Tracking human population structure through time from whole genome sequences

AbstractThe genetic diversity of humans, like many species, has been shaped by a complex pattern of population separations followed by isolation and subsequent admixture. This pattern, reaching at least as far back as the appearance of our species in the paleontological record, has left its traces in our genomes. Reconstructing a population’s history from these traces is a challenging problem. Here we present a novel approach based on the Multiple Sequentially Markovian Coalescent (MSMC) to analyse the population separation history. Our approach, called MSMC-IM, uses an improved implementation of the MSMC (MSMC2) to estimate coalescence rates within and across pairs of populations, and then fits a continuous Isolation-Migration model to these rates to obtain a time-dependent estimate of gene flow. We show, using simulations, that our method can identify complex demographic scenarios involving post-split admixture or archaic introgression. We apply MSMC-IM to whole genome sequences from 15 worldwide populations, tracking the process of human genetic diversification. We detect traces of extremely deep ancestry between some African populations, with around 1% of ancestry dating to divergences older than a million years ago.Author SummaryHuman demographic history is reflected in specific patterns of shared mutations between the genomes from different populations. Here we aim to unravel this pattern to infer population structure through time with a new approach, called MSMC-IM. Based on estimates of coalescence rates within and across populations, MSMC-IM fits a time-dependent migration model to the pairwise rate of coalescences. We implemented this approach as an extension to existing software (MSMC2), and tested it with simulations exhibiting different histories of admixture and gene flow. We then applied it to the genomes from 15 worldwide populations to reveal their pairwise separation history ranging from a few thousand up to several million years ago. Among other results, we find evidence for remarkably deep population structure in some African population pairs, suggesting that deep ancestry dating to one million years ago and older is still present in human populations in small amounts today.

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Faculty Opinions recommendation of Inference of human population history from individual whole-genome sequences.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.11961958.13876055 ◽

2011 ◽

Author(s):

Austin Hughes

Keyword(s):

Human Population ◽

Population History ◽

Whole Genome ◽

Genome Sequences

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An African origin for Mycobacterium bovis

Evolution Medicine and Public Health ◽

10.1093/emph/eoaa005 ◽

2020 ◽

Vol 2020 (1) ◽

pp. 49-59 ◽

Cited By ~ 4

Author(s):

Chloé Loiseau ◽

Fabrizio Menardo ◽

Abraham Aseffa ◽

Elena Hailu ◽

Balako Gumi ◽

...

Keyword(s):

Population Structure ◽

West Africa ◽

Mycobacterium Bovis ◽

Evolutionary History ◽

Whole Genome ◽

Genome Sequences ◽

The World ◽

History Of ◽

Global Population ◽

Different Parts

Abstract Background and objectives Mycobacterium bovis and Mycobacterium caprae are two of the most important agents of tuberculosis in livestock and the most important causes of zoonotic tuberculosis in humans. However, little is known about the global population structure, phylogeography and evolutionary history of these pathogens. Methodology We compiled a global collection of 3364 whole-genome sequences from M.bovis and M.caprae originating from 35 countries and inferred their phylogenetic relationships, geographic origins and age. Results Our results resolved the phylogenetic relationship among the four previously defined clonal complexes of M.bovis, and another eight newly described here. Our phylogeographic analysis showed that M.bovis likely originated in East Africa. While some groups remained restricted to East and West Africa, others have subsequently dispersed to different parts of the world. Conclusions and implications Our results allow a better understanding of the global population structure of M.bovis and its evolutionary history. This knowledge can be used to define better molecular markers for epidemiological investigations of M.bovis in settings where whole-genome sequencing cannot easily be implemented. Lay summary During the last few years, analyses of large globally representative collections of whole-genome sequences (WGS) from the human-adapted Mycobacterium tuberculosis complex (MTBC) lineages have enhanced our understanding of the global population structure, phylogeography and evolutionary history of these pathogens. In contrast, little corresponding data exists for M. bovis, the most important agent of tuberculosis in livestock. Using whole-genome sequences of globally distributed M. bovis isolates, we inferred the genetic relationships among different M. bovis genotypes distributed around the world. The most likely origin of M. bovis is East Africa according to our inferences. While some M. bovis groups remained restricted to East and West Africa, others have subsequently dispersed to different parts of the world driven by cattle movements.

