Data processing and analyses for the manuscript:
De Jong M, Jansen van Rensburg A, Bridle J (20xx) Few genes of large effect underpin specialisation on host plant in the Brown Argus butterfly in the UK.
##UPDATE##
Since we received the Sanger genome before submitting this work, I have re-analysed these data using the new variants called after mapping to the latest genome available NCBI (www.ncbi.nlm.nih.gov) under accession number GCA_905147365.1
See the latest variant filtering here
Note that 14 individuals were removed after assessing relatedness.
Aims:
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Population structure
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Genome scan for loci associated with change host plant species.
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Determine whether these outliers are linked with traits in female host plant choice experiment
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Determine the colonisation history of these populations.
Sample locations, site colonisation history, and dominant host plant data were provided by Maaike. See Brown_Argus_ddRAD_samples.xlsx for info sent June 2018.
Draw map of locations in R.
pwd /Users/alexjvr/2018.postdoc/BrownArgus_2018/BrownArgusDataMap
##R
library(sp) # classes for spatial data
library(raster) # grids, rasters
library(rasterVis) # raster visualisation
library(maptools)
library(rgeos)
##get UK map
require(spatial.tools)
elevation<-getData("alt", country = "GB")
x <- terrain(elevation, opt = c("slope", "aspect"), unit = "degrees")
plot(x)
slope <- terrain(elevation, opt = "slope")
aspect <- terrain(elevation, opt = "aspect")
hill <- hillShade(slope, aspect, 40, 270)
plot(hill, col = grey(0:100/100), legend = FALSE, main = "UK")
#plot(elevation, col = rainbow(25, alpha = 0.35), add = TRUE)
##BA data points
BA.SiteInfo <- read.table("BA_SiteInfo", header=T) ##read table of info into R
UK.coords <- BA.SiteInfo ##change name of file so that it can be manipulated
coordinates(UK.coords) <- c("Long", "Lat") # set spatial coordinates. Remember to check that these make sense
#plot(CH_coords)
#plot(CH_coords, pch = 20, cex = 1, col = "black")
crs.geo <- CRS("+proj=longlat +ellps=WGS84 +datum=WGS84") # geographical, datum WGS84
proj4string(UK.coords) <- crs.geo # define projection system of our data
summary(UK.coords)
##add columns for colour (host plant) and shape (new vs old sites).
UK.coords$pch <- c(17, 15, 17,15, 15, 15, 17, 15, 17)
UK.coords$Colours <- c("gold1", "gold1", "darkorchid3", "gold1", "darkorchid3", "gold1", "darkorchid3", "gold1", "darkorchid3")
##plot map
pdf("BA.sampleMap_20180619.pdf")
plot(hill, col = grey(0:100/100), legend = FALSE, main = "UK")
plot(UK.coords, pch=UK.coords$pch, cex=2, col=UK.coords$Colours, add=T)
dev.off()
Processing of raw Illumina data to a variant file.
Filtering of SNPs for 1) population genetic analyses, and 2) outlier/Environmental association analyses.
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Estimates of genetic diversity
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Genetic distance between populations (Fst)
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Estimate of Isolation by distance
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PCA
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fineRADstructure
How did A.agestis colonise the UK?
- fastSimCoal analyses
Have population at the range margin become specialised? What are the main drivers of genetic divergence here?
- Redundancy and partial Redundancy analyses
Has A.agestis specialised on new host plant at range margins?
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Environmental Association Analysis
Identify outliers