Abstract
The objective of this study was to verify the accuracy of the Genome-Wide Selection (GWS) method in tropical maize breeding for root traits under conditions of nitrogen and phosphorus stress. Forty-one single-crosses were evaluated in two experiments. The first experiment considered low nitrogen availability, and the second experiment considered low phosphorus availability. A randomized block design with two replicates was used. The lateral and axial root lengths were measured using WinRhizo software. The analysis of deviance was calculated using the Restricted Maximum Likelihood/Best Linear Unbiased Prediction (REML/BLUP) method. Eighty microsatellite markers were used to genotype the estimation population. The Random Regression method was used to analyze the GWS (RR-BLUP/GWS) data. The gains per unit time of the GWS and the phenotypic selection method were compared, as the standard phenotypic selection methods were considered to be the Recurrent Selection. The GWS accuracy was higher than the phenotypic selection accuracy for all of the traits evaluated. Thus, the GWS method may significantly increase the genetic gains for root traits that are obtained in tropical maize breeding programs for nutritional stress conditions.
Highlights
The Genome-Wide Selection (GWS) method simultaneously predicts the genetic effects of a large number of molecular markers that are distributed throughout the whole genome of an organism in order to capture the effects of all of the loci and explain the entire genetic variation of a quantitative trait (MEUWISSEN et al, 2001)
Agronomy these markers are identified, their effects are estimated from phenotypic data that are obtained from a population that is known as the estimation population
The analysis of deviance for the two experiments showed one or more sources of genetic variation with significant differences for all traits. This result indicates the existence of genetic variability, which allows for the selection of and genetic gains in maize root traits and, a better response to the effects of abiotic stresses
Summary
The Genome-Wide Selection (GWS) method simultaneously predicts (without the use of significance tests for individual markers) the genetic effects of a large number of molecular markers that are distributed throughout the whole genome of an organism in order to capture the effects of all of the loci and explain the entire genetic variation of a quantitative trait (MEUWISSEN et al, 2001). Agronomy these markers are identified, their effects are estimated from phenotypic data that are obtained from a population that is known as the estimation population. Once the effects are estimated, they are tested in a validation population. After this step, the markers that explain most of the genetic variance of a trait are selected. The markers that explain most of the genetic variance of a trait are selected This information is effectively incorporated into the selection stage of the breeding program (RESENDE, 2008)
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