当前位置: X-MOL 学术Philos. Trans. Royal Soc. B: Biol. Sci. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Sometimes hidden but always there: the assumptions underlying genetic inference of demographic histories
Philosophical Transactions of the Royal Society B: Biological Sciences ( IF 6.3 ) Pub Date : 2020-11-30 , DOI: 10.1098/rstb.2019.0719
Liisa Loog 1
Affiliation  

Demographic processes directly affect patterns of genetic variation within contemporary populations as well as future generations, allowing for demographic inference from patterns of both present-day and past genetic variation. Advances in laboratory procedures, sequencing and genotyping technologies in the past decades have resulted in massive increases in high-quality genome-wide genetic data from present-day populations and allowed retrieval of genetic data from archaeological material, also known as ancient DNA. This has resulted in an explosion of work exploring past changes in population size, structure, continuity and movement. However, as genetic processes are highly stochastic, patterns of genetic variation only indirectly reflect demographic histories. As a result, past demographic processes need to be reconstructed using an inferential approach. This usually involves comparing observed patterns of variation with model expectations from theoretical population genetics. A large number of approaches have been developed based on different population genetic models that each come with assumptions about the data and underlying demography. In this article I review some of the key models and assumptions underlying the most commonly used approaches for past demographic inference and their consequences for our ability to link the inferred demographic processes to the archaeological and climate records.

This article is part of the theme issue ‘Cross-disciplinary approaches to prehistoric demography’.



中文翻译:

有时隐藏但始终存在:人口历史遗传推断的假设

人口统计过程直接影响当代人群以及后代的遗传变异模式,允许从现在和过去的遗传变异模式进行人口统计推断。在过去的几十年中,实验室程序、测序和基因分型技术的进步导致来自当今人群的高质量全基因组遗传数据大量增加,并允许从考古材料(也称为古代 DNA)中检索遗传数据。这导致了探索过去人口规模、结构、连续性和流动变化的工作激增。然而,由于遗传过程是高度随机的,遗传变异的模式只能间接反映人口历史。因此,过去的人口统计过程需要使用推理方法来重建。这通常涉及将观察到的变异模式与理论群体遗传学的模型预期进行比较。已经基于不同的群体遗传模型开发了大量方法,每种方法都带有关于数据和潜在人口统计学的假设。在本文中,我回顾了过去人口推断最常用方法背后的一些关键模型和假设,以及它们对我们将推断的人口过程与考古和气候记录联系起来的能力的影响。已经基于不同的群体遗传模型开发了大量方法,每种方法都带有关于数据和潜在人口统计学的假设。在本文中,我回顾了过去人口推断最常用方法背后的一些关键模型和假设,以及它们对我们将推断的人口过程与考古和气候记录联系起来的能力的影响。已经基于不同的群体遗传模型开发了大量方法,每种方法都带有关于数据和潜在人口统计学的假设。在本文中,我回顾了过去人口推断最常用方法背后的一些关键模型和假设,以及它们对我们将推断的人口过程与考古和气候记录联系起来的能力的影响。

本文是主题问题“史前人口学的跨学科方法”的一部分。

更新日期:2020-12-01
down
wechat
bug