eKhSACIR інституційному репозитарії Харківської державної академії культури
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Meiotic and gene expression analyses in a case of t(1;15) azoospermic boar
No full textInternational audienceThe systematic cytogenetic screening of young boars carried out for more than 20 years in our laboratory allowed us to accurately estimate the prevalence of balanced structural chromosomal rearrangements in the French pig populations (0.5%). Up to now, more than 39000 boars have been analyzed, and 180 new structural abnormalities have been identified. The most frequent were reciprocal translocations (87%). Contrary to humans, altered semen quality (oligo- or azoospermia) was detected in a few cases only: 4 Y-autosome translocations (Y/1, Y/9, Y/14, Y/16) and one autosome/autosome translocation (1/14). Here, we report the case of a t(1;15) reciprocal translocation identified in an infertile zoospermic boar. Breakpoints position was determined by mate pair sequencing of microdissected translocated chromosomes. Meiotic pairing and recombination were investigated by immunostaining of the SCP1, SCP3, and MLH1 proteins, and analyzed by classical and super resolution microcopy. Finally, the impact of meiotic pairing impairments on SSC1 and SSC15, as well as SSCX and SSCY gene expression was investigated by qPCR. Histological analysis revealed a total meiotic arrest at the spermatocyte I stage. The rearrangement was characterized by the translocation of a large part of the SSC15 onto the SSC1, leading to the formation of a tiny derivative chromosome 15. A quadrivalent was observed in 87% of the 113 spermatocytes analyzed, and a trivalent plus univalent in the remaining cells. 40% of the quadrivalents as as well as 33% of the trivalents were associated with the XY body. A γH2AX positive signal on SSC1 or SSC15 chromatin was observed in 87% of the spermatocytes analyzed. These results confirmed the impairment of meiotic process. We will also present on-going results on synaptonemal complex analysis by super-resolution microscopy and the expression of several genes located on SSC1, SSC15, SSCX and SSCY
Evidence that individuals among chickens are able to durably control Mardivirus replication in feathers
No full textSession 2: Epidemiology, diagnosis and pathogenesis - Communication courte (Abstract)International audienc
Modelling variations in partition of carbon balance in lactating ruminants
No full textInternational audienc
Impacts de la méthanisation sur le bilan des flux d’azote dans une succession de culture fertilisée avec des effluents méthanisés ou non : premiers résultats
No full textNational audienc
Applying deep learning for agricultural classification using multitemporal SAR Sentinel-1 for Camargue, France
No full text[Departement_IRSTEA]Territoires [TR1_IRSTEA]SYNERGIE [Axe_IRSTEA]TETIS-ATTOS [ADD1_IRSTEA]Dynamiques spatiales d'anthropisation [Coll_IRSTEA]Proceedings of SPIEInternational audienceThe aim of this paper is to provide a better understanding of potentialities of the new Sentinel-1 radar images for mapping the different crops in the Camargue region in the South France. The originality relies on deep learning techniques. The analysis is carried out on multitemporal Sentinel-1 data over an area in Camargue, France. 50 Sentinel-1 images processed in order to produce an intensity radar data stack from May 2017 to September 2017. We revealed that even with classical machine learning approaches (K nearest neighbors, random forest, and support vector machine), good performance classification could be achieved with F-measure/Accuracy greater than 86 % and Kappa coefficient better than 0.82. We found that the results of the two deep recurrent neural network (RNN)-based classifiers clearly outperformed the classical approaches. Finally, our analyses of Camargue area results show that the same performance was obtained with two different RNN-based classifiers on the Rice class, which is the most dominant crop of this region, with a F-measure metric of 96 %. These results thus highlight that in the near future, these RNN-based techniques will play an important role in the analysis of remote sensing time series
Deciphering the molecular and genetic bases of grape tolerance to trunk diseases
No full textNational audienc
Efficient ReML inference in the Variance Component Mixed Models using Min-Max procedures
No full textInternational audienc
A model of urinary nitrogen excretion: a way to assess diet protein value at individual level?
No full textSession 3: Precision herbivore nutritionNational audienc
Nomenclature for factors of the SLA system, update 2018
No full textNomenclature for factors of the SLA system, update 2018. 6. European Veterinary and Immunology Workshop (EVIW
