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生活在同一栖息地的人类、驯化的农业物种和濒危的本地动物的种群规模最近的变化。这一结果将有助于我们了解人类种群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。这项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)来推动科学发展。这些方法最初将被应用于对马达加斯加的人、牛和两种濒危狐猴物种的研究，这是一个理想的地点，因为人类最初到达该岛的时间相对较晚(几千年前)。世界其他地区对人与环境相互作用的研究，包括较早开始人与环境相互作用的北美地区，也将受益于这些方法。该项目的教育部分将包括每年向不同受众提供生物信息学培训讲习班；参加培训的学生将发展生物和计算机科学技能，这些技能单独和共同具有广泛的科学和工业培训应用。这项提议的科学目标包括重建马达加斯加人、他们的共生驯养牛和两个广泛分布的地方性狐猴物种的高分辨率人口史，所有这些都具有与岛上人类历史最近时间表相关的时间分辨率。通过应用首席调查员开发的新的种群基因组方法，这些结果将相互比较，并与现有的古气候数据进行比较，以开发人为对马达加斯加生物多样性影响历史的综合经验模型。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，因为他们相对较新来到该岛，他们有南岛人和非洲人的混血血统，而且他们与世界上生物多样性、地方性和受威胁最严重的生态系统之一的关系。这项工作将从经验上改变我们对人类活动对马达加斯加生物多样性影响历史的理解，并建立一个综合研究框架，将其应用于世界其他地区，在这些地区，全新世资源利用的集约化和人与环境的相互作用同样是主要感兴趣的主题。该项目教育部分的一个核心内容是每年举办互动式生物信息学培训讲习班，以生物科学和计算科学的融合为基础，这是研究的核心。最先进的研讨会将通过黑客马拉松式的计算工具开发，与该项目的科学目标相结合，用于分析这项研究中产生的基因组数据。该项目的联合资金由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).