The rhizosphere microbiome and host plant glucosinolates exhibit feedback cycles in Brassica rapa.

The rhizosphere microbiome influences many aspects of plant fitness, including production of secondary compounds and defence against insect herbivores. Plants also modulate the composition of the microbial community in the rhizosphere via secretion of root exudates. We tested both the effect of the rhizosphere microbiome on plant traits, and host plant effects on rhizosphere microbes using recombinant inbred lines (RILs) of Brassica rapa that differ in production of glucosinolates (GLS), secondary metabolites that contribute to defence against insect herbivores. First, we investigated the effect of genetic variation in GLS production on the composition of the rhizosphere microbiome. Using a Bayesian Dirichlet-multinomial regression model (DMBVS), we identified both negative and positive associations between bacteria from six genera and the concentration of five GLS compounds produced in plant roots. Additionally, we tested the effects of microbial inoculation (an intact vs. disrupted soil microbiome) on GLS production and insect damage in these RILs. We found a significant microbial treatment × genotype interaction, in which total GLS was higher in the intact relative to the disrupted microbiome treatment in some RILs. However, despite differences in GLS production between microbial treatments, we observed no difference in insect damage between treatments. Together, these results provide evidence for a full feedback cycle of plant-microbe interactions mediated by GLS; that is, GLS compounds produced by the host plant "feed-down" to influence rhizosphere microbial community and rhizosphere microbes "feed-up" to influence GLS production.

Correction: Integrating transcriptomic network reconstruction and eQTL analyses reveals mechanistic connections between genomic architecture and Brassica rapa development.

[This corrects the article DOI: 10.1371/journal.pgen.1008367.].

Naturally segregating genetic variation in circadian period exhibits a regional elevational and climatic cline.

Circadian clocks confer adaptation to predictable 24-h fluctuations in the exogenous environment, but it has yet to be determined what ecological factors maintain natural genetic variation in endogenous circadian period outside of the hypothesized optimum of 24 h. We estimated quantitative genetic variation in circadian period in leaf movement in 30 natural populations of the Arabidopsis relative Boechera stricta sampled within only 1° of latitude but across an elevation gradient spanning 2460-3300 m in the Rocky Mountains. Measuring ~3800 plants from 473 maternal families (7-20 per population), we found that genetic variation was of similar magnitude among versus within populations, with population means varying between 21.9 and 24.9 h and maternal family means within populations varying by up to ~6 h. After statistically accounting for spatial autocorrelation at a habitat extreme, we found that elevation explained a significant proportion of genetic variation in the circadian period, such that higher-elevation populations had shorter mean period lengths and reduced intrapopulation ranges. Environmental data indicate that these spatial trends could be related to steep regional climatic gradients in temperature, precipitation, and their intra-annual variability. Our findings suggest that spatially fine-grained environmental heterogeneity contributes to naturally occurring genetic variation in circadian traits in wild populations.

Integrating transcriptomic network reconstruction and eQTL analyses reveals mechanistic connections between genomic architecture and Brassica rapa development.

Plant developmental dynamics can be heritable, genetically correlated with fitness and yield, and undergo selection. Therefore, characterizing the mechanistic connections between the genetic architecture governing plant development and the resulting ontogenetic dynamics of plants in field settings is critically important for agricultural production and evolutionary ecology. We use hierarchical Bayesian Function-Valued Trait (FVT) models to estimate Brassica rapa growth curves throughout ontogeny, across two treatments, and in two growing seasons. We find genetic variation for plasticity of growth rates and final sizes, but not the inflection point (transition from accelerating to decelerating growth) of growth curves. There are trade-offs between growth rate and duration, indicating that selection for maximum yields at early harvest dates may come at the expense of late harvest yields and vice versa. We generate eigengene modules and determine which are co-expressed with FVT traits using a Weighted Gene Co-expression Analysis. Independently, we seed a Mutual Rank co-expression network model with FVT traits to identify specific genes and gene networks related to FVT. GO-analyses of eigengene modules indicate roles for actin/cytoskeletal genes, herbivore resistance/wounding responses, and cell division, while MR networks demonstrate a close association between metabolic regulation and plant growth. We determine that combining FVT Quantitative Trait Loci (QTL) and MR genes/WGCNA eigengene expression profiles better characterizes phenotypic variation than any single data type (i.e. QTL, gene, or eigengene alone). Our network analysis allows us to employ a targeted eQTL analysis, which we use to identify regulatory hotspots for FVT. We examine cis vs. trans eQTL that mechanistically link FVT QTL with structural trait variation. Colocalization of FVT, gene, and eigengene eQTL provide strong evidence for candidate genes influencing plant height. The study is the first to explore eQTL for FVT, and specifically do so in agroecologically relevant field settings.

