Componentes de produção e caracteres reprodutivos, fisiológicos e de raiz usados na seleção precoce para eficiência do uso de nitrogênio em milho

The objective of this work was to examine the possibility of using yield components and reproductive, physiological, and root traits in early selection for nitrogen use efficiency (NUE) in corn. Sixty-four inbred lines were evaluated under two nitrogen fertilization levels: ideal and low. The evaluations were performed at three phenological stages: eight fully-expanded leaves, tasseling stage, and physiological maturity. It is possible to select superior lines for NUE, but the yield components did not show differential behavior under the different nitrogen levels evaluated. Root, reproductive, and physiological traits are not promising for early selection of corn lines with high NUE. Likewise, the eight-leaves and tasseling stages were not promising for this purpose, since NUE should be estimated taking grain yield into account. However, indirect selection for NUE can be performed via number of ears or using the selection index considering number and weight of ears.O objetivo deste trabalho foi examinar a possibilidade de usar componentes de produção e caracteres reprodutivos, fisiológicos e de raiz na seleção precoce para eficiência de uso de nitrogênio (EUN) em milho. Foram avaliadas 64 linhagens em dois regimes de adubação nitrogenada: ideal e baixo. As avaliações foram feitas em três estádios fenológicos: oito folhas completamente expandidas, florescimento masculino e maturação fisiológica. É possível selecionar linhagens superiores quanto à EUN, mas os componentes de produção não tiveram comportamento diferencial sob os diferentes níveis de nitrogênio avaliados. Os caracteres radiculares, reprodutivos e fisiológicos não se mostraram confiáveis para seleção precoce de linhagens de milho com elevada EUN. De forma semelhante, os estádios de oito folhas e de florescimento masculino não se mostraram promissores para esse propósito, uma vez que, para a estimação da EUN, deve-se levar em consideração a produção de grãos. Entretanto, a seleção indireta para EUN pode ser feita via número de espigas ou com o uso de índice de seleção que considere número e peso de espigas

Optimizing Genomic-Enabled Prediction in Small-Scale Maize Hybrid Breeding Programs: A Roadmap Review

The usefulness of genomic prediction (GP) for many animal and plant breeding programs has been highlighted for many studies in the last 20 years. In maize breeding programs, mostly dedicated to delivering more highly adapted and productive hybrids, this approach has been proved successful for both large- and small-scale breeding programs worldwide. Here, we present some of the strategies developed to improve the accuracy of GP in tropical maize, focusing on its use under low budget and small-scale conditions achieved for most of the hybrid breeding programs in developing countries. We highlight the most important outcomes obtained by the University of São Paulo (USP, Brazil) and how they can improve the accuracy of prediction in tropical maize hybrids. Our roadmap starts with the efforts for germplasm characterization, moving on to the practices for mating design, and the selection of the genotypes that are used to compose the training population in field phenotyping trials. Factors including population structure and the importance of non-additive effects (dominance and epistasis) controlling the desired trait are also outlined. Finally, we explain how the source of the molecular markers, environmental, and the modeling of genotype–environment interaction can affect the accuracy of GP. Results of 7 years of research in a public maize hybrid breeding program under tropical conditions are discussed, and with the great advances that have been made, we find that what is yet to come is exciting. The use of open-source software for the quality control of molecular markers, implementing GP, and envirotyping pipelines may reduce costs in an efficient computational manner. We conclude that exploring new models/tools using high-throughput phenotyping data along with large-scale envirotyping may bring more resolution and realism when predicting genotype performances. Despite the initial costs, mostly for genotyping, the GP platforms in combination with these other data sources can be a cost-effective approach for predicting the performance of maize hybrids for a large set of growing conditions

Increasing cassava root yield: Additive-dominant genetic models for selection of parents and clones

