Local ancestry inference provides insight into Tilapia breeding programmes

Tilapia is one of the most commercially valuable species in aquaculture with over 5 million tonnes of Nile tilapia, Oreochromis niloticus , produced worldwide every year. It has become increasingly important to keep track of the inheritance of the selected traits under continuous improvement (e.g. g...

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Bibliographic Details
Published inScientific reports Vol. 10; no. 1; p. 18613
Main Authors Avallone, Alex, Bartie, Kerry L., Selly, Sarah-Louise C., Taslima, Khanam, Campos Mendoza, Antonio, Bekaert, Michaël
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 29.10.2020
Nature Publishing Group
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Summary:Tilapia is one of the most commercially valuable species in aquaculture with over 5 million tonnes of Nile tilapia, Oreochromis niloticus , produced worldwide every year. It has become increasingly important to keep track of the inheritance of the selected traits under continuous improvement (e.g. growth rate, size at maturity or genetic gender), as selective breeding has also resulted in genes that can hitchhike as part of the process. The goal of this study was to generate a Local Ancestry Interence workflow that harnessed existing tilapia genotyping-by-sequencing studies, such as Double Digest RAD-seq derived Single-Nucleotide Polymorphism markers. We developed a workflow and implemented a suite of tools to resolve the local ancestry of each chromosomal locus based on reference panels of tilapia species of known origin. We used tilapia species, wild populations and breeding programmes to validate our methods. The precision of the pipeline was evaluated on the basis of its ability to identify the genetic makeup of samples of known ancestry. The easy and inexpensive application of local ancestry inference in breeding programmes will facilitate the monitoring of the genetic profile of individuals of interest, the tracking of the movement of genes from parents to offspring and the detection of hybrids and their origin.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-020-75744-9