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Zhu, S. J.

Publications and source records attributed to Zhu, S. J..

3 recordsLinked to original sources

Ancient admixture into Africa from the ancestors of non-Africans

Genetic diversity across human populations has been shaped by demographic history, making it possible to infer past demographic events from extant genomes. However, demographic inference in the ancient past is difficult, particularly around the out-of-Africa event in the Late Middle Paleolithic, a period of profound importance to our species history. Here we present SMCSMC, a Bayesian method for inference of time-varying population sizes and directional migration rates under the coalescent-with-recombination model, to study ancient demographic events. We find evidence for substantial migration from the ancestors of present-day Eurasians into African groups between 40 and 70 thousand years ago, predating the divergence of Eastern and Western Eurasian lineages. This event accounts for previously unexplained genetic diversity in African populations, and supports the existence of novel population substructure in the Late Middle Paleolithic. Our results indicate that our species demographic history around the out-of-Africa event is more complex than previously appreciated.

genomics↗

The origins and relatedness structure of mixed infections vary with local prevalence of P. falciparum malaria

Individual malaria infections can carry multiple strains of Plasmodium falciparum with varying levels of relatedness. Yet, how local epidemiology affects the properties of such mixed infections remains unclear. Here, we develop an enhanced method for strain deconvolution from genome sequencing data, which estimates the number of strains, their proportions, identity-by-descent (IBD) profiles and individual haplotypes. Applying it to the Pf3k data set, we find that the rate of mixed infection varies from 29% to 63% across countries and that 51% of mixed infections involve more than two strains. Further-more, we estimate that 47% of symptomatic dual infections contain sibling strains likely to have been co-transmitted from a single mosquito, and find evidence of mixed infections propagated over successive infection cycles. Finally, leveraging data from the Malaria Atlas Project, we find that prevalence correlates within Africa, but not Asia, with both the rate of mixed infection and the level of IBD.

epidemiology↗

Deconvoluting multiple infections in Plasmodium falciparum from high throughput sequencing data

MotivationThe presence of multiple infecting strains of the malarial parasite Plasmodium falciparum affects key phenotypic traits, including drug resistance and risk of severe disease. Advances in protocols and sequencing technology have made it possible to obtain high-coverage genome-wide sequencing data from blood samples and blood spots taken in the field. However, analysing and interpreting such data is challenging because of the high rate of multiple infections present.\n\nResultsWe have developed a statistical method and implementation for deconvolving multiple genome sequences present in an individual with mixed infections. The software package DEploid uses haplotype structure within a reference panel of clonal isolates as a prior for haplotypes present in a given sample. It estimates the number of strains, their relative proportions and the haplotypes presented in a sample, allowing researchers to study multiple infection in malaria with an unprecedented level of detail.\n\nAvailability and implementationThe open source implementation DEploid is freely available at https://github.com/mcveanlab/DEploid under the conditions of the GPLv3 license. An R version is available at https://github.com/mcveanlab/DEploid-r.\n\nContactjoe.zhu@well.ox.ac.uk or mcvean@well.ox.ac.uk

bioinformatics↗