Genomic prediction in multi-environment trials in maize using statistical and machine learning methods.

In the context of multi-environment trials (MET), genomic prediction is proposed as a tool that allows the prediction of the phenotype of single cross hybrids that were not tested in field trials. This approach saves time and costs compared to traditional breeding methods. Thus, this study aimed to evaluate the genomic prediction of single cross maize hybrids not tested in MET, grain yield and female flowering time. We also aimed to propose an application of machine learning methodologies in MET in the prediction of hybrids and compare their performance with Genomic best linear unbiased prediction (GBLUP) with non-additive effects. Our results highlight that both methodologies are efficient and can be used in maize breeding programs to accurately predict the performance of hybrids in specific environments. The best methodology is case-dependent, specifically, to explore the potential of GBLUP, it is important to perform accurate modeling of the variance components to optimize the prediction of new hybrids. On the other hand, machine learning methodologies can capture non-additive effects without making any assumptions at the outset of the model. Overall, predicting the performance of new hybrids that were not evaluated in any field trials was more challenging than predicting hybrids in sparse test designs.

Genome-Wide Association Study for Root Morphology and Phosphorus Acquisition Efficiency in Diverse Maize Panels.

Maximizing soil exploration through modifications of the root system is a strategy for plants to overcome phosphorus (P) deficiency. Genome-wide association with 561 tropical maize inbred lines from Embrapa and DTMA panels was undertaken for root morphology and P acquisition traits under low- and high-P concentrations, with 353,540 SNPs. P supply modified root morphology traits, biomass and P content in the global maize panel, but root length and root surface area changed differentially in Embrapa and DTMA panels. This suggests that different root plasticity mechanisms exist for maize adaptation to low-P conditions. A total of 87 SNPs were associated to phenotypic traits in both P conditions at -log10(p-value) ≥ 5, whereas only seven SNPs reached the Bonferroni significance. Among these SNPs, S9_137746077, which is located upstream of the gene GRMZM2G378852 that encodes a MAPKKK protein kinase, was significantly associated with total seedling dry weight, with the same allele increasing root length and root surface area under P deficiency. The C allele of S8_88600375, mapped within GRMZM2G044531 that encodes an AGC kinase, significantly enhanced root length under low P, positively affecting root surface area and seedling weight. The broad genetic diversity evaluated in this panel suggests that candidate genes and favorable alleles could be exploited to improve P efficiency in maize breeding programs of Africa and Latin America.

Genome-guided insights of tropical Bacillus strains efficient in maize growth promotion.

Plant growth promoting bacteria (PGPB) are an efficient and sustainable alternative to mitigate biotic and abiotic stresses in maize. This work aimed to sequence the genome of two Bacillus strains (B116 and B119) and to evaluate their plant growth-promoting (PGP) potential in vitro and their capacity to trigger specific responses in different maize genotypes. Analysis of the genomic sequences revealed the presence of genes related to PGP activities. Both strains were able to produce biofilm and exopolysaccharides, and solubilize phosphate. The strain B119 produced higher amounts of IAA-like molecules and phytase, whereas B116 was capable to produce more acid phosphatase. Maize seedlings inoculated with either strains were submitted to polyethylene glycol-induced osmotic stress and showed an increase of thicker roots, which resulted in a higher root dry weight. The inoculation also increased the total dry weight and modified the root morphology of 16 out of 21 maize genotypes, indicating that the bacteria triggered specific responses depending on plant genotype background. Maize root remodeling was related to growth promotion mechanisms found in genomic prediction and confirmed by in vitro analysis. Overall, the genomic and phenotypic characterization brought new insights to the mechanisms of PGP in tropical Bacillus.

Genomic prediction applied to multiple traits and environments in second season maize hybrids.

