Discrete Phenotypes Research Articles

Dysregulated immune networks define distinct respiratory phenotypes of post-acute sequelae of COVID-19

Abstract Long-haul respiratory symptoms are common following severe COVID-19 illness; however, the immune mechanisms contributing to post-acute sequelae of COVID-19 (PASC) remain enigmatic. A comprehensive 2-year longitudinal immune assessment was performed in a cohort of PASC patients receiving pulmonary follow-up care (n=110) by analyzing circulating immune cells using spectral flow cytometry, as well as assessment of virus-specific T cell frequencies, serum antibodies, and plasma mediators. Novel unsupervised machine-learning workflows were used to analyze and integrate multiple clinical and immune measures. Our approach identified discrete respiratory phenotypes according to lung physiology measures that defined the degree of lung fibrosis and its severity. Notably, severe respiratory phenotypes were characterized by immune dysregulation of both innate and adaptive cellular components, including lower ILC-3-like cells and higher activated CD4+ and CD8+ T cells in the blood. On the other hand, all respiratory phenotypes displayed a marked loss of naïve CD8+ T cells and unswitched memory B cells compared to healthy individuals. Spike- and nucleoprotein-specific CD4+ and CD8+ T cells were more abundant in severe respiratory phenotypes. Overall, T cell-derived inflammatory cytokines, along with chemokine receptors and their relationships to cognate ligands, pointed to sustained lung-homing of pathogenic effector cells in fibrotic phenotypes. Integration of high-dimensional data defined discrete cellular and molecular immune networks that provide unconventional and novel mechanistic insight into pulmonary complications post-COVID-19. UO1AI125056 R21 AI160334

Transcriptional and Chromatin Accessibility Profiling of Neural Stem Cells Differentiating into Astrocytes Reveal Dynamic Signatures Affected under Inflammatory Conditions

Astrocytes arise from multipotent neural stem cells (NSCs) and represent the most abundant cell type of the central nervous system (CNS), playing key roles in the developing and adult brain. Since the differentiation of NSCs towards a gliogenic fate is a precisely timed and regulated process, its perturbation gives rise to dysfunctional astrocytic phenotypes. Inflammation, which often underlies neurological disorders, including neurodevelopmental disorders and brain tumors, disrupts the accurate developmental process of NSCs. However, the specific consequences of an inflammatory environment on the epigenetic and transcriptional programs underlying NSCs' differentiation into astrocytes is unexplored. Here, we address this gap by profiling in mice glial precursors from neural tissue derived from early embryonic stages along their astrocytic differentiation trajectory in the presence or absence of tumor necrosis factor (TNF), a master pro-inflammatory cytokine. By using a combination of RNA- and ATAC-sequencing approaches, together with footprint and integrated gene regulatory network analyses, we here identify key differences during the differentiation of NSCs into astrocytes under physiological and inflammatory settings. In agreement with its role to turn cells resistant to inflammatory challenges, we detect Nrf2 as a master transcription factor supporting the astrocytic differentiation under TNF exposure. Further, under these conditions, we unravel additional transcriptional regulatory hubs, including Stat3, Smad3, Cebpb, and Nfkb2, highlighting the interplay among pathways underlying physiological astrocytic developmental processes and those involved in inflammatory responses, resulting in discrete astrocytic phenotypes. Overall, our study reports key transcriptional and epigenetic changes leading to the identification of molecular regulators of astrocytic differentiation. Furthermore, our analyses provide a valuable resource for understanding inflammation-induced astrocytic phenotypes that might contribute to the development and progression of CNS disorders with an inflammatory component.

