral" (MAA.NEUTRAL.txt) and "Outlier" (MAA.OUTLIER.txt) datasets used for population sub-structuring analyses (Minimum count of 4,minimum coverage of 28 and maximum coverage of 100).

Scripts used for bioinformatic analyses and pipeline > "Scripts.txt"

R-script, "PopStructure.R", used for estimates of pairwise differentiation levels, using the 'diffCalc' command of diveRsity (Keenan et al.,2013).