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Amphibians are threatened world-wide, and due to the elusive, seasonal, and often nocturnal habits of adults, biological assessments of amphibian species are often best conducted via genetic analysis of easily-sampled pond-dwelling larvae. Genetic analysis of amphibian species can benefit their conservation in several ways, including identification of evolutionary lineages and subpopulations as fundamental units of conservation, genetic assessment of demography and diversity, and inference of patterns of gene flow among populations and how patterns are affected by environmental variation. In this dissertation I elucidated the evolutionary relationships and population genetic status of a threatened California amphibian (Spea hammondii) at multiple spatial scales using a combination of genetic, genomic, and environmental data. Chapter one utilized limited genetic data to determine phylogenetic relationships of Spea species and used environmental niche modeling to examine ecological differentiation between two allopatric lineages identified within S. hammondii. Chapter two took advantage of a newer genomic-scale dataset of thousands of SNP markers to look at fine-scale patterns of genetic variation among natural and artificial S. hammondii ponds in a highly urbanized region of Southern California. Chapter three also made use of thousands of markers to validate species-level relationships in Spea and used the added genomic resolution to examine relationships within and among genetic clusters and quantified the potential impacts of urbanization on functional genetic connectivity. Broadly, I found that the nominal taxon S. hammondii likely comprises two species. Populations within each species were highly differentiated from one another and had exceptionally low effective population sizes, such that each species lacks sufficient adaptive potential to thrive without intervention. Overall, this dissertation applied a suite of phylogenetic, population genomic, and landscape genomic tools to analyze patterns of genetic variation in S. hammondii to guide ongoing and future conservation efforts.

In this paper, a new multi-objective approach is suggested, known as multi-objective backtracking search algorithm (MOBSA) in order to formulate and solve the optimal power flow (OPF) problem in power systems. Many objective functions are considered like fuel cost, power losses, and voltage deviation. The structure of the proposed method is simple and has one control parameter. In addition, MOBSA is able to solve the highly constrained objectives. A fuzzy membership technique is integrated into the BSA algorithm to extract the best compromise solution from all the obtained Pareto optimal solutions. Furthermore, the capability of the MOBSA approach is evaluated and verified for bi- and tri-objectives, and tested on three standard IEEE power systems, small network 30-bus, medium network 57-bus, and large network 118-bus test systems. The obtained results reveal that the proposed method is efficient to generate well-distributed Pareto optimal non-dominated solutions. Likewise, the comparison analysis with some re-implemented methods as MODE, SPEA, MALO, and those found in the literature as MOABC/D, QOTLBO, NSGA-II and NSMOGSA, assured the superiority, effectiveness, and robustness of MOBSA.

Phenotypic plasticity is defined as the property of organisms to produce distinct phenotypes in response to environmental variation. While for more than a century, biologists have proposed this organismal feature..., Phenotypic plasticity is defined as the property of organisms to produce distinct phenotypes in response to environmental variation. While for more than a century, biologists have proposed this organismal feature to play an important role in evolution and the origin of novelty, the idea has remained contentious. Plasticity is found in all domains of life, but only recently has there been an increase in empirical studies. This contribution is intended as a fresh view and will discuss current and future challenges of plasticity research, and the need to identify associated molecular mechanisms. After a brief summary of conceptual, theoretical, and historical aspects, some of which were responsible for confusion and contention, I will formulate three major research directions and predictions for the role of plasticity as a facilitator of novelty. These predictions result in a four-step model that, when properly filled with molecular mechanisms, will reveal plasticity as a major factor of evolution. Such mechanistic insight must be complemented with comparative investigations to show that plasticity has indeed created novelty and innovation. Together, such studies will help develop a true developmental evolutionary biology.

