Screening of Reference Gene for RT-qPCR in Leymus chinensis During Environmental Stress Conditions
Abstract
Reliable reference genes are critical for ensuring the accuracy of RT-qPCR-based gene expression analysis, especially under environmental stress conditions. In this study, Leymus chinensis was used as the experimental material, and eight candidate reference genes—alpha-tubulin (TUA), beta-tubulin (TUB), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), elongation factor 1-alpha (EF1α), 18S ribosomal RNA (18S rRNA), adenylyl cyclase-associated protein (CAP), adenine phosphoribosyl transferase (APRT), and actin (ACT)—were selected to evaluate their expression stability under cold, drought, heat, NaCl, high pH, wounding, abscisic acid (ABA) and jasmonic acid (JA) treatments. Primer specificity and amplification efficiency were first assessed, and the candidate genes were then comprehensively analyzed using geNorm, NormFinder, BestKeeper, and RefFinder. The results showed that the amplification efficiencies of all primers ranged from 95.0% to 107.2%, and the Ct values of the candidate genes ranged from 17.31 to 30.99. Comprehensive analysis using RefFinder showed that ACTIN was the most stable gene under ABA and NaCl treatments, EF1α under heat and wounding treatments, CAP under JA and high pH treatments, APRT under cold treatment, and TUB under drought treatment. geNorm analysis indicated that two reference genes were sufficient for accurate normalization under each treatment condition. The reliability of the screening results was further confirmed by expression-level validation of LcbZIP46, LcWRKY5, and LcFIN1. This study provides a stable reference gene system for RT-qPCR-based expression analysis in Leymus chinensis under environmental stress conditions.
Fields of Study & Subjects
Molecular Biology Techniques and Applications
Gene expression and cancer classification
Advanced biosensing and bioanalysis techniques
Publication details
- Journal / source
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Volume
- 27
- Issue
- 14
- Pages
- 6426–6426
- Publication date
- 20 July 2026
- Language
- EN