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Phenomes: the current frontier in animal breeding
Improvements in genomic technologies have outpaced the most optimistic predictions, allowing industry-scale application of genomic selection. However, only marginal gains in genetic prediction accuracy can now be expected by increasing marker density up to sequence, unless causative mutations are id...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7934239/ https://www.ncbi.nlm.nih.gov/pubmed/33673800 http://dx.doi.org/10.1186/s12711-021-00618-1 |
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author | Pérez-Enciso, Miguel Steibel, Juan P. |
author_facet | Pérez-Enciso, Miguel Steibel, Juan P. |
author_sort | Pérez-Enciso, Miguel |
collection | PubMed |
description | Improvements in genomic technologies have outpaced the most optimistic predictions, allowing industry-scale application of genomic selection. However, only marginal gains in genetic prediction accuracy can now be expected by increasing marker density up to sequence, unless causative mutations are identified. We argue that some of the most scientifically disrupting and industry-relevant challenges relate to ‘phenomics’ instead of ‘genomics’. Thanks to developments in sensor technology and artificial intelligence, there is a wide range of analytical tools that are already available and many more will be developed. We can now address some of the pressing societal demands on the industry, such as animal welfare concerns or efficiency in the use of resources. From the statistical and computational point of view, phenomics raises two important issues that require further work: penalization and dimension reduction. This will be complicated by the inherent heterogeneity and ‘missingness’ of the data. Overall, we can expect that precision livestock technologies will make it possible to collect hundreds of traits on a continuous basis from large numbers of animals. Perhaps the main revolution will come from redesigning animal breeding schemes to explicitly allow for high-dimensional phenomics. In the meantime, phenomics data will definitely enlighten our knowledge on the biological basis of phenotypes. |
format | Online Article Text |
id | pubmed-7934239 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-79342392021-03-05 Phenomes: the current frontier in animal breeding Pérez-Enciso, Miguel Steibel, Juan P. Genet Sel Evol Opinion Improvements in genomic technologies have outpaced the most optimistic predictions, allowing industry-scale application of genomic selection. However, only marginal gains in genetic prediction accuracy can now be expected by increasing marker density up to sequence, unless causative mutations are identified. We argue that some of the most scientifically disrupting and industry-relevant challenges relate to ‘phenomics’ instead of ‘genomics’. Thanks to developments in sensor technology and artificial intelligence, there is a wide range of analytical tools that are already available and many more will be developed. We can now address some of the pressing societal demands on the industry, such as animal welfare concerns or efficiency in the use of resources. From the statistical and computational point of view, phenomics raises two important issues that require further work: penalization and dimension reduction. This will be complicated by the inherent heterogeneity and ‘missingness’ of the data. Overall, we can expect that precision livestock technologies will make it possible to collect hundreds of traits on a continuous basis from large numbers of animals. Perhaps the main revolution will come from redesigning animal breeding schemes to explicitly allow for high-dimensional phenomics. In the meantime, phenomics data will definitely enlighten our knowledge on the biological basis of phenotypes. BioMed Central 2021-03-05 /pmc/articles/PMC7934239/ /pubmed/33673800 http://dx.doi.org/10.1186/s12711-021-00618-1 Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Opinion Pérez-Enciso, Miguel Steibel, Juan P. Phenomes: the current frontier in animal breeding |
title | Phenomes: the current frontier in animal breeding |
title_full | Phenomes: the current frontier in animal breeding |
title_fullStr | Phenomes: the current frontier in animal breeding |
title_full_unstemmed | Phenomes: the current frontier in animal breeding |
title_short | Phenomes: the current frontier in animal breeding |
title_sort | phenomes: the current frontier in animal breeding |
topic | Opinion |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7934239/ https://www.ncbi.nlm.nih.gov/pubmed/33673800 http://dx.doi.org/10.1186/s12711-021-00618-1 |
work_keys_str_mv | AT perezencisomiguel phenomesthecurrentfrontierinanimalbreeding AT steibeljuanp phenomesthecurrentfrontierinanimalbreeding |