Biology subjects

Billon, Y.

Publications and source records attributed to Billon, Y..

7 recordsLinked to original sources

bioRxiv2026

Host genetics and pre-vaccination blood transcriptome as determinants of vaccine-induced immunity to Influenza A virus in swine

Influenza A virus (IAV) is a major respiratory pathogen in pigs, causing diseases that have significant economic and potential public health consequences. Vaccine effectiveness varies among animals, impacting long-term herd protection due to individual variabilities in antibody levels and persistence over time. Our aim was to identify the genetic factors and pre-vaccination blood transcriptomic profiles that influence immune response levels to the IAV vaccine. A total of 187 piglets were vaccinated at weaning (28 days of age, 0 days post-vaccination, dpv) and boosted three weeks later, and humoral responses were assessed until slaughter (21, 28, 35, and 118 dpv) by measuring serum IAV-specific IgG and hemagglutination inhibition (HAI) titers. The results revealed varying antibody responses and persistence. Genome-wide association studies identified two loci on chromosomes SSC5 and SSC8 associated with a persistence of HAI titers until slaughter. Pre-vaccination blood transcriptomic analyses showed that early and post-boost antibody responses (21, 28 and 35 dpv) and long-term persistence (118 dpv) were associated with distinct baseline immune programs, with extracellular matrix and myeloid-related signatures predicting strong early and peak responses, whereas interferon-related signatures were linked to reduced long-term antibody persistence. Our results highlight the importance of considering the role of immune competence and genetics in vaccine responses in pigs and suggest candidate biomarkers to improve vaccination strategies within breeding programs.

genomics↗

bioRxiv2023

A methyl-seq tool to capture genomic imprinted loci

Genomic imprinting represents an original model of epigenetic regulation resulting in a parent-of-origin expression. Despite the critical role of imprinted genes in mammalian growth, metabolism and neuronal function, there is no molecular tool specifically targeting them for a systematic evaluation. Here, we optimized and compared to bisulfite-based standard a novel methyl-seq system to capture 165 candidate regions for genomic imprinting and ultimately detect parent-of-origin methylation, the main hallmark of imprinting.

genomics↗

bioRxiv2022

Stronger transcriptomic response to feed intake in the duodenum of pig with high feed efficiency from a divergent selection experiment

Feed efficiency is a trait of interest in pigs as it contributes to lowering the ecological and economical costs of pig production. A divergent genetic selection experiment from a Large White pig population was performed for 10 generations, leading to pig lines with relative low-(LRFI, more efficient) and high-(HRFI, less efficient) residual feed intake (RFI). Feeding behaviour and metabolic differences have been previously reported between the two lines. We hypothesised that part of these differences could be related to differential sensing and absorption of nutrients in the proximal intestine. Here we investigated the duodenum transcriptome and DNA methylation profiles comparing overnight fasting with ad libitum feeding in LRFI and HRFI pigs (n=24). We identified 1,106 differentially expressed genes between the two lines, notably affecting pathways of the transmembrane transport activity and related to mitosis or chromosome separation. The LRFI line showed a greater transcriptomic response to feed intake, with 2,222 differentially expressed genes before and after a meal, as compared to 61 differentially expressed genes in the HRFI line. Feed intake affected genes from both anabolic and catabolic pathways in the pig duodenum, such as rRNA production and autophagy. We noted that several nutrient transporter and tight junction genes were differentially expressed between lines and/or by short term feed intake. We also identified 409 differentially methylated regions in the duodenum mucosa between the two lines, while this epigenetic mark was less affected by feeding. However most of the differentially expressed genes were not associated with proximal changes in DNA methylation profiles. Altogether, our findings highlighted that the genetic selection for feed efficiency in pigs changed the transcriptome profiles of the duodenum, and notably its response to feed intake, suggesting key roles for this proximal gut segment in mechanisms underlying feed efficiency.

genomics↗

bioRxiv2022

Automated detection of sow posture changes with millimeter-wave radars and deep learning

Automated behavioural monitoring is increasingly required for animal welfare and precision agriculture. In pig farming, detailed analyses of sow activity are essential to identify and reduce the risks of piglets being crushed during postural changes of their mothers. Here we introduce a new, non-invasive, fast and accurate method for monitoring sow behaviour based on millimeter-wave radars and deep learning analysis. We used our method to predict postural changes in crated sows and distinguish the dangerous one that lie down abruptly from those that lie down carefully using transient postures. Two radars were placed on a metal backing above the head and the upper part of the back of each of ten sows to monitor their activity during 5 hours. We analysed the radar data with a convolutional neural network and identified five postures. The average sensitivity was 96.9% for standing, 90.8% for lying, 91.4% for nursing, 87.6% for sitting, but only 11.9% for kneeling. However, the average specificity and accuracy were greater than 92% for the five postures. Interestingly, two of the ten sows occasionally moved directly from standing to lying, without using the transient postures sitting and kneeling, thereby displaying risky behaviours for their piglets. Our radar-based classifier is more accurate, faster and require less memory than current computer vision approaches. Using more sows will improve the algorithm performance and facilitate future applications for large scale deployment in animal farming. HighlightsO_LIAutomated behavioural analysis is a major challenge for precision farming. C_LIO_LIWe developed automated detection of lactating sow postures with radars and deep learning. C_LIO_LIWe identified five postures, including transitions risky for the piglets. C_LIO_LIOur method is accurate, fast and requires less memory than computer vision. C_LIO_LIRadars thus hold considerable promises for high through-put recording of livestock activity. C_LI

animal behavior and cognition↗

bioRxiv2020

Identification of genomic regions affecting production traits in pigs divergently selected for feed efficiency

