scholarly journals A novel coalescent method insensitive to population structure

2020 ◽  
Author(s):  
Zeqi Yao ◽  
Kehui Liu ◽  
Shanjun Deng ◽  
Xionglei He
Keyword(s):  
Population Structure ◽  
Phylogenetic Tree ◽  
Simulated Data ◽  
Structured Populations ◽  
Population History ◽  
Cell Populations ◽  
Developmental History ◽  
Coalescent Analysis ◽  
History Of ◽  
Larger Sample

AbstractConventional coalescent inferences of population history make the critical assumption that the population under examination is panmictic. However, most populations are structured. This complicates the prevailing coalescent analyses and sometimes leads to inaccurate estimates. To develop a coalescent method unhampered by population structure, we perform two analyses. First, we demonstrate that the coalescent probability of two randomly sampled alleles from the immediate preceding generation (one generation back) is independent of population structure. Second, motivated by this finding, we propose a new coalescent method: i-coalescent analysis. i-coalescent analysis computes the instantaneous coalescent rate (iCR) by using a phylogenetic tree of sampled alleles. Using simulated data, we broadly demonstrate the capability of i-coalescent analysis to accurately reconstruct population size dynamics of highly structured populations, although we find this method often requires larger sample sizes for structured populations than for panmictic populations. Overall, our results indicate i-coalescent analysis to be a useful tool, especially for the inference of population histories with intractable structure such as the developmental history of cell populations in the organs of complex organisms.

scholarly journals Population networks from DNA sequences: methodological developments

2017 ◽  
Author(s):  
B. Schaeffer ◽  
V. Nicolas ◽  
F. Austerlitz ◽  
C. Larédo
Keyword(s):  
Graphical Models ◽  
Dna Sequences ◽  
Genetic Material ◽  
Simulated Data ◽  
Original Method ◽  
Population History ◽  
Data Sets ◽  
Key Factor ◽  
History Of ◽  
Simulated Data Sets

AbstractSeveral classes of methods have been proposed for inferring the history of populations from genetic polymorphism data. As connectivity is a key factor to explain the structure of populations, several graph-based methods have been developed to this aim, using population genetics data. Here we propose an original method based on graphical models that uses DNA sequences to provide relationships between populations. We tested our method on various simulated data sets, describing typical demographic scenarios, for different parameters values. We found that our method behaved noticeably well for realistic demographic evolutionary processes and recovered suitably the migration processes. Our method provides thus a complementary tool for investigating population history based on genetic material.

scholarly journals The story of the lost twins: decoding the genetic identities of the Kumhar and Kurcha populations from the Indian subcontinent

BMC Genetics ◽  
2020 ◽  
Vol 21 (S1) ◽  
Author(s):  
Ranajit Das ◽  
Vladimir A. Ivanisenko ◽  
Anastasia A. Anashkina ◽  
Priyanka Upadhyai
Keyword(s):  
Population Structure ◽  
South India ◽  
Indian Subcontinent ◽  
Uttar Pradesh ◽  
Principal Component ◽  
Population History ◽  
North India ◽  
Geographic Population ◽  
Indian Populations ◽  
History Of

Abstract Background The population structure of the Indian subcontinent is a tapestry of extraordinary diversity characterized by the amalgamation of autochthonous and immigrant ancestries and rigid enforcement of sociocultural stratification. Here we investigated the genetic origin and population history of the Kumhars, a group of people who inhabit large parts of northern India. We compared 27 previously published Kumhar SNP genotype data sampled from Uttar Pradesh in north India to various modern day and ancient populations. Results Various approaches such as Principal Component Analysis (PCA), Admixture, TreeMix concurred that Kumhars have high ASI ancestry, minimal Steppe component and high genomic proximity to the Kurchas, a small and relatively little-known population found ~ 2500 km away in Kerala, south India. Given the same, biogeographical mapping using Geographic Population Structure (GPS) assigned most Kumhar samples in areas neighboring to those where Kurchas are found in south India. Conclusions We hypothesize that the significant genomic similarity between two apparently distinct modern-day Indian populations that inhabit well separated geographical areas with no known overlapping history or links, likely alludes to their common origin during or post the decline of the Indus Valley Civilization (estimated by ALDER). Thereafter, while they dispersed towards opposite ends of the Indian subcontinent, their genomic integrity and likeness remained preserved due to endogamous social practices. Our findings illuminate the genomic history of two Indian populations, allowing a glimpse into one or few of numerous of human migrations that likely occurred across the Indian subcontinent and contributed to shape its varied and vibrant evolutionary past.

