Optimisation sous contrainte de fiabilité d une coque imparfaite

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Cost effective, experimentally robust differential-expression analysis for human/mammalian, pathogen and dual-species transcriptomics.

As sequencing read length has increased, researchers have quickly adopted longer reads for their experiments. Here, we examine 14 pathogen or host-pathogen differential gene expression data sets to assess whether using longer reads is warranted. A variety of data sets was used to assess what genomic attributes might affect the outcome of differential gene expression analysis including: gene density, operons, gene length, number of introns/exons and intron length. No genome attribute was found to influence the data in principal components analysis, hierarchical clustering with bootstrap support, or regression analyses of pairwise comparisons that were undertaken on the same reads, looking at all combinations of paired and unpaired reads trimmed to 36, 54, 72 and 101 bp. Read pairing had the greatest effect when there was little variation in the samples from different conditions or in their replicates (e.g. little differential gene expression). But overall, 54 and 72 bp reads were typically most similar. Given differences in costs and mapping percentages, we recommend 54 bp reads for organisms with no or few introns and 72 bp reads for all others. In a third of the data sets, read pairing had absolutely no effect, despite paired reads having twice as much data. Therefore, single-end reads seem robust for differential-expression analyses, but in eukaryotes paired-end reads are likely desired to analyse splice variants and should be preferred for data sets that are acquired with the intent to be community resources that might be used in secondary data analyses

Conditioned variation in heart rate during static breath-holds in the bottlenose dolphin (Tursiops truncatus)

Funding for this project was provided by the Office of Naval Research to AF (ONR Award # N00014-16-1-3088).Previous reports suggested the existence of direct somatic motor control over heart rate (fH) responses during diving in some marine mammals, as the result of a cognitive and/or learning process rather than being a reflexive response. This would be beneficial for O2 storage management, but would also allow ventilation-perfusion matching for selective gas exchange, where O2 and CO2 can be exchanged with minimal exchange of N2. Such a mechanism explains how air breathing marine vertebrates avoid diving related gas bubble formation during repeated dives, and how stress could interrupt this mechanism and cause excessive N2 exchange. To investigate the conditioned response, we measured the fH-response before and during static breath-holds in three bottlenose dolphins (Tursiops truncatus) when shown a visual symbol to perform either a long (LONG) or short (SHORT) breath-hold, or during a spontaneous breath-hold without a symbol (NS). The average fH (ifHstart), and the rate of change in fH (difH/dt) during the first 20 s of the breath-hold differed between breath-hold types. In addition, the minimum instantaneous fH (ifHmin), and the average instantaneous fH during the last 10 s (ifHend) also differed between breath-hold types. The difH/dt was greater, and the ifHstart, ifHmin, and ifHend were lower during a LONG as compared with either a SHORT, or an NS breath-hold (P < 0.05). Even though the NS breath-hold dives were longer in duration as compared with SHORT breath-hold dives, the difH/dt was greater and the ifHstart, ifHmin, and ifHend were lower during the latter (P < 0.05). In addition, when the dolphin determined the breath-hold duration (NS), the fH was more variable within and between individuals and trials, suggesting a conditioned capacity to adjust the fH-response. These results suggest that dolphins have the capacity to selectively alter the fH-response during diving and provide evidence for significant cardiovascular plasticity in dolphins.Publisher PDFPeer reviewe

Micromechanics of root development in soil

International audienc

Control of the C. albicans Cell Wall Damage Response by Transcriptional Regulator Cas5

The fungal cell wall is vital for growth, development, and interaction of cells with their environment. The response to cell wall damage is well understood from studies in the budding yeast Saccharomyces cerevisiae, where numerous cell wall integrity (CWI) genes are activated by transcription factor ScRlm1. Prior evidence suggests the hypothesis that both response and regulation may be conserved in the major fungal pathogen Candida albicans. We have tested this hypothesis by using a new C. albicans genetic resource: we have screened mutants defective in putative transcription factor genes for sensitivity to the cell wall biosynthesis inhibitor caspofungin. We find that the zinc finger protein CaCas5, which lacks a unique ortholog in S. cerevisiae, governs expression of many CWI genes. CaRlm1 has a modest role in this response. The transcriptional coactivator CaAda2 is also required for expression of many CaCas5-dependent genes, as expected if CaCas5 recruits CaAda2 to activate target gene transcription. Many caspofungin-induced C. albicans genes specify endoplasmic reticulum and secretion functions. Such genes are not induced in S. cerevisiae, but promote its growth in caspofungin. We have used a new resource to identify a key C. albicans transcriptional regulator of CWI genes and antifungal sensitivity. Our gene expression findings indicate that both divergent and conserved response genes may have significant functional roles. Our strategy may be broadly useful for identification of pathogen-specific regulatory pathways and critical response genes

