What makes a model organism? Well, as the name suggests, they are widely studied and have been adapted to a vast array of common genetic techniques. A few of the most often utilized organisms, which you are most likely already (at least) vaguely familiar with, include Drosophila melanogaster (the fruit fly), Escherichia coli, Saccharomyces cerevisiae (the yeast everyone thanks for bread, beer, and vino), Caenorhabditis elegans (everyone’s favorite nematode), and Danio rerio (the zebrafish). Model organisms are often easy to work with in a lab and easily manipulated genetically.
Model organisms are considered to be more manageable representatives of complex systems and have allowed researchers to ask specific questions that might otherwise be tricky to answer. There is a downside to focusing resources on these model organisms, however, since (unlike their name suggests), they are not perfect examples of diversity or function in nature compared to their close relatives. While they are great to work with, there is much we can learn from the less-well-studied organisms hanging around.
Why, you might wonder, is it both interesting and important to look at non-model organisms? In yeast this is an interesting question indeed. The old standby S. cerevisiae has long been a focus in yeast genetic labs, however, there is a suite of additional fascinating yeast species that have distinct evolutionary histories. The evolutionary history of S. cerevisiae has been influenced in no small part by humans. Just a few of my favorite things (wine and bread) can be produced by different strains of S. cerevisiae, which have been domesticated. With this in mind, it makes sense that the genome of a wine strain has undergone vastly different selective pressures than another species happily spending its days on the bark of a tree.
The ability to shift focus away from model organisms to non-model organisms, has been enhanced with fancy high-throughput sequencing. In fact, there are multiple studies that have demonstrated that non-model organisms are pretty interesting, (see this review article, this correspondence and this quite recent (and good) read in BMC Biology). As these articles point out, the number of genomes sequenced has rocketed recently, and studying non-model organisms allows researchers to address a wide array of important and diverse questions focused on different aspects of biology. If you need some evidence, check out Table 2 in the review by Hans Ellegren mentioned above, from the yak to the monarch butterfly, to the Norway spruce, we have learned a ton by turning to those less studied.
In an attempt to enhance the usefulness of next generation sequence (NGS) data obtained from non-model organisms, Money and colleagues recently published an article on a new imputation method. As the authors point out, in order to embark on genome-wide association studies, genome-wide genotype data has to exist. To infer missing genotypes, imputation software is basically required. It is challenging to complete these types of studies with non-model organisms, which often lack an abundance of readily available, high quality, sequenced genomes. Interestingly, Money et al., used LinkImputR to enhance the analysis of sequence data, in particular when used in non-model organisms that might not have a set of resources readily available.
There is no question that traditionally utilized model-organisms have been instrumental in examining a variety of important questions in biology. We have reached the point, however (maybe a while ago), that it is crucial that non-model organisms are not ignored. What say they settle this with NGS? Looks like model organisms have challenged non-model organisms to a sequence-off.
Ellegren, H., 2014. Genome sequencing and population genomics in non-model organisms. Trends in ecology & evolution, 29(1), pp.51-63.
Money, D., Migicovsky, Z., Gardner, K. and Myles, S., 2017. : user-guided genotype calling and imputation for non-model organisms. BMC genomics, 18(1), p.523.
Russell, J.J., Theriot, J.A., Sood, P., Marshall, W.F., Landweber, L.F., Fritz-Laylin, L., Polka, J.K., Oliferenko, S., Gerbich, T., Gladfelter, A. and Umen, J., 2017. Non-model model organisms. BMC biology, 15(1), p.55.
Tagu, D., Colbourne, J.K. and Nègre, N., 2014. Genomic data integration for ecological and evolutionary traits in non-model organisms. BMC genomics, 15(1), p.490.