Genomic selection has been promising in situations where phenotypic assessments are expensive, laborious, and/or inefficient. This work evaluated the efficiency of genomic prediction methods combined with genetic models in clone and parent selection with the goal of increasing fresh root yield, dry root yield, as well as dry matter content in cassava roots. The bias and predictive ability of the combinations of prediction methods Genomic Best Linear Unbiased Prediction (G-BLUP), Bayes B, Bayes Cπ, and Reproducing Kernel Hilbert Spaces with additive and additive-dominant genetic models were estimated. Fresh and dry root yield exhibited predominantly dominant heritability, while dry matter content exhibited predominantly additive heritability. The combination of prediction methods and genetic models did not show significant differences in the predictive ability for dry matter content. On the other hand, the prediction methods with additive-dominant genetic models had significantly higher predictive ability than the additive genetic models for fresh and dry root yield, allowing higher genetic gains in clone selection. However, higher predictive ability for genotypic values did not result in differences in breeding value predictions between additive and additive-dominant genetic models. G-BLUP with the classical additive-dominant genetic model had the best predictive ability and bias estimates for fresh and dry root yield. For dry matter content, the highest predictive ability was obtained by G-BLUP with the additive genetic model. Dry matter content exhibited the highest heritability, predictive ability, and bias estimates compared with other traits. The prediction methods showed similar selection gains with approximately 67% of the phenotypic selection gain. By shortening the breeding cycle time by 40%, genomic selection may overcome phenotypic selection by 10%, 13%, and 18% for fresh root yield, dry root yield, and dry matter content, respectively, with a selection proportion of 15%. The most suitable genetic model for each trait allows for genomic selection optimization in cassava with high selection gains, thereby accelerating the release of new varieties

Genetic vulnerability and relationship between commercials germplasms of maize in Brazil and progenitors of nested association mapping population

O germoplasma comercial de milho é oriundo de apenas sete linhagens endogâmicas, o que pode levar a vulnerabilidade genética deste a estresses abióticos e bióticos, e limitar os ganhos com a seleção no Brasil. A vulnerabilidade genética ocorre em culturas melhoradas de baixa variabilidade genética, presentes em grandes áreas. Por exemplo, a infestação de helmintosporiose em 1970 causou preocupação entre os melhoristas Norte- Americanos com a diversidade genética de seus híbridos. No Brasil, o mercado de sementes é dominado por poucas empresas: Monsanto® (35%), DuPont Pioneer® (30%), Dow Agrosciences® (15%), Syngenta® (10%) e Helix Sementes (4%). Assim é importante o monitoramento da diversidade genética que está sendo utilizada, pois as práticas de melhoramento, registro e marketing de novos cultivares podem conduzir a vulnerabilidade genética. Diante do exposto, o objetivo foi avaliar o risco de vulnerabilidade genética e as relações entre os germoplasmas comerciais brasileiros de milho e destes com os genitores da população Nested Association Mapping (NAM). Visando atender a esses objetivos foram utilizados os genótipos dos híbridos elite das empresas de maiores market-share no Brasil e os genitores da população NAM. Os híbridos foram genotipados para 700 marcadores do tipo SNP, por meio da plataforma Illumina GoldenGate®. Já os dados genômicos dos genitores da NAM foram obtidos no banco de dados do Panzea, os quais foram genotipados para 1536 SNP’s. Os dados dos marcadores para os genótipos foram submetidos às análises de correlação entre as frequências alélicas, estruturação populacional e diversidade genotípica. Pelo tamanho efetivo populacional evidenciou-se baixo risco de vulnerabilidade genética para o germoplasma comercial brasileiro. A distância genética entre o germoplasma comercial brasileiro é menor que a encontrada na NAM, sendo menor ainda entre os híbridos de mesma empresa. O germoplasma comercial brasileiro não apresentou relações estreitas com as linhagens genitoras da população NAM, com exceção da linhagem Norte-Americana B73, esta que pertenceu a mesma população pela estruturação populacional. Isto evidencia que a linhagem B73 ou seu grupo grupo heterótico (Iowa Stiff Stalk Synthetic) tiveram grande influência na formação do germoplasma comercial brasileiro.The limited genetic variability of the Brazilian commercial maize germplasm, originated from only seven inbreed lines, could result in genetic vulnerability to abiotic and biotic stress, and also to limited selection gain. The genetic vulnerability happens to situations with low genetic variability, in large areas. The infection of Southern corn leaf blight in 70’s, concerned the North-American breeders about their hybrids genetic diversity. In Brazil, Monsanto®, DuPont Pioneer®, Dow Agrosciences® and Syngenta® have the largest seed market share. Therefore, it’s important to monitor the genetic diversity available in the country, because breeding practices, registration and marketing of new varieties could result in genetic vulnerability. Thus, the objectives of this study were to evaluate the risk of genetic vulnerability and the relationships between the Brazilian commercial maize germplasm and the Nested Association Mapping (NAM) genitors. Aiming to achieve these objectives, it was include in this work the elite hybrids of the largest market share companies in Brazil and the NAM genitors. The hybrids were genotyped by Illumina GoldenGate® platform, while the genomic data of NAM genitors were obtained in Panzea. The genotypes were subjected to linear correlation analysis, population structure and genetic diversity analysis. It was shown lower risk of genetic vulnerability with the Brazilian commercial germplasm. There is a narrow relationship within the Brazilian commercial germplasm, being closer between the hybrids of same company. The Brazilian commercial germplasm did not show close relationship with the NAM genitors, with exception of North-American line B73, which belonged to the same population of the population structure analysis. This showed that the line B73 or its heterotic group (Iowa Stiff Stalk Synthetic) had great influence at the Brazilian commercial germplasm formation.Coordenação de Aperfeiçoamento de Pessoal de Nível Superio

