February 06, 2004
Researchers Adapt RNA Interference to Study Gene Function on a Large Scale
A method for determining the function of large numbers of genes is
being developed and piloted by Howard Hughes Medical Institute (HHMI)
researchers at Harvard Medical School. In a trial of the technique, the
researchers characterized the role in growth and viability of nearly
all the genes in the genome of the fruit fly Drosophila.
Although the fruit fly genome was chosen for the first study, the
researchers are confident that their technique can be applied to any
organism, including humans. “A major challenge now that many
genome sequences have been determined, is to extract meaningful
functional information from those projects,” said HHMI researcher
Norbert
Perrimon, who directed the study. “While there are a number
of analytical approaches that can measure the level of gene expression
or the interaction between proteins, ours is really the first
high-throughput, full-genome screening method that allows a systematic
interrogation of the function of every gene.”
“Ours is really the first high-throughput, full-genome screening method that allows a systematic interrogation of the function of every gene.”
Norbert Perrimon
The research team, which included Perrimon and colleagues at Harvard
Medical School, the University of Heidelberg and the Max Planck
Institute for Molecular Genetics in Germany, described its technique in
the February 6, 2004, issue of the journal Science.
The screening technique developed by Perrimon and his colleagues
builds on methods developed in one of the hottest areas of biology, RNA
interference (RNAi) research. In RNAi, double-stranded RNA (dsRNA) that
matches the messenger RNA produced by a given gene degrades that
messenger RNA — in effect wiping out the function of that gene in a
cell. RNAi is widely used as a research tool to selectively erase the
cellular contributions of individual genes to study their function.
In their mass screening technique, Perrimon and his colleagues first
created a library of 21,000 dsRNA that corresponded to each of the more
than 16,000 genes in the Drosophila genome. They then applied
each of these dsRNA molecules to cultures of Drosophila cells
and assayed how knocking down the function of a targeted gene affected
cell numbers in the cultures. This basic measure, said Perrimon,
revealed genes that are not only involved in general cell growth, but
also in the cell cycle, cell survival and other such functions.
The researchers then selected 438 genes for further
characterization. The degradation of these genes produced profound
affects on cell number. “Out of this subset, we found many that
produced proteins involved in general metabolic processes such as the
ribosomes that are components of the protein synthesis
machinery,” said Perrimon. “But we also found genes that
are more specific to cell survival.”
According to Perrimon, only 20 percent of the genes that were
identified had corresponding mutations — an important
characteristic for studying gene function. “The classic approach
to studying gene function is to identify mutations in genes and select
those that produce interesting phenotypes that yield insight into
function,” said Perrimon. “But this approach has never
really given us access to the full repertoire of genes. With this
high-throughput technology, however, we can study the function of a
complete set of genes. We can systematically identify all the genes
involving one process.”
The researchers also found that a large proportion of the genes
identified in the genome screen do not code for a known protein,
“which means that there are a great number of proteins that
remain to be identified,” said Perrimon.
Perrimon emphasized that “while in this paper we describe
applying this technique only to one specific assay — the effect on
cell number — we are already applying the methodology to determine the
roles of genes in many other aspects of signal transduction and cell
biology. We are using the technique to study gene function in pathways
involved in communication between cells and those associated with
cancer; as well as aspects of cell biology such as cell shape or
cytoskeletal organization.”
Once researchers amass data on gene function from many such assays,
said Perrimon, they can begin to group genes according to the
signatures of their response in such assays. Such groupings will offer
a guide to further biological studies to map the functional cellular
protein machinery that the genes produce in living organisms.
“The idea is that with this information we might be able to
connect a number of proteins together, implying that they may be
working either in the same pathway, or they may be part of the same
molecular machine in the cell,” said Perrimon.
The RNAi assay will contribute to the screening of new drugs, he
said. “One exciting aspect of this approach is that we can
combine our assay with screening of potential therapeutic
compounds,” he said. “One of the big problems in the
pharmaceutical industry is that researchers may discover
pharmacologically active compounds but have no idea what their targets
are in the cell. However, it would be possible to perform coordinated
screens — one for compounds that interfere with a target pathway and
an RNA interference screen for genes that act in that pathway. This
correlation would allow you to match the compounds with the proteins
they affect in a much more useful way.”
Similarly, said Perrimon, researchers can use RNAi to selectively
target genes in cells infected with pathogenic bacteria, to determine
which ones affect the bacteria's ability to infect cells. Such a screen
could yield key targets for pathogen-specific antibacterial drugs, he
said.
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