Article

Local ancestry inference provides insight into Tilapia breeding programmes

Citation

Avallone A, Bartie KL, Selly SC, Taslima K, Campos Mendoza A & Bekaert M (2020) Local ancestry inference provides insight into Tilapia breeding programmes. Scientific Reports, 10 (1), Art. No.: 18613. https://doi.org/10.1038/s41598-020-75744-9

Abstract
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.

Keywords
Animal breeding; Bioinformatics; Genome informatics; Ichthyology; Phylogenetics; Population genetics

Journal
Scientific Reports: Volume 10, Issue 1

StatusPublished
FundersEuropean Commission (Horizon 2020)
Publication date31/12/2020
Publication date online29/10/2020
Date accepted by journal12/10/2020
URLhttp://hdl.handle.net/1893/31895
PublisherSpringer Science and Business Media LLC
eISSN2045-2322