Salt survival assay of the F2 and F3 progenies of control and salt-treated regenerated plants from leaf and root.

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Salt survival assay of the F2 and F3 progenies of control and salt-treated regenerated plants from leaf and root. The survival rates were analyzed after 14 days on MS media with 150 mM NaCl by scoring plants with green cotyledons. Each line contains 50 seeds per plate with 6 technical replicates and five lines per plant type were used in this experiment. The survival rates (%) were normalized by dividing with the survival rates in MS media without salt to eliminate the deviation from germination rates. 75LOF2/F3, leaf-origin progenies regenerated from salt-treated plants in F2/F3 generation, 75ROF2/F3, root-origin progenies regenerated from salt-treated plants in F2/F3 generation, CLOF2/F3, leaf-origin progenies regenerate from control plants in F2/F3 generation, CROF2/F3, root-origin progenies from control plants in F2/F3 generation. 

Commend in R PROGRAMM 

library(ggplot2)

library(ggpubr)

library(tidyverse)

 

X15_10_18_result_salt_tolerance

raw_data_salt_survivor <- X15_10_18_result_salt_tolerance

raw_data_salt_survivor

raw_data_salt_survivor$Media

 

####### Manipulate data frame

raw_data_salt_survivor

raw_data_salt_survivor <- rename(raw_data_salt_survivor, replicate = '# Replicate')

raw_data_salt_survivor <- rename(raw_data_salt_survivor, percentage = '% Survivors')

raw_data_salt_survivor <- rename(raw_data_salt_survivor, line = Line, generation = Generation, media = Media)

raw_data_salt_survivor

raw_data_salt_survivor_selected <- select(raw_data_salt_survivor, line, replicate, generation, media, percentage)

raw_data_salt_survivor_selected

 

###### Seperating by media

normal_MS <- filter(raw_data_salt_survivor_selected, media == "N")

normal_MS

salt_MS <- filter(raw_data_salt_survivor_selected, media == "S")

salt_MS

normal_MS$line == salt_MS$line # check the accuracy of the line

# All TRUE

normalised_survivor <- mutate(salt_MS, normalised = (salt_MS$percentage*100)/normal_MS$percentage)

normalised_survivor

survivor_graph <- ggplot(data = normalised_survivor) +

  geom_boxplot(aes(x = line, y = normalised, fill = sub("_\\d", "", line))) +

  geom_hline(yintercept = 50, color = "red") +

  facet_grid(generation~.) +

  theme_classic()

survivor_graph

pdf("survival_figure_not_collapsed.pdf", height = 5,width = 7 )

survivor_graph

dev.off()

 

##### Making the survival_percentage in normal media

normal_MS

normal_MS_graph <- ggplot(data = normal_MS) +

  geom_boxplot(aes(x = line, y = percentage, fill = sub("_\\d", "", line))) +

  geom_hline(yintercept = 80, color = "red") +

  facet_grid(generation~.) +

  theme_classic()

normal_MS_graph

pdf("normal_MS_survivors.pdf", height = 5,width = 7 )

normal_MS_graph

dev.off()

 

# TRY geom_boxplot

ggplot(data = normal_MS) +

  geom_boxplot(aes(x = line, y = percentage)) + # without 'fill = ' it still combine 'each line' together

  geom_hline(yintercept = 80, color = "red") +

  facet_grid(generation~.) +

  theme_classic()

 

# aes(x=line) combines CROF2_1 from all replicates together

salt_MS_graph <- ggplot(data = salt_MS) +

  geom_boxplot(aes(x = line, y = percentage, fill = sub("_\\d", "", line))) + # without 'fill = ' it still combine 'each line' together

  geom_hline(yintercept = 50, color = "red") +

  facet_grid(generation~.) +

  theme_classic()

pdf("salt_MS_survivors.pdf", height = 5,width = 7 )

salt_MS_graph

dev.off()

 

DATA 

line    generation  replicate   survivors   total   percentage

Col_0   F2  1   48  49  97.96

Col_0   F2  2   50  51  98.04

Col_0   F2  3   49  50  98.00

Col_0_1 F2  1   47  50  94.00

Col_0_1 F2  2   47  50  94.00

Col_0_1 F2  3   49  50  98.00

CROF2_1 F2  1   44  50  88.00

CROF2_1 F2  2   44  50  88.00

CROF2_1 F2  3   39  50  78.00

CROF2_1 F2  4   NA  NA  NA

CROF2_2 F2  1   45  50  90.00

CROF2_2 F2  2   39  50  78.00

CROF2_2 F2  3   43  50  86.00

 

Attachments:

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