Rapid Chlorophyll a Fluorescence Light Response Curves Mechanistically Inform Photosynthesis Modeling.

Crop improvement is crucial to ensuring global food security under climate change, and hence there is a pressing need for phenotypic observations that are both high throughput and improve mechanistic understanding of plant responses to environmental cues and limitations. In this study, chlorophyll a fluorescence light response curves and gas-exchange observations are combined to test the photosynthetic response to moderate drought in four genotypes of Brassica rapa The quantum yield of PSII (ϕ PSII ) is here analyzed as an exponential decline under changing light intensity and soil moisture. Both the maximum ϕ PSII and the rate of ϕ PSII decline across a large range of light intensities (0-1,000 µmol photons m-2 s-1; ß PSII ) are negatively affected by drought. We introduce an alternative photosynthesis model (ß PSII model) incorporating parameters from rapid fluorescence response curves. Specifically, the model uses ß PSII as an input for estimating the photosynthetic electron transport rate, which agrees well with two existing photosynthesis models (Farquhar-von Caemmerer-Berry and Yin). The ß PSII model represents a major improvement in photosynthesis modeling through the integration of high-throughput fluorescence phenotyping data, resulting in gained parameters of high mechanistic value.

Plastic response to early shade avoidance cues has season-long effect on Beta vulgaris growth and development.

Early-emerging weeds are known to negatively affect crop growth but the mechanisms by which weeds reduce crop yield are not fully understood. In a 4-year study, we evaluated the effect of duration of weed-reflected light on sugar beet (Beta vulgaris L.) growth and development. The study included an early-season weed removal series and a late-season weed addition series of treatments arranged in a randomized complete block, and the study design minimized direct resource competition. If weeds were present from emergence until the two true-leaf sugar beet stage, sugar beet leaf area was reduced 22%, leaf biomass reduced 25%, and root biomass reduced 32% compared to sugar beet grown season-long without surrounding weeds. Leaf area, leaf biomass, and root biomass was similar whether weeds were removed at the two true-leaf stage (approximately 330 GDD after planting) or allowed to remain until sugar beet harvest (approximately 1,240 GDD after planting). Adding weeds at the two true-leaf stage and leaving them until harvest (~1,240 GDD) reduced sugar beet leaf and root biomass by 18% and 23%, respectively. This work suggests sugar beet responds early and near-irreversibly to weed presence and has implications for crop management genetic improvement.

The effect of rhizosphere microbes outweighs host plant genetics in reducing insect herbivory.

Rhizosphere microbes affect plant performance, including plant resistance against insect herbivores; yet, a direct comparison of the relative influence of rhizosphere microbes versus plant genetics on herbivory levels and on metabolites related to defence is lacking. In the crucifer Boechera stricta, we tested the effects of rhizosphere microbes and plant population on herbivore resistance, the primary metabolome, and select secondary metabolites. Plant populations differed significantly in the concentrations of six glucosinolates (GLS), secondary metabolites known to provide herbivore resistance in the Brassicaceae. The population with lower GLS levels experienced ~60% higher levels of aphid (Myzus persicae) attack; no association was observed between GLS and damage by a second herbivore, flea beetles (Phyllotreta cruciferae). Rhizosphere microbiome (disrupted vs. intact native microbiome) had no effect on plant GLS concentrations. However, aphid number and flea beetle damage were respectively about three- and seven-fold higher among plants grown in the disrupted versus intact native microbiome treatment. These differences may be attributable to shifts in primary metabolic pathways previously implicated in host defence against herbivores, including increases in pentose and glucoronate interconversion among plants grown with an intact microbiome. Furthermore, native microbiomes with distinct community composition (as estimated from 16s rRNA amplicon sequencing) differed two-fold in their effect on host plant susceptibility to aphids. The findings suggest that rhizosphere microbes, including distinct native microbiomes, can play a greater role than population in defence against insect herbivores, and act through metabolic mechanisms independent of population.

