Flower orientation influences floral temperature, pollinator visits and plant fitness.

Effective insect pollination requires appropriate responses to internal and external environmental cues in both the plant and the pollinator. Helianthus annuus, a highly outcrossing species, is marked for its uniform eastward orientation of mature pseudanthia, or capitula. Here we investigate how this orientation affects floral microclimate and the consequent effects on plant and pollinator interactions and reproductive fitness. We artificially manipulated sunflower capitulum orientation and temperature in both field and controlled conditions and assessed flower physiology, pollinator visits, seed traits and siring success. East-facing capitula were found to have earlier style elongation, pollen presentation and pollinator visits compared with capitula manipulated to face west. East-facing capitula also sired more offspring than west-facing capitula and under some conditions produced heavier and better-filled seeds. Local ambient temperature change on the capitulum was found to be a key factor regulating the timing of style elongation, pollen emergence and pollinator visits. These results indicate that eastward capitulum orientation helps to control daily rhythms in floral temperature, with direct consequences on the timing of style elongation and pollen emergence, pollinator visitation, and plant fitness.

Tissue-Specific Transcriptome Analysis Reveals Candidate Genes for Terpenoid and Phenylpropanoid Metabolism in the Medicinal Plant Ferula assafoetida.

Ferula assafoetida is a medicinal plant of the Apiaceae family that has traditionally been used for its therapeutic value. Particularly, terpenoid and phenylpropanoid metabolites, major components of the root-derived oleo-gum-resin, exhibit anti-inflammatory and cytotoxic activities, thus offering a resource for potential therapeutic lead compounds. However, genes and enzymes for terpenoid and coumarin-type phenylpropanoid metabolism have thus far remained uncharacterized in F. assafoetida Comparative de novo transcriptome analysis of roots, leaves, stems, and flowers was combined with computational annotation to identify candidate genes with probable roles in terpenoid and coumarin biosynthesis. Gene network analysis showed a high abundance of predicted terpenoid- and phenylpropanoid-metabolic pathway genes in flowers. These findings offer a deeper insight into natural product biosynthesis in F. assafoetida and provide genomic resources for exploiting the medicinal potential of this rare plant.

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.

The genome of the stress-tolerant wild tomato species Solanum pennellii.

Solanum pennellii is a wild tomato species endemic to Andean regions in South America, where it has evolved to thrive in arid habitats. Because of its extreme stress tolerance and unusual morphology, it is an important donor of germplasm for the cultivated tomato Solanum lycopersicum. Introgression lines (ILs) in which large genomic regions of S. lycopersicum are replaced with the corresponding segments from S. pennellii can show remarkably superior agronomic performance. Here we describe a high-quality genome assembly of the parents of the IL population. By anchoring the S. pennellii genome to the genetic map, we define candidate genes for stress tolerance and provide evidence that transposable elements had a role in the evolution of these traits. Our work paves a path toward further tomato improvement and for deciphering the mechanisms underlying the myriad other agronomic traits that can be improved with S. pennellii germplasm.

Evolutionary developmental transcriptomics reveals a gene network module regulating interspecific diversity in plant leaf shape.

Despite a long-standing interest in the genetic basis of morphological diversity, the molecular mechanisms that give rise to developmental variation are incompletely understood. Here, we use comparative transcriptomics coupled with the construction of gene coexpression networks to predict a gene regulatory network (GRN) for leaf development in tomato and two related wild species with strikingly different leaf morphologies. The core network in the leaf developmental GRN contains regulators of leaf morphology that function in global cell proliferation with peripheral gene network modules (GNMs). The BLADE-ON-PETIOLE (BOP) transcription factor in one GNM controls the core network by altering effective concentration of the KNOTTED-like HOMEOBOX gene product. Comparative network analysis and experimental perturbations of BOP levels suggest that variation in BOP expression could explain the diversity in leaf complexity among these species through dynamic rewiring of interactions in the GRN. The peripheral location of the BOP-containing GNM in the leaf developmental GRN and the phenotypic mimics of evolutionary diversity caused by alteration in BOP levels identify a key role for this GNM in canalizing the leaf morphospace by modifying the maturation schedule of leaves to create morphological diversity.

A quantitative genetic basis for leaf morphology in a set of precisely defined tomato introgression lines.

Introgression lines (ILs), in which genetic material from wild tomato species is introgressed into a domesticated background, have been used extensively in tomato (Solanum lycopersicum) improvement. Here, we genotype an IL population derived from the wild desert tomato Solanum pennellii at ultrahigh density, providing the exact gene content harbored by each line. To take advantage of this information, we determine IL phenotypes for a suite of vegetative traits, ranging from leaf complexity, shape, and size to cellular traits, such as stomatal density and epidermal cell phenotypes. Elliptical Fourier descriptors on leaflet outlines provide a global analysis of highly heritable, intricate aspects of leaf morphology. We also demonstrate constraints between leaflet size and leaf complexity, pavement cell size, and stomatal density and show independent segregation of traits previously assumed to be genetically coregulated. Meta-analysis of previously measured traits in the ILs shows an unexpected relationship between leaf morphology and fruit sugar levels, which RNA-Seq data suggest may be attributable to genetically coregulated changes in fruit morphology or the impact of leaf shape on photosynthesis. Together, our results both improve upon the utility of an important genetic resource and attest to a complex, genetic basis for differences in leaf morphology between natural populations.

