Phenomes : the current frontier in animal breeding
Perez-Enciso, Miguel (Centre de Recerca en Agrigenòmica)
Steibel, Juan P. (Michigan State University. Department of Fisheries and Wildlife)

Data:	2021
Resum:	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.
Ajuts:	Agencia Estatal de Investigación PID2019-108829RB-I00 Ministerio de Economía y Competitividad SEV-2015-0533
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Publicat a:	Genetics, selection, evolution, Vol. 53 (March 2021) , art. 22, ISSN 1297-9686

DOI: 10.1186/s12711-021-00618-1
PMID: 33673800

10 p, 1.2 MB

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