A framework for genomics-informed ecophysiological modeling in plants.

Dynamic process-based plant models capture complex physiological response across time, carrying the potential to extend simulations out to novel environments and lend mechanistic insight to observed phenotypes. Despite the translational opportunities for varietal crop improvement that could be unlocked by linking natural genetic variation to first principles-based modeling, these models are challenging to apply to large populations of related individuals. Here we use a combination of model development, experimental evaluation, and genomic prediction in Brassica rapa L. to set the stage for future large-scale process-based modeling of intraspecific variation. We develop a new canopy growth submodel for B. rapa within the process-based model Terrestrial Regional Ecosystem Exchange Simulator (TREES), test input parameters for feasibility of direct estimation with observed phenotypes across cultivated morphotypes and indirect estimation using genomic prediction on a recombinant inbred line population, and explore model performance on an in silico population under non-stressed and mild water-stressed conditions. We find evidence that the updated whole-plant model has the capacity to distill genotype by environment interaction (G×E) into tractable components. The framework presented offers a means to link genetic variation with environment-modulated plant response and serves as a stepping stone towards large-scale prediction of unphenotyped, genetically related individuals under untested environmental scenarios.

Circadian rhythms are associated with shoot architecture in natural settings.

Circadian rhythms are key regulators of diverse biological processes under controlled settings. Yet, the phenotypic and fitness consequences of quantitative variation in circadian rhythms remain largely unexplored in the field. As with other pathways, phenotypic characterization of circadian outputs in the field may reveal novel clock functions. Across consecutive growing seasons, we test for associations between clock variation and flowering phenology, plant size, shoot architecture, and fruit set in clock mutants and segregating progenies of Arabidopsis thaliana expressing quantitative variation in circadian rhythms. Using structural equation modeling, we find that genotypic variation in circadian rhythms within a growing season is associated directly with branching, which in turn affects fruit production. Consistent with direct associations between the clock and branching in segregating progenies, cauline branch number is lower and rosette branch number higher in a short-period mutant relative to wild-type and long-period genotypes, independent of flowering time. Differences in branching arise from variation in meristem fate as well as leaf production rate before flowering and attendant increases in meristem number. Our results suggest that clock variation directly affects shoot architecture in the field, suggesting a novel clock function and means by which the clock affects performance.

Dead or Alive? Using Membrane Failure and Chlorophyll a Fluorescence to Predict Plant Mortality from Drought.

Climate models predict widespread increases in both drought intensity and duration in the next decades. Although water deficiency is a significant determinant of plant survival, limited understanding of plant responses to extreme drought impedes forecasts of both forest and crop productivity under increasing aridity. Drought induces a suite of physiological responses; however, we lack an accurate mechanistic description of plant response to lethal drought that would improve predictive understanding of mortality under altered climate conditions. Here, proxies for leaf cellular damage, chlorophyll a fluorescence, and electrolyte leakage were directly associated with failure to recover from drought upon rewatering in Brassicarapa (genotype R500) and thus define the exact timing of drought-induced death. We validated our results using a second genotype (imb211) that differs substantially in life history traits. Our study demonstrates that whereas changes in carbon dynamics and water transport are critical indicators of drought stress, they can be unrelated to visible metrics of mortality, i.e. lack of meristematic activity and regrowth. In contrast, membrane failure at the cellular scale is the most proximate cause of death. This hypothesis was corroborated in two gymnosperms (Picea engelmannii and Pinus contorta) that experienced lethal water stress in the field and in laboratory conditions. We suggest that measurement of chlorophyll a fluorescence can be used to operationally define plant death arising from drought, and improved plant characterization can enhance surface model predictions of drought mortality and its consequences to ecosystem services at a global scale.

