ROV3G 2021 database: geophysical data on the continental shelf offshore Santo Stefano al Mare and San Lorenzo al mare, Liguria, Italy.

SEANOE database is an online platform where data from oceanographic cruises can be stored.ROV3G scientific cruise is dedicated to the morpho-tectonic study of the ligurian shelf, through the acquisition of bathymetric data and optical images with HROV Ariane. This cruise took place on R/V Europe in october 2021, and constituted a pedagogic project for the students of Master 3G Recherche, Géologie et Géophysique, of Université Côte d'Azur (UCA), attached to Géoazur lab. The M2 students were in charge of the scientific project, they determined the goals of the cruise, took part in the acquisition and interpretation of the data. During the 3 days cruise, we acquired bathymetric data at shallow depth on the continental shelf offshore Santo Stefano al Mare and San Lorenzo al Mare, along the Ligurian coast. The bathymetry on the continental shelf exhibits morphologies that are probably related to the Flyschs formation that is outcroping onshore (Stani et al., 2010), and that is partially capped by late quaternary deposits (as identified in seismic data and interpreted in Bozzano et al., 2006). Ridges identified as paleo-shorelines (paleo-beaches?) have been investigated with HROV ariane whose navigation is also published here. Videos are available on video.ifremer.frHere we publish two bathymetric grids at high-resolution, calculated from the ME70 multibeam echosounder of R/V Europe, using GLOBE software (Poncelet et al., 2022). The shallowest part of the plateau is gridded in a 5 m digital elevation model (DEM), while the entire survey area is gridded at 10m resolution. The back-scatter maps, gridded at 6 m, produced with Sonarscope software (Augustin et al., 2022), are also available (raw and compensated). All grids are in WGS84 (EPSG:4326)

Deciphering molecular origin and functional impact of structural variation in maize through genome sequences comparison and integrative analysis of genetic variation, transcriptome and phenotype data

International audienceStructural variation (SV) is a major driver of plant adaptation and genome evolution. It originates from transposable element insertion, as well as gene Copy Number (CNV) and Presence/Absence Variation (PAV). Maize is a crop species with a complex genome, and exhibits extensive SV among lines, as well as strong phenotypic differences. It is therefore a good model to explore the diverse molecular mechanisms leading to SV, and to investigate to what extent SV impacts phenotypic variation. Finally, the geographical origin of the different maize inbred lines is well described, allowing for linking SV to environmental adaptation. Here, we present whole genome assemblies from seven European and American maize lines of various geographical origins and phenotypes, and with contrasted genome size. This dataset allows unprecedented genome-wide comparisons and characterization of maize SV with high sequence accuracy, thus offering the opportunity to evaluate the prevalence of the molecular mechanisms underlying these variations and to characterize the features responsible for genome size variation. These seven maize lines together with B73 were cultivated under contrasted water conditions in the PHENOARCH phenotyping platform allowing precise characterization of growth and development together with precise measurements of environmental conditions. Thirteen different organs harvested at various developmental stages have been used for RNA-seq-based transcriptome analysis. This massive dataset will be used to evidence the possible role of SVs in quantitative responses to water deficit as well as the impact of SVs in gene regulation networks. Overall, this work will provide insights on the molecular origins and functional consequences of SV

Current and future trends in marine image annotation software

Nuno Gomes-Pereira J, Auger V, Beisiegel K, et al. Current and future trends in marine image annotation software. Progress in Oceanography. 2016;149:106-129.Abstract Given the need to describe, analyze and index large quantities of marine imagery data for exploration and monitoring activities, a range of specialized image annotation tools have been developed worldwide. Image annotation - the process of transposing objects or events represented in a video or still image to the semantic level, may involve human interactions and computer-assisted solutions. Marine image annotation software (MIAS) have enabled over 500 publications to date. We review the functioning, application trends and developments, by comparing general and advanced features of 23 different tools utilized in underwater image analysis. \{MIAS\} requiring human input are basically a graphical user interface, with a video player or image browser that recognizes a specific time code or image code, allowing to log events in a time-stamped (and/or geo-referenced) manner. \{MIAS\} differ from similar software by the capability of integrating data associated to video collection, the most simple being the position coordinates of the video recording platform. \{MIAS\} have three main characteristics: annotating events in real time, in posteriorly to annotation and interact with a database. These range from simple annotation interfaces, to full onboard data management systems, with a variety of toolboxes. Advanced packages allow to input and display of data from multiple sensors or multiple annotators via intranet or internet. Posterior human-mediated annotation often include tools for data display and image analysis, e.g. length, area, image segmentation, point count; and in a few cases the possibility of browsing and editing previous dive logs or to analyze annotation data. The interaction with a database allows the automatic integration of annotations from different surveys, repeated annotation and collaborative annotation of shared datasets, browsing and querying of data. Progress in the field of automated annotation is mostly in post processing, for stable platforms or still images. Integration into available \{MIAS\} is currently limited to semi-automated processes of pixel recognition through computer-vision modules that compile expert-based knowledge. Important topics aiding the choice of a specific software are outlined, the ideal software is discussed and future trends are presented

