Evaluation of Appropriate Reference Genes for Reverse Transcription-Quantitative PCR Studies in Different Tissues of a Desert Poplar via Comparision of Different Algorithms

Abstract

Despite the unshakable status of reverse transcription-quantitative PCR in gene expression analysis, it has certain disadvantages, including that the results are highly dependent on the reference genes selected for data normalization. Since inappropriate endogenous control genes will lead to inaccurate target gene expression profiles, the validation of suitable internal reference genes is essential. Given the increasing interest in functional genes and genomics of Populus euphratica, a desert poplar showing extraordinary adaptation to salt stress, we evaluated the expression stability of ten candidate reference genes in P. euphratica roots, stems, and leaves under salt stress conditions. We used five algorithms, namely, ΔCt, NormFinder, geNorm, GrayNorm, and a rank aggregation method (RankAggreg) to identify suitable normalizers. To support the suitability of the identified reference genes and to compare the relative merits of these different algorithms, we analyzed and compared the relative expression levels of nine P. euphratica functional genes in different tissues. Our results indicate that a combination of multiple reference genes recommended by GrayNorm algorithm (e.g., a combination of Actin, EF1α, GAPDH, RP, UBQ in root) should be used instead of a single reference gene. These results are valuable for research of gene identification in different P. euphratica tissues.