Mechanisms of disulfide bond formation in the human pathogen Streptococcus pyogenes are currently unknown. To date, no disulfide bond-forming thiol-disulfide oxidoreductase (TDOR) has been described and at least one disulfide bonded protein is known in S. pyogenes. This protein is the superantigen SpeA, which contains 3 cysteine residues (Cys 87, Cys90, and Cys98) and has a disulfide bond formed between Cys87 and Cys98. In this study, candidate TDORs were identified from the genome sequence of S. pyogenes MGAS8232. Using mutational and biochemical approaches, one of the candidate proteins, SpyM18_2037 (named here SdbA), was shown to be the catalyst that introduces the disulfide bond in SpeA. SpeA in the culture supernatant remained reduced when sdbA was inactivated and restored to the oxidized state when a functional copy of sdbA was returned to the sdbA-knockout mutant. SdbA has a typical C(46)XXC(49) active site motif commonly found in TDORs. Site-directed mutagenesis experiments showed that the cysteines in the CXXC motif were required for the disulfide bond in SpeA to form. Interactions between SdbA and SpeA were examined using cysteine variant proteins. The results showed that SdbA(C49A) formed a mixed disulfide with SpeA(C87A), suggesting that the N-terminal Cys46 of SdbA and the C-terminal Cys98 of SpeA participated in the initial reaction. SpeA oxidized by SdbA displayed biological activities suggesting that SpeA was properly folded following oxidation by SdbA. In conclusion, formation of the disulfide bond in SpeA is catalyzed by SdbA and the findings represent the first report of disulfide bond formation in S. pyogenes. IMPORTANCE Here, we reported the first example of disulfide bond formation in Streptococcus pyogenes. The results showed that a thiol-disulfide oxidoreductase, named SdbA, is responsible for introducing the disulfide bond in the superantigen SpeA. The cysteine residues in the CXXC motif of SdbA are needed for catalyzing the disulfide bond in SpeA. The disulfide bond in SpeA and neighboring amino acids form a disulfide loop that is conserved among many superantigens, including those from Staphylococcus aureus. SpeA and staphylococcal enterotoxins lacking the disulfide bond are biologically inactive. Thus, the discovery of the enzyme that catalyzes the disulfide bond in SpeA is important for understanding the biochemistry of SpeA production and presents a target for mitigating the virulence of S. pyogenes.

Diadophis punctatus es una serpiente de amplia distribución en Norteamérica. Aunque su historia natural está extensivamente estudiada en Estados Unidos de América, se conoce muy poco sobre su dieta en México. El 30 de octubre de 2018 recibimos un ejemplar de Diadophis punctatus que regurgitó un individuo de Spea multiplicata sin digerir. Este es el primer reporte de la interacción depredador-presa de estas dos especies aportando información valiosa sobre su historia natural. Además, se presenta una revisión de las presas de D. punctatus y de los depredadores de S. multiplicata.

Choosing mates wisely Hybridization between species has long been seen as an accidental contributor to evolution in some cases and as a dead end in others. New evidence is emerging, however, that hybridization may have played important, and nonrandom, roles in adaptation. Chen and Pfennig describe just such a case where female Plains spadefoot toads preferentially choose males from another toad species, the Mexican spadefoot, as mates, but only under certain environmental conditions (see the Perspective by Zuk). The offspring of this preferred hybrid mating event have higher fitness than nonhybrids in the same environment. Thus, not only do hybrids have an advantage, but females of one species are exerting a selective influence on the other species. Science , this issue p. 1377 ; see also p. 1304

In this article, we conducted a new hybrid method between Non-dominated Sorting Genetic Algorithm II (NSGA-III) and SPEA/R (HNSGA-III&SPEA/R). This method is implemented to find the optimal values of the powertrain mount system stiffness parameters. This is the task of finding multi-objective optimization involving six simultaneous optimization goals: mean square acceleration and mean square displacement of the powertrain mount system. A hybrid HNSGA-III&SPEA/R has proposed with the integration of Strength Pareto evolutionary algorithm-based reference direction for Multi-objective (SPEA/R) and Many-objective optimization genetic algorithm (NSGA-III). Several benchmark functions are tested, and results reveal that the HNSGA-III&SPEA/R is more efficient than the typical SPEA/R and NSGA-III. Powertrain mount system stiffness parameters optimization with HNSGA-III&SPEA/R is simulated. It proved the potential of the HNSGA-III&SPEA/R for powertrain mount system stiffness parameter optimization problem.

Frogs and toads (anurans) are widely used to study many biological processes. Yet, few anuran genomes have been sequenced, limiting research on these organisms. Here, we produce a draft genome for the Mexican spadefoot toad, Spea multiplicata, which is a member of an unsequenced anuran clade. Atypically for amphibians, spadefoots inhabit deserts. Consequently, they possess many unique adaptations, including rapid growth and development, prolonged dormancy, phenotypic (developmental) plasticity, and adaptive, interspecies hybridization. We assembled and annotated a 1.07 Gb Sp. multiplicata genome containing 19,639 genes. By comparing this sequence to other available anuran genomes, we found gene amplifications in the gene families of nodal, hyas3, and zp3 in spadefoots, and obtained evidence that anuran genome size differences are partially driven by variability in intergenic DNA content. We also used the genome to identify genes experiencing positive selection and to study gene expression levels in spadefoot hybrids relative to their pure-species parents. Completion of the Sp. multiplicata genome advances efforts to determine the genetic bases of spadefoots’ unique adaptations and enhances comparative genomic research in anurans.

