Ozone loss derived from balloon-borne tracer measurements and the SLIMCAT CTM

Balloon-borne measurements of CFC-11 (on flights of the DIRAC in situ gas chromatograph and the DESCARTES grab sampler), ClO and O3 were made during the 1999/2000 winter as part of the SOLVE-THESEO 2000 campaign. Here we present the CFC-11 data from nine flights and compare them first with data from other instruments which flew during the campaign and then with the vertical distributions calculated by the SLIMCAT 3-D CTM. We calculate ozone loss inside the Arctic vortex between late January and early March using the relation between CFC-11 and O3 measured on the flights, the peak ozone loss (1200 ppbv) occurs in the 440–470 K region in early March in reasonable agreement with other published empirical estimates. There is also a good agreement between ozone losses derived from three independent balloon tracer data sets used here. The magnitude and vertical distribution of the loss derived from the measurements is in good agreement with the loss calculated from SLIMCAT over Kiruna for the same days

Genomic Species Are Ecological Species as Revealed by Comparative Genomics in Agrobacterium tumefaciens

The definition of bacterial species is based on genomic similarities, giving rise to the operational concept of genomic species, but the reasons of the occurrence of differentiated genomic species remain largely unknown. We used the Agrobacterium tumefaciens species complex and particularly the genomic species presently called genomovar G8, which includes the sequenced strain C58, to test the hypothesis of genomic species having specific ecological adaptations possibly involved in the speciation process. We analyzed the gene repertoire specific to G8 to identify potential adaptive genes. By hybridizing 25 strains of A. tumefaciens on DNA microarrays spanning the C58 genome, we highlighted the presence and absence of genes homologous to C58 in the taxon. We found 196 genes specific to genomovar G8 that were mostly clustered into seven genomic islands on the C58 genome—one on the circular chromosome and six on the linear chromosome—suggesting higher plasticity and a major adaptive role of the latter. Clusters encoded putative functional units, four of which had been verified experimentally. The combination of G8-specific functions defines a hypothetical species primary niche for G8 related to commensal interaction with a host plant. This supports that the G8 ancestor was able to exploit a new ecological niche, maybe initiating ecological isolation and thus speciation. Searching genomic data for synapomorphic traits is a powerful way to describe bacterial species. This procedure allowed us to find such phenotypic traits specific to genomovar G8 and thus propose a Latin binomial, Agrobacterium fabrum, for this bona fide genomic species

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Introduction aux principes de la loi relative à l’action en réparation collective et premiers commentaires critiques

0info:eu-repo/semantics/publishe

Des vertus de lapprentissage

International audienc