Population Structure and Genomewide Association Analysis of Resistance to Disease and Insensitivity to Ptr Toxins in Canadian Spring Wheat Using 90K SNP Array

Abstract

Leaf rust, yellow (stripe) rust, common bunt, and tan spot are economically significant diseases affecting wheat (Triticum aestivum L.) production in Canada. In this study, we investigated the genetic relationship and population structure of 81 Canadian western spring wheat cultivars released primarily between 1963 and 2011 and identified genomic regions associated with resistance to the above four diseases and insensitivity to three Pyrenophora tritici‐repentis (Ptr) toxins (Ptr ToxA, Ptr ToxB and Ptr ToxC). The cultivars were evaluated for field reaction to the four diseases and for reaction to the three Ptr toxins in a greenhouse and were genotyped with a subset of 19,919 of the wheat 90K single‐nucleotide polymorphic array and 11 gene‐specific markers. There were large genetic differences among pairwise comparisons of cultivars, except six pairs that showed <0.05 genetic distance. The cultivars exhibited clear population structure, generally in agreement with the major western Canada spring wheat classes. Using a threshold of p ≤ 5 × 10−5 and a weighted mixed linear model, we identified 94 markers from seven chromosomes associated with all traits except Ptr ToxC. Two major‐effect genomic regions on chromosomes 5B (71–74 cM) and 1A (52–53 cM) were associated with Ptr ToxA, of which the former coincided with the Tsn1 gene. For Ptr ToxB, we identified two other major‐effect regions on chromosomes 2B and 5B. The genomic regions associated with common bunt mapped on 2B, 4B, and 7A, whereas those associated with leaf rust mapped at two positions on 2B. We were only able to uncover a single marker‐trait association for tan spot on 7B and for yellow rust on 2A.

Wheat tandem kinases provide insights on disease‐resistance gene flow and host–parasite co‐evolution

“…Population genetic studies are essential for understanding the evolution of wheat under natural hybridization, allopolyploid speciation, natural selection, domestication, and other factors (Fahima et al ., , ; Novoselović et al ., ; Perez‐Lara et al ., ; Wang et al ., ; Eltaher et al ., ). Studies that are based on large amounts of high‐throughput genetic markers are preferable as they are aiming to characterize the general pattern of gene flow between and within populations.…”

“…The characterization of population genetic structure provides important information contributing to a better understanding of spacial distribution, adaptation, and evolution of natural plant populations. In wheat, diverse technologies that are based on randomly distributed markers were used for genotyping both natural WEW populations and domesticated wheat collections, such as RAPDs (Fahima et al ., ), microsatellites (Fahima et al ., ; Wang et al, 2017) DArTs (Novoselović et al ., ), and SNPs (GBS, Eltaher et al ., ; 90K SNP array, Perez‐Lara et al ., ). Various studies have been conducted also based on sequence variation of a single gene in WEW populations and cultivated wheat collections aimed to understand the evolutionary processes that shaped the allelic variation, structure and function of pivotal genes, including the NAM‐B1 ( Gpc‐B1 ) high grain protein and mineral content gene (Lundström et al ., ), the Pm3 powdery mildew resistance gene (Yahiaoui et al ., ), the Lr10 leaf rust‐resistance gene (Sela et al ., ), and the WKS stripe rust‐resistance genes (Huang et al ., ).…”

Physical Mapping of QTL in Four Spring Wheat Populations under Conventional and Organic Management Systems. I. Earliness

“…The wheat breeding group at the University of Alberta has been conducting extensive research in the Canada Western Red Spring (CWRS) wheat class, including (i) developing several improved cultivars [ 7 , 8 , 9 , 10 ], (ii) evaluating the phenotypic performance of diverse cultivars under conventional and/or organic managements [ 11 , 12 , 13 , 14 , 15 , 16 ], (iii) understanding the genetics of earliness that serves as baseline data for developing early maturing cultivars to avoid frost damage [ 17 , 18 , 19 , 20 ], and (iv) mapping genes and QTL associated with diverse traits using biparental populations [ 19 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ] and a genomewide association mapping panel [ 28 , 29 ]. The development of early-maturing CWRS cultivars is of paramount importance in the northern breeding programs to provide farmers not only an option of growing the crop with minimal loss due to frost but also help to escape from the late incidence of diseases, heat, and drought as compared with their late-maturing counterparts.…”

Phenotypic performance and associated QTL of ‘Peace’ × ‘CDC Stanley’ mapping population under conventional and organic management systems

“…The lack of stability and consistency of QTL across management conditions, environments, and genetic backgrounds (populations) are major challenges affecting the likelihood of successfully introgressing QTL through MAS (Bernardo, 2008; Semagn et al., 2010). Several studies reported QTL associated with diverse traits in CWRS wheat class under conventional management (Asif et al., 2015a; Bemister et al., 2019; Chen et al., 2017; Kamran et al., 2013; Perez‐Lara et al., 2016; Perez‐Lara, Semagn, Chen et al., 2017; Perez‐Lara, Semagn, Tran et al., 2017; Zou, Semagn, Iqbal, Chen et al., 2017), but only a few mapping studies were conducted under organic management (Asif et al., 2015a; Chen et al., 2020; Zou, Semagn, Iqbal, N'Diaye et al., 2017). In one of the mapping studies, we reported eight QTL in a recombinant inbred line (RIL) population derived from ‘Attila’ and ‘CDC Go’ evaluated across three organic and conventional management systems of about 500 m apart, and genotyped with 579 diversity arrays technology (DArT) and Rht‐B1 markers (Asif et al., 2015a), but only a single QTL was common between the two managements.…”