Fund Black scientists.

Our nationwide network of BME women faculty collectively argue that racial funding disparity by the National Institutes of Health (NIH) remains the most insidious barrier to success of Black faculty in our profession. We thus refocus attention on this critical barrier and suggest solutions on how it can be dismantled.

The sequential direct and indirect effects of mountain uplift, climatic niche and floral trait evolution on diversification dynamics in an Andean plant clade.

Why and how organismal lineages radiate is commonly studied through either assessing abiotic factors (biogeography, geomorphological processes, climate) or biotic factors (traits, interactions). Despite increasing awareness that both abiotic and biotic processes may have important joint effects on diversification dynamics, few attempts have been made to quantify the relative importance and timing of these factors, and their potentially interlinked direct and indirect effects, on lineage diversification. We here combine assessments of historical biogeography, geomorphology, climatic niche, vegetative and floral trait evolution to test whether these factors jointly, or in isolation, explain diversification dynamics of a Neotropical plant clade (Merianieae, Melastomataceae). After estimating ancestral areas and the changes in niche and trait disparity over time, we employ Phylogenetic Path Analyses as a synthesis tool to test eleven hypotheses on the individual direct and indirect effects of these factors on diversification rates. We find strongest support for interlinked effects of colonization of the uplifting Andes during the mid-Miocene and rapid abiotic climatic niche evolution in explaining a burst in diversification rate in Merianieae. Within Andean habitats, later increases in floral disparity allowed for the exploitation of wider pollination niches (i.e., shifts from bee to vertebrate pollinators), but did not affect diversification rates. Our approach of including both vegetative and floral trait evolution, rare in assessments of plant diversification in general, highlights that the evolution of woody habit and larger flowers preceded the colonization of the Andes, but was likely critical in enabling the rapid radiation in montane environments. Overall, and in concert with the idea that ecological opportunity is a key element of evolutionary radiations, our results suggest that a combination of rapid niche evolution and trait shifts were critical for the exploitation of newly available niche space in the Andes in the mid-Miocene. Further, our results emphasize the importance of incorporating both abiotic and biotic factors into the same analytical framework if we aim to quantify the relative and interlinked effects of these processes on diversification.

A systems and computational biology perspective on advancing CAR therapy.

In the recent decades, chimeric antigen receptor (CAR) therapy signaled a new revolutionary approach to cancer treatment. This method seeks to engineer immune cells expressing an artificially designed receptor, which would endue those cells with the ability to recognize and eliminate tumor cells. While some CAR therapies received FDA approval and others are subject to clinical trials, many aspects of their workings remain elusive. Techniques of systems and computational biology have been frequently employed to explain the operating principles of CAR therapy and suggest further design improvements. In this review, we sought to provide a comprehensive account of those efforts. Specifically, we discuss various computational models of CAR therapy ranging in scale from organismal to molecular. Then, we describe the molecular and functional properties of costimulatory domains frequently incorporated in CAR structure. Finally, we describe the signaling cascades by which those costimulatory domains elicit cellular response against the target. We hope that this comprehensive summary of computational and experimental studies will further motivate the use of systems approaches in advancing CAR therapy.

Flux sampling in genome-scale metabolic modeling of microbial communities.

BACKGROUND: Microbial communities play a crucial role in ecosystem function through metabolic interactions. Genome-scale modeling is a promising method to understand these interactions and identify strategies to optimize the community. Flux balance analysis (FBA) is most often used to predict the flux through all reactions in a genome-scale model; however, the fluxes predicted by FBA depend on a user-defined cellular objective. Flux sampling is an alternative to FBA, as it provides the range of fluxes possible within a microbial community. Furthermore, flux sampling can capture additional heterogeneity across a population, especially when cells exhibit sub-maximal growth rates. RESULTS: In this study, we simulate the metabolism of microbial communities and compare the metabolic characteristics found with FBA and flux sampling. With sampling, we find significant differences in the predicted metabolism, including an increase in cooperative interactions and pathway-specific changes in predicted flux. CONCLUSIONS: Our results suggest the importance of sampling-based approaches to evaluate metabolic interactions. Furthermore, we emphasize the utility of flux sampling in quantitatively studying interactions between cells and organisms.

Stable Interstrand Cross-Links Generated from the Repair of 1,N6-Ethenoadenine in DNA by α-Ketoglutarate/Fe(II)-Dependent Dioxygenase ALKBH2.