Interbreeding species often produce low-fitness hybrids due to genetic incompatibilities between parental genomes. Whether these incompatibilities reflect fixed allelic differences between hybridizing species, or, alternatively, standing variants that segregate within them, remains unknown for many natural systems. Yet, evaluating these alternatives is important for understanding the origins and nature of species boundaries. We examined these alternatives using spadefoot toads (genus Spea), which naturally hybridize. Specifically, we contrasted patterns of gene expression in hybrids relative to pure-species types in experimentally produced tadpoles from allopatric parents versus those from sympatric parents. We evaluated the prediction that segregating variation should result in gene expression differences between hybrids derived from sympatric parents versus hybrids derived from allopatric parents, and found that 24% of the transcriptome showed such differences. Our results further suggest that gene expression in hybrids has evolved in sympatry owing to evolutionary pressures associated with ongoing hybridization. Although we did not measure hybrid incompatibilities directly, we discuss the implications of our findings for understanding the nature of hybrid incompatibilities, how they might vary across populations over time, and the resulting effects on the evolutionary maintenance - or breakdown - of reproductive barriers between species.

Unbiased and sensitive quantification of low abundance small proteins in human plasma (e.g. hormones, immune factors, metabolic regulators) remains an unmet need. These small protein factors are typically analyzed individually and using antibodies that can lack specificity. Mass spectrometry (MS)-based proteomics has the potential to address these problems, however the analysis of plasma by MS is plagued by the extremely large dynamic range of this body fluid, with protein abundances spanning at least 13 orders of magnitude. Here we describe an enrichment assay (SPEA), that greatly simplifies the plasma dynamic range problem by enriching small-proteins of 2–10 kDa, enabling the rapid, specific and sensitive quantification of >100 small-protein factors in a single untargeted LC-MS/MS acquisition. Applying this method to perform deep-proteome profiling of human plasma we identify C5ORF46 as a previously uncharacterized human plasma protein. We further demonstrate the reproducibility of our workflow for low abundance protein analysis using a stable-isotope labeled protein standard of insulin spiked into human plasma. SPEA provides the ability to study numerous important hormones in a single rapid assay, which we applied to study the intermittent fasting response and observed several unexpected changes including decreased plasma abundance of the iron homeostasis regulator hepcidin.

In allocating parallel tasks to cores, most energy and thermal-aware scheduling techniques rely on Dynamic Voltage and Frequency Scaling (DVFS) to mark up and down core speeds for running the system under the desired constraints. While these techniques often meet the imposed system constraints, they are maladroit at identifying the best possible trade-offs between performance and energy, or between performance and temperature. This paper focuses on task-to-core allocation for optimizing performance ( P ), energy ( E ), and temperature ( T ) simultaneously. A solution set yielded by such algorithm comprises of multiple points forming a Pareto-front, not just scalar values. This paper employs Strength Pareto Evolutionary Algorithm (SPEA) and Non-Dominated Sorting Genetic Algorithm (NSGA), which have been demonstrated to be superior evolutionary optimization approaches in several domains. The paper utilizes and compares these techniques in DVFS-based PET-enabled scheduling algorithms, and highlights the differences between the two approaches. The paper also explores how the algorithmic characteristics affect the performance of the scheduling schemes. A variety of criteria combined with extensive experimentation help to compare the two approaches. The results show how varying different system and task parameters affect not just the PET goals individually and collectively but also the quality of trade-offs as well as the spread of solutions on the Pareto-front.