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Precise prediction of antibiotic resistance in Escherichia coli from full genome sequences

10.1101/338194 ◽

2018 ◽

Cited By ~ 2

Author(s):

Danesh Moradigaravand ◽

Martin Palm ◽

Anne Farewell ◽

Ville Mustonen ◽

Jonas Warringer ◽

...

Keyword(s):

Machine Learning ◽

Antibiotic Resistance ◽

Population Structure ◽

Genome Sequencing ◽

Diagnostic Tools ◽

Clinical Settings ◽

Whole Genome ◽

Genome Sequences ◽

E Coli ◽

Resistant Strains

AbstractThe emergence of microbial antibiotic resistance is a global health threat. In clinical settings, the key to controlling spread of resistant strains is accurate and rapid detection. As traditional culture-based methods are time consuming, genetic approaches have recently been developed for this task. The diagnosis is typically made by measuring a few known determinants previously identified from whole genome sequencing, and thus is restricted to existing information on biological mechanisms. To overcome this limitation, we employed machine learning models to predict resistance to 11 compounds across four classes of antibiotics from existing and novel whole genome sequences of 1936 E. coli strains. We considered a range of methods, and examined population structure, isolation year, gene content, and polymorphism information as predictors. Gradient boosted decision trees consistently outperformed alternative models with an average F1 score of 0.88 on held-out data (range 0.66-0.96). While the best models most frequently employed all inputs, an average F1 score of 0.73 could be obtained using population structure information alone. Single nucleotide variation data were less useful, and failed to improve prediction for ten out of 11 antibiotics. These results demonstrate that antibiotic resistance in E. coli can be accurately predicted from whole genome sequences without a priori knowledge of mechanisms, and that both genomic and epidemiological data are informative. This paves way to integrating machine learning approaches into diagnostic tools in the clinic.SummaryOne of the major health threats of 21st century is emergence of antibiotic resistance. To manage its economic impact, efforts are made to develop novel diagnostic tools that rapidly detect resistant strains in clinical settings. In our study, we employed a range machine learning tools to predict antibiotic resistance from whole genome sequencing data for E. coli. We used the presence or absence of genes, population structure and isolation year of isolates as predictors, and could attain average precision of 0.93 and recall of 0.83, without prior knowledge about the causal mechanisms. These results demonstrate the potential application of machine learning methods as a diagnostic tool in healthcare settings.

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An African origin for Mycobacterium bovis

10.1101/773192 ◽

2019 ◽

Cited By ~ 1

Author(s):

Chloé Loiseau ◽

Fabrizio Menardo ◽

Abraham Aseffa ◽

Elena Hailu ◽

Balako Gumi ◽

...

Keyword(s):

Population Structure ◽

Mycobacterium Bovis ◽

Evolutionary History ◽

Whole Genome ◽

African Origin ◽

Genome Sequences ◽

Geographic Origins ◽

History Of ◽

Global Population ◽

Different Parts

ABSTRACTBackground and objectivesMycobacterium bovis and Mycobacterium caprae are two of the most important agents of tuberculosis (TB) in livestock and the most important causes of zoonotic TB in humans. However, little is known about the global population structure, phylogeography and evolutionary history of these pathogens.MethodologyWe compiled a global collection of 3364 whole-genome sequences from M. bovis and M. caprae originating from 35 countries and inferred their phylogenetic relationships, geographic origins and age.ResultsOur results resolved the phylogenetic relationship among the four previously defined clonal complexes of M. bovis, and another eight newly described here. Our phylogeographic analysis showed that M. bovis likely originated in East Africa. While some groups remained restricted to East- and West Africa, others have subsequently dispersed to different parts of the world.Conclusions and implicationsOur results allow a better understanding of the global population structure of M. bovis and its evolutionary history. This knowledge can be used to define better molecular markers for epidemiological investigations of M. bovis in settings where whole genome sequencing cannot easily be implemented.

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