DNA cross-links severely challenge replication and transcription in cells, promoting senescence and cell death. In this paper, we report a novel type of DNA interstrand cross-link (ICL) produced as a side product during the attempted repair of 1,N6-ethenoadenine (εA) by human α-ketoglutarate/Fe(II)-dependent enzyme ALKBH2. This stable/nonreversible ICL was characterized by denaturing polyacrylamide gel electrophoresis analysis and quantified by high-resolution LC-MS in well-matched and mismatched DNA duplexes, yielding 5.7% as the highest level for cross-link formation. The binary lesion is proposed to be generated through covalent bond formation between the epoxide intermediate of εA repair and the exocyclic N6-amino group of adenine or the N4-amino group of cytosine residues in the complementary strand under physiological conditions. The cross-links occur in diverse sequence contexts, and molecular dynamics simulations rationalize the context specificity of cross-link formation. In addition, the cross-link generated from attempted εA repair was detected in cells by highly sensitive LC-MS techniques, giving biological relevance to the cross-link adducts. Overall, a combination of biochemical, computational, and mass spectrometric methods was used to discover and characterize this new type of stable cross-link both in vitro and in human cells, thereby uniquely demonstrating the existence of a potentially harmful ICL during DNA repair by human ALKBH2.

Incomplete lineage sorting and hybridization underlie tree discordance in Petunia and related genera (Petunieae, Solanaceae).

Despite the overarching history of species divergence, phylogenetic studies often reveal distinct topologies across regions of the genome. The sources of these gene tree discordances are variable, but incomplete lineage sorting (ILS) and hybridization are among those with the most biological importance. Petunia serves as a classic system for studying hybridization in the wild. While field studies suggest that hybridization is frequent, the extent of reticulation within Petunia and its closely related genera has never been examined from a phylogenetic perspective. In this study, we used transcriptomic data from 11 Petunia, 16 Calibrachoa, and 10 Fabiana species to illuminate the relationships between these species and investigate whether hybridization played a significant role in the diversification of the clade. We inferred that gene tree discordance within genera is linked to hybridization events along with high levels of ILS due to their rapid diversification. Moreover, network analyses estimated deeper hybridization events between Petunia and Calibrachoa, genera that have different chromosome numbers. Although these genera cannot hybridize at the present time, ancestral hybridization could have played a role in their parallel radiations, as they share the same habitat and life history.

A field guide to cultivating computational biology.

Evolving in sync with the computation revolution over the past 30 years, computational biology has emerged as a mature scientific field. While the field has made major contributions toward improving scientific knowledge and human health, individual computational biology practitioners at various institutions often languish in career development. As optimistic biologists passionate about the future of our field, we propose solutions for both eager and reluctant individual scientists, institutions, publishers, funding agencies, and educators to fully embrace computational biology. We believe that in order to pave the way for the next generation of discoveries, we need to improve recognition for computational biologists and better align pathways of career success with pathways of scientific progress. With 10 outlined steps, we call on all adjacent fields to move away from the traditional individual, single-discipline investigator research model and embrace multidisciplinary, data-driven, team science.

Modeling the heterogeneous apoptotic response of caspase-mediated signaling in tumor cells.

Resisting apoptosis is a hallmark of cancer. For this reason, it may be possible to force cancer cells to die by targeting components along the apoptotic signaling pathway. However, apoptosis signaling is challenging to understand due to dynamic and complex behaviors of ligands, receptors, and intracellular signaling components in response to cancer therapy. In this work, we forecast the apoptotic response based on the combined impact of these features. We expanded a previously established mathematical model of caspase-mediated apoptosis to include extracellular activation and receptor dynamics. In addition, three potential threshold values of caspase-3 necessary for the activation of apoptosis were selected to forecast which cells become apoptotic over time. We first vary ligand and receptor levels with the number of intracellular signaling proteins remaining consistent. Then, we vary the intracellular protein molecules in each simulated tumor cell to forecast the response of a heterogeneous population. By leveraging the benefits of computational modeling, we investigate the combined effect of several factors on the onset of apoptosis. This work provides quantitative insights for how the apoptotic signaling response can be forecasted, and precisely triggered, amongst heterogeneous cells via extracellular activation.

Calibrating agent-based models to tumor images using representation learning.

