37 research outputs found

    Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals

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    peer-reviewedH.D.D., A.J.C., P.J.B. and B.J.H. would like to acknowledge the Dairy Futures Cooperative Research Centre for funding. H.P. and R.F. acknowledge funding from the German Federal Ministry of Education and Research (BMBF) within the AgroClustEr ‘Synbreed—Synergistic Plant and Animal Breeding’ (grant 0315527B). H.P., R.F., R.E. and K.-U.G. acknowledge the Arbeitsgemeinschaft SĂŒddeutscher RinderzĂŒchter, the Arbeitsgemeinschaft Österreichischer FleckviehzĂŒchter and ZuchtData EDV Dienstleistungen for providing genotype data. A. Bagnato acknowledges the European Union (EU) Collaborative Project LowInputBreeds (grant agreement 222623) for providing Brown Swiss genotypes. Braunvieh Schweiz is acknowledged for providing Brown Swiss phenotypes. H.P. and R.F. acknowledge the German Holstein Association (DHV) and the ConfederaciĂłn de Asociaciones de Frisona Española (CONCAFE) for sharing genotype data. H.P. was financially supported by a postdoctoral fellowship from the Deutsche Forschungsgemeinschaft (DFG) (grant PA 2789/1-1). D.B. and D.C.P. acknowledge funding from the Research Stimulus Fund (11/S/112) and Science Foundation Ireland (14/IA/2576). M.S. and F.S.S. acknowledge the Canadian Dairy Network (CDN) for providing the Holstein genotypes. P.S. acknowledges funding from the Genome Canada project entitled ‘Whole Genome Selection through Genome Wide Imputation in Beef Cattle’ and acknowledges WestGrid and Compute/Calcul Canada for providing computing resources. J.F.T. was supported by the National Institute of Food and Agriculture, US Department of Agriculture, under awards 2013-68004-20364 and 2015-67015-23183. A. Bagnato, F.P., M.D. and J.W. acknowledge EU Collaborative Project Quantomics (grant 516 agreement 222664) for providing Brown Swiss and Finnish Ayrshire sequences and genotypes. A.C.B. and R.F.V. acknowledge funding from the public–private partnership ‘Breed4Food’ (code BO-22.04-011- 001-ASG-LR) and EU FP7 IRSES SEQSEL (grant 317697). A.C.B. and R.F.V. acknowledge CRV (Arnhem, the Netherlands) for providing data on Dutch and New Zealand Holstein and Jersey bulls.Stature is affected by many polymorphisms of small effect in humans1. In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes2,3. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10−8) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP–seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals

    A review on clinical genetics in Bovidae

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    A review on clinical genetics in Bovidae . 22.International Colloquium on Animal Cytogenetics and Genomic

    Les anomalies gĂ©nĂ©tiques : dĂ©finition, origine, transmission et Ă©volution, mode d’action

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    Cet article rappelle les notions et principes relatifs aux anomalies gĂ©nĂ©tiques dont on observe rĂ©guliĂšrement des Ă©mergences dans les populations animales d’élevage. Ces anomalies proviennent de mutations naturelles et certaines d’entre elles voient leur frĂ©quence augmenter du fait principalement de la dĂ©rive gĂ©nĂ©tique, parfois de la sĂ©lection. Lorsqu’elles sont dominantes, elles sont gĂ©nĂ©ralement rapidement contre-sĂ©lectionnĂ©es et tendent Ă  disparaĂźtre. Mais lorsqu’elles sont rĂ©cessives, les cas observables ne reprĂ©sentent qu’une toute petite fraction des individus porteurs. On dĂ©finit gĂ©nĂ©ralement les anomalies gĂ©nĂ©tiques comme des syndromes monogĂ©niques. Toutefois, cette rĂšgle a beaucoup d’exceptions, soit parce que l’anomalie se rĂ©vĂšle plus complexe qu’initialement supposĂ©, soit parce que le syndrome prĂ©sente une variabilitĂ© phĂ©notypique due Ă  des gĂšnes modulateurs. Les anomalies rĂ©cessives sont principalement dues Ă  des mutations de type perte de fonction, tandis que les mutations dominantes rĂ©sultent souvent d’interactions entre gĂšnes ou entre protĂ©ines, ou de l’altĂ©ration d’un gĂšne rĂ©presseur. Les anomalies cytogĂ©nĂ©tiques conduisent Ă  des phĂ©notypes anormaux gĂ©nĂ©ralement diffĂ©rents entre types de caryotypes dĂ©sĂ©quilibrĂ©s. Enfin, les anomalies prĂ©sentent parfois des dĂ©terminismes particuliers, par exemple dans le cas de gĂšnes portĂ©s par les chromosomes sexuels ou soumis Ă  empreinte parentale.This article presents an overview of the concepts and principles relative to genetic abnormalities, for which outbreaks are regularly observed in farm animal populations. These genetic defects originate from natural mutations and the frequency of some of them increases under the effect of genetic drift and sometimes of selection. When they are dominant, they are rapidly counter-selected and tend to disappear. But when they are recessive, the affected cases represent only a very small fraction of carrier individuals. Genetic defects are usually monogenic. However, this rule has many exceptions, either because the abnormality is more complex than initially assumed, or because the phenotype presents a variability caused by modulator genes in addition to the major factor. The recessive defects are mainly caused by loss of function mutations, whereas the dominant mutations often result from interactions between genes or between proteins, or from the loss of function of a repressor gene. Chromosomal abnormalities, when they are not lethal, cause syndromes which may vary between the different types of unbalanced caryotypes. Finally, genetic defects sometimes present very peculiar mechanisms, e.g. when the mutated gene is located on a sex chromosome or when it is imprinted

