Comparison of Reliable Reference Genes Following Different Hormone Treatments by Various Algorithms for qRT-PCR Analysis of Metasequoia

Abstract

Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is the most sensitive technique for evaluating gene expression levels. Choosing appropriate reference genes for normalizing target gene expression is important for verifying expression changes. Metasequoia is a high-quality and economically important wood species. However, few systematic studies have examined reference genes in Metasequoia. Here, the expression stability of 14 candidate reference genes in different tissues and following different hormone treatments were analyzed using six algorithms. Candidate reference genes were used to normalize the expression pattern of FLOWERING LOCUS T and pyrabactin resistance-like 8. Analysis using the GrayNorm algorithm showed that ACT2 (Actin 2), HIS (histone superfamily protein H3) and TATA (TATA binding protein) were stably expressed in different tissues. ACT2, EF1α (elongation factor-1 alpha) and HIS were optimal for leaves treated with the flowering induction hormone solution, while Cpn60β (60-kDa chaperonin β-subunit), GAPDH (glyceraldehyde-3-phosphate dehydrogenase) and HIS were the best reference genes for treated buds. EF1α, HIS and TATA were useful reference genes for accurate normalization in abscisic acid-response signaling. Our results emphasize the importance of validating reference genes for qRT-PCR analysis in Metasequoia. To avoid errors, suitable reference genes should be used for different tissues and hormone treatments to increase normalization accuracy. Our study provides a foundation for reference gene normalization when analyzing gene expression in Metasequoia.