Figure
1 :
a) Sampling locations of Embothrium coccineum . Circles,
triangles and diamonds represent samples from the northern, center and
southern part of the species distribution, respectively.Embothrium coccineum distribution area is highlighted in light
grey and hatched lines represent ice limits from UMG. b)Principal component analysis (PCA) based on a 2,155 SNPs data
set of Embothrium coccineum samples. Symbols and colors used for
each locality are as in Figure 1a.
Figure 2: Structure analyses, for K = 2 (a) and K = 4 (b) of 38Embothrium coccineum individuals based on a 2.155 SNPs data set .
Each individual is displayed from north to south represented by a
vertical bar. Sampling location codes are as in Supplementary table 1.
Color corresponds to genetic group and proportion of the genome assigned
to each genetic group is given along the Y-axis.
Figure3:
NJ tree reconstructed based on Nei´s distance between Embothrium
coccineum individuals. NJ reconstruction based on (a) the PG_dataset
of 2.155 SNPs, and (b) the 59 outlier loci putatively under selection.
Sampling location codes are as in Supplementary table 1. Nodes with high
support (> 0,95) are filled in black.
Figure4:
Predictor overall importance plot. The R2 weighted
importance of environmental variables with low level of covariance
explaining the genetic variation across sampling locations as obtained
from GF analysis. Environmental variables used in the analyses are the
same as in Supplementary table 1; bio 14, Precipitation of the driest
month (mm); bio 8, Mean temperature of the wettest quarter (°C);
elevation, Elevation (masl); bio 9, Mean temperature of the driest
quarter (°C); bio 4, Temperature seasonality (°C); bio 3, Isothermality
(%); bio 13, Precipitation of the wettest month (mm).
Figure5:
Estimation of divergence time in Embothrium coccineum based on
Bayesian coalescent analysis using SNAPP. Nodes with high support
(posterior probability > 0.99) are filled in black. Median
ages are provided above nodes with 95% highest posterior densities
(HDP) below. The divergence time was inferred only for the nodes showing
high support (posterior probability > 0.99). Sampling
location codes are as in Supplementary table 1; colored symbol for each
sampling location match Fig. 1a.
Table 1: Genetic diversity of Embothrium coccineum in
each sampling locality. Localities ID are as in Supplementary table 1.
n, number of genotyped individuals; He, expected heterozygosity; Ho,
Observed heterozygosity; FIS, inbreeding coefficient; PPL, percentage of
polymorphic loci; PA, private alleles.
Table 2: Average FST values for pairwise comparisons among
sampling locations of Embothrium coccineum in Chile based on a
set of 2,155 SNPs. All p-values are significant
(<0.05). Sampling location codes are as in Supplementary table
1. North: Ch, Cu and Nah; Center: PM, ChlN, ChlS and Pu; South: Coy,
ChCh and TP.
Table 3: Redundancy analysis (RDA) partitioning among-population
genetic variation in Embothrium coccineum into three components:
environmental (Env), geographic (Geo) and North / Center-South
coancestry (Anc). All p values <0.001.
Supplementary Table
1 :
Environmental characteristics of each sampling location ofEmbothrium coccineum.
GPS coordinates are given for each sampling location. Environmental
variables: bio 14, Precipitation of the driest month (mm); bio 8, Mean
temperature of the wettest quarter (°C); Elv, Elevation (mamsl); bio 9,
Mean temperature of the driest quarter (°C); bio 4, Temperature
seasonality (°C); bio 3, Isothermality (%); bio 13, Precipitation of
the wettest month (mm).