Phenotyping Strategies Research Articles

Förster resonance energy transfer-based kinase mutation phenotyping reveals an aberrant facilitation of Ca2+/calmodulin-dependent CaMKIIα activity in de novo mutations related to intellectual disability.

CaMKIIα plays a fundamental role in learning and memory and is a key determinant of synaptic plasticity. Its kinase activity is regulated by the binding of Ca2+/CaM and by autophosphorylation that operates in an activity-dependent manner. Though many mutations in CAMK2A were linked to a variety of neurological disorders, the multiplicity of its functional substrates renders the systematic molecular phenotyping challenging. In this study, we report a new case of CAMK2A P212L, a recurrent mutation, in a patient with an intellectual disability. To quantify the effect of this mutation, we developed a FRET-based kinase phenotyping strategy and measured aberrance in Ca2+/CaM-dependent activation dynamics in vitro and in synaptically connected neurons. CaMKIIα P212L revealed a significantly facilitated Ca2+/CaM-dependent activation in vitro. Consistently, this mutant showed faster activation and more delayed inactivation in neurons. More prolonged kinase activation was also accompanied by a leftward shift in the CaMKIIα input frequency tuning curve. In keeping with this, molecular phenotyping of other reported CAMK2A de novo mutations linked to intellectual disability revealed aberrant facilitation of Ca2+/CaM-dependent activation of CaMKIIα in most cases. Finally, the pharmacological reversal of CAMK2A P212L phenotype in neurons was demonstrated using an FDA-approved NMDA receptor antagonist memantine, providing a basis for targeted therapeutics in CAMK2A-linked intellectual disability. Taken together, FRET-based kinase mutation phenotyping sheds light on the biological impact of CAMK2A mutations and provides a selective, sensitive, quantitative, and scalable strategy for gaining novel insights into the molecular etiology of intellectual disability.

A molecular phenotypic screen reveals that lobetyolin alleviates cardiac dysfunction in 5/6 nephrectomized mice by inhibiting osteopontin

BackgroundCardiovascular diseases are the major cause of mortality in patients with advanced chronic kidney diseases. The predominant abnormality observed among this population is cardiac dysfunction secondary to myocardial remodelings, such as hypertrophy and fibrosis, emphasizing the need to develop potent therapies that maintain cardiac function in patients with end-stage renal disease. AimsTo identify potential compounds and their targets as treatments for cardiorenal syndrome type 4 (CRS) using molecular phenotyping and in vivo/in vitro experiments. MethodsGene expression was assessed using bioinformatics and verified in animal experiments using 5/6 nephrectomized mice (NPM). Based on this information, a molecular phenotyping strategy was pursued to screen potential compounds. Picrosirius red staining, wheat germ agglutinin staining, Echocardiography, immunofluorescence staining, and real-time quantitative PCR (qPCR) were utilized to evaluate the effects of compounds on CRS in vivo. Furthermore, qPCR, immunofluorescence staining and flow cytometry were applied to assess the effects of these compounds on macrophages/cardiac fibroblasts/cardiomyocytes. RNA-Seq analysis was performed to locate the targets of the selected compounds. Western blotting was performed to validate the targets and mechanisms. The reversibility of these effects was tested by overexpressing Osteopontin (OPN). ResultsOPN expression increased more remarkably in individuals with uremia-induced cardiac dysfunction than in other cardiomyopathies. Lobetyolin (LBT) was identified in the compound screen, and it improved cardiac dysfunction and suppressed remodeling in NPM mice. Additionally, OPN modulated the effect of LBT on cardiac dysfunction in vivo and in vitro. Further experiments revealed that LBT suppressed OPN expression via the phosphorylation of c-Jun N-terminal protein kinase (JNK) signaling pathway. ConclusionsLBT improved CRS by inhibiting OPN expression through the JNK pathway. This study is the first to describe a cardioprotective effect of LBT and provides new insights into CRS drug discovery.

Phenotyping strategies for Elsinöe ampelina symptoms in grapevine (Vitis spp.)

