Multigenerational prediction of genetic values using genome-enabled prediction

Autor: Vinícius Quintão Carneiro, Cosme Damião Cruz, Gabi Nunes Silva, Isabela de Castro Sant' Anna, Marciane da Silva Oliveira, Moysés Nascimento, Ricardo Augusto Diniz Cabral Ferreira, Francyse Edith Chagas
Jazyk: angličtina
Rok vydání: 2019
Předmět:
0106 biological sciences
0301 basic medicine
Linkage disequilibrium
Research Validity
Heredity
Population genetics
01 natural sciences
Linkage Disequilibrium
Statistics
education.field_of_study
Multidisciplinary
Genomics
Research Assessment
Phenotypes
Phenotype
Medicine
Inbreeding
Algorithms
Genome
Plant
Research Article
Genotyping
Genotype
Science
Population
Quantitative Trait Loci
Outcrossing
Quantitative trait locus
Biology
Research and Analysis Methods
Genes
Plant
Polymorphism
Single Nucleotide
03 medical and health sciences
Genetics
Selection
Genetic
education
Molecular Biology Techniques
Molecular Biology
Evolutionary Biology
Population Biology
Models
Genetic
Biology and Life Sciences
Reproducibility of Results
Mating system
Plant Breeding
030104 developmental biology
Genetics
Population
Genetic Loci
Population Genetics
010606 plant biology & botany
Zdroj: PLoS ONE
PLoS ONE, Vol 14, Iss 1, p e0210531 (2019)
ISSN: 1932-6203
Popis: The identification of elite individuals is a critical component of most breeding programs. However, the achievement of this goal is limited by the high cost of phenotyping and experimental research. A significant benefit of genomic selection (GS) to plant breeding is the identification of elite individuals without the need for phenotyping. This study aimed to propose different calibration strategies using combinations between generations from different genetic backgrounds to improve the reliability of GS and to investigate the effects of LD in different types of mating systems: outcrossing (An) self-pollination (Sn) and hybridization (Hn). For this purpose, we simulated a genome with 10 linkage groups. In each group, two QTL were simulated. Subsequently, an F2 population was created, followed by four generations of inbreeding (S1 to S4, H1 to H 4, A1, to A4,). Quantitative traits were simulated in three scenarios considering three degrees of dominance (d/a = 0, 0.5 and 1) and two broad sense heritabilities (h2 = 0.30 and 0.70), totaling six genetic architectures. To evaluate prediction reliability, a model (RR-BLUP) was trained in one generation and used to predict the following generations of mating systems. For example, the marker effects estimated in the F2 population were used to estimate the expected genomic breeding value (GEBV) in populations S1 through A4. The squared correlation between the GEBV and the true genetic value were used to measure the reliability of the predictions. Independently of the population used to estimate the marker effect, reliability showed the lowest values in the scenario where d = 1. For any scenario, the use of the multigenerational prediction methodology improved the reliability of GS.
Databáze: OpenAIRE
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje