Genome wide association study for stripe rust resistance in spring bread wheat (Triticum aestivum L.)

Messoadi, Khalil El; Hanafi, Samira El; Gataa, Zakaria El; Kehel, Zakaria; bouhouch, Yassin; Tadesse, Wuletaw

doi:10.1007/s42161-022-01132-z

Cited by 9 publications

(7 citation statements)

References 40 publications

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“…Similarly, the present study identified that chromosome 2B harbored many yellow rust resistance putative QTLs, and this finding was in line with the reports of Feng et al. (2018) and Khalil et al. (2022) , who described several yellow rust resistance QTLs on the same chromosome, including Yr64, Yr65, YrTr1, YrAlp, YrH122, YrL693, YrC142, YrMY41, QYr.cau-1BS, QYrco.wpg-1BS.1, and QYrco.wpg-1BS.2.…”

Section: Discussionsupporting

confidence: 93%

Genetic architecture of adult-plant resistance to stripe rust in bread wheat (Triticum aestivum L.) association panel

Atsbeha,

Mekonnen,

Kebede

et al. 2023

Front. Plant Sci.

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Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a severe disease in wheat worldwide, including Ethiopia, causing up to 100% wheat yield loss in the worst season. The use of resistant cultivars is considered to be the most effective and durable management technique for controlling the disease. Therefore, the present study targeted the genetic architecture of adult plant resistance to yellow rust in 178 wheat association panels. The panel was phenotyped for yellow rust adult-plant resistance at three locations. Phonological, yield, yield-related, and agro-morphological traits were recorded. The association panel was fingerprinted using the genotyping-by-sequencing (GBS) platform, and a total of 6,788 polymorphic single nucleotide polymorphisms (SNPs) were used for genome-wide association analysis to identify effective yellow rust resistance genes. The marker-trait association analysis was conducted using the Genome Association and Prediction Integrated Tool (GAPIT). The broad-sense heritability for the considered traits ranged from 74.52% to 88.64%, implying the presence of promising yellow rust resistance alleles in the association panel that could be deployed to improve wheat resistance to the disease. The overall linkage disequilibrium (LD) declined within an average physical distance of 31.44 Mbp at r2 = 0.2. Marker-trait association (MTA) analysis identified 148 loci significantly (p = 0.001) associated with yellow rust adult-plant resistance. Most of the detected resistance quantitative trait loci (QTLs) were located on the same chromosomes as previously reported QTLs for yellow rust resistance and mapped on chromosomes 1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4A, 4B, 4D, 5A, 5B, 6A, 6B, 7A, and 7D. However, 12 of the discovered MTAs were not previously documented in the wheat literature, suggesting that they could represent novel loci for stripe rust resistance. Zooming into the QTL regions in IWGSC RefSeq Annotation v1 identified crucial disease resistance-associated genes that are key in plants’ defense mechanisms against pathogen infections. The detected QTLs will be helpful for marker-assisted breeding of wheat to increase resistance to stripe rust. Generally, the present study identified putative QTLs for field resistance to yellow rust and some important agronomic traits. Most of the discovered QTLs have been reported previously, indicating the potential to improve wheat resistance to yellow rust by deploying the QTLs discovered by marker-assisted selection.

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Section: Discussionsupporting

confidence: 93%

Genetic architecture of adult-plant resistance to stripe rust in bread wheat (Triticum aestivum L.) association panel

Atsbeha,

Mekonnen,

Kebede

et al. 2023

Front. Plant Sci.

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“…The Dice similarity index [ 43 ] was used to calculate the genetic similarity between each pair of genotypes. NTSYS-pc V2.1 was used to construct a dendrogram using the unweighted double group method with arithmetic mean (UPGMA) and SAHN clustering [ 25 ]. Principal coordinate analysis (PCoA) and molecular analysis of variance (AMOVA) were calculated using GenAlExV6.5 [ 44 ].…”

Section: Methodsmentioning

confidence: 99%

“…To address this problem, several molecular markers have emerged as biotechnological tools for studying genetic diversity and population structure [ 16 ]. With the development of biological aspects, a number of molecular marker techniques have emerged, such as random amplified polymorphic DNA (RAPD) [ 17 ], amplified fragment length polymorphisms (AFLP) [ 18 ], inter-simple sequence repeats (ISSR) [ 19 ], start codon targeted markers (SCoT) [ 20 ], Inter-primer binding site (iPBS)-retrotransposons [ 21 ], expressed sequence tag (EST) [ 22 ], single nucleotide polymorphism (SNP) [ 23 ], next-generation sequencing (NGS) [ 24 ], divergence array technology (DArT) [ 25 ] and simple sequence repeats (SSR) [ 26 ] have been developed. Of these, SSR markers served as effective molecular markers for studying genetic diversity in hexaploid Türkiye wheat embryos [ 7 , 27 , 28 ].…”

