Plant breeding and genetic engineering have made significant contributions in improving crops and thus addressing the problem of food security over the last few decades. However, due to continuously growing population, increasing urbanization, environmental pollution, land degradation, and global climate change, food security is still a major concern worldwide. More attention needs to be paid to sustainable crop production for ensuring enough food for current and future generations. Emergences of genomic technologies holds promise for improving crop productivity and provide solutions to the food shortage. Recent advances in high throughput technologies have led to generation of a tremendous amount of genomics data from plants that can be put to a variety of uses. Computational tools are essential to analyze this complex data generated from sequencing of genomes, determine complete set of genes, analyze transcripts and proteins encoded by an organism, and understand their interactions that bring out changes in phenotypes.
TopIntroduction
Bioinformatics is an interdisciplinary field involving Microarray, Genomics, Proteomics, Protein modeling Bio Grid computing, Molecular biology, system biology, protein ligand docking and structure prediction of macromolecule (Fig-1). Bioinformatics overlaps other areas of research that are designated informatics and computational biology. Informatics has traditionally been a discipline in which mathematicians, computer scientists, statisticians, and engineers develop technologies for supporting information management in fields like health care. Bioinformatics is now involved in these activities by organizing biological data related to genomes with a view to applying this information in agriculture, pharmacology, and other commercial applications.
Figure 1.
Role of bioinformatics in various field
In recent years sustainable agriculture has assumed a great significance in face of ever-increasing human population, global climate change and environmental problems (Brown and Funk 2008, Turner et al. 2009), newly emerging insect pests, abiotic stress resulting in poor yields etc. It aims at meeting the needs of present generation without eroding the natural resource base of the future generations. Modern agriculture is based on use of synthetic fertilizer and chemical pesticides and has caused enormous damage to land and water bodies. In addition effluents of industries constantly degrade arable land and pollute water bodies. There is loss of biological diversity and erosion of germplasm resources due to monoculture. Genetically modified crops too promote large scale monoculture at expense of diversity. The conventional plant breeding practices may not able to ensure the sustainable production of crop plants under such circumstances. To resolve these problems there is urgent need to breed plants on the basis of better molecular understanding of gene function and regulation of gene expression responsible for increase in crop yield and stress tolerance. Advent of genomic era in plant biotechnology have lead to identification of the genes related to crop yields, crop nutritional quality, and tolerance to biotic and abiotic stresses. Recent advances made in the area of crop genomics and bioinformatics offer substantial opportunities for enhancing the effectiveness of classical plant breeding programs. Bioinformatic information and web sites have become important for crop scientists in gene data mining, and linking this knowledge to its biological significance (Mochida and Shinozaki 2010).
Genomic revolution is providing insights into genes and regulatory networks of complex agronomic traits. Genomics refers to mapping, sequencing and analysis of genome and function of the genome. Structural genomics represent the initial phase of genome analysis and leads to the construction of high resolution genetic, physical and transcript maps of an organism. The ultimate physical map of an organism is its complete sequence. Structural genomics includes the different techniques and analytical tools such as Linkage analysis, Molecular cytogenetics, physical mapping, EST sequencing etc.
Functional genomics refers to the development and application of genome system wide experimental approaches to assess gene function by making use of the information and reagents provided by structural genomics. It is characterized by high throughput experimental methodologies combined with statistical and computational analysis of the results.
Proteomics is the study of proteomes. Proteome refers to all proteins produced by a species and it varies with time. Proteomics is a rapidly evolving field and there has been a very fast development in proteomics technologies like mass spectrometry for rapid and quantitative measurements of proteins in a complex mixture. Proteomics has led to the development of protein sequence databases and has immense application in healthcare, drug reaseach and diagnostics.
Microarrays are the transcriptional profiles of most genes within a genome can be analyzed using microarrays and quantitative analysis of microarray data. Transcriptional profile can help to generate gene expression data that can be used to define a cell type or condition. There is a huge amount of data produced in any microarray experiment and hence computational methods are essential to conduct this analysis.