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Mapping and study of QTL interaction by environment on resistance of soybeans to stink bug complex

Grant number: 18/12399-9
Support type:Scholarships in Brazil - Doctorate
Effective date (Start): April 01, 2019
Field of knowledge:Agronomical Sciences - Agronomy - Crop Science
Principal Investigator:José Baldin Pinheiro
Grantee:Emanoel Sanches Martins
Home Institution: Escola Superior de Agricultura Luiz de Queiroz (ESALQ). Universidade de São Paulo (USP). Piracicaba , SP, Brazil
Associated scholarship(s):19/13010-0 - Validation of QTL and genomic selection of stink bug complex resistance in soybean, BE.EP.DR


Damage induced by stink bug complex in soybean results in loss of millions of dollars annually, and due to extensive areas cultivated these losses have increased and consequently reduce productivity gains. Among control alternatives, the use of soybean resistant cultivars to stink bug complex has been effected. The cultivar resistance is quantitative, in order words controlled by several genes, in this way approaches aim to elucidate control of these pests turns up determinant to soybean future. In this context, the aim of this project is to identify and elucidate interactions between QTLs (quantitative trait loci) and environments involved in soybean resistance to stink bug complex, in a population of recombinant inbred line (RILs). Population with 256 RILs from the cross between IAC-100 (resistant) and CD-215 (susceptible) will be used and the genitors and commercial cultivars AS3730 and Produza included as check in evaluations. The experiments will be carried out at ESALQ Experimental Station, in Piracicaba, SP, through 2016/2017, 2017/2018 and 2018/2019 crop, and will be performed by alpha lattice design 10x26, with three replications. Furthermore, it will be used data from historical series of this population from 2014/2015 and 2015/2016 crops. Overall, it will be evaluated a set of 13 traits associated to stink bug complex resistance and performance agronomic. The Genotyping-by-Sequencing technique will be used for genotyping RILs, from DNA extracted from young leaves. Subsequently, from obtained data the phenotypic data will be analyzed by mixed models and phenotypic and genotypic data will be performed the QTL mapping by Multiple Interval Mapping (MIM), using data from multiple environments, searching for stable QTLs which explain better the genetic architecture for stink bug complex resistance in soybean.