RTM3

Restriction of long-distance movement of several potyviruses in Arabidopsis (Arabidopsis thaliana) is controlled by at least three dominant restricted TEV movement (RTM) genes, named RTM1, RTM2, and RTM3. RTM1 encodes a protein belonging to the jacalin family, and RTM2 encodes a protein that has similarities to small heat shock proteins. In this article, we describe the positional cloning of RTM3, which encodes a protein belonging to an undescribed protein family of 29 members that has a meprin and TRAF homology (MATH) domain in its amino-terminal region and a coiled-coil domain at its carboxy-terminal end. Involvement in the RTM resistance system is the first biological function experimentally identified for a member of this new gene family in plants. Our analyses showed that the coiled-coil domain is not only highly conserved between RTM3-homologous MATH-containing proteins but also in proteins lacking a MATH domain. The cluster organization of the RTM3 homologs in the Arabidopsis genome suggests the role of duplication events in shaping the evolutionary history of this gene family, including the possibility of deletion or duplication of one or the other domain. Protein-protein interaction experiments revealed RTM3 self-interaction as well as an RTM1-RTM3 interaction. However, no interaction has been detected involving RTM2 or the potyviral coat protein previously shown to be the determinant necessary to overcome the RTM resistance. Taken together, these observations strongly suggest the RTM proteins might form a multiprotein complex in the resistance mechanism to block the long-distance movement of potyviruses

RTM3, Which Controls Long-Distance Movement of Potyviruses, Is a Member of a New Plant Gene Family Encoding a Meprin and TRAF Homology Domain-Containing Protein

Restriction of long-distance movement of several potyviruses in Arabidopsis (Arabidopsis thaliana) is controlled by at least three dominant restricted TEV movement (RTM) genes, named RTM1, RTM2, and RTM3. RTM1 encodes a protein belonging to the jacalin family, and RTM2 encodes a protein that has similarities to small heat shock proteins. In this article, we describe the positional cloning of RTM3, which encodes a protein belonging to an undescribed protein family of 29 members that has a meprin and TRAF homology (MATH) domain in its amino-terminal region and a coiled-coil domain at its carboxy-terminal end. Involvement in the RTM resistance system is the first biological function experimentally identified for a member of this new gene family in plants. Our analyses showed that the coiled-coil domain is not only highly conserved between RTM3- homologous MATH-containing proteins but also in proteins lacking a MATH domain. The cluster organization of the RTM3 homologs in the Arabidopsis genome suggests the role of duplication events in shaping the evolutionary history of this gene family, including the possibility of deletion or duplication of one or the other domain. Protein-protein interaction experiments revealed RTM3 self-interaction as well as an RTM1-RTM3 interaction. However, no interaction has been detected involving RTM2 or the potyviral coat protein previously shown to be the determinant necessary to overcome the RTM resistance. Taken together, these observations strongly suggest the RTM proteins might form a multiprotein complex in the resistance mechanism to block the long-distance movement of potyviruses.Copyrighted by the American Society of Plant Biologists

Mapping riparian forest species for biodiversity analysis by fusion of Airborne LiDAR and multispectral satellite imagery

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Fusion of Dense Airborne LiDAR and Multispectral Sentinel-2 and Pleiades Satellite Imagery for Mapping Riparian Forest Species Biodiversity at Tree Level

International audienceMultispectral and 3D LiDAR remote sensing data sources are valuable tools for characterizing the 3D vegetation structure and thus understanding the relationship between forest structure, biodiversity, and microclimate. This study focuses on mapping riparian forest species in the canopy strata using a fusion of Airborne LiDAR data and multispectral multi-source and multi-resolution satellite imagery: Sentinel-2 and Pleiades at tree level. The idea is to assess the contribution of each data source in the tree species classification at the considered level. The data fusion was processed at the feature level and the decision level. At the feature level, LiDAR 2D attributes were derived and combined with multispectral imagery vegetation indices. At the decision level, LiDAR data were used for 3D tree crown delimitation, providing unique trees or groups of trees. The segmented tree crowns were used as a support for an object-based species classification at tree level. Data augmentation techniques were used to improve the training process, and classification was carried out with a random forest classifier. The workflow was entirely automated using a Python script, which allowed the assessment of four different fusion configurations. The best results were obtained by the fusion of Sentinel-2 time series and LiDAR data with a kappa of 0.66, thanks to red edge-based indices that better discriminate vegetation species and the temporal resolution of Sentinel-2 images that allows monitoring the phenological stages, helping to discriminate the species

