Machine learning applied to transcriptomic data to identify genes associated with feed efficiency in pigs.

Journal: Genetics, selection, evolution : GSE
PMID: 30866799

Abstract

BACKGROUND: To date, the molecular mechanisms that underlie residual feed intake (RFI) in pigs are unknown. Results from different genome-wide association studies and gene expression analyses are not always consistent. The aim of this research was to use machine learning to identify genes associated with feed efficiency (FE) using transcriptomic (RNA-Seq) data from pigs that are phenotypically extreme for RFI.

Authors

  • Miriam Piles
    Animal Breeding and Genetics Program, Institute of Agriculture and Food Research and Technology (IRTA), Torre Marimon s/n, 08140, Caldes de Montbui, Barcelona, Spain. miriam.piles@irta.es.
  • Carlos Fernandez-Lozano
    Department of Computer Science and Information Technologies, Faculty of Computer Science, CITIC-Research Center of Information and Communication Technologies, Universidade da Coruña, A Coruña, Spain.
  • María Velasco-Galilea
    Animal Breeding and Genetics Program, Institute of Agriculture and Food Research and Technology (IRTA), Torre Marimon s/n, 08140, Caldes de Montbui, Barcelona, Spain.
  • Olga González-Rodríguez
    Animal Breeding and Genetics Program, Institute of Agriculture and Food Research and Technology (IRTA), Torre Marimon s/n, 08140, Caldes de Montbui, Barcelona, Spain.
  • Juan Pablo Sánchez
    Animal Breeding and Genetics Program, Institute of Agriculture and Food Research and Technology (IRTA), Torre Marimon s/n, 08140, Caldes de Montbui, Barcelona, Spain.
  • David Torrallardona
    Animal Nutrition Program, Institute of Agriculture and Food Research and Technology (IRTA), Mas de Bover, 43120, Constantí, Spain.
  • Maria Ballester
    Animal Breeding and Genetics Program, Institute of Agriculture and Food Research and Technology (IRTA), Torre Marimon s/n, 08140, Caldes de Montbui, Barcelona, Spain.
  • Raquel Quintanilla
    Animal Breeding and Genetics Program, Institute of Agriculture and Food Research and Technology (IRTA), Torre Marimon s/n, 08140, Caldes de Montbui, Barcelona, Spain.

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