University of Illinois Urbana-Champaign

Genetic characterization of a dominant susceptible Rpp1 allele and analysis of quantitative resistance to Asian soybean rust

Wei, Wei

Content Files
Appendix A.xlsx
Appendix B.xlsx
WEI-DISSERTATION-2021.pdf

Permalink

https://hdl.handle.net/2142/110838

Description

Title
Genetic characterization of a dominant susceptible Rpp1 allele and analysis of quantitative resistance to Asian soybean rust
Author(s)
Wei, Wei
Issue Date
2021-04-21
Director of Research (if dissertation) or Advisor (if thesis)
Matthew, Hudson
Doctoral Committee Chair(s)
  • Matthew, Hudson
  • Clough, Steven
Committee Member(s)
  • Domier, Leslie
  • Diers, Brian
  • Jamann, Tiffany
Department of Study
Crop Sciences
Discipline
Crop Sciences
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Date of Ingest
2021-09-17T04:04:40Z
Keyword(s)
  • Soybean
  • Asian Soybean Rust
  • Plant disease resistance
  • Plant-microbe interaction
  • Resistance gene
  • Dominant susceptibility
  • GWAS
Abstract
Asian soybean rust (ASR), caused by fungal pathogen Phakopsora pachyrhizi, is a yield-threatening disease in soybean growing countries (Hartman et al. 2012; Godoy et al. 2016). The yield loss can reach as high as 80% if the conditions are conducive, and no control measures are taken (Yorinori et al. 2005; Walker et al. 2011; Hartman, Miles, and Frederick 2007). Soybean natural resistance to P. pachyrhizi has been identified as single R gene-conferred, and seven Rpp (Rpp1-Rpp7; Resistance to Phakopsora pachyrhizi 1-7) gene loci have been identified and mapped (Hartman et al. 2012). Although multiple Rpp genes have been mapped, none have been cloned and validated, and the molecular mechanisms of Rpp gene-mediated resistance remain largely elusive. A genotype was identified that could suppress resistance from Rpp1, resulting in dominant susceptibility (Garcia et al. 2011). The second chapter of this dissertation describes an exploration of a possible molecular mechanism of this dominant susceptible allele of the Rpp1 locus. To achieve that, genomic sequences of the Rpp1 locus were cloned from the dominant susceptible line (DS), as well as two Rpp1-harboring soybean accessions PI561356 and PI594760B, revealing three NBS-LRR genes in each resistance line and one (DS-R) in the DS line. Identification of the DS-R gene was verified through virus-induced gene silencing that led to resistance being partially restored in the susceptible Rpp1/DS-R heterozygous genotypes. The possible involvement of DS-derived small RNA, a potential mechanism for dominant repression of Rpp1 was explored. Rpp1 locus gene expression and small RNA abundances did not support this hypothesis. On the other hand, yeast two-hybrid assays, and more than 6x higher expression of DS-R than Rpp1 candidates, supported the hypothesis that an overly abundant DS-R protein could interact with and presumably disrupt the functional Rpp1 protein, probably leading to dominant susceptibility. In addition to exploring the DS mechanism, new information about the Rpp1 gene that provides resistance to ASR, was also revealed by protein sequence comparison of candidate proteins across different soybean genotypes. The analyses indicate that the R2 gene (homologous to Glyma.18G281600 of Williams 82) within resistant genotypes PI561356, PI594760B and PI200492 showed the highest probability of being the functional Rpp1 gene. The third chapter of this dissertation describes using genome-wide association (GWA) mapping to identify potential loci for soybean quantitative resistance to ASR. The phenotypic data was leaf disease severity scores from approximately 2,000 USDA soybean germplasm accessions in response to a mixture of four P. pachyrhizi isolates (Miles, Frederick, and Hartman 2006). The diverse soybean panel exhibited a wide distribution of disease scores, independent of R genes. Genotypic data was obtained from publicly available soybean 50K SNP arrays. Two different models were used for GWA: Mixed Linear Model (MLM) and FarmCPU. MLM did not identify any significant loci, but FarmCPU identified five significant loci. The five significant loci taken together explained 5% of the phenotypic variation and the model in total explained 13% of the phenotypic variation. Based on this study, the small effects of the significant loci detected suggested the complexity in the genetic basis of quantitative resistance to ASR, and the low heritability suggested that breeding for quantitative resistance to rust might not be practically effective. This data set was also used to look for possible new Rpp qualitative resistance genes by conducting GWA using the qualitative lesion type data of this soybean diversity panel. A logistic regression model was used for the binary phenotypic data. Five significant loci were detected on chromosome 6, chromosome 11 and chromosome 18, including the already mapped Rpp3 and Rpp1 loci. The locus on chromosome 11 and one of the three loci on chromosome 18, were not close to any known locus, so these markers could be associated with novel Rpp genes. Interestingly, among the two independent loci mapped to the Rpp1 locus, one was not in the fine-mapped Rpp1 locus, which suggested it could be a novel Rpp locus next to Rpp1. Additional evidence supporting this hypothesis was that the resistant allele of this proposed novel Rpp locus was not found in any of the previously characterized Rpp1-containing soybean accessions.
Graduation Semester
2021-05
Type of Resource
Thesis
Permalink
http://hdl.handle.net/2142/110838
Copyright and License Information
Copyright 2021 Wei Wei

Owning Collections

Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois
Dissertations and Theses - Crop Sciences