Polygenic scores
We investigated the predictive value of each climate variable for the
respective polygenic score based on 213 candidate loci, adjusting linear
or quadratic models, selecting the model with the lowest Akaike
information criterion (AIC) value. regressions were highly significant,
and adjusted R2 values ranged between 0.35 and 0.86
(Figure 3). Analysis using all the 1,392 detected outliers resulted in
similar positive regressions, independent of whether or not we corrected
for the population structure (Table S8).
Figure 3. Correlations between individual additive polygenic scores
(symbols) based on 213 candidate loci and each of the five explanatory
climate variables determined per sampling site: Annual mean temperature
(a), Annual precipitation (b), Temperature seasonality (c), Mean diurnal
temperature range (d), and Precipitation seasonality (e). Polygenic
scores were obtained by summing total numbers of favorable alleles. The
line represents the regression line from the model, while the shaded
area represents the 95% confidence interval. Variance explained and
p-values for the linear (c) or quadratic regression (a, b, d, e) fits
are given in the respective upper-left corner.