Exploiting genetic diversity from landraces in wheat breeding for adaptation to climate change.

Climate change has generated unpredictability in the timing and amount of rain, as well as extreme heat and cold spells that have affected grain yields worldwide and threaten food security. Sources of specific adaptation related to drought and heat, as well as associated breeding of genetic traits, will contribute to maintaining grain yields in dry and warm years. Increased crop photosynthesis and biomass have been achieved particularly through disease resistance and healthy leaves. Similarly, sources of drought and heat adaptation through extended photosynthesis and increased biomass would also greatly benefit crop improvement. Wheat landraces have been cultivated for thousands of years under the most extreme environmental conditions. They have also been cultivated in lower input farming systems for which adaptation traits, particularly those that increase the duration of photosynthesis, have been conserved. Landraces are a valuable source of genetic diversity and specific adaptation to local environmental conditions according to their place of origin. Evidence supports the hypothesis that landraces can provide sources of increased biomass and thousand kernel weight, both important traits for adaptation to tolerate drought and heat. Evaluation of wheat landraces stored in gene banks with highly beneficial untapped diversity and sources of stress adaptation, once characterized, should also be used for wheat improvement. Unified development of databases and promotion of data sharing among physiologists, pathologists, wheat quality scientists, national programmes, and breeders will greatly benefit wheat improvement for adaptation to climate change worldwide.

Evaluation and Association Mapping of Resistance to Tan Spot and Stagonospora Nodorum Blotch in Adapted Winter Wheat Germplasm.

Tan spot and Stagonospora nodorum blotch (SNB), often occurring together, are two economically significant diseases of wheat in the Northern Great Plains of the United States. They are caused by the fungi Pyrenophora tritici-repentis and Parastagonospora nodorum, respectively, both of which produce multiple necrotrophic effectors (NE) to cause disease. In this work, 120 hard red winter wheat (HRWW) cultivars or elite lines, mostly from the United States, were evaluated in the greenhouse for their reactions to the two diseases as well as NE produced by the two pathogens. One P. nodorum isolate (Sn4) and four Pyrenophora tritici-repentis isolates (Pti2, 331-9, DW5, and AR CrossB10) were used separately in the disease evaluations. NE sensitivity evaluation included ToxA, Ptr ToxB, SnTox1, and SnTox3. The numbers of lines that were rated highly resistant to individual isolates ranged from 11 (9%) to 30 (25%) but only six lines (5%) were highly resistant to all isolates, indicating limited sources of resistance to both diseases in the U.S. adapted HRWW germplasm. Sensitivity to ToxA was identified in 83 (69%) of the lines and significantly correlated with disease caused by Sn4 and Pti2, whereas sensitivity to other NE was present at much lower frequency and had no significant association with disease. As expected, association mapping located ToxA and SnTox3 sensitivity to chromosome arm 5BL and 5BS, respectively. A total of 24 potential quantitative trait loci was identified with -log (P value) > 3.0 on 12 chromosomes, some of which are novel. This work provides valuable information and tools for HRWW production and breeding in the Northern Great Plains.

Genomic Selection in Preliminary Yield Trials in a Winter Wheat Breeding Program.

Genomic prediction (GP) is now routinely performed in crop plants to predict unobserved phenotypes. The use of predicted phenotypes to make selections is an active area of research. Here, we evaluate GP for predicting grain yield and compare genomic and phenotypic selection by tracking lines advanced. We examined four independent nurseries of F3:6 and F3:7 lines trialed at 6 to 10 locations each year. Yield was analyzed using mixed models that accounted for experimental design and spatial variations. Genotype-by-sequencing provided nearly 27,000 high-quality SNPs. Average genomic predictive ability, estimated for each year by randomly masking lines as missing in steps of 10% from 10 to 90%, and using the remaining lines from the same year as well as lines from other years in a training set, ranged from 0.23 to 0.55. The predictive ability estimated for a new year using the other years ranged from 0.17 to 0.28. Further, we tracked lines advanced based on phenotype from each of the four F3:6 nurseries. Lines with both above average genomic estimated breeding value (GEBV) and phenotypic value (BLUP) were retained for more years compared to lines with either above average GEBV or BLUP alone. The number of lines selected for advancement was substantially greater when predictions were made with 50% of the lines from the testing year added to the training set. Hence, evaluation of only 50% of the lines yearly seems possible. This study provides insights to assess and integrate genomic selection in breeding programs of autogamous crops.