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دانلود کتابچه

    Investigation of microRNAs associated with the sickle cell disease

  • negar zamani alavijeh,1 pegah javid,2 Mansoureh Azadeh,3,*
    1. Zist Fanavari Novin Biotechnology Department, Provincial Technical and vocational Training
    2. Zist Fanavari Novin Biotechnology Department, Provincial Technical and vocational Training Organization
    3. Zist Fanavari Novin Biotechnology Department, Provincial Technical and vocational Training Organization


  • Introduction: Sickle cell is one of the most common genetic and hematological disorders in the world. This disease gradually causes problems for brain, kidneys, bones, vascular system and lungs. Recent studies have indicated that accelerating the detection and investigation of disease interveners may change the pathway of disease.
  • Methods: The analysis on expression of genes involved in sickle cell disease was examined on GSE11524 through the GEO2R package in the GEO dataset. The most differentially expressed genes were analyzed in DAVID database in order to identify the most effective gene in incidence of sickle cell disease. Additionally, the microRNAs associated with this gene were identified using miRWalk database. The Human microRNA Disease Database (HMDD) helped to identify the microRNAs affecting the sickle cell disease.
  • Results: The analyses showed that the most effective gene in sickle cell disease is hemoglobin subunit beta (HBB) gene. Regarding the fact in the miRWalk database, hsa-mir-34a-5p and hsa-mir-34a-3p were identified as HBB-related microRNAs. Furthermore, by using of HMDD database it was found that has-mir-34a is a potential microRNA in the process of sickle cell disorder through downregulation of gene, which caused by miRNA.
  • Conclusion: Knowing the factors influencing the expression of the target gene may be able to change the pathway of the disease and recognizing the involved microRNAs as markers may help us to control diseases. More studies that are detailed are needed to be done on the role of microRNAs related to HBB gene.
  • Keywords: Genetic disorder, non-coding RNA, Bioinformatics, Databases