Multifaceted Transcriptional Network of Estrogen-Related Receptor Alpha in Health and Disease

Estrogen-related receptors (ERRα, β and γ in mammals) are orphan members of the nuclear receptor superfamily acting as transcription factors. ERRs are expressed in several cell types and they display various functions in normal and pathological contexts. Amongst others, they are notably involved in bone homeostasis, energy metabolism and cancer progression. In contrast to other nuclear receptors, the activities of the ERRs are apparently not controlled by a natural ligand but they rely on other means such as the availability of transcriptional co-regulators. Here we focus on ERRα and review the variety of co-regulators that have been identified by various means for this receptor and their reported target genes. ERRα cooperates with distinct co-regulators to control the expression of distinct sets of target genes. This exemplifies the combinatorial specificity of transcriptional regulation that induces discrete cellular phenotypes depending on the selected coregulator. We finally propose an integrated view of the ERRα transcriptional network.

Discrete T-Cell and Inflammatory Profiles in the Blood Define Pulmonary Phenotypes After COVID-19 Illness.

Pulmonary complications arising from severe COVID-19 illness are common. However, patient variability presents a barrier to defining the immune mechanisms involved. We describe a novel method that leverages hundreds of cellular and molecular combinations within a large recovery cohort to identify immune profiles linked to discrete pulmonary phenotypes.

Abstract A016: Aging-dependent emergent mechanical properties of single epithelial cells exploited for detection of breast cancer susceptibility

Abstract Age is the major risk factor in most carcinomas, yet, little is known about the specific reasons aging increases cancer susceptibility. In the mammary gland, luminal epithelial cells rank high as the putative breast cancer cell of origin. Dysregulation of keratin intermediate filament proteins exemplifies a hallmark age-dependent change in luminal cells, which implicates mechanical states unique to cancer susceptible cells. We implemented mechano-node-pore sensing (mechano-NPS), a multi-parametric single-cell analysis that simultaneously measures cell diameter, resistance to compressive deformation, transverse deformation under constant strain, and recovery time after deformation. We demonstrated that the epithelial lineages, chronological ages, and stages of cancer progression of primary human mammary epithelial cells (HMEC) exhibited discrete mechanical phenotypes. We trained a machine learning model that accurately predicted the chronological age of average risk HMEC cells based exclusively on mechanical properties. Application of the model to cells from women who are germline carriers of high-risk cancer-causing mutations showed that they are mechanically old irrespective of their chronological age, suggesting that mechanical states could be a window into detection and prevention of cancer susceptible states. Indeed, this mechano-age model detected high-risk women with >90% accuracy. Mass spectrometry and cell-based functional assays in mammary epithelia revealed that cytoskeleton related proteins keratin 14 (KRT14) and pseudopodium enriched atypical kinase 1 (PEAK1) were key drivers of age-dependent mechanical signatures. Pharmacological and gene silencing approaches that targeted KRT14 and PEAK1 modulated the mechanical age of HMEC and, in the case of PEAK1 modulation, ablated luminal epithelial cells in an age- and lineage- dependent manner. We define an intersection between mechanical phenotypes and novel age-dependent changes in cytoskeleton-related proteins that we hypothesize can be exploited to assess an individual’s breast cancer susceptibility and provide new targets for cancer-prevention strategies. Citation Format: Stefan Hinz, Masaru Miyano, Antigoni Manousopoulou, Rosalyn W. Sayaman, Kristina Y. Aguilera, Michael E. Todhunter, Jennifer C. Lopez, Leo D. Wang, Lydia L. Sohn, Mark A. LaBarge. Aging-dependent emergent mechanical properties of single epithelial cells exploited for detection of breast cancer susceptibility [abstract]. In: Proceedings of the AACR Special Conference: Aging and Cancer; 2022 Nov 17-20; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2022;83(2 Suppl_1):Abstract nr A016.

Covariation of brain and skull shapes as a model to understand the role of crosstalk in development and evolution.

