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The top 5% of all combined SNP of the p-values of the SNPphenotype associations were selected. For each variant, the fifth percentile of the observed p-values was calculated and -log10 transformed. The top 5% of the transformed -log10 p-values was then plotted along the chromosomes. We considered SNPs with minor allele frequency (MAF) < 0.05 to avoid spurious associations due to rare alleles. The horizontal dashed line depicts the threshold for the 0.1% tail of the p-value distribution (0.00134 to 0.00088). SNPs that displayed above-threshold p-values were considered for further analysis. SNPs corresponding to rare alleles (0.05 > MAF > 0.1) are plotted in magenta. The right-most panel shows quantile plots of the expected versus observed p-values for each MAMP variant. Note the different scale of the y-axis of the uppermost panel.
The antiSMASH database [ 4 ] was used to identify all possible secondary metabolites of A. thaliana (a. thaliana draft genome v9.1). The secondary metabolites were filtered using their structural similarity to reported compounds, as described in Fahle et al. [ 5 ]. The remaining compounds were manually checked for the presence of known MAMP epitopes. Compounds were also checked for the presence of biologically relevant functional groups, such as hydroxyl groups, amide groups, or carboxylic acid groups. The following keywords were used to search for compounds: “hydroxy”, “thioether”, “amino”, “amide”, “carbonyl”, and “ester”, while other compounds were manually checked for the presence of known MAMP epitopes.
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A combination of PCR screening, biochemical assays, and genetic approaches, reveals a genetic basis of resistance/susceptibility to fungi, bacteria, and oomycetes in wheat, barley, cotton, and rice. An association study on the basis of resistance/susceptibility in a population of 317 well-characterized cultivars of wheat, barley, and sorghum revealed marker-trait associations for functional resistance/susceptibility to the pathogens Fusarium graminearum, Pseudomonas syringae and Magnaporthe oryzae. A genetic basis for functional resistance/susceptibility to the fungal pathogen F. oxysporum (Fusarium wilt of tomato) was uncovered in a barley diversity panel. Novel MAMP-based markers were developed for both Fusarium wilt resistance/susceptibility markers in barley and for resistance to Stagonospora nodorum (SN), a fungal disease causing overwintering in alfalfa. Several of the associations were confirmed in an independent population of 127 elite cultivars with resistance/susceptibility to both fungal and bacterial diseases. The genetic bases of resistance/susceptibility to the bacterial pathogens bacteria gram-negative Pseudomonas syringae pv. tomato DC3000 (PsHR), Pseudomonas syringae pv. campi (PsHR+), Pseudomonas syringae pv. glycinea (PsHR-), Pseudomonas syringae pv. porri (PsHR-), and Pseudomonas syringae pv. tabaci (PsHR-), and the bacterial gram-positive listeria monocytogenes were also identified in a maize diversity panel. Both the F. oxysporum marker, and the Ps. oryzae marker were confirmed in four elite maize germplasm lines exhibiting Fusarium wilt or preharvest drop of grain. A genetic basis of resistance/susceptibility to Magnaporthe oryzae, an important fungus, causing rice blast disease, was identified in a rice diversity panel, with nine MTI markers. Resistance/susceptibility of rice lines to SN, caused by the fungal pathogen Helminthosporium oryzae, was validated in a core collection of 118 rice genotypes and two linked SSR markers were identified.
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Natural mutations underlying the differences between the two tested pathogen-associated molecular patterns (PAMPs) are identified for the first time in plants and could provide a substantial source of genetic diversity for genetic engineering of new Arabidopsis thaliana varieties. The PROBE based SGI analysis identified a total of 38 SNPs distributed throughout the genome. One hundred seventy-six of the significant SNPs were characterized and several of them were validated in a larger population (n < 0.004). Finally, we conducted a functional validation of these candidate loci. In particular, we showed that 11 different loci were associated with the response to a distinct MAMP, FLG22, but not to the other tested MAMP, EF-TU, underlining that the plant immune system was not responding in exactly the same way to the two bacterial MAMPs. We also compared the distribution of the peak SNPs to that of candidate loci identified within FLS2 and BAK1 genes, which have been previously associated with flg22 and elf18 responses, respectively. The distribution of peak SNPs matched perfectly with that of the candidate loci identified in the FLS2 and BAK1 genes. Moreover, the identification of the SNPs associated with the responses to the two distinct bacterial MAMPs in the same regions where the candidate genes controlling those responses were located raised the possibility that these two PAMPs elicit similar responses in Arabidopsis thaliana. However, our results could not identify any single locus or candidate gene that was associated with SGI for both bacterial MAMPs.
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MAMP PRO 5.0.5.3998 System Requirements

- Windows XP and later, Mac OS X 10.6 and later
- Sun Solaris 8 or later
What’s new in MAMP PRO 5.0.5.3998

- Anchored cloning of E. coli flagellin. An improved version of the cloning method described in “[Anchored cloning of a bacterial flagellin](/research/publication/anchored-cloning-bacterial-flagellin#cloning)”, as well as its application to a set of 42 MAMP variants. Methods and protocols.
- Simple spread of E. coli EF-Tu to carry out allele-specific knock-out of flagellin.
- Specificity of MAMP PRO. Increase in responses of A. thaliana genotypes to different MAMPs, single domain peptides, and single domain peptides along with MAMPs.
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