Circadian rhythms are associated with variation in photosystem II function and photoprotective mechanisms.

The circadian clock regulates many aspects of leaf gas supply and biochemical demand for CO2 , and is hypothesized to improve plant performance. Yet the extent to which the clock may regulate the efficiency of photosystem II (PSII) and photoprotective mechanisms such as heat dissipation is less explored. Based on measurements of chlorophyll a fluorescence, we estimated the maximum efficiency of PSII in light (Fv'/Fm') and heat dissipation by nonphotochemical quenching (NPQ). We further dissected total NPQ into its main components, qE (pH-dependent quenching), qT (state-transition quenching), and qI (quenching related to photoinhibition), in clock mutant genotypes of Arabidopsis thaliana, the cognate wild-type genotypes, and a panel of recombinant inbred lines expressing quantitative variation in clock period. Compared with mutants with altered clock function, we observed that wild-type genotypes with clock period lengths of approximately 24 hr had both higher levels of Fv'/Fm', indicative of improved PSII function, and reduced NPQ, suggestive of lower stress on PSII light harvesting complexes. In the recombinant inbred lines, genetic variances were significant for Fv'/Fm' and all 3 components of NPQ, with qE explaining the greatest proportion of NPQ. Bivariate tests of association and structural equation models of hierarchical trait relationships showed that quantitative clock variation was empirically associated with Fv'/Fm' and NPQ, with qE mediating the relationship with gas exchange. The results demonstrate significant segregating variation for all photoprotective components, and suggest the adaptive significance of the clock may partly derive from its regulation of the light reactions of photosynthesis and of photoprotective mechanisms.

Bayesian estimation and use of high-throughput remote sensing indices for quantitative genetic analyses of leaf growth.

KEY MESSAGE: We develop Bayesian function-valued trait models that mathematically isolate genetic mechanisms underlying leaf growth trajectories by factoring out genotype-specific differences in photosynthesis. Remote sensing data can be used instead of leaf-level physiological measurements. Characterizing the genetic basis of traits that vary during ontogeny and affect plant performance is a major goal in evolutionary biology and agronomy. Describing genetic programs that specifically regulate morphological traits can be complicated by genotypic differences in physiological traits. We describe the growth trajectories of leaves using novel Bayesian function-valued trait (FVT) modeling approaches in Brassica rapa recombinant inbred lines raised in heterogeneous field settings. While frequentist approaches estimate parameter values by treating each experimental replicate discretely, Bayesian models can utilize information in the global dataset, potentially leading to more robust trait estimation. We illustrate this principle by estimating growth asymptotes in the face of missing data and comparing heritabilities of growth trajectory parameters estimated by Bayesian and frequentist approaches. Using pseudo-Bayes factors, we compare the performance of an initial Bayesian logistic growth model and a model that incorporates carbon assimilation (A max) as a cofactor, thus statistically accounting for genotypic differences in carbon resources. We further evaluate two remotely sensed spectroradiometric indices, photochemical reflectance (pri2) and MERIS Terrestrial Chlorophyll Index (mtci) as covariates in lieu of A max, because these two indices were genetically correlated with A max across years and treatments yet allow much higher throughput compared to direct leaf-level gas-exchange measurements. For leaf lengths in uncrowded settings, including A max improves model fit over the initial model. The mtci and pri2 indices also outperform direct A max measurements. Of particular importance for evolutionary biologists and plant breeders, hierarchical Bayesian models estimating FVT parameters improve heritabilities compared to frequentist approaches.

Natural diversity in daily rhythms of gene expression contributes to phenotypic variation.