Section: Introductionmentioning

confidence: 99%

Genetic Diversity and Population Structure in Türkiye Bread Wheat Genotypes Revealed by Simple Sequence Repeats (SSR) Markers

Türkoğlu

Haliloğlu

Mohammadi

et al. 2023

Genes

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Wheat genotypes should be improved through available germplasm genetic diversity to ensure food security. This study investigated the molecular diversity and population structure of a set of Türkiye bread wheat genotypes using 120 microsatellite markers. Based on the results, 651 polymorphic alleles were evaluated to determine genetic diversity and population structure. The number of alleles ranged from 2 to 19, with an average of 5.44 alleles per locus. Polymorphic information content (PIC) ranged from 0.031 to 0.915 with a mean of 0.43. In addition, the gene diversity index ranged from 0.03 to 0.92 with an average of 0.46. The expected heterozygosity ranged from 0.00 to 0.359 with a mean of 0.124. The unbiased expected heterozygosity ranged from 0.00 to 0.319 with an average of 0.112. The mean values of the number of effective alleles (Ne), genetic diversity of Nei (H) and Shannon’s information index (I) were estimated at 1.190, 1.049 and 0.168, respectively. The highest genetic diversity (GD) was estimated between genotypes G1 and G27. In the UPGMA dendrogram, the 63 genotypes were grouped into three clusters. The three main coordinates were able to explain 12.64, 6.38 and 4.90% of genetic diversity, respectively. AMOVA revealed diversity within populations at 78% and between populations at 22%. The current populations were found to be highly structured. Model-based cluster analyses classified the 63 genotypes studied into three subpopulations. The values of F-statistic (Fst) for the identified subpopulations were 0.253, 0.330 and 0.244, respectively. In addition, the expected values of heterozygosity (He) for these sub-populations were recorded as 0.45, 0.46 and 0.44, respectively. Therefore, SSR markers can be useful not only in genetic diversity and association analysis of wheat but also in its germplasm for various agronomic traits or mechanisms of tolerance to environmental stresses.

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“…This is the main goal for wheat breeders in the recent decade. Many efforts have been made to achieve this goal [6,7,[10][11][12][13][14][15][16][17][18][19][20][21][22]. However, breeding programs need a long time to produce promising resistant genotypes.…”

Section: Introductionmentioning

confidence: 99%

Alleviation of Stripe Rust Disease in Wheat Seedlings Using Three Different Species of Trichoderma spp.

Mourad,

Börner,

Esmail

2023

Agriculture

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Wheat stripe rust (WSR) caused by Puccinia striiformis F. tritici Erikss. (Pst) is one of the serious diseases that affect wheat planting areas around the world. Many efforts have been made to control such a serious disease including using fungicides and breeding highly resistant genotypes. However, due to Pst’s ability to produce new races that overcome these fungicides and break the resistance in the highly resistant genotypes, looking for other effective ways to restrict this disease is urgently required. One of the highly effective ways of controlling crop diseases is using biological control. In this study, the efficiency of three different Trichoderma species (Trichoderma asperellum T34, Trichoderma harzianum (TH), and Trichoderma verdinium (TV)) was tested in a set of 34 wheat genotypes at the seedling stage. The evaluation was conducted in two experiments with two different temperature regimes. In each experiment, four treatments were applied, namely, control, T34, TV, and TH. High genetic variation was found among all genotypes in each experiment and under each Trichoderma treatment. Notably, the symptoms of WSR were affected by temperature under all treatments except T34, which had a stable performance in the two experiments. The 34 studied genotypes were highly diverse, related to ten different countries, and consisted of durum and bread wheat. Out of the three studied Trichoderma species, T34 was able to improve WSR resistance in all the studied genotypes suggesting its effectiveness in inducing the resistance and producing a priming response in different wheat genetic backgrounds. The results of this study provided very useful information on the effectiveness of Trichoderma spp. in controlling WSR.

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Genome wide association study for stripe rust resistance in spring bread wheat (Triticum aestivum L.)

Cited by 9 publications

References 40 publications

Genetic architecture of adult-plant resistance to stripe rust in bread wheat (Triticum aestivum L.) association panel

Genetic architecture of adult-plant resistance to stripe rust in bread wheat (Triticum aestivum L.) association panel

Genetic Diversity and Population Structure in Türkiye Bread Wheat Genotypes Revealed by Simple Sequence Repeats (SSR) Markers

Alleviation of Stripe Rust Disease in Wheat Seedlings Using Three Different Species of Trichoderma spp.

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