Multiple merger coalescent models in population genetics.
群体遗传学中的多重合并合并模型。
基本信息
- 批准号:EP/G052026/1
- 负责人:
- 金额:$ 34.72万
- 依托单位:
- 依托单位国家:英国
- 项目类别:Research Grant
- 财政年份:2009
- 资助国家:英国
- 起止时间:2009 至 无数据
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The proposed research lies at the rich interface between mathematics and population genetics. The main purpose of theoretical population genetics is to understand the ways in which the forces of mutation, natural selection, random genetic drift and population structure interact to produce and maintain the complex patterns of genetic variation observed within species. The first step is to distill our understanding of how these forces operate into a workable mathematical model whose predictions can then be compared with data. One of the outstanding successes of this approach is Kingman's coalescent which provides a simple and elegant description of the genealogical trees relating individuals in a sample from a large `panmictic' population. Variations of Kingman's coalescent allow for the introduction of more realistic assumptions about the population such as spatial or genetic structure, selection and recombination. In the resulting `ancestral influence graph', lineages then branch, migrate and coalesce. However, comparison with data shows that these models are still inadequate. The first key observation is that genetic diversity is orders of magnitude lower than predicted by census population size and the `standard' genetic drift captured by Kingman's coalescent. The explanation is that whereas Kingman's coalescent assumes that the total number of offspring produced by a single individual is very small relative to the total population size, in reality offspring distributions can be very skewed. This can be driven by many things, for example large scale extinction-recolonization events or repeated appearances of highly beneficial mutations that rapidly sweep through the population. As a result, when one examines the genealogical trees relating individuals in a sample from the population, they are best approximated by models in which multiple (by which we mean at least three) ancestral lineages can coalesce in a single event. This contrasts with Kingman's coalescent in which only pairwise coalescences are allowed. In recent work of Eldon and Wakeley in the journal Genetics, it is proposed that the reproductive biology of certain marine organisms (including Atlantic cod and Pacific oyster) dictates that we should use such multiple merger coalescents even before we consider demography and natural selection. These organisms are characterized by broadcast spawning, external fertilization, extremely high fecundity and high initial mortality. Similar considerations apply, for example, to some plant populations (which distribute pollen) and some insect populations (where individuals of one gender far outnumber those of the other). Eldon and Wakeley also point out that their mode of reproduction can also account for the excess of single variants observed in sequence data for these organisms, a feature more usually attributed to other causes such as natural selection. There are, then, at least three different mechanisms through which we are led to multiple merger coalescent models. But so far there has been surprisingly little analysis of what the most appropriate models should be. Within the vast collection of so-called lambda and xi-coalescents, are there natural subclasses most suitable for modelling biological populations? And how can we distinguish between them? Almost certainly it will not suffice to look at just a single genetic locus, but rather we must understand correlations across loci. The starting point of this project is, through careful consideration of the biological mechanisms driving the population, to identify suitable classes of coalescent model. We must then understand the (multiple) ancestral selection and ancestral recombination graphs consistent with a given coalescent. The overarching aim is, through a mixture of analysis and simulation, to find ways to disentangle from genetic data the signals of the various demographic and genetic forces that have shaped the population.