Dynamic transcriptomic profiles between tomato and a wild relative reflect distinct developmental architectures.

Developmental differences between species commonly result from changes in the tissue-specific expression of genes. Clustering algorithms are a powerful means to detect coexpression across tissues in single species but are not often applied to multidimensional data sets, such as gene expression across tissues in multiple species. As next-generation sequencing approaches enable interspecific analyses, methods to visualize and explore such data sets will be required. Here, we analyze a data set comprising gene expression profiles across six different tissue types in domesticated tomato (Solanum lycopersicum) and a wild relative (Solanum pennellii). We find that self-organizing maps are a useful means to analyze interspecies data, as orthologs can be assigned to independent levels of a "super self-organizing map." We compare various clustering approaches using a principal component analysis in which the expression of orthologous pairs is indicated by two points. We leverage the expression profile differences between orthologs to look at tissue-specific changes in gene expression between species. Clustering based on expression differences between species (rather than absolute expression profiles) yields groups of genes with large tissue-by-species interactions. The changes in expression profiles of genes we observe reflect differences in developmental architecture, such as changes in meristematic activity between S. lycopersicum and S. pennellii. Together, our results offer a suite of data-exploration methods that will be important to visualize and make biological sense of next-generation sequencing experiments designed explicitly to discover tissue-by-species interactions in gene expression data.

Fine genetic mapping of RXopJ4, a bacterial spot disease resistance locus from Solanum pennellii LA716.

The RXopJ4 resistance locus from the wild accession Solanum pennellii (Sp) LA716 confers resistance to bacterial spot disease of tomato (S. lycopersicum, Sl) caused by Xanthomonas perforans (Xp). RXopJ4 resistance depends on recognition of the pathogen type III effector protein XopJ4. We used a collection of Sp introgression lines (ILs) to narrow the RXopJ4 locus to a 4.2-Mb segment on the long arm of chromosome 6, encompassed by the ILs 6-2 and 6-2-2. We then adapted or developed a collection of 14 molecular markers to map on a segregating F(2) population from a cross between the susceptible parent Sl FL8000 and the resistant parent RXopJ4 8000 OC(7). In the F(2) population, a 190-kb segment between the markers J350 and J352 cosegregated with resistance. This fine mapping will enable both the identification of candidate genes and the detection of resistant plants using cosegregating markers. The RXopJ4 resistance gene(s), in combination with other recently characterized genes and a quantitative trait locus (QTL) for bacterial spot disease resistance, will likely be an effective tool for the development of durable resistance in cultivated tomato.

Sequence diversity in three tomato species: SNPs, markers, and molecular evolution.

BACKGROUND: Tomato species are of significant agricultural and ecological interest, with cultivated tomato being among the most common vegetable crops grown. Wild tomato species are native to diverse habitats in South America and show great morphological and ecological diversity that has proven useful in breeding programs. However, relatively little is known about nucleotide diversity between tomato species. Until recently limited sequence information was available for tomato, preventing genome-wide evolutionary analyses. Now, an extensive collection of tomato expressed sequence tags (ESTs) is available at the SOL Genomics Network (SGN). This database holds sequences from several species, annotated with quality values, assembled into unigenes, and tested for homology against other genomes. Despite the importance of polymorphism detection for breeding and natural variation studies, such analyses in tomato have mostly been restricted to cultivated accessions. Importantly, previous polymorphisms surveys mostly ignored the linked meta-information, limiting functional and evolutionary analyses. The current data in SGN is thus an under-exploited resource. Here we describe a cross-species analysis taking full-advantage of available information. RESULTS: We mined 20,000 interspecific polymorphisms between Solanum lycopersicum and S. habrochaites or S. pennellii and 28,800 intraspecific polymorphisms within S. lycopersicum. Using the available meta-information we classified genes into functional categories and obtained estimations of single nucleotide polymorphisms (SNP) quality, position in the gene, and effect on the encoded proteins, allowing us to perform evolutionary analyses. Finally, we developed a set of more than 10,000 between-species molecular markers optimized by sequence quality and predicted intron position. Experimental validation of 491 of these molecular markers resulted in confirmation of 413 polymorphisms. CONCLUSION: We present a new analysis of the extensive tomato EST sequences available that represents the most comprehensive survey of sequence diversity across Solanum species to date. These SNPs, plus thousands of molecular makers designed to detect the polymorphisms are available to the community via a website. Evolutionary analyses on these polymorphism uncovered sets of genes potentially important for the evolution and domestication of tomato; interestingly these sets were enriched for genes involved in response to the environment.