Everyone
knows about genes. Genes are information. They meticulously
describe every component that makes up and runs the tiny cells
that make up our bodies. The long path between the single-cell
fertilized egg and the billions of coordinated cells that make
up a human being is basically a sequential story of this
information being read, translated and used to incrementally
reach the next small step. As cells divide, they use this
gene-encoded information to change their structure, function and
interaction. The salient point is that every cell contains the
same genes – it is how, when (and how much) each of the
individual genes is used that makes all the difference. This
process is called gene expression. Theoretically, if we had a
complete and exact understanding of the timing and level of the
expression of every gene during development we would be a long
way towards a real understanding of the overall process.
Until
very recently, obtaining such a complete and exact understanding
was the stuff of science fiction. Determining the expression of
a single gene has been a meticulous process and there are
thousands of genes simultaneously expressed in most cells.
However, recent advances brought about by an unlikely collision
between genetics and “Silicon Valley” high tech have paved
the way for the necessary simultaneous and accurate expression
analysis to become a reality. So called “gene chips”,
developed through the same basic technology used to make
computer chips, are revolutionizing biomedicine and will soon
become standard tools in almost every aspect of medical
diagnostics and practice.
Using
gene expression chips, a single experiment can provide solid
information on the expression of thousands of genes. This
expression profile is essentially a “snapshot” of what is
going on at that time in the cell. While this information is
itself of great interest, the real power of such experiments
emerges when comparisons can be made between different cells,
time points, treatments, and underlying conditions. For
instance, in reproductive biology we would like to know how the
pattern of expressed genes changes as the early embryo divides
and developmental changes are made. Knowing which genes are
critical to normal early developmental processes will be
critical to understanding these processes during assisted
reproductive protocols. Of potentially even greater interest
will be the ability to compare gene expression patterns between
normal “good quality” embryos and those manifesting
developmental problems. These comparisons will no doubt reveal
genes that are either directly involved in abnormal development
or genes that are markers of such development. Such marker genes
could potentially be used in diagnostic scenarios to identify
embryos with normal or abnormal development. Such expression
analysis could also potentially identify embryos that harbor
genetic disease mutations or other abnormalities.
