Window-based population genetic analysis
To understand genetic differentiation in monarchs, we calculated various
population genetic statistics using Vcftools v. 0.1.15
(Danecek et al. , 2011) for
individual populations and for pairwise population comparisons. To
reduce the number of false positives, we only considered SNPs that were
covered in all individuals in the population for the population-based
statistics and SNPs that were covered in all individuals in both
populations in pairwise comparison statistics. Nucleotide diversity
(θπ ) and Tajima’s D (Td )
were calculated in windows of 10,000 base pairs (10kb) across the genome
using Vcftools v. 0.1.15 (Danecek et
al. , 2011). Western monarchs were down-sampled to match the number of
eastern samples (8 males and 6 females) to calculate Tajima’s D
(Td ) and allele frequencies using Vcftools v.
0.1.15 (Danecek et al. , 2011). We
calculated genetic differentiation (FST ) for each
site using Vcftools v. 0.1.15 (Daneceket al. , 2011) and averaged across the genome in windows of 10kb.
To ensure that our conclusions were not driven by genomic window size,
we also calculated genetic differentiation (FST )
for different window sizes (100 bp, 500 bp and 5,000 bp) to verify our
findings. Absolute divergence (DXY ) was
calculated in windows of 10kb across the genome using the allele
frequencies. Windows with less than 10% of total sites covered were
filtered out to eliminate extremely high values. Fixed, shared and
private polymorphisms were calculated between eastern and western
monarchs using the allele frequencies. FST values
were Z-transformed (FSTZ =
(Window FST / Genome AverageFST ) / Standard deviation of Genome wideFST ) to obtain the relative genetic
differentiation in the windows to the genomic mean to identify outlier
windows. The top 1% of theFSTZ values were selected as
the genetic differentiation outliers and the bottom 1% Tajima’s D
values were selected as Tajima’s D outliers.