Biology subjects

Nygren, E.

Publications and source records attributed to Nygren, E..

2 recordsLinked to original sources

bioRxiv2026

Trans-kingdom delivery of aphid-derived small RNAs into Arabidopsis thaliana modulates plant immunity

Herbivore insects are on an evolutionary tug-of-war with plants. An important part of the plant-herbivore insect interaction is the exchange of molecules, in particular proteins (in the form of effectors) and RNA. Among RNAs, small RNAs have been identified as important molecules shaping the communication between different pests/parasites and their host, but the role of these molecules in the interaction between aphids and plants is not well understood. Here, we explored the role of aphid-derived sRNAs in the interaction between Arabidopsis thaliana and the green peach aphid, Myzus persicae. Using sRNA sequencing, we identified a significant amount of bona-fide aphid-derived sRNAs within Arabidopsis tissues. Using immunoprecipitation followed by sRNA sequencing and degradome sequencing we determined that these sRNAs are incorporated into endogenous AGO proteins, in particular AGO1, and induce the cleavage of transcripts involved in the modulation of the immune response against the aphid. Our results indicate that aphid sRNAs attenuate the immune response of Arabidopsis thaliana and can improve aphid performance. In addition, we identified that aphid-derived sRNAs are commonly injected into other aphid-host combinations. Accordingly, our work indicates that aphid-derived sRNAs are active players in aphid-host interactions.

Plant Biology↗

bioRxiv2019

Learning temporal integration from internal feedback

There has been much focus on the mechanisms of temporal integration, but little on how circuits learn to integrate. In the adult oculomotor system, where a neural integrator maintains fixations, changes in integration dynamics can be driven by visual error signals. However, we show through dark-rearing experiments that visual inputs are not necessary for initial integrator development. We therefore propose a vision-independent learning mechanism whereby a recurrent network learns to integrate via a teaching signal formed by low-pass filtered feedback of its population activity. The key is the segregation of local recurrent inputs onto a dendritic compartment and teaching inputs onto a somatic compartment of an integrator neuron. Model instantiation for oculomotor control shows how a self-corrective teaching signal through the cerebellum can generate an integrator with both the dynamical and tuning properties necessary to drive eye muscles and maintain gaze angle. This bootstrap learning paradigm may be relevant for development and plasticity of temporal integration more generally. Highlights- A neuronal architecture that learns to integrate saccadic commands for eye position. - Learning is based on the recurrent dendritic prediction of somatic teaching signals. - Experiment and model show that no visual feedback is required for initial integrator learning. - Cerebellum is an internal teacher for motor nuclei and integrator population.

neuroscience↗