Morel, P. | bioRxiv Science

bioRxiv2021

Cell layer-specific expression of the B-class MADS-box gene PhDEF drives petal tube or limb development in petunia flowers

Floral homeotic MADS-box transcription factors ensure the correct morphogenesis of floral organs, which are organized in different cell layers deriving from the meristematic L1, L2 and L3 layers. How cells from these distinct layers acquire their respective identity and coordinate their growth to ensure normal floral organ morphogenesis is unresolved. Here, we study petunia petals that form a limb and tube through congenital fusion, a complex morphology that coevolved with pollinators. We have identified petunia mutants expressing the B-class MADS-box gene PhDEF in the epidermis or in the mesophyll of the petal only, called wico and star respectively. Strikingly, wico flowers form a strongly reduced tube while their limbs are almost normal, while star flowers form a normal tube but very reduced and unpigmented limbs, showing that petunia petal morphogenesis is highly modular. Comparative transcriptome analysis of star, wico and wild-type petals revealed a strong down-regulation of the anthocyanin production pathway in star petals including its major regulator ANTHOCYANIN2 (AN2). We found that PhDEF directly binds to AN2 regulatory sequence in vitro by gel shift assay, and in vivo by chromatin immunoprecipitation, suggesting that PhDEF directly activates the petal pigmentation pathway by activating AN2. Altogether, we show that cell-layer specific homeotic activity in petunia petals differently impacts tube and limb development, revealing the relative importance of the different cell layers in the modular architecture of petunia petals.

plant biology↗

bioRxiv2021

Statistical determinants of visuomotor adaptation in a virtual reality three-dimensional environment

Neurorehabilitation in patients suffering from motor deficits relies on relearning or re-adapting motor skills. Yet our understanding of motor learning is based mostly on results from one or two-dimensional experimental paradigms with highly confined movements. Since everyday movements are conducted in three-dimensional space, it is important to further our understanding about the effect that gravitational forces or perceptual anisotropy might or might not have on motor learning along all different dimensions relative to the body. Here we test how well existing concepts of motor learning generalize to movements in 3D. We ask how a subjects variability in movement planning and sensory perception influences motor adaptation along three different body axes. To extract variability and relate it to adaptation rate, we employed a novel hierarchical two-state space model using Bayesian modeling via Hamiltonian Monte Carlo procedures. Our results show that differences in adaptation rate occur between the coronal, sagittal and horizontal planes and can be explained by the Kalman gain, i.e., a statistically optimal solution integrating planning and sensory information weighted by the inverse of their variability. This indicates that optimal integration theory for error correction holds for 3D movements and explains adaptation rate variation between movements in different planes.

neuroscience↗