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Data paper: Dataset describing the effects of environmental enrichment and sows’ characteristics on the peripheral blood mononuclear cell transcriptome

Blood immune cells transcriptome can be used as a tool to investigate molecular mechanisms or identify biomarkers of several physiological processes. Factors such as reproductive status, age, or physical and mental states resulting from social and non-social environmental aspects can influence the a...

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Published in:Animal - Open Space 2024-12, Vol.3, p.100078, Article 100078
Main Authors: Lopes, M.M., Vincent, A., Thomas, F., Clouard, C., Comte, R., Brien, M., Chambeaud, J., Hérault, F., Guichoux, E., Boury, C., Resmond, R., Merlot, E.
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Language:English
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Summary:Blood immune cells transcriptome can be used as a tool to investigate molecular mechanisms or identify biomarkers of several physiological processes. Factors such as reproductive status, age, or physical and mental states resulting from social and non-social environmental aspects can influence the activation and phenotype of immune cells. This data paper describes the gene expression levels in peripheral blood mononuclear cells (PBMCs) of multiparous sows, using RNA sequencing. Sows of various parity ranks were housed during gestation in a stable social group either in a conventional environment on a slatted concrete floor (C) or in an enriched environment with deep straw litter and a bigger space allowance (E). Videos were recorded between days 99 and 104 of gestation (G; G99 and G104) to determine the sows’ dominance status. Blood samples were collected at 98 days of gestation (G98) and 12 days of lactation (L12), and the PBMC fraction was isolated. Then, total RNA was extracted from PBMC and submitted to next-generation sequencing using the Illumina NextSeq 2000 system. Quality control, mapping, and annotation were performed using the Dragen RNA v3.8.4 software. The differential analysis was performed using the R package DESeq2. Differentially expressed genes (DEGs) were identified using a criterion of adjusted P-value (p-adj) cut-off 1.2 or 
ISSN:2772-6940
2772-6940
DOI:10.1016/j.anopes.2024.100078