The changing role of model organisms in genetics

SPOTLIGHT ON GENETICS

Advances in sequencing technology are giving researchers access to a wide range of genomes, from microbes to mammals. What does the future hold for traditional models?

EVOLUTIONARY BIOLOGIST Thomas Hunt Morgan may have immortalized the role of Drosophila melanogaster in genetics research, but the fruitfly was not his first choice of experimental model. Seeking a short-lived organism that could be easily bred in the laboratory under changing conditions, he tried the mouse, rat, pigeon and even a plant louse before settling on Drosophila. A century after Morgan's seminal work on sex-linked inheritance, scientists still use the fruitfly to investigate and demonstrate basic genetic principles. But it is far from the only tool available to modern geneticists.

Techniques for sequencing genes and genomes have developed at ever-increasing rates, and the turn of the 21st century was dotted with announcements of successful genome-sequencing projects, from yeast in 1997 to the tomato in May this year (go.nature.com/Zpz7sB). “What you're seeing is a dramatic expansion in the number of organisms and strains you can study,” says Eric Schadt, chair of the department of genetics and genomics sciences at Mount Sinai School of Medicine in New York. The ease with which sequencing technologies can be applied to all manner of species presents a potential conundrum for researchers: should they continue to work on the established models or start afresh with some of the myriad organisms now available?

Advances in sequencing technology could lead to a revolution in research on the fruitfly Drosophila melanogaster. Credit: EYE OF SCIENCE/SCIENCE PHOTO LIBRARY

The Big Five

The well-established ‘big five’ model organisms for genetics research, as described by Michael Snyder, director of Stanford University Center for Genomics and Personalized Medicine, are yeast, mouse, the nematode Caenorhabditis elegans, thale cress (Arabidopsis thaliana) and Drosophila. Snyder says the number one reason for working with these standard models these days is the wealth of biological information available about them and innumerable proven experimental techniques. His lab tests virtually every technical process on yeast before applying it to other model organisms or humans. “You have this vast database that lets you make connections you wouldn't otherwise make, and discover things you wouldn't normally look for,” he says. “That's hard to beat.”

Stéphane Noselli, director of the Institute of Biology Valrose (iBV) in Nice, France, who works primarily on Drosophila, agrees: “You can answer so many difficult questions with this small organism, from gene function to cell biology and physiology. It's a complete system.”

Researchers at contract research organization KeyGene, based in the Netherlands, use Arabidopsis to validate new techniques and technologies for crop breeding. “Arabidopsis provides us with an ideal test system because it has a small genome that has been sequenced to a high level of accuracy and isn't expensive to use,” explains chief scientific officer Michiel van Eijk.

The quantity of genetic information available for these standard model systems is just one of their advantages. They are all relatively sturdy organisms, and — with the exception of the mouse, whose maintenance is more complicated — they are inexpensive and easy to grow in the lab.

Emerging models

While basic cellular or biological problems are more easily solved with standard organisms, established models have been less useful in other, more complex areas. A lack of suitable systems for modeling ageing, for example, has encouraged researchers to branch out. Anne Brunet, Snyder's colleague at Stanford University, works on the killifish Nothobranchius furzeri. These fish live in African ponds that regularly dry out, so they complete their life cycle in a couple of months – perfect for studying the ageing process. Eugene Berezikov, one of the first recruits to the European Research Institute for the Biology of Ageing, which opened at University Medical Center Groningen in the Netherlands in January this year, is developing genomic tools to analyse the flatworm Macrostomum lignano. The worm's regeneration capabilities make it an ideal ageing model, while its small size, physical transparency and simple culturing techniques mean it can be easily handled in the lab.

Stanford University, where all biology students take programming courses. Credit: NORBERT VON DER GROEBEN/STANFORD SCHOOL OF MEDICINE

The challenge of new models is that researchers start with little established biological knowledge. According to the NCBI's PubMed database there have only been 10 research papers published on M. lignano, and just eight on N. furzeri; a stark contrast to the figure of 15,477 for D. melanogaster. However, Brunet says the hard work that goes into developing a new model organism is worthwhile — as well as providing a valuable new experimental model to a range of scientific communities, it can also be an excellent career move. “Dario Valenzano, who was a graduate student when he jumpstarted the N. furzeri project, has set up the model entirely from scratch, developing the first linkage map and creating the first transgenic lines,” she says. “He's now likely to focus on this in his own lab.”