Covariation among discrete phenotypes can arise due to selection for shared functions, and/or shared genetic and developmental underpinnings. The consequences of such phenotypic integration are far-reachingand can act to either facilitate or limit morphological variation. The vertebrate brain is known to act as an "organizer"of craniofacial development, secreting morphogens that can affect the shape of the growing neurocranium, consistent with roles for pleiotropy in brain-neurocranium covariation. Here, we test this hypothesis in cichlid fishes by first examining the degree of shape integration between the brain and the neurocranium using three-dimensionalgeometric morphometrics in an F5 hybrid population, and then genetically mapping trait covariation using quantitative trait loci (QTL) analysis. We observe shape associations between the brain and the neurocranium, a pattern that holds even when we assess associations between the brain and constituent parts of the neurocranium: the rostrum and braincase. We also recover robust genetic signals for both hard- and soft-tissue traitsand identify a genomic region where QTL for the brain and braincase overlap, implicating a role for pleiotropy in patterning trait covariation. Fine mapping of the overlapping genomic region identifies a candidate gene, notch1a, which is known to be involved in patterning skeletal and neural tissues during development. Taken together, these data offer a genetic hypothesis for brain-neurocranium covariation, as well as a potential mechanism by which behavioral shifts may simultaneously drive rapid change in neuroanatomy and craniofacial morphology.

Sympatry of genetically distinct Atlantic Puffins (Fratercula arctica) in the High Arctic

Across its range, the Atlantic Puffin Fratercula arctica is divided into four separate genetic clusters that correspond with geography and/or size differences. However, in the Western Atlantic High Arctic, there is a Puffin colony (Thule) that comprises two discrete size phenotypes. Using whole genome sequencing data of six Thule individuals from these two phenotypes, we found that Thule consists of three distinct genetic clusters, with no signs of recent interbreeding. Our results suggest the beginnings of a potential northward shift of boreal Atlantic Puffins in the West Atlantic, consistent with responses to a warming High Arctic climate.

Physiology of chemokines in the cancer microenvironment.

Chemokines are chemotactic cytokines whose canonical functions govern movement of receptor-expressing cells along chemical gradients. Chemokines are a physiological system that is finely tuned by ligand and receptor expression, ligand or receptor oligomerization, redundancy, expression of atypical receptors, and non-GPCR binding partners that cumulatively influence discrete pharmacological signaling responses and cellular functions. In cancer, chemokines play paradoxical roles in both the directed emigration of metastatic, receptor-expressing cancer cells out of the tumor as well as immigration of tumor-infiltrating immune cells that culminate in a tumor-unique immune microenvironment. In the age of precision oncology, strategies to effectively harness the power of immunotherapy requires consideration of chemokine gradients within the unique spatial topography and temporal influences with heterogeneous tumors. In this article, we review current literature on the diversity of chemokine ligands and their cellular receptors that detect and process chemotactic gradients and illustrate how differences between ligand recognition and receptor activation influence the signaling machinery that drives cellular movement into and out of the tumor microenvironment. Facets of chemokine physiology across discrete cancer immune phenotypes are contrasted to existing chemokine-centered therapies in cancer.

Using crowdsourced photographic records to explore geographical variation in colour polymorphism

AbstractAimIn wide‐ranging taxa occupying broad climate gradients, alternative colour pattern variants (i.e. morphs) may emerge as an adaptive response to local climatic regimes. We explore the patterns of geographical segregation among colour morphs of the Lace monitor and determine whether morphs occupy divergent climatic niches along a mesic–arid gradient.LocationEastern and south‐eastern Australia.TaxonVaranus varius.MethodsWe compiled a dataset of crowdsourced, georeferenced photographic records (n = 1637) of V. varius and scored each photographed lizard as one of two discrete colour pattern phenotypes—Lace morph (mostly dark with fine pale patterning) or Bell's morph (broad yellow and black bands). We then analysed the geographical segregation of colour morphs under an exploratory point‐pattern process analysis framework. Finally, we quantified similarities and differences between each colour morphs' realised climatic niche in univariate and multivariate (i.e. Centroid shift, Overlap, Unfilling, and Expansion and n‐dimensional hypervolume frameworks) environmental space.ResultsWhile both morphs co‐occur over much of the species' range, there is a coastal–inland clinal transition in the relative densities of the morphs' occurrences—the Bell's morph becomes the more prevalent phenotype towards inland locations and is rare or absent towards coastal regions. Analysis of the realised climatic niches shows that the Bell's morph exploits areas that are relatively more arid, receive more solar irradiation and experience a broader range of thermal extremes than those occupied by the Lace morph.Main conclusionsThe mesic–arid transition zone in eastern Australia is a primary axis of environmental variation over which geographical variation in colour polymorphism has emerged in V. varius. More broadly, this study demonstrates how photographs from citizen science platforms can be used to explore geographical variation in colour polymorphisms without needing to conduct expensive, time‐consuming field studies on wild organisms.

