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  • Journal of Agricultural Production
  • Volume:1 Issue:1
  • Phylogeny, Characterisation and Identification of Creatine Kinase Genes (ckma and ckmb) in Zebrafish...

Phylogeny, Characterisation and Identification of Creatine Kinase Genes (ckma and ckmb) in Zebrafish (Danio rerio)

Authors : Gökhan ARSLAN, Erdal ÖZDEMİR, Mehtap BAYIR
Pages : 12-21
View : 19 | Download : 12
Publication Date : 2020-12-31
Article Type : Research Paper
Abstract :Creatine kinase genes insert ignore into journalissuearticles values(ckma and ckmb); in zebrafish insert ignore into journalissuearticles values(Danio rerio);, an aquatic model organism, have been characterized and identified. However, the gene structure is designed using exons, introns, amino acids produced by the exons. TATA boxex, poly A tails and 5` UTR and 3` UTR regions of zebrafish ckma and ckma genes are showed at the gene structure. In addition, chromosomal regions of ckma and ckmb genes were determined. The other genes which are placed in the same region with ckma and ckmb genes were found in medaka and human which are the orthologs of zebrafish, and conserved gene syntheny was designed manually according to these regions. In addition, phylogenetic relationship was determined between zebrafish and it’s some orthologs using ckma and ckmb gene sequences. Genetic affinity between zebrafish and its orthologs was calculated as similarity-identity % rate and given as a table. For all these studies, bioinformatics databases insert ignore into journalissuearticles values(NCBI database, Ensembl genomic database, Expasy, Reverse Complementary); and programs insert ignore into journalissuearticles values(MEGA6 program, BLOSUM62 matrix program and BioEdit software); were used. In this study, characterization and identification of ckma and ckmb genes in zebrafish insert ignore into journalissuearticles values(D. rerio); was completed using bioinformatics tools and some data to be used in the future studies on molecular stress response were presented.
Keywords : Danio rerio, Genomic organisation, Model organism, Bioinformatics

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