Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical lines

Mendonça, Leandro de Freitas; Granato, Ítalo Stefanine Correia; Alves, Filipe Couto; Morais, Pedro Patric Pinho; Vidotti, Miriam Suzane; Fritsche‐Neto, Roberto

doi:10.1590/1678-992x-2016-0313

Cited by 21 publications

(22 citation statements)

References 9 publications

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“…The genetic material was composed of 906 maize single-crosses [22] obtained in a partial diallel using 49 of the 64 inbred lines studied in Morosini et al [18] (S1 Table). The 49 inbred lines were selected based on their nitrogen use efficiency [23] and identified as belonging from two heterotic groups, 35 flint and 15 dent [24]. Thorough study of the population of hybrids was previously reported [24,25].…”

Section: Phenotype Assessment and Analysismentioning

confidence: 99%

On the usefulness of parental lines GWAS for predicting low heritability traits in tropical maize hybrids

et al. 2020

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Genome-wide association studies (GWAS) is one of the most popular methods of studying the genetic control of traits. This methodology has been intensely performed on inbred genotypes to identify causal variants. Nonetheless, the lack of covariance between the phenotype of inbred lines and their offspring in cross-pollinated species (such as maize) raises questions on the applicability of these findings in a hybrid breeding context. To address this topic, we incorporated previously reported parental lines GWAS information into the prediction of a low heritability trait in hybrids. This was done by marker-assisted selection based on significant markers identified in the lines and by genomic prediction having these markers as fixed effects. Additive-dominance GWAS of hybrids, a non-conventional procedure, was also performed for comparison purposes. Our results suggest that incorporating information from parental inbred lines GWAS led to decreases in the predictive ability of hybrids. Correspondingly, inbred lines and hybrids-based GWAS yielded different results. These findings do not invalidate GWAS on inbred lines for selection purposes, but mean that it may not be directly useful for hybrid breeding. OPEN ACCESSCitation: Galli G, Alves FC, Morosini JS, Fritsche-Neto R (2020) On the usefulness of parental lines GWAS for predicting low heritability traits in tropical maize hybrids. PLoS ONE 15(2): e0228724. https://doi.org/10.1371/journal.

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Section: Phenotype Assessment and Analysismentioning

confidence: 99%

On the usefulness of parental lines GWAS for predicting low heritability traits in tropical maize hybrids

et al. 2020

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“…In this study, we used the LNAE index (Low-N Agronomic Efficiency) to measure the tolerance of 64 tropical maize lines to low-N availability in the soil. In the LNAE index calculation, both the absolute GY at low-N availability and the ratio between low-N and optimum-N are considered [3,8]. Therefore, LNAE is an important index in maize breeding programs aimed at developing high-yielding cultivars even under low-N conditions.…”

Section: Discussionmentioning

confidence: 99%

“…N fertilization is expensive and also harmful to the environment because of the negative effect on water quality. In this context, the development of nutritionally efficient maize cultivars, which yield more with low fertilization, is a way to reduce fertilizer usage [2,3].…”

Section: Introductionmentioning

confidence: 99%

“…Maize tolerance to low availability of N in the soil is a complex trait influenced by genetic and environmental factors, including soil nitrogen availability, nitrogen uptake, assimilation, transportation, and remobilization [ 4 ]. Breeding programs use some indices related to low-N stress tolerance based on several quantitative traits [ 3 , 5 – 8 ]. For example, Low-N Agronomic Efficiency (LNAE) is an index that accounts for the absolute grain yield at low-N and the ratio between low-N and optimal-N conditions [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