Distinct Impairments Characterizing Different ADNP Mutants Reveal Aberrant Cytoplasmic-Nuclear Crosstalk.

(1) Background: Activity-dependent neuroprotective protein (ADNP) is essential for neuronal structure and function. Multiple de novo pathological mutations in ADNP cause the autistic ADNP syndrome, and they have been further suggested to affect Alzheimer’s disease progression in a somatic form. Here, we asked if different ADNP mutations produce specific neuronal-like phenotypes toward better understanding and personalized medicine. (2) Methods: We employed CRISPR/Cas9 genome editing in N1E-115 neuroblastoma cells to form neuron-like cell lines expressing ADNP mutant proteins conjugated to GFP. These new cell lines were characterized by quantitative morphology, immunocytochemistry and live cell imaging. (3) Results: Our novel cell lines, constitutively expressing GFP-ADNP p.Pro403 (p.Ser404* human orthologue) and GFP-ADNP p.Tyr718* (p.Tyr719* human orthologue), revealed new and distinct phenotypes. Increased neurite numbers (day 1, in culture) and increased neurite lengths upon differentiation (day 7, in culture) were linked with p.Pro403*. In contrast, p.Tyr718* decreased cell numbers (day 1). These discrete phenotypes were associated with an increased expression of both mutant proteins in the cytoplasm. Reduced nuclear/cytoplasmic boundaries were observed in the p.Tyr718* ADNP-mutant line, with this malformation being corrected by the ADNP-derived fragment drug candidate NAP. (4) Conclusions: Distinct impairments characterize different ADNP mutants and reveal aberrant cytoplasmic-nuclear crosstalk.

Sex-specific morphs: the genetics and evolution of intra-sexual variation.

Sex-specific morphs exhibit discrete phenotypes, often including many disparate traits, that are observed in only one sex. These morphs have evolved independently in many different animals and are often associated with alternative mating strategies. The remarkable diversity of sex-specific morphs offers unique opportunities to understand the genetic basis of complex phenotypes, as the distinct nature of many morphs makes it easier to both categorize and compare genomes than for continuous traits. Sex-specific morphs also expand the study of sexual dimorphism beyond traditional bimodal comparisons of male and female averages, as they allow for a more expansive range of sexualization. Although ecological and endocrinological studies of sex-specific morphs have been advancing for some time, genomic and transcriptomic studies of morphs are far more recent. These studies reveal not only many different paths to the evolution of sex-specific morphs but also many commonalities, such as the role of sex-determining genes and hormone signalling in morph development, and the mixing of male and female traits within some morphs.

Hormones do not maketh the mole-rat: No steroid hormone signatures of subordinate behavioral phenotypes

