Project titles for:
Project titles for: 2007-09
- Comparison of software for Analysis of Molecular Marker Data
- In silico Prediction of miRNA in Rice Genome
- Web Tools for Bioinformatics
- In silico Structure Prediction of enzyme Arsenite methyltransferase
- Comparison of various software for QTL Analysis
- QSAR studies of Tuberculosis Inhibitors
- Determination of common transcription factor binding site in promoter region of abiotic stress resistance gene in rice
- SNP Mining in Rice Genome
- Protein Modelling of Betaine Aldehyde Dehydrogenase-2 in Rice
- Data Mining of Chemical Substructures for Biological Efficacy
- Plant Disease Database mined from PubMed
- Comparison of Protein Structure Prediction Methods
- Virtual High Throughput Screening for Influenza Virus Inhibitors
- Combinatorial Libraries for Screening against Tuberculosis Inhibitors
Single nucleotide polymorphisms (SNPs) may be considered the ultimate genetic marker as they represent the finest resolution of a DNA sequence (a single nucleotide), are generally abundant in populations and have a low mutation rate. Single nucleotide polymorphisms (SNPs) are important tools in studying complex genetic traits and genome evolution. SNP mining can be done by experimental and computational methods. Computational strategies for SNP discovery make use of the large number of sequences present in public databases (in most cases as expressed sequence tags (ESTs)) and are considered to be faster and more cost-effective than experimental procedures. A major challenge in computational SNP discovery is distinguishing allelic variation from sequence variation between paralogous sequences, in addition to recognizing sequencing errors. For the majority of the public EST sequences, trace or quality files are lacking which makes detection of reliable SNPs even more difficult because it has to rely on sequence comparisons only. In the current project online SNP and allele detection tool HaploSNPer which is based on QualitySNP pipeline is used. HaploSNPer is an efficient tool for SNP detection, storage and retrieval in diploid as well as polyploid species and quality files are not needed. In the present project of SNP mining, Oryza sativa ssp indica genome sequence data was taken from Gramene Database .A Perl script was written to cut the large sequence of chromosome into small parts of 1 lakh bp. Genome sequence data of oryza sativa ssp indica was given as input in online SNP and allele detection tool haploSNPer. As a result 203,279 potential SNPs and 88089 reliable SNPs were detected in oryza sativa ssp indica and japonica. In the 203,279 potential SNPs detected transitions, transversions and indels were 67660, 91904 and 43165 respectively. In the 880, 89 reliable SNPs detected transitions, transversions and indels were.37345, 34507, and 16237 respectively.