Biology subjects

Shchur, V.

Publications and source records attributed to Shchur, V..

7 recordsLinked to original sources

bioRxiv2025

An archaic reference-free method to jointly infer Neanderthal and Denisovan introgressed segments in modern human genomes

Admixture between populations is a common feature of human history. Admixture events introduce new genetic variation that can fuel evolution. Characterizing the significance of admixture events on the evolution of a population across various species is of great interest to evolutionary geneticists. Local Ancestry Inference (LAI) methods infer genetic ancestry of an individual at a particular chromosomal location. Certain methods specialize in detecting archaic introgression, which consists of interbreeding between modern and archaic humans like Neanderthals and Denisovans. Most current LAI methods allow the detection of a single archaic ancestry, and post-processing may distinguish between multiple waves of introgression. These methods vary in how they choose archaic or modern reference genomes for the inference. Here, we present a new HMM-based method (DAIseg), which has the advantage of simultaneously distinguishing between multiple waves of ancient and recent admixture, using only modern human reference genomes. Simulations demonstrate that DAIseg achieves higher overall performance than state-of-the-art methods. We also apply DAIseg to Papuan populations to jointly detect Denisovan and Neanderthal introgressed segments, and identify a higher number of archaic segments than previous methods. Analysis of inferred introgressed segments, shows that we can identify evidence for two Denisovan introgression events in Papuans without having any post-processing and filtering. Overall, on top of being able to deal with both Archaic and recent admixture, DAIseg provides a more principled approach for detecting and classifying Denisovan and Neanderthal segments which will improve downstream analysis of introgressed segments to infer the impact of archaic introgression in humans.

bioinformatics↗

bioRxiv2022

Estimating population split times and migration rates from historical effective population sizes

The estimation of effective population sizes (Ne) through time is of fundamental interest in population genetics, but the interpretation of Ne as the effective number of breeding individuals in the population is challenged by the effect of population structure. In fact, variation in Ne reported in many studies may be a consequence of changes in migration rates between populations rather than changes in actual population size. We address this long-standing problem here by constructing joint models of population size changes, migration, and divergence that can adjust temporal estimates of Ne and estimate the actual Ne of a local deme connected to another population through migration. We also develop a method for estimating divergence times and migration rates taking into account complex scenarios of changing population sizes. We apply the method to previously published data from humans, and show that, when taking migration and changes in Ne into account, the estimated divergence between the San and Dinka populations is approximately 108 kya, and not 255 kya as reported in a previous study. Using simulations, we demonstrate that the previously reported and surprisingly old estimates of divergence between San and Dinka is in fact caused by a quantifiable estimation bias due to changes in Ne through time.

evolutionary biology↗

bioRxiv2021

Genomic insights into the recent population history of Mapuche Native Americans

The last few years have witnessed an explosive generation of genomic data from ancient and modern Native American populations. These data shed light on key demographic shifts that occurred in geographically diverse territories of South America, such as the Andean highlands, Southern Patagonia and the Amazon basin. We used genomic data to study the recent population history of the Mapuche, who are the major Native population from the Southern Cone (Chile and Argentina). We found evidence of specific shared genetic ancestry between the Mapuche and ancient populations from Southern Patagonia, Central Chile and the Argentine Pampas. Despite previous evidence of cultural influence of Inca and Tiwanaku polities over the Mapuche, we did not find evidence of specific shared ancestry between them, nor with Amazonian groups. We estimated the effective population size dynamics of the Mapuche ancestral population during the last millennia, identifying a population bottle-neck around 1650 AD, coinciding with a period of Spaniards invasions into the territory inhabited by the Mapuche. Finally, we show that admixed Chileans underwent post-admixture adaptation in their Mapuche subancestry component in genes related with lipid metabolism, suggesting adaptation to scarce food availability.

