Version 4

Whole genome resequencing data enables a targeted SNP panel for conservation and aquaculture of Oreochromis cichlid fishes

Ciezarek, Adam;Ford, Antonia;Etherington, Graham;Kasozi, Nasser;Malinsky, Milan;Mehta, Tarang;Penso-Dolfin, Luca;Ngatunga, Benjamin;Shechonge, Asilatu;Tamatamah, Rashid;Haerty, Wilfried;di Palma, Federica;Genner, Martin;George, Turner

Description

Cichlid fish of the genus Oreochromis form the basis of the global tilapia aquaculture and fisheries industries. Broodstocks for aquaculture are often collected from wild populations, which in Africa may be from locations containing multiple Oreochromis species. However, many species are difficult to distinguish morphologically, hampering efforts to maintain good quality farmed strains. Additionally, non-native farmed tilapia populations are known to be widely distributed across Africa and to hybridize with native Oreochromis species, which themselves are important for capture fisheries. The morphological identification of these hybrids is particularly unreliable. Here, we describe the development of a single nucleotide polymorphism (SNP) genotyping panel from whole-genome resequencing data that enables targeted species identification in Tanzania. We demonstrate that an optimized panel of 96 genome-wide SNPs based on FST outliers performs comparably to whole genome resequencing in distinguishing species and identifying hybrids. We also show this panel outperforms microsatellite-based and phenotype-based classification methods. Case studies indicate several locations where introduced aquaculture species have become established in the wild, threatening native Oreochromis species. The novel SNP markers identified here represent an important resource for assessing broodstock purity in hatcheries and helping to conserve unique endemic biodiversity.

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Mentions (0)

Metrics

Dataset Index

0.8

FAIR Score

77%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Dryad

License

Creative Commons Zero v1.0 Universal

Assigned Domain

Subfield

General Agricultural and Biological Sciences

Field

Agricultural and Biological Sciences

Domain

Life Sciences

Confidence Score

56%

Source

Scholar Data Model

Normalization Factors

FT

57.69

CTw

1.00

MTw

1.00