11 results on '"Muret, k"'
Search Results
2. Serotyping of Toxoplasma gondii in pregnant women. Predominance of type II in the old world and type I and III in the new world
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Peyron, F, Lobry, J, Muret, k, Ferrandiz, J, Gomez-Marin, J.E., Petersen, Eskild, Meroni, V, Rausher, B, Picot, S, and Cesbron-Delauw, M.F.
- Published
- 2006
3. Comprehensive Catalog of Variants Potentially Associated with Hidradenitis Suppurativa, Including Newly Identified Variants from a Cohort of 100 Patients.
- Author
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Muret K, Le Goff V, Dandine-Roulland C, Hotz C, Jean-Louis F, Boisson B, Mesrob L, Sandron F, Daian D, Olaso R, Le Floch E, Meyer V, Wolkenstein P, Casanova JL, Lévy Y, Bonnet E, Deleuze JF, and Hüe S
- Subjects
- Humans, Male, Female, Cohort Studies, Receptors, Notch genetics, Mutation, Adult, Genetic Variation, Signal Transduction genetics, Middle Aged, Hidradenitis Suppurativa genetics, Exome Sequencing, Amyloid Precursor Protein Secretases genetics, Amyloid Precursor Protein Secretases metabolism, Genetic Predisposition to Disease
- Abstract
Hidradenitis suppurativa (HS) is a chronic skin disease characterized by painful, recurrent abscesses, nodules, and scarring, primarily in skin folds. The exact causes of HS are multifactorial, involving genetic, hormonal, and environmental factors. It is associated with systemic diseases such as metabolic syndrome and inflammatory bowel disease. Genetic studies have identified mutations in the γ-secretase complex that affect Notch signaling pathways critical for skin cell regulation. Despite its high heritability, most reported HS cases do not follow a simple genetic pattern. In this article, we performed whole-exome sequencing (WES) on a cohort of 100 individuals with HS, and we provide a comprehensive review of the variants known to be described or associated with HS. 91 variants were associated with the γ-secretase complex, and 78 variants were associated with other genes involved in the Notch pathway, keratinization, or immune response. Through this new genetic analysis, we have added ten new variants to the existing catalogs. All variants are available in a .vcf file and are provided as a resource for future studies.
- Published
- 2024
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4. DLK1/DIO3 locus upregulation by a β-catenin-dependent enhancer drives cell proliferation and liver tumorigenesis.
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Sanceau J, Poupel L, Joubel C, Lagoutte I, Caruso S, Pinto S, Desbois-Mouthon C, Godard C, Hamimi A, Montmory E, Dulary C, Chantalat S, Roehrig A, Muret K, Saint-Pierre B, Deleuze JF, Mouillet-Richard S, Forné T, Grosset CF, Zucman-Rossi J, Colnot S, and Gougelet A
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- Animals, Humans, Mice, beta Catenin genetics, beta Catenin metabolism, Calcium-Binding Proteins genetics, Calcium-Binding Proteins metabolism, Carcinogenesis genetics, Catenins genetics, Catenins metabolism, Cell Proliferation genetics, Membrane Proteins genetics, Membrane Proteins metabolism, Up-Regulation, Carcinoma, Hepatocellular genetics, Carcinoma, Hepatocellular metabolism, Liver Neoplasms genetics
- Abstract
The CTNNB1 gene, encoding β-catenin, is frequently mutated in hepatocellular carcinoma (HCC, ∼30%) and in hepatoblastoma (HB, >80%), in which DLK1/DIO3 locus induction is correlated with CTNNB1 mutations. Here, we aim to decipher how sustained β-catenin activation regulates DLK1/DIO3 locus expression and the role this locus plays in HB and HCC development in mouse models deleted for Apc (Apc
Δhep ) or Ctnnb1-exon 3 (β-cateninΔExon3 ) and in human CTNNB1-mutated hepatic cancer cells. We identified an enhancer site bound by TCF-4/β-catenin complexes in an open conformation upon sustained β-catenin activation (DLK1-Wnt responsive element [WRE]) and increasing DLK1/DIO3 locus transcription in β-catenin-mutated human HB and mouse models. DLK1-WRE editing by CRISPR-Cas9 approach impaired DLK1/DIO3 locus expression and slowed tumor growth in subcutaneous CTNNB1-mutated tumor cell grafts, ApcΔhep HB and β-cateninΔExon3 HCC. Tumor growth inhibition resulted either from increased FADD expression and subsequent caspase-3 cleavage in the first case or from decreased expression of cell cycle actors regulated by FoxM1 in the others. Therefore, the DLK1/DIO3 locus is an essential determinant of FoxM1-dependent cell proliferation during β-catenin-driven liver tumorigenesis. Targeting the DLK1-WRE enhancer to silence the DLK1/DIO3 locus might thus represent an interesting therapeutic strategy to restrict tumor growth in primary liver cancers with CTNNB1 mutations., Competing Interests: Declaration of interests Two patents, PCT/EP2023/053419 and EP22305162.4, have been deposited by J.S., L.P., S.C., and A.G., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)- Published
- 2024
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5. Fourth Report on Chicken Genes and Chromosomes 2022.
