Wednesday, June 13, 2007

Proteomics and Genomics


The dream of having the complete genome sequence is now a reality. The complete sequence of several genomes including the human one is known. However, the understanding of probably half a million human proteins encoded by some 80,000 genes is still a long way away and the hard work to unravel the complexity of biological systems is yet to come.
A new fundamental concept called proteome (Protein Complement to a genome) has recently emerged that should drastically help phonemics to unravel biochemical and physiological mechanisms of complex multivariate diseases at the functional molecular level. A new discipline, proteomics, has been initiated that complements physical genomic research. Proteomics can be defined as the qualitative and quantitative comparison of proteomes under different conditions to further unravel biological processes.

In a border sense proteomics is defined as the analysis of complete complements of proteins. Proteomics include not only the identification and quantification of proteins, but also the determination of their localization, modifications, interactions, activities, and, ultimately, their function. Initially encompassing just two-dimensional (2D) gel electrophoresis for protein separation and identification, proteomics now refers to any procedure that characterizes large sets of proteins. The explosive growth of this field is driven by multiple forces – genomics and its revelation of more and more new proteins; powerful protein technologies, such as newly developed mass-spectrometry approaches, global [yeast] two-hybrid techniques, and spin-offs from DNA arrays, and innovative computational tools and methods to process, analyze, and interpret prodigious amounts of data.

Types: As compared with genomics, proteomics is not differentiated completely. Presently only two divisions are prominent i.e., functional and comparative proteomics.

Functional proteomics: Relating function to gene expression and protein-protein interactions is yielding large database of interacting proteins. Extensive pathway maps of these interactions are being scored and deciphered by novel high throughput technologies. However, traditional methods of screening have not been very successful in identifying protein-protein interaction inhibitors. The proteomic pipeline is under way to reveal and identify and understand biological mechanisms that exist between proteins, protein folding and how protein structure relates to function. This explosion in genomic and proteomic data, the exponential increase of Known protein structures should make it easier to develop highly specific, safer and more effective pharmaceuticals.

Comparative proteomics: It is comparing proteome of two different organisms for the functional and structural studies. For Example the C. elegans proteome was used as an alignment template to assist in novel human gene identification. Among the available 18,452 C. elegans protein sequences, results indicate that at least 83% had human homologous genes, with 7954 records of C. elegans proteins matching known human gene transcripts.



Genomics is operationally defined as investigations in to the structure and function of very large number of genes undertaken in to the structure and function of very large number o genes undertaken in a simultaneous fashion. Genomics has its origin in the US Government sponsored Human Genome Project Project (HGP). Initiated in the mid – 1980s, its initial intent was to map, sequence, and characterize all human chromosomes in order to facilitate more effective discovery of genes. Genomics encompasses various technologies used to discover and charcterize genes, with a view to identify those that cause or predispose to diseases. It includes new approaches to the understanding of gene expression, gene function and the selection and validation of genes leading to the design of efficacious and specific drug. Geonomics tools also find applications in the discovery of better ways to fight infectious diseases. Recent advances in genomics are bringing about a revolution in our understanding of the molecular mechanisms of disease, including the complex interplay of genetic and environmental factors. Geonomics is also stimulating the discovery of breakthrough healthcare products by revelaing thousands of new biological targets for the development of drugs, and by giving scientists innovative way to design new drugs, vaccines and DNA diagnostics. Genomics based therapaeutics includes “traditional”small chemical drug, protein drugs, and potentially gene therapy.

Types: Geonmics is broadly classified into functional, structural and comparitive genomics and subdivided into biochemical genomics, physiological genomics, evolutionary genomics and phylogenomics.

Functional genomics: functional genomics aims to discover the biological function of particular genes and to uncover how sets of genes and their products work together in health and disease. In its broadest definition, functional genomics encompasses many traditional molecular genetic and other biological approaches.

Structural geonomics: Involves quick determination of 3D structures of large numbers of proteins ( or other complex biological molecules, such as nucleic acids), ultimately accounting for an organism’s entire proteome. As traditionally defined, the term structural geonomics is referred to the use of sequencing and mapping technologies, with the support of bioinformatics to develop complete genome maps (genetic, physical, and transcript maps) and to elucidate geonomics sequences of different organisms, particularly humans. Now, however, the term is increasingly used to refer to high-throughput methods for determining protein structures.

Comparative geonomics: Comparative studies of whole genomes help researchers understand what parts of the genome in one organism are similar to those in another, how the overall structure of genes and genomes have evolved, and how to interfere with these events in the model organism or humans. Comparative genomics is also a critical enabling field for functional genomics, because it gives researchers an indication of which model organism is most appropriate for a particular study.

Biochemical genomics: Biochemical genomics approaches to identify genes by the activities of their products with respect of their involvement in metabolism.

Evolutionary genomics: Looking at how genes have been preserved through evolution, or how genes or their functions have diverged.

Phylogenomics: The study of the evolution of genes and gene families using DNA sequence information from organisms selected at major branch points along the phylogenetic continuum.

Physiological genomics: Indicates that it covers “ a wide variety of studies from human and from informative model systems with techniques linking genes and pathways to physiology, from prokaryotes to eukaryotes.

Database, techniques and software used

  • Data bases
  • Genome sequence at Entrez genome and TIGR databases.
  • Analysis Techniques
    • Basecalling: to convert fluorscene intensities from the sequencing experiment into four-letter sequence code.
    • Genome mapping and assembly: to organize the sequences of short fragments of raw DNA sequence data into a cohrent whole.
    • Genome annotation: to connect functional information about the genome to specific sequence location.
    • Genome comparison: to identify components of genome structure that differentiate one organism from another.
    • Micro array image analysis : to identify and quantitative spots in raw micro array data.
    • Clustering analysis of micro array data: to identify genes that appear to be expressed as linked groups.

  • Tools/software
  • Basecalling: Phred
  • Genome mapping and assembly: Phrad, Staden package
  • Genome annotation: MAGPIE
  • Genome comparison: PipMaker, MUMmer.
  • Microarray images analysis: CrazyQuant, Spsotfinder, Array View.

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