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varver:脊椎动物微卫星变异数据库。

varver: a database of microsatellite variation in vertebrates.

机构信息

Department of Evolutionary Studies of Biosystems, Graduate University for Advanced Studies (SOKENDAI), Hayama, Kanagawa, 240-0193, Japan.

Department of Mathematical Engineering, Musashino University, 3-3-3 Ariake, Koto-ku, Tokyo, 135-8181, Japan.

出版信息

Mol Ecol Resour. 2017 Jul;17(4):824-833. doi: 10.1111/1755-0998.12625. Epub 2016 Nov 21.

Abstract

Understanding how genetic variation is maintained within a species is important in ecology, evolution, conservation and population genetics. Tremendous efforts have been made to evaluate the patterns of genetic variation in natural populations of various species. For this purpose, microsatellites have played a major role since the 1990s. Here we describe a comprehensive database, varver (Variation in Vertebrates) that provides complete information regarding microsatellite variation in natural populations of vertebrates. For each species, varver includes basic information of the species, a list of publications reporting the microsatellite variation, and tables of genetic variation within and between populations (heterozygosity and F ). The geographic location and rough sampling range are also shown for each sampled population. The database should be useful for researchers interested in not only specific species but also comparing multiple species. We discuss the utility of microsatellite data, particularly for meta-analyses that involve multiple microsatellite loci from various species. We show that in such analyses, it is extremely important to correct for biases caused by differences in mutation rate, mainly due to repeat unit and number.

摘要

了解遗传变异在物种内是如何维持的,对于生态学、进化、保护和群体遗传学都很重要。人们已经做出了巨大的努力来评估各种物种的自然种群中的遗传变异模式。为此,微卫星自 20 世纪 90 年代以来发挥了重要作用。在这里,我们描述了一个综合数据库 varver(脊椎动物的变异),它提供了关于脊椎动物自然种群中微卫星变异的完整信息。对于每个物种,varver 包括物种的基本信息、报告微卫星变异的出版物列表,以及种群内和种群间遗传变异的表格(杂合度和 F)。还为每个采样种群显示了地理位置和大致的采样范围。该数据库对于不仅对特定物种感兴趣,而且对比较多个物种的研究人员应该是有用的。我们讨论了微卫星数据的实用性,特别是对于涉及来自不同物种的多个微卫星基因座的荟萃分析。我们表明,在这种分析中,纠正由于突变率差异(主要是由于重复单元和数量)引起的偏差是极其重要的。

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