Genomic selection has become a reality in plant breeding programs with the reduction in genotyping costs. Especially in maize breeding programs, it emerges as a promising tool for predicting hybrid performance. The dynamics of a commercial breeding program involve the evaluation of several traits simultaneously in a large set of target environments. Therefore, multi-trait multi-environment (MTME) genomic prediction models can leverage these datasets by exploring the correlation between traits and Genotype-by-Environment (G×E) interaction. Herein, we assess predictive abilities of univariate and multivariate genomic prediction models in a maize breeding program. To this end, we used data from 415 maize hybrids evaluated in 4 years of second season field trials for the traits grain yield, number of ears, and grain moisture. Genotypes of these hybrids were inferred in silico based on their parental inbred lines using single nucleotide polymorphisms (SNPs) markers obtained via genotyping-by-sequencing (GBS). Because genotypic information was available for only 257 hybrids, we used the genomic and pedigree relationship matrices to obtain the H matrix for all 415 hybrids. Our results demonstrated that in the single-environment context the use of multi-trait models was always superior in comparison to their univariate counterparts. Besides that, although MTME models were not particularly successful in predicting hybrid performance in untested years, they improved the ability to predict the performance of hybrids that had not been evaluated in any environment. However, the computational requirements of this kind of model could represent a limitation to its practical implementation and further investigation is necessary.

Relative importance of gene effects for nitrogen-use efficiency in popcorn.

The objective of this study was to evaluate the effects of additive and non-additive genes on the efficiency of nitrogen (N) use and N responsiveness in inbred popcorn lines. The parents, hybrids and reciprocal crosses were evaluated in a 10x10 triple lattice design at two sites and two levels of N availability. To establish different N levels in the two experiments, fertilization was carried out at sowing, according to soil analysis reports. However, for the experiments with ideal nitrogen availability, N was sidedressed according to the crop requirement, whereas for the N-poor experiments sidedressing consisted of 30% of that applied in the N-rich environment. Two indices were evaluated, the Harmonic Mean of the Relative Performance (HMRP) and Agronomic Efficiency under Low Nitrogen Availability (AELN), both based on grain yield at both N levels. Both additive and non-additive gene effects were important for selection for N-use efficiency. Moreover, there was allelic complementarity between the lines and a reciprocal effect for N-use efficiency, indicating the importance of the choice of the parents used as male or female. The best hybrids were obtained from inbred popcorn lines with contrasting N-use efficiency and N responsiveness.

Improving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials.

Breeding for drought tolerance is a challenging task that requires costly, extensive, and precise phenotyping. Genomic selection (GS) can be used to maximize selection efficiency and the genetic gains in maize (Zea mays L.) breeding programs for drought tolerance. Here, we evaluated the accuracy of genomic selection (GS) using additive (A) and additive + dominance (AD) models to predict the performance of untested maize single-cross hybrids for drought tolerance in multi-environment trials. Phenotypic data of five drought tolerance traits were measured in 308 hybrids along eight trials under water-stressed (WS) and well-watered (WW) conditions over two years and two locations in Brazil. Hybrids' genotypes were inferred based on their parents' genotypes (inbred lines) using single-nucleotide polymorphism markers obtained via genotyping-by-sequencing. GS analyses were performed using genomic best linear unbiased prediction by fitting a factor analytic (FA) multiplicative mixed model. Two cross-validation (CV) schemes were tested: CV1 and CV2. The FA framework allowed for investigating the stability of additive and dominance effects across environments, as well as the additive-by-environment and the dominance-by-environment interactions, with interesting applications for parental and hybrid selection. Results showed differences in the predictive accuracy between A and AD models, using both CV1 and CV2, for the five traits in both water conditions. For grain yield (GY) under WS and using CV1, the AD model doubled the predictive accuracy in comparison to the A model. Through CV2, GS models benefit from borrowing information of correlated trials, resulting in an increase of 40% and 9% in the predictive accuracy of GY under WS for A and AD models, respectively. These results highlight the importance of multi-environment trial analyses using GS models that incorporate additive and dominance effects for genomic predictions of GY under drought in maize single-cross hybrids.

Identification of sources of resistance to anthracnose stalk rot in maize / Identificação de fontes de resistência à antracnose do colmo do milho

ABSTRACT: Adoption of resistant cultivars is the primary measure used to control anthracnose stalk rot. The goal of this study was to identify maize-resistant genotypes to anthracnose stalk rot, which are similar to the hybrid 2B710. Experiments were performed at Embrapa Maize and Sorghum experimental fields in Brazil. The first experimental trial evaluated 234 maize lines as well as two commercials hybrids, BRS1010 (susceptible) and 2B710 (resistant). Artificial inoculations were performed with a strain at the blister (R2) phase, and evaluation of disease severity was performed after 30 days. The second experimental trial evaluated 48 maize lines and hybrids, inoculated with two Colletotrichum graminicola strains. In the first trial, eight resistance groups were formed, and the last lines were more resistant, as was the hybrid 2B710, with values between 11.50% and 23.0% of severity. In the second trial, there was an interaction between the two factors, lines and isolates, and the lines often showed the same reaction features as those obtained in the first trial. However, the disease severity was higher for most lines, even when using other isolates. These lines with effective levels of resistance could be used in future studies of inheritance, in programs to develop hybrids, and to identify molecular markers associated with resistance to anthracnose stalk rot in maize.

