Machine learning algorithms identified relevant SNPs for milk fat content in cattle

In recent years, machine learning methods have been shown to be efficient in identifying a subset of single nucleotide polymorphisms (SNP) underlying a trait of interest. The aim of this study was the construction of predictive models using machine learning algorithms, for the identification of loci...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Ríos, Pablo, Raschia, María Agustina, Maizon, Daniel O., Demitrio, Daniel, Poli, Mario A.
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2021
Materias:
Ciencias Informáticas
Machine learning methods
Single nucleotide polymorphisms
Estimated breeding values
Dairy cattle
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/140595
http://50jaiio.sadio.org.ar/pdfs/cai/CAI-14.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-140595
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Machine learning methods
Single nucleotide polymorphisms
Estimated breeding values
Dairy cattle
spellingShingle Ciencias Informáticas
Machine learning methods
Single nucleotide polymorphisms
Estimated breeding values
Dairy cattle
Ríos, Pablo
Raschia, María Agustina
Maizon, Daniel O.
Demitrio, Daniel
Poli, Mario A.
Machine learning algorithms identified relevant SNPs for milk fat content in cattle
topic_facet Ciencias Informáticas
Machine learning methods
Single nucleotide polymorphisms
Estimated breeding values
Dairy cattle
description In recent years, machine learning methods have been shown to be efficient in identifying a subset of single nucleotide polymorphisms (SNP) underlying a trait of interest. The aim of this study was the construction of predictive models using machine learning algorithms, for the identification of loci that best explain the variance in milk fat production of dairy cattle. Further objectives involve determining the genes flanking relevant SNPs and retrieving the pathways, biological processes, or molecular functions overrepresented by them. Fat production values adjusted for fixed effects (FPadj) and estimated breeding values for milk fat production (EBVFP) were used as phenotypes and SNPs as predictor variables. The models constructed for EBVFP performed better and yield considerably less relevant SNPs than models for FPadj. Among the genes flanking relevant SNPs, signaling transduction pathways and gated channel activities were detected as overrepresented. The loci obtained for EBVFP matched better with previously reported relevant loci for milk fat content than those obtained for FPadj. Based on the better performance showed by the models trained for EBVFP and their agreement with previous reported results for the trait studied, we conclude that the relationship among individuals should be accounted for in the phenotype used.
format Objeto de conferencia
Objeto de conferencia
author Ríos, Pablo
Raschia, María Agustina
Maizon, Daniel O.
Demitrio, Daniel
Poli, Mario A.
author_facet Ríos, Pablo
Raschia, María Agustina
Maizon, Daniel O.
Demitrio, Daniel
Poli, Mario A.
author_sort Ríos, Pablo
title Machine learning algorithms identified relevant SNPs for milk fat content in cattle
title_short Machine learning algorithms identified relevant SNPs for milk fat content in cattle
title_full Machine learning algorithms identified relevant SNPs for milk fat content in cattle
title_fullStr Machine learning algorithms identified relevant SNPs for milk fat content in cattle
title_full_unstemmed Machine learning algorithms identified relevant SNPs for milk fat content in cattle
title_sort machine learning algorithms identified relevant snps for milk fat content in cattle
publishDate 2021
url http://sedici.unlp.edu.ar/handle/10915/140595
http://50jaiio.sadio.org.ar/pdfs/cai/CAI-14.pdf
work_keys_str_mv AT riospablo machinelearningalgorithmsidentifiedrelevantsnpsformilkfatcontentincattle
AT raschiamariaagustina machinelearningalgorithmsidentifiedrelevantsnpsformilkfatcontentincattle
AT maizondanielo machinelearningalgorithmsidentifiedrelevantsnpsformilkfatcontentincattle
AT demitriodaniel machinelearningalgorithmsidentifiedrelevantsnpsformilkfatcontentincattle
AT polimarioa machinelearningalgorithmsidentifiedrelevantsnpsformilkfatcontentincattle
bdutipo_str Repositorios
_version_ 1764820459176591360

Ejemplares similares