Genome-wide association analysis reveals QTL and candidate mutations involved in white spotting in cattle

International audienceAbstractBackgroundWhite spotting of the coat is a characteristic trait of various domestic species including cattle and other mammals. It is a hallmark of Holstein–Friesian cattle, and several previous studies have detected genetic loci with major effects for white spotting in animals with Holstein–Friesian ancestry. Here, our aim was to better understand the underlying genetic and molecular mechanisms of white spotting, by conducting the largest mapping study for this trait in cattle, to date.ResultsUsing imputed whole-genome sequence data, we conducted a genome-wide association analysis in 2973 mixed-breed cows and bulls. Highly significant quantitative trait loci (QTL) were found on chromosomes 6 and 22, highlighting the well-established coat color genes KIT and MITF as likely responsible for these effects. These results are in broad agreement with previous studies, although we also report a third significant QTL on chromosome 2 that appears to be novel. This signal maps immediately adjacent to the PAX3 gene, which encodes a known transcription factor that controls MITF expression and is the causal locus for white spotting in horses. More detailed examination of these loci revealed a candidate causal mutation in PAX3 (p.Thr424Met), and another candidate mutation (rs209784468) within a conserved element in intron 2 of MITF transcripts expressed in the skin. These analyses also revealed a mechanistic ambiguity at the chromosome 6 locus, where highly dispersed association signals suggested multiple or multiallelic QTL involving KIT and/or other genes in this region.ConclusionsOur findings extend those of previous studies that reported KIT as a likely causal gene for white spotting, and report novel associations between candidate causal mutations in both the MITF and PAX3 genes. The sizes of the effects of these QTL are substantial, and could be used to select animals with darker, or conversely whiter, coats depending on the desired characteristics

Problèmes de validation des méthodes d'estimation des précipitations par satellite en Afrique intertropicale

Dans le cadre de l'alerte précoce, le centre AGRHYMET dispose d'un outil de diagnostic de l'état hydrique des cultures et de prévision des rendements du mil. L'analyse est basée sur la simulation du bilan hydrique à partir des données pluviométriques journalières fournies tous les dix jours par les météorologies nationales des pays du CILSS. La spatialisation des termes du bilan hydrique ou des estimations de rendements peut être considérablement améliorée en remplaçant les données de postes, disponibles en nombre insuffisant en cours de campagne par les champs pluviométriques estimés à partir des images METEOSAT. L'intégration de ce modèle dans un système d'information géographique est envisagée et permettra de prendre en compte des données agronomiques spatialisées (capacité de rétention en eau des sols, occupation des sols par les cultures...). (Résumé d'auteur

A functional approach to fattening in chickens

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Approche transcriptomique de l'engraissement chez le poulet de chair

*INRA UMR Génétique Animale 35042 Rennes (FRA) Diffusion du document : INRA UMR Génétique Animale 35042 Rennes (FRA)National audienc

Automatic Text Generation: How to Write the Plot of a Novel with NooJ

Automatic Text Generation (ATG) is a Natural Language Processing (NLP) task that aims at writing acceptable and grammatical written text exploiting machine-representation systems, such as for instance knowledge bases, taxonomies and ontologies. In this sense, it is possible to state that an ATG system works like a translator that converts data into a natural-language written representation. The methods to produce the final texts may differ from those used by compilers, due to the inherent expressivity of natural languages. ATG is not a recent discipline, even if commercial ATG technology has only recently become widely available. Today, many software environments cope with ATG, as Text Spinner, DKB Lettere, or textOmatic*Composer, to mention just some of them. As a discipline strictly connected to NLP, ATG should be based strongly on morph-syntax formalization and semantic predicate use. However, in some cases it seems possible to avoid these steps. A simple example of ATG not involving the use of morph-syntactic and semantic rules may be the generation of texts using only simple alphabetic letters. This method can prove itself useful when the text to gener-ate is somehow generic in terms of semantics, and fix in terms of syntax. For in-stance, it can be used to generate a letter to a consumer stating that a credit card spending limit has been reached, or also to generate receipts from an ATM machine, or Social Media notifications. However, in theory and practice the automatic generation of more complex texts can only be based on a complete system of Natural Language Formalization (NLF), as for instance Maurice Gross’ Lexicon-Grammar. Therefore, in order to build an ATG procedure for novel plots, in this paper we will use both Lexicon-Grammar theoretical and practical framework and Max Silberztein’s NooJ NLP Environment , which as it is well known are in a strict connection. Starting from Gross’ definition of semantic predicates [1] and from the NooJ paraphrase generation routine [5,6], our aim will be to write automatically the basic plot of a novel. While achieving our aim, we will take into due account that the novel is a kind of writing difficult to define formally [7], and that the automatic writing of a novel plot is probably one of the most complex challenges an ATG routine can choose to tackle. Finally, in carrying out our research, we will also make extensive references to Text Linguistics (TL) and its theoretical and practical contact points with Formal Linguis-tics (FL)

Transcription from a gene desert in a melanoma porcine model

International audienceThe genetic mechanisms underlying cutaneous melanoma onset and progression need to be further understood to improve patients' care. Several studies have focused on the genetic determinism of melanoma development in the MeLiM pig, a biomedical model of cutaneous melanoma. The objective of this study was to better describe the influence of a particular genomic region on melanoma progression in the MeliM model. Indeed, a large region of theSus scrofachromosome 1 has been identified by linkage and association analyses, but the causal mechanisms have remained elusive. To deepen the analysis of this candidate region, a dedicated SNP panel was used to fine map the locus, downsizing the interval to less than 2 Mb, in a genomic region located within a large gene desert. Transcription from this locus was addressed using a tiling array strategy and further validated by RT-PCR in a large panel of tissues. Overall, the gene desert showed an extensive transcriptional landscape, notably dominated by repeated element transcription in tumor and fetal tissues. The transcription of LINE-1 and PERVs has been confirmed in skin and tumor samples from MeLiM pigs. In conclusion, although this study still does not identify a candidate mutation for melanoma occurrence or progression, it highlights a potential role of repeated element transcriptional activity in the MeLiM model