AbstractGrapevine anthracnose, caused by Elsinöe ampelina, is a fungal disease with no mapped resistance loci. Thus, this study aimed to evaluate different traits used to phenotype grapevine anthracnose looking for correlated traits and reproducibility during evaluations. Phenotyping was conducted with F1 siblings segregating for resistance to grapevine anthracnose. The progenies were inoculated with Elsinoë ampelina. Leaves, canes and shoots were phenotyped three times. Real severity and number of anthracnose spots were determined from digital photographs. Complementary, the number of spots was estimated using a scale from 0 to 9 and the severity using standard area diagram (SAD) developed for leaves and shoots. The results revealed positive correlation between real and estimated number of anthracnose spots, and the real and estimated severity. However, the number of anthracnose spots did not correlate with severity. The real data from severity and number of spots presented higher variation than the estimated data based on the SAD and scale, respectively. The evaluation strategy based on number of anthracnose spots showed reproducibility in the three independent bioassays, being the most accurate phenotyping strategy for grapevine anthracnose symptoms.

An improved method for cytochrome p450 reaction phenotyping using a sequential qualitative-then-quantitative approach.

Cytochrome P450 reaction phenotyping to determine the fraction of metabolism values (fm) for individual enzymes is a standard study in the evaluation of a new drug. However, there are technical challenges in these studies caused by shortcomings in the selectivity of P450 inhibitors and unreliable scaling procedures for recombinant P450 (rCYP) data. In this investigation, a two-step "qualitative-then-quantitative" approach to P450 reaction phenotyping is described. In the first step, each rCYP is tested qualitatively for potential to generate metabolites. In the second step, selective inhibitors for the P450s identified in step1 are tested for their effects on metabolism using full inhibition curves. Forty-eight drugs were evaluated in step 1 and there were no examples of missing an enzyme important to in vivo clearance. Five drugs (escitalopram, fluvastatin, pioglitazone, propranolol, and risperidone) were selected for full phenotyping in step2 to determine fm values, with findings compared to fm values estimated from single inhibitor concentration data and rCYP with intersystem-extrapolation-factor corrections. The two-step approach yielded fm values for major drug clearing enzymes that are close to those estimated from clinical data: escitalopram and CYP2C19 (0.42 vs 0.36-0.82), fluvastatin and CYP2C9 (0.76 vs 0.76), pioglitazone and CYP2C8 (0.72 vs 0.73), propranolol and CYP2D6 (0.68 vs 0.37-0.56) and risperidone and CYP2D6 (0.60 vs 0.66-0.88). Reaction phenotyping data generated in this fashion should offer better input to physiologically-based pharmacokinetic models for prediction of DDI and impact of genetic polymorphisms on drug clearance. The qualitative-then-quantitative approach is proposed as a replacement to standard reaction phenotyping strategies. Significance Statement P450 reaction phenotyping is important for projecting drug-drug interactions and interpatient variability in drug exposure. However, currently recommended practices can frequently fail to provide reliable estimates of the fractional contributions of specific P450 enzymes (fm) to drug clearance. In this report, we describe a two-step qualitative-then-quantitative reaction phenotyping approach that yields more accurate estimates of fm.

Uncovering the burden of hidden ciliopathies in the 100 000 Genomes Project: a reverse phenotyping approach

BackgroundThe 100 000 Genomes Project (100K) recruited National Health Service patients with eligible rare diseases and cancer between 2016 and 2018. PanelApp virtual gene panels were applied to whole genome...

Variance parameter estimation for age at puberty phenotypes under 2 levels of phenotype censorship

Age at puberty (AGEP) is a moderately heritable trait in cattle that may be predictive of an animal's genetic merit for reproductive success later in life. In addition, under some mating strategies (for example, where mating begins before all animals have attained puberty) animals that attain puberty at a relatively young age will also likely conceive earlier than their herd mates, and thus begin their productive life earlier. Unfortunately, AGEP is challenging to measure because animals must be observed over a period of several months. Our objectives for this study were twofold. The first objective was to produce variance components for AGEP. The second objective was to investigate the implications of a simplified phenotyping strategy for AGEP, when the interval between repeated blood plasma progesterone measures was extended from weekly to monthly, increasing the extent of left, interval, and right censoring. We measured AGEP in a closely monitored population of around 500 Holstein-Friesian heifers, born in 2015 and managed under a seasonal, pasture-based dairy system. Animals were blood tested weekly from approximately 240 to 440 d of age and were deemed to have reached puberty when blood plasma progesterone elevation (>1 ng/mL) was detected in 2 of 3 consecutive blood tests (AGEP_Weekly). To simulate a simplified phenotyping strategy based on monthly herd visits (AGEP_Monthly), we selectively disregarded data from all but 3 blood test events, when animals were around 300, 330, and 360 d of age (standard deviation = 14.5 d). The posterior mean of estimated heritabilities for AGEP_Weekly was 0.54, with a 90% credibility interval (90% CRI) of 0.41 to 0.66, whereas it was 0.44 (90% CRI 0.32 to 0.57) for AGEP_Monthly. The correlation between EBVs for AGEP_Weekly and AGEP_Monthly was 0.87 (90% CRI, 0.84 to 0.89). We conclude that in this population, AGEP is a moderately heritable trait. Further, increasing phenotype censorship from weekly to monthly observations would not have altered the main conclusions of this analysis. Our results support the strategic use of censoring to reduce costs and animal ethics considerations associated with collection of puberty phenotypes.

