Journal
PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS
Volume 24, Issue 3, Pages 369-378Publisher
SPRINGER
DOI: 10.1007/s12298-018-0528-1
Keywords
Normalizer genes; Endogenous genes; Quantitative real time; Stability; Gene expression
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Funding
- CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico, Brasilia, Brazil)
- CAPES (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior, Brasilia, Brazil)
- UESC (Universidade Estadual de Santa Cruz, Ilheus, Bahia, Brazil)
- CAPES Foundation
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Bixa orellana L., popularly known as annatto, produces several secondary metabolites of pharmaceutical and industrial interest, including bixin, whose molecular basis of biosynthesis remain to be determined. Gene expression analysis by quantitative real-time PCR (qPCR) is an important tool to advance such knowledge. However, correct interpretation of qPCR data requires the use of suitable reference genes in order to reduce experimental variations. In the present study, we have selected four different candidates for reference genes in B. orellana, coding for 40S ribosomal protein S9 (RPS9), histone H4 (H4), 60S ribosomal protein L38 (RPL38) and 18S ribosomal RNA (18SrRNA). Their expression stabilities in different tissues (e.g. flower buds, flowers, leaves and seeds at different developmental stages) were analyzed using five statistical tools (NormFinder, geNorm, BestKeeper, Delta Ct method and RefFinder). The results indicated that RPL38 is the most stable gene in different tissues and stages of seed development and 18SrRNA is the most unstable among the analyzed genes. In order to validate the candidate reference genes, we have analyzed the relative expression of a target gene coding for carotenoid cleavage dioxygenase 1 (CCD1) using the stable RPL38 and the least stable gene, 18SrRNA, for normalization of the qPCR data. The results demonstrated significant differences in the interpretation of the CCD1 gene expression data, depending on the reference gene used, reinforcing the importance of the correct selection of reference genes for normalization.
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