Wheat is one of the most widely cultivated cereal crops worldwide, with an annual production of approximately 761 million tons (Crop Prospects and Food situation, 2020). Global wheat yields are threatened by climate change (Asseng et al., 2015, Barlow et al., 2015) and rapidly evolving pathogens, including rust diseases (Chaves et al., 2013). Among the rusts, stripe rust (YR) caused by Puccinia striiformis f.sp. tritici (Pst) is an economically important disease that has caused several major epidemics worldwide, resulting in significant production losses (Sanin and Nazarova 2010, Hovmoller et al., 2011, Ellis et al., 2014b, Xia et al., 2016a, Rahmatov, 2016, Ali et al., 2017). Historically, YR was prevalent in cooler climates, however, the majority of wheat growing areas in the world have now become prone to YR (Ali et al., 2014b, Hubbard et al., 2015). Currently, 88% of global wheat production is under threat to YR, which accounts for annual losses of more than one billion US dollars (Beddow et al., 2015a). Deployment of YR resistant varieties is the preferred method of rust disease management because it is cost-effective and reduces the reliance on fungicides (Chen, 2005a).
Genetic resistance to YR is broadly categorized into two major classes: all stage resistance (ASR) (e.g. R-genes) and adult plant resistance (APR-genes). ASR is often underpinned by a single gene with a large effect that provides effective resistance at all stages of plant growth. The R-gene interacts with the pathogen in a gene-for-gene relationship (Flor, 1971), and therefore is commonly referred to as “race-specific” resistance (Ellis et al., 2014a). When deployed in a variety grown on a large scale, strong selection pressure is exerted on the pathogen population to select for mutations that overcome the resistance mechanism. Therefore, this type of resistance is often rendered ineffective within just 3-5 years. In contrast, APR is typically controlled by multiple genes, each with minor or partial effect and are usually best expressed at adult growth stages. Most of the well-characterised APR genes are race nonspecific and usually confer a “slow rusting” phenotype, which is known to be more durable (Lagudah, 2011a, Ellis et al., 2014a, Mundt, 2014). Importantly, APR genes can contribute to high levels of resistance through additive or epistatic effects (Sorensen et al., 2014). Some of the genes, such as pleiotropic APRs and high temperature adult plant (HTAP) resistance genes, are highly valuable in breeding programs. For instance, APR genes Yr18, Yr29, Yr30 and Yr46 confer pleiotropic resistance to YR, leaf rust, stem rust and powdery mildew of wheat (Lan et al., 2015), while Yr18, Yr29, Yr36, Yr39 and Yr52 exhibit HTAP resistance (Chen, 2013b).
To date, 83 Yr resistance genes (Yr1–83) have been officially designated, along with 47 genes that have been temporarily named (McIntosh et al., 2019). According to the available information, most are classified as R-genes, whereas only 18 are classified as APR genes (Wu et al., 2016). Notably, only three APR genes Yr18/Lr34 (Krattinger et al., 2009), Yr36 (Fu et al., 2009), and Yr46 (Moore et al., 2015a) have been cloned to date (Liu et al., 2015). The majority of the R-genes, which have been deployed in various wheat varieties, are no longer effective due to the emergence of virulent pathotypes (Hovmoller et al., 2011). For instance, a large number of predominant races evolved from the year 2000 onwards and displayed added virulence to numerous resistance genes such as Yr2, Yr6, Yr7, Yr8, Yr9, Yr10, Yr17, Yr27, Yr43 and Yr44 (Wan and Chen, 2014). Virulence was also reported for some of the APR genes (Sorensen et al., 2014). Therefore, an additional level of durable genetic resistance could be achieved by pyramiding both seedling and APR genes in future varieties (Mundt, 2014). Hence, the discovery of new sources of genetic resistance is a priority for wheat research and the successful integration of new technologies in crop improvement programs is important to achieve long-term rust control.
Plant genetic resources that are stored in gene banks worldwide are a valuable source of genetic diversity for biotic and abiotic stresses (Rao, 2004b). Among these, wheat landraces and wild relatives are valuable sources of novel alleles for YR resistance (Sthapit et al., 2014, Manickavelu et al., 2016, Sthapit Kandel et al., 2017, Pasam et al., 2017). In previous studies, three important Yr genes (Yr47, Yr51 and Yr57) have been successfully characterized from wheat landraces in the Watkins collection (Bansal et al., 2011, Randhawa et al., 2015). Another historically important germplasm collection is preserved at the N.I. Vavilov Institute of Plant Genetic Resources (VIR) in Saint Petersburg, Russia, which holds ~38,430 wheat accessions. The collection comprises 76% bread wheat, 16% durum wheat and 7.9% wild and primitive wheats from diverse geographical origins (i.e., Africa, east and west Asia, USA, Canada, Central and South America, Europe) and of diverse biological status, including wild forms, local cultivars, breeding lines, mutants and artificial allopolyploids (Mitrofanova, 2012). While the VIR collection is yet to be explored for YR resistance, previous studies have highlighted the genetic variation for a number of biotic stresses (Mitrofanova, 2012, Sadovaya et al., 2015, Riaz et al., 2016a, Riaz et al., 2018).
To unravel the genetic architecture of rust resistance, bi-parental linkage mapping studies are traditionally performed (Yang et al,2017). However, high costs associated with population development, poor mapping resolution due to low recombination and the constraint of low allelic diversity, are some of the limitations associated with the linkage mapping approach (Flint-Garcia, 2013). Alternatively, a GWAS approach can be applied to a collection of accessions or a natural population. It offers broader allele coverage and higher mapping resolution due to historical recombination events among the panel of lines (Brachi et al., 2011a). This helps to localise the association signals to smaller regions within the chromosome and supports more efficient identification of candidate gene(s). However, applying GWAS to germplasm collections can be challenging because of population structure, which can result in spurious correlations between markers and traits (Gupta, Kulwal et al. 2019, Yang et al,2017). Another drawback is the low detection power of rare alleles with larger effects or multi-allelic variants with minor effects. Thus, an ideal GWAS analysis requires a large population size, high marker density and a mixed linear model to detect true genotype-phenotype associations (Bulli et al., 2016a). GWAS was initially successfully implemented for rust resistance in hexaploid wheat by Crossa et al. (2007b). Since then, it has been widely used in several studies to detect genomic regions associated with YR resistance in spring, winter, synthetic wheat germplasm, and landraces (Zegeye et al., 2014, Jighly et al., 2015, Maccaferri et al., 2015b, Naruoka et al., 2015,Bulli et al., 2016a, Godoy et al., 2017, Liu et al., 2017).
In this study, we evaluated 292 hexaploid bread wheat accessions from the VIR against Pst to identify novel sources of YR resistance. We applied GWAS to identify key genomic regions that could support the development of new cultivars incorporating durable resistance to YR.