The forgotten variable? Does the euthanasia method and sample storage condition influence an organisms transcriptome – a gene expression analysis on multiple tissues in pigs

Abstract

Abstract Background Transcriptomic studies often require collection of fresh tissues post euthanasia. The chosen euthanasia method might have the potential to induce variations in gene expressions that are unlinked with the experimental design. The present study compared the suitability of ‘nitrogen gas in foam’ (ANOXIA) in comparison to a non-barbiturate anaesthetic, T-61® (T61), for euthanizing piglets used in transcriptome research. Further, the effect of common tissue storage conditions, RNAlater™ (RL) and snap freezing in liquid nitrogen (LN2), on gene expression profiles were also analysed. Results On comparison of the 3’mRNA-Seq data generated from pituitary, hypothalamus, liver and lung tissues, no significant differential expression in the protein coding genes were detected between the euthanasia methods. This implies that the nitrogen anoxia method could be a suitable alternative for euthanasia of piglets used in transcriptomic research. However, small nuclear RNAs (snRNAs) that constitute the eukaryotic spliceosomal machinery were found to be significantly higher (log2fold change ≥ 2.0, and adjusted p value ≤ 0.1) in pituitary samples collected using ANOXIA. Non-protein coding genes like snRNAs that play an important role in pre-mRNA splicing can subsequently modify gene expression. Storage in RL was found to be superior in preserving RNA compared to LN2 storage, as evidenced by the significantly higher RIN values in representative samples. However, storage in RL as opposed to LN2, also influenced differential gene expression in multiple tissues, perhaps as a result of its inability to inhibit biological activity during storage. Hence such external sources of variations should be carefully considered before arriving at research conclusions. Conclusions Source of biological variations like euthanasia method and storage condition can confound research findings. Even if we are unable to prevent the effect of these external factors, it will be useful to identify the impact of these variables on the parameter under observation and thereby prevent misinterpretation of our results.