10 research outputs found

    Industrialisation des procédures d'analyses de données de séquençage pan-génomiques constitutionnelles

    No full text
    The number of rare diseases is assessed between 5000 and 8000 distinct pathologies. Individually, these diseases are rare, but together they represent a major health problem at the population level. Because of the limited number of patients with certain diseases and the lack of knowledge about them, diagnosis for patients is often delayed.More than 80 % of rare diseases have a genetic origin, the vast majority of which are monogenic. The democratization of high-throughput sequencing technologies since 2005 has allowed the massive acquisition of genomic data from both healthy individuals and patients. However, establishing a diagnosis of a rare disease with current molecular biology technologies remains difficult.The industrial-scale application of exome and genome sequencing analyses associated with the constant increase in medical knowledge represents a concrete hope to bring a diagnosis to the majority of patients concerned by a rare disease suspected to be genetic.This thesis was particularly interested in the implementation of processes for constitutional genome-wide sequencing data analysis following industrial standards and bioinformatics good practices. Then, in the detection of copy number variations from exome sequencing data, but under-explored by many laboratories.Finally, this thesis has allowed the development and the initiation of collaborations still active today. This has been concretized by a study on detection of small somatic variations in an in vitro model of cancer development linked to the cellular microenvironment, the detection of structural variations using the innovative Oxford Nanopore sequencing technology and the comparison of prioritization methodologies for genetic variations using clinical descriptions based on HPO terms.Le nombre de maladies rares est estimĂ© Ă  entre 5000 et 8000 pathologies distinctes. Elles sont individuellement rares puisque par dĂ©finition elles affectent moins de 1 individu sur 2000 dans la population gĂ©nĂ©rale, mais leur nombre les rend collectivement frĂ©quentes. En raison du nombre limitĂ© de patients atteints de certaines maladies et du manque de connaissances Ă  leur sujet, le diagnostic pour les patients est souvent retardĂ©.Plus de 80 % des maladies rares auraient une origine gĂ©nĂ©tique, en grande majoritĂ© monogĂ©nique. La dĂ©mocratisation des technologies de sĂ©quençage Ă  haut dĂ©bit depuis 2005 a permis l’acquisition massive de donnĂ©es gĂ©nomiques que ce soit d’individus sains ou de patients. Pourtant, Ă©tablir un diagnostic de maladie rare avec les technologies de biologie molĂ©culaire actuelle reste difficile.L’application Ă  Ă©chelle industrielle des analyses de sĂ©quençage d’exome et de gĂ©nome associĂ©e avec l’augmentation constante des connaissances mĂ©dicales reprĂ©sente un espoir concret pour apporter un diagnostic Ă  la majoritĂ© des patients concernĂ©s par une maladie rare suspecte d’ĂȘtre gĂ©nĂ©tique.Cette thĂšse s’est particuliĂšrement intĂ©ressĂ©e Ă  la mise en place de processus d’analyse de donnĂ©es de sĂ©quençage pangĂ©nomiques constitutionnelles selon les standards industriels et les bonnes pratiques en vigueur dans le domaine. Puis, Ă  la dĂ©tection de variations de nombre de copies Ă  partir de donnĂ©es de sĂ©quençage d’exomes, analyse souvent inexplorĂ©e par de nombreux laboratoires.Enfin, cette thĂšse aura permis le dĂ©veloppement et l’initiation de collaborations encore actives Ă  ce jour. Cela s’est concrĂ©tisĂ© par une Ă©tude ayant comme objet la dĂ©tection de variations la dĂ©tection somatique de petite taille dans un modĂšle in vitro de dĂ©veloppement de cancer liĂ© au microenvironnement cellulaire, la dĂ©tection de variations structurales Ă  l’aide de la technologie de sĂ©quençage novatrice Oxford Nanopore et la comparaison de mĂ©thodologies de priorisations de variations gĂ©nĂ©tiques Ă  l’aide de descriptions cliniques basĂ©es sur les termes HPO

    Industrialisation des procédures d'analyses de données de séquençage pan-génomiques constitutionnelles

