33 research outputs found

    Rapid transcriptional plasticity of duplicated gene clusters enables a clonally reproducing aphid to colonise diverse plant species

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    Background: The prevailing paradigm of host-parasite evolution is that arms races lead to increasing specialisation via genetic adaptation. Insect herbivores are no exception and the majority have evolved to colonise a small number of closely related host species. Remarkably, the green peach aphid, Myzus persicae, colonises plant species across 40 families and single M. persicae clonal lineages can colonise distantly related plants. This remarkable ability makes M. persicae a highly destructive pest of many important crop species. Results: To investigate the exceptional phenotypic plasticity of M. persicae, we sequenced the M. persicae genome and assessed how one clonal lineage responds to host plant species of different families. We show that genetically identical individuals are able to colonise distantly related host species through the differential regulation of genes belonging to aphid-expanded gene families. Multigene clusters collectively upregulate in single aphids within two days upon host switch. Furthermore, we demonstrate the functional significance of this rapid transcriptional change using RNA interference (RNAi)-mediated knock-down of genes belonging to the cathepsin B gene family. Knock-down of cathepsin B genes reduced aphid fitness, but only on the host that induced upregulation of these genes. Conclusions: Previous research has focused on the role of genetic adaptation of parasites to their hosts. Here we show that the generalist aphid pest M. persicae is able to colonise diverse host plant species in the absence of genetic specialisation. This is achieved through rapid transcriptional plasticity of genes that have duplicated during aphid evolution

    Agroecological management of cucurbit-infesting fruit fly: a review

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    Plant species diversity for sustainable management of crop pests and diseases in agroecosystems: a review

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    Learning Dynamics with Synchronous, Asynchronous and General Semantics

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    International audienceLearning from interpretation transition (LFIT) automatically constructs a model of the dynamics of a system from the observation of its state transitions. So far, the systems that LFIT handles are restricted to synchronous deterministic dynamics, i.e., all variables update their values at the same time and, for each state of the system, there is only one possible next state. However, other dynamics exist in the field of logical modeling, in particular the asynchronous semantics which is widely used to model biological systems. In this paper, we focus on a method that learns the dynamics of the system independently of its semantics. For this purpose, we propose a modeling of multi-valued systems as logic programs in which a rule represents what can occurs rather than what will occurs. This modeling allows us to represent non-determinism and to propose an extension of LFIT in the form of a semantics free algorithm to learn from discrete multi-valued transitions, regardless of their update schemes. We show through theoretical results that synchronous, asynchronous and general semantics are all captured by this method. Practical evaluation is performed on randomly generated systems and benchmarks from biological literature to study the scalabil-ity of this new algorithm regarding the three aforementioned semantics

    Combining Knowledge and Metrics to Control Software Quality Factors

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    The LESD project (Linguistic Engineering for Software Development) aimed to develop computing tools for analysis and reasoning on functional or preliminary specifications of aerospace software written in English

    Certifying Standard and Stratified Datalog Inference Engines in SSReflect

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    International audienceWe propose a SSReflect library for logic programming in the Datalog setting. As part of this work, we give a first mechanization of standard Datalog and of its extension with stratified negation. The library contains a formalization of the model theoretical and fix-point semantics of the languages, implemented through bottom-up and, respectively, through stratified evaluation procedures. We provide corresponding soundness, termination, completeness and model minimality proofs. To this end, we rely on the Coq proof assistant and SSReflect. In this context, we also construct a preliminary framework for dealing with stratified programs. We consider this to be a necessary first step towards the certification of security-aware data-centric applications

    From failure to success : comparing a denotational and a declarative semantics for Horn clause logic

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    The main purpose of the paper is to relate different models for Horn Clause Logic: operational, denotational, declarative. We study their relationship by contrasting models based on interleaving, on the one hand, to models based on maximal parallelism, on the other. We make use of complete metric spaces as an important mathematical tool, both in defining and in comparing the various models
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