Agent-based models (ABMs) have enabled great advances in the study of tumor development and therapeutic response, allowing researchers to explore the spatiotemporal evolution of the tumor and its microenvironment. However, these models face serious drawbacks in the realm of parameterization - ABM parameters are typically set individually based on various data and literature sources, rather than through a rigorous parameter estimation approach. While ABMs can be fit to simple time-course data (such as tumor volume), that type of data loses the spatial information that is a defining feature of ABMs. While tumor images provide spatial information, it is exceedingly difficult to compare tumor images to ABM simulations beyond a qualitative visual comparison. Without a quantitative method of comparing the similarity of tumor images to ABM simulations, a rigorous parameter fitting is not possible. Here, we present a novel approach that applies neural networks to represent both tumor images and ABM simulations as low dimensional points, with the distance between points acting as a quantitative measure of difference between the two. This enables a quantitative comparison of tumor images and ABM simulations, where the distance between simulated and experimental images can be minimized using standard parameter-fitting algorithms. Here, we describe this method and present two examples to demonstrate the application of the approach to estimate parameters for two distinct ABMs. Overall, we provide a novel method to robustly estimate ABM parameters.

Fluoride-Ion Donor Properties of AsF5.

Arsenic pentafluoride undergoes ligand-induced autoionization in the presence of 1,10-phenanthroline (phen) in a SO2ClF solution to form the donor-stabilized [AsF4(phen)][AsF6] salt. Reacting [AsF4(phen)][AsF6] with the strong Lewis acid SbF5·SO2 yields the mixed arsenic-antimony salt [AsF4(phen)][Sb2F11]. These salts are the first examples of crystallographically characterized donor-stabilized [AsF4]+ cations. The analogous reaction of AsF5 and 2,2'-bipyridine (bipy) does not result in autoionization but leads to the formation of the neutral 2:1 adduct (AsF5)2·bipy. The gas-phase and solution fluoride-ion affinities of [AsF4]+ and [SbF4]+ were calculated, revealing them to be incredibly strong Lewis acids. Density functional theory calculations and natural bond orbital analysis show that significant electron-pair donation from phen to the As center in [AsF4(phen)]+ occurs and quenches the extreme electrophilicity of the [AsF4]+ cation.

Is Metal Stabilization of the Leaving Group Required or Can Lysine Facilitate Phosphodiester Bond Cleavage in Nucleic Acids? A Computational Study of EndoV.

Endonuclease V (EndoV) is a single-metal-dependent enzyme that repairs deaminated DNA nucleobases in cells by cleaving the phosphodiester bond, and this enzyme has proven to be a powerful tool in biotechnology and medicine. The catalytic mechanism used by EndoV must be understood to design new disease detection and therapeutic solutions and further exploit the enzyme in interdisciplinary applications. This study has used a mixed molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) approach to compare eight distinct catalytic pathways and provides the first proposed mechanism for bacterial EndoV. The calculations demonstrate that mechanisms involving either direct or indirect metal coordination to the leaving group of the substrate previously proposed for other nucleases are unlikely for EndoV, regardless of the general base (histidine, aspartate, and substrate phosphate moiety). Instead, distinct catalytic pathways are characterized for EndoV that involve K139 stabilizing the leaving group, a metal-coordinated water stabilizing the transition structure, and either H214 or a substrate phosphate group activating the water nucleophile. In silico K139A and H214A mutational results support the newly proposed roles of these residues. Although this is a previously unseen combination of general base, general acid, and metal-binding architecture for a one-metal-dependent endonuclease, our proposed catalytic mechanisms are fully consistent with experimental kinetic, structural, and mutational data. In addition to substantiating a growing body of literature, suggesting that one metal is enough to catalyze P-O bond cleavage in nucleic acids, this new fundamental understanding of the catalytic function will promote the exploration of new and improved applications of EndoV.

Elucidation of the catalytic mechanism of a single-metal dependent homing endonuclease using QM and QM/MM approaches: the case study of I-PpoI.