Genotyping and phenotyping strategies for genetic improvement of meat quality and carcass composition in swine

BackgroundMeat quality and composition traits have become valuable in modern pork production; however, genetic improvement has been slow due to high phenotyping costs. Combining genomic information with multi-trait indirect selection based on cheaper indicator traits is an alternative for continued cost-effective genetic improvement.MethodsData from an ongoing breeding program were used in this study. Phenotypic and genomic information was collected on three-way crossbred and purebred Duroc animals belonging to 28 half-sib families. We applied different methods to assess the value of using purebred and crossbred information (both genomic and phenotypic) to predict expensive-to-record traits measured on crossbred individuals. Estimation of multi-trait variance components set the basis for comparing the different scenarios, together with a fourfold cross-validation approach to validate the phenotyping schemes under four genotyping strategies.ResultsThe benefit of including genomic information for multi-trait prediction depended on the breeding goal trait, the indicator traits included, and the source of genomic information. While some traits benefitted significantly from genotyping crossbreds (e.g., loin intramuscular fat content, backfat depth, and belly weight), multi-trait prediction was advantageous for some traits even in the absence of genomic information (e.g., loin muscle weight, subjective color, and subjective firmness).ConclusionsOur results show the value of using different sources of phenotypic and genomic information. For most of the traits studied, including crossbred genomic information was more beneficial than performing multi-trait prediction. Thus, we recommend including crossbred individuals in the reference population when these are phenotyped for the breeding objective.

Monitoring Lung Injury Severity and Ventilation Intensity during Mechanical Ventilation.

Acute respiratory distress syndrome (ARDS) is a severe form of respiratory failure burden by high hospital mortality. No specific pharmacologic treatment is currently available and its ventilatory management is a key strategy to allow reparative and regenerative lung tissue processes. Unfortunately, a poor management of mechanical ventilation can induce ventilation induced lung injury (VILI) caused by physical and biological forces which are at play. Different parameters have been described over the years to assess lung injury severity and facilitate optimization of mechanical ventilation. Indices of lung injury severity include variables related to gas exchange abnormalities, ventilatory setting and respiratory mechanics, ventilation intensity, and the presence of lung hyperinflation versus derecruitment. Recently, specific indexes have been proposed to quantify the stress and the strain released over time using more comprehensive algorithms of calculation such as the mechanical power, and the interaction between driving pressure (DP) and respiratory rate (RR) in the novel DP multiplied by four plus RR [(4 × DP) + RR] index. These new parameters introduce the concept of ventilation intensity as contributing factor of VILI. Ventilation intensity should be taken into account to optimize protective mechanical ventilation strategies, with the aim to reduce intensity to the lowest level required to maintain gas exchange to reduce the potential for VILI. This is further gaining relevance in the current era of phenotyping and enrichment strategies in ARDS.

Anatomics: High-throughput phenotyping of plant anatomy.

Anatomics is a novel phenotyping strategy focused on high-throughput imaging and quantification of plant anatomy from field-grown plants. Here we highlight its potential applications for genetic and physiological analysis of plant anatomical phenotypes.

