Proportional odds model applied to mapping of disease resistance genes in plants

Molecular markers have been used extensively to map quantitative trait loci (QTL) controlling disease resistance in plants. Mapping is usually done by establishing a statistical association between molecular marker genotypes and quantitative variations in disease resistance. However, most statistical approaches require a continuous distribution of the response variable, a requirement not always met since evaluation of disease resistance is often done using visual ratings based on an ordinal scale of disease severity. This paper discusses the application of the proportional odds model to the mapping of disease resistance genes in plants amenable to expression as ordinal data. The model was used to map two resistance QTL of maize to Puccinia sorghi. The microsatellite markers bngl166 and bngl669, located on chromosomes 2 and 8, respectively, were used to genotype F2 individuals from a segregating population. Genotypes at each marker locus were then compared by assessing disease severity in F3 plants derived from the selfing of each genotyped F2 plant based on an ordinal scale severity. The residual deviance and the chi-square score statistic indicated a good fit of the model to the data and the odds had a constant proportionality at each threshold. Single-marker analyses detected significant differences among marker genotypes at both marker loci, indicating that these markers were linked to disease resistance QTL. The inclusion of the interaction term after single-marker analysis provided strong evidence of an epistatic interaction between the two QTL. These results indicate that the proportional odds model can be used as an alternative to traditional methods in cases where the response variable consists of an ordinal scale, thus eliminating the problems of heterocedasticity, non-linearity, and the non-normality of residuals often associated with this type of data.

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The Arabidopsis RPS4 bacterial-resistance gene is a member of the TIR-NBS-LRR family of disease-resistance genes

The Plant Journal ◽

10.1046/j.1365-313x.1999.t01-1-00600.x ◽

1999 ◽

Vol 20 (3) ◽

pp. 265-277 ◽

Cited By ~ 224

Author(s):

Walter Gassmann ◽

Matthew E. Hinsch ◽

Brian J. Staskawicz

Keyword(s):

Disease Resistance ◽

Resistance Gene ◽

Resistance Genes ◽

Bacterial Resistance ◽

Disease Resistance Genes

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Genome-Wide Analysis of NBS-Encoding Disease Resistance Genes in Maize Inbred Line B73

ACTA AGRONOMICA SINICA ◽

10.3724/sp.j.1006.2009.00566 ◽

2009 ◽

Vol 35 (3) ◽

pp. 566-570 ◽

Cited By ~ 1

Author(s):

Jie-Ming WANG ◽

Hai-Yang JIANG ◽

Yang ZHAO ◽

Yan XIANG ◽

Su-Wen ZHU ◽

...

Keyword(s):

Disease Resistance ◽

Inbred Line ◽

Resistance Genes ◽

Disease Resistance Genes ◽

Maize Inbred Line ◽

Genome Wide Analysis ◽

Genome Wide

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Comparative Mapping of Three Bacterial, Three Fungal, and One Virus Disease-resistance Genes in Common Bean

HortScience ◽

10.21273/hortsci.33.3.547a ◽

1998 ◽

Vol 33 (3) ◽

pp. 547a-547

Author(s):

Geunhwa Jung ◽

James Nienhuis ◽

Dermot P. Coyne ◽

H.M. Ariyarathne

Keyword(s):

Disease Resistance ◽

Common Bean ◽

Pseudomonas Syringae ◽

Resistance Genes ◽

Fungal Pathogens ◽

Xanthomonas Campestris ◽

Virus Disease ◽

Disease Resistance Genes ◽

Brown Spot ◽

Viral Pathogen

Common bacterial blight (CBB), bacterial brown spot (BBS), and halo blight (HB), incited by the bacterial pathogens Xanthomonas campestris pv. phaseoli (Smith) Dye, Pseodomonas syringae pv. syringa, and Pseudomonas syringae pv. phaseolicola, respectively are important diseases of common bean. In addition three fungal pathogens, web blight (WB) Thanatephorus cucumeris, rust Uromyces appendiculatus, and white mold (WM) Sclerotinia sclerotiorum, are also destructive diseases attacking common bean. Bean common mosaic virus is also one of most major virus disease. Resistance genes (QTLs and major genes) to three bacterial (CBB, BBS, and HB), three fungal (WB, rust, and WM), and one viral pathogen (BCMV) were previously mapped in two common bean populations (BAC 6 × HT 7719 and Belneb RR-1 × A55). The objective of this research was to use an integrated RAPD map of the two populations to compare the positions and effect of resistance QTL in common bean. Results indicate that two chromosomal regions associated with QTL for CBB resistance mapped in both populations. The same chromosomal regions associated with QTL for disease resistance to different pathogens or same pathogens were detected in the integrated population.

