Genome-Wide Association Mapping for Stripe Rust Resistance in Pakistani Spring Wheat Genotypes

Abstract

Stripe rust caused by the pathogen Puccinia striiformis f. sp. tritici (Pst) is a major threat for wheat, resulting in low yield and grain quality loss in many countries. Genetic resistance is a prevalent method to combat the disease. Mapping the resistant loci and their association with traits is highly exploited in this era. A panel of 465 Pakistani spring wheat genotypes were evaluated for their phenotypic response to stripe rust at the seedling and adult plant stages. A total of 765 single nucleotide polymorphism (SNP) markers were applied on 465 wheat genotypes to evaluate their stripe rust response against nine races during the seedling test and in three locations for the field test. Currently, twenty SNPs dispersed on twelve chromosomal regions (1A, 1B, 1D, 2A, 2B, 4A, 4B, 5B, 6A, 6B, 6D and 7B) have been identified that were associated with rust race-specific resistance at the seedling stage. Thirty SNPs dispersed on eighteen chromosomal regions (1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4B, 5A, 5B, 6A, 6B, 6D, 7A, 7B and 7D) are associated with adult plant resistance. SNP loci IWB3662 was linked with all three Pakistani races, and likewise IWA2344 and IWA4096 were found to be linked with three different USA races. The present research findings can be applied by wheat breeders to increase their resistant capability and yield potential of their cultivars, through marker-assisted selection.

Plant Biodiversity and Genetic Resources Matter!

“…Examples of conservation activities that impact on the use of the genetic resources that have been covered in this Special Issue include the following: easy access to genetic resources increases the capacity of breeders to respond to climate change and the availability of appropriate technologies [41]; access to traditional knowledge on the use of wild plant species [27]; a systematic association-mapping of wheat varieties with SNP markers was successfully used to associate adult plant stripe rust resistance with specific rust races, and results can be used in marker-assisted selection [29]; the analysis of a local genetic panel of manna ash with a continental dataset allowed conclusions on the presence of a possible glacial refuge, and thus facilitates the collecting and use of more genetic diversity [38]; the systematic characterization of ancient grape germplasm in Cyprus allowed the discovery of so far unnoticed genetic diversity [35]; literature searches and conducting field surveys allowed the identification of unknown wild food plants in Kenya [20]; fact sheets promoted the use of traditional food plants in the South Pacific [26]; the exploitation of the local genetic diversity of traditional pea landraces in Greece is fundamental for conservation practices and crop improvement through breeding strategies [32]; the evaluation of maize landrace accessions under heat and drought stresses resulted in invaluable sources of genes/alleles for adaptation breeding [30]; the review of recent efforts that build evidence of the importance of wild food plants in selected countries, while providing examples of cross-sectoral cooperation and multi-stakeholder approaches, contributes to enhancing their sustainable use [19]; the advances in conventional and molecular breeding for the drought tolerance of conventional staple crops, and the introduction of drought-tolerant neglected and underutilized species into existing production systems has the potential to enhance the resilience of agricultural production under conditions of water scarcity [40]; the utilization of advanced phenotyping tools, coupled with high-throughput genotyping, will accelerate the use of genetic resources and fast-track the development of more resilient food crops for the future [24]; and genomics-assisted breeding is increasingly facilitating the introgression of favorable genes and quantitative trait loci from wild species into cultigens, and will lead to a wider use of crop wild relatives in the development of resilient cultivars [25].…”

“…Several papers highlight the importance of vegetables as well as traditional, underutilized and wild food plants for food and nutrition security in general [19,25], in pilot studies in Kenya [20], and on atolls in the South Pacific [26], including specific crops, such as Hairy Stork's Bill (Erodium crassifolium) [27], and the sister of the common pomegranate (Punica protopunica), the latter also having interesting medicinal properties [28]. A number of papers focus on the genetic diversity of specific crops or specific traits in a range of food crops for the benefit of plant breeding, such as genome-wide association mapping for stripe rust resistance in spring wheat [29], diversity studies for drought and heat stress in maize landraces [30], nitrogen fixation and water use efficiency in common bean landraces and cultivars in Honduras [31], species identification of Katsouni pea on Greek Islands [32], wild potato germplasm evaluation for starch content and nitrogen utilization efficiency [33], diversity, population structure and marker-trait association for 100-seed weight in a safflower (Carthamus tinctorius) germplasm panel [34], the composition of Cypriot grapevine varieties [35], species assignment, genetic diversity and phylogeographic relationships of wild germplasm of macadamia [36], genetic diversity and population structure of Rhododendron rex subsp. rex [37], and genetic distinctiveness of a Sicilian manna ash (Fraxinus angustifolia) collection [38].…”

Genetic Variability through Induced Mutation

“…SNPs genotyping have been applied in many organism including rice [112][113][114], Arabidopsis [115], maize [116], soybean [117] and wheat [118]. The high class order of the rice genome has offered genome-wide SNPs source [119].…”

GWAS for Stripe Rust Resistance in Wild Emmer Wheat (Triticum dicoccoides) Population: Obstacles and Solutions

“…Most of the GWAS for adult plant stripe rust resistance in wheat used single-locus association algorithms that may not capture the multi-locus complexity of agronomic traits. However, in recent years, more GWAS to identify stripe rust APR have been using multi-locus analysis models such as FramCPU, BLINK, MMLM, and mrMLM [33][34][35][36][37][38][39].…”