Homing endonucleases (HEs) are highly specific DNA cleaving enzymes, with I-PpoI having been suggested to use a single metal to accelerate phosphodiester bond cleavage. Although an I-PpoI mechanism has been proposed based on experimental structural data, no consensus has been reached regarding the roles of the metal or key active site amino acids. This study uses QM cluster and QM/MM calculations to provide atomic-level details of the I-PpoI catalytic mechanism. Minimal QM cluster and large-scale QM/MM models demonstrate that the experimentally-proposed pathway involving direct Mg2+ coordination to the substrate coupled with leaving group protonation through a metal-activated water is not feasible due to an inconducive I-PpoI active site alignment. Despite QM cluster models of varying size uncovering a pathway involving leaving group protonation by a metal-activated water, indirect (water-mediated) metal coordination to the substrate is required to afford this pathway, which renders this mechanism energetically infeasible. Instead, QM cluster models reveal that the preferred pathway involves direct Mg2+-O3' coordination to stabilize the charged substrate and assist leaving group departure, while H98 activates the water nucleophile. These calculations also underscore that both catalytic residues that directly interact with the substrate and secondary amino acids that position or stabilize these residues are required for efficient catalysis. QM/MM calculations on the solvated enzyme-DNA complex verify the preferred mechanism, which is fully consistent with experimental kinetic, structural, and mutational data. The fundamental understanding of the I-PpoI mechanism of action, gained from the present work can be used to further explore potential uses of this enzyme in biotechnology and medicine, and direct future computational investigations of other members of the understudied HE family.

The electronic frailty index and outcomes in patients with myocardial infarction.

BACKGROUND: Frailty is increasingly present in patients with acute myocardial infarction. The electronic Frailty Index (eFI) is a validated method of identifying vulnerable older patients in the community from routine primary care data. Our aim was to assess the relationship between the eFI and outcomes in older patients hospitalised with acute myocardial infarction. STUDY DESIGN AND SETTING: Retrospective cohort study using the DataLoch Heart Disease Registry comprising consecutive patients aged 65 years or over hospitalised with a myocardial infarction between October 2013 and March 2021. METHODS: Patients were classified as fit, mild, moderate, or severely frail based on their eFI score. Cox-regression analysis was used to determine the association between frailty category and all-cause mortality. RESULTS: In 4670 patients (median age 77 years [71-84], 43% female), 1865 (40%) were classified as fit, with 1699 (36%), 798 (17%) and 308 (7%) classified as mild, moderate and severely frail, respectively. In total, 1142 patients died within 12 months of which 248 (13%) and 147 (48%) were classified as fit and severely frail, respectively. After adjustment, any degree of frailty was associated with an increased risk of all-cause death with the risk greatest in the severely frail (reference = fit, adjusted hazard ratio 2.87 [95% confidence intervals 2.24 to 3.66]). CONCLUSION: The eFI identified patients at high risk of death following myocardial infarction. Automatic calculation within administrative data is feasible and could provide a low-cost method of identifying vulnerable older patients on hospital presentation.

Impact of surgical lung biopsy on lung function and survival in patients with idiopathic pulmonary fibrosis in a multi-centre registry cohort.

BACKGROUND AND OBJECTIVE: Establishing an accurate and timely diagnosis of idiopathic pulmonary fibrosis (IPF) is essential for appropriate management and prognostication. In some cases, surgical lung biopsy (SLB) is performed but carries non-negligible risk. The objective of this retrospective study was to determine if SLB is associated with accelerated lung function decline in patients with IPF using the Canadian Registry for Pulmonary Fibrosis. METHODS: Linear mixed models and Cox proportional hazards regression models were used to compare decline in forced vital capacity (FVC)%, diffusion capacity of the lung (DLCO%) and risk of death or lung transplantation between SLB and non-SLB patients. Adjustments were made for baseline age, sex, smoking history, antifibrotic use, and lung function. A similar analysis compared lung function changes 12 months pre- and post-SLB. RESULTS: A total of 81 SLB patients and 468 non-SLB patients were included. In the SLB group, the post-biopsy annual FVC% decline was 2.0% (±0.8) in unadjusted, and 2.1% (±0.8) in adjusted models. There was no difference in FVC% decline, DLCO% decline, or time to death or lung transplantation between the two groups, in adjusted or unadjusted models (all p-values >0.07). In the pre-post SLB group, no differences were identified in FVC% decline in unadjusted or adjusted models (p = 0.07 for both). CONCLUSION: No association between SLB and lung function decline or risk of death or lung transplantation was identified in this multi-centre study of patients with IPF.

Troponin in early presenters to rule out myocardial infarction.