    No full text
    The number of rare diseases is assessed between 5000 and 8000 distinct pathologies. Individually, these diseases are rare, but together they represent a major health problem at the population level. Because of the limited number of patients with certain diseases and the lack of knowledge about them, diagnosis for patients is often delayed.More than 80 % of rare diseases have a genetic origin, the vast majority of which are monogenic. The democratization of high-throughput sequencing technologies since 2005 has allowed the massive acquisition of genomic data from both healthy individuals and patients. However, establishing a diagnosis of a rare disease with current molecular biology technologies remains difficult.The industrial-scale application of exome and genome sequencing analyses associated with the constant increase in medical knowledge represents a concrete hope to bring a diagnosis to the majority of patients concerned by a rare disease suspected to be genetic.This thesis was particularly interested in the implementation of processes for constitutional genome-wide sequencing data analysis following industrial standards and bioinformatics good practices. Then, in the detection of copy number variations from exome sequencing data, but under-explored by many laboratories.Finally, this thesis has allowed the development and the initiation of collaborations still active today. This has been concretized by a study on detection of small somatic variations in an in vitro model of cancer development linked to the cellular microenvironment, the detection of structural variations using the innovative Oxford Nanopore sequencing technology and the comparison of prioritization methodologies for genetic variations using clinical descriptions based on HPO terms.Le nombre de maladies rares est estimĂ© Ă  entre 5000 et 8000 pathologies distinctes. Elles sont individuellement rares puisque par dĂ©finition elles affectent moins de 1 individu sur 2000 dans la population gĂ©nĂ©rale, mais leur nombre les rend collectivement frĂ©quentes. En raison du nombre limitĂ© de patients atteints de certaines maladies et du manque de connaissances Ă  leur sujet, le diagnostic pour les patients est souvent retardĂ©.Plus de 80 % des maladies rares auraient une origine gĂ©nĂ©tique, en grande majoritĂ© monogĂ©nique. La dĂ©mocratisation des technologies de sĂ©quençage Ă  haut dĂ©bit depuis 2005 a permis l’acquisition massive de donnĂ©es gĂ©nomiques que ce soit d’individus sains ou de patients. Pourtant, Ă©tablir un diagnostic de maladie rare avec les technologies de biologie molĂ©culaire actuelle reste difficile.L’application Ă  Ă©chelle industrielle des analyses de sĂ©quençage d’exome et de gĂ©nome associĂ©e avec l’augmentation constante des connaissances mĂ©dicales reprĂ©sente un espoir concret pour apporter un diagnostic Ă  la majoritĂ© des patients concernĂ©s par une maladie rare suspecte d’ĂȘtre gĂ©nĂ©tique.Cette thĂšse s’est particuliĂšrement intĂ©ressĂ©e Ă  la mise en place de processus d’analyse de donnĂ©es de sĂ©quençage pangĂ©nomiques constitutionnelles selon les standards industriels et les bonnes pratiques en vigueur dans le domaine. Puis, Ă  la dĂ©tection de variations de nombre de copies Ă  partir de donnĂ©es de sĂ©quençage d’exomes, analyse souvent inexplorĂ©e par de nombreux laboratoires.Enfin, cette thĂšse aura permis le dĂ©veloppement et l’initiation de collaborations encore actives Ă  ce jour. Cela s’est concrĂ©tisĂ© par une Ă©tude ayant comme objet la dĂ©tection de variations la dĂ©tection somatique de petite taille dans un modĂšle in vitro de dĂ©veloppement de cancer liĂ© au microenvironnement cellulaire, la dĂ©tection de variations structurales Ă  l’aide de la technologie de sĂ©quençage novatrice Oxford Nanopore et la comparaison de mĂ©thodologies de priorisations de variations gĂ©nĂ©tiques Ă  l’aide de descriptions cliniques basĂ©es sur les termes HPO

    Industrialization of constitutional pan-genomic sequencing data analysis procedures

