Prediction of candidate genes associated with resistance to soybean rust (<i>Phakopsora pachyrhizi</i>) in line UG‐5

Gebremedhn, Hailay Mehari; Msiska, Ulemu Mercy; Weldekidan, Miesho Belay; Odong, Thomas; Rubaihayo, Patrick; Tukamuhabwa, Phinehas

doi:10.1111/pbr.12847

Cited by 3 publications

(4 citation statements)

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“…Yamanaka et al (2015) and Aoyagi et al (2020) found in the accessions Xiao Jing Huang, Himeshirazu and WC2 single genes for resistance to ASR, which share the same positions as Rpp1, between Sct_187 and Sat_064, and a similar reaction pro le against P. pachyrhizi inoculum. Conversely, Hossain et al (2015), Yamanaka et al (2016), Gebremedhn et al (2018Gebremedhn et al ( , 2020 and Chen et al (2015) identi ed in the genotypes PI 587905, PI 594767A, PI 587855, UG-5 and SX6907 resistance genes in similar location as Rpp1-b, between Sat_372 and Sat_064. Rocha et al (2016) also studied the reaction of PI 594767 A, however using an isolate (PPUFV02) different from the one used by Hossain et al (2015).…”

Section: Introductionmentioning

confidence: 93%

Mapping of a soybean rust resistance in PI 594756 at the Rpp1 locus

Barros

Avelino²,

Silva³

et al. 2023

Mol Breeding

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Asian soybean rust (ASR), caused by the fungus Phakopsora pachyrhizi, is the main disease affecting soybean production in Brazil. The plant introduction PI 594756 is a resistance source that has been employed in breeding for resistance to ASR in this country. This study aimed at investigating the resistance of the PI 594756 to a panel of P. pachyrhizi isolates and mapping its resistance in populations derived from the cross with the susceptible PI 594891. The PI 594756 and resistant varieties were inoculated with seven ASR monosporic isolates. F 2 and F 2:3 populations were tested against ASR in a greenhouse and used to map a resistance gene to a likely genomic location by means of bulked segregant analysis. Bulks were genotyped with In nium BeadChips and the genomic region identi ed was saturated with target GBS (tGBS). PI 594756 presented a unique resistance pro le compared to the differential varieties, being resistant to six isolates and immune to one. The resistance was visually monogenic dominant; however, it was classi ed as incompletely dominant when quantitatively studied. Genetic and QTL mapping placed the PI 594756 gene between chromosome (chr) 18 55, 863,741 and 56,123,516. This position is slightly upstream mapping positionsof Rpp1 (PI 200492) and Rpp1-b (PI 594538A). Finally, we performed a haplotype analysis of a panel composed of Brazilian historical germplasm, sources of Rpp genes and resistant varieties and found SNPs that can successfully differentiated the new allele from PI 594756 from Rpp1 and Rpp1-b sources. The haplotype identi ed can be used as a tool for marker assisted selection.

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Section: Introductionmentioning

confidence: 93%

Mapping of a soybean rust resistance in PI 594756 at the Rpp1 locus

Barros

Avelino²,

Silva³

et al. 2023

Mol Breeding

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Section: Introductionmentioning

confidence: 94%

Mapping of a soybean rust resistance in PI 594756 at the Rpp1 locus

Barros

Avelino

Silva

et al. 2022

Preprint

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Asian soybean rust (ASR), caused by the fungus Phakopsora pachyrhizi, is the main disease affecting soybean production in Brazil. The plant introduction PI 594756 is a resistance source that has been employed in breeding for resistance to ASR in this country. This study aimed at investigating the resistance of the PI 594756 to a panel of P. pachyrhizi isolates and mapping its resistance in populations derived from the cross with the susceptible PI 594891. The PI 594756 and resistant varieties were inoculated with seven ASR monosporic isolates. F2 and F2:3 populations were tested against ASR in a greenhouse and used to map a resistance gene to a likely genomic location by means of bulked segregant analysis. Bulks were genotyped with Infinium BeadChips and the genomic region identified was saturated with target GBS (tGBS). PI 594756 presented a unique resistance profile compared to the differential varieties, being resistant to six isolates and immune to one. The resistance was visually monogenic dominant; however, it was classified as incompletely dominant when quantitatively studied. Genetic and QTL mapping placed the PI 594756 gene between chromosome (chr) 18 55,863,741 and 56,123,516. This position is slightly upstream mapping positionsof Rpp1 (PI 200492) and Rpp1-b (PI 594538A). Finally, we performed a haplotype analysis of a panel composed of Brazilian historical germplasm, sources of Rpp genes and resistant varieties and found SNPs that can successfully differentiated the new allele from PI 594756 from Rpp1 and Rpp1-b sources. The haplotype identified can be used as a tool for marker assisted selection.

