Research activities which draw heavily on the Bioinformatics resources :

• Study of the proteome in the blast fungus was initiated using high resolution 2D gels and the imaging software for identification of protein differences. In addition to optimizing the methods for proteome analysis in this fungus, several proteins crucial to the establishment of the fungus on susceptible host have also been identified.

• The glucose oxidase (GOX) generated H₂O₂ induced/repressed proteins were identified in the Oryza sativa L. database by sequence similarity searches in BLASTP program. Protein domain analysis was performed using SMART (Shultz, J et al., 1998) program to identify the conserved domains in these proteins. Also, influence of GOX generated H₂O₂ on various agronomic traits in the transgenic rice was calculated by using ANOVA of Prism 3.0 version package.

• Using RasMOL Molecular graphics program, visualization of proteins were done. We have created a resistance gene (R) family database and identified the conserved domains in the resistance genes by performing multiple sequence alignment using CLUSTALW program. Modelling of Avr CO39 protein is under way to identify the interacting protein domains in the gene products of resistance genes and avirulence gene.

• Linkage analysis of blast resistance genes and molecular markers (AFLP and SSLP) were done using Mapmaker program version 3.0 (Lander et.al., 1987).

• Pot2 fingerprints of Magnaporthe grisea and % DLA obtained on RILs were analysed to perform cluster analysis using UPGMA and SAHN programs of NTSYS-pc package. Correlation analysis by the MXCOMP program was done for pair of similarity matrices to compare the relationships within and among the M. grisea populations. Principal coordinate analysis was performed on the basis of dice similarities with the procedure DCENTRE of NTSYS-pc. Based on the analyses of the combined infection category (% DLA) and Pot2 fingerprint profiles, different genetic lineages of M. grisea were obtained. POPGENE and STATISTICA packages were used to calculated genetic diversity, genetic distance, different, and gene flow etc., using Pot2 fingerprints M. grisea isolates.

• STATGRAPHICS package was used to optimize the growth conditions of yeast and bacteria for efficient production of enzymes/metabolites.

• In order to study the microbial diversity in the Jute retting environment, PCR amplification and sequencing of 16S rDNA from the DNA isolated from water used in retting was done. Sequence similarity analysis was done by BLAST search in RDB (Ribosome Database Bank) to identify the organisms present in jute retting environment.

• Similarly, 16S rDNA analysis was done to identify the soil microflora in the pesticide treated soils.