Coala: an R framework for coalescent simulation

Staab, Paul; Metzler, Dirk

doi:10.1093/bioinformatics/btw098

Cited by 31 publications

(30 citation statements)

References 21 publications

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“…Nonexcluded genes were simulated for corresponding Tajima's D values using the R package coala, a wrapper for ms (88,89). Inferred parameters for the best-fit one-population demographic scenario for the P. falciparum ancestral-like population, the entire P. vivax population, and the P. vivax monoclonal population were used to parameterize coalescent simulations.…”

Section: Discussionmentioning

confidence: 99%

Selective sweep suggests transcriptional regulation may underlie Plasmodium vivax resilience to malaria control measures in Cambodia

Parobek

Lin

Saunders

et al. 2016

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

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Cambodia, in which both Plasmodium vivax and Plasmodium falciparum are endemic, has been the focus of numerous malaria-control interventions, resulting in a marked decline in overall malaria incidence. Despite this decline, the number of P. vivax cases has actually increased. To understand better the factors underlying this resilience, we compared the genetic responses of the two species to recent selective pressures. We sequenced and studied the genomes of 70 P. vivax and 80 P. falciparum isolates collected between 2009 and 2013. We found that although P. falciparum has undergone population fracturing, the coendemic P. vivax population has grown undisrupted, resulting in a larger effective population size, no discernable population structure, and frequent multiclonal infections. Signatures of selection suggest recent, species-specific evolutionary differences. Particularly, in contrast to P. falciparum, P. vivax transcription factors, chromatin modifiers, and histone deacetylases have undergone strong directional selection, including a particularly strong selective sweep at an AP2 transcription factor. Together, our findings point to different population-level adaptive mechanisms used by P. vivax and P. falciparum parasites. Although population substructuring in P. falciparum has resulted in clonal outgrowths of resistant parasites, P. vivax may use a nuanced transcriptional regulatory approach to population maintenance, enabling it to preserve a larger, more diverse population better suited to facing selective threats. We conclude that transcriptional control may underlie P. vivax's resilience to malaria control measures. Novel strategies to target such processes are likely required to eradicate P. vivax and achieve malaria elimination.D uring the last decade, western Cambodia has been the focus of numerous and multimodal interventions to control the spread of artemisinin-resistant Plasmodium falciparum (1, 2). Such interventions, including increased vector control, increased surveillance, and improved access to quality artemisinin-combination therapy (ACT), would be expected to curtail coendemic Plasmodium vivax as well. However, even as P. falciparum infections in Cambodia decreased by 81% between 2009 and 2013, P. vivax cases have increased, making it the predominant species in the Mekong region (3-6). This scenario, repeated in Brazil and other areas of coendemicity, has led to growing awareness that P. vivax, although infecting the same populations and transmitted by the same mosquito vectors, will likely be the more challenging species to eradicate (6-9). In this study, we use population genomics to gain insight into the evolutionary factors underlying P. vivax's resilience to malaria control measures.Population genetic studies have previously hinted at the resilience of P. vivax populations in comparison with P. falciparum. Studies of microsatellites and highly variable antigens of sympatric P. vivax and P. falciparum populations in Southeast Asia and the Southwest Pacific have consistently shown P. viv...

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Section: Discussionmentioning

confidence: 99%

Selective sweep suggests transcriptional regulation may underlie Plasmodium vivax resilience to malaria control measures in Cambodia

Parobek

Lin

Saunders

et al. 2016

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

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“…We first calculated the site frequency spectrum (SFS) of a separate SNP dataset treated identically to our primary SNP dataset except for filters based on minimum minor allele count and minor allele frequency using the R package adegenet's glSum() function (Jombart, 2008). We next defined demographic models of a single population with either a single population-scaled nucleotide diversity parameter (our "null") model, or both and an exponential population growth parameter (our "growth") model using the coalescent simulator framework coala v. 0.5.3 in R (Staab & Metzler, 2016). Under the "growth" model, the population size changes by a factor − , where is the time in generations since the growth has started.…”

Section: Methodsmentioning

confidence: 99%

Panmixia across elevation in thermally sensitive Andean dung beetles

Linck

Celi

Sheldon

2019

Preprint

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Janzen's seasonality hypothesis predicts that organisms inhabiting environments with limited climatic variability will evolve a reduced thermal tolerance breadth compared with organisms experiencing greater climatic variability. In turn, narrow tolerance breadth may select against dispersal across strong temperature gradients, such as those found across elevation. This can result in narrow elevational ranges and generate a pattern of isolation-by-environment, or neutral genetic differentiation correlated with environmental variables that is independent of geographic distance. We tested for signatures of isolation-by-environment across elevation using genome-wide SNP data from five species of Andean dung beetles (subfamily Scarabaeinae) with well-characterized, narrow thermal physiologies and narrow elevational distributions. Contrary to our expectations, we found no evidence of population genetic structure associated with elevation and little signal of isolation-by-environment. Further, elevational ranges for four of five species appear to be at equilibrium and show no evidence of demographic constraints at range limits. Taken together, these results suggest physiological constraints on dispersal may primarily operate outside of a stable realized niche.

