HAL ENVT (Ecole Nationale Vétérinaire de Toulouse)
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Stabilization of G-Quadruplexes Modulates the Expression of DNA Damage and Unfolded Protein Response Genes in Canine Lymphoma/Leukemia Cells
No full textInternational audienceG-quadruplexes have been identified as a promising anti-cancer target because of their ability to modulate the stability of mRNAs encoding oncogenes, tumor suppressor genes, and other potential therapeutic targets. Deregulation of DNA damage and Unfolded Protein Response pathways in cancer cells may create vulnerabilities that can be exploited therapeutically. Previous studies have shown variations in the relative expression of DDR and UPR components in canine lymphoma and leukemia cell lines CLBL-1, CLB70, and GL-1. In the present study, we report the presence of G-quadruplex structures in these canine cell lines. Downregulation of the expression of DDR and UPR components at the mRNA level was observed in the CLBL-1 and CLB70 cell lines after stabilization of G4 structures using the ligand PhenDC3. In contrast, in GL-1 cells, important components of the DDR pathway, such as PARP1, GADD45A, and PIK3CB were upregulated in response to PhenDC3 treatment. Downregulation of DDIT4 mRNA expression, which encodes an important UPR component, was detected in the CLBL-1 and GL-1 cell lines after PhenDC3 exposure. These results suggest that G4 structures can be used to manipulate the expression of potential targets to treat lymphoma in dogs. A substantial enrichment of DNA replication and pyrimidine metabolism pathways was found in the GL-1 cell line after G4 stabilization. This finding suggests that PhenDC3 may induce DNA replication stress in this cell line. Collectively, these results support the feasibility of employing canine cancer cells as a model system to investigate the role of G-quadruplex structures in cancer
Rethinking the role of animals in antimicrobial resistance
No full textInternational audienceNo abstract availabl
Improved CRISPR-base editor tools for genome edition in Mycoplasma bovis: Application to surface proteins
No full textInternational audienceAmong the minimal bacteria belonging to the genus Mycoplasma, several of them are recognized pathogens for a wide diversity of animals. Mycoplasma bovis is one of the most significant species infecting dairy and fattening cows, causing mastitis and pneumonia, respectively. Attempts to control the disease have led to mass culling and costs of hundreds of millions in treatments and compensation worldwide, emphasizing the need for improved vaccines. Within the RAMbo-V consortium (Rational Approach to a Mycoplasma bovis Vaccine), we believe that advances in genome engineering tools provide a unique opportunity to pave the way towards producing a vaccine strain of M. bovis expressing at its surface a specific set of conserved antigenic structures. Advances in CRISPR-based tools, such as SpyCas9 recognizing PAM variants and base editors, have allowed for an increase in potential uses. These technologies paired with an algorithm predicting the complete array of potential targets within a given CDS library of M. bovis has allowed for a more in-depth look at the possibilities of these technologies and the feasibility of gene knockouts. Here we report the use of multiple tools in M. bovis that led to the knockout of genes of interest such as the vsp (variable surface proteins) locus. VSPs are abundant and phase-variable components of the M. bovis membrane, which may participate in surface crowding and masking of stably expressed proteins, in addition to their putative biological functions. Targeting of the Xer1 tyrosine recombinase that permits spontaneous non-coordinate phase-variable expression results in the generation of phase-locked mutants. The development of genome engineering tools will permit targeting virulence factors and optimized antigenic presentation. Such tools will be useful to build a vaccine chassis that would allow presentation of selected epitopes at the cell surface, leading to an improved immune response
Prediction of hidden individual inbreeding depression loadin French dairy sheep
No full textInternational audienc
Analyse des déterminants à la massification de pratiques limitant le recours aux produits phytopharmaceutiques
No full textInternational audienceDepuis 2008, le plan Ecophyto visant à réduire de 50 % l'utilisation des produits phyto-pharmaceutiques (PPP) en 2018 n'a pas atteint ses objectifs initiaux.Néanmoins, plusieurs innovations ont été développées et adoptées dans les filières agricoles afin réduire l'utilisation des PPP. L’étude a été réalisée par une étudiante, Eugénie Roy, en interaction avec le Comité Scientifique et Technique Ecophyto pour identifier les leviers et les obstacles à la mise en œuvre et à la massification de ces innovations
Heritability and correlations for honey yield, handling ease, brood quantity, and traits related to resilience in a French honeybee population
