Genetic architecture of life history traits and environment-specific trade-offs

Abstract

Life history theory predicts the evolution of trait combinations that enhance fitness, and the occurrence of trade-offs depends in part on the magnitude of variation in growth rate or acquisition. Using recombinant inbred lines, we examined the genetic architecture of age and size at reproduction across abiotic conditions encountered by cultivars and naturalized populations of Brassica rapa. We found that genotypes are plastic to seasonal setting, such that reproduction was accelerated under conditions encountered by summer annual populations and genetic variances for age at reproduction varied across simulated seasonal settings. Using an acquisition-allocation model, we predicted the likelihood of trade-offs. Consistent with predicted relationships, we observed a trade-off where early maturity is associated with small size at maturity under simulated summer and fall annual conditions but not under winter annual conditions. The trade-off in the summer annual setting was observed despite significant genotypic variation in growth rate, which is often expected to decouple age and size at reproduction because rapidly growing genotypes could mature early and attain a larger size relative to slowly growing genotypes that mature later. The absence of a trade-off in the winter setting is presumably attributable to the absence of genotypic differences in age at reproduction. We observed QTL for age at reproduction that jointly regulated size at reproduction in both the summer and fall annual settings, but these QTL were environment-specific (i.e. different QTL contributed to the trade-off in the fall vs. summer annual settings). Thus, at least some of the genetic mechanisms underlying observed trade-offs differed across environments.

Genotypic variation in biomass allocation in response to field drought has a greater affect on yield than gas exchange or phenology

“…We compared the position and additive effects of QTL identified in the present study to those identified in previous studies using the same RILs, but from different environments (i.e., [37, 38, 40, 41, 71]). Overall, only a small proportion of the QTL found in this study were identified in previous studies, indicating that the environment in which the plant is grown can strongly affect the loci underlying phenotypic trait variation.…”

“…Several QTL for ecophysiological were previously identified in [41], namely QTL for g s on the top of chromosome 1 in both treatments; a QTL at the bottom of chromosome 3 for Fv'/Fm' in WW, and a QTL at 53 cM on chromosome 8 for δ 13 C in WW. Several QTL were previously identified for vegetative and allocation traits in [40], namely QTL in the center of on chromosome 3 for biomass traits in both treatments, and a QTL at 70 cM on chromosome 7 for root:shoot in both treatments. Finally, a QTL in the center of chromosome 3 for plant height in both treatments was previously identified in [37].…”

Paths to selection on life history loci in different natural environments across the native range of Arabidopsis thaliana

“…Life history traits often exhibit plastic responses to environmental variation (Scheiner 1993;Dorn et al 2000;Haselhorst et al 2011). Such plasticity can alter the expression of heritable variation and the architecture of trait correlations across environments (Falconer 1952;Bennington & McGraw 1996;Hoffmann & Parsons 1997;Donohue & Schmitt 1999).…”

Natural variation in life history strategy ofArabidopsis thalianadetermines stress responses to drought and insects of different feeding guilds

“…In addition, studies on other taxa also found evidence that flowering‐time genes can have pleiotropic effects on other traits such as water‐use efficiency in Brassica rapa (Franks ), vegetative biomass in A. barbata (Latta & Gardner ) and size at reproduction in B. rapa (Haselhorst et al . ).…”