    No full text
    Le nombre de maladies rares est estimĂ© Ă  entre 5000 et 8000 pathologies distinctes. Elles sont individuellement rares puisque par dĂ©finition elles affectent moins de 1 individu sur 2000 dans la population gĂ©nĂ©rale, mais leur nombre les rend collectivement frĂ©quentes. En raison du nombre limitĂ© de patients atteints de certaines maladies et du manque de connaissances Ă  leur sujet, le diagnostic pour les patients est souvent retardĂ©.Plus de 80 % des maladies rares auraient une origine gĂ©nĂ©tique, en grande majoritĂ© monogĂ©nique. La dĂ©mocratisation des technologies de sĂ©quençage Ă  haut dĂ©bit depuis 2005 a permis l’acquisition massive de donnĂ©es gĂ©nomiques que ce soit d’individus sains ou de patients. Pourtant, Ă©tablir un diagnostic de maladie rare avec les technologies de biologie molĂ©culaire actuelle reste difficile.L’application Ă  Ă©chelle industrielle des analyses de sĂ©quençage d’exome et de gĂ©nome associĂ©e avec l’augmentation constante des connaissances mĂ©dicales reprĂ©sente un espoir concret pour apporter un diagnostic Ă  la majoritĂ© des patients concernĂ©s par une maladie rare suspecte d’ĂȘtre gĂ©nĂ©tique.Cette thĂšse s’est particuliĂšrement intĂ©ressĂ©e Ă  la mise en place de processus d’analyse de donnĂ©es de sĂ©quençage pangĂ©nomiques constitutionnelles selon les standards industriels et les bonnes pratiques en vigueur dans le domaine. Puis, Ă  la dĂ©tection de variations de nombre de copies Ă  partir de donnĂ©es de sĂ©quençage d’exomes, analyse souvent inexplorĂ©e par de nombreux laboratoires.Enfin, cette thĂšse aura permis le dĂ©veloppement et l’initiation de collaborations encore actives Ă  ce jour. Cela s’est concrĂ©tisĂ© par une Ă©tude ayant comme objet la dĂ©tection de variations la dĂ©tection somatique de petite taille dans un modĂšle in vitro de dĂ©veloppement de cancer liĂ© au microenvironnement cellulaire, la dĂ©tection de variations structurales Ă  l’aide de la technologie de sĂ©quençage novatrice Oxford Nanopore et la comparaison de mĂ©thodologies de priorisations de variations gĂ©nĂ©tiques Ă  l’aide de descriptions cliniques basĂ©es sur les termes HPO.The number of rare diseases is assessed between 5000 and 8000 distinct pathologies. Individually, these diseases are rare, but together they represent a major health problem at the population level. Because of the limited number of patients with certain diseases and the lack of knowledge about them, diagnosis for patients is often delayed.More than 80 % of rare diseases have a genetic origin, the vast majority of which are monogenic. The democratization of high-throughput sequencing technologies since 2005 has allowed the massive acquisition of genomic data from both healthy individuals and patients. However, establishing a diagnosis of a rare disease with current molecular biology technologies remains difficult.The industrial-scale application of exome and genome sequencing analyses associated with the constant increase in medical knowledge represents a concrete hope to bring a diagnosis to the majority of patients concerned by a rare disease suspected to be genetic.This thesis was particularly interested in the implementation of processes for constitutional genome-wide sequencing data analysis following industrial standards and bioinformatics good practices. Then, in the detection of copy number variations from exome sequencing data, but under-explored by many laboratories.Finally, this thesis has allowed the development and the initiation of collaborations still active today. This has been concretized by a study on detection of small somatic variations in an in vitro model of cancer development linked to the cellular microenvironment, the detection of structural variations using the innovative Oxford Nanopore sequencing technology and the comparison of prioritization methodologies for genetic variations using clinical descriptions based on HPO terms

    Industrialisation des procédures d'analyses de données de séquençage pan-génomiques constitutionnelles