genetics↗

bioRxiv2020

Inferring Adaptive Introgression Using Hidden Markov Models

Adaptive introgression - the flow of adaptive genetic variation between species or populations - has attracted significant interest in recent years and it has been implicated in a number of cases of adaptation, from pesticide resistance and immunity, to local adaptation. Despite this, methods for identification of adaptive introgression from population genomic data are lacking. Here, we present Ancestry_HMM-S, a Hidden Markov Model based method for identifying genes undergoing adaptive introgression and quantifying the strength of selection acting on them. Through extensive validation, we show that this method performs well on moderately sized datasets for realistic population and selection parameters. We apply Ancestry_HMM-S to a dataset of an admixed Drosophila melanogaster population from South Africa and we identify 17 loci which show signatures of adaptive introgression, four of which have previously been shown to confer resistance to insecticides. Ancestry_HMM-S provides a powerful method for inferring adaptive introgression in datasets that are typically collected when studying admixed populations. This method will enable powerful insights into the genetic consequences of admixture across diverse populations. Ancestry_HMM-S can be downloaded from https://github.com/jesvedberg/Ancestry_HMM-S/.

evolutionary biology↗

bioRxiv2019

On the distribution of tract lengths during adaptive introgression

Admixture is increasingly being recognized as an important factor in evolutionary genetics. The distribution of genomic admixture tracts, and the resulting effects on admixture linkage disequilibrium, can be used to date the timing of admixture between species or populations. However, the theory used for such prediction assumes selective neutrality despite the fact that many famous examples of admixture involve natural selection acting for or against admixture. In this paper, we investigate the effects of positive selection on the distribution of tract lengths. We develop a theoretical framework that relies on approximating the trajectory of the selected allele using a logistic function. By numerically calculating the expected allele trajectory, we also show that the approach can be extended to cases where the logistic approximation is poor due to the effects of genetic drift. Using simulations, we show that the model is highly accurate under most scenarios. We use the model to show that positive selection on average will tend to increase the admixture tract length. However, perhaps counter-intuitively, conditional on the allele frequency at the time of sampling, positive selection will actually produce shorter expected tract lengths. We discuss the consequences of our results in interpreting the timing of the introgression of EPAS1 from Denisovans into the ancestors of Tibetans.

genomics↗

bioRxiv2019

Fast and scalable genome-wide inference of local tree topologies from large number of haplotypes based on tree consistent PBWT data structure

Estimation of the relationship between DNA sequences is one of the most important problems in genomics. Understanding these relationships is central to demographic inference, correction of population structure in GWAS, identifying signals of selection etc. The data structure containing the full information about sample genealogy is called the ancestral recombination graph (ARG). However, ARG inference is a very difficult problem, not least due to a very complex state space. In this work we describe a new approach for fast and scalable generation of local tree topologies relating large numbers of haplotypes. Our method is closely related to the estimation of ARG, and captures both local and global properties of an ARG. It is based on a data structure which we call tree consistent PBWT, a modification of PBWT data structure introduced by R. Durbin (2014). We also explore some methods to estimate the quality of the generated tree topologies and to make inferences based on them. At the end we discuss a probabilistic model which could potentially lead to the estimation of ARG node times.

genomics↗

bioRxiv2017

On The Number Of Siblings And p-th Cousins In A Large Population Sample

1.The number of individuals in a random sample with close relatives in the sample is a quantity of interest when designing Genome Wide Association Studies (GWAS) and other cohort based genetic, and non-genetic, studies. In this paper, we develop expressions for the distribution and expectation of the number of p-th cousins in a sample from a population of size N under two diploid Wright-Fisher models. We also develop simple asymptotic expressions for large values of N. For example, the expected proportion of individuals with at least one p-th cousin in a sample of K individuals, for a diploid dioecious Wright-Fisher model, is approximately 1 - e-(22p-1)K/N. Our results show that a substantial fraction of individuals in the sample will have at least a second cousin if the sampling fraction (K/N) is on the order of 10-2. This confirms that, for large cohort samples, relatedness among individuals cannot easily be ignored.

evolutionary biology↗