Genome data mining approach to identify potential protein in crop plants.

There is a need to produce more crop plants to meet the future global demand. However, the climate change has affected the global crop yield. Consequently, finding an alternative approach to improve crop yield becomes essential. The development of sequencing techniques, as well as information technologies, have enabled us to perform genome data mining. Using genome data mining approach, it is possible to identify or discover a protein which has a particular characteristic. This study aims to identify a protein, which could potentially improve crop yield, using genome data mining approach. D1 protein was used as the target, as this protein is highly involved in photosynthesis. Then, protein sequences of various crop plants were collected from biological database. After conducting data trimming and filtering, sequence analysis was performed. The analysis was used to construct phylogenetic tree and create a 3D protein model. Sequence analysis displayed variation in amino acid sequence in D1 protein. Protein modelling located the variations, which scattered within D1 protein. Furthermore, we highlighted the amino acid residues that are the targets for genetic engineering. The research findings may provide a reference to improve crop production through genome mining approach. [ABSTRACT FROM AUTHOR]