BackgroundStreptococcal pyrogenic exotoxin (SPE)A expression is epidemiologically linked to streptococcal tonsillo-pharyngitis and outbreaks of scarlet fever, although the mechanisms by which superantigens confer advantageStreptococcus pyogenesare unclear.S. pyogenesis an exclusively human pathogen. As the leukocyte profile of tonsil differs from peripheral blood, the impact of SPEA production on human tonsil cell function was investigated.MethodsHuman tonsil cells from routine tonsillectomy, were co-incubated with purified streptococcal superantigens or isogenic streptococcal culture supernatants, differing only in superantigen content. Tonsil cell proliferation was quantified by tritium-incorporation, and cell surface characteristics assessed by flow-cytometry. Soluble mediators were measured using ELISA and quantitative (q)RT-PCR was performed for immunoglobulin gene expression.ResultsTonsil T cells proliferated in response to SPEA and demonstrated typical release of pro-inflammatory cytokines. When cultured in the absence of superantigen, tonsil preparations released large quantities of immunoglobulin over 7d. In contrast, marked B cell apoptosis and abrogation of total IgA, IgM, and IgG production occurred in the presence of SPEA and other superantigens. In SPEA-stimulated cultures, T follicular helper (TfH) cells showed a reduction in CXCR5 expression, but up-regulation of CD134 (OX40), CD278 (ICOS) and CD150 (SLAM) expression, indicative of a phenotypic change in the TfH population and associated with impaired chemotactic response to CXCL13.ConclusionsSPEA and other superantigens cause dysregulated tonsil immune function, driving T cells from TFH to a proliferating phenotype, with resultant loss of B cells and immunoglobulin production, providing superantigen-producing bacteria with a likely survival advantage.

This study imitates the gene-therapy process at the forefront of medicine and proposes an innovative evaluative crossover operator. The evaluative crossover integrates a geneevaluation method with a gene-therapy approach in the traditional NSGA-II for finding uniformly distributed Pareto-optimal front of multi-objective optimization problems. To further enhance the advantages of fast non-dominate sorting and diversity preservation in NSGA-II, the proposed gene-evaluation method partially evaluates the merit of different crossover genes by substituting them in better parent and then calculating the fitness variances. The gene-therapy approach incorporates with the evaluative crossover to cure the mating parents mutually with respect to their gene contribution in order to retain superior genomes in the evolutionary population. Some comprehensive investigations for parameter setting are performed on a benchmark problem. Especially, three parameters of the evaluative crossover with a reasonable set of values are analyzed to realize their evolutionary effect. The experimental results show that a 100% crossover percentage with 10% crossover rate and a random therapeutic coefficient can achieve the best performance for E-NSGA-II. The proposed algorithm is tested on nine unconstrained multi-objective optimization problems. The experimental results are compared with five existing algorithms. The results show that the proposed E-NSGA-II is able to converge the Pareto-optimal front of all test problems, even though other algorithms experiences difficulties in approaching the global optima on some functions. E-NSGA-II can also achieve better diversity qualities than others. The results of algorithm analysis also reveal that the proposed evaluative crossover can intuitively evaluate gene contributions that can guide E-NSGA-II to perform an efficient search by dynamically shifting emphasis to significant genome in the feasible space without abdicating any portion of the candidate schemata. Although the convergence metric on the disconnected problem POL is slightly worse than four algorithms, E-NSGA-II outperforms almost all other algorithms on the mean of the convergence metric in other test problems. For the diversity metric, E-NSGA-II also performs better than all other algorithms dramatically in all test problems except for NSGA-II on POL and KUR. In the future, the proposed E-NSGA-II should further develop the properties of a simple yet efficient evaluative crossover operator, a revised mutation operator and a parameter-less approach to deal with a wide spectrum of real world multi-objective problems.

Polyphenism-in which multiple distinct phenotypes are produced from a single genotype owing to differing environmental conditions-is commonplace, but its molecular bases are poorly understood. Here, we examine the transcriptomic bases of a polyphenism in Mexican spadefoot toads (Spea multiplicata). Depending on their environment, their tadpoles develop into either a default "omnivore" morph or a novel "carnivore" morph. We compared patterns of gene expression among sibships that exhibited high versus low production of carnivores when reared in conditions that induce the carnivore morph versus those that do not. We found that production of the novel carnivore morph actually involved changes in fewer genes than did the maintenance of the default omnivore morph in the inducing environment. However, only body samples showed this pattern; head samples showed the opposite pattern. We also found that changes to lipid metabolism (especially cholesterol biosynthesis) and peroxisome contents and function might be crucial for establishing and maintaining differences between the morphs. Thus, our findings suggest that carnivore phenotype might have originally evolved following the breakdown of robustness mechanisms that maintain the default omnivore phenotype, and that the carnivore morph is developmentally regulated by lipid metabolism and peroxisomal form, function, and/or signaling. This study also serves as a springboard for further exploration into the nature and causes of plasticity in an emerging model system.

