Genomic prediction applied to high-biomass sorghum for bioenergy production.

Autor: de Oliveira AA; 1Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, SP 13418-900 Brazil., Pastina MM; Embrapa Maize and Sorghum, Sete Lagoas, Minas Gerais 35701-970 Brazil., de Souza VF; Embrapa Maize and Sorghum, Sete Lagoas, Minas Gerais 35701-970 Brazil., da Costa Parrella RA; Embrapa Maize and Sorghum, Sete Lagoas, Minas Gerais 35701-970 Brazil., Noda RW; Embrapa Maize and Sorghum, Sete Lagoas, Minas Gerais 35701-970 Brazil., Simeone MLF; Embrapa Maize and Sorghum, Sete Lagoas, Minas Gerais 35701-970 Brazil., Schaffert RE; Embrapa Maize and Sorghum, Sete Lagoas, Minas Gerais 35701-970 Brazil., de Magalhães JV; Embrapa Maize and Sorghum, Sete Lagoas, Minas Gerais 35701-970 Brazil., Damasceno CMB; Embrapa Maize and Sorghum, Sete Lagoas, Minas Gerais 35701-970 Brazil., Margarido GRA; 1Department of Genetics, Luiz de Queiroz College of Agriculture, University of São Paulo, Piracicaba, SP 13418-900 Brazil.
Jazyk: angličtina
Zdroj: Molecular breeding : new strategies in plant improvement [Mol Breed] 2018; Vol. 38 (4), pp. 49. Date of Electronic Publication: 2018 Apr 10.
DOI: 10.1007/s11032-018-0802-5
Abstrakt: The increasing cost of energy and finite oil and gas reserves have created a need to develop alternative fuels from renewable sources. Due to its abiotic stress tolerance and annual cultivation, high-biomass sorghum ( Sorghum bicolor L. Moench) shows potential as a bioenergy crop. Genomic selection is a useful tool for accelerating genetic gains and could restructure plant breeding programs by enabling early selection and reducing breeding cycle duration. This work aimed at predicting breeding values via genomic selection models for 200 sorghum genotypes comprising landrace accessions and breeding lines from biomass and saccharine groups. These genotypes were divided into two sub-panels, according to breeding purpose. We evaluated the following phenotypic biomass traits: days to flowering, plant height, fresh and dry matter yield, and fiber, cellulose, hemicellulose, and lignin proportions. Genotyping by sequencing yielded more than 258,000 single-nucleotide polymorphism markers, which revealed population structure between subpanels. We then fitted and compared genomic selection models BayesA, BayesB, BayesCπ, BayesLasso, Bayes Ridge Regression and random regression best linear unbiased predictor. The resulting predictive abilities varied little between the different models, but substantially between traits. Different scenarios of prediction showed the potential of using genomic selection results between sub-panels and years, although the genotype by environment interaction negatively affected accuracies. Functional enrichment analyses performed with the marker-predicted effects suggested several interesting associations, with potential for revealing biological processes relevant to the studied quantitative traits. This work shows that genomic selection can be successfully applied in biomass sorghum breeding programs.
Competing Interests: Compliance with ethical standardsThe authors declare that they have no conflict of interest.
Databáze: MEDLINE
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