Stripe rust or yellow rust, caused by Puccinia striiformis f. sp. tritici (Pst), is one of the most destructive diseases of wheat (Triticum aestivum L.) worldwide. Growing resistant cultivars is the most effective approach to control the disease. There have been numerous reports on the resistance genes to stripe rust (Yr gene) in wheat, but just a few Yr genes are resistant to currently epidemic races and applied in wheat production. Gene pyramiding is considered to be an effective way to enhance durable disease resistance in crops. In this experiment, a panel of Yr gene pyramiding lines (consisting of 3–8 Yr genes) with cv. Chuanyu12 as background parent were constructed by using marker assistant selection and evaluated under currently epidemic Pst races. The results showed that the number of pyramided Yr genes was significant correlated with stripe rust resistance (p < 0.001). Yr15, Yr62 and Yr65 are effective to the current Pst races. Pyramiding more than four effective or partially effective Yr genes can provide enough resistance to stripe rust. And additive effects or epistatic effects existed in gene combinations in this study, such as Yr26 + Yr48, Yr30 + Yr64 and Yr30 + Yr48 et al. Moreover, the effects of Yr gene pyramids on currently prevalent Pst races and agronomic traits were also evaluated, and Yr-gene pyramiding lines with desirable agronomic traits were obtained for durable controlling Pst in wheat breeding.

Developing stripe rust resistant wheat (Triticum aestivum L.) lines with gene pyramiding strategy and marker-assisted selection

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Integrating multipurpose perennial grains crops in Western European farming systems

Molecular markers such as RFLP, RAPD, AFLP, CAPS, DArT, SSR, SNP, etc. have been widely used in wheat genetic studies but have their own limitations. More recent types of molecular makers are the improved versions of some of the already available techniques due to the developments in the areas of next-generation sequencing, high-throughput genotyping, detection procedures and bioinformatics applications. At present, SNP markers have become a good choice due to their abundance in the genome, codominant inheritance, locus specificity, flexibility for high-throughput genotyping/detection formats and being relatively inexpensive. The next-generation sequencing (NGS) technologies have facilitated the discovery of a large number of SNPs for the development of high-resolution genetic maps, QTL/gene discovery and marker-assisted introgression, thereby improving the efficiency in wheat breeding. In this chapter, we attempt to review the recent advancements made in the area of molecular marker technologies such as hybridization-based platforms (fixed array), genotyping-by-sequencing (de novo), KASP genotyping, etc. The molecular markers developed with these advanced technologies in wheat offer easier means to map polymorphic genetic loci at highest density that facilitate enriching chromosomal regions to identify QTLs and candidate genes underlying important traits.

Advances in Molecular Markers and Their Use in Genetic Improvement of Wheat

Rust caused by the fungus Puccinia helianthi and downy mildew (DM) caused by the obligate pathogen Plasmopara halstedii are two of the most globally important sunflower diseases. Resistance to rust and DM is controlled by race-specific single dominant genes. The present study aimed at pyramiding rust resistance genes combined with a DM resistance gene, using molecular markers. Four rust resistant lines, HA-R3 (carrying the R4 gene), HA-R2 (R5), HA-R8 (R15), and RHA 397 (R13b), were each crossed with a common line, RHA 464, carrying a rust gene R12 and a DM gene PlArg. An additional cross was made between HA-R8 and RHA 397. Co-dominant simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers linked to the target genes were used to discriminate between homozygotes and heterozygotes in F2 populations. Five pyramids with different combinations of rust resistance genes were selected in the homozygous condition through marker-assisted selection, and three of them were combined with a DM resistance gene PlArg: R4/R12/PlArg, R5/R12/PlArg, R13b/R12/PlArg, R15/R12, and R13b/R15. The pyramiding lines with the stacking of two rust and one DM genes were resistant to all known races of North American sunflower rust and all known races of the pathogen causing DM, potentially providing multiple and durable resistance to both rust and DM. A cluster of 12 SNP markers spanning a region of 34.5 Mb on chromosome 1, which co-segregate with PlArg, were tested in four populations. Use of those markers, located in a recombination suppressed region in marker selection, is discussed.

https://www.mdpi.com/2073-4425/11/1/10/pdf

Marker-Assisted Gene Pyramiding and the Reliability of Using SNP Markers Located in the Recombination Suppressed Regions of Sunflower (Helianthus annuus L.).

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.

/pdf/breeding-with-major-and-minor-genes-genomic-selection-for-32tmomxuf8.pdf

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

This study was undertaken to pyramid two effective leaf rust resistance genes (Lr19 and Lr24) derived from Thinopyrum (syn. Agropyron), in the susceptible, but agronomically superior wheat cultivar HD2733 using marker-assisted selection. In the year 2001, HD2733 was released for irrigated timely sown conditions of the north eastern plains zone (NEPZ) of India became susceptible to leaf rust, a major disease of the region. Background selection helped in developing near-isogenic lines (NILs) of HD2733 with Lr19 and Lr24 with 97.27 and 98.94%, respectively, of genomic similarity with the parent cultivar, after two backcrossing and one generation of selfing.NILs were intercrossed to combine the genes Lr19 and Lr24. The combination of these two genes in the cultivar HD2733 is expected to provide durable leaf rust resistance in farmers' fields.

Pratima Kumari

Papers

Marker-assisted pyramiding of Thinopyrum-derived leaf rust resistance genes Lr19 and Lr24 in bread wheat variety HD2733.