    Dossier : Anomalies génétiques - Avant-propos

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    Dossier : Anomalies génétiques - Avant-propo

    Uncovering Adaptation from Sequence Data : Lessons from Genome Resequencing of Four Cattle Breeds

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    Detecting the molecular basis of adaptation is one of the major questions in population genetics. With the advance in sequencing technologies, nearly complete interrogation of genome-wide polymorphisms in multiple populations is becoming feasible in some species, with the expectation that it will extend quickly to new ones. Here, we investigate the advantages of sequencing for the detection of adaptive loci in multiple populations, exploiting a recently published data set in cattle (Bos taurus). We used two different approaches to detect statistically significant signals of positive selection: a within-population approach aimed at identifyinghard selective sweeps and a population-differentiation approach that can capture other selection events such as soft or incomplete sweeps. We show that the two methods are complementary in that they indeed capture different kinds of selection signatures. Our study confirmed some of the well-known adaptive loci in cattle (e.g., MC1R, KIT, GHR, PLAG1, NCAPG/LCORL) and detected some new ones (e.g., ARL15, PRLR, CYP19A1, PPM1L). Compared to genome scans based on medium- or high-density SNP data, we found that sequencing offered an increased detection power and a higher resolution in the localization of selection signatures. In several cases, we could even pinpoint the underlying causal adaptive mutation or at least a very small number of possible candidates (e.g.,MC1R, PLAG1). Our results on these candidates suggest that a vast majority of adaptive mutations are likely to be regulatory rather than protein-coding variants

    Rare phenotypes in domestic animals: unique resources for multiple applications

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    Preservation of specific and inheritable phenotypes of current or potential future importance is one of the main purposes of conservation of animal genetic resources. In this review, we investigate the issues behind the characterisation, utilisation and conservation of rare phenotypes, considering their multiple paths of relevance, variable levels of complexity and mode of inheritance. Accurately assessing the rarity of a given phenotype, especially a complex one, is not a simple task, because it requires the phenotypic and genetic characterisation of a large number of animals and populations and remains dependent of the scale of the study. Once characterised, specific phenotypes may contribute to various purposes (adaptedness, production, biological model, aesthetics, etc.) with adequate introgression programmes, which justifies the consideration of (real or potential) existence of such characteristics in in situ or ex situ conservation strategies. Recent biotechnological developments (genomic and genetic engineering) will undoubtedly bring important changes to the way phenotypes are characterised, introgressed and managed