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Smith J, Alfieri JM, Anthony N, Arensburger P, Athrey GN, Balacco J, Balic A, Bardou P, Barela P, Bigot Y, Blackmon H, Borodin PM, Carroll R, Casono MC, Charles M, Cheng H, Chiodi M, Cigan L, Coghill LM, Crooijmans R, Das N, Davey S, Davidian A, Degalez F, Dekkers JM, Derks M, Diack AB, Djikeng A, Drechsler Y, Dyomin A, Fedrigo O, Fiddaman SR, Formenti G, Frantz LAF, Fulton JE, Gaginskaya E, Galkina S, Gallardo RA, Geibel J, Gheyas AA, Godinez CJP, Goodell A, Graves JAM, Griffin DK, Haase B, Han JL, Hanotte O, Henderson LJ, Hou ZC, Howe K, Huynh L, Ilatsia E, Jarvis ED, Johnson SM, Kaufman J, Kelly T, Kemp S, Kern C, Keroack JH, Klopp C, Lagarrigue S, Lamont SJ, Lange M, Lanke A, Larkin DM, Larson G, Layos JKN, Lebrasseur O, Malinovskaya LP, Martin RJ, Martin Cerezo ML, Mason AS, McCarthy FM, McGrew MJ, Mountcastle J, Muhonja CK, Muir W, Muret K, Murphy TD, Ng'ang'a I, Nishibori M, O'Connor RE, Ogugo M, Okimoto R, Ouko O, Patel HR, Perini F, Pigozzi MI, Potter KC, Price PD, Reimer C, Rice ES, Rocos N, Rogers TF, Saelao P, Schauer J, Schnabel RD, Schneider VA, Simianer H, Smith A, Stevens MP, Stiers K, Tiambo CK, Tixier-Boichard M, Torgasheva AA, Tracey A, Tregaskes CA, Vervelde L, Wang Y, Warren WC, Waters PD, Webb D, Weigend S, Wolc A, Wright AE, Wright D, Wu Z, Yamagata M, Yang C, Yin ZT, Young MC, Zhang G, Zhao B, and Zhou H
- Published
- 2022
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6. Watch Out for a Second SNP: Focus on Multi-Nucleotide Variants in Coding Regions and Rescued Stop-Gained.
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Degalez F, Jehl F, Muret K, Bernard M, Lecerf F, Lagoutte L, Désert C, Pitel F, Klopp C, and Lagarrigue S
- Abstract
Most single-nucleotide polymorphisms (SNPs) are located in non-coding regions, but the fraction usually studied is harbored in protein-coding regions because potential impacts on proteins are relatively easy to predict by popular tools such as the Variant Effect Predictor. These tools annotate variants independently without considering the potential effect of grouped or haplotypic variations, often called "multi-nucleotide variants" (MNVs). Here, we used a large RNA-seq dataset to survey MNVs, comprising 382 chicken samples originating from 11 populations analyzed in the companion paper in which 9.5M SNPs- including 3.3M SNPs with reliable genotypes-were detected. We focused our study on in-codon MNVs and evaluate their potential mis-annotation. Using GATK HaplotypeCaller read-based phasing results, we identified 2,965 MNVs observed in at least five individuals located in 1,792 genes. We found 41.1% of them showing a novel impact when compared to the effect of their constituent SNPs analyzed separately. The biggest impact variation flux concerns the originally annotated stop-gained consequences, for which around 95% were rescued; this flux is followed by the missense consequences for which 37% were reannotated with a different amino acid. We then present in more depth the rescued stop-gained MNVs and give an illustration in the SLC27A4 gene. As previously shown in human datasets, our results in chicken demonstrate the value of haplotype-aware variant annotation, and the interest to consider MNVs in the coding region, particularly when searching for severe functional consequence such as stop-gained variants., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Degalez, Jehl, Muret, Bernard, Lecerf, Lagoutte, Désert, Pitel, Klopp and Lagarrigue.)
- Published
- 2021
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7. Author Correction: An integrative atlas of chicken long non-coding genes and their annotations across 25 tissues.
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Jehl F, Muret K, Bernard M, Boutin M, Lagoutte L, Désert C, Dehais P, Esquerré D, Acloque H, Giuffra E, Djebali S, Foissac S, Derrien T, Pitel F, Zerjal T, Klopp C, and Lagarrigue S
- Published
- 2021
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8. An integrative atlas of chicken long non-coding genes and their annotations across 25 tissues.