Efficacy Assessment and Mechanism Exploration of Haptoglobin Phenotyping and Peptide Supplementation Strategy for Restenosis

Restenosis is a common complication after balloon angioplasty, and the major mechanism is associated with abnormal proliferation, migration and cellular inflammation of vascular smooth muscle cells. However, its therapeutic diagnosis and treatment as well as the fundamental molecular mechanisms have not been fully established. Different haptoglobin (Hp) phenotypes have been clinically confirmed to be related to the incidence of restenosis, and various Hp subunits have also been found to have a variety of cellular activities, which have the potential to inhibit restenosis. Previous studies have shown that patients with Hp 1‐1 phenotype have the least incidence of restenosis. Therefore, the main axis of this study is to evaluate the efficacies and safeties of the Hp subunits as protein drugs for preventing restenosis, as well as exploring their possible regulatory mechanisms. We have constructed the expression vectors of different Hp subunits to understand the regulatory activities of these subunits on critical signaling pathways. Rat carotid artery balloon‐injury model was used to evaluate the efficacies, additive effects, and possible toxicities of potential Hp subunit on preventing restenosis. The outcomes of this project will help us to understand the feasibility, efficacy and safety of the Hp subunit as protein drugs for preventing vascular restenosis.

The Genetic Diagnosis of Ultrarare DEEs: An Ongoing Challenge.

Epileptic encephalopathies (EEs) and developmental and epileptic encephalopathies (DEEs) are a group of severe early-onset neurodevelopmental disorders (NDDs). In recent years, next-generation equencing (NGS) technologies enabled the discovery of numerous genes involved in these conditions. However, more than 50% of patients remained undiagnosed. A major obstacle lies in the high degree of genetic heterogeneity and the wide phenotypic variability that has characterized these disorders. Interpreting a large amount of NGS data is also a crucial challenge. This study describes a dynamic diagnostic procedure used to investigate 17 patients with DEE or EE with previous negative or inconclusive genetic testing by whole-exome sequencing (WES), leading to a definite diagnosis in about 59% of participants. Biallelic mutations caused most of the diagnosed cases (50%), and a pathogenic somatic mutation resulted in 10% of the subjects. The high diagnostic yield reached highlights the relevance of the scientific approach, the importance of the reverse phenotyping strategy, and the involvement of a dedicated multidisciplinary team. The study emphasizes the role of recessive and somatic variants, new genetic mechanisms, and the complexity of genotype–phenotype associations. In older patients, WES results could end invasive diagnostic procedures and allow a more accurate transition. Finally, an early pursued diagnosis is essential for comprehensive care of patients, precision approach, knowledge of prognosis, patient and family planning, and quality of life.

Modeling Trophoblast Cell-Guided Uterine Spiral Artery Transformation in the Rat.

The rat possesses hemochorial placentation with deep intrauterine trophoblast cell invasion and trophoblast-guided uterine spiral artery remodeling, which resembles human placentation. Uterine spiral arteries are extensively remodeled to deliver sufficient supply of maternal blood and nutrients to the developing fetus. Inadequacies in these key processes negatively impact fetal growth and development. Recent innovations in genome editing combined with effective phenotyping strategies have provided new insights into placental development. Application of these research approaches has highlighted both conserved and species-specific features of hemochorial placentation. The review provides foundational information on rat hemochorial placental development and function during physiological and pathological states, especially as related to the invasive trophoblast cell-guided transformation of uterine spiral arteries. Our goal is to showcase the utility of the rat as a model for in vivo mechanistic investigations targeting regulatory events within the uterine-placental interface.

Machine learning predicts cancer subtypes and progression from blood immune signatures.

Clinical adoption of immune checkpoint inhibitors in cancer management has highlighted the interconnection between carcinogenesis and the immune system. Immune cells are integral to the tumour microenvironment and can influence the outcome of therapies. Better understanding of an individual's immune landscape may play an important role in treatment personalisation. Peripheral blood is a readily accessible source of information to study an individual's immune landscape compared to more complex and invasive tumour bioipsies, and may hold immense diagnostic and prognostic potential. Identifying the critical components of these immune signatures in peripheral blood presents an attractive alternative to tumour biopsy-based immune phenotyping strategies. We used two syngeneic solid tumour models, a 4T1 breast cancer model and a CT26 colorectal cancer model, in a longitudinal study of the peripheral blood immune landscape. Our strategy combined two highly accessible approaches, blood leukocyte immune phenotyping and plasma soluble immune factor characterisation, to identify distinguishing immune signatures of the CT26 and 4T1 tumour models using machine learning. Myeloid cells, specifically neutrophils and PD-L1-expressing myeloid cells, were found to correlate with tumour size in both the models. Elevated levels of G-CSF, IL-6 and CXCL13, and B cell counts were associated with 4T1 growth, whereas CCL17, CXCL10, total myeloid cells, CCL2, IL-10, CXCL1, and Ly6Cintermediate monocytes were associated with CT26 tumour development. Peripheral blood appears to be an accessible means to interrogate tumour-dependent changes to the host immune landscape, and to identify blood immune phenotypes for future treatment stratification.

