Suitability of three common reference genes for quantitative real-time PCR in honey bees

被引:46
|
作者
Reim, Tina [1 ]
Thamm, Markus [1 ]
Rolke, Daniel [1 ]
Blenau, Wolfgang [2 ]
Scheiner, Ricarda [1 ]
机构
[1] Univ Potsdam, Inst Biochem & Biol, D-14476 Potsdam, Germany
[2] Goethe Univ Frankfurt, Polytech Gesell, Inst Bienenkunde, D-60054 Frankfurt, Oberursel, Germany
关键词
gene expression; quantitative PCR; reference gene; stability program; Apis mellifera; POLYMERASE-CHAIN-REACTION; DIVISION-OF-LABOR; APIS-MELLIFERA; HOUSEKEEPING GENES; MUSHROOM BODIES; EXPRESSION; VALIDATION; RNA; QUANTIFICATION; BRAIN;
D O I
10.1007/s13592-012-0184-3
中图分类号
Q96 [昆虫学];
学科分类号
摘要
Honey bees are important model organisms for neurobiology, because they display a large array of behaviors. To link behavior with individual gene function, quantitative polymerase chain reaction is frequently used. Comparing gene expression of different individuals requires data normalization using adequate reference genes. These should ideally be expressed stably throughout lifetime. Unfortunately, this is frequently not the case. We studied how well three commonly used reference genes are suited for this purpose and measured gene expression in the brains of honey bees differing in age and social role. Although rpl32 is used most frequently, it only remains stable in expression between newly emerged bees, nurse-aged bees, and pollen foragers but shows a peak at the age of 12 days. The genes gapdh and ef1 alpha-f1, in contrast, are expressed stably in the brain throughout all age groups except newly emerged bees. According to stability software, gapdh was expressed most stably, followed by rpl32 and ef1 alpha-f1.
引用
收藏
页码:342 / 350
页数:9
相关论文
共 50 条
  • [41] Selection of reference genes for quantitative real-time PCR normalization in European quail tissues
    Fabiana Cristina Belchior de Sousa
    Carlos Souza do Nascimento
    Maíse dos Santos Macário
    Renan dos Santos Araújo
    Leandro Teixeira Barbosa
    Geraldo Fábio Viana Bayão
    Katiene Régia Silva Sousa
    Molecular Biology Reports, 2021, 48 : 67 - 76
  • [42] Selection of reliable reference genes for quantitative real-time RT-PCR in alfalfa
    Wang, Xuemin
    Fu, Yuanyuan
    Ban, Liping
    Wang, Zan
    Feng, Guangyan
    Li, Jun
    Gao, Hongwen
    GENES & GENETIC SYSTEMS, 2015, 90 (03) : 175 - 180
  • [43] Screening and validation of reference genes in Dracaena cochinchinensis using quantitative real-time PCR
    Shixi Gao
    Junxiang Peng
    Mei Rong
    Yang Liu
    Yanhong Xu
    Jianhe Wei
    Scientific Reports, 14
  • [44] Selection of Stable Reference Genes for Real-Time Quantitative PCR Analysis in Edwardsiella tarda
    Sun, Zhongyang
    Deng, Jia
    Wu, Haizhen
    Wang, Qiyao
    Zhang, Yuanxing
    JOURNAL OF MICROBIOLOGY AND BIOTECHNOLOGY, 2017, 27 (01) : 112 - 121
  • [45] Selection of stable reference genes for quantitative real-time PCR in porcine gastrointestinal tissues
    Ryan, M. T.
    Collins, C. B.
    O'Doherty, J. V.
    Sweeney, T.
    LIVESTOCK SCIENCE, 2010, 133 (1-3) : 42 - 44
  • [46] Selection of reference genes for quantitative real-time RT-PCR analysis in citrus
    Yan, Jiawen
    Yuan, Feirong
    Long, Guiyou
    Qin, Lei
    Deng, Ziniu
    MOLECULAR BIOLOGY REPORTS, 2012, 39 (02) : 1831 - 1838
  • [47] Screening for Suitable Reference Genes for Quantitative Real-Time PCR in Heterosigma akashiwo (Raphidophyceae)
    Ji, Nanjing
    Li, Ling
    Lin, Lingxiao
    Lin, Senjie
    PLOS ONE, 2015, 10 (07):
  • [48] Screening and validation of reference genes in Dracaena cochinchinensis using quantitative real-time PCR
    Gao, Shixi
    Peng, Junxiang
    Rong, Mei
    Liu, Yang
    Xu, Yanhong
    Wei, Jianhe
    SCIENTIFIC REPORTS, 2024, 14 (01)
  • [49] Validation of Reference Genes for Real-Time Quantitative PCR (qPCR) Analysis of Avibacterium paragallinarum
    Wen, Shuxiang
    Chen, Xiaoling
    Xu, Fuzhou
    Sun, Huiling
    PLOS ONE, 2016, 11 (12):
  • [50] Quantitative real-time PCR based evaluation and validation of reference genes in Gossypium arboreum
    Raghavendra, K. P.
    Kumar, Rakesh
    Das, Joy
    Santosh, H. B.
    More, Sachin A.
    Ramakrishna, N.
    Chawla, Shilpa G.
    Kranthi, Sandhya
    Kranthi, Keshav Raj
    INDIAN JOURNAL OF AGRICULTURAL SCIENCES, 2020, 90 (01): : 40 - 47