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Jehl F, Muret K, Bernard M, Boutin M, Lagoutte L, Désert C, Dehais P, Esquerré D, Acloque H, Giuffra E, Djebali S, Foissac S, Derrien T, Pitel F, Zerjal T, Klopp C, and Lagarrigue S
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- Animals, Atlases as Topic, Avian Proteins genetics, Gene Expression Profiling, Gene Expression Regulation, Gene Regulatory Networks, MicroRNAs genetics, Organ Specificity, Sequence Analysis, RNA, Tissue Distribution, Chickens genetics, Computational Biology methods, Molecular Sequence Annotation methods, RNA, Long Noncoding genetics
- Abstract
Long non-coding RNAs (LNC) regulate numerous biological processes. In contrast to human, the identification of LNC in farm species, like chicken, is still lacunar. We propose a catalogue of 52,075 chicken genes enriched in LNC ( http://www.fragencode.org/ ), built from the Ensembl reference extended using novel LNC modelled here from 364 RNA-seq and LNC from four public databases. The Ensembl reference grew from 4,643 to 30,084 LNC, of which 59% and 41% with expression ≥ 0.5 and ≥ 1 TPM respectively. Characterization of these LNC relatively to the closest protein coding genes (PCG) revealed that 79% of LNC are in intergenic regions, as in other species. Expression analysis across 25 tissues revealed an enrichment of co-expressed LNC:PCG pairs, suggesting co-regulation and/or co-function. As expected LNC were more tissue-specific than PCG (25% vs. 10%). Similarly to human, 16% of chicken LNC hosted one or more miRNA. We highlighted a new chicken LNC, hosting miR155, conserved in human, highly expressed in immune tissues like miR155, and correlated with immunity-related PCG in both species. Among LNC:PCG pairs tissue-specific in the same tissue, we revealed an enrichment of divergent pairs with the PCG coding transcription factors, as for example LHX5, HXD3 and TBX4, in both human and chicken.
- Published
- 2020
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9. Multi-species annotation of transcriptome and chromatin structure in domesticated animals.
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Foissac S, Djebali S, Munyard K, Vialaneix N, Rau A, Muret K, Esquerré D, Zytnicki M, Derrien T, Bardou P, Blanc F, Cabau C, Crisci E, Dhorne-Pollet S, Drouet F, Faraut T, Gonzalez I, Goubil A, Lacroix-Lamandé S, Laurent F, Marthey S, Marti-Marimon M, Momal-Leisenring R, Mompart F, Quéré P, Robelin D, Cristobal MS, Tosser-Klopp G, Vincent-Naulleau S, Fabre S, Pinard-Van der Laan MH, Klopp C, Tixier-Boichard M, Acloque H, Lagarrigue S, and Giuffra E
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- Animals, Cattle, Chickens, Goats, Phylogeny, Sus scrofa, Animals, Domestic genetics, Chromatin genetics, Molecular Sequence Annotation, Transcriptome
- Abstract
Background: Comparative genomics studies are central in identifying the coding and non-coding elements associated with complex traits, and the functional annotation of genomes is a critical step to decipher the genotype-to-phenotype relationships in livestock animals. As part of the Functional Annotation of Animal Genomes (FAANG) action, the FR-AgENCODE project aimed to create reference functional maps of domesticated animals by profiling the landscape of transcription (RNA-seq), chromatin accessibility (ATAC-seq) and conformation (Hi-C) in species representing ruminants (cattle, goat), monogastrics (pig) and birds (chicken), using three target samples related to metabolism (liver) and immunity (CD4+ and CD8+ T cells)., Results: RNA-seq assays considerably extended the available catalog of annotated transcripts and identified differentially expressed genes with unknown function, including new syntenic lncRNAs. ATAC-seq highlighted an enrichment for transcription factor binding sites in differentially accessible regions of the chromatin. Comparative analyses revealed a core set of conserved regulatory regions across species. Topologically associating domains (TADs) and epigenetic A/B compartments annotated from Hi-C data were consistent with RNA-seq and ATAC-seq data. Multi-species comparisons showed that conserved TAD boundaries had stronger insulation properties than species-specific ones and that the genomic distribution of orthologous genes in A/B compartments was significantly conserved across species., Conclusions: We report the first multi-species and multi-assay genome annotation results obtained by a FAANG project. Beyond the generation of reference annotations and the confirmation of previous findings on model animals, the integrative analysis of data from multiple assays and species sheds a new light on the multi-scale selective pressure shaping genome organization from birds to mammals. Overall, these results emphasize the value of FAANG for research on domesticated animals and reinforces the importance of future meta-analyses of the reference datasets being generated by this community on different species.
