EvoLaps 2: Advanced phylogeographic visualization

Chevenet, F; Fargette, D; Bastide, P; Vitré, T; Guindon, S

doi:10.1093/ve/vead078

Cited by 4 publications

(1 citation statement)

References 19 publications

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“…For year

, predicted occurrence of the WNV (right) was inferred using data collected earlier than the end of December of year

1

. The maps were generated with EvoLaps2 [ 6 ]…”

Section: Figurementioning

confidence: 99%

Modeling the velocity of evolving lineages and predicting dispersal patterns

Bastide,

Rocu,

Wirtz

et al. 2024

Preprint

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Accurate estimation of the dispersal velocity or speed of evolving organisms is no mean feat. In fact, existing probabilistic models in phylogeography or spatial population genetics generally do not provide an adequate framework to define velocity in a relevant manner. For instance, the very concept of instan-taneous speed simply does not exist under one of the most popular approaches that models the evolution of spatial coordinates as Brownian trajectories running along a phylogeny [30]. Here, we introduce a new family of models – the so-called “Phylogenetic Integrated Velocity” (PIV) models – that use Gaussian processes to explicitly model the velocity of evolving lineages instead of focusing on the fluctuation of spatial coordinates over time. We describe the properties of these models and show an increased accuracy of velocity estimates compared to previous approaches. Analyses of West Nile virus data in the U.S.A. indicate that PIV models provide sensible predictions of the dispersal of evolving pathogens at a one-year time horizon. These results demonstrate the feasibility and relevance of predictive phylogeography in monitoring epidemics in time and space.

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“…For year

, predicted occurrence of the WNV (right) was inferred using data collected earlier than the end of December of year

1

. The maps were generated with EvoLaps2 [ 6 ]…”

Section: Figurementioning

confidence: 99%

Modeling the velocity of evolving lineages and predicting dispersal patterns

Bastide,

Rocu,

Wirtz

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Modeling the velocity of evolving lineages and predicting dispersal patterns

Bastide,

Rocu,

Wirtz

et al. 2024

Proc. Natl. Acad. Sci. U.S.A.

View full text Add to dashboard Cite

Accurate estimation of the dispersal velocity or speed of evolving organisms is no mean feat. In fact, existing probabilistic models in phylogeography or spatial population genetics generally do not provide an adequate framework to define velocity in a relevant manner. For instance, the very concept of instantaneous speed simply does not exist under one of the most popular approaches that models the evolution of spatial coordinates as Brownian trajectories running along a phylogeny. Here, we introduce a family of models—the so-called Phylogenetic Integrated Velocity (PIV) models—that use Gaussian processes to explicitly model the velocity of evolving lineages instead of focusing on the fluctuation of spatial coordinates over time. We describe the properties of these models and show an increased accuracy of velocity estimates compared to previous approaches. Analyses of West Nile virus data in the United States indicate that PIV models provide sensible predictions of the dispersal of evolving pathogens at a one-year time horizon. These results demonstrate the feasibility and relevance of predictive phylogeography in monitoring epidemics in time and space.

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Grains, trade and war in the multimodal transmission of Rice yellow mottle virus: an historical and phylogeographical retrospective

Ndikumana,

Onaga,

Pinel-Galzi

et al. 2024

Preprint

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Rice yellow mottle virus (RYMV) is a major pathogen of rice in Africa. RYMV has a narrow host range limited to rice and a few related poaceae species. We explore the links between the spread of RYMV in East Africa and rice history since the second half of the 19thcentury. The phylogeography of RYMV in East Africa was reconstructed from coat protein gene sequences (ORF4) of 335 isolates sampled over two million square kilometers between 1966 and 2020. Dispersal patterns obtained from ORF2a and ORF2b sequences, and from full-length sequences converged to the same scenario. The following imprints of rice cultivation on RYMV epidemiology were unveiled. RYMV emerged in the middle of the 19thcentury in the Eastern Arc Mountains where slash and burn rice cultivation was practiced. Several spillovers from wild hosts to cultivated rice occurred. RYMV was then rapidly introduced into the adjacent large rice growing Kilombero valley. Harvested seeds are contaminated by debris of virus infected plants that subsist after threshing and winnowing. Long-distance dispersal of RYMV is consistent (i) with rice introduction along the caravan routes from the Indian Ocean Coast to Lake Victoria in the second half of the 19thcentury, (ii) seed movement from East Africa to West Africa at the end of the 19thcentury, from Lake Victoria to the north of Ethiopia in the second half of the 20thcentury and to Madagascar at the end of the 20thcentury, (iii) and, unexpectedly, with rice transport at the end of the First World War as a troop staple food from the Kilombero valley towards the South of Lake Malawi. Overall, RYMV dispersal was associated to a broad range of human activities, some of them unsuspected. Consequently, RYMV has a wide dispersal capacity, its dispersal metrics estimated from phylogeographic reconstructions are similar to those of highly mobile zoonotic viruses.

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EvoLaps 2: Advanced phylogeographic visualization

Cited by 4 publications

References 19 publications

Modeling the velocity of evolving lineages and predicting dispersal patterns

Modeling the velocity of evolving lineages and predicting dispersal patterns

Modeling the velocity of evolving lineages and predicting dispersal patterns

Grains, trade and war in the multimodal transmission of Rice yellow mottle virus: an historical and phylogeographical retrospective

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