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Updated: Feb 4, 2026

Single-Cell Suspension Preparation from Nile Tilapia Intestine for Single-Cell Sequencing
Published on: February 10, 2023
Transcriptomic response to parasite infection in Nile tilapia (Oreochromis niloticus) depends on rearing density
Amy R Ellison1, Tamsyn M Uren Webster2, Olivier Rey2,3
1School of Biosciences, Cardiff University, Cardiff, CF10 3AX, UK. EllisonA@cardiff.ac.uk.
Background:
Captive animal populations, be it for food production or conservation programmes, are often maintained at densities far beyond those in natural environments, which can have profound effects on behaviour, immune and stress levels, and ultimately welfare. How such alterations impact transcriptional responses to pathogen infection is a 'different kettle of fish' and remains poorly understood. Here, we assessed survival and gene expression profiles of infected fish reared at two different densities to elucidate potential functional genomic mechanisms for density-related differences in disease susceptibility.
Results:
Utilising a whole-transcriptome sequencing (RNAseq) approach, we demonstrate that rearing density in tilapia (Oreochromis niloticus) significantly impacts susceptibility to the oomycete Saprolegnia parasitica, via altered transcriptional infection responses. Tilapia held at low densities have increased expression of genes related to stress, likely due to increased aggressive interactions. When challenged with Saprolegnia, low-density fish exhibit altered expression of inflammatory gene responses and enhanced levels of adaptive immune gene suppression compared to fish reared at higher density, resulting in significantly increased mortality rates. In addition, Saprolegnia infection substantially perturbs expression of circadian clock genes, with fish reared at low-density having higher levels of molecular clock dysregulation.
Conclusions:
Our results reveal the wide-scale impact of stocking density on transcriptional responses to infection and highlight the need to incorporate circadian biology into our understanding of disease dynamics in managed animals.
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