Phylogenomic analysis of the Chlamydomonas genome unmasks proteins potentially involved in photosynthetic function and regulation

Chlamydomonas reinhardtii, a unicellular green alga, has been exploited as a reference organism for identifying proteins and activities associated with the photosynthetic apparatus and the functioning of chloroplasts. Recently, the full genome sequence of Chlamydomonas was generated and a set of gene models, representing all genes on the genome, was developed. Using these gene models, and gene models developed for the genomes of other organisms, a phylogenomic, comparative analysis was performed to identify proteins encoded on the Chlamydomonas genome which were likely involved in chloroplast functions (or specifically associated with the green algal lineage); this set of proteins has been designated the GreenCut. Further analyses of those GreenCut proteins with uncharacterized functions and the generation of mutant strains aberrant for these proteins are beginning to unmask new layers of functionality/regulation that are integrated into the workings of the photosynthetic apparatus

Defects in tRNA Modification Associated with Neurological and Developmental Dysfunctions in Caenorhabditis elegans Elongator Mutants

Elongator is a six subunit protein complex, conserved from yeast to humans. Mutations in the human Elongator homologue, hELP1, are associated with the neurological disease familial dysautonomia. However, how Elongator functions in metazoans, and how the human mutations affect neural functions is incompletely understood. Here we show that in Caenorhabditis elegans, ELPC-1 and ELPC-3, components of the Elongator complex, are required for the formation of the 5-carbamoylmethyl and 5-methylcarboxymethyl side chains of wobble uridines in tRNA. The lack of these modifications leads to defects in translation in C. elegans. ELPC-1::GFP and ELPC-3::GFP reporters are strongly expressed in a subset of chemosensory neurons required for salt chemotaxis learning. elpc-1 or elpc-3 gene inactivation causes a defect in this process, associated with a posttranscriptional reduction of neuropeptide and a decreased accumulation of acetylcholine in the synaptic cleft. elpc-1 and elpc-3 mutations are synthetic lethal together with those in tuc-1, which is required for thiolation of tRNAs having the 5′methylcarboxymethyl side chain. elpc-1; tuc-1 and elpc-3; tuc-1 double mutants display developmental defects. Our results suggest that, by its effect on tRNA modification, Elongator promotes both neural function and development

Reconstructing 3D coastal cliffs from airborne oblique photographs without ground control points

Coastal cliff collapse hazard assessment requires measuring cliff face topography at regular intervals. Terrestrial laser scanner techniques have proven useful so far but are expensive to use either through purchasing the equipment or through survey subcontracting. In addition, terrestrial laser surveys take time which is sometimes incompatible with the time during with the beach is accessible at low-tide. By comparison, structure from motion techniques (SFM) are much less costly to implement, and if airborne, acquisition of several kilometers of coastline can be done in a matter of minutes. In this paper, the potential of GPS-tagged oblique airborne photographs and SFM techniques is examined to reconstruct chalk cliff dense 3D point clouds without Ground Control Points (GCP). The focus is put on comparing the relative 3D point of views reconstructed by Visual SFM with their synchronous Solmeta Geotagger Pro2 GPS locations using robust estimators. With a set of 568 oblique photos, shot from the open door of an airplane with a triplet of synchronized Nikon D7000, GPS and SFM-determined view point coordinates converge to X: ±31.5 m; Y: ±39.7 m; Z: ±13.0 m (LE66). Uncertainty in GPS position affects the model scale, angular attitude of the reference frame (the shoreline ends up tilted by 2°) and absolute positioning. Ground Control Points cannot be avoided to orient such models