Daily rhythms of gene expression provide a benefit to most organisms by ensuring that biological processes are activated at the optimal time of day. Although temporal patterns of expression control plant traits of agricultural importance, how natural genetic variation modifies these patterns during the day and how precisely these patterns influence phenotypes is poorly understood. The circadian clock regulates the timing of gene expression, and natural variation in circadian rhythms has been described, but circadian rhythms are measured in artificial continuous conditions that do not reflect the complexity of biologically relevant day/night cycles. By studying transcriptional rhythms of the evening-expressed gene gigantea (GI) at high temporal resolution and during day/night cycles, we show that natural variation in the timing of GI expression occurs mostly under long days in 77 Arabidopsis accessions. This variation is explained by natural alleles that alter light sensitivity of GI, specifically in the evening, and that act at least partly independent of circadian rhythms. Natural alleles induce precise changes in the temporal waveform of GI expression, and these changes have detectable effects on phytochrome interacting factor 4 expression and growth. Our findings provide a paradigm for how natural alleles act within day/night cycles to precisely modify temporal gene expression waveforms and cause phenotypic diversity. Such alleles could confer an advantage by adjusting the activity of temporally regulated processes without severely disrupting the circadian system.

Allelic polymorphism of GIGANTEA is responsible for naturally occurring variation in circadian period in Brassica rapa.

GIGANTEA (GI) was originally identified by a late-flowering mutant in Arabidopsis, but subsequently has been shown to act in circadian period determination, light inhibition of hypocotyl elongation, and responses to multiple abiotic stresses, including tolerance to high salt and cold (freezing) temperature. Genetic mapping and analysis of families of heterogeneous inbred lines showed that natural variation in GI is responsible for a major quantitative trait locus in circadian period in Brassica rapa. We confirmed this conclusion by transgenic rescue of an Arabidopsis gi-201 loss of function mutant. The two B. rapa GI alleles each fully rescued the delayed flowering of Arabidopsis gi-201 but showed differential rescue of perturbations in red light inhibition of hypocotyl elongation and altered cold and salt tolerance. The B. rapa R500 GI allele, which failed to rescue the hypocotyl and abiotic stress phenotypes, disrupted circadian period determination in Arabidopsis. Analysis of chimeric B. rapa GI alleles identified the causal nucleotide polymorphism, which results in an amino acid substitution (S264A) between the two GI proteins. This polymorphism underlies variation in circadian period, cold and salt tolerance, and red light inhibition of hypocotyl elongation. Loss-of-function mutations of B. rapa GI confer delayed flowering, perturbed circadian rhythms in leaf movement, and increased freezing and increased salt tolerance, consistent with effects of similar mutations in Arabidopsis. Collectively, these data suggest that allelic variation of GI-and possibly of clock genes in general-offers an attractive target for molecular breeding for enhanced stress tolerance and potentially for improved crop yield.

Polyploidy and the relationship between leaf structure and function: implications for correlated evolution of anatomy, morphology, and physiology in Brassica.

BACKGROUND: Polyploidy is well studied from a genetic and genomic perspective, but the morphological, anatomical, and physiological consequences of polyploidy remain relatively uncharacterized. Whether these potential changes bear on functional integration or are idiosyncratic remains an open question. Repeated allotetraploid events and multiple genomic combinations as well as overlapping targets of artificial selection make the Brassica triangle an excellent system for exploring variation in the connection between plant structure (anatomy and morphology) and function (physiology). We examine phenotypic integration among structural aspects of leaves including external morphology and internal anatomy with leaf-level physiology among several species of Brassica. We compare diploid and allotetraploid species to ascertain patterns of phenotypic correlations among structural and functional traits and test the hypothesis that allotetraploidy results in trait disintegration allowing for transgressive phenotypes and additional evolutionary and crop improvement potential. RESULTS: Among six Brassica species, we found significant effects of species and ploidy level for morphological, anatomical and physiological traits. We identified three suites of intercorrelated traits in both diploid parents and allotetraploids: Morphological traits (such as leaf area and perimeter) anatomic traits (including ab- and ad- axial epidermis) and aspects of physiology. In general, there were more correlations between structural and functional traits for allotetraploid hybrids than diploid parents. Parents and hybrids did not have any significant structure-function correlations in common. Of particular note, there were no significant correlations between morphological structure and physiological function in the diploid parents. Increased phenotypic integration in the allotetraploid hybrids may be due, in part, to increased trait ranges or simply different structure-function relationships. CONCLUSIONS: Genomic and chromosomal instability in early generation allotetraploids may allow Brassica species to explore new trait space and potentially reach higher adaptive peaks than their progenitor species could, despite temporary fitness costs associated with unstable genomes. The trait correlations that disappear after hybridization as well as the novel trait correlations observed in allotetraploid hybrids may represent relatively evolutionarily labile associations and therefore could be ideal targets for artificial selection and crop improvement.

