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

Sant’Ana, Gustavo César; Espolador, Fernando Garcia; Granato, Ítalo Stefanine Correia; Mendonça, Leandro Freitas; Fritsche‐Neto, Roberto; Borém, Aluízio

doi:10.1371/journal.pone.0239900

Cited by 4 publications

(2 citation statements)

References 43 publications

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“…The very first step on our scientific road was to carry out germplasm characterization on the newly acquired inbred lines (Sant'Ana et al, 2020 ). Genomic diversity and population structure of germplasm (e.g., heterotic groups) are widely known to accelerate genetic gains in breeding programs.…”

Section: Germplasm Characterizationmentioning

confidence: 99%

“…The grouping, based on the Nitrogen Acquisition Efficiency (NAE) values, classified the lines into two phenotypic groups, the first of which was composed of genotypes with high NAE (called H_NAE group) and the second of genotypes with low NAE (called L_NAE group). The groups H_NAE and L_NAE presented mean NAE values of 3,304 and 1,644, respectively (Sant'Ana et al, 2020 ). The population structure analysis revealed a weak relationship between genetic and phenotypic diversities.…”

Section: Germplasm Characterizationmentioning

confidence: 99%

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

et al. 2021

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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.

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Section: Germplasm Characterizationmentioning

confidence: 99%

Section: Germplasm Characterizationmentioning

confidence: 99%

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

et al. 2021

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Genetic diversity among maize (Zea mays L.) inbred lines adapted to Japanese climates

Mitsuhashi

2024

PLoS ONE

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Understanding the genetic diversity of inbred lines is vital for development of superior F1 varieties. The present study aimed to analyze Japanese maize parental inbred lines and determine their genetic diversity for future breeding. Genetic analyses were conducted using multiple methods. Principal component analysis (PCA), phylogenetic trees, and Bayesian clustering reflected borders between heterotic groups according to the derivation of each inbred line. A self-pollinated line derived from a classic F1 variety and another line from an open-pollinated population from the same derivation were classified as separate components by PCA and Bayesian clustering. The result suggests that open pollination could be essential in modern breeding. Of those classified as dent or flint based on their derivation, some had a combination of all components or clusters. Therefore, the classification of inbred lines should be based on their derivation and DNA markers. The findings will be valuable for breeding and genetic studies in Japan. Additionally, these techniques may be used to obtain a more significant number of SNPs and related phenotypic data.

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Breeding trials in water-stress conditions: identification of sensitive traits in early stages and characterization of a tropical maize public panel

Machado

Pontes

Silveira

et al. 2023

Preprint

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One of the major goals of modern agriculture is to achieve increased crop yield using less water. Despite the significant advances in genomics, a phenotypic characterization efficient is essential for the success of a modern breeding program, which wants to speed up the genetic gains by deploying selection in the early stages. Thus, this study aimed to identify which traits are most important to discriminate the maize genotypes to support early selection under contrasting water availability conditions. For this, we used a public diversity panel consisting of 360 tropical maize inbred lines, involving two conditions, well-watered (WW) and water-stress (WS), in eight trials. Evaluations were carried out in the phenological stage V6 for shoot and root traits. There was a significant variation in the panel performance, mainly for root traits under WS conditions, composing six clusters. However, the traits showed a similar pattern of clustering evidenced by principal components in WW and WS conditions. Moreover, a strong relationship was found among the roots' length, surface area, and volume. Based on this, we suggest discarding the most error-prone ones. Our results showed via Redundancy Analysis (RDA) that plant height, stalk diameter, and lateral roots length are traits more sensitive to WS and, therefore, may be considered in early selection in breeding programs aiming for water use efficiency.

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

Cited by 4 publications

References 43 publications

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

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

Genetic diversity among maize (Zea mays L.) inbred lines adapted to Japanese climates

Breeding trials in water-stress conditions: identification of sensitive traits in early stages and characterization of a tropical maize public panel

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