BackgroundFeed efficiency is a major driver of the sustainability of pig production systems. Understanding biological mechanisms underlying these agronomic traits is an important issue whether for environment and farms economy. This study aimed at identifying genomic regions affecting residual feed intake (RFI) and other production traits in two pig lines divergently selected for RFI during 9 generations (LRFI, low RFI; HRFI, high RFI). ResultsWe built a whole dataset of 570,447 single nucleotide polymorphisms (SNPs) in 2,426 pigs with records for 24 production traits after both imputation and prediction of genotypes using pedigree information. Genome-wide association studies (GWAS) were performed including both lines (Global-GWAS) or each line independently (LRFI-GWAS and HRFI-GWAS). A total of 54 chromosomic regions were detected with the Global-GWAS, whereas 37 and 61 regions were detected in LRFI-GWAS and HRFI-GWAS, respectively. Among those, only 15 regions were shared between at least two analyses, and only one was common between the three GWAS but affecting different traits. Among the 12 QTL detected for RFI, some were close to QTL detected for meat quality traits and 9 pinpointed novel genomic regions for some harbored candidate genes involved in cell proliferation and differentiation processes of gastrointestinal tissues or lipid metabolism-related signaling pathways. Detection of mostly different QTL regions between the three designs suggests the strong impact of the dataset on the detection power, which could be due to the changes of allelic frequencies during the line selection. ConclusionsBesides efficiently detecting known and new QTL regions for feed efficiency, the combination of GWAS carried out per line or simultaneously using all individuals highlighted the identification of chromosomic regions under selection that affect various production traits.

genetics↗

bioRxiv2020

The maturity in fetal pigs using a multi-fluid metabolomic approach

In mammalian species, the first days after birth are an important period for survival and the rates of mortality before weaning are high. In pigs, the perinatal deaths average 20% of the litter, with important economic and societal consequences. Among the factors influencing piglet survival at birth, the maturity is likely to be one of the most important. Maturity can be defined as the outcome of complex mechanisms of intra-uterine development and maturation occurring during the last month of gestation. Here, we provide new insights on maturity by studying the end of gestation at two different stages (three weeks before term and close to term) in two breeds of pigs that strongly differ in terms of neonatal survival. Since metabolomics is a promising approach for phenotype characterization or biomarker discovery, we provide a complete understanding of the metabolome of the fetuses in late gestation in three fluids (plasma, urine, and amniotic fluid). We found that biological processes related to amino acid and carbohy-drate metabolisms are critical for piglet maturity. We also confirmed some previously described metabolites associated with delayed growth (e.g., proline and myo-inositol). Altogether, our study proposes new routes for a better characterization of piglet maturity at birth.

developmental biology↗

bioRxiv2018

Towards the quantitative characterization of piglets’ robustness to weaning: A modelling approach

Weaning is a critical transition phase in swine production in which piglets must cope with different stressors that may affect their health. During this period, the prophylactic use of antibiotics is still frequent to limit piglet morbidity, which raises both economic and public health concerns such as the appearance of antimicrobial-resistant microbes. With the interest of developing tools for assisting health and management decisions around weaning, it is key to provide robustness indexes that inform on the animals capacity to endure the challenges associated to weaning. This work aimed at developing a modelling approach for facilitating the quantification of piglet resilience to weaning. We monitored 325 Large White pigs weaned at 28 days of age and further housed and fed conventionally during the post-weaning period without antibiotic administration. Body weight and diarrhoea scores were recorded before and after weaning, and blood was sampled at weaning and one week later for collecting haematological data. We constructed a dynamic model based on the Gompertz-Makeham law to describe live weight trajectories during the first 75 days after weaning following the rationale that the animal response is partitioned in two time windows (a perturbation and a recovery window). Model calibration was performed for each animal. Our results show that the transition time between the two time windows, as well as the weight trajectories are characteristic for each individual. The model captured the weight dynamics of animals at different degrees of perturbation, with an average coefficient of determination of 0.99, and a concordance correlation coefficient of 0.99. The utility of the model is that it provides biological parameters that inform on the amplitude and length of perturbation, and the rate of animal recovery. Our rationale is that the dynamics of weight inform on the capability of the animal to cope with the weaning disturbance. Indeed, there were significant correlations between model parameters and individual diarrhoea scores and haematological traits. Overall, the parameters of our model can be useful for constructing weaning robustness indexes by using exclusively the growth curves. We foresee that this modelling approach will provide a step forward in the quantitative characterization of robustness.\n\nImplicationsThe quantitative characterization of animal robustness at weaning is a key step for management strategies to improve health and welfare. This characterization is also instrumental for the further design of selection strategies for productivity and robustness. Within a precision livestock farming optic, this study develops a mathematical modelling approach to describe the body weight of piglets from weaning with the rationale that weight trajectories provide central information to quantify the capability of the animal to cope with the weaning disturbance.

systems biology↗