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Differential Display Techniques 217
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Differential Display
A Technical Overview
John M. S. Bartlett
1. Introduction
Since the completion of the human genome-sequencing project, scientists are now
able to read the code of all human genes stored on the 46 chromosomes of the human
genetic library. However, we are far from reaching an understanding of the functional
relationships existing between more than a tiny fraction of these genes. The value of
the human genome-sequencing project, beyond the simple collation of data, has been
to teach us that it is possible to take a highly intensive analytical approach to the study
of human systems in health and disease (1–4).
The aim of our research has now shifted from the study of individual genes, isolated
from the cellular environment in which they play their roles, to the investigation of the
hugely complex interactions between gene and gene families. We are shifting from
the observation of individual trees to an evaluation of the wood itself. To accomplish this,
novel techniques have emerged that simultaneously allow the analysis of entire
pathways or indeed entire cellular transcription patterns. The challenge this provides is
both a molecular and mathematical one. Experiments now yield vast amounts of data
that must be sifted through to formulate novel hypotheses. Conversely, we are now
able to see how whole families of genes are regulated and interact rather than having to
slowly piece together information often from quite different experimental approaches.
The continuing development of biomathematical modeling systems (5–9) is essential
to this approach.
Over the next decade, scientists face the challenge of transforming the knowledge
gained of the human genome sequence into a practical and functional understanding
of complex biological systems in health and disease. It is clear that analysis of gene
expression represents a highly significant pointer to the altered function of transcripts
identified by the human genome project whose function is largely unknown. The ability
to select candidate genes from expression libraries from different tissues and disease
states (and stages) for rapid investigation represents the single most important driver
behind the current explosion in expression library analysis. It is therefore critical
that we understand both the potentials and limitations of technologies available for
expression analysis of entire transcriptomes.
From: Methods in Molecular Biology, Vol. 226: PCR Protocols, Second Edition
Edited by: J. M. S. Bartlett and D. Stirling © Humana Press Inc., Totowa, NJ
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