RESUMO: O uso de cultivares resistentes é a principal medida para o manejo da antracnose do colmo em milho. Neste trabalho, objetivou-se identificar linhagens com níveis de resistência à antracnose do colmo, similar ao híbrido 2B710, considerado resistente. Dois experimentos foram conduzidos na Embrapa Milho e Sorgo. No primeiro experimento, foram avaliados 234 linhagens e os híbridos BRS1010 (suscetível) e 2B710 (resistente). Foi realizada inoculação artificial com um isolado de C. graminicola , na fase de pré-pendoamento e, após 30 dias, foi realizada a avaliação da severidade da antracnose no colmo. O segundo experimento foi conduzido com 48 linhagens e os híbridos inoculados com dois isolados de C. graminicola . No primeiro experimento, os genótipos formaram oito grupos com base na severidade da doença e as linhagens do último grupo foram consideradas as mais resistentes, incluindo o híbrido 2B710, em que os genótipos apresentaram valores de severidade entre 11,50 a 23%. No segundo experimento, houve interação entre os fatores linhagens e isolados e, de modo geral, as linhagens apresentaram a mesma tendência de reação obtida no primeiro experimento, no entanto, a severidade da doença foi maior para a maioria das linhagens, mesmo quando utilizado o outro isolado. Com isso, foi possível realizar a seleção de linhagens com bons níveis de resistência, as quais podem ser utilizadas em programas de melhoramento, em estudos de herança, desenvolvimento de híbridos e identificação de marcadores moleculares, associados com resistência à antracnose do colmo.

Performance of testers with different genetic structure for evaluation of maize inbred lines / Desempenho de testadores com diferentes estruturas genéticas para avaliação de linhagens endogâmicas de milho

The objective of this study was to evaluate four maize testers for identification of superior inbreed lines in testcross. The four testers evaluated are cultivars with narrow or wide genetic base (single-cross hybrids and open pollinated varieties) and two kernel types (flint or dent). SynD and SynF testers are open pollinated varieties with dent and flint kernels, respectively, and FSH and DSH testers are single-cross hybrids with flint and dent kernels, respectively. SynD tester showed the biggest genetic variance among the maize inbreed lines in crosses. The effects of general combining ability (GCA) for lines and specific combining ability (SCA) for lines x testers were significant, whereas GCA effects for testers were not significant. SynD and SynF testers identified the largest number of lines with higher GCA. The DSH and FSH testers showed suitable to identify lines with high SCA. It was concluded that SynD and SynF testers are adequate to identify inbreed lines with high GCA effects, and it's possible to identify new lines with high heterotic potential in each one of the four testers.

O objetivo deste estudo foi avaliar quatro testadores de milho quanto à capacidade de identificar linhagens superiores em testcross. Os quatro testadores avaliados são cultivares com base genética ampla (variedades de polinização aberta) e estreita (híbridos simples) e dois tipos de grãos (duro e dentado). Os testadores SynD e SynF são populações de milho de polinização aberta com grãos dentados e duros, respectivamente, e FSH e DSH são híbridos simples com grãos duros e dentados, respectivamente. O testador SynD possibilitou a maior expressão de variância genética entre os cruzamentos com as linhagens. A capacidade geral de combinação (CGC) das linhagens e a capacidade específica de combinação (CEC) entre linhagens e testadores foram significativas, enquanto que os efeitos de CGC dos testadores foram não significativos. Concluiu-se que os testadores SynD e SynF mostram-se adequados para identificar linhagens com maiores efeitos de GCA e é possível identificar novas linhagens com alto potencial heterótico com cada um dos quatro testadores utilizados.