Evolution, diversity, and function of the disease susceptibility gene Snn1 in wheat.

Septoria nodorum blotch (SNB), caused by Parastagonospora nodorum, is a disease of durum and common wheat initiated by the recognition of pathogen-produced necrotrophic effectors (NEs) by specific wheat genes. The wheat gene Snn1 was previously cloned, and it encodes a wall-associated kinase that directly interacts with the NE SnTox1 leading to programmed cell death and ultimately the development of SNB. Here, sequence analysis of Snn1 from 114 accessions including diploid, tetraploid, and hexaploid wheat species revealed that some wheat lines possess two copies of Snn1 (designated Snn1-B1 and Snn1-B2) approximately 120 kb apart. Snn1-B2 evolved relatively recently as a paralog of Snn1-B1, and both genes have undergone diversifying selection. Three point mutations associated with the formation of the first SnTox1-sensitive Snn1-B1 allele from a primitive wild wheat were identified. Four subsequent and independent SNPs, three in Snn1-B1 and one in Snn1-B2, converted the sensitive alleles to insensitive forms. Protein modeling indicated these four mutations could abolish Snn1-SnTox1 compatibility either through destabilization of the Snn1 protein or direct disruption of the protein-protein interaction. A high-throughput marker was developed for the absent allele of Snn1, and it was 100% accurate at predicting SnTox1-insensitive lines in both durum and spring wheat. Results of this study increase our understanding of the evolution, diversity, and function of Snn1-B1 and Snn1-B2 genes and will be useful for marker-assisted elimination of these genes for better host resistance.

Association mapping of tan spot and septoria nodorum blotch resistance in cultivated emmer wheat.

KEY MESSAGE: A total of 65 SNPs associated with resistance to tan spot and septoria nodorum blotch were identified in a panel of 180 cultivated emmer accessions through association mapping Tan spot and septoria nodorum blotch (SNB) are foliar diseases caused by the respective fungal pathogens Pyrenophora tritici-repentis and Parastagonospora nodorum that affect global wheat production. To find new sources of resistance, we evaluated a panel of 180 cultivated emmer wheat (Triticum turgidum ssp. dicoccum) accessions for reactions to four P. tritici-repentis isolates Pti2, 86-124, 331-9 and DW5, two P. nodorum isolate, Sn4 and Sn2000, and four necrotrophic effectors (NEs) produced by the pathogens. About 8-36% of the accessions exhibited resistance to the four P. tritici-repentis isolates, with five accessions demonstrating resistance to all isolates. For SNB, 64% accessions showed resistance to Sn4, 43% to Sn2000 and 36% to both isolates, with Spain (11% accessions) as the most common origin of resistance. To understand the genetic basis of resistance, association mapping was performed using SNP (single nucleotide polymorphism) markers generated by genotype-by-sequencing and the 9 K SNP Infinium array. A total of 46 SNPs were significantly associated with tan spot and 19 SNPs with SNB resistance or susceptibility. Six trait loci on chromosome arms 1BL, 3BL, 4AL (2), 6BL and 7AL conferred resistance to two or more isolates. Known NE sensitivity genes for disease development were undetected except Snn5 for Sn2000, suggesting novel genetic factors are controlling host-pathogen interaction in cultivated emmer. The emmer accessions with the highest levels of resistance to the six pathogen isolates (e.g., CItr 14133-1, PI 94634-1 and PI 377672) could serve as donors for tan spot and SNB resistance in wheat breeding programs.

Implementing multi-trait genomic selection to improve grain milling quality in oats (Avena sativa L.).

Oats (Avena sativa L.) provide unique nutritional benefits and contribute to sustainable agricultural systems. Breeding high-value oat varieties that meet milling industry standards is crucial for satisfying the demand for oat-based food products. Test weight, thins, and groat percentage are primary traits that define oat milling quality and the final price of food-grade oats. Conventional selection for milling quality is costly and burdensome. Multi-trait genomic selection (MTGS) combines information from genome-wide markers and secondary traits genetically correlated with primary traits to predict breeding values of primary traits on candidate breeding lines. MTGS can improve prediction accuracy and significantly accelerate the rate of genetic gain. In this study, we evaluated different MTGS models that used morphometric grain traits to improve prediction accuracy for primary grain quality traits within the constraints of a breeding program. We evaluated 558 breeding lines from the University of Illinois Oat Breeding Program across 2 years for primary milling traits, test weight, thins, and groat percentage, and secondary grain morphometric traits derived from kernel and groat images. Kernel morphometric traits were genetically correlated with test weight and thins percentage but were uncorrelated with groat percentage. For test weight and thins percentage, the MTGS model that included the kernel morphometric traits in both training and candidate sets outperformed single-trait models by 52% and 59%, respectively. In contrast, MTGS models for groat percentage were not significantly better than the single-trait model. We found that incorporating kernel morphometric traits can improve the genomic selection for test weight and thins percentage.