A Simple and Accurate Method Based on a Water-Consumption Model for Phenotyping Soybean Genotypes under Hydric Deficit Conditions

Drought limits crop productivity and reduces yield stability. Drought tolerance as a selection criterion in breeding programs requires the development of high-throughput, precise, and low-cost phenotyping strategies. We developed a mathematical model, based on biological approaches, for evaluating soybean plants’ response to drought under controlled growth conditions. The model describes the kinetics of water consumption of a plant pot substrate system (PPS) with low sampling requirements. The model generated two parameters, t0.5 (time necessary for the PPS to reach half of the maximum amount of evapotranspirable water) and Gw(t0.5) (stomatal conductance [Gw] at t0.5), which determined the water- consumption curve of each genotype. An analysis of the kinetics of water consumption in response to a progressive water deficit in a biparental and breeding population was performed as a preliminary test of the model. A correspondence analysis between the t0.5 and Gw(t0.5) parameters with the genetic structure of the populations shows a genetic association. The phenotyping methodology presented in this work and drought susceptibility in field conditions are discussed based on previous results. This work could be useful for improving the selection of soybean genotypes in relation to their performance under drought conditions.

Novel SLC9A6 Variation in Female Carriers With Intellectual Disability and Atypical Parkinsonism.

Background and ObjectivesVariations in SLC9A6 cause the X-linked neurologic disorder Christianson syndrome in males. Meanwhile, female carriers with SLC9A6 variations may remain asymptomatic or develop intellectual disability, behavioral problems, and psychiatric illnesses. Only a few female carriers have been reported to have associated atypical parkinsonism in late life.MethodsWe present a Japanese family with a novel SLC9A6 variation identified by quad whole-exome sequencing analysis and a reverse phenotyping strategy. The molecular and cellular impacts of the W89R variation in vitro were examined.ResultsThe missense variation (c.265T>C, p.Trp89Arg) in SLC9A6 cosegregated with atypical parkinsonism and intellectual disability in female carriers of this family. The female carriers in this family presented with bradykinesia, rigidity, and tremor, predominately on the right side. We found that the W89R variation changed membrane traffic of NHE6-harboring vesicles, indicating potential involvement in the disease pathogenesis.DiscussionThis study might have revealed an example of a monogenic origin of atypical parkinsonism in females with SLC9A6 variations and draw attention to this understudied female-specific phenotype in clinical practice.

Sleep apnea phenotyping and relationship to disease in a large clinical biobank.

ObjectiveSleep apnea is associated with a broad range of pathophysiology. While electronic health record (EHR) information has the potential for revealing relationships between sleep apnea and associated risk factors and outcomes, practical challenges hinder its use. Our objectives were to develop a sleep apnea phenotyping algorithm that improves the precision of EHR case/control information using natural language processing (NLP); identify novel associations between sleep apnea and comorbidities in a large clinical biobank; and investigate the relationship between polysomnography statistics and comorbid disease using NLP phenotyping.Materials and MethodsWe performed clinical chart reviews on 300 participants putatively diagnosed with sleep apnea and applied International Classification of Sleep Disorders criteria to classify true cases and noncases. We evaluated 2 NLP and diagnosis code-only methods for their abilities to maximize phenotyping precision. The lead algorithm was used to identify incident and cross-sectional associations between sleep apnea and common comorbidities using 4876 NLP-defined sleep apnea cases and 3× matched controls.ResultsThe optimal NLP phenotyping strategy had improved model precision (≥0.943) compared to the use of one diagnosis code (≤0.733). Of the tested diseases, 170 disorders had significant incidence odds ratios (ORs) between cases and controls, 8 of which were confirmed using polysomnography (n = 4544), and 281 disorders had significant prevalence OR between sleep apnea cases versus controls, 41 of which were confirmed using polysomnography data.Discussion and ConclusionAn NLP-informed algorithm can improve the accuracy of case-control sleep apnea ascertainment and thus improve the performance of phenome-wide, genetic, and other EHR analyses of a highly prevalent disorder.

A β-glucuronidase (GUS) Based Bacterial Competition Assay to Assess Fine Differencesin Fitness during Plant Infection.

