scholarly journals Estimating Ancestral Population Parameters

Genetics ◽  
1997 ◽  
Vol 145 (3) ◽  
pp. 847-855 ◽  
Author(s):  
John Wakeley ◽  
Jody Hey

The expected numbers of different categories of polymorphic sites are derived for two related models of population history: the isolation model, in which an ancestral population splits into two descendents, and the size-change model, in which a single population undergoes an instantaneous change in size. For the isolation model, the observed numbers of shared, fixed, and exclusive polymorphic sites are used to estimate the relative sizes of the three populations, ancestral plus two descendent, as well as the time of the split. For the size-change model, the numbers of sites segregating at particular frequencies in the sample are used to estimate the relative sizes of the ancestral and descendent populations plus the time the change took place. Parameters are estimated by choosing values that most closely equate expectations with observations. Computer simulations show that current and historical population parameters can be estimated accurately. The methods are applied to DNA data from two species of Drosophila and to some human mitochondrial DNA sequences.

2017 ◽  
Vol 4 (3) ◽  
pp. 443-455 ◽  
Author(s):  
Vikram Kapoor ◽  
◽  
Michael Elk ◽  
Carlos Toledo-Hernandez ◽  
Jorge W. Santo Domingo ◽  
...  

2016 ◽  
Vol 36 (1) ◽  
Author(s):  
Paola Berchialla

We introduce a Bayesian hierarchical model for mitochondrial DNA sequence data, which is fitted via acceptance-rejection algorithms. The model incorporates parametric models of population history explicitly as well as a mutational process allowing for a simultaneous parameter estimation whose importance has become increasingly clear in many recent studies. The model is applied to a sample of DNA sequences from the Italian population.


Genetics ◽  
1994 ◽  
Vol 136 (2) ◽  
pp. 673-683 ◽  
Author(s):  
P Marjoram ◽  
P Donnelly

Abstract We consider the effect on the distribution of pairwise differences between mitochondrial DNA sequences of the incorporation into the underlying population genetics model of two particular effects that seem realistic for human populations. The first is that the population size was roughly constant before growing to its current level. The second is that the population is geographically subdivided rather than panmictic. In each case these features tend to encourage multimodal distributions of pairwise differences, in contrast to existing, unimodal datasets. We argue that population genetics models currently used to analyze such data may thus fail to reflect important features of human mitochondrial DNA evolution. These may include selection on the mitochondrial genome, more realistic mutation mechanisms, or special population or migration dynamics. Particularly in view of the variability inherent in the single available human mitochondrial genealogy, it is argued that until these effects are better understood, inferences from such data should be rather cautious.


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