In some cooperatively breeding groups, individuals have distinct behavioral characteristics that are often stable and predictable across time. However, in others, as in the eusocial naked mole-rat, evidence for behavioral phenotypes is ambiguous. Here, we study whether the naked mole-rat can be divided into discrete phenotypes and if circulating hormone concentrations underpin these differences. Naked mole-rat colonies consist of a single breeding female and large numbers of non-reproductive subordinates that in some cases can exceed several hundred in a colony. The subordinates can potentially be divided into soldiers, who defend the colony; workers, who maintain it; and dispersers, who want to leave it. We established six colonies de novo, tracked them over three years, and assessed the behavior and hormone concentrations of the subordinates. We found that soldiers tended to be from earlier litters and were higher ranked compared to workers, whereas dispersers were distributed throughout litters and rankings. There was no difference in estradiol, testosterone, or dehydroepiandrosterone (DHEA) concentrations among phenotypes. Progesterone concentrations were higher in soldiers, but this difference appeared to be driven by a few individuals. Principal component analysis demonstrated that soldiers separated into a discrete category relative to workers/dispersers, with the highest ranked loadings being age, body mass, and testosterone concentrations. However, the higher testosterone in soldiers was correlated with large body size instead of strictly behavioral phenotype. Workers and dispersers have more overlap with each other and no hormonal differences. Thus the behavioral variation in subordinate naked mole-rats is likely not driven by circulating steroid hormone concentrations, but rather it may stem from alternative neural and/or neuroendocrine mechanisms.

Uncertainty quantification in variable selection for genetic fine-mapping using bayesian neural networks

SummaryIn this paper, we propose a new approach for variable selection using a collection of Bayesian neural networks with a focus on quantifying uncertainty over which variables are selected. Motivated by fine-mapping applications in statistical genetics, we refer to our framework as an “ensemble of single-effect neural networks” (ESNN) which generalizes the “sum of single effects” regression framework by both accounting for nonlinear structure in genotypic data (e.g., dominance effects) and having the capability to model discrete phenotypes (e.g., case-control studies). Through extensive simulations, we demonstrate our method’s ability to produce calibrated posterior summaries such as credible sets and posterior inclusion probabilities, particularly for traits with genetic architectures that have significant proportions of non-additive variation driven by correlated variants. Lastly, we use real data to demonstrate that the ESNN framework improves upon the state of the art for identifying true effect variables underlying various complex traits.

Heart failure with preserved ejection fraction (HFpEF) in type 2 diabetes mellitus: from pathophysiology to therapeutics.

Type 2 diabetes mellitus (T2DM or T2D) is a devastating metabolic abnormality featured by insulin resistance, hyperglycemia, and hyperlipidemia. T2D provokes unique metabolic changes and compromises cardiovascular geometry and function. Meanwhile, T2D increases the overall risk for heart failure (HF) and acts independent of classical risk factors including coronary artery disease, hypertension, and valvular heart diseases. The incidence of HF is extremely high in patients with T2D and is manifested as HF with preserved, reduced, and midrange ejection fraction (HFpEF, HFrEF, and HFmrEF, respectively), all of which significantly worsen the prognosis for T2D. HFpEF is seen in approximately half of the HF cases and is defined as a heterogenous syndrome with discrete phenotypes, particularly in close association with metabolic syndrome. Nonetheless, management of HFpEF in T2D remains unclear, largely due to the poorly defined pathophysiology behind HFpEF. Here, in this review, we will summarize findings from multiple preclinical and clinical studies as well as recent clinical trials, mainly focusing on the pathophysiology, potential mechanisms, and therapies of HFpEF in T2D.

Naked Mole-Rat Social Phenotypes Vary in Investigative and Aggressive Behavior in a Laboratory Partner Preference Paradigm

Here we employed the partner preference test (PPT) to examine how naked mole-rat non-breeding individuals of different behavioral phenotypes make social decisions. Naked mole-rats from six colonies were classified into three behavioral phenotypes (soldiers, dispersers, and workers) using a battery of behavioral tests. They then participated in a 3 h long PPT, where they could freely interact with a tethered familiar or tethered unfamiliar conspecific. By comparing the three behavioral phenotypes, we tested the hypothesis that the PPT can be used to interrogate social decision-making in this species, revealing individual differences in behavior that are consistent with discrete social phenotypes. We also tested whether a shorter, 10 min version of the paradigm is sufficient to capture group differences in behavior. Overall, soldiers had higher aggression scores toward unfamiliar conspecifics than both workers and dispersers at the 10 min and 3 h comparison times. At the 10 min comparison time, workers showed a stronger preference for the familiar animal’s chamber, as well as for investigating the familiar conspecific, compared to both dispersers and soldiers. At the 3 h time point, no phenotype differences were seen with chamber or investigation preference scores. Overall, all phenotypes spent more time in chambers with another animal vs. being alone. Use of the PPT in a comparative context has demonstrated that the test identifies species and group differences in affiliative and aggressive behavior toward familiar and unfamiliar animals, revealing individual differences in social decision-making and, importantly, capturing aspects of species-specific social organization seen in nature.