A Spitzer c2d Legacy Survey to Identify and Characterize Disks with Inner Dust Holes

Understanding how disks dissipate is essential to studies of planet formation. However, identifying exactly how dust and gas dissipates is complicated due to difficulty in finding objects clearly in the transition of losing their surrounding material. We use Spitzer IRS spectra to examine 35 photometrically-selected candidate cold disks (disks with large inner dust holes). The infrared spectra are supplemented with optical spectra to determine stellar and accretion properties and 1.3mm photometry to measure disk masses. Based on detailed SED modeling, we identify 15 new cold disks. The remaining 20 objects have IRS spectra that are consistent with disks without holes, disks that are observed close to edge-on, or stars with background emission. Based on these results, we determine reliable criteria for identifying disks with inner holes from Spitzer photometry and examine criteria already in the literature. Applying these criteria to the c2d surveyed star-forming regions gives a frequency of such objects of at least 4% and most likely of order 12% of the YSO population identified by Spitzer. We also examine the properties of these new cold disks in combination with cold disks from the literature. Hole sizes in this sample are generally smaller than for previously discovered disks and reflect a distribution in better agreement with exoplanet orbit radii. We find correlations between hole size and both disk and stellar masses. Silicate features, including crystalline features, are present in the overwhelming majority of the sample although 10 micron feature strength above the continuum declines for holes with radii larger than ~7 AU. In contrast, PAHs are only detected in 2 out of 15 sources. Only a quarter of the cold disk sample shows no signs of accretion, making it unlikely that photoevaporation is the dominant hole forming process in most cases.Comment: 24 pages, 18 figures and 8 tables. Fixed a typo in Table

Academic Well-Being and Structural Characteristics of Peer Networks in School

Peer networks at school and students’ position in these networks can influence their academic well-being. We study here individual students’ network position (isolation, popularity, social activity) and peer network structures at the school level (centralization, density, clustering, school connectedness) and their relations to students’ academic well-being (school burnout, SB; schoolwork engagement, SE). Classroom surveys for 14–16-year-olds (N = 11,015) were conducted in six European cities (SILNE survey). Students were asked to nominate up to five schoolmates with whom they preferred to do schoolwork. SB and SE correlated negatively (−0.32; p < 0.0001). Students had on average 3.4 incoming (popularity; range 0–5) and 3.4 outgoing (social activity; 0–5) social ties. Percentage of isolated students was 1.4. Students’ network position was associated weakly with academic well-being—popular students had less SB and higher SE, and socially active students had higher SE. School-level peer networks showed high clustering and school connectedness, but low density and low centralization. Clustering was associated with higher SB. Low centralization and high school connectedness protected from SB. Dense networks supported SE as did high average school connectedness. Correlations between these network indicators and academic well-being were, however, low. Our study showed that both students’ network position and network characteristics at the school level can influence adolescents’ academic well-being

Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads

Background: Comprehensive annotation and quantification of transcriptomes are outstanding problems in functional genomics. While high throughput mRNA sequencing (RNA-Seq) has emerged as a powerful tool for addressing these problems, its success is dependent upon the availability and quality of reference genome sequences, thus limiting the organisms to which it can be applied. Results: Here, we describe Rnnotator, an automated software pipeline that generates transcript models by de novo assembly of RNA-Seq data without the need for a reference genome. We have applied the Rnnotator assembly pipeline to two yeast transcriptomes and compared the results to the reference gene catalogs of these organisms. The contigs produced by Rnnotator are highly accurate (95percent) and reconstruct full-length genes for the majority of the existing gene models (54.3percent). Furthermore, our analyses revealed many novel transcribed regions that are absent from well annotated genomes, suggesting Rnnotator serves as a complementary approach to analysis based on a reference genome for comprehensive transcriptomics. Conclusions: These results demonstrate that the Rnnotator pipeline is able to reconstruct full-length transcripts in the absence of a complete reference genome