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- 2019
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10. Long noncoding RNAs in lipid metabolism: literature review and conservation analysis across species.
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Muret K, Désert C, Lagoutte L, Boutin M, Gondret F, Zerjal T, and Lagarrigue S
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- Animals, Chickens genetics, Humans, Mammals genetics, Mice, Phylogeny, Terminology as Topic, Lipid Metabolism genetics, RNA, Long Noncoding genetics, RNA, Long Noncoding metabolism
- Abstract
Background: Lipids are important for the cell and organism life since they are major components of membranes, energy reserves and are also signal molecules. The main organs for the energy synthesis and storage are the liver and adipose tissue, both in humans and in more distant species such as chicken. Long noncoding RNAs (lncRNAs) are known to be involved in many biological processes including lipid metabolism., Results: In this context, this paper provides the most exhaustive list of lncRNAs involved in lipid metabolism with 60 genes identified after an in-depth analysis of the bibliography, while all "review" type articles list a total of 27 genes. These 60 lncRNAs are mainly described in human or mice and only a few of them have a precise described mode-of-action. Because these genes are still named in a non-standard way making such a study tedious, we propose a standard name for this list according to the rules dictated by the HUGO consortium. Moreover, we identified about 10% of lncRNAs which are conserved between mammals and chicken and 2% between mammals and fishes. Finally, we demonstrated that two lncRNA were wrongly considered as lncRNAs in the literature since they are 3' extensions of the closest coding gene., Conclusions: Such a lncRNAs catalogue can participate to the understanding of the lipid metabolism regulators; it can be useful to better understand the genetic regulation of some human diseases (obesity, hepatic steatosis) or traits of economic interest in livestock species (meat quality, carcass composition). We have no doubt that this first set will be rapidly enriched in coming years.
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- 2019
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11. Long noncoding RNA repertoire in chicken liver and adipose tissue.
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Muret K, Klopp C, Wucher V, Esquerré D, Legeai F, Lecerf F, Désert C, Boutin M, Jehl F, Acloque H, Giuffra E, Djebali S, Foissac S, Derrien T, and Lagarrigue S
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- Animals, Chickens metabolism, Conserved Sequence, Evolution, Molecular, Gene Expression Profiling, Gene Expression Regulation, Genome, Genotype, Humans, Lipid Metabolism genetics, Open Reading Frames, Organ Specificity, Phenotype, Quantitative Trait Loci, RNA, Antisense, RNA, Long Noncoding chemistry, RNA, Messenger genetics, Adipose Tissue metabolism, Chickens genetics, Liver metabolism, RNA, Long Noncoding genetics, Transcriptome
- Abstract
Background: Improving functional annotation of the chicken genome is a key challenge in bridging the gap between genotype and phenotype. Among all transcribed regions, long noncoding RNAs (lncRNAs) are a major component of the transcriptome and its regulation, and whole-transcriptome sequencing (RNA-Seq) has greatly improved their identification and characterization. We performed an extensive profiling of the lncRNA transcriptome in the chicken liver and adipose tissue by RNA-Seq. We focused on these two tissues because of their importance in various economical traits for which energy storage and mobilization play key roles and also because of their high cell homogeneity. To predict lncRNAs, we used a recently developed tool called FEELnc, which also classifies them with respect to their distance and strand orientation to the closest protein-coding genes. Moreover, to confidently identify the genes/transcripts expressed in each tissue (a complex task for weakly expressed molecules such as lncRNAs), we probed a particularly large number of biological replicates (16 per tissue) compared to common multi-tissue studies with a larger set of tissues but less sampling., Results: We predicted 2193 lncRNA genes, among which 1670 were robustly expressed across replicates in the liver and/or adipose tissue and which were classified into 1493 intergenic and 177 intragenic lncRNAs located between and within protein-coding genes, respectively. We observed similar structural features between chickens and mammals, with strong synteny conservation but without sequence conservation. As previously reported, we confirm that lncRNAs have a lower and more tissue-specific expression than mRNAs. Finally, we showed that adjacent lncRNA-mRNA genes in divergent orientation have a higher co-expression level when separated by less than 1 kb compared to more distant divergent pairs. Among these, we highlighted for the first time a novel lncRNA candidate involved in lipid metabolism, lnc_DHCR24, which is highly correlated with the DHCR24 gene that encodes a key enzyme of cholesterol biosynthesis., Conclusions: We provide a comprehensive lncRNA repertoire in the chicken liver and adipose tissue, which shows interesting patterns of co-expression between mRNAs and lncRNAs. It contributes to improving the structural and functional annotation of the chicken genome and provides a basis for further studies on energy storage and mobilization traits in the chicken.
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- 2017
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