From genotype to phenotype: Genetic redundancy and the maintenance of an adaptive polymorphism in the context of high gene flow.

A central question in evolution is how several adaptive phenotypes are maintained within a species. Theory predicts that the genetic determination of a trait, and in particular the amounts of redundancy in the mapping of genotypes to phenotypes, mediates evolutionary outcomes of phenotypic selection. In Mediterranean wild thyme, numerous discrete chemical phenotypes (chemotypes) occur in close geographic proximity. Chemotypes are defined by the predominant monoterpene produced by individual plants in their essential oil. In this study, we analyze the ecological genetics of six chemotypes nested within two well‐established chemical families (hereafter ecotypes). Ecotypes, and chemotypes within ecotypes, are spatially segregated, and their distributions track local differences in the abiotic environment. By combining population genomic, phenotypic, and environmental data from 700 individuals, we show how the genetics of ecotype determination mediates this evolutionary response. Variation in three terpene‐synthase loci explains variation in ecotype identity, with one single locus accounting for as much as 78% of this variation. Phenotypic selection combined with low segregating genotypic redundancy of ecotypes leaves a clear footprint at the genomic level: alleles associated with ecotype identity track environmental variation despite extensive gene flow. Different chemotypes within each ecotype differentially track environmental variation. Their identity is determined by multiple loci and displays a wider range of genotypic redundancy that dilutes phenotypic selection on their characteristic alleles. Our study thus provides a novel illustration of how genetic redundancy of a phenotype modulates the ability of selection to maintain adaptive differentiation. Identifying the precise genetics of the chemical polymorphism in thyme is the next crucial step for our understanding of the origin and maintenance of a polymorphism that is present in many aromatic plants.

Associations of ATP-Sensitive Potassium Channel's Gene Polymorphisms With Type 2 Diabetes and Related Cardiovascular Phenotypes.

