Complex population structure and haplotype patterns in the Western European honey bee from sequencing a large panel of haploid drones:Sequencing haploid honey bee drones

International audienceHoney bee subspecies originate from specific geographical areas in Africa, Europe and the Middle East, and beekeepers interested in specific phenotypes have imported genetic material to regions outside of the bees' original range for use either in pure lines or controlled crosses. Moreover, imported drones are present in the environment and mate naturally with queens from the local subspecies. The resulting admixture complicates population genetics analyses, and population stratification can be a major problem for association studies. To better understand Western European honey bee populations, we produced a whole genome sequence and single nucleotide polymorphism (SNP) genotype data set from 870 haploid drones and demonstrate its utility for the identification of nine genetic backgrounds and various degrees of admixture in a subset of 629 samples. Five backgrounds identified correspond to subspecies, two to isolated populations on islands and two to managed populations. We also highlight several large haplotype blocks, some of which coincide with the position of centromeres. The largest is 3.6 Mb long and represents 21% of chromosome 11, with two major haplotypes corresponding to the two dominant genetic backgrounds identified. This large naturally phased data set is available as a single vcf file that can now serve as a reference for subsequent populations genomics studies in the honey bee, such as (i) selecting individuals of verified homogeneous genetic backgrounds as references, (ii) imputing genotypes from a lower-density data set generated by an SNP-chip or by low-pass sequencing, or (iii) selecting SNPs compatible with the requirements of genotyping chips

Complex population structure and haplotype patterns in the Western European honey bee from sequencing a large panel of haploid drones

Honey bee subspecies originate from specific geographical areas in Africa, Europe and the Middle East, and beekeepers interested in specific phenotypes have imported genetic material to regions outside of the bees' original range for use either in pure lines or controlled crosses. Moreover, imported drones are present in the environment and mate naturally with queens from the local subspecies. The resulting admixture complicates population genetics analyses, and population stratification can be a major problem for association studies. To better understand Western European honey bee populations, we produced a whole genome sequence and single nucleotide polymorphism (SNP) genotype data set from 870 haploid drones and demonstrate its utility for the identification of nine genetic backgrounds and various degrees of admixture in a subset of 629 samples. Five backgrounds identified correspond to subspecies, two to isolated populations on islands and two to managed populations. We also highlight several large haplotype blocks, some of which coincide with the position of centromeres. The largest is 3.6 Mb long and represents 21% of chromosome 11, with two major haplotypes corresponding to the two dominant genetic backgrounds identified. This large naturally phased data set is available as a single vcf file that can now serve as a reference for subsequent populations genomics studies in the honey bee, such as (i) selecting individuals of verified homogeneous genetic backgrounds as references, (ii) imputing genotypes from a lower-density data set generated by an SNP-chip or by low-pass sequencing, or (iii) selecting SNPs compatible with the requirements of genotyping chips.This work was performed in collaboration with the GeT platform, Toulouse (France), a partner of the National Infrastructure France Génomique, thanks to support by the Commissariat aux Grands Invetissements (ANR-10-INBS-0009). Bioinformatics analyses were performed on the GenoToul Bioinfo computer cluster. This work was funded by a grant from the INRA Département de Génétique Animale (INRA Animal Genetics division) and by the SeqApiPop programme, funded by the FranceAgriMer grant 14-21-AT. We thank John Kefuss for helpful discussions. We thank Andrew Abrahams for providing honey bee samples from Colonsay (Scotland), the Association Conservatoire de l'Abeille Noire Bretonne (ACANB) for samples from Ouessant (France), CETA de Savoie for sample from Savoie, ADAPI for samples from Porquerolles and all beekeepers and bee breeders who kindly participated in this study by providing samples from their colonies.info:eu-repo/semantics/publishedVersio

Multi-criteria optimisation of processes including environmental impacts : case of eco-extraction of antioxidant biomolecules from agri-food by-products