Epistasis × environment interactions among Arabidopsis thaliana glucosinolate genes impact complex traits and fitness in the field.

Despite the growing number of studies showing that genotype × environment and epistatic interactions control fitness, the influences of epistasis × environment interactions on adaptive trait evolution remain largely uncharacterized. Across three field trials, we quantified aliphatic glucosinolate (GSL) defense chemistry, leaf damage, and relative fitness using mutant lines of Arabidopsis thaliana varying at pairs of causal aliphatic GSL defense genes to test the impact of epistatic and epistasis × environment interactions on adaptive trait variation. We found that aliphatic GSL accumulation was primarily influenced by additive and epistatic genetic variation, leaf damage was primarily influenced by environmental variation and relative fitness was primarily influenced by epistasis and epistasis × environment interactions. Epistasis × environment interactions accounted for up to 48% of the relative fitness variation in the field. At a single field site, the impact of epistasis on relative fitness varied significantly over 2 yr, showing that epistasis × environment interactions within a location can be temporally dynamic. These results suggest that the environmental dependency of epistasis can profoundly influence the response to selection, shaping the adaptive trajectories of natural populations in complex ways, and deserves further consideration in future evolutionary studies.

Circadian rhythms vary over the growing season and correlate with fitness components.

Circadian clocks have evolved independently in all three domains of life, suggesting that internal mechanisms of time-keeping are adaptive in contemporary populations. However, the performance consequences of either discrete or quantitative clock variation have rarely been tested in field settings. Clock sensitivity of diverse segregating lines to the environment remains uncharacterized as do the statistical genetic parameters that determine evolutionary potential. In field studies with Arabidopsis thaliana, we found that major perturbations to circadian cycle length (referred to as clock period) via mutation reduce both survival and fecundity. Subtler adjustments via genomic introgression of naturally occurring alleles indicated that clock periods slightly >24 hr were adaptive, consistent with prior models describing how well the timing of biological processes is adjusted within a diurnal cycle (referred to as phase). In segregating recombinant inbred lines (RILs), circadian phase varied up to 2 hr across months of the growing season, and both period and phase expressed significant genetic variances. Performance metrics including developmental rate, size and fruit set were described by principal components (PC) analyses and circadian parameters correlated with the first PC, such that period lengths slightly >24 hr were associated with improved performance in multiple RIL sets. These experiments translate functional analyses of clock behaviour performed in controlled settings to natural ones, demonstrating that quantitative variation in circadian phase is highly responsive to seasonally variable abiotic factors. The results expand upon prior studies in controlled settings, showing that discrete and quantitative variation in clock phenotypes correlates with performance in nature.