    Du phénotype à la mutation causale : le cas des anomalies récessives bovines

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    Cet article prĂ©sente la mĂ©thodologie utilisĂ©e pour identifier la mutation responsable d’une anomalie gĂ©nĂ©tique Ă  partir de cas d’animaux affectĂ©s. Dans un premier temps, une collection de cas aussi homogĂšnes que possible est constituĂ©e, de la mĂȘme race et avec les mĂȘmes signes cliniques, complĂ©tĂ©e par une population tĂ©moin apparentĂ©e mais non atteinte. Une analyse de pedigree est possible pour rechercher l’ancĂȘtre commun qui a pu transmettre l’anomalie Ă  chacun des cas. Le gĂ©notypage par puce permet de mettre en Ă©vidence trĂšs rapidement une petite rĂ©gion du gĂ©nome homozygote et identique Ă  tous les marqueurs qui contient la mutation recherchĂ©e. La mutation est ensuite identifiĂ©e par sĂ©quençage du gĂ©nome de quelques cas, filtrage des variants observĂ©s sur la base d’une part, de leur prĂ©sence chez d’autres animaux, et d’autre part, de leur annotation fonctionnelle. Une validation statistique est ensuite pratiquĂ©e par gĂ©notypage Ă  grande Ă©chelle, pour vĂ©rifier l’association totale entre gĂ©notype et phĂ©notype. Enfin, la causalitĂ© de la mutation est Ă©tudiĂ©e par analyse fonctionnelle, incluant l’analyse des ARN et des protĂ©ines, l’imagerie cellulaire, voire la crĂ©ation de modĂšles transgĂ©niques.This article presents the methodology used to identify the mutation responsible for a genetic defect from the observation of cases. In the first step, a set of homogeneous cases are collected, from the same breed and with the same clinical signs. This collection is completed by a related but unaffected control population. A pedigree analysis is possible to point towards a common ancestor who may have transmitted the defect to all cases. A genotyping step using a SNP chip is used to display a small genomic region homozygous and identical at all markers and including the mutation. The mutation is then identified by genome sequencing of a few cases followed by the filtering of the variants against a large sequence database of unaffected animals. The best candidate variants are retained on the basis of their functional annotation. The mutation is then statistically confirmed on the basis of large scale genotyping, to verify the complete association between the mutation and the phenotype. Finally, the causality of the mutation is proven by functional analysis, including RNA and protein analysis, cellular imaging, and even through transgenic models carrying the mutation

    Anticiper l'émergence d'anomalies génétiques grùce aux données génomiques

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    Avec le rĂ©cent dĂ©veloppement des approches reposant sur le gĂ©notypage et sĂ©quençage Ă  haut dĂ©bit, identifier la mutation responsable d’une anomalie Ă  partir de quelques cas est beaucoup plus simple qu’auparavant. Toutefois, il n’est pas toujours possible d’observer des cas et de disposer du matĂ©riel biologique correspondant. Cet article prĂ©sente deux approches reposant sur l’analyse de donnĂ©es Ă  haut dĂ©bit, permettant d’identifier des mutations rĂ©cessives lĂ©tales ou d’orienter plus efficacement leur recherche Ă  partir des donnĂ©es de sĂ©quence du gĂ©nome. La premiĂšre approche utilise les donnĂ©es de gĂ©notypage Ă  haut dĂ©bit pour rechercher des rĂ©gions du gĂ©nome prĂ©sentant un dĂ©ficit en homozygotes. Cette mĂ©thode a dĂ©jĂ  permis de caractĂ©riser plusieurs mutations dans chacune des races bovines analysĂ©es. Dans la seconde approche, on recherche dans les donnĂ©es de sĂ©quence disponibles des variants dont l’annotation suggĂšre qu’ils ne sont pas tolĂ©rĂ©s Ă  l’état homozygote. Le nombre de faux positifs est Ă©levĂ©, mais ces donnĂ©es permettent d’orienter la phase d’observation et de diagnostic plus efficacement et, dans les cas les plus favorables, d’anticiper l’émergence de l’anomalie. Des exemples sont fournis avec le gĂšne RP1 responsable de dĂ©gĂ©nĂ©rescence rĂ©tinienne ou le gĂšne EDAR responsable de l’absence de poils et de dents.With the recent development of approaches using high throughput genotyping and sequencing, identifying the causal mutation underlying a genetic defect from several cases has become much simpler. However, cases, or their corresponding biological material, are not always available. This article presents two approaches relying on high throughput data analysis to identify recessive lethal mutations or to efficiently orient their research from genome sequence. The first approach uses genotyping data to look for genomic rĂ©gions presenting a deficit in homozygotes. This method has proven to be efficient with several mutations already characterized in each analyzed bovine breed. In the second approach, DNA variants are searched in the available whole genome sequences, with strong annotations suggesting that they are not tolerated in the homozygous state. The number of false positives is relatively high but these variants can orient the observation step toward mating at risk or homozygous animals and, in the most favorable cases, to anticipate the outbreak of the defect. Examples are provided with the RP1 gene responsible for retina degeneration or the EDAR gene responsible for the ectodermal anhidrotic syndrome

