Discrete Phenotypes Research Articles

Novel adverse outcome pathways revealed by chemical genetics in a developing marine fish.

Crude oil spills are a worldwide ocean conservation threat. Fish are particularly vulnerable to the oiling of spawning habitats, and crude oil causes severe abnormalities in embryos and larvae. However, the underlying mechanisms for these developmental defects are not well understood. Here, we explore the transcriptional basis for four discrete crude oil injury phenotypes in the early life stages of the commercially important Atlantic haddock (Melanogrammus aeglefinus). These include defects in (1) cardiac form and function, (2) craniofacial development, (3) ionoregulation and fluid balance, and (4) cholesterol synthesis and homeostasis. Our findings suggest a key role for intracellular calcium cycling and excitation-transcription coupling in the dysregulation of heart and jaw morphogenesis. Moreover, the disruption of ionoregulatory pathways sheds new light on buoyancy control in marine fish embryos. Overall, our chemical-genetic approach identifies initiating events for distinct adverse outcome pathways and novel roles for individual genes in fundamental developmental processes.

Discrete phenotypes are not underpinned by genome-wide genetic differentiation in the squat lobster Munida gregaria (Crustacea: Decapoda: Munididae): a multi-marker study covering the Patagonian shelf.

BackgroundDNA barcoding has demonstrated that many discrete phenotypes are in fact genetically distinct (pseudo)cryptic species. Genetically identical, isogenic individuals, however, can also express similarly different phenotypes in response to a trigger condition, e.g. in the environment. This alternative explanation to cryptic speciation often remains untested because it requires considerable effort to reject the hypothesis that the observed underlying genetic homogeneity of the different phenotypes may be trivially caused by too slowly evolving molecular markers.The widespread squat lobster Munida gregaria comprises two discrete ecotypes, gregaria s. str. and subrugosa, which were long regarded as different species due to marked differences in morphological, ecological and behavioral traits. We studied the morphometry and genetics of M. gregaria s. l. and tested (1) whether the phenotypic differences remain stable after continental-scale sampling and inclusion of different life stages, (2) and whether each phenotype is underpinned by a specific genotype.ResultsA total number of 219 gregaria s. str. and subrugosa individuals from 25 stations encompassing almost entire range in South America were included in morphological and genetic analyses using nine unlinked hypervariable microsatellites and new COI sequences. Results from the PCA and using discriminant functions demonstrated that the morphology of the two forms remains discrete. The mitochondrial data showed a shallow, star-like haplotype network and complete overlap of genetic distances within and among ecotypes. Coalescent-based species delimitation methods, PTP and GMYC, coherently suggested that haplotypes of both ecotypes forms a single species. Although all microsatellite markers possess sufficient genetic variation, AMOVA, PCoA and Bayesian clustering approaches revealed no genetic clusters corresponding to ecotypes or geographic units across the entire South-American distribution. No evidence of isolation-by-distance could be detected for this species in South America.ConclusionsDespite their pronounced bimodal morphologies and different lifestyles, the gregaria s. str. and subrugosa ecotypes form a single, dimorphic species M. gregaria s. l.. Based on adequate geographic coverage and multiple independent polymorphic loci, there is no indication that each phenotype may have a unique genetic basis, leaving phenotypic plasticity or localized genomic islands of speciation as possible explanations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12862-016-0836-4) contains supplementary material, which is available to authorized users.

Contrasting activity budgets of alternative reproductive tactics in male striped mice

To maximize their fitness, individuals of one sex can display discrete reproductive phenotypes, called alternative reproductive tactics (ARTs). Individuals following ARTs show behavioural variation, which might result in differences in energy intake and expenditure. However, few studies have compared activity budgets and non-sexual behaviour of individuals following ARTs in nature. We studied male African striped mice Rhabdomys pumilio, which can follow three ARTs: (1) breeding male of a group of females; (2) philopatrics remaining in their natal group; or (3) solitary living roamers. We predicted that each tactic is characterized by its specific activity budget, representing alternative energy trade-offs. We conducted focal animal observations on 70 males following ARTs. Roamers had higher travelling rates than philopatrics, and breeders had larger daily range sizes compared to philopatrics but not roamers. Philopatrics had higher foraging rates than breeders and showed more socio-positive behaviour than roamers. Breeders and philopatrics were in their nest more often than roamers, potentially engaging in social interactions with other group members. Roamers were chased off more often than breeders, but the three tactics did not differ concerning rates of socio-negative behaviour. Overall, philopatrics allocated their time towards behaviours that would increase body mass and survival probability, which could improve the probability to switch to a tactic of higher reproductive success. In contrast, breeders and roamers allocated their time towards behaviours that would increase their chances to mate. In conclusion, following ARTs results in contrasting activity budgets that reflect the differences in reproductive behaviours observed between tactics.

