Developmental genetics and evolution of butterfly colour patterns

了解基因和基因产物之间的相互作用是现代生物学面临的最大挑战之一。这些复杂的相互作用可以产生令人惊讶的复杂的生物结构，但即使是最简单的结构往往也是许多基因在发育过程中相互作用的产物。当这些基因相互作用出错时，可能会导致出生缺陷、先天性疾病，甚至癌症。为了实现了解表型进化的遗传基础这一长期目标，我的实验室选择探索鳞翅目(蝴蝶和飞蛾)翅膀上颜色模式产生的遗传网络，并阐明这些网络是如何改变以产生颜色模式多样性的。蝴蝶色彩图案是完成这项工作的一个很好的模型系统，因为它们高度可变，由定义明确的亚单位组成，存在于两个维度，并且结构简单。此外，许多颜色模式在体温调节、配偶选择和捕食者避免中都有明确的角色，因此与自然选择或性选择相关的明显的健康益处，使这些模式的进化和发展特别有趣。加拿大自然科学和工程理事会的资助将使我的实验室能够研究基因相互作用的模式，这些模式负责产生一些非常简单的表型：蝴蝶翅膀上的颜色模式。通过应用实验和计算方法来发展这些简单的表型，我们可以学习关于基因网络如何运作的基本原理。然后，我们可以将这些基本原则应用于更复杂的遗传网络，这些遗传网络负责对人类和所有其他生物的健康至关重要的复杂表型。

Understanding the interactions between genes and gene products is one of the greatest challenges to modern biology. These complex interactions can produce biological structures of amazing complexity, but even the simplest of structures are often the product of many genes interacting with each other during development. When these genetic interactions go awry, it can result in birth defects, congenital disease, or even cancer. To achieve the long-term goal of understanding the genetic basis for phenotypic evolution, my lab has chosen to explore the genetic networks that underlie the production of colour patterns on the wings of Lepidoptera (butterflies and moths) and elucidate how these networks have changed to produce colour pattern diversity. Butterfly color patterns are an excellent model system in which to do this work because they are highly variable, consist of clearly defined subunits, exist in two dimensions, and are structurally simple. Further, many colour patterns have defined roles in thermoregulation, mate choice, and predator avoidance and thus have clear fitness benefits associated with natural or sexual selection, making the evolution and development of these patterns particularly interesting. Funding from the Natural Sciences and Engineering Council of Canada will enable my laboratory to study patterns of genetic interaction that are responsible for producing some very simple phenotypes: the colour patterns on the wings of butterflies. By applying experimental and computational approaches to the development of these simple phenotypes, we can learn fundamental principles about how networks of genes behave. We can then apply these fundamental principles to more complex genetic networks responsible for the complex phenotypes critical to the health of humans and all other organisms.