Applied phenomics and genomics for improving barley yellow dwarf resistance in winter wheat

Abstract

Barley yellow dwarf is one of the major viral diseases of cereals. Phenotyping barley yellow dwarf in wheat is extremely challenging due to similarities to other biotic and abiotic stresses. Breeding for resistance is additionally challenging as the wheat primary germplasm pool lacks genetic resistance, with most of the few resistance genes named to date originating from a wild relative species. The objectives of this study were to (1) evaluate the use of high-throughput phenotyping to improve barley yellow dwarf assessment; (2) identify genomic regions associated with barley yellow dwarf resistance; and (3) evaluate the ability of genomic selection models to predict barley yellow dwarf resistance. Up to 107 wheat lines were phenotyped during each of 5 field seasons under both insecticide treated and untreated plots. Across all seasons, barley yellow dwarf severity was lower within the insecticide treatment along with increased plant height and grain yield compared with untreated entries. Only 9.2% of the lines were positive for the presence of the translocated segment carrying the resistance gene Bdv2. Despite the low frequency, this region was identified through association mapping. Furthermore, we mapped a potentially novel genomic region for barley yellow dwarf resistance on chromosome 5AS. Given the variable heritability of the trait (0.211-0.806), we obtained a predictive ability for barley yellow dwarf severity ranging between 0.06 and 0.26. Including the presence or absence of Bdv2 as a covariate in the genomic selection models had a large effect for predicting barley yellow dwarf but almost no effect for other observed traits. This study was the first attempt to characterize barley yellow dwarf using field-high-throughput phenotyping and apply genomic selection to predict disease severity. These methods have the potential to improve barley yellow dwarf characterization, additionally identifying new sources of resistance will be crucial for delivering barley yellow dwarf resistant germplasm.

Keywords: Triticum aestivum; barley yellow dwarf (BYD); genome-wide association mapping (GWAS); genomic selection (GS); high-throughput phenotyping (HTP); resistance; tolerance; virus.

Fig. 1.

Adjusted phenotypic values for the traits collected manually for 5 different field seasons (2015–2016 to 2019–2020). a–e): Barley yellow dwarf severity (%) characterized as the typical visual symptoms of yellowing/purpling on leaves using a 0–100% visual scale; f–i) manual plant height/stunting (PTHT_M) (m), note that the trait was not recorded for the 2015–2016 season; and j–n) grain yield (tons/ha). The dashed line represents the mean value for the trait in each treatment.

Fig. 2.

Broad-sense heritability of wheat phenotypic traits collected manually, including visual barley yellow dwarf (BYD) score, plant height (PTHT_M), and grain yield (GY) during 5 different field seasons under 2 insecticide treatments.

Fig. 3.

Scatterplot of the first two principal component axis, made from principal component analysis on the marker matrix, n = 357 wheat lines, markers = 29,480. Each data point represents an individual wheat line that is color-coded by (a) breeding status; (b) prediction of Bdv2 presence/absence; and (c) adjusted mean for BYD severity (BYD BLUE) scored visually. Total variance explained by each principal component (PC) is listed on the axis.

Fig. 4.

Manhattan plots showing the marker-trait associations using 346 wheat accessions and 29,480 SNP markers obtained with genotyping-by-sequencing (GBS) for (a) BYD severity and (b) presence/absence of Bdv2 resistance gene. The 21 labeled wheat chromosomes with physical positions are on the x-axis and y-axis is the –log10 of the P-value for each SNP marker. Horizontal dashed lines represent the false discovery rate threshold at 0.01 level and highlighted data points above the threshold represent SNPs significantly associated with the trait. In (a), the length of the region and the haplotypes defined by the significant SNP markers is displayed.

Fig. 5.

Measurement of barley yellow dwarf disease severity in wheat based on certain haplotype effects were (a) the presence or absence of the translocation segment carrying the resistance gene Bdv2; (b) the 2 haplotypes for the significant region on chromosome 5AS; (c) the combination of 5A haplotypes with the presence or absence of Bdv2 gene; and (d) the 5A haplotypes combined with presence of Bdv2 resistant allele. Boxplots show the significant reduction of BYD disease severity by averaging the phenotypic best linear unbiased estimated (BLUE) values for the lines. Count is the number of wheat genotypes averaged in each group and mean is the mean BLUE value for the group.

Fig. 6.

Genomic selection model predictive ability where each column represents one trait, and each row shows the conformation of the training population including size of training and testing population and number of lines with presence of Bdv2 resistance gene. The value in each cell represents the predictive ability which is the correlation between the GS predicted value (GBLUP) and the phenotypic BLUP.