Breeding With Major and Minor Genes: Genomic Selection for Quantitative Disease Resistance.

Disease resistance in plants is mostly quantitative, with both major and minor genes controlling resistance. This research aimed to optimize genomic selection (GS) models for use in breeding programs that are needed to select both major and minor genes for resistance. In this study, stripe rust (Puccinia striiformis Westend. f. sp. tritici Erikss.) of wheat (Triticum aestivum L.) was used as a model for quantitative disease resistance. The quantitative nature of stripe rust is usually phenotyped with two disease traits, infection type (IT) and disease severity (SEV). We compared two types of training populations composed of 2,630 breeding lines (BLs) phenotyped in single-plot trials from 4 years (2016-2020) and 475 diversity panel (DP) lines from 4 years (2013-2016), both across two locations. We also compared the accuracy of models using four different major gene markers and genome-wide association study (GWAS) markers as fixed effects. The prediction models used 31,975 markers that are replicated 50 times using a 5-fold cross-validation. We then compared GS models using a marker-assisted selection (MAS) to compare the prediction accuracy of the markers alone and in combination. GS models had higher accuracies than MAS and reached an accuracy of 0.72 for disease SEV. The major gene and GWAS markers had only a small to nil increase in the prediction accuracy more than the base GS model, with the highest accuracy increase of 0.03 for the major markers and 0.06 for the GWAS markers. There was a statistical increase in the accuracy using the disease SEV trait, BLs, population type, and combining years. There was also a statistical increase in the accuracy using the major markers in the validation sets as the mean accuracy decreased. The inclusion of fixed effects in low prediction scenarios increased the accuracy up to 0.06 for GS models using significant GWAS markers. Our results indicate that GS can accurately predict quantitative disease resistance in the presence of major and minor genes.

Comparison of Single-Trait and Multi-Trait Genome-Wide Association Models and Inclusion of Correlated Traits in the Dissection of the Genetic Architecture of a Complex Trait in a Breeding Program.

Unknown genetic architecture makes it difficult to characterize the genetic basis of traits and associated molecular markers because of the complexity of small effect quantitative trait loci (QTLs), environmental effects, and difficulty in phenotyping. Seedling emergence of wheat (Triticum aestivum L.) from deep planting, has a poorly understood genetic architecture, is a vital factor affecting stand establishment and grain yield, and is historically correlated with coleoptile length. This study aimed to dissect the genetic architecture of seedling emergence while accounting for correlated traits using one multi-trait genome-wide association study (MT-GWAS) model and three single-trait GWAS (ST-GWAS) models. The ST-GWAS models included one single-locus model [mixed-linear model (MLM)] and two multi-locus models [fixed and random model circulating probability unification (FarmCPU) and Bayesian information and linkage-disequilibrium iteratively nested keyway (BLINK)]. We conducted GWAS using two populations. The first population consisted of 473 varieties from a diverse association mapping panel phenotyped from 2015 to 2019. The second population consisted of 279 breeding lines phenotyped in 2015 in Lind, WA, with 40,368 markers. We also compared the inclusion of coleoptile length and markers associated with reduced height as covariates in our ST-GWAS models. ST-GWAS found 107 significant markers across 19 chromosomes, while MT-GWAS found 82 significant markers across 14 chromosomes. The FarmCPU and BLINK models, including covariates, were able to identify many small effect markers while identifying large effect markers on chromosome 5A. By using multi-locus model breeding, programs can uncover the complex nature of traits to help identify candidate genes and the underlying architecture of a trait, such as seedling emergence.

Copy number and haplotype variation at the VRN-A1 and central FR-A2 loci are associated with frost tolerance in hexaploid wheat.

KEY MESSAGE: The interaction between VRN - A1 and FR - A2 largely affect the frost tolerance of hexaploid wheat. Frost tolerance is critical for wheat survival during cold winters. Natural variation for this trait is mainly associated with allelic differences at the VERNALIZATION 1 (VRN1) and FROST RESISTANCE 2 (FR2) loci. VRN1 regulates the transition between vegetative and reproductive stages and FR2, a locus including several tandemly duplicated C-REPEAT BINDING FACTOR (CBF) transcription factors, regulates the expression of Cold-regulated genes. We identified sequence and copy number variation at these two loci among winter and spring wheat varieties and characterized their association with frost tolerance. We identified two FR-A2 haplotypes-'FR-A2-S' and 'FR-A2-T'-distinguished by two insertion/deletions and ten single nucleotide polymorphisms within the CBF-A12 and CBF-A15 genes. Increased copy number of CBF-A14 was frequently associated with the FR-A2-T haplotype and with higher CBF14 transcript levels in response to cold. Factorial ANOVAs revealed significant interactions between VRN1 and FR-A2 for frost tolerance in both winter and spring panels suggesting a crosstalk between vernalization and cold acclimation pathways. The model including these two loci and their interaction explained 32.0 and 20.7 % of the variation in frost tolerance in the winter and spring panels, respectively. The interaction was validated in a winter wheat F 4:5 population segregating for both genes. Increased VRN-A1 copy number was associated with improved frost tolerance among varieties carrying the FR-A2-T allele but not among those carrying the FR-A2-S allele. These results suggest that selection of varieties carrying the FR-A2-T allele and three copies of the recessive vrn-A1 allele would be a good strategy to improve frost tolerance in wheat.

Large deletions in the CBF gene cluster at the Fr-B2 locus are associated with reduced frost tolerance in wheat.

Wheat plants which are exposed to periods of low temperatures (cold acclimation) exhibit increased survival rates when they are subsequently exposed to freezing temperatures. This process is associated with large-scale changes in the transcriptome which are modulated by a set of tandemly duplicated C-repeat Binding Factor (CBF) transcription factors located at the Frost Resistance-2 (Fr-2) locus. While Arabidopsis has three tandemly duplicated CBF genes, the CBF family in wheat has undergone an expansion and at least 15 CBF genes have been identified, 11 of which are present at the Fr-2 loci on homeologous group 5 chromosomes. We report here the discovery of three large deletions which eliminate 6, 9, and all 11 CBF genes from the Fr-B2 locus in tetraploid and hexaploid wheat. In wild emmer wheat, the Fr-B2 deletions were found only among the accessions from the southern sub-populations. Among cultivated wheats, the Fr-B2 deletions were more common among varieties with a spring growth habit than among those with a winter growth habit. Replicated freezing tolerance experiments showed that both the deletion of nine CBF genes in tetraploid wheat and the complete Fr-B2 deletion in hexaploid wheat were associated with significant reductions in survival after exposure to freezing temperatures. Our results suggest that selection for the wild-type Fr-B2 allele may be beneficial for breeders selecting for varieties with improved frost tolerance.