A member of a new plant gene family encoding a meprin and TRAF homology (MATH) domain-containing protein is involved in restriction of long distance movement of plant viruses

Restriction of long distance movement of several potyviruses in Arabidopsis thaliana is controlled by at least three dominant restricted TEV movement (RTM) genes, named RTM1, RTM2 and RTM3 and acts as a non-conventional resistance. RTM1 encodes a protein belonging to the jacalin family and RTM2 encodes a protein which has similarities to small heat shock proteins. The recent cloning of RTM3 which encodes a protein belonging to an unknown protein family of 29 members that has a meprin and TRAF homology (MATH) domain in its N-terminal region and a coiled-coil (CC) domain at its C-terminal end is an important breakthrough for a better understanding of this resistance process. Not only the third gene involved in this resistance has been identified and has allowed revealing a new gene family in plant but the discovery that the RTM3 protein interacts directly with RTM1 strongly suggests that the RTM proteins form a multimeric complex. However, these data also highlight striking similarities of the RTM resistance with the well known R-gene mediated resistance

An investigation into lidar scan angle impacts on stand attribute predictions in different forest environments

International audienceAs studies have underlined the sensitivity of lidar metrics to scan angles, the objective of this study was twofold. Firstly, we further investigated the influence of lidar scan angle on the ABA predictions of stand attributes of riparian (29 field plots), broadleaf (42 field plots), coniferous (31 field plots) and mixed (45 field plots) forest types in France. Secondly, we evaluated the potential of voxelisation approaches to normalise scan angle effects in lidar metrics and mitigate scan angle effects in ABA models. To achieve these objectives, we first selected a model based on four lidar metrics with different sensitivities to lidar scan angle, i.e. mean and variance of canopy height values, gap-fraction, and coefficient of variation of plant area density (PAD) profile. For each plot, we considered the point cloud scanned from one flight line independently and characterised each resulting point cloud by the mean scan angle (MSA) and classified them into one of three classes: A (0° <=MSA < 10°), B (10°<=MSA < 20°) or C (20°<=MSA < 30°). An experimental setup involving nine scenarios was conceived to study the impact of the number of flight lines (scenarios fl1, fl2 and fl3) and predominant scan angle (scenarios A, B or C) or combination of scan angle directions (scenarios A and B, or A and C, or B and C), on area-based approach (ABA) models. We built ABA models for the same forest plots for 5000 resampled datasets in each scenario to predict three forest attributes, i.e., stem and total volume (Vst and Vtot) and basal area (BA). Three goodness-of-fit criteria were computed for each model (coefficient of determination (R2), relative root mean square error (rRMSE) and mean percentage error (MPE). We compared the distributions of the goodness-of-fit criteria between scenarios to assess the behaviour of the predictive models when: 1) the number of flight lines (i.e., scan angles) increases (fl1, fl2 or fl3); 2) lidar datasets comprise specific scan angle (A, B or C) or combination of scan angles (AB, AC or BC); 3) voxelisation is used to compute Pf and CVPAD. The results show that models built with point clouds scanned from multiple flight lines were more robust, with a lower standard deviation of their goodness-of-fit criteria. On average, across all forest types, compared to fl1, the standard deviations of R2 distributions were lower for fl2 and fl3 by 42 % and 77 %, respectively. We also observed that a dataset with a predominantly nadir configuration (i.e., scenario A) did not always result in better predictions (mean R2 higher by 0.08, 0.07, 0.04 for scenario B for broadleaf, coniferous and mixed, respectively). For a set of calibration plots, the resulting forest attribute models depend on the acquisition geometry over the plots, as observed in this study, which could result in unreliable wall-to-wall predictions. The risk is particularly high in acquisitions with low overlapping rates, with many areas covered by only one flight line. Using voxel-based Pf and CVPAD together with the mean and variance of heights helped to mitigate the impacts of changes in scan angles by a) increasing the means of the distributions, thereby improving the accuracy of predictions, or b) reducing the standard deviations, thereby increasing prediction precision, or c) both of the above