scholarly journals An Efficient Algorithm for Estimating Population History from Genetic Data

2021 ◽  
Author(s):  
Alan R. Rogers

AbstractLegofit is a statistical package that uses genetic data to estimate the history of population size, subdivision, and admixture. This article describes a new deterministic algorithm, which makes Legofit orders of magnitude faster and more accurate.

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1236
Author(s):  
Elisabeth Hempel ◽  
Michael V. Westbury ◽  
José H. Grau ◽  
Alexandra Trinks ◽  
Johanna L. A. Paijmans ◽  
...  

Since the 19th century, the addax (Addax nasomaculatus) has lost approximately 99% of its former range. Along with its close relatives, the blue antelope (Hippotragus leucophaeus) and the scimitar-horned oryx (Oryx dammah), the addax may be the third large African mammal species to go extinct in the wild in recent times. Despite this, the evolutionary history of this critically endangered species remains virtually unknown. To gain insight into the population history of the addax, we used hybridization capture to generate ten complete mitochondrial genomes from historical samples and assembled a nuclear genome. We found that both mitochondrial and nuclear diversity are low compared to other African bovids. Analysis of mitochondrial genomes revealed a most recent common ancestor ~32 kya (95% CI 11–58 kya) and weak phylogeographic structure, indicating that the addax likely existed as a highly mobile, panmictic population across its Sahelo–Saharan range in the past. PSMC analysis revealed a continuous decline in effective population size since ~2 Ma, with short intermediate increases at ~500 and ~44 kya. Our results suggest that the addax went through a major bottleneck in the Late Pleistocene, remaining at low population size prior to the human disturbances of the last few centuries.


2017 ◽  
Author(s):  
John Hawks

AbstractHuman populations have a complex history of introgression and of changing population size. Human genetic variation has been affected by both these processes, so that inference of past population size depends upon the pattern of gene flow and introgression among past populations. One remarkable aspect of human population history as inferred from genetics is a consistent “wave” of larger effective population size, prior to the bottlenecks and expansions of the last 100,000 years. Here I carry out a series of simulations to investigate how introgression and gene flow from genetically divergent ancestral populations affect the inference of ancestral effective population size. Both introgression and gene flow from an extinct, genetically divergent population consistently produce a wave in the history of inferred effective population size. The time and amplitude of the wave reflect the time of origin of the genetically divergent ancestral populations and the strength of introgression or gene flow. These results demonstrate that even small fractions of introgression or gene flow from ancient populations may have large effects on the inference of effective population size.


2005 ◽  
Vol 15 (2) ◽  
pp. 193-223 ◽  
Author(s):  
Clive Gamble ◽  
William Davies ◽  
Paul Pettitt ◽  
Lee Hazelwood ◽  
Martin Richards

This article presents the initial results from the S2AGES data base of calibrated radiocarbon estimates from western Europe in the period 25,000–10,000 years ago. Our aim is to present a population history of this sub-continental region by providing a chronologically-secure framework for the interpretation of data from genetics and archaeology. In particular, we define five population events in this period, using dates-as-data, and examine the implications for the archaeology of Late Glacial colonization. We contrast this detailed regional approach to the larger project which we call the cognitive origins synthesis that includes historical linguistics in the reconstruction of population history. We conclude that only archaeology can currently provide the framework for population history and the evaluation of genetic data. Finally, if progress is to be made in the new interdisciplinary field of population history then both disciplines need to refrain from inappropriate agricultural thinking that fosters distorting models of European prehistory, and they should also pay less, if any, attention to historical linguistics.With comments from L.G. Straus, J.-P. Bocquet-Appel, P.A. Underhill & R. Housley and followed by a reply from the author.


2014 ◽  
Author(s):  
Olivier Mazet ◽  
Willy Rodríguez ◽  
Lounès Chikhi

The rapid development of sequencing technologies represents new opportunities for population genetics research. It is expected that genomic data will increase our ability to reconstruct the history of populations. While this increase in genetic information will likely help biologists and anthropologists to reconstruct the demographic history of populations, it also represents new challenges. Recent work has shown that structured populations generate signals of population size change. As a consequence it is often difficult to determine whether demographic events such as expansions or contractions (bottlenecks) inferred from genetic data are real or due to the fact that populations are structured in nature. Given that few inferential methods allow us to account for that structure, and that genomic data will necessarily increase the precision of parameter estimates, it is important to develop new approaches. In the present study we analyse two demographic models. The first is a model of instantaneous population size change whereas the second is the classical symmetric island model. We (i) re-derive the distribution of coalescence times under the two models for a sample of size two, (ii) use a maximum likelihood approach to estimate the parameters of these models (iii) validate this estimation procedure under a wide array of parameter combinations, (iv) implement and validate a model choice procedure by using a Kolmogorov-Smirnov test. Altogether we show that it is possible to estimate parameters under several models and perform efficient model choice using genetic data from a single diploid individual.


2020 ◽  
Vol 51 (9) ◽  
Author(s):  
Iván de la Hera ◽  
Jordi Gómez ◽  
Eileen Dillane ◽  
Azaitz Unanue ◽  
Antón Pérez‐Rodríguez ◽  
...  

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