Type 2 diabetes (T2D) is characterized by increased levels of blood glucose but is increasingly recognized as a heterogeneous disease, especially its multiple discrete cardiovascular phenotypes. Genetic variations play key roles in the heterogeneity of diabetic cardiovascular phenotypes. This study investigates possible associations of ATP-sensitive potassium channel (KATP) variants with cardiovascular phenotypes among the Chinese patients with T2D. Six hundred thirty-six patients with T2D and 634 non-diabetic individuals were analyzed in the study. Nine KATP variants were determined by MassARRAY. The KATP rs2285676 (AA + GA, OR = 1.43, 95% CI: 1.13–1.81, P = 0.003), rs1799858 (CC, OR = 1.42, 95% CI: 1.12–1.78, P = 0.004), and rs141294036 (CC, OR = 1.45, 95% CI: 1.15–1.83, P = 0.002) are associated with increased T2D risk. A follow-up of at least 45.8-months (median) indicates further association between the 3 variants and risks of diabetic-related cardiovascular conditions. The associations are categorized as follows: new-onset/recurrent acute coronary syndrome (ACS) (rs2285676/AA + GA, HR = 1.37, 95% CI: 1.10–1.70, P = 0.005; rs141294036/TT + CT, HR = 1.59, 95% CI: 1.28–1.99, P < 0.001), new-onset stroke (rs1799858/CC, HR = 2.58, 95% CI: 1.22–5.43, P = 0.013; rs141294036/CC, HR = 2.30, 95% CI: 1.16–4.55, P = 0.017), new-onset of heart failure (HF) (rs1799858/TT + CT, HR = 2.78, 95% CI: 2.07–3.74, P < 0.001; rs141294036/TT + CT, HR = 1.45, 95% CI: 1.07–1.96, P = 0.015), and new-onset atrial fibrillation (AF) (rs1799858/TT + CT, HR = 2.05, 95% CI: 1.25–3.37, P = 0.004; rs141294036/CC, HR = 2.31, 95% CI: 1.40–3.82, P = 0.001). In particular, the CC genotype of rs1799858 (OR = 2.38, 95% CI: 1.11–5.10, P = 0.025) and rs141294036 (OR = 1.95, 95% CI: 1.04–3.66, P = 0.037) are only associated with the risk of ischemic stroke while its counterpart genotype (TT + CT) is associated with the risks of HF with preserved ejection fraction (HFpEF) (rs1799858, OR = 3.46, 95% CI: 2.31–5.18, P < 0.001) and HF with mildly reduced ejection fraction (HFmrEF) (rs141294036, OR = 2.74, 95% CI: 1.05–7.15, P = 0.039). Furthermore, the 3 variants are associated with increased risks of abnormal serum levels of triglyceride (TIRG) (≥ 1.70 mmol/L), low-density lipoprotein cholesterol (LDL-C) (≥ 1.40 mmol/L), apolipoprotein B (ApoB) (≥ 80 mg/dL), apolipoprotein A-I (ApoA-I) level (< 120 mg/dL), lipoprotein(a) Lp(a) (≥ 300 mg/dL) and high-sensitivity C-reactive protein (HsCRP) (≥ 3.0 mg/L) but exhibited heterogeneity (all P < 0.05). The KATP rs2285676, rs1799858, and rs141294036 are associated with increased risks of T2D and its related cardiovascular phenotypes (ACS, stroke, HF, and AF), but show heterogeneity. The 3 KATP variants may be promising markers for diabetic cardiovascular events favoring “genotype-phenotype” oriented prevention and treatment strategies.

Properties of phenotypic plasticity in discrete threshold traits.

Forms of phenotypic plasticity in key traits, and forms of selection on and genetic variation in such plasticity, fundamentally underpin phenotypic, population dynamic, and evolutionary responses to environmental variation and directional change. Accordingly, numerous theoretical and empirical studies have examined properties and consequences of plasticity, primarily considering traits that are continuously distributed on observed phenotypic scales with linear reaction norms. However, many environmentally sensitive traits are expressed as discrete alternative phenotypes and are appropriately characterized as quantitative genetic threshold traits. Here, we highlight that forms of phenotypic plasticity, genetic variation, and inheritance in plasticity, and outcomes of selection on plasticity, could differ substantially between threshold traits and continuously distributed traits (as are typically considered). We thereby highlight theoretical developments that are required to rationalize and predict phenotypic and microevolutionary dynamics involving plastic threshold traits, and outline how intrinsic properties of such traits could provide relatively straightforward explanations for apparently idiosyncratic observed patterns of phenotypic variation. We summarize how key quantitative genetic parameters underlying threshold traits can be estimated, and thereby set the scene for embedding dynamic discrete traits into theoretical and empirical understanding of the role of plasticity in driving phenotypic, population, and evolutionary responses to environmental variation and change.

TheSticta filix - Sticta laceraconundrum (lichenized Ascomycota: Peltigeraceae subfamily Lobarioideae): unresolved lineage sorting or developmental switch?

