/methyl_farnesoate_reproduction

Effects of methyl farnesoate on male production in Daphnia pulex clones

Primary LanguageR

Effect of Methyl Farnesoate on Male Production in European Daphnia pulex Clones

Background

Daphnia pulex are freshwater crustaceans that are able to control their reproductive strategies in response to environmental cues. Under certain conditions, such as changes in population density or availability of resources, D. pulex can switch from asexual to sexual reproduction. The presence of methyl farnesoate, a hormone analog of juvenile growth hormone, has been observed to influence this reproductive switch, potentially increasing the production of male offspring. Understanding the effect of methyl farnesoate on male production can provide insights into the reproductive ecology and environmental adaptability of D. pulex.

  • Experiment completed by Caroline Roda (car9sw@virginia.edu) and Connor S. Murray (csm6hg@virginia.edu) in Fall 2022.

  • This repository contains the R code and data for analyzing the effect of methyl farnesoate on male production in Daphnia pulex clones.

R Code to Plot Male Production in Daphnia pulex Clones

```r
# Calcualte the effect size and analyze methyl farnesoate exposure experiment
# Connor Murray
# 6.3.2024

# Libraries
library(data.table)
library(tidyverse)
library(patchwork)

# Working directory
setwd("C:/Users/Conno/Desktop/UndergradProjects_2022/Methyl_farn/Data/")

# Load data file
dt <- data.table(fread("Daphnia_Research_Aim1.csv") %>% 
        mutate(sc=case_when(Clone=="D8179" ~ "A",
                            Clone=="D8222" ~ "C",
                            Clone %like% "H" ~ "Hybrids")))

# Pooled Standard deviation
pooled_sd <- dt %>% 
  summarize(sd=sd(Prop_Male, na.rm = T))

# Cohen's D: effect Sizes
coh <- dt %>% 
  group_by(Treatment, Clone) %>% 
  summarize(mean=sum(Male_neonates, na.rm=T)/sum(Total_neonates, na.rm=T)) %>% 
  pivot_wider(names_from = c(Treatment), values_from=c(mean)) %>% 
  group_by(Clone) %>% 
  summarize(eff=((MF-C)/pooled_sd$sd))

# Average Effect size across all clones
mean(coh$eff, na.rm=T)

lower_ci <- function(mean, se, n, conf_level = 0.95){
  lower_ci <- mean - qt(1 - ((1 - conf_level) / 2), n - 1) * se
}
upper_ci <- function(mean, se, n, conf_level = 0.95){
  upper_ci <- mean + qt(1 - ((1 - conf_level) / 2), n - 1) * se
}

# Plot results - avg diff bet trmts
out1 <- {dt[Total_neonates>0] %>%
    mutate(male=Male_neonates/Total_neonates) %>% 
    group_by(Treatment, Clone, sc) %>% 
    summarise(male_tot = mean(male, na.rm = TRUE),
              ssd = sd(male, na.rm = TRUE),
              n = n()) %>%
    mutate(se = ssd / sqrt(n),
           lci.male = lower_ci(male_tot, se, n),
           uci.male = upper_ci(male_tot, se, n)) %>% 
  ggplot(.,aes(x=as.factor(Treatment), 
             ymin=lci.male, 
             ymax=uci.male,
             y=male_tot,
             color=sc)) +
  geom_pointrange(position = position_jitterdodge(dodge.width = 0.2, jitter.width = 0.5),
                  size=2) +
  theme_bw() +
  labs(x = "Treatment", 
       color = "Clone",
       fill = "Clone",
       y = "Proportion of Males") +
  scale_color_manual(values = c("C"="Purple", "A"="Blue", "Hybrids"="orange")) +
  #scale_fill_manual(values = c("C"="Purple", "MF"="steelblue4")) +
  theme(strip.text = element_text(face="bold.italic", size=12),
        legend.text = element_text(size=16),
        legend.title = element_text(face="bold", size=18),
        axis.text.x = element_text(face="bold", size=18),
        axis.text.y = element_text(face="bold", size=18),
        axis.title.x = element_text(face="bold", size=18),
        axis.title.y = element_text(face="bold", size=18),
        axis.title = element_text(face="bold", size=20))}

png(filename = "../Data/mf_exposure_mean_CI.png")
out1
dev.off()
```

alt

```
# Plot - avg male prod over time
out2 <- {dt[Total_neonates>0] %>% 
    pivot_longer(cols = c(Prop_Male, Prop_Female, 
                          Male_neonates, Female_neonates)) %>% 
    ggplot(.,aes(x=value, 
                 fill=Treatment)) +
    facet_wrap(~name, nrow = 2, scales = "free_x") +
    geom_histogram(color="black", size=1) +
    theme_bw() +
    labs(x = "Number or Prop.",
         fill = "Treatment",
         y = "Number of Clutches") +
    scale_fill_manual(values = c("C"="lightgreen", "MF"="steelblue4")) +
    theme(strip.text = element_text(face="bold", size=20),
          legend.text = element_text(face="bold", size=20),
          legend.title = element_text(face="bold", size=20),
          axis.text.x = element_text(face="bold", size=18),
          axis.text.y = element_text(face="bold", size=18),
          axis.title.x = element_text(face="bold", size=18),
          axis.title.y = element_text(face="bold", size=18),
          axis.title = element_text(face="bold", size=20))}

pdf(file = "../Data/mf_exposure_tot.pdf")
out2
dev.off()
```

alt