Experimental phylogenies to benchmark ancestral sequence reconstruction

用于基准祖先序列重建的实验系统发育

• 批准号: 1145698
• 负责人: Eric Gaucher
• 金额: $ 68万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2016-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1145698&HistoricalAwards=false
• 关键词: Experimental; phylogenies; benchmark; ancestral; sequence

The concept of experimental paleogenetics was proposed more than forty years ago as a way to exploit molecular sequence information to gain a better understanding modern phenotypic diversity. Only recently have computational reconstructions of ancestral sequences been supported by models of character state inference and robust phylogenies. Laboratory synthesis of the inferred genes and proteins has, in turn, guided inference regarding ancestral phenotypes based on the properties of these ancient biomolecules. This approach aims to improve the accuracy in inferring ancient genes though the development of an application in experimental phylogenetics. The approach allows researchers to connect genotype and phenotype for ancestral sequence reconstruction methods in a manner currently not possible. The software uses theoretical and computational simulations to benchmark the performances of various models. The proposed research will extend and experimentally validate the field of ancestral sequence reconstruction, allowing researchers to place confidence in the ability of ancestral sequence reconstruction to facilitate the community's understanding of molecular adaptation.The research group participates in teaching and service activities intended to train the next generation of scientists. On one hand, this consists of teaching courses that include Evolutionary Synthetic Biology and Astrobiology. On the other hand, this consists of promoting scientific ideas and training outside of the University setting. For instance, a K-12 science outreach program has been created to promote a diverse learning community and increase the participation of underrepresented groups in evolutionary biology and molecular evolution research.

实验古遗传学的概念是在四十多年前提出的，作为一种利用分子序列信息来更好地理解现代表型多样性的方法。直到最近，祖先序列的计算重建才得到了字符状态推断和鲁棒的遗传模型的支持。实验室合成的推断基因和蛋白质，反过来，指导推断祖先的表型的基础上，这些古老的生物分子的属性。该方法旨在通过在实验遗传学中的应用，提高推断古代基因的准确性。该方法允许研究人员以目前不可能的方式连接基因型和表型以用于祖先序列重建方法。该软件使用理论和计算模拟来衡量各种模型的性能。该研究将扩展和实验验证祖先序列重建的领域，使研究人员对祖先序列重建的能力充满信心，以促进社区对分子适应的理解。该研究小组参与旨在培养下一代科学家的教学和服务活动。一方面，这包括教学课程，包括进化合成生物学和天体生物学。另一方面，这包括在大学环境之外促进科学思想和培训。例如，已经创建了K-12科学推广计划，以促进多样化的学习社区，并增加代表性不足的群体参与进化生物学和分子进化研究。