Comparative Genomics Analysis of Growth Hormone (GH), Insulin-Like Growth Factor 1 (IGF-1) and Myostatin (MSTN) Gene Sequences in Chicken, Rabbit and Sheep.
ABSTRACT
The gene sequences of Growth hormone (GH), Insulin-like Growth Factor 1 (IGF-1) and Myostatin (MSTN) were downloaded from National Center for Biotechnology Information (NCBI) database,
through Entrez of the database as non-redundant reference sequence in FASTA format, using respective accession numbers of the various genes in the GenBank to access the necessary gene information.
They were subjected to different computational tools, on-line softwares and programs; for Multiple sequence alignment, phylogenetic tree, BLAST-like alignment tool (BLAT),
Basic Like Alignment Search Tool (BLAST)were used to analyzed for gene number in a genome, exon type and number per gene, number of codons per gene; gaps within the alignment of the three species for each gene;
Single nucleotide polymorphism between the alignments of chicken by rabbit, chicken by sheep, and rabbit by sheep; the conserved regions between the alignments of chicken by rabbit,
chicken by sheep, rabbit by sheep, and chicken by rabbit by sheep and other parameters by submitting the genes respective sequences in FASTA format to the tool.
It is concluded that; the number of GH gene of sheep is higher than that of GH of chicken, than GH of rabbit but the number IGF-1 gene of rabbit and sheep are higher than that of chicken IGF-1 gene, while the number of rabbit myostatin is higher than that of chicken and sheep Myostatin.
The number of genes in chicken, rabbit and sheep genomes plays a key role in establishing effective gene function. The genes shares some conserved regions but the length/size, gene number, exon number, exon type, number of gene/genome, gene DNA strand, codons/gene, gaps, SNP varied greatly among chicken, rabbit and sheep species.
1.0 INTRODUCTION
Bioinformatics is the science of storing, extracting, organizing, analyzing, interpreting and utilizing information from biological sequences and molecules (Khalid, 2010).
Bioinformatics is often defined as the application of computational techniques to understand and organize the information associated with biological macro-molecules (Luscombe et al., 2001).
It has been mainly fueled by advances in DNA sequencing and mapping techniques (Khalid, 2010). Over the past few decades, rapid developments in genomic, other molecular research technologies and information technologies have combined to produce a tremendous amount of information related to molecular biology.
The primary goal of bioinformatics is to increase the understanding of biological processes (Khalid, 2010).As biology is increasingly becoming a technology-driven science,
databases have become indispensable to store not only data, but also the results of experiments generated by different research projects around the world (Hey et al., 2009).
A biological database is a collection of information, or data from a biological system, stored in a computer readable format.
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