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Seasonal Stability Assessment of Reference Genes for Quantitative Real-Time Polymerase Chain Reaction Normalization in Bombus terrestris .

Kathannan SankarKyeong-Yong LeeKyu-Won KwakSu-Jin LeeYoung-Bo Lee
Published in: Current issues in molecular biology (2024)
Bumblebees ( B. terrestris ) play a crucial role as highly efficient biological agents in commercial pollination. Understanding the molecular mechanisms governing their adaptation to diverse seasonal environments may pave the way for effective management strategies in the future. With the burgeoning advancement in post-genetic studies focusing on B. terrestris , there is a critical need to normalize quantitative real-time PCR (qRT-PCR) data using suitable reference genes. To address this necessity, we employed RefFinder, a software-based tool, to assess the suitability of several candidate endogenous control genes, including actin ( ACT ), arginine kinase ( AK ), elongation factor 1 alpha ( EF1 ), glyceraldehyde-3-phosphate ( GAPDH ), phospholipase ( PLA2 ), and ribosomal proteins ( S18 , S28 ). These genes were evaluated for their efficacy as biological endogenous controls by examining their expression patterns across various environmental conditions corresponding to different seasons (Spring, Summer, Autumn, Winter) and tissues (ovary, fat body, thorax, head) in bumblebees. Moreover, the study investigated the significance of selecting appropriate reference genes for three key genes involved in the juvenile hormone (JH) signaling pathways: Krüppel homolog 1 ( Kr-h1 ), methyl farnesoate epoxidase ( MFE ), and Vitellogenin ( Vg ). Our research identifies specific genes suitable for normalization in B. terrestris , thereby offering valuable insights into gene expression and functional metabolic genetics under varying seasonal conditions. This catalog of reference genes will serve as a valuable resource for future research endeavors.
Keyphrases
  • genome wide
  • gene expression
  • bioinformatics analysis
  • dna methylation
  • genome wide identification
  • adipose tissue
  • high resolution
  • real time pcr
  • genome wide analysis
  • oxidative stress
  • big data
  • heat stress