WUSCHEL-related homeobox family genes in rice control lateral root primordium size

The development of a plastic root system is essential for stable crop production under variable environments. Rice plants have two types of lateral roots (LRs): S-type (short and thin) and L-type (long, thick, and capable of further branching). LR types are determined at the primordium stage, with a larger primordium size in L-types than S-types. Despite the importance of LR types for rice adaptability to variable water conditions, molecular mechanisms underlying the primordium size control of LRs are unknown. Here, we show that two WUSCHEL-related homeobox (WOX) genes have opposing roles in controlling LR primordium (LRP) size in rice. Root tip excision on seminal roots induced L-type LR formation with wider primordia formed from an early developmental stage. QHB/OsWOX5 was isolated as a causative gene of a mutant that is defective in S-type LR formation but produces more L-type LRs than wild-type (WT) plants following root tip excision. A transcriptome analysis revealed that OsWOX10 is highly up-regulated in L-type LRPs. OsWOX10 overexpression in LRPs increased the LR diameter in an expression-dependent manner. Conversely, the mutation in OsWOX10 decreased the L-type LR diameter under mild drought conditions. The qhb mutants had higher OsWOX10 expression than WT after root tip excision. A yeast one-hybrid assay revealed that the transcriptional repressive activity of QHB was lost in qhb mutants. An electrophoresis mobility shift assay revealed that OsWOX10 is a potential target of QHB. These data suggest that QHB represses LR diameter increase, repressing OsWOX10. Our findings could help improve root system plasticity under variable environments.

The population genetics of collateral resistance and sensitivity

Resistance mutations against one drug can elicit collateral sensitivity against other drugs. Multi-drug treatments exploiting such trade-offs can help slow down the evolution of resistance. However, if mutations with diverse collateral effects are available, a treated population may evolve either collateral sensitivity or collateral resistance. How to design treatments robust to such uncertainty is unclear. We show that many resistance mutations in Escherichia coli against various antibiotics indeed have diverse collateral effects. We propose to characterize such diversity with a joint distribution of fitness effects (JDFE) and develop a theory for describing and predicting collateral evolution based on simple statistics of the JDFE. We show how to robustly rank drug pairs to minimize the risk of collateral resistance and how to estimate JDFEs. In addition to practical applications, these results have implications for our understanding of evolution in variable environments.

Life history adaptations to fluctuating environments: Combined effects of demographic buffering and lability of vital rates

Demographic buffering and lability have both been identified as important adaptive strategies to optimise long-term fitness in variable environments. These strategies are not mutually exclusive, however we lack efficient methods to measure their relative importance. Here, we define a new index to measure the total lability for a given life history, and use stochastic simulations to disentangle relative fitness effects of buffering and lability. The simulations use 81 animal matrix population models, and different scenarios to explore how the strategies vary across life histories. The highest potential for adaptive demographic lability was found for short- to intermediately long-lived species, while demographic buffering was the main response in slow-living species. This study suggests that faster-living species are more responsive to environmental variability, both for positive or negative effects. Our methods and results provide a more comprehensive view of adaptations to variability, of high relevance to predict species responses to climate change.

Biodiversity Hotspots for Conservation of Hancornia speciosa GOMES

Hancornia speciosa is the target of research on genetic diversity, ethnobotanical and medicinal studies. However, information on the genetic variability of populations associated with modeling the potential distribution in the state of Sergipe has not yet been performed. The objective of this study was to predict the potential occurrence of H. speciosa in areas of high use of their fruits. The maximum entropy method was used to detect the distribution patterns of H. speciosa in variable environments. The diversity of four natural populations, situated in areas of extractivist, was determined by ISSR molecular markers. The species occurs more densely in the coastal regions of Sergipe. The prediction of occurrence indicates that the species reduces areas of occurrence, mainly due to anthropic actions. It is suggested that the species needs public policies aimed at its conservation and the priority populations for conservation.

Evolution of phenotypic fluctuation under host-parasite interactions

Robustness and plasticity are essential features that allow biological systems to cope with complex and variable environments. In a constant environment, robustness, i.e., insensitivity of phenotypes, is expected to increase, whereas plasticity, i.e., the changeability of phenotypes, tends to diminish. Under a variable environment, existence of plasticity will be relevant. The robustness and plasticity, on the other hand, are related to phenotypic variances. As phenotypic variances decrease with the increase in robustness to perturbations, they are expected to decrease through the evolution. However, in nature, phenotypic fluctuation is preserved to a certain degree. One possible cause for this is environmental variation, where one of the most important “environmental” factors will be inter-species interactions. As a first step toward investigating phenotypic fluctuation in response to an inter-species interaction, we present the study of a simple two-species system that comprises hosts and parasites. Hosts are expected to evolve to achieve a phenotype that optimizes fitness. Then, the robustness of the corresponding phenotype will be increased by reducing phenotypic fluctuations. Conversely, plasticity tends to evolve to avoid certain phenotypes that are attacked by parasites. By using a dynamic model of gene expression for the host, we investigate the evolution of the genotype-phenotype map and of phenotypic variances. If the host–parasite interaction is weak, the fittest phenotype of the host evolves to reduce phenotypic variances. In contrast, if there exists a sufficient degree of interaction, the phenotypic variances of hosts increase to escape parasite attacks. For the latter case, we found two strategies: if the noise in the stochastic gene expression is below a certain threshold, the phenotypic variance increases via genetic diversification, whereas above this threshold, it is increased mediated by noise-induced phenotypic fluctuation. We examine how the increase in the phenotypic variances caused by parasite interactions influences the growth rate of a single host, and observed a trade-off between the two. Our results help elucidate the roles played by noise and genetic mutations in the evolution of phenotypic fluctuation and robustness in response to host–parasite interactions.

Adaptability of Improved NEAT in Variable Environments

Qualitative research experiment to gather descriptive data on the NEAT algorithm’s performance in an environment with variability. Individual research performed for my AP Research paper. The experiment conducted using Python and the NEAT-Python library. The research conducted was for the sake of doing research in the field of AI in computer science and is rather outdated.

Adaptability of Improved NEAT in Variable Environments

Qualitative research experiment to gather descriptive data on the NEAT algorithm’s performance in an environment with variability. Individual research performed for my AP Research paper. The experiment conducted using Python and the NEAT-Python library. The research conducted was for the sake of doing research in the field of AI in computer science and is rather outdated.

The role of phenotypic plasticity in the establishment of range margins

It has been argued that adaptive phenotypic plasticity may facilitate range expansions over spatially and temporally variable environments. However, plasticity may induce fitness costs. This may hinder the evolution of plasticity. Earlier modelling studies examined the role of plasticity during range expansions of populations with fixed genetic variance. However, genetic variance evolves in natural populations. This may critically alter model outcomes. We ask: How does the capacity for plasticity in populations with evolving genetic variance alter range margins that populations without the capacity for plasticity are expected to attain? We answered this question using computer simulations and analytical approximations. We found a critical plasticity cost above which the capacity for plasticity has no impact on the expected range of the population. Below the critical cost, by contrast, plasticity facilitates range expansion, extending the range in comparison to that expected for populations without plasticity. We further found that populations may evolve plasticity to buffer temporal environmental fluctuations, but only when the plasticity cost is below the critical cost. Thus, the cost of plasticity is a key factor involved in range expansions of populations with the potential to express plastic response in the adaptive trait.