Kokkinias, P. | bioRxiv Science

bioRxiv2023

Development of genomic markers associated to production traits in lumpfish (Cyclopterus lumpus)

Cleaner fish species have gained great importance in the control of sea lice, among them, lumpfish (Cyclopterus lumpus) has become one of the most popular. Lumpfish life cycle has been closed, and hatchery reproduction is now possible, however, current production is reliant on wild caught broodstock to meet the increasing demand. Selective breeding practices are called to play an important role in the successful breeding of most aquaculture species, including lumpfish. In this study we analysed a lumpfish population for the identification of genomic markers linked to production traits. Sequencing of RAD libraries allowed us to identify, 7,193 informative markers within the sampled individuals. Genome wide association analysis for sex, weight, condition factor and standard length was performed. One single major QTL region was identified for sex determination, while nine QTL regions were detected for weight, and three QTL regions for standard length. A total of 177 SNP markers of interest (from QTL regions) and 399 top Fst SNP markers were combined in a low-density panel, useful to obtain relevant genetic information from lumpfish populations. Moreover, a robust combined subset of 29 SNP markers (10 associated to sex, 14 to weight and 18 to standard length) provided over 90% accuracy in predicting the animals phenotype. Overall, our findings provide significant insights into the genetic control of important traits in lumpfish and deliver important genomic resources that will facilitate the establishment of selective breeding programs in lumpfish.

genomics↗

bioRxiv2022

Impact of mixing between parallel year groups on genomic prediction in Atlantic salmon breeding programmes under random selection

A commercial breeding programme in Atlantic salmon utilises a four-year generation interval with four parallel breeding populations. In this study, we develop a computer simulation of a salmon breeding programme and explore the impact of gene flow between the parallel year groups on the accuracy of genomic prediction within and between breeding lines. We simulated four parallel lines for 10 discrete generations with random selection and different mixing rates between parallel year groups. The genetic distance between fish (as a measure of diversity) and the accuracy of estimated genomic breeding values were used as criteria of comparison. With no mixing the genetic distance increased between populations, the genetic variation within populations decreased and there was no increase in accuracy when combining data across populations. Even a low percentage of mixing decreased the genetic distance between populations and increased the genetic variation within populations. The higher the percentage of mixing the faster the lines became more similar. The accuracy of prediction climbed as the percentage of mixing increased. The increase in accuracy from the combined evaluation approach compared to the within evaluation approach was greater with an increased percentage of mixing. In conclusion, if there is no gene flow between populations the lines drift apart and there is no value in combining information across populations for genomic breeding value prediction. Only a low amount of mixing between lines brings the lines closer together and facilitates the use of information across lines to improve breeding value prediction. Optimising gene flow between lines should be an integral part of salmon breeding programme design.

genetics↗