Perrault Aux Prises Avec la Fontaine: Imitation, Compétition et Correction Dans Les Fables de Faërne (1699)

Known especially for his fairy tales, Charles Perrault is also the author of the Fables de Faërne (1699). In this French translation of the Neo-Latin volume Fabulae Centum (1564), written by the Italian humanist Gabriel Faerno, Perrault had to position himself against his renowned predecessor Jean de La Fontaine, who had been dominating fable literature for decades. Perrault could either imitate his famous example, or evade it, due to anxiety of influence. To illustrate this inner struggle, we systematically compare both authors’ fables, concentrating our analysis on versification (metre and rhyme), vocabulary and apostrophe. In our comparison, we constantly verify whether any of the resemblances could be attributable to other French, versified fable books read by both Perrault and La Fontaine. Occasionally, this seems to be the case for the anonymous collection L’Esbatement moral des animaux (1578).Vakpublicati

An Expressed Sequence Tag collection from the male antennae of the Noctuid moth Spodoptera littoralis: a resource for olfactory and pheromone detection research

<p>Abstract</p> <p>Background</p> <p>Nocturnal insects such as moths are ideal models to study the molecular bases of olfaction that they use, among examples, for the detection of mating partners and host plants. Knowing how an odour generates a neuronal signal in insect antennae is crucial for understanding the physiological bases of olfaction, and also could lead to the identification of original targets for the development of olfactory-based control strategies against herbivorous moth pests. Here, we describe an Expressed Sequence Tag (EST) project to characterize the antennal transcriptome of the noctuid pest model, <it>Spodoptera littoralis</it>, and to identify candidate genes involved in odour/pheromone detection.</p> <p>Results</p> <p>By targeting cDNAs from male antennae, we biased gene discovery towards genes potentially involved in male olfaction, including pheromone reception. A total of 20760 ESTs were obtained from a normalized library and were assembled in 9033 unigenes. 6530 were annotated based on BLAST analyses and gene prediction software identified 6738 ORFs. The unigenes were compared to the <it>Bombyx mori </it>proteome and to ESTs derived from Lepidoptera transcriptome projects. We identified a large number of candidate genes involved in odour and pheromone detection and turnover, including 31 candidate chemosensory receptor genes, but also genes potentially involved in olfactory modulation.</p> <p>Conclusions</p> <p>Our project has generated a large collection of antennal transcripts from a Lepidoptera. The normalization process, allowing enrichment in low abundant genes, proved to be particularly relevant to identify chemosensory receptors in a species for which no genomic data are available. Our results also suggest that olfactory modulation can take place at the level of the antennae itself. These EST resources will be invaluable for exploring the mechanisms of olfaction and pheromone detection in <it>S. littoralis</it>, and for ultimately identifying original targets to fight against moth herbivorous pests.</p

Traitement informatique du signal électrique provenant de colorimètre à flux continu

National audienc

Traitement informatique du signal electrique provenant de colorimetre a flux continu

National audienc

Traitement informatique du signal électrique provenant de colorimètre à flux continu

National audienc

Combined linkage and linkage disequilibrium QTL mapping in multiple families of maize (Zea mays L.) line crosses highlights complementarities between models based on parental haplotype and single locus polymorphism

International audienceAdvancements in genotyping are rapidly decreasing marker costs and increasing marker density. This opens new possibilities for mapping quantitative trait loci (QTL), in particular by combining linkage disequilibrium information and linkage analysis (LDLA). In this study, we compared different approaches to detect QTL for four traits of agronomical importance in two large multi-parental datasets of maize (Zea mays L.) of 895 and 928 testcross progenies composed of 7 and 21 biparental families, respectively, and genotyped with 491 markers. We compared to traditional linkage-based methods two LDLA models relying on the dense genotyping of parental lines with 17,728 SNP: one based on a clustering approach of parental line segments into ancestral alleles and one based on single marker information. The two LDLA models generally identified more QTL (60 and 52 QTL in total) than classical linkage models (49 and 44 QTL in total). However, they performed inconsistently over datasets and traits suggesting that a compromise must be found between the reduction of allele number for increasing statistical power and the adequacy of the model to potentially complex allelic variation. For some QTL, the model exclusively based on linkage analysis, which assumed that each parental line carried a different QTL allele, was able to capture remaining variation not explained by LDLA models. These complementarities between models clearly suggest that the different QTL mapping approaches must be considered to capture the different levels of allelic variation at QTL involved in complex traits