AIMS: Whether a single cardiac troponin measurement can safely rule out myocardial infarction in patients presenting within a few hours of symptom onset is uncertain. The study aim was to assess the performance of troponin in early presenters. METHODS AND RESULTS: In patients with possible myocardial infarction, the diagnostic performance of a single measurement of high-sensitivity cardiac troponin I at presentation was evaluated and externally validated in those tested ≤3, 4-12, and >12 h from symptom onset. The limit-of-detection (2 ng/L), rule-out (5 ng/L), and sex-specific 99th centile (16 ng/L in women; 34 ng/L in men) thresholds were compared. In 41 103 consecutive patients [60 (17) years, 46% women], 12 595 (31%) presented within 3 h, and 3728 (9%) had myocardial infarction. In those presenting ≤3 h, a threshold of 2 ng/L had greater sensitivity and negative predictive value [99.4% (95% confidence interval 99.2%-99.5%) and 99.7% (99.6%-99.8%)] compared with 5 ng/L [96.5% (96.2%-96.8%) and 99.3% (99.1%-99.4%)]. In those presenting ≥3 h, the sensitivity and negative predictive value were similar for both thresholds. The sensitivity of the 99th centile was low in early and late presenters at 71.4% (70.6%-72.2%) and 92.5% (92.0%-93.0%), respectively. Findings were consistent in an external validation cohort of 7088 patients. CONCLUSION: In early presenters, a single measurement of high-sensitivity cardiac troponin I below the limit of detection may facilitate the safe rule out of myocardial infarction. The 99th centile should not be used to rule out myocardial infarction at presentation even in those presenting later following symptom onset.

Soil data recency: The foundation for harmonizing soil data across time.

Sustainable soil resource management depends on reliable soil information, often derived from 'legacy soil data' or a combination of old and new soil data. However, the task of harmonizing soil data collected at different times remains a largely unexplored in the literature. Addressing this challenge requires incorporating the temporal dimension into mathematical and statistical models for spatio-temporal soil studies. This study aimed to create a comprehensive framework for harmonizing soil data across various time. We assessed the integration of historical and recent soil data, ranging from 4 to 48 years old data, using soil data recency analysis. To achieve this, we introduced an 'age of data' attribute, calculating the time difference between soil survey years and the present (e.g., 2022). We applied three machine learning models - Decision Trees (DT), Random Forest (RF), Gradient Boosting (GBM) - to a dataset containing 6339 sites and 28,149 depth-harmonized layers. The results consistently demonstrated robust performance across models, RF outperforming with an R-squared value of 0.99, RMSE of 1.41, and a concordance of 0.97. Similarly, DT and GBM also showed strong predictive power. Terrain-derived environmental covariates played a more important role than land use and land cover (LULC) change in predicting soil data recency. While LULC change showed soil organic carbon concentration variability across the different depths, it was a less important factor. Anthropogenic factors, such as LULC change and normalized difference vegetation index (NDVI), were not primary determinants of soil data recency. Variations in soil depth had no impact on predicting soil data recency. This study validated that terrain-derived covariates, especially elevation factors, effectively explain the quality of older soil data when predicting current soil attributes using the soil data recency concept. This approach has the potential to enhance real-time estimates, such as carbon budgets, and we emphasize its importance in global earth system models.

Distinctive Formation of a DNA-Protein Cross-Link during the Repair of DNA Oxidative Damage: Insights into Human Disease from MD Simulations and QM/MM Calculations.

Reactive oxygen species damage DNA and result in health issues. The major damage product, 8-oxo-7,8-dihydroguanine (8oG), is repaired by human adenine DNA glycosylase homologue (MUTYH). Although MUTYH misfunction is associated with a genetic disorder called MUTYH-associated polyposis (MAP) and MUTYH is a potential target for cancer drugs, the catalytic mechanism required to develop disease treatments is debated in the literature. This study uses molecular dynamics simulations and quantum mechanics/molecular mechanics techniques initiated from DNA-protein complexes that represent different stages of the repair pathway to map the catalytic mechanism of the wild-type MUTYH bacterial homologue (MutY). This multipronged computational approach characterizes a DNA-protein cross-linking mechanism that is consistent with all previous experimental data and is a distinct pathway across the broad class of monofunctional glycosylase repair enzymes. In addition to clarifying how the cross-link is formed, accommodated by the enzyme, and hydrolyzed for product release, our calculations rationalize why cross-link formation is favored over immediate glycosidic bond hydrolysis, the accepted mechanism for all other monofunctional DNA glycosylases to date. Calculations on the Y126F mutant MutY highlight critical roles for active site residues throughout the reaction, while investigation of the N146S mutant rationalizes the connection between the analogous N224S MUTYH mutation and MAP. In addition to furthering our knowledge of the chemistry associated with a devastating disorder, the structural information gained about the distinctive MutY mechanism compared to other repair enzymes represents an important step for the development of specific and potent small-molecule inhibitors as cancer therapeutics.

