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The following points highlight the three main omic technologies in plant biotechnology. The technologies are: 1. Transcriptomics 2. Metabolomics 3. Phenomics.
Technology # 1. Transcriptomics:
Utility of microarray and sequence-based process to expression profiling fueled additional approach to current genomic data within bioinformatics. Microarray technology helps in gene expression analysis in many plant species. Sequence based methods have real potential to determine quantitative levels of gene expression.
The most commonly used method for sequence- based expression analysis is serial analysis of gene expression (SAGE) and massive parallel signature sequencing (MPSS). Only SAGE has been adopted for plant genomes. But signature of MPSS for annotation genomes with expressed genes is likely to extend MPSS technique for crop species.
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Hybridization based microarray, due to their simultaneous analysis of sample, are ideal tool for transcriptome studies. There are many software tools for analysing microarray data. Recently, in microarray technology a complete oligonucleotide based unique arrays are being developed for the major plant species.
Technology # 2. Metabolomics:
It involves analysis of small molecule metabolites and polymers such as starch. Metabolomics is based on description of pathways and correct its database. Some of the metabolomics database such as Kyoto Encyclopedia of Genes and Genomes are frequently used on well-characterized biochemical pathways.
Bioinformatics of metabolomics involves identification and characterization of a broad range of metabolites. The metabolism has several direct applications in plant biotechnology. Particularly mutation in the pathways. Metabolomics play a significant role like guaging direct phenotype, Measuring Quantitative and Qualitative traits such as starches in cereal grains or oils in oil seeds.
Technology # 3. Phenomics:
In continuation of exploration of genomics several omic technologies has been added up for new field for example, phenomics, high throughput analysis of phenotype, has probably biggest exploration in plant biotechnology. Besides greater degree of plasticity led to genetic variation provides opportunities for crop improvement.
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The field of phenomic developed from phenotype characterization of mutant plant and storage of these data in scorable database. With the application of phenomics to high throughput analysis, plant development and natural variation creates a link in the chain from the genetics of crop development to crop production.
