The coalescent

Kingmán, J. F. C.

doi:10.1016/0304-4149(82)90011-4

Cited by 2,250 publications

(1,688 citation statements)

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“…To examine the robustness property of our IA estimate in the presence of genetic drift, the final simulation experiment we present incorporates a simple evolution model, which roughly corresponds to the intermixture model in Long (1991) and each remains constant in time. Genealogies are generated according to coalescent theory (Kingman 1982) and using the program ms (Hudson 2002). Each genealogy represents a chromosomal segment of 5cM.…”

Section: Simulation 4: Effects Of Ld and Genetic Drift All Simulatiomentioning

confidence: 99%

Estimation of individual admixture: Analytical and study design considerations

Tang

Peng

Wang

et al. 2005

Genetic Epidemiology

617

642

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The genome of an admixed individual represents a mixture of alleles from different ancestries.In the United States, the two largest minority groups, African Americans and Hispanics, are both admixed. An understanding of the admixture proportion at an individual level (individual admixture, or IA) is valuable for both population geneticists and epidemiologists who conduct case-control association studies in these groups. Here we present an extension of a previously described frequentist (maximum likelihood or ML) approach to estimate individual admixture that allows for uncertainty in ancestral allele frequencies. We compare this approach both to prior partial likelihood based methods as well as more recently described Bayesian MCMC methods.Our full ML method demonstrates increased robustness when compared to an existing partial ML approach. Simulations also suggest that this frequentist estimator achieves similar efficiency, measured by the mean squared error criterion, as Bayesian methods but requires just a tiny fraction of the computational time to produce point estimates, allowing for extensive analysis (e.g. simulations) not possible by Bayesian methods. Our simulation results demonstrate that inclusion of ancestral populations or their surrogates in the analysis is required by any method of IA estimation to obtain reasonable results.keywords: admixture, EM algorithm, maximum likelihood estimate.

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Section: Simulation 4: Effects Of Ld and Genetic Drift All Simulatiomentioning

confidence: 99%

Estimation of individual admixture: Analytical and study design considerations

Tang

Peng

Wang

et al. 2005

Genetic Epidemiology

617

642

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“…To assess historical genetic connectivity, we estimated the number of migrants per generation from the scaled migration rate, M ¼ 4Nem/h, where m is the migration rate. Time to most recent common ancestor (TMRCA) and effective population size were estimated from the mutation parameter h [Kingman (1982), see also Hein et al (2005)] using a generation time of 20 years (based on flowering time; unpubl. data).…”

Section: Demographic History and Historical Connectivitymentioning

confidence: 99%

A large historical refugium explains spatial patterns of genetic diversity in a Neotropical savanna tree species

Souza

Collevatti

Lima‐Ribeiro

et al. 2016

Ann Bot

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Background and Aims The relative role of Pleistocene climate changes in driving the geographic distribution and genetic diversity of South American species is not well known, especially from open biomes such as the Cerrado, the most diverse tropical savanna, encompassing high levels of endemism. Here the effects of Quaternary climatic changes on demographic history, distribution dynamics and genetic diversity of Dimorphandra mollis, an endemic tree species widely distributed in the Cerrado, were investigated.Methods A total of 38 populations covering most of the distribution of D. mollis were analysed using internal transcribed spacer (ITS) sequences and nuclear microsatellite variation [simple sequence repeats (SSRs)]. The framework incorporated statistical phylogeography, coalescent analyses and ecological niche modelling (ENM).Key Results Different signatures of Quaternary climatic changes were found for ITS sequences and SSRs corresponding to different time slices. Coalescent analyses revealed large and constant effective population sizes, with high historical connectivity among the populations for ITS sequences and low effective population sizes and gene flow with recent population retraction for SSRs. ENMs indicated a slight geographical range retraction during the Last Glacial Maximum. A large historical refugium across central Brazil was predicted. Spatially explicit analyses showed a spatial cline pattern in genetic diversity related to the paleodistribution of D. mollis and to the centre of its historical refugium.Conclusions The complex genetic patterns found in D. mollis are the result of a slight geographical range retraction during the Last Glacial Maximum followed by population expansion to the east and south from a large refugium in the central part of the Cerrado. This historical refugium is coincident with an area predicted to be climatically stable under future climate scenarios. The identified refugium should be given high priority in conservation polices to safeguard the evolutionary potential of the species under predicted future climatic changes.

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“…This model is in turn formally equivalent to a model of coalescing random walks (Holley and Liggett, 1975;Liggett, 1985;Chave et al, 2002), an equivalence that provided the basis for the coalescence theory in genetics (Kingman, 1982). At time t; the voter at site x has a preference passed on through exactly one source or antecedent, for every time t À t5t: Let A x ðtÞ be the position of this antecedent at time t À t; so that A x ð0Þ ¼ x: This is a simple random walk, where the distance jjA x ðtÞ À A x ðt þ 1Þjj 2 travelled at each timestep is 1.…”

Section: Voter Model and The No Speciation Limitmentioning

confidence: 99%