Novel gene-brain structure relationships in psychotic disorder revealed using parallel independent component analyses

BackgroundSchizophrenia, schizoaffective disorder, and psychotic bipolar disorder overlap with regard to symptoms, structural and functional brain abnormalities, and genetic risk factors. Neurobiological pathways connecting genes to clinical phenotypes across the spectrum from schizophrenia to psychotic bipolar disorder remain largely unknown. MethodsWe examined the relationship between structural brain changes and risk alleles across the psychosis spectrum in the multi-site Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) cohort. Regional MRI brain volumes were examined in 389 subjects with a psychotic disorder (139 schizophrenia, 90 schizoaffective disorder, and 160 psychotic bipolar disorder) and 123 healthy controls. 451,701 single-nucleotide polymorphisms were screened and processed using parallel independent component analysis (para-ICA) to assess associations between genes and structural brain abnormalities in probands. Results482 subjects were included after quality control (364 individuals with psychotic disorder and 118 healthy controls). Para-ICA identified four genetic components including several risk genes already known to contribute to schizophrenia and bipolar disorder and revealed three structural components that showed overlapping relationships with the disease risk genes across the three psychotic disorders. Functional ontologies representing these gene clusters included physiological pathways involved in brain development, synaptic transmission, and ion channel activity. ConclusionsHeritable brain structural findings such as reduced cortical thickness and surface area in probands across the psychosis spectrum were associated with somewhat distinct genes related to putative disease pathways implicated in psychotic disorders. This suggests that brain structural alterations might represent discrete psychosis intermediate phenotypes along common neurobiological pathways underlying disease expression across the psychosis spectrum.

Informatics-Based Discovery of Disease-Associated Immune Profiles.

Advances in flow and mass cytometry are enabling ultra-high resolution immune profiling in mice and humans on an unprecedented scale. However, the resulting high-content datasets challenge traditional views of cytometry data, which are both limited in scope and biased by pre-existing hypotheses. Computational solutions are now emerging (e.g., Citrus, AutoGate, SPADE) that automate cell gating or enable visualization of relative subset abundance within healthy versus diseased mice or humans. Yet these tools require significant computational fluency and fail to show quantitative relationships between discrete immune phenotypes and continuous disease variables. Here we describe a simple informatics platform that uses hierarchical clustering and nearest neighbor algorithms to associate manually gated immune phenotypes with clinical or pre-clinical disease endpoints of interest in a rapid and unbiased manner. Using this approach, we identify discrete immune profiles that correspond with either weight loss or histologic colitis in a T cell transfer model of inflammatory bowel disease (IBD), and show distinct nodes of immune dysregulation in the IBDs, Crohn’s disease and ulcerative colitis. This streamlined informatics approach for cytometry data analysis leverages publicly available software, can be applied to manually or computationally gated cytometry data, is suitable for any clinical or pre-clinical setting, and embraces ultra-high content flow and mass cytometry as a discovery engine.

Regulation of macrophage polarization and plasticity by complex activation signals.

Macrophages are versatile cells of the immune system that play an important role in both advancing and resolving inflammation. Macrophage activation has been described as a continuum, and different stimuli lead to M1, M2, or mixed phenotypes. In addition, macrophages expressing markers associated with both M1 and M2 function are observed in vivo. Using flow cytometry, we examine how macrophage populations respond to combined M1 and M2 activation signals, presented either simultaneously or sequentially. We demonstrate that macrophages exposed to a combination of LPS, IFN-γ, IL-4, and IL-13 acquire a mixed activation state, with individual cells expressing both M1 marker CD86 and M2 marker CD206 instead of polarizing to discrete phenotypes. Over time, co-stimulated macrophages lose expression of CD86 and display increased expression of CD206. In addition, we find that exposure to LPS/IFN-γ potentiates the subsequent response to IL-4/IL-13, whereas pre-polarization with IL-4/IL-13 inhibits the response to LPS/IFN-γ. Mathematical modeling of candidate regulatory networks indicates that a complex inter-dependence of M1- and M2-associated pathways underlies macrophage activation. Specifically, a mutual inhibition motif was not by itself sufficient to reproduce the temporal marker expression data; incoherent feed-forward of M1 activation as well as both inhibition and activation of M2 by M1 were required. Together these results corroborate a continuum model of macrophage activation and demonstrate that phenotypic markers evolve with time and with exposure to complex signals.

