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Costs of reproduction due to resource allocation trade-offs have long been recognized as key forces in life history evolution, but little is known about their functional or genetic basis. Arabidopsis lyrata, a perennial relative of the annual model plant A. thaliana with a wide climatic distribution, has populations that are strongly diverged in resource allocation. In this study, we evaluated the genetic and functional basis for variation in resource allocation in a reciprocal transplant experiment, using four A. lyrata populations and F2 progeny from a cross between North Carolina (NC) and Norway parents, which had the most divergent resource allocation patterns. Local alleles at quantitative trait loci (QTL) at a North Carolina field site increased reproductive output while reducing vegetative growth. These QTL had little overlap with flowering date QTL. Structural equation models incorporating QTL genotypes and traits indicated that resource allocation differences result primarily from QTL effects on early vegetative growth patterns, with cascading effects on later vegetative and reproductive development. At a Norway field site, North Carolina alleles at some of the same QTL regions reduced survival and reproductive output components, but these effects were not associated with resource allocation trade-offs in the Norway environment. Our results indicate that resource allocation in perennial plants may involve important adaptive mechanisms largely independent of flowering time. Moreover, the contributions of resource allocation QTL to local adaptation appear to result from their effects on developmental timing and its interaction with environmental constraints, and not from simple models of reproductive costs.

Inbreeding depression is important in the evolution of plant populations and mating systems. Previous studies have suggested that early-acting inbreeding depression in plants is primarily due to lethal alleles and possibly epistatic interactions. Recent advances in molecular markers now make genetic mapping a powerful tool to study the genetic architecture of inbreeding depression. We describe a genome-wide evaluation of embryonic viability loci in a selfed family of loblolly pine (Pinus taeda L.), using data from AFLP markers from an essentially complete genome map. Locus positions and effects were estimated from segregation ratios using a maximum-likelihood interval mapping procedure. We identified 19 loci showing moderately deleterious to lethal embryonic effects. These loci account for >13 lethal equivalents, greater than the average of 8.5 lethal equivalents reported for loblolly pine. Viability alleles show predominantly recessive action, although potential overdominance occurs at 3 loci. We found no evidence for epistasis in the distribution of pairwise marker correlations or in the regression of fitness on the number of markers linked to deleterious alleles. The predominant role of semilethal alleles in embryonic inbreeding depression has implications for the evolution of isolated populations and for genetic conservation and breeding programs in conifers.

The use of high-throughput genomic techniques to map gene expression quantitative trait loci has spurred the development of path analysis approaches for predicting functional networks linking genes and natural trait variation. The goal of this study was to test whether potentially confounding factors, including effects of common environment and genes not included in path models, affect predictions of cause–effect relationships among traits generated by QTL path analyses. Structural equation modeling (SEM) was used to test simple QTL-trait networks under different regulatory scenarios involving direct and indirect effects. SEM identified the correct models under simple scenarios, but when common-environment effects were simulated in conjunction with direct QTL effects on traits, they were poorly distinguished from indirect effects, leading to false support for indirect models. Application of SEM to loblolly pine QTL data provided support for biologically plausible a priori hypotheses of QTL mechanisms affecting height and diameter growth. However, some biologically implausible models were also well supported. The results emphasize the need to include any available functional information, including predictions for genetic and environmental correlations, to develop plausible models if biologically useful trait network predictions are to be made.