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

BACKGROUND: Plant performance in agricultural and natural settings varies with moisture availability, and understanding the range of potential drought responses and the underlying genetic architecture is important for understanding how plants will respond to both natural and artificial selection in various water regimes. Here, we raised genotypes of Brassica rapa under well-watered and drought treatments in the field. Our primary goal was to understand the genetic architecture and yield effects of different drought-escape and dehydration-avoidance strategies. RESULTS: Drought treatments reduced soil moisture by 62 % of field capacity. Drought decreased biomass accumulation and fruit production by as much as 48 %, whereas instantaneous water-use efficiency and root:shoot ratio increased. Genotypes differed in the mean value of all traits and in the sensitivity of biomass accumulation, root:shoot ratio, and fruit production to drought. Bivariate correlations involving gas-exchange and phenology were largely constant across environments, whereas those involving root:shoot varied across treatments. Although root:shoot was typically unrelated to gas-exchange or yield under well-watered conditions, genotypes with low to moderate increases in root:shoot allocation in response to drought survived the growing season, maintained maximum photosynthesis levels, and produced more fruit than genotypes with the greatest root allocation under drought. QTL for gas-exchange and yield components (total biomass or fruit production) had common effects across environments while those for root:shoot were often environment-specific. CONCLUSIONS: Increases in root allocation beyond those needed to survive and maintain favorable water relations came at the cost of fruit production. The environment-specific effects of root:shoot ratio on yield and the differential expression of QTL for this trait across water regimes have important implications for efforts to improve crops for drought resistance.

Selection during crop diversification involves correlated evolution of the circadian clock and ecophysiological traits in Brassica rapa.

Crop selection often leads to dramatic morphological diversification, in which allocation to the harvestable component increases. Shifts in allocation are predicted to impact (as well as rely on) physiological traits; yet, little is known about the evolution of gas exchange and related anatomical features during crop diversification. In Brassica rapa, we tested for physiological differentiation among three crop morphotypes (leaf, turnip, and oilseed) and for correlated evolution of circadian, gas exchange, and phenological traits. We also examined internal and surficial leaf anatomical features and biochemical limits to photosynthesis. Crop types differed in gas exchange; oilseed varieties had higher net carbon assimilation and stomatal conductance relative to vegetable types. Phylogenetically independent contrasts indicated correlated evolution between circadian traits and both gas exchange and biomass accumulation; shifts to shorter circadian period (closer to 24 h) between phylogenetic nodes are associated with higher stomatal conductance, lower photosynthetic rate (when CO2 supply is factored out), and lower biomass accumulation. Crop type differences in gas exchange are also associated with stomatal density, epidermal thickness, numbers of palisade layers, and biochemical limits to photosynthesis. Brassica crop diversification involves correlated evolution of circadian and physiological traits, which is potentially relevant to understanding mechanistic targets for crop improvement.

Genetic architecture, biochemical underpinnings and ecological impact of floral UV patterning.

Floral attraction traits can significantly affect pollinator visitation patterns, but adaptive evolution of these traits may be constrained by correlations with other traits. In some cases, molecular pathways contributing to floral attraction are well characterized, offering the opportunity to explore loci potentially underlying variation among individuals. Here, we quantify the range of variation in floral UV patterning (i.e. UV 'bulls-eye nectar guides) among crop and wild accessions of Brassica rapa. We then use experimental crosses to examine the genetic architecture, candidate loci and biochemical underpinnings of this patterning as well as phenotypic manipulations to test the ecological impact. We find qualitative variation in UV patterning between wild (commonly lacking UV patterns) and crop (commonly exhibiting UV patterns) accessions. Similar to the majority of crops, recombinant inbred lines (RILs) derived from an oilseed crop × WI fast-plant® cross exhibit UV patterns, the size of which varies extensively among genotypes. In RILs, we further observe strong statistical-genetic and QTL correlations within petal morphological traits and within measurements of petal UV patterning; however, correlations between morphology and UV patterning are weak or nonsignificant, suggesting that UV patterning is regulated and may evolve independently of overall petal size. HPLC analyses reveal a high concentration of sinapoyl glucose in UV-absorbing petal regions, which, in concert with physical locations of UV-trait QTLs, suggest a regulatory and structural gene as candidates underlying observed quantitative variation. Finally, insects prefer flowers with UV bulls-eye patterns over those that lack patterns, validating the importance of UV patterning in pollen-limited populations of B. rapa.