    No full text
    The number of rare diseases is assessed between 5000 and 8000 distinct pathologies. Individually, these diseases are rare, but together they represent a major health problem at the population level. Because of the limited number of patients with certain diseases and the lack of knowledge about them, diagnosis for patients is often delayed.More than 80 % of rare diseases have a genetic origin, the vast majority of which are monogenic. The democratization of high-throughput sequencing technologies since 2005 has allowed the massive acquisition of genomic data from both healthy individuals and patients. However, establishing a diagnosis of a rare disease with current molecular biology technologies remains difficult.The industrial-scale application of exome and genome sequencing analyses associated with the constant increase in medical knowledge represents a concrete hope to bring a diagnosis to the majority of patients concerned by a rare disease suspected to be genetic.This thesis was particularly interested in the implementation of processes for constitutional genome-wide sequencing data analysis following industrial standards and bioinformatics good practices. Then, in the detection of copy number variations from exome sequencing data, but under-explored by many laboratories.Finally, this thesis has allowed the development and the initiation of collaborations still active today. This has been concretized by a study on detection of small somatic variations in an in vitro model of cancer development linked to the cellular microenvironment, the detection of structural variations using the innovative Oxford Nanopore sequencing technology and the comparison of prioritization methodologies for genetic variations using clinical descriptions based on HPO terms.Le nombre de maladies rares est estimĂ© Ă  entre 5000 et 8000 pathologies distinctes. Elles sont individuellement rares puisque par dĂ©finition elles affectent moins de 1 individu sur 2000 dans la population gĂ©nĂ©rale, mais leur nombre les rend collectivement frĂ©quentes. En raison du nombre limitĂ© de patients atteints de certaines maladies et du manque de connaissances Ă  leur sujet, le diagnostic pour les patients est souvent retardĂ©.Plus de 80 % des maladies rares auraient une origine gĂ©nĂ©tique, en grande majoritĂ© monogĂ©nique. La dĂ©mocratisation des technologies de sĂ©quençage Ă  haut dĂ©bit depuis 2005 a permis l’acquisition massive de donnĂ©es gĂ©nomiques que ce soit d’individus sains ou de patients. Pourtant, Ă©tablir un diagnostic de maladie rare avec les technologies de biologie molĂ©culaire actuelle reste difficile.L’application Ă  Ă©chelle industrielle des analyses de sĂ©quençage d’exome et de gĂ©nome associĂ©e avec l’augmentation constante des connaissances mĂ©dicales reprĂ©sente un espoir concret pour apporter un diagnostic Ă  la majoritĂ© des patients concernĂ©s par une maladie rare suspecte d’ĂȘtre gĂ©nĂ©tique.Cette thĂšse s’est particuliĂšrement intĂ©ressĂ©e Ă  la mise en place de processus d’analyse de donnĂ©es de sĂ©quençage pangĂ©nomiques constitutionnelles selon les standards industriels et les bonnes pratiques en vigueur dans le domaine. Puis, Ă  la dĂ©tection de variations de nombre de copies Ă  partir de donnĂ©es de sĂ©quençage d’exomes, analyse souvent inexplorĂ©e par de nombreux laboratoires.Enfin, cette thĂšse aura permis le dĂ©veloppement et l’initiation de collaborations encore actives Ă  ce jour. Cela s’est concrĂ©tisĂ© par une Ă©tude ayant comme objet la dĂ©tection de variations la dĂ©tection somatique de petite taille dans un modĂšle in vitro de dĂ©veloppement de cancer liĂ© au microenvironnement cellulaire, la dĂ©tection de variations structurales Ă  l’aide de la technologie de sĂ©quençage novatrice Oxford Nanopore et la comparaison de mĂ©thodologies de priorisations de variations gĂ©nĂ©tiques Ă  l’aide de descriptions cliniques basĂ©es sur les termes HPO

    Adoption et adaptation

    No full text
    RĂ©alisĂ©s dans le cadre de la cinquiĂšme rencontre de l'École doctorale d'archĂ©ologie portant sur le thĂšme « Adoption et adaptation », les neufs articles de ce volume illustrent la pluralitĂ© et la complexitĂ© de ce sujet Ă  forte rĂ©sonnance actuelle. La culture matĂ©rielle du Moyen-Orient, de l'Europe occidentale et de la MĂ©soamĂ©rique, depuis le NĂ©olithique jusqu'au dĂ©but de l'Ă©poque moderne est ici au centre des observations, exprimant aussi bien les formes d'adaptation Ă  un environnement que les transmissions des formes et des fonctions dans l'espace et dans le temps

    Genome Alert!: A standardized procedure for genomic variant reinterpretation and automated gene–phenotype reassessment in clinical routine

    No full text
    International audiencePurpose: Retrospective interpretation of sequenced data in light of the current literature is a major concern of the field. Such reinterpretation is manual and both human resources and variable operating procedures are the main bottlenecks.Methods: Genome Alert! method automatically reports changes with potential clinical significance in variant classification between releases of the ClinVar database. Using ClinVar submissions across time, this method assigns validity category to gene-disease associations.Results: Between July 2017 and December 2019, the retrospective analysis of ClinVar submissions revealed a monthly median of 1247 changes in variant classification with potential clinical significance and 23 new gene-disease associations. Re-examination of 4929 targeted sequencing files highlighted 45 changes in variant classification, and of these classifications, 89% were expert validated, leading to 4 additional diagnoses. Genome Alert! gene-disease association catalog provided 75 high-confidence associations not available in the OMIM morbid list; of which, 20% became available in OMIM morbid list For more than 356 negative exome sequencing data that were reannotated for variants in these 75 genes, this elective approach led to a new diagnosis.Conclusion: Genome Alert! (https://genomealert.univ-grenoble-alpes.fr/) enables systematic and reproducible reinterpretation of acquired sequencing data in a clinical routine with limited human resource effect

    Extracellular vesicles from myelodysplastic mesenchymal stromal cells induce DNA damage and mutagenesis of hematopoietic stem cells through miRNA transfer

