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联合遗传和地理数据库,以了解纬度与人口动态学之间的关系。

Uniting genetic and geographic databases to understand the relationship between latitude and population demography.

机构信息

Department of Herpetology, American Museum of Natural History, New York, New York, USA.

出版信息

Mol Ecol Resour. 2022 Nov;22(8):2827-2829. doi: 10.1111/1755-0998.13688. Epub 2022 Jul 26.

Abstract

It was not known that phylogenetic analysis of population genetic data would show geographic structure when Avise et al. (1979) introduced the unnamed field of phylogeography. Since then, the field has grown from using single gene fragments to whole genomes resulting in more than 22,000 publications. This seemingly simple relationship between geography and genetic variation has provided the foundation for studying speciation, species delimitation, hybrid zone dynamics, adaptation, conservation genetics, community assembly, and historical demography to name a few (see Burbrink & Ruane, 2021; Edwards et al., 2016). As with many burgeoning fields, there is often little consideration of how to make data sets accessible for future researchers addressing more comprehensive questions under a common framework. For example, it is important in biogeography to examine how shared environments or barriers affect population structure across communities of species, or test if range size or latitude are correlated with genetic diversity across taxa (Myers et al., 2019; Smith et al., 2017). However, addressing these types of questions using existing data requires researchers to assemble large databases manually. Genetic and geographic databases used to store this information like NCBI Genbank (National Center for Biotechnology Information) and GBIF (Global Biodiversity Information Facility) are disconnected, and often of limited general use for conducting multitaxon studies. In this issue of Molecular Ecology Resources, Pelletier et al. (2022) have automated the process of connecting geography to DNA sequences via the phylogatR (phylogeographic data aggregation and repurposing) database.

摘要

当 Avise 等人(1979 年)引入未命名的生物地理学领域时,人们并不知道对群体遗传数据进行系统发育分析会显示出地理结构。从那时起,该领域已经从使用单个基因片段发展到使用整个基因组,这导致了超过 22000 篇的出版物。这种地理和遗传变异之间看似简单的关系为研究物种形成、物种界限、杂种区动态、适应、保护遗传学、群落组装和历史人口统计学等提供了基础(见 Burbrink 和 Ruane,2021 年;Edwards 等人,2016 年)。与许多新兴领域一样,人们通常很少考虑如何使数据集可供未来的研究人员在共同的框架下解决更全面的问题。例如,在生物地理学中,研究共享环境或障碍如何影响物种群落的种群结构,或者检验范围大小或纬度是否与跨分类群的遗传多样性相关(Myers 等人,2019 年;Smith 等人,2017 年)。然而,使用现有数据来解决这些类型的问题需要研究人员手动组装大型数据库。用于存储此类信息的遗传和地理数据库,如 NCBI Genbank(美国国家生物技术信息中心)和 GBIF(全球生物多样性信息设施)是不相连的,并且通常对进行多分类群研究的使用有限。在本期《分子生态学资源》中,Pelletier 等人(2022 年)通过 phylogatR(生物地理学数据聚合和再利用)数据库实现了将地理与 DNA 序列连接的自动化过程。

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