Agronomic potential of genebank landrace elite accessions for common bean genetic breeding

Plant breeding efficiency relies mainly on genetic diversity and selection to release new cultivars. This study aimed to identify landraces with favorable characteristics that can be used as parents of segregating populations in common bean (Phaseolus vulgaris L.) breeding programs. Firstly, ten bean genotypes were selected because they showed promising agronomic performance, and the following seven adaptive traits of four commercial bean cultivars were evaluated: i) plant height; ii) diameter of the stem; iii) height of the insertion of the first pod; iv) pod number per plant; v) grain number per pod; vi) weight of a thousand grains and vii) grain yield. The accessions BAF 07, BAF 44, and BAF 45 are promising in terms of increasing plant height, and accession BAF 01, in terms of reducing plant height. The accession BAF 07 was also the most promising in terms of a plant ideotype that combines higher plant height, maximum height of the insertion of the first pod, and increment in grain yield. Moreover, the selection can be made between and within accessions, because genetic variability is also present within landraces

Seleção precoce em plantas segregantes de feijoeiro para resistência à murcha de Curtobacterium Early selection in segregating common bean plants for resistance to bacterial wilt

Os objetivos deste trabalho foram estimar a eficiência da seleção, em populações segregantes de feijoeiro, para a resistência à murcha de Curtobacterium, e indicar o melhor período do ciclo da cultura para se proceder à seleção das plantas resistentes. Foram realizados os cruzamentos convergentes IAC-Carioca Aruã x SCS Guará, IAC-Carioca Pyatã x SCS Guará e IAC-Carioca Pyatã x Pérola, dando origem às gerações F1, F2, F2:3, F3:4, que foram inoculadas com Curtobacterium flaccumfaciens pv. flaccumfaciens isolado 2634. A resistência foi avaliada segundo escala de notas referentes aos sintomas comuns da doença aos 20, 40 e 60 dias após a inoculação. Os resultados indicaram que as gerações segregantes de Aruã x Guará, Pyatã x Guará e Pyatã x Pérola possuem comportamento semelhante em relação à resistência aos sintomas da murcha de Curtobacterium. A seleção foi efetiva para as gerações oriundas de Aruã x Guará e Pyatã x Pérola e o período entre 40 e 60 dias após a inoculação é o mais adequado para seleção de plantas segregantes para resistência.The objective of this study were both the estimation of the efficiency of selection in segregating populations of common bean for the resistance to Curtobacterium and also the indication of the best time of the cycle to make the selection of resistant plants. To this end, we used converging crosses between IAC-Carioca Aruã x SCS Guará, IAC-Carioca Pyatã x IAC-Carioca and SCS Guará x Pérola, originating filial generations (F1, F2, F2:3 and F3:4) which were subsequently inoculated with Curtobacterium flaccumfaciens pv. Flaccumfaciens, isolate 2634, and evaluated according to a scale related to the common symptoms of the disease at 20, 40 and 60 days after inoculation. The results showed that the segregating generations of Aruã x Guará, Pyatã x Guará and Pyatã x Pérola had similar behavior in relation to resistance to the Curtobacterium symptoms. The selection is effective for the coming generations of Aruã x Guará and Pyatã x Pérola and the favorable time for distinguishing and selecting reliably segregating plants occurs between 40 and 60 days after inoculation

Cassava yield traits predicted by genomic selection methods.

