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Applications of Omics Technology for Livestock Selection and Improvement

Conventional animal selection and breeding methods were based on the phenotypic performance of the animals. These methods have limitations, particularly for sex-limited traits and traits expressed later in the life cycle (e.g., carcass traits). Consequently, the genetic gain has been slow with high...

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Autores principales: Chakraborty, Dibyendu, Sharma, Neelesh, Kour, Savleen, Sodhi, Simrinder Singh, Gupta, Mukesh Kumar, Lee, Sung Jin, Son, Young Ok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9204716/
https://www.ncbi.nlm.nih.gov/pubmed/35719396
http://dx.doi.org/10.3389/fgene.2022.774113
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author Chakraborty, Dibyendu
Sharma, Neelesh
Kour, Savleen
Sodhi, Simrinder Singh
Gupta, Mukesh Kumar
Lee, Sung Jin
Son, Young Ok
author_facet Chakraborty, Dibyendu
Sharma, Neelesh
Kour, Savleen
Sodhi, Simrinder Singh
Gupta, Mukesh Kumar
Lee, Sung Jin
Son, Young Ok
author_sort Chakraborty, Dibyendu
collection PubMed
description Conventional animal selection and breeding methods were based on the phenotypic performance of the animals. These methods have limitations, particularly for sex-limited traits and traits expressed later in the life cycle (e.g., carcass traits). Consequently, the genetic gain has been slow with high generation intervals. With the advent of high-throughput omics techniques and the availability of multi-omics technologies and sophisticated analytic packages, several promising tools and methods have been developed to estimate the actual genetic potential of the animals. It has now become possible to collect and access large and complex datasets comprising different genomics, transcriptomics, proteomics, metabolomics, and phonemics data as well as animal-level data (such as longevity, behavior, adaptation, etc.,), which provides new opportunities to better understand the mechanisms regulating animals’ actual performance. The cost of omics technology and expertise of several fields like biology, bioinformatics, statistics, and computational biology make these technology impediments to its use in some cases. The population size and accurate phenotypic data recordings are other significant constraints for appropriate selection and breeding strategies. Nevertheless, omics technologies can estimate more accurate breeding values (BVs) and increase the genetic gain by assisting the section of genetically superior, disease-free animals at an early stage of life for enhancing animal productivity and profitability. This manuscript provides an overview of various omics technologies and their limitations for animal genetic selection and breeding decisions.
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spelling pubmed-92047162022-06-18 Applications of Omics Technology for Livestock Selection and Improvement Chakraborty, Dibyendu Sharma, Neelesh Kour, Savleen Sodhi, Simrinder Singh Gupta, Mukesh Kumar Lee, Sung Jin Son, Young Ok Front Genet Genetics Conventional animal selection and breeding methods were based on the phenotypic performance of the animals. These methods have limitations, particularly for sex-limited traits and traits expressed later in the life cycle (e.g., carcass traits). Consequently, the genetic gain has been slow with high generation intervals. With the advent of high-throughput omics techniques and the availability of multi-omics technologies and sophisticated analytic packages, several promising tools and methods have been developed to estimate the actual genetic potential of the animals. It has now become possible to collect and access large and complex datasets comprising different genomics, transcriptomics, proteomics, metabolomics, and phonemics data as well as animal-level data (such as longevity, behavior, adaptation, etc.,), which provides new opportunities to better understand the mechanisms regulating animals’ actual performance. The cost of omics technology and expertise of several fields like biology, bioinformatics, statistics, and computational biology make these technology impediments to its use in some cases. The population size and accurate phenotypic data recordings are other significant constraints for appropriate selection and breeding strategies. Nevertheless, omics technologies can estimate more accurate breeding values (BVs) and increase the genetic gain by assisting the section of genetically superior, disease-free animals at an early stage of life for enhancing animal productivity and profitability. This manuscript provides an overview of various omics technologies and their limitations for animal genetic selection and breeding decisions. Frontiers Media S.A. 2022-06-02 /pmc/articles/PMC9204716/ /pubmed/35719396 http://dx.doi.org/10.3389/fgene.2022.774113 Text en Copyright © 2022 Chakraborty, Sharma, Kour, Sodhi, Gupta, Lee and Son. https://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
Chakraborty, Dibyendu
Sharma, Neelesh
Kour, Savleen
Sodhi, Simrinder Singh
Gupta, Mukesh Kumar
Lee, Sung Jin
Son, Young Ok
Applications of Omics Technology for Livestock Selection and Improvement
title Applications of Omics Technology for Livestock Selection and Improvement
title_full Applications of Omics Technology for Livestock Selection and Improvement
title_fullStr Applications of Omics Technology for Livestock Selection and Improvement
title_full_unstemmed Applications of Omics Technology for Livestock Selection and Improvement
title_short Applications of Omics Technology for Livestock Selection and Improvement
title_sort applications of omics technology for livestock selection and improvement
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9204716/
https://www.ncbi.nlm.nih.gov/pubmed/35719396
http://dx.doi.org/10.3389/fgene.2022.774113
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