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ARS Home » Plains Area » Fargo, North Dakota » Edward T. Schafer Agricultural Research Center » Sunflower and Plant Biology Research » Research » Research Project #435159

Research Project: Enhancing Soybean for Resistance to Sclerotinia Stem Rot

Location: Sunflower and Plant Biology Research

Project Number: 3060-21220-031-22-S
Project Type: Non-Assistance Cooperative Agreement

Start Date: Jul 1, 2018
End Date: Dec 31, 2020

1) Enrich the frequency of favorable alleles in the F 2:3 lines of 8 breeding population via MAS. 2) Continue on evaluation of advanced breeding lines for resistance to SSR and release the best lines as germplasm or varieties. 3) Maximize reliability of genomic selection (GS) model by enlarging training population size, optimizing statistical method and choice of reference individuals in the training population.

For Objective 1, all F2 lines will be grown in the greenhouse the next year and allowed to self-pollinate to produce F3 lines. All F3 lines will be genotyped with SNPs markers (Table 2) identified from our previous studies. About 35% F4 lines with favorable alleles at target QTL will be planted in hill plots. Those selected lines will be subjected to further selection according to performance in the hill plots and final yield. For Objective 2, over 100 advanced breeding lines derived from multiple sources of resistance to Sclerotinia will be evaluated for resistance to SSR in our Sclerotinia disease nursery. The Sclerotinia disease nursery is a naturally infected field on our research farm with frequent heavy natural Sclerotinia infections. An irrigation system will be used to provide the wet condition to promote the disease development during the flowing period. About 15% of the lines will be selected based on their resistance to SSR, yield, and other agronomic traits. The selected lines will be re-evaluated in our disease nursery for resistance to SSR and yield under disease pressure. Five to 10 lines will be selected and tested in the Uniform Soybean Tests – Northern Region (19 locations in 10 northern US states and 1 Canadian province), for yield and other agronomic traits. The best lines will be released to the public. For Objective 3, since the size and the composition of this set are essential parameters affecting the prediction reliabilities. On one hand all advances breeding lines used in Objective 2 will be genotyped with Illumina SoySNP6k _v2 BeadChip. These genotypic data combining with the disease score data will be integrated with the previously acquired dataset to enlarge the training set. On the other hand, we seek to optimize criteria of choice of individuals in training set for maximize reliability of GS model.