Biology subjects

Kai Yuan

Publications and source records attributed to Kai Yuan.

3 recordsLinked to original sources

bioRxiv2016

AdmixSim: A Forward-Time Simulator for Various and Complex Scenarios of Population Admixture

BackgroundPopulation admixture has been a common phenomenon in human, animals and plants, and plays a very important role in shaping individual genetic architecture and population genetic diversity. Inference of population admixture, however, is challenging and typically relies on in silico simulation. We are aware of the lack of a computer tool for such a purpose, especially a simulator is not available for generating data under various and complex admixture scenarios.\n\nResultsHere we developed a forward-time simulator (AdmixSim) under standard Wright Fisher model, which can simulate admixed populations with: 1) multiple ancestral populations; 2) multiple waves of admixture events; 3) fluctuating population size; and 4) fluctuating admixture proportions. Results of analysis of the simulated data by AdmixSim show that our simulator can fast and accurately generate data resemble real one. We included in AdmixSim all possible parameters that allow users to modify and simulate any kinds of admixture scenarios easily so that it is very flexible. AdmixSim records recombination break points and trace of each chromosomal segment from different ancestral populations, with which users can easily do further analysis and comparative studies with empirical data.\n\nConclusionsAdmixSim is expected to facilitate the study of population admixture by providing a simulation framework with flexible implementation of various admixture models and parameters.

Bioinformatics↗

bioRxiv2015

Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with multiple exponential functions

Admixture-introduced linkage disequilibrium (LD) has recently been introduced into the inference of the histories of complex admixtures. However, the influence of ancestral source populations on the LD pattern in admixed populations is not properly taken into consideration by currently available methods, which affects the estimation of several gene flow parameters from empirical data. We first illustrated the dynamic changes of LD in admixed populations and mathematically formulated the LD under a generalized admixture model with finite population size. We next developed a new method, MALDmef, by fitting LD with multiple exponential functions for inferring and dating multiple-wave admixtures. MALDmef takes into account the effects of source populations which substantially affect modeling LD in admixed population, which renders it capable of efficiently detecting and dating multiple-wave admixture events. The performance of MALDmef was evaluated by simulation and it was shown to be more accurate than MALDER, a state-of-the-art method that was recently developed for similar purposes, under various admixture models. We further applied MALDmef to analyzing genome-wide data from the Human Genome Diversity Project (HGDP) and the HapMap Project. Interestingly, we were able to identify more than one admixture events in several populations, which have yet to be reported. For example, two major admixture events were identified in the Xinjiang Uyghur, occurring around 27-30 generations ago and 182-195 generations ago, respectively. In an African population (MKK), three recent major admixtures occurring 13-16, 50-67, and 107-139 generations ago were detected. Our method is a considerable improvement over other current methods and further facilitates the inference of the histories of complex population admixtures.

Evolutionary Biology↗

bioRxiv2015

Length Distribution of Ancestral Tracks under a General Admixture Model and Its Applications in Population History Inference

As a chromosome is sliced into pieces by recombination after entering an admixed population, ancestral tracks of chromosomes are shortened with the pasting of generations. The length distribution of ancestral tracks reflects information of recombination and thus can be used to infer the histories of admixed populations. Previous studies have shown that inference based on ancestral tracks is powerful in recovering the histories of admixed populations. However, population histories are always complex, and previous studies only deduced the length distribution of ancestral tracks under very simple admixture models. The deduction of length distribution of ancestral tracks under a more general model will greatly elevate the power in inferring population histories. Here we first deduced the length distribution of ancestral tracks under a general model in an admixed population, and proposed general principles in parameter estimation and model selection with the length distribution. Next, we focused on studying the length distribution of ancestral tracks and its applications under three typical admixture models, which were all special cases of our general model. Extensive simulations showed that the length distribution of ancestral tracks was well predicted by our theoretical models. We further developed a new method based on the length distribution of ancestral tracks and good performance was observed when it was applied in inferring population histories under the three typical models. Notably, our method was insensitive to demographic history, sample size and threshold to discard short tracks. Finally, we applied our method in African Americans and Mexicans from the HapMap dataset, and several South Asian populations from the Human Genome Diversity Project dataset. The results showed that the histories of African Americans and Mexicans matched the historical records well, and the population admixture history of South Asians was very complex and could be traced back to around 100 generations ago.

Genetics↗