Thesis - Open Access
Master of Science (MS)
Sunish K. Sehgal
Global wheat production is threatened by the change in climate thus leading lead to the increase in the biotic and abiotic stresses. We need to increase wheat productivity at a faster pace and manage these challenges to meet the growing demand. Development of cultivars with durable disease resistance and enhancing the rate of genetic gain in wheat are the major goals in wheat breeding programs. Bacterial Leaf Streak (BLS) is one of the most threatening bacterial diseases to wheat in the US Northern Great Plains. Unlike fungal diseases, bacterial diseases cannot be effectively managed using chemicals and thus developing disease resistant cultivars would be the most economical control for BLS. Identification and characterization of genomic regions in wheat that confer resistance to BLS can be an effective way to mobilize resistance genes in wheat breeding. Here we performed Genome – wide association mapping on a Hard Winter Wheat Association Panel (HWWMP) to identify genomic regions that confer resistance to BLS. The genotyped data for this panel of 300 winter wheat lines from the major breeding programs across the Midwestern region of the US was obtained from T3 Triticale Toolbox (under the GPL license). The responses of all these lines against Xanthomonas campestris pv. translucens in the greenhouse and field conditions were evaluated. Association Mapping (AM) was used to detect marker – trait associations using ECMLM, and we identified five QTL regions (Q.bls.sdsu.1AL, Q.bls.sdsu.1BS, Q.bls.sdsu.3AL, Q.bls.sdsu.4AL and Q.bls.sdsu.7AS) conferring BLS resistance. In total, these five QTLs explained 42% of the variation. Eleven genotypes were identified, which could be used as a source of resistance against BLS. Comparative analysis of three of the identified QTLs (Q.bls.sdsu.1AL, Q.bls.sdsu.3AL and Q.bls.sdsu.4AL) with rice showed BLS resistance genes in rice (qBLSr5d, qBLSr1, and qBLSr3d) located on syntenic regions in rice chromosomes 5R, 1R and 3R respectively. The 11 BLS resistant genotypes and SNP markers linked to QTLs identified in our study could facilitate breeding BLS resistance in wheat. For grain yield improvement, we assessed the robustness for genomic selection (GS) in the South Dakota State Winter Wheat Breeding program (SDSWWBP). We performed GS with a set of 434 advanced breeding lines (AYT and PYT nurseries) between the years 2014 – 2017. These lines were genotyped by sequencing GBS and the yield data from 34 years × location combinations were used as a phenotype. We developed training and validation datasets for testing the genomic prediction accuracies. Single and multiyear analysis were done using several GS models (rrBLUP, PLSR, ELNET and Random Forest). The average predictions accuracies within a single year across locations were 0.62. However, with the multi-year-location analysis, the average genomic prediction accuracies were 0.26 for two-year combination, 0.32 for three-year combination and 0.36 for the four-year combination. Our results suggested several years of data is required to develop better genome-wide selection models.
Includes bibliographical references (pages 86-92)
Number of Pages
South Dakota State University
In Copyright - Non-Commercial Use Permitted
Ramakrishnan, Sai Mukund, "Application of Genomic Approaches to Improve Yield and Bacterial Leaf Streak Resistance in Winter Wheat" (2018). Electronic Theses and Dissertations. 2418.