An insilico approach to discover SNP’ in Oryza sativa (Japonica cultivator group).
Rushket M.J. ,Krushnasingh R.R. ,Sachin R.A.
Yeshwant College of Bioinformatics and Biotechnology,Parbhani.431401
Swami Ramanand Teerth Marathwada University Nanded, Maharashtra
Single Nucleotide Polymorphism (SNP) is a DNA sequence variation at a single nucleotide level. It is estimated that SNPs occur once per 100~300 bases in the genome. The dramatic increase in genotyping efficiency in the last couple of years has made large-scale high density genome-wide SNP association analysis practical for many research groups. Genotype
data have much more complex and indirect relationships with genes and proteins. Most SNPs are not even in the coding sequences of genes. They may influence biological processes in many conceivable ways that is reduce transcription factor binding affinity to the promoter region, alter a microRNA binding site, change mRNA stability, modify the RNA splicing pattern, destroy an internal ribosomal binding site and many more.
Given the complexity of the way that a SNP allele may influence the function of a protein, it is highly desirable to have a comprehensive database where researchers can easily access the most up-to date SNP functional annotations.
Single nucleotide polymorphism is a small genetic change or variation that can occur within a DNA sequence. Single nucleotide polymorphisms distribute numerously and high-density throughout rice (Oryza sativa L.) genome. A total of 80,127 SNP sites were identified in rice genome, and one SNP every 154 bp was found between two rice subspecies japonica and indica The SNP rate is 0. 65%. SNPs are very considerable among within the subspecies cultivars, even it can be found between closely related cultivars, in which it has been difficult to find polymorphic sites by conventional methods. The frequency of SNPs in rice genome varied between chromosomes, it means-number of SNP’ occurrence in some chromosome is very few while in other chromosomes of it is larger extent, in other words we can say, it showed uneven distribution of polymorphism-rich(more in number) and -poor regions(few in number) along each chromosome. Several routes have been used for identification of SNP in rice, such as sequencing PCR products of DNA samples, screening SNP’ in SSR fragments, and searching for SNP’ through the rice genome sequences and EST database. A number of genotyping systems have been developed to identify SNPs in rice genome.
According to wet lab observations the data provided is insufficient and not completely helpful to user and hence in order to overcome to this problem in this project we people, attempt to provide an adequate information with the help of Bioinformatics and also providing overall information related to SNP and its applications, thus our in silico
work will not be only to approved the mistakes of Wet-lab studies but also providing other related information about SNP’.