Matematicheskaya Biologiya i Bioinformatika
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive
Impact factor

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS



Mat. Biolog. Bioinform.:
Year:
Volume:
Issue:
Page:
Find






Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register


Matematicheskaya Biologiya i Bioinformatika, 2024, Volume 19, Issue 1, Pages 155–168
DOI: https://doi.org/10.17537/2024.19.155
(Mi mbb552)
 

Bioinformatics

A bioinformatics analysis for unveiling novel long noncoding RNAs and their regulatory impact on key genes associated with vitiligo

Safa Sadeq Fayeza, Ahmed AbdulJabbar Suleimanb

a College of Medicine, University of Anbar, Ramadi, Anbar, Iraq
b Biotechnology Department, College of Science, University of Anbar, Ramadi, Anbar, Iraq
Abstract: Vitiligo involves the gradual disappearance of melanocytes, causing skin depigmentation. Long noncoding RNAs (lncRNAs), a type of noncoding RNA, are important for regulating inflammation and immunity. Despite this significance, there needs to be more published research on how lncRNAs are expressed in vitiligo cases and their potential roles in the biology of this skin condition. This study aims to elucidate the molecular landscape of vitiligo by analyzing gene expression profiles of vitiligo skin and normal skin. Two datasets, RNA-seq and microarray, were thoroughly investigated to identify differentially expressed (DE) genes and lncRNAs associated with vitiligo development. Functional enrichment analysis revealed biological processes and pathways influenced by dysregulated genes, highlighting intricate processes such as melanin biosynthesis and melanogenesis, shedding light on the complex regulatory networks involved in pigmentation and immune responses. Protein-protein interaction analysis highlighted significantly downregulated hub genes, including TYRP1, MLANA, MC1R, SLC45A2, PAX3, TYR, DCT, OCA2, PMEL, and SOX10, revealing significant functional relationships among identified hub genes within the network. RNA-seq data analysis uncovered DE-lncRNAs, emphasizing the regulatory role of lncRNAs in vitiligo. Moreover, the correlation analysis between the expression of lncRNAs and key genes associated with melanogenesis (OCA2, TYRP1, and PMEL) unveiled novel upregulated lncRNAs such as CRTC3-AS1, LCMT1-AS1, LINC02178 contributing to vitiligo development. Additionally, lncRNA-gene networks constructed based on key melanocyte-related genes provided insights into the molecular relationships relevant to vitiligo. Overall, this study offers a comprehensive understanding of vitiligo pathogenesis, identifying potential therapeutic targets and laying the foundation for future research in this critical area.
Key words: vitiligo, sirtuin 1 gene, DE-lncRNAs, DEGs, DNA-seq and microarray data.
Received 23.02.2024, 13.04.2024, Published 01.05.2024
Bibliographic databases:
Document Type: Article
Language: English
Citation: Safa Sadeq Fayez, Ahmed AbdulJabbar Suleiman, “A bioinformatics analysis for unveiling novel long noncoding RNAs and their regulatory impact on key genes associated with vitiligo”, Mat. Biolog. Bioinform., 19:1 (2024), 155–168
Citation in format AMSBIB
\Bibitem{FaySul24}
\by Safa~Sadeq~Fayez, Ahmed~AbdulJabbar~Suleiman
\paper A bioinformatics analysis for unveiling novel long noncoding RNAs and their regulatory impact on key genes associated with vitiligo
\jour Mat. Biolog. Bioinform.
\yr 2024
\vol 19
\issue 1
\pages 155--168
\mathnet{http://mi.mathnet.ru/mbb552}
\crossref{https://doi.org/10.17537/2024.19.155}
\elib{https://elibrary.ru/item.asp?id=68485691}
Linking options:
  • https://www.mathnet.ru/eng/mbb552
  • https://www.mathnet.ru/eng/mbb/v19/i1/p155
  • Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
     
      Contact us:
     Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2025