Pour répondre à l’enjeu actuel majeur d’amélioration de la performance environnementale des procédés, une méthodologie pour l’optimisation multicritère d’éco-procédés incluant les aspects de productivité, énergétiques et environnementaux a été proposée. Dans cette étude, elle a été appliquée au cas de la récupération de polyphénols antioxydants à partir d’un coproduit agroalimentaire. L’optimisation prend en compte les rendements en polyphénols totaux et l’activité antioxydante des extraits obtenus à partir de graines de betterave déclassées ainsi que la consommation d’énergie des équipements impliqués et les impacts environnementaux générés pendant le cycle de vie du procédé. Les procédés d’extraction assistée : par ultrasons (US), par micro-ondes (MO) et par l’association de ces deux technologies ont été étudiés. Pour chaque procédé un modèle global a été développé comme outil pour l’optimisation multicritère intégrant selon l’étude des paramètres opératoires parmi le temps, la composition du solvant, le ratio solvant/coproduit, la puissance des US, la puissance des MO et le volume du solvant. Le modèle a été obtenu en combinant des équations cinétiques avec les méthodes de plan d’expérience et d’analyse de cycle de vie. Cet outil permet de prédire les conditions optimales de fonctionnement de chaque procédé en respectant diverses contraintes spécifiques telles que la maximisation du rendement d’extraction et/ou la minimisation du temps d’extraction, de la consommation d’énergie et/ou des impacts environnementaux. Cette méthodologie pourrait facilement être adaptée pour l’optimisation multicritère d’autres procédés.To meet the current major challenge of improving the environmental performance of processes, a methodology for the multi-criteria optimisation of green processes including productivity, energy and environmental aspects has been proposed. In this study, it was applied to the case of antioxidant polyphenols recovery from an agri-food by-product. The optimisation takes into account the total polyphenol yield and the antioxidant activity of extracts obtained from declassified beet seeds, as well as the energy consumption of the equipment involved and the environmental impacts generated during the process life cycle. Extraction processes assisted by ultrasound (US), microwave (MO) and a combination of these two technologies were studied. For each process, a global model was developed as a tool for multi-criteria optimisation, integrating parameters such as time, solvent composition, solvent/by-product ratio, US power, MO power and solvent volume, depending on the study. The model was obtained by combining kinetic equations to the methods of experimental design and life cycle assessment. This tool allows to predict the optimal operating conditions for each process while respecting specific constraints such as maximising extraction yield and/or minimising extraction time, energy consumption and/or environmental impacts. This methodology could easily be adapted for multicriteria optimisation of other processes

Multi-Criteria Optimization including Environmental Impacts of a Microwave-Assisted Extraction of Polyphenols and Comparison with an Ultrasound-Assisted Extraction Process

Valorization of wastes and by-products using environmentally friendly technologies with an optimal cost–benefit relationship is a current major issue in agri-food industries. An original tool was recently developed for multi-criteria optimization of an ultrasound-assisted extraction (UAE) process including the assessment of environmental impacts using Life Cycle Assessment. In the present work, this methodology was adapted and applied to another green extraction process, microwave-assisted extraction (MAE), with the same case study, valorization of antioxidant polyphenols from downgraded beet seeds. Once built, the obtained multi-criteria optimization tool was used to investigate performances of the MAE process regarding productivity criteria (polyphenol concentration and antioxidant activity of the extracts), energy consumption and environmental impacts as functions of operating parameters (time, solvent composition, microwave power density, and liquid–solid ratio). The MAE process was optimized under different constraints and compared to the UAE process. For the studied conditions and different investigated scenarios, MAE enabled obtaining extracts with higher polyphenol concentrations and antioxidant activity (approximately 33% and 23% enhancements, respectively), and to strongly reduce extraction duration (by a factor up to 6), whereas UAE enabled reducing the energy consumption (up to 3.6 fold) and the environmental impacts (up to 12% for climate change)

DNA metabarcoding and microscopic analyses of sea turtles biofilms: Complementary to understand turtle behavior.

Sea turtles are distributed in tropical and subtropical seas worldwide. They play several ecological roles and are considered important indicators of the health of marine ecosystems. Studying epibiotic diatoms living on turtle shells suggestively has great potential in the study of turtle behavior because diatoms are always there. However, diatom identification at the species level is time consuming, requires well-trained specialists, and there is a high probability of finding new taxa growing on turtle shells, which makes identification tricky. An alternative approach based on DNA barcoding and high throughput sequencing (HTS), metabarcoding, has been developed in recent years to identify species at the community level by using a DNA reference library. The suitabilities of morphological and molecular approaches were compared. Diatom assemblages were sampled from seven juvenile green turtles (Chelonia mydas) from Mayotte Island, France. The structures of the epibiotic diatom assemblages differed between both approaches. This resulted in different clustering of the turtles based on their diatom communities. Metabarcoding allowed better discrimination between turtles based on their epibiotic diatom assemblages and put into evidence the presence of a cryptic diatom diversity. Microscopy, for its part, provided more ecological information of sea turtles based on historical bibliographical data and the abundances of ecological guilds of the diatom species present in the samples. This study shows the complementary nature of these two methods for studying turtle behavior

