RPW8/HR repeats control NLR activation in Arabidopsis thaliana

Abstract

In many plant species, conflicts between divergent elements of the immune system, especially nucleotide-binding oligomerization domain-like receptors (NLR), can lead to hybrid necrosis. Here, we report deleterious allele-specific interactions between an NLR and a non-NLR gene cluster, resulting in not one, but multiple hybrid necrosis cases in Arabidopsis thaliana . The NLR cluster is RESISTANCE TO PERONOSPORA PARASITICA 7 ( RPP7 ), which can confer strain-specific resistance to oomycetes. The non-NLR cluster is RESISTANCE TO POWDERY MILDEW 8 ( RPW8 ) / HOMOLOG OF RPW8 ( HR ), which can confer broad-spectrum resistance to both fungi and oomycetes. RPW8/HR proteins contain at the N-terminus a potential transmembrane domain, followed by a specific coiled-coil (CC) domain that is similar to a domain found in pore-forming toxins MLKL and HET-S from mammals and fungi. C-terminal to the CC domain is a variable number of 21- or 14-amino acid repeats, reminiscent of regulatory 21-amino acid repeats in fungal HET-S. The number of repeats in different RPW8/HR proteins along with the sequence of a short C-terminal tail predicts their ability to activate immunity in combination with specific RPP7 partners. Whether a larger or smaller number of repeats is more dangerous depends on the specific RPW8/HR autoimmune risk variant.

aradeepopsis: From images to phenotypic traits using deep transfer learning

“…Second, we wanted to test whether our pipeline would remain robust when using data generated on different phenotyping platforms, with different image recording systems, pot sizes and shapes, and background composition. We used images from three published studies [20][21][22], which were generated on the RAPA platform [23], and re-analyzed them using araDEEPopsis. Correlation analysis of published rosette area and our own measurements resulted in R 2 values of 0.996 [21] and 0.979 [20], respectively ( Fig 5).…”

“…We used images from three published studies [20][21][22], which were generated on the RAPA platform [23], and re-analyzed them using araDEEPopsis. Correlation analysis of published rosette area and our own measurements resulted in R 2 values of 0.996 [21] and 0.979 [20], respectively ( Fig 5). Despite this overall very strong correlation, we noticed individual images in which our segmentation disagreed with the published one.…”

“…Second, we wanted to test whether our pipeline would remain robust when using data generated on different phenotyping platforms, with different image recording systems, pot sizes and shapes, and background composition. We used images from three published studies [20][21][22], generated on either the RAPA platform [23] at the Max Planck Institute for Developmental Biology in Tübingen, Germany [20,21], or the WIWAM platform (https://www.psb.ugent.be/phenotyping/pippa) at the VIB in Ghent, Belgium [22,24], and re-analyzed them using ᴀʀᴀᴅᴇᴇᴘᴏᴘsɪs. Correlation analysis of the published rosette area derived from the RAPA system and our own measurements resulted in R 2 values of 0.996 [21] and 0.979 [20], respectively (Fig 5A,B).…”

“…Unfortunately, original segmentations were not available for these images, but when inspecting some of the outliers, we again noticed highly accurate segmentation by ᴀʀᴀᴅᴇᴇᴘᴏᴘsɪs relative to the actual image ( Fig S1). [20] with the same order as in (A).…”

“…Panel four shows the original segmentation, panel five the segmentation by araDEEPopsis. (B) Validation against[20] with the same order as in (A).…”