CAREER: Genetic architecture and the construction of complex social traits

包括动物、植物、甚至微生物在内的生物群体常常可以共同完成个体无法单独完成的任务。然而，不帮助邻居的个人会侵蚀群体生活的好处，这会破坏群体的稳定。从长远来看，这些力量的平衡导致一些种群和物种生活在复杂的群体中，而另一些则过着孤独的生活。生活在复杂群体中的物种包括蚂蚁和蜂群、鬣狗氏族和人类社会。进化生物学和经济学的数学工具已经被用来预测群体生活的利大于弊。尽管这些预测可以解释整个生命之树的广泛模式，但它们并没有更新，以纳入DNA技术的最新进展。这些进步彻底改变了科学家对基因对人类疾病影响的理解，也帮助生物学家将基因与许多不同动物物种的社会行为和群体合作倾向联系起来。这项研究将为科学界开发新的数学和计算工具，这些工具将明确地整合这些数据，以便生物学家能够更好地理解影响社会行为和群体生活的基因的历史和功能。这些知识不仅将阐明合作与冲突的进化起源，还将帮助生物学家剖析群体生活的遗传基础，这对于理解社会环境变化可能对人类健康产生负面影响的机制非常重要。所有年龄段的学生都将得到这项研究的支持，并获得重要的数学和计算训练。这项研究将通过创造新的数学和计算工具，专门解决遗传连锁、重组和上位性在复杂社会特征进化中的作用，将社会行为的进化理论与种群基因组学联系起来。这些工具将包括：(i)新的种群遗传方法和模拟工具，用于评价减少重组对促进合作演变的作用；这可能是在许多社会物种中发现的“超级基因”进化的先驱；(2)研究多性状协同进化和自身重组的新方法，使研究超基因的长期进化成为可能；（iii）新的模拟方法，用于研究当这些基因成为社会特征的基础时，基因调控相互作用是如何演变的，这将有助于更好地理解社会行为如何影响基因网络的进化。高中生、本科生、研究生和博士后将从这项研究中受益。该奖项由环境生物学部门的进化过程、综合有机体系统部门的行为系统和刺激竞争研究的既定计划（EPSCoR）共同资助。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Groups of organisms including animals, plants, and even microbes can often accomplish tasks together that individuals cannot do alone. However, individuals who do not help their neighbors erode the benefits of group living, which can destabilize the group. In the long run, the balance of these forces leads some populations and species to live in complex groups while others live solitary lives. Examples of species living in complex groups include ant and bee colonies, hyena clans, and human societies. Mathematical tools from evolutionary biology and economics have been used to predict when the benefits of group living might outweigh the costs. Although these predictions can explain broad patterns across the tree of life, they have not been updated to incorporate recent advances in DNA technology. These advances have revolutionized how scientists understand the influence of genes on human disease and have also helped biologists link genes to social behavior and the propensity to act cooperatively in groups in many different animals species. This research will develop new mathematical and computational tools for the scientific community that will explicitly incorporate these data so that biologists can better understand the history and function of genes that affect social behavior and group living. This knowledge will not only shed light on the evolutionary origins of cooperation and conflict, it will help biologists dissect the genetic basis of group living, which is important for understanding the mechanisms by which changes in the social environment might negatively impact human health. Students of all ages will be supported by this research and gain important mathematical and computational training. This research will bridge evolutionary theory for social behavior with population genomics by creating new mathematical and computational tools that specifically address the role of genetic linkage, recombination, and epistasis in the evolution of complex social traits. These tools will include: (i) new population genetic methods and simulation tools for evaluating the role of reduced recombination in enhancing the evolution of cooperation; this could be a precursor to the evolution of "super genes" found in a number of social species; (ii) new methods for studying the coevolution of multiple traits and recombination itself, which will allow the study of the long-term evolution of supergenes; and (iii) new simulation approaches for investigating how gene regulatory interactions evolve when those genes underlie social traits, which will allow a better understanding of how social behavior affects the evolution of gene networks. High school students, undergraduates, graduate students, and a postdoctoral fellow will benefit from this research. This award was co-funded by Evolutionary Processes in the Division of Environmental Biology, Behavioral Systems in the Division of Integrative Organismal Systems, and the Established Program to Stimulate Competitive Research (EPSCoR).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.