Autour d’Elephant de Gus Van Sant

Elephant bénéficie d’une si grande légitimité critique que l’on pourrait se demander ce que l’on peut encore avoir à en dire. Précisément : « l’immunité » dont bénéficie cette Palme d’or au Festival de Cannes de 2003 s’est selon nous exercée au détriment d’une analyse en profondeur, et a contribué à minimiser tout ce qui excède le travail proprement dit du cinéaste. C’est pourquoi les auteurs s’attachent ici en particulier à la dimension socioculturelle et intermédiale du film: non seulement à l’objet filmique en tant que tel, mais à ce qui se passe « autour d’Elephant ». Remerciements à Martial Knaebe

Convergent Rewiring of the Virulence Regulatory Network Promotes Adaptation of Ralstonia solanacearum on Resistant Tomato

International audienceAbstract The evolutionary and adaptive potential of a pathogen is a key determinant for successful host colonization and proliferation but remains poorly known for most of the pathogens. Here, we used experimental evolution combined with phenotyping, genomics, and transcriptomics to estimate the adaptive potential of the bacterial plant pathogen Ralstonia solanacearum to overcome the quantitative resistance of the tomato cultivar Hawaii 7996. After serial passaging over 300 generations, we observed pathogen adaptation to within-plant environment of the resistant cultivar but no plant resistance breakdown. Genomic sequence analysis of the adapted clones revealed few genetic alterations, but we provide evidence that all but one were gain of function mutations. Transcriptomic analyses revealed that even if different adaptive events occurred in independently evolved clones, there is convergence toward a global rewiring of the virulence regulatory network as evidenced by largely overlapping gene expression profiles. A subset of four transcription regulators, including HrpB, the activator of the type 3 secretion system regulon and EfpR, a global regulator of virulence and metabolic functions, emerged as key nodes of this regulatory network that are frequently targeted to redirect the pathogen’s physiology and improve its fitness in adverse conditions. Significant transcriptomic variations were also detected in evolved clones showing no genomic polymorphism, suggesting that epigenetic modifications regulate expression of some of the virulence network components and play a major role in adaptation as well

Evidence for increased fitness of a plant pathogen conferred by epigenetic variation

Abstract Adaptation is usually explained by adaptive genetic mutations that are transmitted from parents to offspring and become fixed in the adapted population. However, more and more studies show that genetic mutation analysis alone is not sufficient to fully explain the processes of adaptive evolution and report the existence of non-genetic (or epigenetic) inheritance and its significant role in the generation of adapted phenotypes. In the present work, we tested the hypothesis of the role of DNA methylation, a form of epigenetic modification, in adaptation of the plant pathogen Ralstonia solanacearum to the host plant during an experimental evolution. Using SMRT-seq technology, we analyzed the methylomes of 31 experimentally evolved clones that were obtained after serial passages on a given host plant during 300 generations, either on susceptible or tolerant hosts. Comparison with the methylome of the ancestral clone revealed between 12 and 21 differential methylated sites (DMSs) at the GTWWAC motif in the evolved clones. Gene expression analysis of the 39 genes targeted by these DMSs revealed limited correlation between differential methylation and differential gene expression. Only one gene showed a correlation, the RSp0338 gene encoding the EpsR regulator protein. The MSRE-qPCR (Methylation Sensitive Restriction Enzyme - qPCR) technology was used as an alternative approach to assess the methylation state of the DMSs found by SMRT-seq between the ancestral and evolved clones. This approach also found the two DMSs upstream of RSp0338. Using site-directed mutagenesis, we demonstrated the contribution of these two DMSs in host adaptation. As these DMSs appeared very quickly in the experimental evolution, we hypothesize that such fast epigenetic changes can allow rapid adaptation to the plant stem environment. To our knowledge, this is the first study showing a link between epigenetic variation and evolutionary adaptation to new environment