Selection and validation of reference genes for quantitative real-time PCR in the green microalgae Tetraselmis chui

Quantitative real-time reverse transcription PCR (RT-qPCR) is a highly sensitive technique that can be applied to analyze how genes are modulated by culture conditions, but identification of appropriate reference genes for normalization is a critical factor to be considered. For this reason, the expression stability of 18 candidate reference genes was evaluated for the green microalgae Tetraselmis chui using the widely employed algorithms geNorm, NormFinder, BestKeeper, the comparative Delta C-T method, and RefFinder. Microalgae samples were collected from large scale outdoor photobioreactors during the growing phase (OUT_GP), and during the semi-continuous phase at different times of the day (OUT_DC). Samples from standard indoor cultures under highly controlled conditions (IND) were also collected to complement the other data. Different rankings for the candidate reference genes were obtained depending on the culture conditions and the algorithm employed. After comparison of the achieved ranks with the different methods, the references genes selected for samples from specific culture conditions were ALD and EFL in OUT_GP, RPL32 and UBCE in OUT_DC, and cdkA and UBCE in IND. Moreover, the genes EFL and cdkA or EFL and UBCE appeared as appropriate combinations for pools generated from all samples (ALL). Examination in the OUT_DC cultures of genes encoding the large and small subunits of ADP-glucose pyrophosphorylase (AGPL and AGPS, respectively) confirmed the reliability of the identified reference genes, RPL32 and UBCE. The present study represents a useful contribution for studies of gene expression in T. chui, and also represents the first step to set-up an RT-qPCR platform for quality control of T. chui biomass production in industrial facilities.

Automated summary

Quantitative real-time reverse transcription PCR (RT-qPCR) was used to analyze gene modulation in green microalgae Tetraselmis chui, with evaluation of 18 candidate reference genes using different algorithms under various culture conditions. The study identified specific reference genes for different culture conditions and highlighted the reliability of these genes for gene expression studies in T. chui. This research contributes to establishing an RT-qPCR platform for quality control of biomass production in industrial facilities.