Molecular Mapping and QTL Controlling the Stink Bug Resistance in Soybean

Soybean (Glycine max (L.) Merrill) is one of the most important crops in the world and it is a major source of protein and vegetable oil. Brazil is the second largest producer of soybean, with a production of more than 81 million tons of grain in an area of almost 28 million hectares in 2012/2013. Stink bugs are one of the most important pests of soybean in several countries. These insects are responsible for significant yield losses and for reductions in seed quality and germination. They are also responsible for changes in seed oil and protein concentration and impairment of mechanical harvesting. There has been an increase in the use of insecticides to control this pest resulting in environmental damage and greater crop production costs. Moreover, indiscriminate use of pesticides on certain crops has contributed to the selection of resistant insect populations. The identification of QTL in soybean controlling stink bug resistance can enhance breeding programs by reducing the cycle of selection through the identification of plants with desirable traits. In this study, 228 F₂ plants obtained from crosses between IAC100 (resistant parent) and CD-215 (susceptible parent), were genotyped to construct a molecular map. F_2:3 lines were phenotypically measured for 15 traits including the number of days to flowering, plant height at flowering, number of days to maturity, plant height at maturity, graining period, lodging, leaf retention, agronomic value, index of pod damage, number of pods per plant, number of seeds, weight of spotted seeds, healthy seed weight, weight of a hundred seeds and grain yield. Linkage analysis was performed in OneMap and resulted in a map with 2397cM, consisting of 495 markers distributed across all 20 soybean linkage groups. The Model 6 (Zmapqtl) in QTL Cartographer® was used for the CIM analysis and QTL presence was evaluated for each 1cM considering a window size of 10cM. The LR threshold was determined considering 1000 permutation tests at 5% of significance. 88 QTL were identified for the 15 traits described above, distributed through 15 linkage groups. Due to a close position of some QTL and relation among traits we can infer that maybe the same QTL is controlling more than one trait. Those QTL associated with desirable agronomic and resistance traits will be used in a fine mapping approach to identify markers tightly linked with them. This strategy will be of greatest importance for soybean breeding programs accelerating the identification of desirable plants.