这项拟议的研究位于数学和种群遗传学之间的丰富界面上。理论种群遗传学的主要目的是了解突变、自然选择、随机遗传漂移和种群结构的力量如何相互作用,以产生和维持物种内观察到的复杂的遗传变异模式。第一步是将我们对这些力量如何运作的理解提炼成一个可行的数学模型,然后将预测与数据进行比较。这一方法的突出成功之一是Kingman的联合,它简单而优雅地描述了从一个大的“泛种族”群体中抽取的样本中与个人相关的谱系树。金曼组合的变化允许引入关于种群的更现实的假设,如空间或遗传结构、选择和重组。在由此产生的“祖传影响图”中,血统随后分支、迁徙和合并。然而,与数据的对比表明,这些模型仍然存在不足。第一个关键的观察结果是,遗传多样性比人口普查预测的种群规模和Kingman的联合体捕捉到的“标准”遗传漂移要低几个数量级。解释是,尽管Kingman的联合体假设单个个体产生的后代总数相对于总种群规模非常小,但实际上后代分布可能非常不平衡。这可能是由许多因素推动的,例如大规模灭绝-重新殖民事件或迅速席卷整个种群的高度有益突变的反复出现。因此,当一个人检查与种群样本中的个体相关的谱系树时,它们最接近于多个(我们指的是至少三个)祖先谱系可以合并为一个事件的模型。这与Kingman的合并形成了鲜明对比,在Kingman的合并中,只允许两两合并。在Eldon和Wakeley最近发表在《遗传学》杂志上的文章中,有人提出,某些海洋生物(包括大西洋鳕鱼和太平洋牡蛎)的繁殖生物学决定了我们甚至在考虑人口统计学和自然选择之前就应该使用这种多重合并。这些生物的特点是分散产卵、体外受精、极高的繁殖力和高初始死亡率。例如,类似的考虑也适用于一些植物种群(传播花粉)和一些昆虫种群(其中一种性别的个体数量远远超过另一种性别)。Eldon和Wakeley还指出,他们的繁殖模式也可以解释在这些生物体的序列数据中观察到的单一变异的过量,这一特征更多地归因于其他原因,如自然选择。那么,至少有三种不同的机制可以引导我们形成多种合并合并模式。但到目前为止,关于最合适的模型应该是什么的分析令人惊讶地少之又少。在所谓的lambda和xi类的庞大集合中,有没有自然子类最适合对生物种群进行建模?我们如何区分它们呢?几乎可以肯定的是,仅仅研究一个遗传基因座是不够的,相反,我们必须了解各个基因座之间的相关性。这个项目的出发点是,通过仔细考虑驱动种群的生物学机制,确定合适的类合并模型。然后,我们必须了解与给定的合并一致的(多个)祖先选择和祖先重组图。总体目标是,通过分析和模拟的混合,找到从遗传数据中分离各种人口和遗传力量的信号的方法,这些因素塑造了种群。
项目成果
期刊论文数量(7)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Hybrid-Lambda: simulation of multiple merger and Kingman gene genealogies in species networks and species trees
Hybrid-Lambda:物种网络和物种树中多重合并和 Kingman 基因谱系的模拟
- DOI:10.1101/023465
- 发表时间:2015
- 期刊:
- 影响因子:0
- 作者:Zhu S
- 通讯作者:Zhu S
An Ancestral Recombination Graph for Diploid Populations with Skewed Offspring Distribution
- DOI:10.1534/genetics.112.144329
- 发表时间:2013-01-01
- 期刊:
- 影响因子:3.3
- 作者:Birkner, Matthias;Blath, Jochen;Eldon, Bjarki
- 通讯作者:Eldon, Bjarki
Hybrid-Lambda: simulation of multiple merger and Kingman gene genealogies in species networks and species trees.
- DOI:10.1186/s12859-015-0721-y
- 发表时间:2015-09-15
- 期刊:
- 影响因子:3
- 作者:Zhu S;Degnan JH;Goldstien SJ;Eldon B
- 通讯作者:Eldon B
Age of an allele and gene genealogies of nested subsamples for populations admitting large offspring numbers
允许大量后代的群体的等位基因年龄和嵌套子样本的基因谱系
- DOI:10.48550/arxiv.1212.1792
- 发表时间:2012
- 期刊:
- 影响因子:0
- 作者:Eldon B
- 通讯作者:Eldon B
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Alison Etheridge其他文献
Alison Etheridge的其他文献
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{{ truncateString('Alison Etheridge', 18)}}的其他基金
Modelling populations in heterogeneous environments
异构环境中的群体建模
- 批准号:
EP/K034316/1 - 财政年份:2013
- 资助金额:
$ 34.72万 - 项目类别:
Research Grant
Natural Selection in Spatially Structured Populations
空间结构种群的自然选择
- 批准号:
EP/I01361X/1 - 财政年份:2011
- 资助金额:
$ 34.72万 - 项目类别:
Research Grant
Resubmission (due to requested amendments): New models for spatially structured populations
重新提交(根据要求的修改):空间结构人口的新模型
- 批准号:
EP/E065945/1 - 财政年份:2007
- 资助金额:
$ 34.72万 - 项目类别:
Research Grant
Stochastic Population Genetic Models of Chronic Pathogens
慢性病原体的随机群体遗传模型
- 批准号:
EP/E010989/1 - 财政年份:2006
- 资助金额:
$ 34.72万 - 项目类别:
Research Grant
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