Competition assays are a simple phenotyping strategy that confront two bacterial strains to evaluate their relative fitness. Because they are more accurate than single-strain growth assays, competition assays can be used to highlight slight differences that would not otherwise be detectable. In the frame of host-pathogens interactions, they can be very useful to study the contribution of individual bacterial genes to bacterial fitness and lead to the identification of new adaptive traits. Here, we describe how to perform such competition assays by taking the example of the model phytopathogenic bacterium Xanthomonas campestris pv. campestris during infection of the mesophyll of its cauliflower host. This phenotypic assay is based on the use of a Competitive Index (CI) that compares the relative abundance of co-inoculated strains before and after inoculation. Since multiplication is a direct proxy for bacterial fitness, the evolution of the ratio between both strains in the mixed population is a direct way to assess differences in fitness in a given environment. In this protocol, we exploit the blue staining of GUS-expressing bacteria to count blue vs. white colonies on plates and estimate the competitiveness of the strains of interest in plant mesophyll.

Cotton row spacing and unmanned aerial vehicle sensors

AbstractThe use of unmanned aerial vehicles (UAVs) to identify the number and area of cotton (Gossypium hirsutum L.) bolls in a field plot can serve as an important high‐throughput phenotyping strategy for predicting seedcotton yield. The objectives of this study were to determine if the prediction of seedcotton yield using a UAV could be improved in skip‐row spacing versus solid‐row spacing and if a genotype × row‐spacing interaction occurs for important yield and fiber traits. A split‐plot design was used with the main plot being row spacing and the sub‐plot consisting of five cotton genotypes. Trials were conducted at three locations in 2017 and 2018. Seedcotton yield, lint yield, lint percent, and fiber qualities were measured for all treatments. In 2018, UAVs with red, green, and blue (RGB) cameras were flown across the fields at two locations to estimate open‐boll count and boll area at the end of the growing season. In general, lint yield and fiber quality were not affected by genotype × row spacing interactions. Seedcotton yield estimations from UAV‐based RGB sensors were improved when cotton was planted on a skip‐row spacing versus a solid row configuration. However, several issues beyond the improvement of seedcotton yield predictions with UAVs need to be considered before research programs use skip‐row spacing.

Smartphone-based digital phenotyping for dry eye toward P4 medicine: a crowdsourced cross-sectional study

Multidimensional integrative data analysis of digital phenotyping is crucial for elucidating the pathologies of multifactorial and heterogeneous diseases, such as the dry eye (DE). This crowdsourced cross-sectional study explored a novel smartphone-based digital phenotyping strategy to stratify and visualize the heterogenous DE symptoms into distinct subgroups. Multidimensional integrative data were collected from 3,593 participants between November 2016 and September 2019. Dimension reduction via Uniform Manifold Approximation and Projection stratified the collected data into seven clusters of symptomatic DE. Symptom profiles and risk factors in each cluster were identified by hierarchical heatmaps and multivariate logistic regressions. Stratified DE subgroups were visualized by chord diagrams, co-occurrence networks, and Circos plot analyses to improve interpretability. Maximum blink interval was reduced in clusters 1, 2, and 5 compared to non-symptomatic DE. Clusters 1 and 5 had severe DE symptoms. A data-driven multidimensional analysis with digital phenotyping may establish predictive, preventive, personalized, and participatory medicine.

Multiple epistatic DNA variants in a single gene affect gene expression in trans.

DNA variants that alter gene expression in trans are important sources of phenotypic variation. Nevertheless, the identity of trans-acting variants remains poorly understood. Single causal variants in several genes have been reported to affect the expression of numerous distant genes in trans. Whether these simple molecular architectures are representative of trans-acting variation is unknown. Here, we studied the large RAS signaling regulator gene IRA2, which contains variants with extensive trans-acting effects on gene expression in the yeast Saccharomyces cerevisiae. We used systematic CRISPR-based genome engineering and a sensitive phenotyping strategy to dissect causal variants to the nucleotide level. In contrast to the simple molecular architectures known so far, IRA2 contained at least seven causal nonsynonymous variants. The effects of these variants were modulated by nonadditive, epistatic interactions. Two variants at the 5'-end affected gene expression and growth only when combined with a third variant that also had no effect in isolation. Our findings indicate that the molecular basis of trans-acting genetic variation may be considerably more complex than previously appreciated.