In the present research, a multi-objective mathematical model for construction material supply chain design under uncertainty is investigated. The considered supply chain is made up of a primary supplier and a number of projects (i.e., customers) demanding for different construction materials in different periods of time depending on the technical specifications of the demanded product in terms of life time. Moreover, the rate of product loss due to ill-timed transportation affects the respective managerial decisions. However, the most significant issue to address is the presence of uncertainty, for which we used the robust programming method proposed by Bertsimas and Sim. In order to solve the formulated mathematical model, we used epsilon-constraint method and the best-worst method as a multi-criteria decision-making method for small-scale cases, and meta-heuristic algorithms (NSGA-II, PESA, and SPEA) for large-scale problems. According to the obtained numerical results, one can observe that the SPEA algorithm outperformed all other algorithms, making it the optimal choice for addressing real cases. Moreover, a sensitivity analysis on the problem at different levels of the associated uncertainty with the parameters indicated the large impact of the uncertainty on the final outcomes. Results of this model can be used as efficient managerial instruments for optimizing the construction material supply chain design problem in the scope of civil project management.

Genome sequencing of a unique frog (Glandirana rugosa) having XY/ZW systems within the species and comparative genomics with other six frogs were performed using a batch-learning self-organizing map, which is unsupervised AI for oligonucleotide compositions, to clarify its genome characteristics., The Japanese wrinkled frog (Glandirana rugosa) is unique in having both XX-XY and ZZ-ZW types of sex chromosomes within the species. The genome sequencing and comparative genomics with other frogs should be important to understand mechanisms of turnover of sex chromosomes within one species or during a short period. In this study, we analyzed the newly sequenced genome of G. rugosa using a batch-learning self-organizing map which is unsupervised artificial intelligence for oligonucleotide compositions. To clarify genome characteristics of G. rugosa, we compared its short oligonucleotide compositions in all 1-Mb genomic fragments with those of other six frog species (Pyxicephalus adspersus, Rhinella marina, Spea multiplicata, Leptobrachium leishanense, Xenopus laevis, and Xenopus tropicalis). In G. rugosa, we found an Mb-level large size of repeat sequences having a high identity with the W chromosome of the African bullfrog (P. adspersus). Our study concluded that G. rugosa has unique genome characteristics with a high CG frequency, and its genome is assumed to heterochromatinize a large size of genome via methylataion of CG.

Trading strategies are usually employed for finding trading signals for increasing returns as well as reducing risks. As a result, many approaches have been proposed for obtaining trading strategy portfolio. The group trading strategy portfolio (GTSP) optimization approaches that can be used to provide various trading strategy portfolios were also proposed. Because different criteria should be considered to derive GTSPs, a MOGA (multi-objective genetic algorithm) based approach has been presented for searching non-dominated solutions. In this paper, to extract a better set of non-dominated solutions, we propose a SPEA-based algorithm for deriving GTSPs with two objective functions. Since the goal of trading is to get profit, the first objective function is utilized to evaluate the return and risk of a candidate GTSP. The second objective function is used to evaluate whether the numbers of strategies between groups are similar and weights of groups as well. Experiments were conducted on a financial dataset to show the effectiveness of the proposed approach and comparison results of the proposed approach and the previous approach.

Anti-sense transcription is increasingly being recognized as an important regulator of gene expression. But the transcriptome complementation of anti-sense RNA in hybrid relative to their inbred parents was largely unknown. In this study, we profiled strand-specific RNA sequencing (RNA-seq) in a maize hybrid and its inbred parents (B73 and Mo17) in two tissues. More anti-sense transcripts were present in the hybrid compared with the parental lines. We detected 293 and 242 single-parent expression of anti-sense (SPEA) transcripts in maize immature ear and leaf tissues, respectively. There was little overlap of the SPEA transcripts between the two maize tissues. These results suggested that SPEA is a general mechanism that drives extensive complementation in maize hybrids. More importantly, extremely high-level expression of anti-sense transcripts was associated with low-level expression of the cognate sense transcript by reducing the level of histone H3 lysine 36 methylation (H3K36me3). In summary, these SPEA transcripts increased our knowledge about the transcriptomic complementation in hybrid.