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Identification of Three Putative Signal Transduction Genes Involved in R Gene-Specified Disease Resistance in Arabidopsis

Genetics ◽

10.1093/genetics/152.1.401 ◽

1999 ◽

Vol 152 (1) ◽

pp. 401-412 ◽

Cited By ~ 1

Author(s):

Randall F Warren ◽

Peter M Merritt ◽

Eric Holub ◽

Roger W Innes

Keyword(s):

Disease Resistance ◽

Pseudomonas Syringae ◽

Resistance Genes ◽

Virulent Strain ◽

Disease Resistance Genes ◽

Avirulence Gene ◽

Detectable Effect ◽

Disease Resistance Gene ◽

Protein Functions ◽

Signal Transduction Genes

Abstract The RPS5 disease resistance gene of Arabidopsis mediates recognition of Pseudomonas syringae strains that possess the avirulence gene avrPphB. By screening for loss of RPS5-specified resistance, we identified five pbs (avrPphB susceptible) mutants that represent three different genes. Mutations in PBS1 completely blocked RPS5-mediated resistance, but had little to no effect on resistance specified by other disease resistance genes, suggesting that PBS1 facilitates recognition of the avrPphB protein. The pbs2 mutation dramatically reduced resistance mediated by the RPS5 and RPM1 resistance genes, but had no detectable effect on resistance mediated by RPS4 and had an intermediate effect on RPS2-mediated resistance. The pbs2 mutation also had varying effects on resistance mediated by seven different RPP (recognition of Peronospora parasitica) genes. These data indicate that the PBS2 protein functions in a pathway that is important only to a subset of disease-resistance genes. The pbs3 mutation partially suppressed all four P. syringae-resistance genes (RPS5, RPM1, RPS2, and RPS4), and it had weak-to-intermediate effects on the RPP genes. In addition, the pbs3 mutant allowed higher bacterial growth in response to a virulent strain of P. syringae, indicating that the PBS3 gene product functions in a pathway involved in restricting the spread of both virulent and avirulent pathogens. The pbs mutations are recessive and have been mapped to chromosomes I (pbs2) and V (pbs1 and pbs3).

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Organization, Expression and Evolution of a Disease Resistance Gene Cluster in Soybean

Genetics ◽

10.1093/genetics/162.4.1961 ◽

2002 ◽

Vol 162 (4) ◽

pp. 1961-1977

Author(s):

Michelle A Graham ◽

Laura Fredrick Marek ◽

Randy C Shoemaker

Keyword(s):

Disease Resistance ◽

Resistance Gene ◽

Resistance Genes ◽

Developmental Stages ◽

Gene Evolution ◽

Pcr Amplification ◽

Disease Resistance Genes ◽

Disease Resistance Gene ◽

R Genes ◽

Specific Primers

Abstract PCR amplification was previously used to identify a cluster of resistance gene analogues (RGAs) on soybean linkage group J. Resistance to powdery mildew (Rmd-c), Phytophthora stem and root rot (Rps2), and an ineffective nodulation gene (Rj2) map within this cluster. BAC fingerprinting and RGA-specific primers were used to develop a contig of BAC clones spanning this region in cultivar “Williams 82” [rps2, Rmd (adult onset), rj2]. Two cDNAs with homology to the TIR/NBD/LRR family of R-genes have also been mapped to opposite ends of a BAC in the contig Gm_Isb001_091F11 (BAC 91F11). Sequence analyses of BAC 91F11 identified 16 different resistance-like gene (RLG) sequences with homology to the TIR/NBD/LRR family of disease resistance genes. Four of these RLGs represent two potentially novel classes of disease resistance genes: TIR/NBD domains fused inframe to a putative defense-related protein (NtPRp27-like) and TIR domains fused inframe to soybean calmodulin Ca2+-binding domains. RT-PCR analyses using gene-specific primers allowed us to monitor the expression of individual genes in different tissues and developmental stages. Three genes appeared to be constitutively expressed, while three were differentially expressed. Analyses of the R-genes within this BAC suggest that R-gene evolution in soybean is a complex and dynamic process.

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