Sister species, different histories: comparative phylogeography of two bird species associated with Amazonian open vegetation

2020 ◽  
Vol 132 (1) ◽  
pp. 161-173
Author(s):  
Camila D Ritter ◽  
Laís A Coelho ◽  
João Mg Capurucho ◽  
Sergio H Borges ◽  
Cíntia Cornelius ◽  
...  
Keyword(s):  
Population Structure ◽  
Bird Species ◽  
Population History ◽  
Sister Species ◽  
White Sand ◽  
Migration Rates ◽  
History Of ◽  
The Last Glacial Maximum ◽  
Vegetation Patches ◽  
The Last Glacial

Abstract Although the expansion of open vegetation within Amazonia was the basis for the Forest Refugia hypothesis, studies of Amazonian biota diversification have focussed mostly on forest taxa. Here we compare the phylogeographic patterns and population history of two sister species associated with Amazonian open-vegetation patches, Elaenia cristata and Elaenia ruficeps (Aves: Tyrannidae). We sampled individuals across Amazonia for both species, and in the central Brazilian savannas (Cerrado) for E. cristata. We sequenced one mitochondrial (ND2) and two nuclear (BFib7 and ACO) markers. We tested for population structure, estimated migration rates and elucidated the historical demography of each species. The Amazon River is the strongest barrier for E. ruficeps and the Branco River is a secondary barrier. For the more broadly distributed E. cristata, there was no discernible population structure. Both species attained their current genetic diversity recently and E. cristata has undergone demographic expansion since the Last Glacial Maximum, The results suggest distinct effects of recent landscape change on population history for the two species. E. ruficeps, which only occurs in Amazonian white sand habitats, has been more isolated in open-vegetation patches than E. cristata, which occupies Amazonian savannas, and extends into the Central Brazilian Cerrado.

Inferring the Population History of an Epidemic from a Phylogenetic Tree

1996 ◽  
Vol 182 (2) ◽  
pp. 173-178 ◽  
Author(s):  
Chi-Keong Ong ◽  
Sean Nee ◽  
Andrew Rambaut ◽  
Paul H. Harvey
Keyword(s):  
Phylogenetic Tree ◽  
Population History ◽  
History Of

scholarly journals Inferring number of populations and changes in connectivity under the n-island model

Heredity ◽  
2021 ◽  
Author(s):  
Armando Arredondo ◽  
Beatriz Mourato ◽  
Khoa Nguyen ◽  
Simon Boitard ◽  
Willy Rodríguez ◽  
...  
Keyword(s):  
Population Structure ◽  
Gene Flow ◽  
Population Size ◽  
Demographic History ◽  
Simulated Data ◽  
Fixed Number ◽  
Ancestral Population ◽  
Demographic Model ◽  
History Of ◽  
Time Periods

AbstractInferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, ignoring population structure. Alternatively, when structure is assumed, it is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate). The IICR can be estimated for a single diploid individual using the PSMC method of Li and Durbin (2011). For an isolated panmictic population, the IICR matches the population size history, and this is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme with limited connection to population size changes. Our method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise stationary symmetrical island models. In our models we assume a fixed number of time periods during which gene flow is constant, but gene flow is allowed to change between time periods. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.

scholarly journals The complex admixture history and recent southern origins of Siberian populations

2015 ◽  
Author(s):  
Irina Pugach ◽  
Rostislav Matveev ◽  
Viktor Spitsyn ◽  
Sergey Makarov ◽  
Innokentiy Novgorodov ◽  
...  
Keyword(s):  
Early Stage ◽  
Simulated Data ◽  
Population History ◽  
Population Replacement ◽  
The North ◽  
Complex Population ◽  
Shared Ancestry ◽  
History Of ◽  
Different Populations ◽  
The Last Glacial

Although Siberia was inhabited by modern humans at an early stage, there is still debate over whether this area remained habitable during the extremely cold period of the Last Glacial Maximum or whether it was subsequently repopulated by peoples with a recent shared ancestry. Previous studies of the genetic history of Siberian populations were hampered by the extensive admixture that appears to have taken place among these populations, since commonly used methods assume a tree-like population history and at most single admixture events. We therefore developed a new method based on the covariance of ancestry components, which we validated with simulated data, in order to investigate this potentially complex admixture history and to distinguish the effects of shared ancestry from prehistoric migrations and contact. We furthermore adapted a previously devised method of admixture dating for use with multiple events of gene flow, and applied these methods to whole-genome genotype data from over 500 individuals belonging to 20 different Siberian ethnolinguistic groups. The results of these analyses indicate that there have indeed been multiple layers of admixture detectable in most of the Siberian populations, with considerable differences in the admixture histories of individual populations, and with the earliest events dated to not more than 4500 years ago. Furthermore, most of the populations of Siberia included here, even those settled far to the north, can be shown to have a southern origin. These results provide support for a recent population replacement in this region, with the northward expansions of different populations possibly being driven partly by the advent of pastoralism, especially reindeer domestication. These newly developed methods to analyse multiple admixture events should aid in the investigation of similarly complex population histories elsewhere.

