VALIDATION OF QTL AND GENOMIC SELECTION OF STINK BUG COMPLEX RESISTANCE IN SOYBEAN

• Grant number: 19/13010-0
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Effective date (Start): October 31, 2019
• Effective date (End): August 31, 2020
• Field of knowledge: Agronomical Sciences - Agronomy - Crop Science
• Principal Investigator: José Baldin Pinheiro
• Grantee: Emanoel Sanches Martins
• Supervisor: Alexander Edward Lipka
• Host Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
• Research place: University of Illinois at Urbana-Champaign, United States
• Associated to the scholarship: 18/12399-9 - Mapping and study of QTL interaction by environment on resistance of soybeans to stink bug complex, BP.DR

Abstract

The aim of this project is to identify the QTLs involved in resistance to the soybean stink bug complex in a population of recombinant inbred lines (RILs), validate these QTLs through a genome-wide association study (GWAS) and finally perform a genomic selection. Two populations will be used: a mapping population with 256 RILs and controls, developed from the cross between IAC-100 (resistant) and CD-215 (susceptible); and a GWAS population, composed of 299 inbred lines and controls from a multiparental cross. Data from five harvests of RILs population as well as the 2018/2019 harvest data for the GWAS population, will be used. The experiments were carried out at the ESALQ Experimental Station in the city of Piracicaba, State of São Paulo, Brazil. The experimental design was an alpha lattice 10x26 and 16x19 for the RILs and GWAS population, respectively, with three replicates each. We evaluated nine traits associated with the resistance to the stink bug complex and agronomic performance. To obtain the genotypic data, genotyping-by-sequencing (GBS) was used for RILs and SoySNP50K iSelect BeadChip will be used for the GWAS population. In the RILs population, the phenotypic data will be analyzed through mixed models and later QTL mapping through Multiple Interval Mapping (MIM), using data from multiple environments. The study of GWAS will be carried out in order to validate the QTLs found in the RILs population. Finally, we will perform a genomic selection study using the GBLUP approach.