Functional Genetic Screen to Identify Interneurons Governing Behaviorally Distinct Aspects of Drosophila Larval Motor Programs.

Drosophila larval crawling is an attractive system to study rhythmic motor output at the level of animal behavior. Larval crawling consists of waves of muscle contractions generating forward or reverse locomotion. In addition, larvae undergo additional behaviors, including head casts, turning, and feeding. It is likely that some neurons (e.g., motor neurons) are used in all these behaviors, but the identity (or even existence) of neurons dedicated to specific aspects of behavior is unclear. To identify neurons that regulate specific aspects of larval locomotion, we performed a genetic screen to identify neurons that, when activated, could elicit distinct motor programs. We used 165 Janelia CRM-Gal4 lines—chosen for sparse neuronal expression—to ectopically express the warmth-inducible neuronal activator TrpA1, and screened for locomotor defects. The primary screen measured forward locomotion velocity, and we identified 63 lines that had locomotion velocities significantly slower than controls following TrpA1 activation (28°). A secondary screen was performed on these lines, revealing multiple discrete behavioral phenotypes, including slow forward locomotion, excessive reverse locomotion, excessive turning, excessive feeding, immobile, rigid paralysis, and delayed paralysis. While many of the Gal4 lines had motor, sensory, or muscle expression that may account for some or all of the phenotype, some lines showed specific expression in a sparse pattern of interneurons. Our results show that distinct motor programs utilize distinct subsets of interneurons, and provide an entry point for characterizing interneurons governing different elements of the larval motor program.

Male disguised females: costs and benefits of female‐limited dimorphism in a butterfly

1. In polymorphic species, two or more discrete phenotypes co‐occur simultaneously. Sex‐limited polymorphism is a particular case of polymorphism, in which several discrete morphs coexist within one of the two sexes only. Several hypotheses were proposed to explain the existence and the maintenance of sex‐limited polymorphism in insects: (i) the morphs have similar fitness, such as similar survival and expected fecundity, and their frequencies vary randomly (i.e. the null hypothesis); (ii) harassment by males is reduced towards the less common female morph, in this case andromorph females (i.e. the male mimicry and learned mate recognition hypotheses); (iii) morphs differ in predation risk (i.e. the predation hypothesis); or (iv) morphs differ in thermoregulation ability (i.e. the thermoregulation hypothesis).2. Field observations and experiments were employed to compare the relative support of these hypotheses using dimorphic females of the bog fritillary butterfly. Differences were detected between morphs in survival, fecundity, harassment by males, predation pressure and thermal properties, thereby rejecting the null hypothesis.3. The lifestyle of both morphs is associated with different costs and benefits, with advantages in daily survival and precocious emergence for the gynomorph females, and advantages in fecundity, predation and male harassment for the andromorph females. Besides, as the bog fritillary butterfly is protandrous (i.e. males emerge before females), the longer development of andromorph females puts them at risk of emerging when all the males are dead. The results raise the question as to which mechanisms control the ontogenetic pathways driving the production of the two morphs (i.e. genetic polymorphism or phenotypic plasticity).

Contribution of high-content imaging technologies to the development of anti-infective drugs.

Originally developed to study fundamental aspects of cellular biology, high‐content imaging (HCI) was rapidly adapted to study host–pathogen interactions at the cellular level and adopted as a technology of choice to unravel disease biology. HCI platforms allow for the visualization and quantification of discrete phenotypes that cannot be captured using classical screening approaches. A key advantage of high‐content screening technologies lies in the possibility to develop and interrogate physiologically significant, predictive ex vivo disease models that reproduce complex conditions relevant for infection. Here we review and discuss recent advances in HCI technologies and chemical biology approaches that are contributing to an increased understanding of the intricate host–pathogen interrelationship on the cellular level, and which will foster the development of novel therapeutic approaches for the treatment of human bacterial and protozoan infections. © 2016 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of ISAC

Validation and Refinement of Chronic Lung Allograft Dysfunction Phenotypes in Bilateral and Single Lung Recipients

