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.

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.

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 desertadapted 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.

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 ~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 hotspots 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, and 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 expression QTL 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.

Light is an essential resource for photosynthesis. Limitation of light by shade from plant neighbors can induce a light competition program known as the shade avoidance response (SAR), thereby altering plant growth and development for the sake of survival. Natural genetic variation in SAR is found in plants adapted to distinct environments, including domesticated tomato Solanum lycopersicum and its wild relative Solanum pennellii. QTL mapping was used to examine variation of the SAR between these two species. We found organ specific responses in the elongation of the stem and petiole, including developmental acceleration of growth. Through RNAseq analysis we identified a number of ILs with reduced expression of auxin-related genes in shade treatment. These same ILs display a shade tolerant phenotype in stem growth and overall height. We also identified ILs with altered SAR expression of cell wall expansion genes, although these genotypes had no accompanying alteration in phenotype. Examination of weighted gene co-expression connectivity networks in sun- and shade-treated plants revealed connectivity changes in auxin and light signaling genes; this result was supported by the identification of motifs within the promoters of a subset of shade-responsive genes that were enriched in light signaling, developmental pathways, and auxin responsive transcriptional domains. The identification of both systemic and organ-specific shade tolerance in the ILs, as well as associated changes in the transcriptome, has the potential to inform future studies for breeding plants able to be grown closely (while neighbor-shaded), yet still maintaining high yield.