No full textInternational audienceThere is growing interest in selective breeding of the honeybee, resulting in the emergence of new breeding projects, often with an emphasis on improving resilience traits, in particular toward brood diseases. Lately, feed autonomy is also gaining importance. Here, we use data from a small breeding nucleus in France to estimate genetic parameters for common bee breeding traits and a novel trait reflecting honey reserves in the brood chamber. Open-mated queens were produced each year from inseminated dams between 2019 and 2021, and ~330 colonies were phenotyped each following year at three periods during the entire beekeeping season. Genetic parameters were estimated using ReML with an animal model. Narrow-sense heritability estimates ranged from low (around 0.15) for calmness and total capped brood surface both measured in early summer, to moderate (0.30 to 0.40) for hygienic behavior in spring, honey yield, and phoretic V. destructor load in early summer. Honey reserves in the brood chamber showed an intermediate heritability throughout the season (around 0.25). Gentleness had a null heritability. Most correlations between phenotypes adjusted for environmental fixed effects were close to zero. Among exceptions, there were honey reserves in the brood chamber in early summer with honey yield (around −0.2) and with the total capped brood surface in early summer (around −0.3). These estimates, although uncertain due to the dataset size, suggest that selection for production and resilience will be effective, even though simultaneous selection for honey yield and feed reserves might be difficult due to a possible genetic antagonism between both traits
Using high-density SNP data to unravel the origin of the Franches-Montagnes horse breed
No full textInternational audienceAbstractBackgroundThe Franches-Montagnes (FM) is the last native horse breed of Switzerland, established at the end of the 19th century by cross-breeding local mares with Anglo-Norman stallions. We collected high-density SNP genotype data (Axiom™ 670 K Equine genotyping array) from 522 FM horses, including 44 old-type horses (OF), 514 European Warmblood horses (WB) from Sweden and Switzerland (including a stallion used for cross-breeding in 1990), 136 purebred Arabians (AR), 32 Shagya Arabians (SA), and 64 Thoroughbred (TB) horses, as introgressed WB stallions showed TB origin in their pedigrees. The aim of the study was to ascertain fine-scale population structures of the FM breed, including estimation of individual admixture levels and genomic inbreeding (FROH) by means of Runs of Homozygosity.ResultsTo assess fine-scale population structures within the FM breed, we applied a three-step approach, which combined admixture, genetic contribution, and FROH of individuals into a high-resolution network visualization. Based on this approach, we were able to demonstrate that population substructures, as detected by model-based clustering, can be either associated with a different genetic origin or with the progeny of most influential sires. Within the FM breed, admixed horses explained most of the genetic variance of the current breeding population, while OF horses only accounted for a small proportion of the variance. Furthermore, we illustrated that FM horses showed high TB admixture levels and we identified inconsistencies in the origin of FM horses descending from the Arabian stallion Doktryner. With the exception of WB, FM horses were less inbred compared to the other breeds. However, the relatively few but long ROH segments suggested diversity loss in both FM subpopulations. Genes located in FM- and OF-specific ROH islands had known functions involved in conformation and behaviour, two traits that are highly valued by breeders.ConclusionsThe FM remains the last native Swiss breed, clearly distinguishable from other historically introgressed breeds, but it suffered bottlenecks due to intensive selection of stallions, restrictive mating choices based on arbitrary definitions of pure breeding, and selection of rare coat colours. To preserve the genetic diversity of FM horses, future conservation managements strategies should involve a well-balanced selection of stallions (e.g., by integrating OF stallions in the FM breeding population) and avoid selection for rare coat colours
Implementation of genomic selection in French dairy sheep and goats and opportunities for sustainable animal breeding
No full textIn France, the implementation of genomic selection in dairy sheep and goats seemed less obvious than in dairy cattle, due to higher relative cost of genotyping, small reference populations and high genetic diversity. Our research work using "Single-Step GBLUP" approach has, however, yielded genomic reliability similar to those obtained in some dairy cattle breeds, as well as higher theoretical accuracies of genomic estimated breeding values (GEBV) for genotyped young male candidates. This work led selection schemes to switch to genomic selection in the late 2010s. Studies then focused on ways of increasing reliability of genomic evaluations. In sheep, the over-dispersion of GEBVs for young candidates can be reduced by taking into account missing pedigrees using the metafounders method. In goats, the genomic prediction quality can be improved by weighting SNPs (WSSGBLUP) to take account of major genes or QTLs, or by using sequence data. In order to assess the possibilities of building an international reference population, across-countries genomic correlations were estimated. These correlations make it possible to envisage collaborative projects between France and Spain for two sheep breeds, and France and Italy for goats. Genomic selection opens up the possibility of selecting new traits. Small ruminant farms are often located in areas with severe environmental constraints where they suffer the consequences of climate change. In this context, breeders are concerned about resilience and efficiency traits, key elements for sustainable animal breeding. Thus, a genomic evaluation of artificial insemination success of females has been developed for goats, and a genomic evaluation of rams for their resistance to gastro-intestinal parasites is now operational in three breeds of sheep. Finally, research work has been carried out in both species on functional longevity, feed efficiency, milk persistency and maturity, opening up new selection prospects.Part of this work has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 772787 (SMARTER).Key Words: genomic selection, dairy sheep, dairy goat
