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G3 (Bethesda) ; 2020 Jun 01.
Artigo em Inglês | MEDLINE | ID: mdl-32482728


Zinc (Zn) deficiency is a major risk factor for human health, affecting about 30% of the world's population. To study the potential of genomic selection (GS) for maize with increased Zn concentration, an association panel and two doubled haploid (DH) populations were evaluated in three environments. Three genomic prediction models, M (M1: Environment + Line, M2: Environment + Line + Genomic, and M3: Environment + Line + Genomic + Genomic × Environment) incorporating main effects (lines and genomic) and the interaction between genomic and environment (G × E) were assessed to estimate the prediction ability (rMP ) for each model. Two distinct cross-validation (CV) schemes simulating two genomic prediction breeding scenarios were used. CV1 predicts the performance of newly developed lines, whereas CV2 predicts the performance of lines tested in sparse multi-location trials. Predictions for Zn in CV1 ranged from -0.01 to 0.56 for DH1, 0.04 to 0.50 for DH2 and -0.001 to 0.47 for the association panel. For CV2, rMP values ranged from 0.67 to 0.71 for DH1, 0.40 to 0.56 for DH2 and 0.64 to 0.72 for the association panel. The genomic prediction model which included G × E had the highest average rMP for both CV1 (0.39 and 0.44) and CV2 (0.71 and 0.51) for the association panel and DH2 population, respectively. These results suggest that GS has potential to accelerate breeding for enhanced kernel Zn concentration by facilitating selection of superior genotypes.

PLoS One ; 14(3): e0212200, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-30893307


High throughput phenotyping technologies are lagging behind modern marker technology impairing the use of secondary traits to increase genetic gains in plant breeding. We aimed to assess whether the combined use of hyperspectral data with modern marker technology could be used to improve across location pre-harvest yield predictions using different statistical models. A maize bi-parental doubled haploid (DH) population derived from F1, which consisted of 97 lines was evaluated in testcross combination under heat stress as well as combined heat and drought stress during the 2014 and 2016 summer season in Ciudad Obregon, Sonora, Mexico (27°20" N, 109°54" W, 38 m asl). Full hyperspectral data, indicative of crop physiological processes at the canopy level, was repeatedly measured throughout the grain filling period and related to grain yield. Partial least squares regression (PLSR), random forest (RF), ridge regression (RR) and Bayesian ridge regression (BayesB) were used to assess prediction accuracies on grain yield within (two-fold cross-validation) and across environments (leave-one-environment-out-cross-validation) using molecular markers (M), hyperspectral data (H) and the combination of both (HM). Highest prediction accuracy for grain yield averaged across within and across location predictions (rGP) were obtained for BayesB followed by RR, RF and PLSR. The combined use of hyperspectral and molecular marker data as input factor on average had higher predictions for grain yield than hyperspectral data or molecular marker data alone. The highest prediction accuracy for grain yield across environments was measured for BayesB when molecular marker data and hyperspectral data were used as input factors, while the highest within environment prediction was obtained when BayesB was used in combination with hyperspectral data. It is discussed how the combined use of hyperspectral data with molecular marker technology could be used to introduce physiological genomic estimated breeding values (PGEBV) as a pre-harvest decision support tool to select genetically superior lines.

Agricultura/métodos , Resposta ao Choque Térmico/genética , Zea mays/genética , Teorema de Bayes , Biomarcadores , Secas , Grão Comestível/genética , Previsões/métodos , Genoma de Planta/genética , Genômica , Genótipo , Temperatura Alta , México , Modelos Genéticos , Fenótipo , Melhoramento Vegetal/métodos , Tolerância ao Sal/genética , Seleção Genética/genética
Theor Appl Genet ; 129(4): 753-765, 2016 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-26849239


KEY MESSAGE: Molecular characterization information on genetic diversity, population structure and genetic relationships provided by this research will help maize breeders to better understand how to utilize the current CML collection. CIMMYT maize inbred lines (CMLs) have been widely used all over the world and have contributed greatly to both tropical and temperate maize improvement. Genetic diversity and population structure of the current CML collection and of six temperate inbred lines were assessed and relationships among all lines were determined with genotyping-by-sequencing SNPs. Results indicated that: (1) wider genetic distance and low kinship coefficients among most pairs of lines reflected the uniqueness of most lines in the current CML collection; (2) the population structure and genetic divergence between the Temperate subgroup and Tropical subgroups were clear; three major environmental adaptation groups (Lowland Tropical, Subtropical/Mid-altitude and Highland Tropical subgroups) were clearly present in the current CML collection; (3) the genetic diversity of the three Tropical subgroups was similar and greater than that of the Temperate subgroup; the average genetic distance between the Temperate and Tropical subgroups was greater than among Tropical subgroups; and (4) heterotic patterns in each environmental adaptation group estimated using GBS SNPs were only partially consistent with patterns estimated based on combining ability tests and pedigree information. Combining current heterotic information based on combining ability tests and the genetic relationships inferred from molecular marker analyses may be the best strategy to define heterotic groups for future tropical maize improvement. Information resulting from this research will help breeders to better understand how to utilize all the CMLs to select parental lines, replace testers, assign heterotic groups and create a core set of breeding germplasm.

Genótipo , Vigor Híbrido , Polimorfismo de Nucleotídeo Único , Zea mays/genética , DNA de Plantas/genética , Frequência do Gene , Endogamia , Melhoramento Vegetal , Análise de Sequência de DNA
Proc Natl Acad Sci U S A ; 104(28): 11844-9, 2007 Jul 10.
Artigo em Inglês | MEDLINE | ID: mdl-17615239


Analysis of the sequences of 74 randomly selected BACs demonstrated that the maize nuclear genome contains approximately 37,000 candidate genes with homologues in other plant species. An additional approximately 5,500 predicted genes are severely truncated and probably pseudogenes. The distribution of genes is uneven, with approximately 30% of BACs containing no genes. BAC gene density varies from 0 to 7.9 per 100 kb, whereas most gene islands contain only one gene. The average number of genes per gene island is 1.7. Only 72% of these genes show collinearity with the rice genome. Particular LTR retrotransposon families (e.g., Gyma) are enriched on gene-free BACs, most of which do not come from pericentromeres or other large heterochromatic regions. Gene-containing BACs are relatively enriched in different families of LTR retrotransposons (e.g., Ji). Two major bursts of LTR retrotransposon activity in the last 2 million years are responsible for the large size of the maize genome, but only the more recent of these is well represented in gene-containing BACs, suggesting that LTR retrotransposons are more efficiently removed in these domains. The results demonstrate that sample sequencing and careful annotation of a few randomly selected BACs can provide a robust description of a complex plant genome.

Cromossomos Artificiais Bacterianos/genética , Genoma de Planta , Análise de Sequência de DNA , Zea mays/genética , Genes de Plantas , Marcadores Genéticos , Família Multigênica , Oryza/genética , Distribuição Aleatória , Análise de Sequência de DNA/métodos