AbstractWe assessed the status of two New Zealand endemic morphodemes in the genus Sticta, currently treated as two separate taxa, Sticta filix and Sticta lacera. Both are green-algal lichens with a distinct stipe that grow in forested habitats and are suitable indicators of the indigenous vegetation health in forest ecosystems in New Zealand. They exhibit different morphologies and substrate ecologies: S. filix forms rather robust thalli, often on exposed trunks of phorophytes, with erect stems distinctly emerging from the substrate, whereas S. lacera is a more delicate lichen growing near the base of trees, usually among bryophyte mats or sheltered in the exposed portions of the phorophyte root-plate, with a prostrate, branched, stolon-like stem barely emerging from the substrate. Throughout their range, both taxa grow sympatrically and often in close proximity (syntopically). Despite the differences, ITS barcoding does not support the two morphodemes as separate species. In this study we assessed two possible explanations: (1) S. filix and S. lacera are discrete phenotypes of a single species, caused by developmental switching triggered by a discrete environmental variable, the propagules developing either on bare substrate or between bryophytes; and (2) the two morphodemes represent separate lineages, but ITS does not provide sufficient resolution to reflect this. We performed a quantitative analysis of morphological and ecological parameters, based on vouchered herbarium collections and field observations on iNaturalist NZ (https://inaturalist.nz), to assess the level of discreteness of the growth forms and to test for a correlation with the presence of a bryophyte mat. We further took advantage of an existing molecular data set from a target capture approach, comprised of 205 protein markers. This data set was used to establish a framework of percentage identities between pairs of the same and of different species among lobarioid Peltigeraceae and then to test whether the S. filix/lacera pairing fell closer to a within-species or a between-species pairing. The morphometric analysis of herbarium material resolved S. filix and S. lacera as two discrete morphs with little overlap, supported by numerous observations on iNaturalist NZ. However, whereas herbarium material suggested a significant association of the lacera morph with bryophyte mats, no such pattern was evident from field images on iNaturalist NZ, in which both morphs frequently associated with bryophyte mats. This highlights the limitations of herbarium material to correctly assess substrate ecology, whereas iNaturalist NZ postings had issues with correct identifications, given that especially S. lacera is easily confused with Pseudocyphellaria multifida. Based on the target capture data, the percentage identity of the S. filix/lacera pairing (99.43%) was significantly higher than that of all 12 between-species pairings (93.20–98.01%); it was at the same time lower than that of all within-species pairings (99.63–99.99%) but significantly so only in comparison with five out of the eight within-species pairings. The target capture approach is thus inconclusive, but the combination of all data suggests that S. filix and S. lacera are not discrete morphodemes of a single species but represent two separate lineages which emerged recently and hence cannot be resolved using the ITS barcoding marker or even a deeper phylogenomic approach based on protein-coding markers. We propose transplantation experiments and the application of RADseq to further assess this situation.

Accelerating strain phenotyping with desorption electrospray ionization-imaging mass spectrometry and untargeted analysis of intact microbial colonies

Reading and writing DNA were once the rate-limiting step in synthetic biology workflows. This has been replaced by the search for the optimal target sequences to produce systems with desired properties. Directed evolution and screening mutant libraries are proven technologies for isolating strains with enhanced performance whenever specialized assays are available for rapidly detecting a phenotype of interest. Armed with technologies such as CRISPR-Cas9, these experiments are capable of generating libraries of up to 1010 genetic variants. At a rate of 102 samples per day, standard analytical methods for assessing metabolic phenotypes represent a major bottleneck to modern synthetic biology workflows. To address this issue, we have developed a desorption electrospray ionization-imaging mass spectrometry screening assay that directly samples microorganisms. This technology increases the throughput of metabolic measurements by reducing sample preparation and analyzing organisms in a multiplexed fashion. To further accelerate synthetic biology workflows, we utilized untargeted acquisitions and unsupervised analytics to assess multiple targets for future engineering strategies within a single acquisition. We demonstrate the utility of the developed method using Escherichia coli strains engineered to overproduce free fatty acids. We determined discrete metabolic phenotypes associated with each strain, which include the primary fatty acid product, secondary products, and additional metabolites outside the engineered product pathway. Furthermore, we measured changes in amino acid levels and membrane lipid composition, which affect cell viability. In sum, we present an analytical method to accelerate synthetic biology workflows through rapid, untargeted, and multiplexed metabolomic analyses.