In this study, a new methodology, hybrid Strength Pareto Evolutionary Algorithm Reference Direction (SPEA/R) with Deep Neural Network (HDNN&SPEA/R), has been developed to achieve cost optimization of stiffness parameter for powertrain mount systems. This problem is formalized as a multi-objective optimization problem involving six optimization objectives: mean square acceleration of a rear engine mount, mean square displacement of a rear engine mount, mean square acceleration of a front left engine mount, mean square displacement of a front left engine mount, mean square acceleration of a front right engine mount, and mean square displacement of a front right engine mount. A hybrid HDNN&SPEA/R is proposed with the integration of genetic algorithm, deep neural network, and a Strength Pareto evolutionary algorithm based on reference direction for multi-objective SPEA/R. Several benchmark functions are tested, and results reveal that the HDNN&SPEA/R is more efficient than the typical deep neural network. stiffness parameter for powertrain mount systems optimization with HDNN&SPEA/R is simulated, respectively. It proved the potential of the HDNN&SPEA/R for stiffness parameter for powertrain mount systems optimization problem.

Streptococcus pyogenes encodes multiple virulence factors and their presence is often related to the severity of the disease. We designed the system of four low-volume multiplex PCR reactions to detect genes encoding 20 virulence factors: spd3, sdc, sdaB, sdaD, speB, spyCEP, scpA, mac, sic, speL, speK, speM, speC, speI, speA, speH, speG, speJ, smeZ, and ssa. Classification of strains based on the virulence factors absence or presence correlates with PFGE MLST and emm typing results. The typing/detection system is fast and cost-effective, can be used to detect GAS virulence factors and as a rapid tool to effectively differentiate between strains.

Social preferences enable animals to selectively interact with some individuals over others. One influential idea for the evolution of social preferences is that preferred signals evolve because they elicit greater neural responses from sensory systems. However, in juvenile plains spadefoot toad (Spea bombifrons), a species with condition-dependent mating preferences, responses of the preoptic area, but not of the auditory midbrain, mirror adult social preferences. To examine whether this separation of signal representation from signal valuation generalizes to other anurans, we compared the relative contributions of noradrenergic signalling in the preoptic area and auditory midbrain of S. bombifrons and its close relative Spea multiplicata. We manipulated body condition in juvenile toads by controlling diet and used high pressure liquid chromatography to compare call-induced levels of noradrenaline and its metabolite MHPG in the auditory midbrain and preoptic area of the two species. We found that calls from the two species induced different levels of noradrenaline and MHPG in the auditory system, with higher levels measured in both species for the more energetic S. bombifrons call. In contrast, noradrenaline levels in the preoptic area mirrored patterns of social preferences in both S. bombifrons and S. multiplicata. That is, noradrenaline levels were higher in response to the preferred calls within each species and were modified by diet in S. bombifrons (with condition-dependent preferences) but not S. multiplicata (with condition-independent preferences). Our results are consistent with a potentially important role for preoptic noradrenaline in the development of social preferences and indicate that it could be a target of selection in the evolution of condition-dependent social preferences.

We developed a new actuator, the plus Series-Parallel Elastic Actuator (+SPEA), which is a redundant actuator using brakes. This actuator can achieve additional objectives, other than performing a given task, such as minimum electrical energy consumption. In this paper, we developed a novel control strategy which consists of solving an optimal control problem. Solving this problem allows to use the redundancy of the actuator, as the brakes, in order to achieve lower electrical consumption. The results are then compared to the consumption of an equivalent non-redundant stiff actuator. The results highlight the capability of the actuator to reduce energy consumption in comparison with the latter actuator.

Plasticity-first evolution (PFE) posits that novel features arise when selection refines pre-existing phenotypic plasticity into an adaptive phenotype. However, PFE is controversial because few tests have been conducted in natural populations. Here we present evidence that PFE fostered the origin of an evolutionary novelty that allowed certain amphibians to invade a new niche—a distinctive carnivore morph. We compared morphology, gene expression and growth of three species of spadefoot toad tadpoles when reared on alternative diets: Scaphiopus holbrookii, which (like most frogs) never produce carnivores; Spea multiplicata, which sometimes produce carnivores, but only through diet-induced plasticity; and Spea bombifrons, which often produce carnivores regardless of diet. Consistent with PFE, we found diet-induced plasticity—in morphology and gene expression—in Sc. holbrookii, adaptive refinement of this plasticity in Sp. multiplicata, and further refinement of the carnivore phenotype in Sp. bombifrons. Generally, phenotypic plasticity might play a significant, if underappreciated, role in evolutionary innovation. Phenotypic plasticity may play a role in initiating novelty. This study provides evidence for selection on phenotypic plasticity leading to the evolution of a carnivore morph tadpole, which allowed spadefoot toads to invade a new niche.