DOI: 10.5061/dryad.r4xgxd2p6
title: Data from: Leaf abaxial and adaxial surfaces differentially affect the interaction of Botrytis cinerea across several eudicots

description: Eudicot plant species have leaves with two surfaces: the lower abaxial and
 the upper adaxial surface. Each surface varies in a diversity of
 components and molecular signals, resulting in potentially different
 degrees of resistance to pathogens. We tested how Botrytis cinerea, a
 necrotroph fungal pathogen, interacts with the two different leaf surfaces
 across 16 crop species and 20 Arabidopsis genotypes. This showed that the
 abaxial surface is generally more susceptible to the pathogen than the
 adaxial surface. In Arabidopsis, the differential lesion area between leaf
 surfaces was associated with jasmonic acid (JA) and salicylic acid (SA)
 signaling and differential induction of defense chemistry across the two
 surfaces. When infecting the adaxial surface, leaves mounted stronger
 defenses by producing more glucosinolates and camalexin defense compounds,
 partially explaining the differential susceptibility across surfaces.
 Testing a collection of 96 B. cinerea strains showed genetic heterogeneity
 of growth patterns, with a few strains preferring the adaxial surface
 while most are more virulent on the abaxial surface. Overall, we show that
 leaf-Botrytis interactions are complex with host-specific,
 surface-specific, and strain-specific patterns.
description: To assess how developmental patterns between leaf surfaces
 influence Botrytis interactions, we first tested 16 species from eight
 different plant families with diverse natural histories. These eight
 families are sampled from the caryophyllales in the basal core eudicots to
 asterids and rosids. As physical and chemical defenses and also defense
 signaling were shaped by the environment, herbivore, and pathogen
 pressures across the evolutionary timescale, those species constitute a
 sampling of defensive strategies existing in the eudicots while focusing
 on crops of economical value. To test how the effect of the leaf surfaces
 varies across genotypes within a host species, we infected 20 <em>A.
 thaliana</em> genotypes. Those genotypes included SA and JA
 signaling mutants that control over the chemical defense variation in
 addition to TFs and enzymes along the pathways. Finally, to assess how the
 diversity in the pathogen interacts with developmental patterns between
 leaf surfaces, we infected 96 Botrytis strains on a single host genotype.
 This provided an analysis of how abaxial/adaxial leaf surface variation
 influences the host-Botrytis interaction across diverse host species, host
 genotypes, and pathogen genotypes providing an initial investigation into
 the conditionality of this phenomena.
description: # Leaf abaxial and adaxial surfaces differentially affect the interaction
 of Botrytis cinerea across several eudicots
 [https://doi.org/10.5061/dryad.r4xgxd2p6](https://doi.org/10.5061/dryad.r4xgxd2p6) ## Description of the data and file structure Check the **Rnotebook_surface** to find more information on the files and R codes. This notebook aims to compile and annotate the R scripts used for the analysis of the Leaf surface-Botrytis dataset. This notebook charges R scripts that contain all the code. The main result figures are plotted directly in the notebook. ## Experimental design: Sixteen Eudicot species and 20 A.thaliana genotypes were analyzed. Detached leaves were inoculated with Botrytis in ‘experimental trays’, that constitutes a micro-environment for a randomized collection of isolates. After 72h, pictures of all trays were taken. Image analysis for calculation of lesion area (and many other parameters) was conducted in R. For image analysis R codes, see the **Image_analysis_pipeline_Final R notebook**. ### **General name usage:** **Genotype** = plant genotype **Species** = different eudicot plant species **Isolate or Iso** = Botrytis strains **Surface:** U = Up= leaf adaxial surface D = Down = leaf  Abaxial surface **Treatment:** treatment = infection with Botrytis. Control = uninfected leaves. **Image / experimental tray** = tray with phytoagar in which the infected detached leaves where pictured to measure the lesion area **Plant tray** = tray in the growth chamber in which each individual plant was located ## 1. Testing the leaf surface effect across 16 eudicot species ### Associated files: #### **Eudi16\_72h\_all1.txt** Raw data Columns M:FE units = pixels [See Fordyce et al 2018  [www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851](http://www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851)] Column FG: Units = cm2 Column FH: units = mm2 **Eudicot16_UD_clean.txt** Data after removal of failed lesions Columns M:FE units = pixels [See Fordyce et al 2018  [www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851](http://www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851)] Column FG: Units = cm2 Columns FH-FM: units = mm2 Columns FN:FS: Parameters for the removal of failed lesions #### **Stomata\_forPlot.txt** Average count of stomata on the abaxial and adaxial surfaces [stomata/mm2]. #### **Eudicot\_Stomata\_counts\_col.txt** Raw data : Count of stomata on the abaxial and adaxial surfaces [stomata/mm2]. ### R Code: #### **Eudi\_UD\_analysis\_final.R** ## 2. Testing the leaf surface effect within Arabidopsis thaliana ### Associated files: #### **G24I10\_72H.txt** Columns K-FC units = pixels [See Fordyce et al 2018  [www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851](http://www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851)] #### **G24I10\_96h.txt** Columns F-EX units = pixels [See Fordyce et al 2018  [www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851](http://www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851)] #### **G24I10\_UD\_48h.txt** Columns F-EX units = pixels [See Fordyce et al 2018  [www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851](http://www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851)] #### **Genotype\_Emmeans\_Cat** Least-square (emmeans) corrected means, standard error (SE), degree of freedom (DF), lower and upper confidence levels (CL).  #### **Data\_Plot\_Lesion\_GT.txt** Mean lesion area in mm2 ### R Code: #### **Ara20\_72h\_all.R** ## 3. Testing the effect of leaf surface on glucosinolate and camalexin content ### Associated files: #### **GSL\_Leaf\_Data1.txt** Columns P-AU: HPLC peak area data. Columns starting with: X are raw data peak area; Q are data normalized by absorbance coefficient; QL are data normalized both to absorbance and leaf area. Columns BD-BT: units = pixels [See Fordyce et al 2018  [www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851](http://www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851)] Columns Bu-CA: Units = cm2 #### **Cam\_Leaf\_Data1.txt** Columns Q-S : raw data Columns AB-AR: units = pixels [See Fordyce et al 2018  [www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851](http://www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851)] Columns AS-AW: Units = cm2 Column AX-BB: Normalized data #### **Chemotype\_LM\_model\_pie.txt** Results from linear modeling. Df= degree of freedom, SumSq= sum of squares, Perc=Percentatage of variance calculated from the sum of squares, MeanSQ = mean of squares. Pr(F) = p-value.  ### R Code: #### **Glucosinolates\_Camalexin.R** ## 4. Testing how the diverse Botrytis strains interact with the leaf surfaces ### Associated files: #### **Lesion\_C0l0\_48h.txt** columns J: FB: units = pixels [See Fordyce et al 2018  [www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851](http://www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851)] #### **Col0\_UpDown72h.txt** columns K-FC: units = pixels [See Fordyce et al 2018  [www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851](http://www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851)] #### **UpDown\_Exp1\_Results96.txt** columns I-FA: units = pixels [See Fordyce et al 2018  [www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851](http://www.plantphysiol.org/cgi/doi/10.1104/pp.18.00851)] ### R Code: #### **Bcin96.R** #### **geom\_split\_violin** # 5. Supplemental Material #### **Supplemental\_material.pdf**  Supplemental figures * `Table S1`: Information on the 16 eudicot species used to test how the leaf surfaces influence host-Botrytis interactions across species. In addition to the information on the seeds’ origin, the average leaf thickness, stomata density and lesion area on each leaf surface are provided. * `Table S2`: Information on the 20 *A. thaliana genotypes used to test how leaf surfaces change the interaction with Botrytis within a species. Mutants are deficient in SA and JA defense signaling, aliphatic and indolic glucosinolates, putative cyanogenic glycosides, and camalexin biosynthesis. * `Table S3`: Information on the 96 *B.cinerea* strains used in this study. For each strain the geographical origin, the host it was isolated from (not equal to host specialization or pathovars) are provided. Values for general virulence and host specificity (Caseys et al. 2021) and camalexin sensitivity (Zhang et al. 2017) were used to subset the 10 strains associated to the Eudicot and Arabidopsis experiments. Which strain was used in which experiment (Eudicots, Arabidopsis, and/or Botrytis96) is also provided. ### Files and variables #### File: Github\_Surface.zip **Description:** All input files and R codes for all 4 datasets and analyses ## Code/software R stat  Warning: This was coded for and functional with R version: R version 3.6.0 (2019-04-26) -- "Planting of a Tree" Platform: x86_64-apple-darwin15.6.0 (64-bit)