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“…For instance, existing R packages that access the GBIF (GBIF 2018) database (rgbif, Chamberlain and Boettiger 2017) and construct ecological niche models (ENMTools, Warren et al 2010, wallace, Kass et al 2018, enmSdm, Smith 2019) could be linked with packages for realistic models of population demography (e.g. coala, Staab and Metzler 2016), and analysis of population genetic data (e.g. coala, Staab and Metzler 2016), and analysis of population genetic data (e.g.…”

Section: Section 4 Continued Challenges and Frontiersmentioning

confidence: 99%

“…These Figure 6. (A) A simple three-parameter model of population divergence, simulated 100 000 times using the R 'coala' package (Staab and Metzler 2016). Time elapses from top to bottom; 'T' signifies the time of divergence.…”

Section: Advance 1 Significant Improvements In the State-of-the-artmentioning

confidence: 99%

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Inference of biogeographic history by formally integrating distinct lines of evidence: genetic, environmental niche and fossil

Hoban

Dawson

Robinson³

et al. 2019

Ecography

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A primary focus of historical biogeography is to understand changes in species ranges, abundance and genetic connectivity, and changes in community composition. Traditionally, biogeographic inference has relied on distinct lines of evidence, including DNA sequences, fossils and hindcasted ecological niche models. In this review we propose that the development of integrative modeling approaches that leverage multiple distinct data types from diverse disciplines has the potential to revolutionize the field of biogeography. Although each data type contains information on a distinct aspect of species' biogeographic histories, few studies formally integrate multiple types in analysis. For example, post hoc congruence among analyses based on different data types (e.g. fossils and genetics) is commonly assumed to indicate likely biogeographic histories. Unfortunately, analyses of different data often reach discordant conclusions. Thus, fundamental and unresolved debates continue regarding speed and timing of postglacial migration, location and size of glacial refugia, and degree of long distance dispersal. Formal statistical integration can help address these issues. More specifically, formal integration can leverage all available evidence, account for inherent biases associated with different data types, and quantify data and process uncertainty. Novel, quantitative integration of data and models across fields is now possible due to recent advances in cyberinfrastructure, spatial modeling, online and aggregated ecological databases, data processing and quantitative methods. Our purpose is to make the case for and give examples of rigorous integration of genetic, fossil and environmental/ occurrence data for inferring biogeographic history. In particular, we 1) review the need for such a framework; 2) explain common data types and approaches used to infer biogeographic history (and the challenges with each); 3) review state-of-the-art examples of data integration in biogeography; 4) lay out a series of novel, suggested improvements on current methods; and 5) provide an outlook on technical feasibility and future opportunities. Ecography E4 awardGlossary ABC (approximate Bayesian computation; also see Box 1) -a simulation-based statistical method that approximates the likelihood of a model through comparisons of summary statistics calculated from simulated and observed data. Biogeographic history -the study of processes and patterns related to: geographic range shifts, contractions and expansions; demographic fluctuations; locations of refugia; and migration patterns. Bottleneck -a drastic reduction in population size that often also results in a loss of genetic diversity; colonization at a continental scale often involves serial bottlenecks. Coalescent theory -a body of theory that uses probabilistic models to reconstruct the genealogy of a sample backward in time from the sampled lineages (present) to the most recent common ancestor (past). DRM (dynamic range model) -a hierarchical Bayesian approach to estimate paramet...

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Coala: an R framework for coalescent simulation

Abstract: metzler@bio.lmu.de.

Cited by 31 publications

References 21 publications

Selective sweep suggests transcriptional regulation may underlie Plasmodium vivax resilience to malaria control measures in Cambodia

Selective sweep suggests transcriptional regulation may underlie Plasmodium vivax resilience to malaria control measures in Cambodia

Panmixia across elevation in thermally sensitive Andean dung beetles

Inference of biogeographic history by formally integrating distinct lines of evidence: genetic, environmental niche and fossil

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