Genomic selection (GS) has been used to optimize genetic gains when phenotypic selection is considered costly and difficult to measure. The objective of this work was to evaluate the efficiency and consistency of GS prediction for cassava yield traits (Manihot esculenta Crantz) using different methods, taking into account the effect of population structure. BLUPs and deregressed BLUPs were obtained for 888 cassava accessions and evaluated for fresh root yield, dry root yield and dry matter content in roots in 21 trials conducted from 2011 to 2016. The deregressed BLUPs obtained for the accessions from a 48K single nucleotide polymorphism dataset were used for genomic predictions based on the BayesB, BLASSO, RR-BLUP, G-BLUP and RKHS methods. The accessions' BLUPs were used in the validation step using four cross-validation strategies, taking into account population structure and different GS methods. Similar estimates of predictive ability and bias were identified for the different genomic selection methods in the first cross-validation strategy. Lower predictive ability was observed for fresh root yield (0.4569 -RR-BLUP to 0.4756-RKHS) and dry root yield (0.4689 -G-BLUP to 0.4818-RKHS) in comparison with dry matter content (0.5655 -BLASSO to 0.5670 -RKHS). However, the RKHS method exhibited higher efficiency and consistency in most of the validation scenarios in terms of prediction ability for fresh root yield and dry root yield. The correlations of the genomic estimated breeding values between the genomic selection methods were quite high (0.99-1.00), resulting in high coincidence of clone selection regardless of the genomic selection method. The deviance analyses within and between the validation clusters formed by the discriminant analysis of principal components were significant for all traits. Therefore, this study indicated that i) the prediction of dry matter content was more accurate compared to that of yield traits, possibly as a result of the smaller influence of non-additive genetic effects; ii) the RKHS method resulted in high and stable prediction ability in most of the validation scenarios; and iii) some kinship between the validation and training populations is desirable in order for genomic selection to succeed due to the significant effect of population structure on genomic selection predictions

20 Maize Hybrids Genotyped

These data has 20 maize hybrids genotyped for 768 Small Nuclear Polymorphisms markers.<div><div>Hybrids represent the Brazilian commercial germoplasm.</div><div>Hybrids in line and markers in columns.</div><div>None Quality control applied to the markers (MAF and Call Rate).<br>The Genotypes are as nitrogenous bases (ex. G/G) and missing data as -/-.</div></div

Genetic Vulnerability and the Relationship of Commercial Germplasms of Maize in Brazil with the Nested Association Mapping Parents.

A few breeding companies dominate the maize (Zea mays L.) hybrid market in Brazil: Monsanto® (35%), DuPont Pioneer® (30%), Dow Agrosciences® (15%), Syngenta® (10%) and Helix Sementes (4%). Therefore, it is important to monitor the genetic diversity in commercial germplasms as breeding practices, registration and marketing of new cultivars can lead to a significant reduction of the genetic diversity. Reduced genetic variation may lead to crop vulnerabilities, food insecurity and limited genetic gains following selection. The aim of this study was to evaluate the genetic vulnerability risk by examining the relationship between the commercial Brazilian maize germplasms and the Nested Association Mapping (NAM) Parents. For this purpose, we used the commercial hybrids with the largest market share in Brazil and the NAM parents. The hybrids were genotyped for 768 single nucleotide polymorphisms (SNPs), using the Illumina Goldengate® platform. The NAM parent genomic data, comprising 1,536 SNPs for each line, were obtained from the Panzea data bank. The population structure, genetic diversity and the correlation between allele frequencies were analyzed. Based on the estimated effective population size and genetic variability, it was found that there is a low risk of genetic vulnerability in the commercial Brazilian maize germplasms. However, the genetic diversity is lower than those found in the NAM parents. Furthermore, the Brazilian germplasms presented no close relations with most NAM parents, except B73. This indicates that B73, or its heterotic group (Iowa Stiff Stalk Synthetic), contributed to the development of the commercial Brazilian germplasms