The clinical course of chronic lung allograft dysfunction (CLAD) is heterogeneous. Forced vital capacity (FVC) loss at onset, which may suggest a restrictive phenotype, was associated with worse survival for bilateral lung transplant recipients in one previously published single-center study. We sought to replicate the significance of FVC loss in an independent, retrospectively identified cohort of bilateral lung transplant recipients and to investigate extended application of this approach to single lung recipients. FVC loss and other potential predictors of survival after the onset of CLAD were assessed using Kaplan-Meier and Cox proportional hazards models. FVC loss at the onset of CLAD was associated with higher mortality in an independent cohort of bilateral lung transplant recipients (hazard ratio [HR], 2.75; 95% confidence interval [CI], 2.02-3.73; P < 0.0001) and in a multicenter cohort of single lung recipients (HR, 1.80; 95% CI, 1.09-2.98; P = 0.02). Including all subjects, the deleterious impact of FVC loss on survival persisted after adjustment for other relevant clinical variables (HR, 2.36; 95% CI, 1.77-3.15; P < 0.0001). In patients who develop CLAD without FVC loss, chest computed tomography features suggestive of pleural or parenchymal fibrosis also predicted worse survival in both bilateral (HR, 2.01; 95% CI, 1.16-5.20; P = 0.02) and single recipients (HR, 2.47; 95% CI, 1.24-10.57; P = 0.02). We independently validated the prognostic significance of FVC loss for bilateral lung recipients and demonstrated that this approach to CLAD classification also confers prognostic information for single lung transplant recipients. Improved understanding of these discrete phenotypes is critical to the development of effective therapies.

PME58 plays a role in pectin distribution during seed coat mucilage extrusion through homogalacturonan modification.

Pectins are major components of plant primary cell walls. They include homogalacturonans (HGs), which are the most abundant pectin and can be the target of apoplastic enzymes like pectin methylesterases (PMEs) that control their methylesterification level. Several PMEs are expressed in the seed coat of Arabidopsis thaliana, particularly in mucilage secretory cells (MSCs). On the basis of public transcriptomic data, seven PME genes were selected and checked for their seed-specific expression by quantitative reverse transcription PCR. Of these, PME58 presented the highest level of expression and was specifically expressed in MSCs at the early stages of seed development. pme58 mutants presented two discrete phenotypes: (i) their adherent mucilage was less stained by ruthenium red when compared to wild-type seeds, but only in the presence of EDTA, a Ca(2+)chelator; and (ii) the MSC surface area was decreased. These phenotypes are the consequence of an increase in the degree of HG methylesterification connected to a decrease in PME activity. Analysis of the sugar composition of soluble and adherent mucilage showed that, in the presence of EDTA, sugars of adherent mucilage were more readily extracted in pme58 mutants. Immunolabelling with LM19, an antibody that preferentially recognizes unesterified HGs, also showed that molecular interactions with HGs were modified in the adherent mucilage of pme58 mutants, suggesting a role of PME58 in mucilage structure and organization. In conclusion, PME58 is the first PME identified to play a direct role in seed mucilage structure.

Molecular variability elicits a tunable switch with discrete neuromodulatory response phenotypes.

Recent single cell studies show extensive molecular variability underlying cellular responses. We evaluated the impact of molecular variability in the expression of cell signaling components and ion channels on electrophysiological excitability and neuromodulation. We employed a computational approach that integrated neuropeptide receptor-mediated signaling with electrophysiology. We simulated a population of neurons in which expression levels of a neuropeptide receptor and multiple ion channels were simultaneously varied within a physiological range. We analyzed the effects of variation on the electrophysiological response to a neuropeptide stimulus. Our results revealed distinct response patterns associated with low versus high receptor levels. Neurons with low receptor levels showed increased excitability and neurons with high receptor levels showed reduced excitability. These response patterns were separated by a narrow receptor level range forming a separatrix. The position of this separatrix was dependent on the expression levels of multiple ion channels. To assess the relative contributions of receptor and ion channel levels to the response profiles, we categorized the responses into six phenotypes based on response kinetics and magnitude. We applied several multivariate statistical approaches and found that receptor and channel expression levels influence the neuromodulation response phenotype through a complex though systematic mapping. Our analyses extended our understanding of how cellular responses to neuromodulation vary as a function of molecular expression. Our study showed that receptor expression and biophysical state interact with distinct relative contributions to neuronal excitability.

