Invasion

• Validation of Invasion
  • Conclusion
• Material and Methods
  • Simulations
  • Visualization

Validation of Invasion

A TE with a transposition rate u will show an exponential increase in copy numbers according to the equation:

ct=c0*(1+u)^t
ct TE copys at generation t
c0 TE copys at generation 0
u transposition rate
t generations

We tested if a simulated invasion reproduces this expectations.
We used a transposition rate of u=0.1 a population size of N=1000, a starting number of TEs of c0=10 and simulated the invasion for 100 generations.
A chromosome of size 1Mb and no piRNA clusters were simulated. We used 500 replicates.

Which yields the following results:

• bold line: expectations based on the equation shown above
• grey lines: observed invasions for 500 replicates

Conclusion

Invade accurately reproduces the expected exponential increase of TE copy numbers in a population (no piRNA clusters).

Material and Methods

Simulations

java -jar invade.jar cluster --min-w 0.1 --genome mb:1 --rr cm_mb:4 --u 0.1 --N 1000 --gen 100 --basepop seg:10 --rep 500 --silent --steps 1 --cluster-insertions 1 --simid "1"  > test-s10.txt 

Visualization

We visualized the observed and the expected invasion with the following R-code

library(ggplot2)
library(RColorBrewer)
library(plyr)
library(gridExtra)
theme_set(theme_bw())

cn<-seq(0,99,1)
res<-10*1.1^cn
theo<-data.frame(x=1:100,y=res)
t<-read.table("test-s10.txt")
names(t)<-c("rep","gen","c1","c2","c3","tes")
t$rep<-as.factor(t$rep)

gl<-ggplot()+geom_line(data=t,aes(x=gen,group=rep,y=tes*1000),alpha=0.15,size=0.3)+scale_y_log10()+geom_line(data=theo,aes(x=x,y=y),size=2)+theme(legend.position="none")+ylab("TE copies in population")+xlab("generation")
plot(gl)