Genetic assignment of individuals to source populations using network estimation tools

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

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 F_ST 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.

Dispersal in a house sparrow metapopulation: An integrative case study of genetic assignment calibrated with ecological data and pedigree information

Dispersal has a crucial role determining ecoevolutionary dynamics through both gene flow and population size regulation. However, to study dispersal and its consequences, one must distinguish immigrants from residents. Dispersers can be identified using telemetry, capture-mark-recapture (CMR) methods, or genetic assignment methods. All of these methods have disadvantages, such as high costs and substantial field efforts needed for telemetry and CMR surveys, and adequate genetic distance required in genetic assignment. In this study, we used genome-wide 200K Single Nucleotide Polymorphism data and two different genetic assignment approaches (GSI_SIM, Bayesian framework; BONE, network-based estimation) to identify the dispersers in a house sparrow (Passer domesticus) metapopulation sampled over 16 years. Our results showed higher assignment accuracy with BONE. Hence, we proceeded to diagnose potential sources of errors in the assignment results from the BONE method due to variation in levels of interpopulation genetic differentiation, intrapopulation genetic variation and sample size. We show that assignment accuracy is high even at low levels of genetic differentiation and that it increases with the proportion of a population that has been sampled. Finally, we highlight that dispersal studies integrating both ecological and genetic data provide robust assessments of the dispersal patterns in natural populations.