    Prise en compte des anomalies génétiques en sélection : le cas des bovins

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    Pendant plusieurs dizaines d’annĂ©es aprĂšs la mise en place des programmes de sĂ©lection gĂ©nĂ©tique, la dĂ©couverte de nouvelles anomalies est restĂ©e sporadique. Cela a incitĂ© jusqu’à prĂ©sent les gestionnaires de ces programmes Ă  appliquer une politique d’éradication drastique des reproducteurs porteurs, combinĂ©e Ă  la procrĂ©ation de futurs reproducteurs non porteurs. Mais la situation est en train de changer avec l’avĂšnement de la sĂ©lection gĂ©nomique et des technologies associĂ©es, qui permettent de dĂ©tecter les anomalies plus rapidement et donc en plus grand nombre. Il est donc indispensable de faire Ă©voluer la façon de les prendre en compte dans les programmes de sĂ©lection. Un Ă©tat de la situation dans la population doit d’abord ĂȘtre Ă©tabli en estimant la frĂ©quence allĂ©lique de l’anomalie et en caractĂ©risant le statut des reproducteurs les plus importants avec les tests molĂ©culaires disponibles, en particulier avec les puces Ă  « Single Nucleotide Polymorphism » (SNP). Dans certains cas, une prĂ©diction indirecte, Ă  partir d’haplotypes ou d’imputation, permet de connaĂźtre le statut Ă  la mutation des reproducteurs plus anciens avec une forte probabilitĂ© sans nĂ©cessitĂ© de rĂ©-analyser leur ADN. Une fois ce bilan Ă©tabli, les mesures Ă  prendre dĂ©pendent du poids Ă©conomique des anomalies qui est fonction de deux paramĂštres, le coĂ»t par individu atteint et la frĂ©quence allĂ©lique dans la population. La mĂ©thode optimale permettant une Ă©radication progressive des anomalies repose sur l’utilisation d’un objectif de sĂ©lection combinant les anomalies aux autres caractĂšres. Une phase dĂ©licate Ă  gĂ©rer, principalement au travers des accouplements, est celle de l’utilisation de reproducteurs porteurs durant la pĂ©riode de transition entre la dĂ©couverte de l’anomalie et l’éradication complĂšte. Enfin, il est rappelĂ© qu’une mesure simple permettant de limiter l’émergence de nouvelles anomalies est d’utiliser un nombre Ă©levĂ© de reproducteurs tout en restreignant leur taille de descendance.For years, genetic defects were discovered sporadically and this led breeders to eradicate drastically all the carriers in combination with the procreation of non carrier future reproducing animals. However there is a new paradigm with the setting up of genomic selection since genetic defects are now detected much faster and, consequently, in larger numbers. Therefore it is necessary to adapt the way genetic defects are taken into account in selection. A good overview of the genetic situation must be obtained by estimating the allelic frequency in the population and by assessing the status of most major reproducing animals with the available diagnosis tests, now often included in SNP chips. Noteworthy, this status may also be assessed indirectly through haplotypic prediction for older animals and does not always require to genotype them again. Then the selection plan must be set up in the light of the economic weight of the defects, which depends on the cost of affected cases and allelic frequency. The optimal method to gradually eradicate genetic defects relies on the use of a breeding objective combining genetic defects with the other traits, with their economic weights. The transition phase between the discovery of a genetic defect and its complete eradication is always delicate and is usually coped by orienting the matings to avoid cases. Finally, it is recalled that using a large number of breeding animals while restricting their number of offspring is a simple measure that efficiently limits the outbreaks of new genetic defects

    Causes de la mortalitĂ© embryonnaire ou fƓtale de 2 mutants bovins

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    CrĂ©dits Incitatifs 2012Champ ThĂ©matique: AdaptationCauses de la mortalitĂ© embryonnaire ou fƓtale de 2 mutants bovins. JournĂ©es d’Animation des CrĂ©dits Incitatifs du DĂ©partement de Physiologie Animale et SystĂšmes d’Elevage (JACI Phase 2016
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