New susceptibility locus for rheumatoid arthritis suggested by a genome-wide linkage study

Rheumatoid arthritis (RA), the most common autoimmune disease, is associated in families with other autoimmune diseases, including insulin-dependent diabetes mellitus (IDDM). Its genetic component has been suggested by familial aggregation (λs = 5), twin studies, and segregation analysis. HLA, which is the only susceptibility locus known, has been estimated to account for one-third of this component. The aim of this paper was to identify new RA loci. A genome scan was performed with 114 European Caucasian RA sib pairs from 97 nuclear families. Linkage was significant only for HLA (P < 2.5⋅10(−5)) and nominal for 19 markers in 14 other regions (P < 0.05). Four of the loci implicated in IDDM potentially overlap with these regions: the putative IDDM6, IDDM9, IDDM13, and DXS998 loci. The first two of these candidate regions, defined in the RA genome scan by the markers D18S68-D18S61-D18S469 (18q22–23) and D3S1267 (3q13), respectively, were studied in 194 additional RA sib pairs from 164 nuclear families. Support for linkage to chromosome 3 only was extended significantly (P = 0.002). The analysis of all 261 families provided a linkage evidence of P = 0.001 and suggested an interaction between this putative RA locus and HLA. This locus could account for 16% of the genetic component of RA. Candidate genes include those coding for CD80 and CD86, molecules involved in antigen-specific T cell recognition. In conclusion, this first genome scan in RA Caucasian families revealed 14 candidate regions, one of which was supported further by the study of a second set of families

New perspectives in studying active faults in metropolitan France: the “Active faults France” (FACT/ATS) research axis from the Resif-Epos consortium

International audienceMainland France is part of a plate interior with a strong structural heritage, undergoing a low rate of deformation, where destructive earthquakes can nevertheless occur. In this paper, we emphasize that the knowledge of active faults is still largely fragmentary, and that significant efforts are needed to generate robust data, in particular on the numerous faults, that still lack any study. This is the aim of the “Failles ACTives France” (FACT) axis launched in the framework of the Transverse Seismicity Action (ATS) of the Resif-Epos consortium. We present some recent investigations carried out along suspected active faults in mountainous areas, their forelands and remote lowlands, which implement new approaches and new tools, and allow characterizing their Quaternary activity

The Listeria transcriptional landscape from saprophytism to virulence.

The bacterium Listeria monocytogenes is ubiquitous in the environment and can lead to severe food-borne infections. It has recently emerged as a multifaceted model in pathogenesis. However, how this bacterium switches from a saprophyte to a pathogen is largely unknown. Here, using tiling arrays and RNAs from wild-type and mutant bacteria grown in vitro, ex vivo and in vivo, we have analysed the transcription of its entire genome. We provide the complete Listeria operon map and have uncovered far more diverse types of RNAs than expected: in addition to 50 small RNAs (&lt;500 nucleotides), at least two of which are involved in virulence in mice, we have identified antisense RNAs covering several open-reading frames and long overlapping 5' and 3' untranslated regions. We discovered that riboswitches can act as terminators for upstream genes. When Listeria reaches the host intestinal lumen, an extensive transcriptional reshaping occurs with a SigB-mediated activation of virulence genes. In contrast, in the blood, PrfA controls transcription of virulence genes. Remarkably, several non-coding RNAs absent in the non-pathogenic species Listeria innocua exhibit the same expression patterns as the virulence genes. Together, our data unravel successive and coordinated global transcriptional changes during infection and point to previously unknown regulatory mechanisms in bacteria