Benchmarking of sequencing technologies for CpG methylation detection: applications to quail and pig
No full textInternational audienceContext : Current technologies for detecting and analyzing epigenetic modifications are not yet as advanced or as cost-effective as those used for genetic analysis. This makes large-scale screening of epigenetic traits in breeding populations challenging and expensive. Advances in technology and a deeper understanding of epigenetic mechanisms will likely enhance the effectiveness and precision of epigenetic breeding in the future.Objectives : Provide research teams with a powerful and innovative method to study methylation marks in a large number of individuals within breeding programs.Questions : Is Whole Genome Bisulfite Sequencing (WGBS) still the gold standard for DNA methylation analysis ? Is Enzymatic Methyl-seq (EM-seq) a better reference to represent the short-read sequencing ? Technologies like Oxford Nanopore (ONT) and PacBio offer the advantage of long reads but are they powerful for detecting methylation
Exploring the metabolic effects of different genotoxic compounds from transcriptomics data: using gene selection to unravel significant effects
No full textInternational audienceAbstractToxic agents are a major risk for human/animal health and biosystems, particularly those that damage the genome called genotoxic substances. Understanding the modes of action of these genotoxic compounds, particularly at the level of metabolic pathways, is a current need in order to be able to characterize them. As part of the ANR GENOSHIFT project, a multi-omics study is carried out to identify transcriptomic and metabolic biomarkers of exposition following chronic exposure of human liver cells to 12 genotoxic compounds of reference, at low doses.Human liver cells (HepaRP line [1]) were treated with each genotoxic compound for five days. From the same cells, RNA was extracted for transcriptomic analysis (Agilent SurePrint G3 Human GE V3 8x60K microarray) on the one hand, and on the other hand the cell pellets were extracted for metabolomic analysis by Nuclear Magnetic Resonance (NMR 600 MHz). These analyses allowed to generate transcriptomic (64 samples and 31, 972 variables) and metabolomic (64 samples and 875 variables) data, respectively. To identify biomarkers of the genotoxic effects of these compounds, multivariate statistical analyzes were performed independently on each of these omics data.First, to identify genes and metabolites correlated and modulated by chronic exposure of cells to these genotoxic compounds, statistical integration is necessary. Omics data contains a large number of variables, some of which may be noisy, irrelevant or redundant. These redundant, irrelevant or noisy variables can reduce the overall accuracy of a prediction model or even lead to a non-significant model. The transcriptomic data block, compared to the metabolomic data block, contains a large number of genes which are not all “informative”. In addition, this large number of genes can give the transcriptomic data a greater weight than the metabolomic data during integration even if it does not report more information. To overcome these problems, a variable selection step on the transcriptomic data block was applied before statistical integration.Two selection methods were tested to reduce the dimension of transcriptomic data. Affinity Propagation Clustering (AP clustering) [2], an unsupervised clustering method, allows to remove redundancy between variables. The second method, RELIEFF [3], a supervised method, was combined with AP clustering [2], to select both discriminative and non-redundant variables. These methods were applied on the transcriptomics data obtained in cells exposed to Aflatoxin B1 (AFB1), for which there were 5473 differentially expressed genes, and to Cisplatin (CIS) for which there were no differentially expressed genes. RELIEFF combined with AP clustering enabled to select discriminant and non-redundant genes for these two compounds. With 57 genes for AFB1 and 34 genes for CIS, the groups (control and treatment) were separated. AP clustering also selected nonredundant genes (at least 16 genes for the compound AFB1 and 34 genes for CIS) and thus reduced the data dimension.These results show that the RELIEFF method combined with AP clustering is able to select discriminant and non-redundant genes, particularly for compounds for which there is a weak genotoxic effect (e.g., CIS). The unsupervised method (AP clustering) reduced the size of the data by selecting around a few thousand or even around twenty variables.References1. Brun C., Allain C., Ferron PJ., Younoussa H., Colicchio B., Jeandidier E., M’Kacher R., Guguen-Guillouzo C., Bertile F. Extended lifespan and improved genome stability in HepaRG-derived cell lines through reprogramming by high-density stress. Proc Natl Acad Sci. 2023 Sep 5;120(36):e2219298120.2. Frey B. J. and Dueck D. Clustering by passing messages between data points. Science 315, 972-976. DOI:doi:10.1126/science.1136800. 2007 Feb 16;315(5814):972–6.3. Kononenko I., Simes E. and Robnik-Sikonja M. Overcoming the Myopia of Induction Learning Algorithms withRELIEFF. Applied Intelligence, Vol.7, 1, 39-55. 1997