Cookie Hinweis

Wir verwenden Cookies, um Ihnen ein optimales Webseiten-Erlebnis zu bieten. Dazu zählen Cookies, die für den Betrieb der Seite notwendig sind, sowie solche, die lediglich zu anonymen Statistikzwecken, für Komforteinstellungen oder zur Anzeige personalisierter Inhalte genutzt werden. Sie können selbst entscheiden, welche Kategorien Sie zulassen möchten. Bitte beachten Sie, dass auf Basis Ihrer Einstellungen womöglich nicht mehr alle Funktionalitäten der Seite zur Verfügung stehen. Weitere Informationen finden Sie in unseren Datenschutzhinweisen .


Diese Cookies sind für die Funktionalität unserer Website erforderlich und können nicht deaktiviert werden.

Name Webedition CMS
Zweck Dieses Cookie wird vom CMS (Content Management System) Webedition für die unverwechselbare Identifizierung eines Anwenders gesetzt. Es bietet dem Anwender bessere Bedienerführung, z.B. Speicherung von Sucheinstellungen oder Formulardaten. Typischerweise wird dieses Cookie beim Schließen des Browsers gelöscht.
Name econda
Zweck Session-Cookie für die Webanalyse Software econda. Diese läuft im Modus „Anonymisiertes Messen“.

Diese Cookies helfen uns zu verstehen, wie Besucher mit unserer Webseite interagieren, indem Informationen anonym gesammelt und analysiert werden. Je nach Tool werden ein oder mehrere Cookies des Anbieters gesetzt.

Name econda
Zweck Measure with Visitor Cookie emos_jcvid
Externe Medien

Inhalte von externen Medienplattformen werden standardmäßig blockiert. Wenn Cookies von externen Medien akzeptiert werden, bedarf der Zugriff auf diese Inhalte keiner manuellen Zustimmung mehr.

Name YouTube
Zweck Zeige YouTube Inhalte
Name Twitter
Zweck Twitter Feeds aktivieren

Team spirit in the genome

No. 15c | 02/04/2015

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.

Genetic interaction network analysis identifies protein complexes and other groups of closely cooperating proteins (colored dots). Directed interactions of proteins or whole groups, with each other are shown with the arrows.

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

With more than 3,000 employees, the German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ) is Germany’s largest biomedical research institute. DKFZ scientists identify cancer risk factors, investigate how cancer progresses and develop new cancer prevention strategies. They are also developing new methods to diagnose tumors more precisely and treat cancer patients more successfully. The DKFZ's Cancer Information Service (KID) provides patients, interested citizens and experts with individual answers to questions relating to cancer.

To transfer promising approaches from cancer research to the clinic and thus improve the prognosis of cancer patients, the DKFZ cooperates with excellent research institutions and university hospitals throughout Germany:

  • National Center for Tumor Diseases (NCT, 6 sites)
  • German Cancer Consortium (DKTK, 8 sites)
  • Hopp Children's Cancer Center (KiTZ) Heidelberg
  • Helmholtz Institute for Translational Oncology (HI-TRON Mainz) - A Helmholtz Institute of the DKFZ
  • DKFZ-Hector Cancer Institute at the University Medical Center Mannheim
  • National Cancer Prevention Center (jointly with German Cancer Aid)
The DKFZ is 90 percent financed by the Federal Ministry of Education and Research and 10 percent by the state of Baden-Württemberg. The DKFZ is a member of the Helmholtz Association of German Research Centers.


Subscribe to our RSS-Feed.

to top
powered by webEdition CMS