Combining quantitative trait loci analysis with physiological models to predict genotype-specific transpiration rates

Transpiration is controlled by evaporative demand and stomatal conductance (g(s)), and there can be substantial genetic variation in g(s). A key parameter in empirical models of transpiration is minimum stomatal conductance (g(0)), a trait that can be measured and has a large effect on g(s) and transpiration. In Arabidopsis thaliana, g(0) exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g(0) QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying g(s) variation.