DKFZ: Genes, like people, are fundamentally social. Just as we often work in teams, companies, or other more or less complex organisations, genes often work together in genetic networks. And just as our productivity is often influenced by who we work with, the effects of genes depend on the peers they interact with. That’s why understanding genetic predispositions remains a challenge – each person’s genome is a unique combination of genes, and it’s difficult to work out how they will interact and function as a team. In football, a team of star players may end up standing in each other’s way, whereas a team with good team spirits can achieve success that one would not expect from the players individually.
For the past 100 years geneticists have
tried to untangle the complex webs of genetic interactions, and to
identify how gene variants affect what other genes do. Ideally,
biologists would like a global picture of all genetic interactions in
the cell, but this has been hard to track down. Now work led by Michael
Boutros of the German Cancer Research Centre (DKFZ), Heidelberg, in
collaboration with Wolfgang Huber at EMBL Heidelberg, have shown how it
can be done. The study is reported today in the journal eLife.
The team developed their approach using cells
from the fruit fly Drosophila. First they selected genes which, when
mutated, had an effect on important characteristics like cell growth and
division. This generated a list of 1,367 genes, of which 72 were picked
out as likely hubs in the genes’ social network.
To work out which of these genes – or, more
precisely, the proteins they produce – interact, the team set about
silencing pairs of genes using a technique called RNA interference
(RNAi). The logic behind this approach is that if the effect of
silencing both genes at the same time is different from what is expected
from the effects of silencing each of them singularly, then that points
to a genetic interaction. In these RNAi experiments, each of the 1,367
genes was silenced in combination with one of the 72 key genes. “We took
more than a million images of cells”, says co-author Thomas Sandmann of
DKFZ, “and tested almost 100,000 pairwise combinations of silenced
genes”. All this data was analysed with automated algorithms on a bank
of computers, a process that Bernd Fischer, formerly a member of the
Huber lab and now at DKFZ, says “would have taken more than two years on
a single computer”.
13% (12,361) of the pairs showed evidence of a
genetic interaction, indicating that they work together. But Fischer and
his co-workers weren’t just content knowing which genes interact – they
wanted to know how. So they developed a method to work out the
direction of genetic interactions – whether gene A influenced gene B, or
vice versa. “This is novel, and hasn’t been done on this scale before,”
says Huber. Beyond revealing the direction of the interactions, their
analysis also showed whether genes amplified, or diminished, the effects
of each other. This way of teasing out the way genes interact across
the whole cell could be used to shed light on the genetic interactions
in many complex cellular processes, from fruit flies to human cells.
Such insights will eventually help for getting a
better understanding of genomes and their output –what biologists call
the phenotype – and also for finding new targets for anticancer drugs.
Typically, it’s difficult to restore the function of proteins that are
broken by mutations in cancer, but maps of genetic interactions provide a
way around that problem. “New drugs attempt to exploit lethal genetic
interactions to specifically target vulnerabilities in cancer cells”,
says Boutros. “And genetic interactions may also explain how resistance
to cancer drugs arises”.
Wolfgang Huber, Michael Boutros, Bernd Fischer,
Thomas Sandmann, Thomas Horn, Maximilian Billmann, Varun Chaudhary: A
map of directional genetic interactions in a metazoan cell. eLife 2015, DOI: 10.7554/eLife.05464