eKhSACIR інституційному репозитарії Харківської державної академії культури
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Does polyribonucleotide nucleotidyltransferase (PNPase) mutation affect the energetic metabolism and the microRNA profile in cell and mitochondria ?
No full text7. worldInternational audienc
High-protein exposure during gestation - consequences on food preferences and health in adult rat offspring in self-selection models
No full textInternational audienc
Small non coding RNA from frozen bull sperm cells: biomarkers of male fertility?
No full textInternational audienceThe sperm cell has been generally considered as a cab driver, carrying and protecting his genetic heritage, but a new vision of its functions has emerged recently. Indeed, sperm cells also carry small noncoding RNAs (sncRNAs) into oocytes during fertilization. Although their roles remain largely unclear, involvement of sperm-borne miRNAs in mouse epigenetic inheritance has been evidenced and paternal miRNAs and/or endo-siRNAs have been shown to be dispensable for fertilization but crucial for the transcriptomic homeostasis and the developmental of zygotes and 2 cells-embryos. This study aimed at unraveling the sncRNA content from bull frozen sperm cells and identifying miRNA or piRNAs associated with fertility. Total RNA has been produced from 40 ejaculates originating from Holstein and Montbeliard bulls with contrasting fertility. To achieve this task, a novel protocol has been developed to ensure good quality and reproducibility. Quality control was ensured by total RNA quantification using the RNA HS Qubit Assay kit, as well as miR125 quantitation by RTqPCR (miRCURY LNA Universal RT microRNA PCR kit; Exiqon). Starting from 77 million of frozen sperm cells on average, RNA yield was 51 ± 15ng, leading to miR125 Cycle Threshold values in a 19 - 20 range. Only small RNA (<200 nucleotides) were retained to construct NGS libraries, which were sequenced at modest depth (40 million 50 bp single reads, Illumina HiSeq; Exiqon). BWA mapping and annotation was performed, identifying about two thirds of the sequenced reads. Among identified sequences, 16% are annotated as miRNA, 13% as rRNA, 7.5% as tRNA, 7.2% as long non coding RNA, 6.5% as mitochondrial RNA and 17% as mRNA. By the use of miRDeep2 software, 3196 miRNA expressed within all samples have been identified, including 583 known and 2613 putative miRNAs. Interestingly, the remaining unknown sequences are consistent in terms of size with piRNA, which are known to be expressed spermatocytes, spermatids and sperm cells. Expression normalization and statistical analysis were carried out using the DESeq2 package, highlighting 47 differentially expressed miRNA between fertility groups
La supplémentation de fibres alimentaires, en surnutrition, limite la lipogenèse hépatique et favorisent la β-oxydation musculaire
No full textNational audienc
Long-non coding RNAs repertoires in liver and two T lymphocyte cell types in four livestock species
No full textUnderstanding genome-to-phenome relationships requires deep and cross-disciplinary genetic analyses among which functional annotation provides crucial insights. The development of High Throughput Sequencing and RNA-seq now help us to find a large number of heterogeneous and low-expressed transcripts known to be long non-coding RNAs (lncRNAs). One of the aims of the FAANG pilot project ‘FR-AgENCODE’ is to identify and characterise the long non-coding RNAs of multiple tissues and cell lines in 4 farm animals (chicken, bovine, pig and goat) of both sexes. Here, we focus our analysis on the liver tissue and two blood T-cell types (CD3+CD4+, CD3+CD8+) where samples were collected through 4 biological replicates (2 males and 2 females). It allows us to compare lncRNA repertoires between tissues, sex and species in relation with fundamental biological functions like energy storage and immunity. High depth strand-specific RNA-seq produced ~200Mpaired-end reads for each of the 16 RNA-seq datasets. After transcriptome reconstruction, we used the recently published FEELnc program (Wucher et al., 2017, Nucleic Acid Research) to identify lncRNAs longer than 200 bp and without protein-coding capabilities. FEELnc also classifies lncRNAs based on their genomic localizationswith respect to the ENSEMBL protein-coding annotation: intergenic lncRNAs are categorized depending on the distance and orientation with respect to the closest mRNAs and the intragenic lncRNAs are extracted based on their overlap with mRNAs exons and introns. We will report these lncRNA repertoires in terms of intergenic/ intragenic lncRNA class, structure and expression and comparing these features between livestock species, tissues and sexes. By profiling the transcriptional landscape of lncRNAs in these 4 species, this data will further contribute to the global action for annotating functional elements of livestock genomes
Describing the dynamics of wheat canopy structure at early stages by assimilating observations of green fractions within a 3D wheat model
No full textInternational audienceMonitoring the dynamics of canopy architecture during the early stages is highly desirable for breeders to select cultivars of high drought-tolerance, resistance to weed infestation, improved water-use efficiency and potentially high grain yield. To achieve this objective, we propose to assimilate phenotyping observations into 3D canopy model. The feasibility and interest of this approach was evaluated through in silico experiments on wheat crops. A sequential assimilation scheme was developed to limit the space of canopy realization since the simulations of the 3D canopy architecture as well as the derivation of the corresponding phenotyping measurements is computer demanding. The early growth was decomposed into 2 consecutive stages. For each stage, 5 main influential parameters were identified. The green fraction measurements are estimated from RGB images simulated at several dates during the early stages and from several view inclination angles. The 5 influential parameters of the first phase and the 5 additional ones used for the second phase were estimated using a neural network machine learning technique with the GF temporal profiles as inputs. The posterior information derived after the first phase was used as prior information for the second phase of assimilation. Results show that the parameters defining the size and rate of change of the green wheat crop elements were estimated with a relatively good accuracy. Conversely, the parameters driving the orientation and inclination of the elements were retrieved with a poor accuracy. However, some important emerging properties were very well retrieved, including the GAI and the number of tillers with more than 3 leaves at the beginning of stem elongation. Further detailed sensitivity analysis highlights the importance of getting enough dates of measurements covering the growth cycle, while dates separated by less than a phyllochron do not provide significant additional information. The sensitivity analysis highlighted also the importance of the inclined observations. The assimilation approach proposed appears very general and could be applied to a number of phenotyping measurements completed along the growth cycle. Nevertheless, because our results were achieved using in silico experiments, further validation is necessary using actual field measurements
Assessment and monitoring of polluted soils using nematodes: results of a meta-analysis
No full textAssessment and monitoring of polluted soils using nematodes: results of a meta-analysis. 3rd International symposium on nematodes as envir. bioindicator
A human cross-over study to test differences in bioavailable protein using a dual stable isotope ratio method
No full textInternational audienc
Genetic evaluation of claw health traits accounting for potential preselection of cows to be trimmed
No full textInternational audienc
Interactive evolutionary modelling of living complex food systems
No full textModelling the production and stabilisation process of lactic acid starters has several practical applications, ranging from assessing the e!cacy of new industrial methods, to proposing alternative sustainable systems of food production. In order to reach this objective, however, it is necessary to overcome several obstacles, tied to the complex nature and interactions of the target processes. In this paper, we present a novel complex system modelling approach, exploiting both stand-alone evolutionary search and visual interaction with the user. The presented framework is then tested on a real-world case study, for which it shows promising results