Abstract IA24: Computational dissection of phenotypic and functional heterogeneity in cancer

Abstract Cells within a single tumor are known to display extensive phenotypic and functional heterogeneity. Many life-threatening features of cancer, including drug resistance, metastasis and relapse, are facets of intratumor heterogeneity. With emerging single-cell measurement technologies, the field is poised to make important strides in understanding and controlling this heterogeneity. However, these technologies require advances in analytical methods to interpret the complex data they produce. Using mass cytometry, which measures single cells in ~31 simultaneous proteomic features, we developed novel methods for analyzing phenotypic heterogeneity in cancer. We use AML as an example to demonstrate the power of our approach. The heart of our approach is Phenograph, a graph-based representation of single-cells which represents the phenotypic structure of the sample and can be partitioned into subsets of densely interconnected nodes, called communities. Using Phenograph, we deconstructed several AML samples into discrete phenotypes. Analyzing the resulting subpopulations provided insights into functional heterogeneity of AML. Phenograph can be applied to characterize heterogeneity and primitive subpopulations in additional cancers. Citation Format: Dana Pe'er. Computational dissection of phenotypic and functional heterogeneity in cancer. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr IA24.

Semiparametric Allelic Tests for Mapping Multiple Phenotypes: Binomial Regression and Mahalanobis Distance.

Binary phenotypes commonly arise due to multiple underlying quantitative precursors and genetic variants may impact multiple traits in a pleiotropic manner. Hence, simultaneously analyzing such correlated traits may be more powerful than analyzing individual traits. Various genotype-level methods, e.g., MultiPhen (O'Reilly etal. []), have been developed to identify genetic factors underlying a multivariate phenotype. For univariate phenotypes, the usefulness and applicability of allele-level tests have been investigated. The test of allele frequency difference among cases and controls is commonly used for mapping case-control association. However, allelic methods for multivariate association mapping have not been studied much. In this article, we explore two allelic tests of multivariate association: one using a Binomial regression model based on inverted regression of genotype on phenotype (Binomial regression-based Association of Multivariate Phenotypes [BAMP]), and the other employing the Mahalanobis distance between two sample means of the multivariate phenotype vector for two alleles at a single-nucleotide polymorphism (Distance-based Association of Multivariate Phenotypes [DAMP]). These methods can incorporate both discrete and continuous phenotypes. Some theoretical properties for BAMP are studied. Using simulations, the power of the methods for detecting multivariate association is compared with the genotype-level test MultiPhen's. The allelic tests yield marginally higher power than MultiPhen for multivariate phenotypes. For one/two binary traits under recessive mode of inheritance, allelic tests are found to be substantially more powerful. All three tests are applied to two different real data and the results offer some support for the simulation study. We propose a hybrid approach for testing multivariate association that implements MultiPhen when Hardy-Weinberg Equilibrium (HWE) is violated and BAMP otherwise, because the allelic approaches assume HWE.

Alternative reproductive tactics in female striped mice: heavier females are more likely to breed solitarily than communally.

Alternative reproductive tactics (ARTs) are discrete reproductive phenotypes governed by decision rules called strategies. ARTs are fixed for life in species with alternative strategies, while tactic expression is plastic in species with a single strategy. ARTs have been investigated in males of many species, but few studies have tested whether the same theoretical framework applies in females. Female striped mice (Rhabdomys pumilio) employ three ARTs: communal breeders give birth in a nest shared with female kin and a breeding male and show allo-parental care; returners give birth away from the shared nest and later return to it; and solitary breeders give birth away from the shared nest and do not return to the group. Here, studying free-living female striped mice over six breeding seasons, we tested whether ARTs arise from alternative strategies or a single strategy. We also asked to what extent stochastic extrinsic factors explain whether individuals become solitary rather than group living. Females switched tactics, consistent with a single strategy, so we tested whether this represented a mixed or conditional single strategy. Only the latter predicts differences between ARTs in traits indicating competitive ability, such as body mass or age, before individuals adopt a tactic. We weighed females at conception when they were still group living to eliminate potential confounding effects of gestation and subsequent social tactic (solitary versus group living) on body mass. Females that went on to use a solitary ART were heavier than those that became communal breeders and returners, in support of a conditional strategy. Solitary breeders also arose through extrinsic factors (mortality of all adult female group members). They weighed less than females that became solitary while relatives were alive, but did not differ in body mass from communal breeders and returners. We conclude that ART theory applies to both sexes, with female striped mice following a conditional single strategy. Future studies should consider the possibility that phenotypes that superficially resemble evolved tactics might also arise through non-adaptive extrinsic causes.