scholarly journals Inferring number of populations and changes in connectivity under the n-island model

2020 ◽  
Author(s):  
Armando Arredondo ◽  
Beatriz Mourato ◽  
Khoa Nguyen ◽  
Simon Boitard ◽  
Willy Rodríguez ◽  
...  
Keyword(s):  
Population Structure ◽  
Demographic History ◽  
A Priori ◽  
Simulated Data ◽  
Fixed Number ◽  
Ancestral Population ◽  
Demographic Model ◽  
Automated Method ◽  
History Of ◽  
Diploid Individual

AbstractInferring the demographic history of species is one of the greatest challenges in populations genetics. This history is often represented as a history of size changes, thus ignoring population structure. Alternatively, structure is defined a priori as a population tree and not inferred. Here we propose a framework based on the IICR (Inverse Instantaneous Coalescence Rate), which can be estimated using the PSMC method of Li and Durbin (2011) for a single diploid individual. For an isolated population, the IICR matches the population size history, which is how the PSMC outputs are generally interpreted. However, it is increasingly acknowledged that the IICR is a function of the demographic model and sampling scheme. Our automated method fits observed IICR curves of diploid individuals with IICR curves obtained under piecewise-stationary symmetrical island models, in which we assume a fixed number of time periods during which gene flow is constant. We infer the number of islands, their sizes, the periods at which connectivity changes and the corresponding rates of connectivity. Validation with simulated data showed that the method can accurately recover most of the scenario parameters. Our application to a set of five human PSMCs yielded demographic histories that are in agreement with previous studies using similar methods and with recent research suggesting ancient human structure. They are in contrast with the widely accepted view of human evolution consisting of one ancestral population branching into three large continental and panmictic populations with varying degrees of connectivity and no population structure within each continent.

Population Structure and Population History of Anopheles dirus Mosquitoes in Southeast Asia

2000 ◽  
Vol 17 (6) ◽  
pp. 962-974 ◽  
Author(s):  
Catherine Walton ◽  
Jane M. Handley ◽  
Willoughby Tun-Lin† ◽  
Frank H. Collins ◽  
Ralph E. Harbach ◽  
...  
Keyword(s):  
Population Structure ◽  
Southeast Asia ◽  
Population History ◽  
Anopheles Dirus ◽  
History Of

scholarly journals Unraveling the population history of Indian Siddis

2017 ◽  
Author(s):  
Ranajit Das ◽  
Priyanka Upadhyai
Keyword(s):  
Population Structure ◽  
Genetic Relatedness ◽  
Population History ◽  
Sub Saharan Africa ◽  
European Ancestry ◽  
Migration Routes ◽  
East African ◽  
North East ◽  
History Of ◽  
Sub Saharan

AbstractThe Siddis are a unique Indian tribe of African, South Asian and European ancestry. While their ancestral origins have been traced to the Bantu populations from sub-Saharan Africa, their population history has remained an enigmatic question. Here, we have traced the biogeographical origin of the Siddis employing an admixture based algorithm, Geographical Population Structure (GPS). We evaluated 14 Siddi genomes in reference to 5 African populations from the 1000 Genomes project and 7 Bantu populations from the Human Genome Diversity project. GPS assigned the Siddi genomes to west Zambia and the present-day border between Zimbabwe and northeastern Botswana, overlapping with one of the principal areas of secondary Bantu settlement in Africa, ~1700 years before present (YBP). This is concordant with the secondary Bantu dispersal route from the east African Bantu center that brought the African ancestors of the Siddis to settlement sites in southeast Africa, from where they were disseminated to India, by the Portuguese. Our results also suggest that while the Siddi genomes are significantly different from that of the Bantus, they displayed the highest genomic proximity to the Luhyas and North-East Bantus from Kenya, and that ancestral Siddis are likely to have split from the Luhyas, ~2700 YBP, in congruence with known Bantu expansion and population migration routes. Together with historical, linguistic and anthropological evidences our findings shine light on the genetic relatedness between populations, fine-scale population structure and recapitulate the population history of the Siddis, in the ethnohistorical context of India.

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