Advances in sequencing technologies could soon resolve the dearth of data for new models. The availability of cheaper, faster sequencers — Life Technologies now offer a bench-top model that can sequence a genome in a day at a cost of US$1,000 — has led to a plethora of ambitious projects that aim to reveal the genomes of everything from microbes to mammals over the coming years. In October 2011 a group of international researchers published the first findings from the 29 Mammals Project (go.nature.com/omuX3z), an initiative launched in 2005 to identify functional elements of the human genome by comparing it with those of other mammals. The project, led by the Broad Institute in the United States, has sequenced the genomes of 24 mammals, including the rhesus macaque, rat and cow, adding to the five pre-existing sequenced mammalian genomes (human, chimpanzee, mouse, dog and opposum). The Chinese genomics institute BGI, which operates a network of the world's biggest genome-sequencing centres, is involved in over 20 sequencing projects. It aims to sequence 10,000 microbial genomes, 1,000 plant and animal genomes and 10,000 vertebrate genomes, in collaboration with numerous institutions worldwide.

Researchers considering a move to a new model organism need to have a thorough understanding of its biology, says iBV's Noselli. “It involves a lot of investment,” he says. The developmental biology department at the Pasteur Institute in Paris, France, now uses Drosophila, chick, zebrafish and the emerging vertebrate model organism amphioxus, a fish-like marine animal also known as the lancelet, but this only came about after years of investment in a solid research base of mouse genetics.

In with the old

The only people we'll go after are those who think at a systems-wide scale, rather than classically trained reductionists. Eric Schadt, Mount Sinai School of Medicine

Although sequencing is opening up a vast array of research avenues, Schadt at Mount Sinai cautions that adapting existing technologies for novel organisms is going to be “a much longer road than we appreciate”. He argues that the best short-term use of new tools is to give geneticists a more sophisticated view of existing model organisms; in fact, he believes the field is heading for a revolution in Drosophila studies. He and his colleagues have just recruited additional staff to expand on promising work in a Drosophila lab at Mount Sinai. “It would be really difficult to develop it all from scratch in a new system,” he says. “It's hard to justify.”

Both Schadt and Guilio Superti-Furga, scientific director of the Center for Molecular Medicine (CeMM) in Vienna, Austria, predict that technological advances will encourage researchers to further study wild-type strains of existing mutant models, rather than moving straight into new systems. New mutations in established model organisms are also attracting interest. “Some groups are using genome-wide association studies to identify every potential disease risk gene, and making mouse models for each of them,” says Christine Van Broeckhoven, professor of molecular biology and genetics at Antwerp University and a director at life sciences research institute VIB in Belgium.

KeyGene's van Eijk adds that researchers will continue to revert to model organisms when faced with the unknown. “Once each technological barrier is broken, there are more questions,” he says. “It will always be the case that a limited number of model species stay ahead.”

Technically minded

As well as influencing which model genetic organisms will be used in the future, the vast quantities of data generated by collaborative genome-sequencing efforts is changing the field of genetics as a whole. Many leading departments are looking towards informatics-driven investigations and scientists are no longer being hired purely for their laboratory experience. Institutions list bioinformatic and statistical skills as key criteria when taking on new staff. “Investigators must be able to use all the new literature and databases,” says CeMM's Superti-Furga. “The next generation of researchers require much more computational skill.” Schadt agrees that geneticists need experience of a quantitative subject to be competitive in the field: “Ten years from now you'll be a dinosaur — extinct — if you don't”. Knowledge of systems biology is also an asset, he adds. “The only people we'll go after are those who think at a systems-wide scale, rather than classically trained reductionists.”

Many institutions have already embedded bioinformatics in their degree programmes. At Stanford University all biological sciences students now have to take programming classes, and the University of Washington set up an interdisciplinary computational molecular biology PhD more than a decade ago.

Robert Desnick, dean for genetics and genomic medicine at Mount Sinai, says computational genomics will be particularly important in research into human disease. Being trained in both computational genomics and biology is “going to pay off at every level of science,” he says.

Practical experience of sequencing is also advantageous. For example, the New York Genome Center (NYGC), an independent biomedical research start-up scheduled to begin operations in 2012, is currently “aggressively recruiting lab technicians with experience with Illumina HiSeq technology,” according to founding executive director Nancy Keller. The majority of the centre's initial 500 staff will be sequencing and bioinformatics professionals. NYGC's initial research focus will be human genomics, but it will also support the mouse genetics carried out at its founding institutions. “We expect that our focus and mission will evolve over time, and we are open to expanding in the future into other model organisms,” says Keller.

Stanford's Snyder says it is important to recognise the intrinsic value of traditional models in translational research as they can help accelerate the discovery of clinically relevant findings. “What we know about the cell cycle was pioneered in yeast; neurobiology, from flies and worms,” he says. “That background information can't be understated in terms of its value.”

So while there is certainly a place within the genetics field for research and development involving new model organisms, the traditional ones are by no means redundant.