Thermal plasticity of growth and development varies adaptively among alternative developmental pathways.

Polyphenism, the expression of discrete alternative phenotypes, is often a consequence of a developmental switch. Physiological changes induced by a developmental switch potentially affect reaction norms, but the evolution and existence of alternative reaction norms remains poorly understood. Here, we demonstrate that, in the butterfly Pieris napi (Lepidoptera: Pieridae), thermal reaction norms of several life history traits vary adaptively among switch-induced alternative developmental pathways of diapause and direct development. The switch was affected both by photoperiod and temperature, ambient temperature during late development having the potential to override earlier photoperiodic cues. Directly developing larvae had higher development and growth rates than diapausing ones across the studied thermal gradient. Reaction norm shapes also differed between the alternative developmental pathways, indicating pathway-specific selection on thermal sensitivity. Relative mass increments decreased linearly with increasing temperature and were higher under direct development than diapause. Contrary to predictions, population phenology did not explain trait variation or thermal sensitivity, but our experimental design probably lacks power for finding subtle phenology effects. We demonstrate adaptive differentiation in thermal reaction norms among alternative phenotypes, and suggest that the consequences of an environmentally dependent developmental switch primarily drive the evolution of alternative thermal reaction norms in P. napi.

Abstract A32: Computational dissection of phenotypic and functional heterogeneity in acute myeloid leukemia.

Abstract Cells within a single tumor are known to display extensive phenotypic and functional heterogeneity. Many life-threatening features of cancer, including drug resistance, metastasis and relapse, are facets of intratumor heterogeneity. With emerging single-cell measurement technologies, the field is poised to make important strides in understanding and controlling this heterogeneity. However, these technologies require coordinated advances in analytical methods to interpret the complex data they produce. Acute myeloid leukemia (AML) is an aggressive bone marrow malignancy in which the importance of cellular heterogeneity has been well characterized. However, previous studies have only scraped the surface of the heterogeneity in this disease. Using mass cytometry, which measures single cells in ~40 simultaneous proteomic features, we developed novel methods for analyzing phenotypic heterogeneity in cancer. Our approach provides an extensive compendium of surface-marker and signaling phenotypes in AML that extends current boundaries of knowledge. The heart of our approach is a graph-based representation of the single-cell samples. In this representation, each cell is modeled by a node connected to its neighbors—the cells most phenotypically similar to it. Constructed by local rules connecting cells, the graph as a whole represents the phenotypic structure of the sample. The graph can be partitioned into subsets of densely interconnected nodes, called communities, which represent distinct phenotypic subpopulations. Unlike parametric methods such as mixture models, this method makes no assumption about the size, distribution, or number of subpopulations. Using our graph-based approach, we deconstructed several AML samples into discrete phenotypes. Comparing phenotypes across patients, we found a striking degree of order. Every phenotype identifiable phenotype was discoverable in multiple (but not all) patients, implying a constraint on the space of allowable AML phenotypes. For each phenotype we also identified cognate healthy cell types at different stages of bone marrow maturation, indicating a constraint that is linked to normal developmental programs. Our data contain measurements of under various environmental perturbations and we designed a method to statistically quantify evoked signaling responses, producing high-dimensional signaling phenotypes for each subpopulation, which we regard as a representation of cellular functional potential. We found a tight coupling between surface and signaling phenotypes in healthy cells that is disrupted in AML. We identified a primitive signaling phenotype, derived from healthy stem and progenitor cells, which was not correlated with the primitive surface marker profile typically used to define primitive cells in AML. Using single-cell frequencies to deconvolve existing bulk gene expression data, we identified genes associated with this primitive signaling phenotype. These genes are enriched for primitive hematopoietic annotations and produce a clinically predictive signature that is more powerful than genes associated with the primitive surface profile, validating the utility of our approach and indicating novel regulators of the primitive hematopoietic cell state. Citation Format: Jacob H. Levine, Erin F. Simonds, Sean C. Bendall, Garry P. Nolan, Dana Pe'er. Computational dissection of phenotypic and functional heterogeneity in acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference on Hematologic Malignancies: Translating Discoveries to Novel Therapies; Sep 20-23, 2014; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2015;21(17 Suppl):Abstract nr A32.