CLIFF COLLAPSE HAZARD FROM REPEATED MULTICOPTER UAV ACQUISITIONS: RETURN ON EXPERIENCE

Cliff collapse poses a serious hazard to infrastructure and passers-by. Obtaining information such as magnitude-frequency relationship for a specific site is of great help to adapt appropriate mitigation measures. While it is possible to monitor hundreds-of-meter-long cliff sites with ground based techniques (e.g. lidar or photogrammetry), it is both time consuming and scientifically limiting to focus on short cliff sections. In the project SUAVE, we sought to investigate whether an octocopter UAV photogrammetric survey would perform sufficiently well in order to repeatedly survey cliff face geometry and derive rock fall inventories amenable to probabilistic rock fall hazard computation. An experiment was therefore run on a well-studied site of the chalk coast of Normandy, in Mesnil Val, along the English Channel (Northern France). Two campaigns were organized in January and June 2015 which surveyed about 60 ha of coastline, including the 80-m-high cliff face, the chalk platform at its foot, and the hinterland in a matter of 4 hours from start to finish. To conform with UAV regulations, the flight was flown in 3 legs for a total of about 30 minutes in the air. A total of 868 and 1106 photos were respectively shot with a Sony NEX 7 with fixed focal 16mm. Three lines of sight were combined: horizontal shots for cliff face imaging, 45°-oblique views to tie plateau/platform photos with cliff face images, and regular vertical shots. Photogrammetrically derived dense point clouds were produced with Agisoft Photoscan at ultra-high density (median density is 1 point every 1.7cm). Point cloud density proved a critical parameter to reproduce faithfully the chalk face’s geometry. Tuning down the density parameter to “high” or “medium”, though efficient from a computational point of view, generated artefacts along chalk bed edges (i.e. smoothing the sharp gradient) and ultimately creating ghost volumes when computing cloud to cloud differences. Yet, from a hazard point of view, this is where small rock fall will most likely occur. Absolute orientation of both point clouds proved unsufficient despite the 30 black and white quadrants ground control point DGPS surveyed. Additional ICP was necessary to reach centimeter-level accuracy and segment rock fall scars corresponding to the expected average daily rock fall volume (ca. 0.013 m3)

FACETS : A CLOUDCOMPARE PLUGIN TO EXTRACT GEOLOGICAL PLANES FROM UNSTRUCTURED 3D POINT CLOUDS

Geological planar facets (stratification, fault, joint…) are key features to unravel the tectonic history of rock outcrop or appreciate the stability of a hazardous rock cliff. Measuring their spatial attitude (dip and strike) is generally performed by hand with a compass/clinometer, which is time consuming, requires some degree of censoring (i.e. refusing to measure some features judged unimportant at the time), is not always possible for fractures higher up on the outcrop and is somewhat hazardous. 3D virtual geological outcrop hold the potential to alleviate these issues. Efficiently segmenting massive 3D point clouds into individual planar facets, inside a convenient software environment was lacking. FACETS is a dedicated plugin within CloudCompare v2.6.2 (http://cloudcompare.org/ ) implemented to perform planar facet extraction, calculate their dip and dip direction (i.e. azimuth of steepest decent) and report the extracted data in interactive stereograms. Two algorithms perform the segmentation: Kd-Tree and Fast Marching. Both divide the point cloud into sub-cells, then compute elementary planar objects and aggregate them progressively according to a planeity threshold into polygons. The boundaries of the polygons are adjusted around segmented points with a tension parameter, and the facet polygons can be exported as 3D polygon shapefiles towards third party GIS software or simply as ASCII comma separated files. One of the great features of FACETS is the capability to explore planar objects but also 3D points with normals with the stereogram tool. Poles can be readily displayed, queried and manually segmented interactively. The plugin blends seamlessly into CloudCompare to leverage all its other 3D point cloud manipulation features. A demonstration of the tool is presented to illustrate these different features. While designed for geological applications, FACETS could be more widely applied to any planar objects

Emergent characteristics of rockfall inventories captured at a regional scale

High-resolution rockfall inventories captured at a regional scale are scarce. This is partly owing to difficulties in measuring the range of possible rockfall volumes with sufficient accuracy and completeness, and at a scale exceeding the influence of localised controls. This paucity of data restricts our ability to abstract patterns of erosion, identify longterm changes in behaviour and assess how rockfalls respond to changes in rock mass structural and environmental conditions. We have addressed this by developing a workflow that is tailored to monitoring rockfalls and the resulting cliff retreat continuously (in space), in 3D and over large spatial scales (> 10 4 m). We tested our approach by analysing rockfall activity along 20.5 km of coastal cliffs in North Yorkshire (UK), in what we understand to be the first multi-temporal detection of rockfalls at a regional scale. We show that rockfall magnitude-frequency relationships, which often underpin predictive models of erosion, are highly sensitive to the spatial extent of monitoring. Variations in rockfall shape with volume also imply a systemic shift in the underlying mechanisms of detachment with scale, leading us to question the validity of applying a single probabilistic model to the full range of rockfalls observed here. Finally, our data emphasise the importance of cliff retreat as an episodic process. Going forwards, there will a pressing need to understand and model the erosional response of such coastlines to rising global sea levels as well as projected changes to winds, tides, wave climates, precipitation and storm events. The methodologies and data presented here are fundamental to achieving this, marking a step-change in our ability to understand the competing effects of different processes in determining the magnitude and frequency of rockfall activity and ultimately meaning that we are better placed to investigate relationships between process and form/erosion at critical, regional scales