African Journal of
Biotechnology

  • Abbreviation: Afr. J. Biotechnol.
  • Language: English
  • ISSN: 1684-5315
  • DOI: 10.5897/AJB
  • Start Year: 2002
  • Published Articles: 12487

Full Length Research Paper

Bioinformatics and phylogenetic analysis of human Tp73 gene

  Naureen Aslam Khattak1, Arslan Sehgal2 and Asif Mir2*  
  1Department of Biochemistry, PMAS-Arid University, Rawalpindi 2Bioinformatics and Biotechnology, DES, FBAS International Islamic University, Islamabad, Pakistan.
Email: [email protected]

  •  Accepted: 26 April 2013
  •  Published: 26 June 2013

Abstract

 

The Tp73 gene encoding p73 protein belongs to the Tp53 gene family and it functions in the initiation of cell-cycle arrest or apoptosis and also involves in regulating a series of pathways including breast cancer, neuroblastoma and cholorectal cancer. New discoveries about the control and function of p73 are still in progress and it is hoped to develop better diagnostics and therapeutics by exploiting this system. Evolutionary studies are of principal importance in the field of biological research since for a very long time as provided the basis for comparative genomics. The sequence of Homo sapiens Tp73, transcript variant-7 mRNA sequence was retrieved from the NCBI in FASTA format and was studied for its relationships and percent similarity within human and others species. Genetic variation among Tp73 found in human beings and other organisms were studied in detail. Phylogenetic analysis and multiple sequence alignment of the human Tp73, transcript variant-7 mRNA sequence through unweighted pair group method with arithmetic mean (UPGMA) was performed which showed its pattern of variations and relationship among different organisms especially with rat, mouse and chimpanzee. This current study will help in modern research strategies through the manipulation and exploitation of p73, as its pathways are promising and one can predict its extensive clinical and biological  use in the near future for the human benefit worldwide.

 

Key words: Tp73, Bioinformatics, phylogenetics analysis, cancer, Tp53.