Aaron Hong, Rebecca G Cheek, Suhashi Nihara De Silva, Kingshuk Mukherjee, Isha Yooseph, Marco Oliva, Mark Heim, Chris W Funk, David Tallmon, Christina Boucher
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引用次数: 0
Abstract
The genetic effective size (Ne) is arguably one of the most important characteristics of a population as it impacts the rate of loss of genetic diversity. Methods that estimate Ne are important in population and conservation genetic studies as they quantify the risk of a population being inbred or lacking genetic diversity. Yet there are very few methods that can estimate the Ne from data from a single population and without extensive information about the genetics of the population, such as a linkage map, or a reference genome of the species of interest. We present ONeSAMP 3.0, an algorithm for estimating Ne from single nucleotide polymorphism data collected from a single population sample using approximate Bayesian computation and local linear regression. We demonstrate the utility of this approach using simulated Wright-Fisher populations, and empirical data from five endangered Channel Island fox (Urocyon littoralis) populations to evaluate the performance of ONeSAMP 3.0 compared to a commonly used Ne estimator. Our results show that ONeSAMP 3.0 is broadly applicable to natural populations and is flexible enough that future versions could easily include summary statistics appropriate for a suite of biological and sampling conditions. ONeSAMP 3.0 is publicly available under the GNU General Public License at https://github.com/AaronHong1024/ONeSAMP_3.
遗传有效大小(Ne)可以说是种群最重要的特征之一,因为它影响着遗传多样性的丧失速度。估算 Ne 值的方法在种群和保护遗传研究中非常重要,因为它们可以量化种群近亲繁殖或缺乏遗传多样性的风险。然而,目前只有极少数方法可以在没有大量种群遗传学信息(如连接图或相关物种的参考基因组)的情况下,通过单个种群的数据估算 Ne 值。我们介绍了 ONeSAMP 3.0,这是一种利用近似贝叶斯计算和局部线性回归从单一种群样本收集的单核苷酸多态性(SNP)数据中估算 Ne 的算法。我们使用模拟的 Wright-Fisher 种群和来自五个濒危海峡岛狐(Urocyon littoralis)种群的经验数据展示了这种方法的实用性,以评估 ONeSAMP 3.0 与常用 Ne 估计器相比的性能。我们的研究结果表明,ONeSAMP 3.0 广泛适用于自然种群,而且非常灵活,未来的版本可以很容易地包含适合各种生物和采样条件的汇总统计。ONeSAMP 3.0 在 GNU 许可证下公开发布,网址为 https://github.com/AaronHong1024/ONeSAMP_3。
期刊介绍:
G3: Genes, Genomes, Genetics provides a forum for the publication of high‐quality foundational research, particularly research that generates useful genetic and genomic information such as genome maps, single gene studies, genome‐wide association and QTL studies, as well as genome reports, mutant screens, and advances in methods and technology. The Editorial Board of G3 believes that rapid dissemination of these data is the necessary foundation for analysis that leads to mechanistic insights.
G3, published by the Genetics Society of America, meets the critical and growing need of the genetics community for rapid review and publication of important results in all areas of genetics. G3 offers the opportunity to publish the puzzling finding or to present unpublished results that may not have been submitted for review and publication due to a perceived lack of a potential high-impact finding. G3 has earned the DOAJ Seal, which is a mark of certification for open access journals, awarded by DOAJ to journals that achieve a high level of openness, adhere to Best Practice and high publishing standards.