Identifying the Utility of Species-Tree Approaches for Deep Radiations

确定物种树方法在深辐射中的效用

• 批准号: 1118815
• 负责人: L. Lacey Knowles
• 金额: $ 33.06万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1118815&HistoricalAwards=false
• 关键词: Identifying; Utility; Species; Tree; Approaches

The unprecedented amount of DNA sequence data made available by recent technological advances is changing how biologists approach questions. Such data have great power to reveal the history of species diversification by improving estimates of species relationships. However, the opportunities for improving estimates of species relationships are at risk because data collection is outpacing the development of analytical methods to handle the data. This project explores the power and limitations in recently developed methods to infer the history of "deep radiations" (events of rapid species diversifications that occurred in the distant past), which may be hampered by conflicting historical signal from different genomic regions. It will use computer simulations to not only evaluate key data properties affecting historical reconstructions, but also identify what combination of data and methodological practices are likely to improve estimates of species relationships. These simulations will be informed by examples from nature, assuring that biological realities, not just theoretical ideals, are jointly considered. Deep radiations are of particular interest because they have had a major impact on present day diversity. Our inability to accurately infer the species relationships that define these events impedes our ability to link diversification with global events such as climate change and movements of the earth's continents. By identifying methodological properties and types of analyses that effectively utilize the genomic data now becoming available, this project will improve the foundation that many evolutionary and ecological questions depend upon -- a resolved history of species diversification.

由于最近的技术进步，大量的DNA序列数据正在改变生物学家解决问题的方式。这些数据通过改进物种关系的估计，对揭示物种多样化的历史有很大的帮助。然而，由于数据收集的速度超过了处理数据的分析方法的发展，改善物种关系估计的机会正处于危险之中。本项目探讨了最近发展的推断“深辐射”（发生在遥远过去的物种快速多样化事件）历史的方法的力量和局限性，这些方法可能受到来自不同基因组区域的相互冲突的历史信号的阻碍。它将使用计算机模拟，不仅评估影响历史重建的关键数据属性，而且还确定数据和方法实践的哪些组合可能改善物种关系的估计。这些模拟将以自然界的例子为依据，确保共同考虑生物现实，而不仅仅是理论理想。深辐射之所以特别有趣，是因为它们对当今的生物多样性产生了重大影响。我们无法准确地推断出定义这些事件的物种关系，这阻碍了我们将多样性与气候变化和地球大陆运动等全球事件联系起来的能力。通过确定有效利用现有基因组数据的方法属性和分析类型，该项目将改善许多进化和生态问题所依赖的基础——解决物种多样化的历史。