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保护基因组学中的大数据:提升技能、防范风险并紧跟领域发展。

Big Data in Conservation Genomics: Boosting Skills, Hedging Bets, and Staying Current in the Field.

机构信息

Division of Biological Sciences, University of Montana, Missoula, MT.

Department of Biology, Utah State University, Logan, UT.

出版信息

J Hered. 2021 Jul 15;112(4):313-327. doi: 10.1093/jhered/esab019.

DOI:10.1093/jhered/esab019
PMID:33860294
Abstract

A current challenge in the fields of evolutionary, ecological, and conservation genomics is balancing production of large-scale datasets with additional training often required to handle such datasets. Thus, there is an increasing need for conservation geneticists to continually learn and train to stay up-to-date through avenues such as symposia, meetings, and workshops. The ConGen meeting is a near-annual workshop that strives to guide participants in understanding population genetics principles, study design, data processing, analysis, interpretation, and applications to real-world conservation issues. Each year of ConGen gathers a diverse set of instructors, students, and resulting lectures, hands-on sessions, and discussions. Here, we summarize key lessons learned from the 2019 meeting and more recent updates to the field with a focus on big data in conservation genomics. First, we highlight classical and contemporary issues in study design that are especially relevant to working with big datasets, including the intricacies of data filtering. We next emphasize the importance of building analytical skills and simulating data, and how these skills have applications within and outside of conservation genetics careers. We also highlight recent technological advances and novel applications to conservation of wild populations. Finally, we provide data and recommendations to support ongoing efforts by ConGen organizers and instructors-and beyond-to increase participation of underrepresented minorities in conservation and eco-evolutionary sciences. The future success of conservation genetics requires both continual training in handling big data and a diverse group of people and approaches to tackle key issues, including the global biodiversity-loss crisis.

摘要

目前,进化生物学、生态学和保护基因组学领域面临的一个挑战是,在生成大规模数据集的同时,还需要额外的培训来处理这些数据集。因此,保护遗传学家越来越需要通过研讨会、会议和研讨会等途径不断学习和培训,以保持最新的知识。ConGen 会议是一个近乎年度的研讨会,旨在指导参与者理解群体遗传学原理、研究设计、数据处理、分析、解释以及将这些原理应用于现实保护问题。每年的 ConGen 会议都会聚集一批不同的讲师、学生和相关的讲座、实践课程和讨论。在这里,我们总结了 2019 年会议的主要经验教训以及该领域的最新更新,重点介绍了保护基因组学中的大数据。首先,我们强调了与处理大数据集相关的经典和当代研究设计问题,包括数据过滤的复杂性。其次,我们强调了构建分析技能和模拟数据的重要性,以及这些技能在保护遗传学职业内外的应用。我们还强调了最近的技术进步和新颖的应用,以保护野生种群。最后,我们提供数据和建议,以支持 ConGen 组织者和讲师的持续努力,并扩大保护和生态进化科学领域中代表性不足的少数群体的参与。保护遗传学的未来成功需要不断培训处理大数据的能力,以及需要多样化的人群和方法来解决关键问题,包括全球生物多样性丧失危机。

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J Hered. 2021 Jul 15;112(4):313-327. doi: 10.1093/jhered/esab019.
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