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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. gr...

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Autores principales: Avallone, Alex, Bartie, Kerry L., Selly, Sarah-Louise C., Taslima, Khanam, Campos Mendoza, Antonio, Bekaert, Michaël
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596482/
https://www.ncbi.nlm.nih.gov/pubmed/33122794
http://dx.doi.org/10.1038/s41598-020-75744-9
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author Avallone, Alex
Bartie, Kerry L.
Selly, Sarah-Louise C.
Taslima, Khanam
Campos Mendoza, Antonio
Bekaert, Michaël
author_facet Avallone, Alex
Bartie, Kerry L.
Selly, Sarah-Louise C.
Taslima, Khanam
Campos Mendoza, Antonio
Bekaert, Michaël
author_sort Avallone, Alex
collection PubMed
description 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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spelling pubmed-75964822020-10-30 Local ancestry inference provides insight into Tilapia breeding programmes Avallone, Alex Bartie, Kerry L. Selly, Sarah-Louise C. Taslima, Khanam Campos Mendoza, Antonio Bekaert, Michaël Sci Rep Article 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. Nature Publishing Group UK 2020-10-29 /pmc/articles/PMC7596482/ /pubmed/33122794 http://dx.doi.org/10.1038/s41598-020-75744-9 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Avallone, Alex
Bartie, Kerry L.
Selly, Sarah-Louise C.
Taslima, Khanam
Campos Mendoza, Antonio
Bekaert, Michaël
Local ancestry inference provides insight into Tilapia breeding programmes
title Local ancestry inference provides insight into Tilapia breeding programmes
title_full Local ancestry inference provides insight into Tilapia breeding programmes
title_fullStr Local ancestry inference provides insight into Tilapia breeding programmes
title_full_unstemmed Local ancestry inference provides insight into Tilapia breeding programmes
title_short Local ancestry inference provides insight into Tilapia breeding programmes
title_sort local ancestry inference provides insight into tilapia breeding programmes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596482/
https://www.ncbi.nlm.nih.gov/pubmed/33122794
http://dx.doi.org/10.1038/s41598-020-75744-9
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