The Human Genome Project was of enormous importance—it gave us a vast amount of genetic information, with the sequence of the three billion base pairs of the human genome now determined.
However, with that project completed, the real work of understanding the human genome has only just begun. It’s not enough to be able to read the genome—there are around thirty thousand genes, more than fifty percent of which are of unknown function, and massive stretches of non-coding DNA, on the human genome, and a great deal more knowledge is there waiting to be uncovered.
The science of functional genomics
is one way in which we can begin to understand the mysteries of the human genome. Functional genomics investigates the function and activity of specific genes, as well as genes in general.
For example, functional genomics might involve the study of a specific gene—the protein it codes for, how its function is regulated, and what factors cause it to be expressed. On the other hand, discovering more general information about genes might be a goal, to learn more about processes such as gene regulation, transcription, translation, and interactions between DNA and proteins.
In general, functional genomics is a field of genetic research which involves dynamic information about the genome (rather than determining, for example, the DNA sequence of a gene, or how the protein it codes for is structured).
Often, this means looking at what happens when genetic processes go wrong—what, for example, are the consequences of a single nucleotide polymorphism? Interestingly enough, the answer to this question can vary depending on the gene involved, the protein coded for, the location of the polymorphism in the gene, the function of the protein, and many other factors.
To study functional genomics, high-throughput techniques such as DNA microarrays (often used to detect polymorphisms or measure changes in DNA expression levels) and SAGE (serial analysis of gene expression—a technique which produces a ‘snapshot’ of all the mRNA in a sample) are often used for characterizing mRNA. For proteins, gel electrophoresis and mass spectrometry are two often-used techniques.
Another important approach in functional genomics
is the use of knockout mouse models. These are strains of mice in which a particular gene of interest has been “knocked out” so that the mouse does not express the protein coded for by the gene. Doing this allows researchers to determine the function of the gene which has been removed.