Genome wide selection methods applied to high biomass sorghum for the production of second generation ethanol

• Grant number: 13/25132-7
• Support Opportunities: Scholarships in Brazil - Master
• Start date: April 01, 2014
• End date: July 31, 2015
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: Gabriel Rodrigues Alves Margarido
• Grantee: Amanda Avelar de Oliveira
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil

Abstract

Increased concerns about environmental issues have aroused global interest in the use of alternative fuels. The use of plant biomass emerges as a viable alternative for the generation of biofuels. Different organic materials have been used, including high biomass sorghum (Sorghum bicolor L. Moench), a type of sorghum with rapid growth and high yield potential, which has good chances of becoming an important crop for ethanol production. Genomic selection has great potential and could, in the medium term, restructure plant breeding programs, promoting greater genetic gains when compared to other methods and significantly reducing the time required for the development of new cultivars through early selection. This work proposes to evaluate models of genomic selection to be used for the prediction of breeding values for a panel of high biomass sorghum individuals of Embrapa / Milho e Sorgo. This panel was designed by Embrapa breeders and includes materials from the gene bank and materials used in forage sorghum breeding programs of this institution, as well as core collections from CIRAD and ICRISAT. The 200 lines in the panel are currently in the final stages of phenotypic assessment and will be genotyped using genotyping by sequencing technology. The phenotypic traits evaluated include days to flowering, plant length, amount of fresh and dry mass and fiber, cellulose, hemicellulose and lignin proportions. Based on these genotypic and phenotypic data, we will use the following models of genomic selection: RRBLUP / GBLUP, Bayes A, Bayes B, Bayes C and Bayes CÀ. For each of the evaluated phenotypic traits, we will fit and compare the various statistical models based on the accuracy of genomic estimated breeding values and the ranking of the top individuals.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

DE OLIVEIRA, AMANDA AVELAR; PASTINA, MARIA MARTA; DE SOUZA, VANDER FILIPE; DA COSTA PARRELLA, RAFAEL AUGUSTO; NODA, ROBERTO WILLIANS; FERREIRA SIMEONE, MARIA LUCIA; SCHAFFERT, ROBERT EUGENE; DE MAGALHES, JURANDIR VIEIRA; BORGES DAMASCENO, CYNTHIA MARIA; ALVES MARGARIDO, GABRIEL RODRIGUES. Genomic prediction applied to high-biomass sorghum for bioenergy production. MOLECULAR BREEDING, v. 38, n. 4, APR 2018. (15/22993-7, 13/25132-7)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

OLIVEIRA, Amanda Avelar de. Genome wide selection methods applied to high biomass sorghum for the production of second generation ethanol. 2015. Master's Dissertation - Universidade de São Paulo (USP). Escola Superior de Agricultura Luiz de Queiroz (ESALA/BC) Piracicaba.