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Population structure analysis and identification of genomic regions under selection associated with low-nitrogen tolerance in tropical maize lines

et al. 2020

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Increasing low nitrogen (N) tolerance in maize is an important goal for food security and agricultural sustainability. In order to analyze the population structure of tropical maize lines and identify genomic regions associated with low-N tolerance, a set of 64 inbred lines were evaluated under low-N and optimal-N conditions. The low-N Agronomic Efficiency index (LNAE) of each line was calculated. The maize lines were genotyped using 417,112 SNPs markers. The grouping based on the LNAE values classified the lines into two phenotypic groups, the first comprised by genotypes with high LNAE (named H_LNAE group), while the second one comprised genotypes with low LNAE (named L_LNAE group). The H_LNAE and L_LNAE groups had LNAE mean values of 3,304 and 1,644, respectively. The population structure analysis revealed a weak relationship between genetic and phenotypic diversity. Pairs of lines were identified, having at the same time high LNAE and high genetic distance from each other. A set of 29 SNPs markers exhibited a significant difference in allelic frequencies (Fst > 0.2) between H_LNAE and L_LNAE groups. The Pearson's correlation between LNAE and the favorable alleles in this set of SNPs was 0.69. These SNPs could be useful for marker-assisted selection for low-N tolerance in maize breeding programs. The results of this study could help maize breeders identify accessions to be used in the development of low-N tolerant cultivars.

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“…Data was available for a total of 906 maize single-crosses derived from forty-nine inbred lines, contrast in the use of nitrogen [47], crossed in an unbalanced diallel mating design . Field trials were organized in an unreplicated augmented block design consisting of 47 (year 1) or 50 (year 2) blocks with 16 hybrids and two commercial checks evaluated in each block.…”

Section: Application To a Dataset Of Tropical Maize Hybrids Derived Fmentioning

confidence: 99%

Unraveling the impact of genotype by environment interaction complexity and a new proposal to understand the contribution of additive and non-additive effects on genomic prediction in tropical maize single-crosses

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Unraveling the impact of genotype by environment interaction complexity and a new proposal to understand the contribution of additive and non-additive effects on genomic prediction in tropical maize single-crosses The use of molecular markers to predict non-tested materials in field trials has been extensively employed in breeding programs. The genomic prediction of single crosses is a promising approach in maize breeding programs as it reduces selection cycle and permits the selection of promising crosses. Accounting for nonadditive effects on genomic prediction can increase prediction accuracy of models depending on the traits genetic architecture. Genomic prediction was first developed for single environments and recently extended to exploit the genotype by environment interactions for prediction of non-evaluated individuals. The employment of multi-environment genomic models is advantageous in several aspects and has enabled significant higher prediction accuracies than single environment models. However, only a small number of studies regarding the inclusion of non-additive effects in these models are reported. Moreover, the genotype by environment interaction complexity can largely impact the prediction accuracy of these models. Thus, the objectives were to i) evaluate the contribution of additive and non-additive (dominance and epistasis) effects for the prediction of agronomical traits with different genetic architecture in tropical maize single-crosses grown under two nitrogen regimes (ideal and stressing), and ii) verify the impact of the genotype by environment interaction complexity, and the inclusion of dominance deviations, on the prediction accuracy of hybrids grain yield using a multienvironment prediction model. For this, we used phenotypic and genotypic data of 906 single-crosses evaluated during two years, at two locations, under two nitrogen regimes, totaling eight contrasting environments (combination of year x locations x nitrogen regimes). The traits considered in the study were grain yield, ear, and plant height. The results regarding the inclusion of additive and non-additive effects (dominance and epistasis) in genomic prediction models suggest that non-additive effects play an important role in stressing conditions, having a high, medium and low contribution for phenotypic expression of grain yield, plant height, and ear height, respectively. The inclusion of dominance deviations in multi-environment prediction model increases the prediction accuracy. Furthermore, a linear relationship between genotype by environment complexity and prediction accuracy was found.

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Accuracy and simultaneous selection gains for N-stress tolerance and N-use efficiency in maize tropical lines

Cited by 21 publications

References 9 publications

On the usefulness of parental lines GWAS for predicting low heritability traits in tropical maize hybrids

On the usefulness of parental lines GWAS for predicting low heritability traits in tropical maize hybrids

Population structure analysis and identification of genomic regions under selection associated with low-nitrogen tolerance in tropical maize lines

Unraveling the impact of genotype by environment interaction complexity and a new proposal to understand the contribution of additive and non-additive effects on genomic prediction in tropical maize single-crosses

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