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Genomics for Ruminants in Developing Countries: From Principles to Practice

Using genomic information, local ruminant populations can be better characterized and compared to selected ones. Genetic relationships between animals can be established even without systematic pedigree recording, provided a budget is available for genotyping. Genomic selection (GS) can rely on a su...

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Autores principales: Ducrocq, Vincent, Laloe, Denis, Swaminathan, Marimuthu, Rognon, Xavier, Tixier-Boichard, Michèle, Zerjal, Tatiana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6053532/
https://www.ncbi.nlm.nih.gov/pubmed/30057590
http://dx.doi.org/10.3389/fgene.2018.00251
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author Ducrocq, Vincent
Laloe, Denis
Swaminathan, Marimuthu
Rognon, Xavier
Tixier-Boichard, Michèle
Zerjal, Tatiana
author_facet Ducrocq, Vincent
Laloe, Denis
Swaminathan, Marimuthu
Rognon, Xavier
Tixier-Boichard, Michèle
Zerjal, Tatiana
author_sort Ducrocq, Vincent
collection PubMed
description Using genomic information, local ruminant populations can be better characterized and compared to selected ones. Genetic relationships between animals can be established even without systematic pedigree recording, provided a budget is available for genotyping. Genomic selection (GS) can rely on a subset of the total population and does not require a costly national infrastructure, e.g., based on progeny testing. Yet, the use of genomic tools for animal breeding in developing countries is still limited. We identify three main reasons for this: (i) the instruments for cheap recording of phenotypes and data management are still limiting. (ii) many developing countries are recurrently exposed to unfavorable conditions (heat, diseases, poor nutrition) requiring special attention to fitness traits, (iii) a high level of expertise in quantitative genetics, modeling, and data manipulation is needed to perform genomic analyses. Yet, the potential outcomes go much beyond genetic improvements and can improve the resilience of the whole farming system. They include a better management of genetic diversity of local populations, a more balanced genetic progress and the possibility to unravel the genetic basis of adaptation of local breeds through whole genome approaches. A GS program being developed by BAIF, a large Indian NGO, is analyzed as a pilot case. It relies on the creation of a female reference population of Bos indicus and crossbreds, recorded with modern technology (e.g., smartphones) to collect performances at low cost in tiny herds on production and fertility. Finally, recommendations for the implementation of GS in developing countries are proposed.
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spelling pubmed-60535322018-07-27 Genomics for Ruminants in Developing Countries: From Principles to Practice Ducrocq, Vincent Laloe, Denis Swaminathan, Marimuthu Rognon, Xavier Tixier-Boichard, Michèle Zerjal, Tatiana Front Genet Genetics Using genomic information, local ruminant populations can be better characterized and compared to selected ones. Genetic relationships between animals can be established even without systematic pedigree recording, provided a budget is available for genotyping. Genomic selection (GS) can rely on a subset of the total population and does not require a costly national infrastructure, e.g., based on progeny testing. Yet, the use of genomic tools for animal breeding in developing countries is still limited. We identify three main reasons for this: (i) the instruments for cheap recording of phenotypes and data management are still limiting. (ii) many developing countries are recurrently exposed to unfavorable conditions (heat, diseases, poor nutrition) requiring special attention to fitness traits, (iii) a high level of expertise in quantitative genetics, modeling, and data manipulation is needed to perform genomic analyses. Yet, the potential outcomes go much beyond genetic improvements and can improve the resilience of the whole farming system. They include a better management of genetic diversity of local populations, a more balanced genetic progress and the possibility to unravel the genetic basis of adaptation of local breeds through whole genome approaches. A GS program being developed by BAIF, a large Indian NGO, is analyzed as a pilot case. It relies on the creation of a female reference population of Bos indicus and crossbreds, recorded with modern technology (e.g., smartphones) to collect performances at low cost in tiny herds on production and fertility. Finally, recommendations for the implementation of GS in developing countries are proposed. Frontiers Media S.A. 2018-07-13 /pmc/articles/PMC6053532/ /pubmed/30057590 http://dx.doi.org/10.3389/fgene.2018.00251 Text en Copyright © 2018 Ducrocq, Laloe, Swaminathan, Rognon, Tixier-Boichard and Zerjal. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Ducrocq, Vincent
Laloe, Denis
Swaminathan, Marimuthu
Rognon, Xavier
Tixier-Boichard, Michèle
Zerjal, Tatiana
Genomics for Ruminants in Developing Countries: From Principles to Practice
title Genomics for Ruminants in Developing Countries: From Principles to Practice
title_full Genomics for Ruminants in Developing Countries: From Principles to Practice
title_fullStr Genomics for Ruminants in Developing Countries: From Principles to Practice
title_full_unstemmed Genomics for Ruminants in Developing Countries: From Principles to Practice
title_short Genomics for Ruminants in Developing Countries: From Principles to Practice
title_sort genomics for ruminants in developing countries: from principles to practice
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6053532/
https://www.ncbi.nlm.nih.gov/pubmed/30057590
http://dx.doi.org/10.3389/fgene.2018.00251
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