eQTL Regulating Transcript Levels Associated with Diverse Biological Processes in Tomato.

Variation in gene expression, in addition to sequence polymorphisms, is known to influence developmental, physiological, and metabolic traits in plants. Genetic mapping populations have facilitated identification of expression quantitative trait loci (eQTL), the genetic determinants of variation in gene expression patterns. We used an introgression population developed from the wild desert-adapted Solanum pennellii and domesticated tomato (Solanum lycopersicum) to identify the genetic basis of transcript level variation. We established the effect of each introgression on the transcriptome and identified approximately 7,200 eQTL regulating the steady-state transcript levels of 5,300 genes. Barnes-Hut t-distributed stochastic neighbor embedding clustering identified 42 modules revealing novel associations between transcript level patterns and biological processes. The results showed a complex genetic architecture of global transcript abundance pattern in tomato. Several genetic hot spots regulating a large number of transcript level patterns relating to diverse biological processes such as plant defense and photosynthesis were identified. Important eQTL regulating transcript level patterns were related to leaf number and complexity as well as hypocotyl length. Genes associated with leaf development showed an inverse correlation with photosynthetic gene expression, but eQTL regulating genes associated with leaf development and photosynthesis were dispersed across the genome. This comprehensive eQTL analysis details the influence of these loci on plant phenotypes and will be a valuable community resource for investigations on the genetic effects of eQTL on phenotypic traits in tomato.

Resolving distinct genetic regulators of tomato leaf shape within a heteroblastic and ontogenetic context.

Leaf shape is mutable, changing in ways modulated by both development and environment within genotypes. A complete model of leaf phenotype would incorporate the changes in leaf shape during juvenile-to-adult phase transitions and the ontogeny of each leaf. Here, we provide a morphometric description of >33,000 leaflets from a set of tomato (Solanum spp) introgression lines grown under controlled environment conditions. We first compare the shape of these leaves, arising during vegetative development, with >11,000 previously published leaflets from a field setting and >11,000 leaflets from wild tomato relatives. We then quantify the changes in shape, across ontogeny, for successive leaves in the heteroblastic series. Using principal component analysis, we then separate genetic effects modulating (1) the overall shape of all leaves versus (2) the shape of specific leaves in the series, finding the former more heritable than the latter and comparing quantitative trait loci regulating each. Our results demonstrate that phenotype is highly contextual and that unbiased assessments of phenotype, for quantitative genetic or other purposes, would ideally sample the many developmental and environmental factors that modulate it.

Molecular control of crop shade avoidance.

The shade avoidance response (SAR) in crops can be detrimental to yield, as precious carbon resources are redirected to stem or petiole elongation at the expense of biomass production. While breeding efforts have inadvertently attenuated this response in staple crops through correlated selection for yield at high density, it has not been eliminated. The extensive work done in Arabidopsis has provided a detailed understanding of the SAR and can be used as a framework for understanding the SAR in crop species. Recent crop SAR works point to auxin as a key factor in regulating the SAR in several crop species. These works also clearly demonstrate that one model for crop SAR will not fit all, and thus we need to move forward with studying the genetic players of the SAR in several model crop species. In this review, we provide the current knowledge of the SAR as reported at the physiological and molecular levels.