CAREER: An integrative genomic and biodemographic analysis of prehistoric human-environment interactions in an island ecosystem, with bioinformatics capacity development

这个职业项目将应用新的生物和计算机科学方法来研究人类，驯化农业物种和濒危本土动物的人口规模的最新变化，所有这些动物都生活在同一个栖息地。这些结果将帮助我们了解人类人口增长如何影响野生物种的自然种群，以及人，驯养动物和环境之间的复杂相互作用。该研究将通过开发新的基因组方法和用于分析基因组数据的计算“大数据”分析（生物信息学）来推进科学。这些方法最初将应用于对马达加斯加的人、牛和两种濒危狐猴物种的研究，马达加斯加是一个理想的地点，因为人类首次到达该岛相对较近（几千年前）。对世界其他地区人类与环境相互作用的研究，包括人类与环境相互作用开始较早的北美洲，也将受益于这些方法。该项目的教育部分将包括每年为不同受众举办生物信息学培训讲习班;参与的学生将发展生物和计算机科学技能，单独和共同将有广泛的科学和工业培训的适用性。这项建议的科学目标包括重建马达加斯加人民的高分辨率人口统计历史，他们的畜牧业驯化牛，和两个广泛分布的地方性狐猴物种，所有这些都具有与岛上人类历史最近时间轴相关的时间分辨率。这些结果，可能通过应用新的人口基因组方法开发的主要研究者，将相互比较，并提供古气候数据，开发一个综合的经验模型的历史上的人为影响马达加斯加的生物多样性。马达加斯加是研究人类与环境相互作用的过程和后果的重要岛屿。马达加斯加人有一段有趣的历史，因为他们相对较晚才到达该岛，他们的南岛语和非洲血统混合，并且因为他们与世界上最具生物多样性，地方性和受威胁的生态之一的关系。这项工作将从经验上改变我们对马达加斯加生物多样性的人为影响的历史的理解，并建立一个综合的研究框架，应用到世界其他地区的全新世资源利用集约化和人与环境的相互作用也是主要的兴趣。该项目教育部分的核心是每年提供互动式生物信息学培训研讨会，该研讨会建立在生物和计算科学的整合基础上，这是研究的核心。最先进的研讨会将通过以下方式与项目的科学目标相结合？黑客？风格的发展计算工具的分析基因组数据在这项研究中产生的。该项目的联合资金由美国国家科学基金会国际科学与工程办公室（OISE）提供。

This CAREER project will apply new biological and computer science methods to study recent changes in the population sizes of humans, domesticated agricultural species, and endangered native animals all living in the same habitat. The results will help us understand how human population growth affects natural populations of wild species, and the complex interactions among people, domesticated animals, and the environment. The study will advance science through the development of new genomic methods and computational "big data" analyses (bioinformatics) for analyzing genomic data. These methods will initially be applied to a study of people, their cattle, and two endangered lemur species in Madagascar, which is an ideal site because humans first arrived to the island relatively recently (several thousand years ago). Research on human-environment interactions in other regions of the world, including North America where human-environment interaction started earlier, will also benefit from these methods. The educational component of the project will involve the annual delivery of bioinformatics training workshops to diverse audiences; participating students will develop biological and computer science skills that separately and together will have wide scientific and industrial training applicability.The scientific aims of this proposal include reconstructing high-resolution demographic histories for Malagasy people, their commensal domesticated cattle, and two widely-distributed endemic lemur species, all with temporal resolution relevant to the recent timeline of human history on the island. These results, made possible by the application of novel population genomic methods developed by the principal investigator, will be compared to each other and to available paleoclimate data to develop an integrated empirical model of the history of anthropogenic effects on Madagascar's biodiversity. Madagascar is an important island for studying the processes and consequences of human-environment interaction. The people of Madagascar have an interesting history because of their relatively recent arrival to the island, their mixed Austronesian and African ancestry, and because of their relationship to one of the world's most biologically diverse, endemic and threatened ecologies. This work will empirically transform our understanding of the history of anthropogenic effects on Madagascar's biodiversity and establish an integrative research framework for application to other regions of the world where Holocene resource use intensification and human-environment interaction are likewise topics of major interest. A centerpiece of the educational component of this project is the annual delivery of interactive-style bioinformatics training workshops that build on the integration of biological and computational science that is central to the research. The most advanced workshop will be integrated with the project's scientific aims through ?hackathon?-style development of computational tools for analyses of the genomic data generated in this study. Joint funding for this project is provided by the National Science Foundation's Office of International Science and Engineering (OISE).