Genome-Wide Selection for tropical maize root traits under conditions of nitrogen and phosphorus stress

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. Seleçâo Genômica Ampia para caracteres de raíz em milho tropical em condiçôes de estresse de nitrogênio e fósforo RESUMO. O objetivo deste estudo foi verificar a acurácia do método da Seleçâo Genômica Ampia (GWS) no melhoramento de milho tropical para caracteres de raiz em condiçôes de estresse de nitrogênio e fósforo. Quarenta e um híbridos simples foram avahados em dois experimentos. O primeiro experimento considerou baixa disponibilidade de nitrogênio e o segundo baixa disponibilidade de fósforo. Para isto, foi usado o delineamento de blocos casualizados com duas repetiçôes. Os comprimentos de raiz lateral e axial foram medidos utilizando o software WinRhizo. As análises de deviance foram realizadas pelo método da Máxima Verossimilhança Restrita / Melhor Preditor Linear Náo-viesado (REML/BLUP). Oitenta marcadores microssatélites foram utilizados para determinar o genotipo da populacáo de estimaçâo. O método de regressao aleatoria foi utilizado ñas análises de GWS (RR-BLUP/GWS). Os ganhos por unidade de tempo da GWS e dos métodos de selegáo fenotípica foram comparados, sendo que como método padráo de seleçâo fenotípica foi considerado a seleçâo recorrente. A acurácia da GWS foi maior do que a acurácia da seleçâo fenotípica para todas as características avahadas. Assim, o método GWS pode aumentar significativamente os ganhos genéticos para características de raízes que sâo obtidos em programas de melhoramento de milho tropical condiçôes de estresse nutricional. Palavras-chave: seleçâo assistida por marcadores, seleçâo recorrente, estresses abióticos.

Genetic Diversity and Genomic Selection in Eucalyptus Benthamii

“…Torres-Dini et al (2016), despite using a high number of markers (15,106 SNPs), obtained low accuracy results with a small population (78 individuals) of eucalyptus hybrids. And regarding the number of markers, papers show reliable results with trials using around eighty SRR markers (Fritsche-Neto et al 2012).…”

Prediction of heterosis in the recent rapeseed (Brassica napus) polyploid by pairing parental nucleotide sequences

“…As a promising new breeding method, GS has been applied to the prediction of heterosis of various crops such as rice [11,12,16], corn [17], barley [18], wheat [19], ryegrass [20], and pumpkin [21]. The traits which were predicted in the different studies were not only limited to yield and yield components [16][17][18][19][20][21], but also those traits such as biotic-and abiotic-stress tolerances [22,23], nutrient utilization efficiency [24,25]. Compared with the previous GS studies on other crops, our research had the following characteristics.…”

Contrasting Phosphorus Environments as Indicators for Popcorn Breeding Lines

“…For this, breeding programs of the main crop species need to assess traits related to plant adaptation at environments with reduced nutrient demand (Van de Wiel et al, 2016). In this sense, some species have been studied, such as coffee (Neto et al, 2016), wheat (Gunes et al, 2006), rice (Wissuwa and Ae, 2001), bean (Ochoa et al, 2006), maize (Fritsche-Neto et al, 2012;DoVale and Fritsche-Neto, 2013), and popcorn (Mundim et al, 2013;Mundim et al, 2014).…”