    No full text
    International audiencePhysiopathology of myelodysplastic syndrome (MDS) remains poorly understood and the role of the microenvironment is increasingly highlighted. Recent studies in mouse models demonstrate that abnormalities of mesenchymal stromal cells (MSC) contribute to the physiopathology of MDS. In particular, genetic deletion of dicer1, a gene encoding a type III RNase essential for the genesis of miRNA, in murine MSC-derived osteoprogenitors led to a pathological microenvironment generating myelodysplastic features in hematopoietic progenitors and ultimately leading to acute myeloid leukemia [1]. In human, there is an increased susceptibility to senescence of the MDS mesenchymal stem cells and defects in the support properties of the growth of hematopoietic stem cells (HSC) [2]. These observations establish a causal relationship between deregulation of the hematopoietic niche and MDS pathogenesis. However, so far only few studies have addressed the mechanisms by microenvironmental MSC and HSC exchange signals that may interfere with miRNA processing, specifically in the human MDS microenvironment

    Extracellular vesicles from myelodysplastic mesenchymal stromal cells induce DNA damage and mutagenesis of hematopoietic stem cells through miRNA transfer

    No full text
    International audiencePhysiopathology of myelodysplastic syndrome (MDS) remains poorly understood and the role of the microenvironment is increasingly highlighted. Recent studies in mouse models demonstrate that abnormalities of mesenchymal stromal cells (MSC) contribute to the physiopathology of MDS. In particular, genetic deletion of dicer1, a gene encoding a type III RNase essential for the genesis of miRNA, in murine MSC-derived osteoprogenitors led to a pathological microenvironment generating myelodysplastic features in hematopoietic progenitors and ultimately leading to acute myeloid leukemia [1]. In human, there is an increased susceptibility to senescence of the MDS mesenchymal stem cells and defects in the support properties of the growth of hematopoietic stem cells (HSC) [2]. These observations establish a causal relationship between deregulation of the hematopoietic niche and MDS pathogenesis. However, so far only few studies have addressed the mechanisms by microenvironmental MSC and HSC exchange signals that may interfere with miRNA processing, specifically in the human MDS microenvironment

    Extracellular vesicles from myelodysplastic mesenchymal stromal cells induce DNA damage and mutagenesis of hematopoietic stem cells through miRNA transfer

    No full text
    International audiencePhysiopathology of myelodysplastic syndrome (MDS) remains poorly understood and the role of the microenvironment is increasingly highlighted. Recent studies in mouse models demonstrate that abnormalities of mesenchymal stromal cells (MSC) contribute to the physiopathology of MDS. In particular, genetic deletion of dicer1, a gene encoding a type III RNase essential for the genesis of miRNA, in murine MSC-derived osteoprogenitors led to a pathological microenvironment generating myelodysplastic features in hematopoietic progenitors and ultimately leading to acute myeloid leukemia [1]. In human, there is an increased susceptibility to senescence of the MDS mesenchymal stem cells and defects in the support properties of the growth of hematopoietic stem cells (HSC) [2]. These observations establish a causal relationship between deregulation of the hematopoietic niche and MDS pathogenesis. However, so far only few studies have addressed the mechanisms by microenvironmental MSC and HSC exchange signals that may interfere with miRNA processing, specifically in the human MDS microenvironment

    Exome sequencing as a first-tier test for copy number variant detection: retrospective evaluation and prospective screening in 2418 cases

    No full text
    International audienceBackground Despite the availability of whole exome (WES) and genome sequencing (WGS), chromosomal microarray (CMA) remains the first-line diagnostic test in most rare disorders diagnostic workup, looking for copy number variations (CNVs), with a diagnostic yield of 10%–20%. The question of the equivalence of CMA and WES in CNV calling is an organisational and economic question, especially when ordering a WGS after a negative CMA and/or WES. Methods This study measures the equivalence between CMA and GATK4 exome sequencing depth of coverage method in detecting coding CNVs on a retrospective cohort of 615 unrelated individuals. A prospective detection of WES-CNV on a cohort of 2418 unrelated individuals, including the 615 individuals from the validation cohort, was performed. Results On the retrospective validation cohort, every CNV detectable by the method (ie, a CNV with at least one exon not in a dark zone) was accurately called (64/64 events). In the prospective cohort, 32 diagnoses were performed among the 2418 individuals with CNVs ranging from 704 bp to aneuploidy. An incidental finding was reported. The overall increase in diagnostic yield was of 1.7%, varying from 1.2% in individuals with multiple congenital anomalies to 1.9% in individuals with chronic kidney failure. Conclusion Combining single-nucleotide variant (SNV) and CNV detection increases the suitability of exome sequencing as a first-tier diagnostic test for suspected rare Mendelian disorders. Before considering the prescription of a WGS after a negative WES, a careful reanalysis with updated CNV calling and SNV annotation should be considered
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