Modified from Figure 1 (Belleghem et al., 2017). Sample of diversity among H. erato.
What drives different coloration among birds, insects, flowers? One of the major goals in evolutionary studies is understanding what is going on in DNA that makes organisms different. A fancy way to say this is studying how an organism’s genotype (the genome) influences the phenotype (observed characteristics).
Modified from Figure 1 (Belleghem et al., 2017). Geographical distribution, phylogeny and color pattern diversity among H. erato individuals
From yeast to Darwin’s finches (and everything in between), there are a variety of models that provide study systems to tease apart the link between genotype and phenotype. In particular, it’s helpful when the model system has undergone a recent adaptive radiation, so that there are a bunch of representatives that look diverse.
Figure 3 (Belleghem et al., 2017). Association mapping in hybrid zones and phylogenetic comparisons identify the modular genetic architecture of black forewing variation.
One of these ideal model organisms is Heliconius erato, a butterfly, in which only a handful of genes (termed the “toolkit genes”) have been deemed responsible for determining wing color patterns. In a recent study by Belleghem et al. (2017), the authors demonstrate that it’s not so much the genes themselves but short non-coding regions located nearby that are responsible for the beautiful array of diverse wing color patterns that exist.
There are more than 400 types of wing color patterns among the 46 known species in the genus Heliconius. Talk about eye candy for your model system, jeeze. Clearly, Heliconius is fantastic for studying the genetic basis for diversity. Why so many different patterns? Wing color is important in nature since it plays role in indicating toxicity or finding that special someone when it’s time to mate.
Figure 4 (Belleghem et al., 2017). Modular architecture of red pattern variation.
Bellegham and colleagues put together a nice reference genome, and sequenced an additional 116 individuals, including 101 H. erato representatives as well as 15 individuals from 8 other related species (which used for comparison). The butterflies were collected from a variety of locations in Central and South America, beautifully depicted in Figure 1. The coverage for these re-sequenced genomes ranged from 15 to 30X. For a nice intro to this model system, check out this summary from the lead author, which also will also make you appreciate how many people from different countries were involved in this article.
This study found that individuals clustered genetically according to geographic location (and not the pretty wing pattern). They found that the same wing pattern was found in locations near the Caribbean as well as the Amazon. The main force driving the different coloration in wing patterns is natural selection, and with their data set Belleghem and colleagues were able to identify the specific regions of the genomes responsible for different color patterns.
The key finding was that for the most important parts of the genome implicated in color pattern determination, small regulatory regions are the actual players driving diversity. This study was a huge effort, and the findings are eloquently presented. Sequencing such a large group of genomes from diverse geographic locations allowed not only careful investigation of that whole genotype/phenotype situation but also a pretty nice biogeographical analysis. I suppose in the end, it’s not just one H. erato of a different color, but that is what makes things interesting.
Reference
Van Belleghem, S.M., Rastas, P., Papanicolaou, A., Martin, S.H., Arias, C.F., Supple, M.A., Hanly, J.J., Mallet, J., Lewis, J.J., Hines, H.M. and Ruiz, M., 2017. Complex modular architecture around a simple toolkit of wing pattern genes. Nature Ecology & Evolution, 1, p.0052. doi:10.1038/s41559-016-0052