Transcription Factors Evolve Faster Than Their Structural Gene Targets in the Flavonoid Pigment Pathway.

Dissecting the relationship between gene function and substitution rates is key to understanding genome-wide patterns of molecular evolution. Biochemical pathways provide powerful systems for investigating this relationship because the functional role of each gene is often well characterized. Here, we investigate the evolution of the flavonoid pigment pathway in the colorful Petunieae clade of the tomato family (Solanaceae). This pathway is broadly conserved in plants, both in terms of its structural elements and its MYB, basic helix-loop-helix, and WD40 transcriptional regulators, and its function has been extensively studied, particularly in model species of petunia. We built a phylotranscriptomic data set for 69 species of Petunieae to infer patterns of molecular evolution across pathway genes and across lineages. We found that transcription factors exhibit faster rates of molecular evolution (dN/dS) than their targets, with the highly specialized MYB genes evolving fastest. Using the largest comparative data set to date, we recovered little support for the hypothesis that upstream enzymes evolve slower than those occupying more downstream positions, although expression levels do predict molecular evolutionary rates. Although shifts in floral pigmentation were only weakly related to changes affecting coding regions, we found a strong relationship with the presence/absence patterns of MYB transcripts. Intensely pigmented species express all three main MYB anthocyanin activators in petals, whereas pale or white species express few or none. Our findings reinforce the notion that pathway regulators have a dynamic history, involving higher rates of molecular evolution than structural components, along with frequent changes in expression during color transitions.

Opposing Patterns of Altitude-Driven Pollinator Turnover in the Tropical and Temperate Americas.

AbstractAbiotic factors (e.g., temperature, precipitation) vary markedly along elevational gradients and differentially affect major groups of pollinators. Ectothermic bees, for example, are impeded in visiting flowers by cold and rainy conditions common at high elevations, while endothermic hummingbirds may continue foraging under such conditions. Despite the possibly far-reaching effects of the abiotic environment on plant-pollinator interactions, we know little about how these factors play out at broad ecogeographic scales. We address this knowledge gap by investigating how pollination systems vary across elevations in 26 plant clades from the Americas. Specifically, we explore Cruden's 1972 hypothesis that the harsh montane environment drives a turnover from insect to vertebrate pollination at higher elevations. We compared the elevational distribution and bioclimatic attributes for a total of 2,232 flowering plants and found that Cruden's hypothesis holds only in the tropics. Above 30°N and below 30°S, plants pollinated by vertebrates (mostly hummingbirds) tend to occur at lower elevations than those pollinated by insects. We hypothesize that this latitudinal transition is due to the distribution of moist, forested habitats favored by vertebrate pollinators, which are common at high elevations in the tropics but not in the temperate Americas.

Evolutionary walks through flower colour space driven by gene expression in Petunia and allies (Petunieae).

The structure and function of biochemical and developmental pathways determine the range of accessible phenotypes, which are the substrate for evolutionary change. Accordingly, we expect that observed phenotypic variation across species is strongly influenced by pathway structure, with different phenotypes arising due to changes in activity along pathway branches. Here, we use flower colour as a model to investigate how the structure of pigment pathways shapes the evolution of phenotypic diversity. We focus on the phenotypically diverse Petunieae clade in the nightshade family, which contains ca 180 species of Petunia and related genera, as a model to understand how flavonoid pathway gene expression maps onto pigment production. We use multivariate comparative methods to estimate co-expression relationships between pathway enzymes and transcriptional regulators, and then assess how expression of these genes relates to the major axes of variation in floral pigmentation. Our results indicate that coordinated shifts in gene expression predict transitions in both total anthocyanin levels and pigment type, which, in turn, incur trade-offs with the production of UV-absorbing flavonol compounds. These findings demonstrate that the intrinsic structure of the flavonoid pathway and its regulatory architecture underlies the accessibility of pigment phenotypes and shapes evolutionary outcomes for floral pigment production.