GxE in the MAGIC population
Genotype x environment interaction analysis was carried out after
correcting data for micro-environmental heterogeneity and removing
outliers. As a first step, variance analysis was conducted with ASReml-R
package and the variance components from model (2) used to estimate the
proportion of GxE variance (\(\text{prop.}{\sigma^{2}}_{\text{GxE}}\))
and heritability at the whole design level (\(H^{2}\)). Significant GxE
was found for every trait and the\(\text{prop.}{\sigma^{2}}_{\text{GxE}}\) varied from 0.15 (for nflw) to
0.68 (for leaf). Although GxE was significant, seven out of the ten
measured traits showed a higher proportion of genotypic variance
compared to GxE (Supplemental Table 3). The broad-sense heritability of
the whole design \(H^{2}\) was largely variable according to the trait,
varying from 0.18 (nfr) to 0.77 (flw). Its calculation took into account
the residual environment-specific variance which showed different range
according to the trait, lowering heritability of traits such as nfr and
fset (Supplemental Table 3). Furthermore, \(H^{2}\) at the whole design
level was lower than the heritability computed in single environment
(Supplemental Figure 3).
Afterwards, the proportion of the GxE that could be predicted by the
environmental covariates was assessed following the factorial regression
model (4). Across traits, different environmental covariates
significantly explained the GxE #(Supplemental Figure 4). Considering
only the most significant covariate, from 18% (FW) to 47% (fset) of
the GxE (proportion of the sum of squares) could be reliably attributed
to the responses of genotypes to climatic parameters measured within the
greenhouses. To perform the factorial regression model (4), the most
important environmental covariate was first identified for each trait
(Supplemental Figure 4). Growth traits, height and leaf were for example
mostly affected by the thermal amplitude and maximal temperature,
respectively, while yield component traits, FW and nfr were particularly
sensitive to the sum of degree day. The vapour pressure deficit (Vpd,
kPa) was the most important environmental factor affecting firm, fset
and SSC. Flowering time (flw) and nflw were mostly affected by minimal
temperatures and relative humidity, respectively. Stem diameter was the
only trait for which none of the environmental covariates significantly
affected the trait.