Computational modeling of electrophysiology and molecular variability in single neurons reveals a tunable switch with discrete neuromodulatory response phenotypes

Computational modeling of electrophysiology and molecular variability in single neurons reveals a tunable switch with discrete neuromodulatory response phenotypes

The effect of early, comprehensive genomic testing on clinical care in neonatal diabetes: an international cohort study

SummaryBackgroundTraditional genetic testing focusses on analysis of one or a few genes according to clinical features; this approach is changing as improved sequencing methods enable simultaneous analysis of several genes. Neonatal diabetes is the presenting feature of many discrete clinical phenotypes defined by different genetic causes. Genetic subtype defines treatment, with improved glycaemic control on sulfonylurea treatment for most patients with potassium channel mutations. We investigated the effect of early, comprehensive testing of all known genetic causes of neonatal diabetes.MethodsIn this large, international, cohort study, we studied patients with neonatal diabetes diagnosed with diabetes before 6 months of age who were referred from 79 countries. We identified mutations by comprehensive genetic testing including Sanger sequencing, 6q24 methylation analysis, and targeted next-generation sequencing of all known neonatal diabetes genes.FindingsBetween January, 2000, and August, 2013, genetic testing was done in 1020 patients (571 boys, 449 girls). Mutations in the potassium channel genes were the most common cause (n=390) of neonatal diabetes, but were identified less frequently in consanguineous families (12% in consanguineous families vs 46% in non-consanguineous families; p<0·0001). Median duration of diabetes at the time of genetic testing decreased from more than 4 years before 2005 to less than 3 months after 2012. Earlier referral for genetic testing affected the clinical phenotype. In patients with genetically diagnosed Wolcott-Rallison syndrome, 23 (88%) of 26 patients tested within 3 months from diagnosis had isolated diabetes, compared with three (17%) of 18 patients referred later (>4 years; p<0·0001), in whom skeletal and liver involvement was common. Similarly, for patients with genetically diagnosed transient neonatal diabetes, the diabetes had remitted in only ten (10%) of 101 patients tested early (<3 months) compared with 60 (100%) of the 60 later referrals (p<0·0001).InterpretationPatients are now referred for genetic testing closer to their presentation with neonatal diabetes. Comprehensive testing of all causes identified causal mutations in more than 80% of cases. The genetic result predicts the best diabetes treatment and development of related features. This model represents a new framework for clinical care with genetic diagnosis preceding development of clinical features and guiding clinical management.FundingWellcome Trust and Diabetes UK.

Variation in song system anatomy and androgen levels does not correspond to song characteristics in a tropical songbird

Variation in song structure and song production of birds are thought to relate to variation of both androgen levels and neural nuclei in the song system, as typically these nuclei are larger in males than in females, vary in size among males and are sensitive to steroid hormones . We investigated the relationships among song and note structure, singing rate, androgen levels and the sizes of two song nuclei, the higher vocal centre (HVC) and the robust nucleus of the arcopallium (RA) in male and female red-backed fairy-wrens, Malurus melanocephalus . Males of this duetting species express three discrete reproductive phenotypes that differ in plumage colour and behaviour. Although HVC and RA structure differed between the sexes, there were no sex differences in note structure and complexity of songs, although females differed from some male types in song rate and frequency characteristics. Both auxiliary males and females had significantly lower androgen levels than the two breeding male phenotypes. Male reproductive phenotypes had similar song characteristics and HVC and RA structure, but differed in androgen levels. Sexes and male phenotypes varied in song rate, but these differences did not correspond to differences in androgen levels. Thus, sex differences in song nuclei anatomy and androgen levels were not associated with differences in song structure and singing rate; and, the differences in androgen levels among male phenotypes were not reflected in differences in singing rate, song structure or the song nuclei. We conclude that, similar to other recent findings, the sexes of the red-backed fairy-wren can produce similar song and express similar singing behaviour despite differences in song system structure and circulating androgen levels; singing and song system anatomy appear not to be part of the suite of traits associated with differences in androgen levels in male red-backed fairy-wrens. • We examined potential factors influencing song variation in red-backed fairy-wrens. • Sexes differed in song nuclei anatomy but not in singing rate or song structure. • Females had lower androgen levels than breeding males but higher levels than auxiliary males. • Male phenotypes differed in androgen levels but not in song nuclei anatomy or song structure.