arXiv subjects

Ingrid David

Publications and source records attributed to Ingrid David.

3 recordsLinked to original sources

arXiv2026

Genetic determinism of circadian rhythm of feed intake and relation with feed efficiency evaluated in group-housed growing Large White pigs

Background Genetic parameters of feeding behaviours traits from electronic feeding stations in relation to feed efficiency have been widely explored. However, genetic determinism of the circadian rhythm of feed intake throughout the fattening phase in group-housed growing pigs fed ad libitum has never been investigated, despite the well-known relationships between animals' circadian rhythms and the optimization of their metabolism. The objective of this study was to (i) propose three new traits derived from time-frequency approach applied to electronic feeding data from 2,297 Large White pigs that reflect the consistency of circadian feed intake rhythm throughout fattening (so called DayCR) and the precocity of its establishment (so called IndexCR and gCR), and then to (ii) estimate the heritability of those traits and their genetic correlations with residual feed intake using a multiple trait model. Results Results highlighted moderate heritability estimates for the three circadian traits (range h2: [0.24; 0.35]) and high heritability for residual feed intake (0.41). High genetic correlations (range of absolute values: [0.87; 0.98]) among circadian traits suggested that pigs exhibiting a 24-hour periodicity in feed intake on most days of fattening, particularly during the final fattening period, establish their circadian rhythm earlier than the other pigs. The low (range of absolute values: [0.18; 0.27]) but favourable genetic correlations between residual feed intake and circadian traits revealed that animals with a consistent and early 24-hour periodicity of feed intake also tend to be more feed efficient. Conclusions This study proposed to apply time-frequency analysis on longitudinal feeding data to detect 24-hour periodicities in the hourly feed intake pattern across days throughout fattening in growing-pigs. Results suggested that part of the variability observed in the establishment of circadian rhythm is genetically driven, further supporting the feasibility of genetic selection on circadian traits. Considering the well-established biological mechanisms underlying circadian feeding rhythm, selecting animals for their ability to exhibit an early and consistent 24-hour periodicity of feed intake could promote metabolic homeostasis, thereby enhancing animal performance and resilience.

q-bio.PE↗

arXiv2025

Simulating transgenerational hologenomes under selection with RITHMS

A holobiont is made up of a host organism together with its microbiota. In the context of animal breeding, the holobiont can be viewed as the single unit upon which selection operates. Therefore, integrating microbiota data into genomic prediction models may be a promising approach to improve predictions of phenotypic and genetic values. Nevertheless, there is a paucity of hologenomic transgenerational data to address this hypothesis, and thus to fill this gap, we propose a new simulation framework. Our approach, an R Implementation of a Transgenerational Hologenomic Model-based Simulator (RITHMS) is an open-source package. It builds upon simulated transgenerational genotypes from the Modular Breeding Program Simulator (MoBPS) package and incorporates distinctive characteristics of the microbiota, notably vertical and horizontal transmission as well as modulation due to the environment and host genetics. In addition, RITHMS can account for a variety of selection strategies and is adaptable to different genetic architectures. We simulated transgenerational hologenomic data using RITHMS under a wide variety of scenarios, varying heritability, microbiability, and microbiota transmissibility. We found that simulated data accurately preserved key characteristics across generations, notably microbial diversity metrics, exhibited the expected behavior in terms of correlation between taxa and of modulation of vertical and horizontal transmission, response to environmental effects and the evolution of phenotypic values depending on selection strategy. Our results support the relevance of our simulation framework and illustrate its possible use for building a selection index balancing genetic gain and microbial diversity and for evaluating the impact of partially observed microbiota data. RITHMS is an advanced, flexible tool for generating transgenerational hologenomes under selection that incorporate the complex interplay between genetics, microbiota and environment.

stat.ME↗

arXiv2024

Classifying active and inactive states of growing rabbits from accelerometer data using machine learning algorithms

This study explores how wearable accelerometers, small devices that measure acceleration, can help monitor the activity of growing rabbits. We equipped 16 rabbits with these devices and filmed them for two weeks. By watching the videos and using a special software we figure out what the rabbits were doing -- things like lying down, eating, moving around, and more. These activitties were grouped into two states: active or inactive. Then, this information along acceleration data was used to teach a computer program to recognize when the rabbits were active or not. This technology offers a reliable way to understand rabbit behavior, which could lead to better management practices in animal production.

eess.SP↗