Plant Cell Reports

, Volume 34, Issue 7, pp 1139–1149 | Cite as

Comprehensive selection of reference genes for quantitative gene expression analysis during seed development in Brassica napus

  • Ronei Dorneles Machado
  • Ana Paula Christoff
  • Guilherme Loss-Morais
  • Márcia Margis-Pinheiro
  • Rogério Margis
  • Ana Paula KörbesEmail author
Original Paper


Key message

MicroRNAs have higher expression stability than protein-coding genes in B. napus seeds and are therefore good reference genes for miRNA and mRNA RT-qPCR analysis.


Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) has become the “gold standard” to gain insight into function of genes. However, the accuracy of the technique depends on appropriate reference genes for quantification analysis in different experimental conditions. Accumulation of microRNAs (miRNAs) has also been studied by RT-qPCR, but there are no reference genes currently validated for normalization of Brassica napus miRNA expression data. In this study, we selected 43 B. napus miRNAs and 18 previously validated mRNA reference genes. The expression stability of the candidate reference genes was evaluated in different tissue samples (stages of seed development, flowers, and leaves) using geNorm, NormFinder, and RefFinder analysis. The best-ranked reference genes for expression studies during seed development (miR167-1_2, miR11-1, miR159-1 and miR168-1) were used to asses the expression of miR03-1. Since candidate miRNAs showed higher expression stability than protein-coding genes in most of the tested conditions, the expression profile of DGAT1 gene was compared when normalized by the four most stable miRNAs reference genes and by the four most stable mRNA reference genes. The expected expression pattern of DGAT1 during seed development was achieved with the use of miRNA as reference genes. In conclusion, the most stable miRNA reference genes can be employed in the normalization of RT-qPCR quantification of miRNAs and protein-coding genes. This work is the first to perform a comprehensive survey of the stability of miRNA reference genes in B. napus and provides guidelines to obtain more accurate RT-qPCR results in B. napus seeds studies.


RT-qPCR microRNAs geNorm Normalization Rapeseed Seeds 



This work was financially supported by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES-CNPq, Brazilian Ministry of Education), Conselho Nacional de Desenvolvimento Científico e Tecnológico (Genoprot-CNPq-MCT No. 559636/2009-1; CNPq-Universal No. 472575/2011-2), Fundação de Amparo à Pesquisa do Estado do Rio Grande do Sul (Agroestruturante-FAPERGS). APK, APC, and GLM were sponsored by research and Ph.D. grants from CAPES. RM and MM were sponsored by research grants from CNPq.

Conflict of interest

The authors declare that they have no conflict of interest.

Supplementary material

299_2015_1773_MOESM1_ESM.tif (673 kb)
Supplementary Fig. 1 Ranking of candidate reference genes based on NormFinder analysis for (a) stages of seed development, (b) flowers, (c) and leaf samples. Lower stability values indicate more stable gene expression (TIFF 672 kb)
299_2015_1773_MOESM2_ESM.pdf (58 kb)
Supplementary Table 1 Primer sequences and amplicon characteristics of 61 candidate reference genes tested for gene expression normalization (PDF 58 kb)
299_2015_1773_MOESM3_ESM.pdf (136 kb)
Supplementary Table 2 Accession numbers of B. napus protein-coding genes used in this study (PDF 135 kb)
299_2015_1773_MOESM4_ESM.xlsx (16 kb)
Supplementary Table 3 Ranking of candidate reference genes for all tissues sample set was based on gene expression stability calculated by NormFinder. Each tissue sample set was considered as a group for NormaFinder analysis (XLSX 16 kb)
299_2015_1773_MOESM5_ESM.xlsx (22 kb)
Supplementary Table 4 BestKeeper descriptive statistics calculated by RefFinder (XLSX 23 kb)
299_2015_1773_MOESM6_ESM.docx (16 kb)
Supplementary Table 5 Gene expression stability of the best candidate reference genes for flower data set (top) and leaf data set (bottom) as assessed by RefFinder (DOCX 16 kb)


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Ronei Dorneles Machado
    • 1
  • Ana Paula Christoff
    • 1
  • Guilherme Loss-Morais
    • 2
    • 3
  • Márcia Margis-Pinheiro
    • 1
    • 2
  • Rogério Margis
    • 1
    • 2
    • 4
  • Ana Paula Körbes
    • 1
    Email author
  1. 1.Departamento de Genética, PPGGBMUniversidade Federal do Rio Grande do Sul, UFRGSPorto AlegreBrazil
  2. 2.Centro de Biotecnologia, PPGBCMUniversidade Federal do Rio Grande do Sul, UFRGSPorto AlegreBrazil
  3. 3.LNCC, Laboratório Nacional de Computação Científica, LabinfoLaboratório de BioinformáticaPetrópolisBrazil
  4. 4.Departamento de BiofísicaUniversidade Federal do Rio Grande do Sul, UFRGSPorto AlegreBrazil

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