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“…Another promising strategy for sustainable and effective SBR resistance is to utilize alternative R gene combinations and dynamic turnover in the field ( Childs et al., 2018a ). However, the identity of these Rpp genes needs to be revealed ( Gebremedhn et al., 2020 ). Under the current conditions, it is also impractical to rely only on several major genes or combinations of these genes to control the SBR disease in field production.…”

Section: Introductionmentioning

confidence: 99%

“…In addition to major genes, many recent molecular studies have revealed more disease-resistant pathways in soybeans ( Childs et al., 2018b ). The resistance usually occurs in the form of signals, transcription factors, NB-LRR, or secondary metabolites ( Gebremedhn et al., 2020 ; Waheed et al., 2021 ). They usually improve not only the resistance to a particular pathogen but the overall resistance of the plant as well.…”

Section: Introductionmentioning

confidence: 99%

A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybean

et al. 2023

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Soybean brown rust (SBR), caused by Phakopsora pachyrhizi, is a devastating fungal disease that threatens global soybean production. This study conducted a genome-wide association study (GWAS) with seven models on a panel of 3,082 soybean accessions to identify the markers associated with SBR resistance by 30,314 high quality single nucleotide polymorphism (SNPs). Then five genomic selection (GS) models, including Ridge regression best linear unbiased predictor (rrBLUP), Genomic best linear unbiased predictor (gBLUP), Bayesian least absolute shrinkage and selection operator (Bayesian LASSO), Random Forest (RF), and Support vector machines (SVM), were used to predict breeding values of SBR resistance using whole genome SNP sets and GWAS-based marker sets. Four SNPs, namely Gm18_57,223,391 (LOD = 2.69), Gm16_29,491,946 (LOD = 3.86), Gm06_45,035,185 (LOD = 4.74), and Gm18_51,994,200 (LOD = 3.60), were located near the reported P. pachyrhizi R genes, Rpp1, Rpp2, Rpp3, and Rpp4, respectively. Other significant SNPs, including Gm02_7,235,181 (LOD = 7.91), Gm02_7234594 (LOD = 7.61), Gm03_38,913,029 (LOD = 6.85), Gm04_46,003,059 (LOD = 6.03), Gm09_1,951,644 (LOD = 10.07), Gm10_39,142,024 (LOD = 7.12), Gm12_28,136,735 (LOD = 7.03), Gm13_16,350,701(LOD = 5.63), Gm14_6,185,611 (LOD = 5.51), and Gm19_44,734,953 (LOD = 6.02), were associated with abundant disease resistance genes, such as Glyma.02G084100, Glyma.03G175300, Glyma.04g189500, Glyma.09G023800, Glyma.12G160400, Glyma.13G064500, Glyma.14g073300, and Glyma.19G190200. The annotations of these genes included but not limited to: LRR class gene, cytochrome 450, cell wall structure, RCC1, NAC, ABC transporter, F-box domain, etc. The GWAS based markers showed more accuracies in genomic prediction than the whole genome SNPs, and Bayesian LASSO model was the ideal model in SBR resistance prediction with 44.5% ~ 60.4% accuracies. This study aids breeders in predicting selection accuracy of complex traits such as disease resistance and can shorten the soybean breeding cycle by the identified markers

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Prediction of candidate genes associated with resistance to soybean rust (Phakopsora pachyrhizi) in line UG‐5

Cited by 3 publications

References 39 publications

Mapping of a soybean rust resistance in PI 594756 at the Rpp1 locus

Mapping of a soybean rust resistance in PI 594756 at the Rpp1 locus

Mapping of a soybean rust resistance in PI 594756 at the Rpp1 locus

A genome-wide association study and genomic prediction for Phakopsora pachyrhizi resistance in soybean

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