randtip, a generalized framework to expand incomplete phylogenies using non-molecular phylogenetic information

The increasing availability of molecular information has lifted our understanding of species evolutionary relationships to unprecedent levels. However, current estimates of the world's biodiversity suggest that about a fifth of all extant species are yet to be described, and we still lack molecular information for many of the known species. Hence, evolutionary biologists will have to tackle phylogenetic uncertainty for a long time to come. This prospect has urged the development of software to expand phylogenies based on non-molecular phylogenetic information, and while the available tools provide some valuable features, major drawbacks persist and some of the proposed solutions are hardly generalizable to any group of organisms. Here, we present a completely generalized and flexible framework to expand incomplete molecular phylogenies. The framework is implemented in the R package "randtip", a toolkit of functions that was designed to randomly bind phylogenetically uncertain taxa in backbone phylogenies through a fully customizable and automatic procedure that uses taxonomic ranks as a major source of phylogenetic information. Although randtip is capable of automatically generating fully operative phylogenies for any group of organisms using just a list of species and a backbone tree, we stress that the "blind" expansion of phylogenies (using randtip or any other available software) often leads to suboptimal solutions. Thus, we discuss a variety of circumstances that may require customizing simulation parameters beyond default settings to optimally expand the trees, including a detailed step-by-step workflow. Phylogenetic uncertainty should be tackled with caution, assessing potential pitfalls and opportunities to optimize parameter space prior to launch any simulation. Used judiciously, our framework will help evolutionary biologists to efficiently expand incomplete molecular phylogenies and thereby account for phylogenetic uncertainty in quantitative analyses.

Updating species diversity of Colletotrichum, with a phylogenomic overview

The genus Colletotrichum includes important plant pathogens, endophytes, saprobes and human pathogens. Even though the polyphasic approach has facilitated Colletotrichum species identification, knowledge of the overall species diversity and host distribution is largely incomplete. To address this, we examined 952 Colletotrichum strains isolated from plants representing 322 species from 248 genera, or air and soil samples, from 87 locations in China, as well as 56 strains from Saudi Arabia, Thailand, Turkey, and the UK. Based on morphological characteristics and multi-locus phylogenetic analyses, the strains were assigned to 107 species, including 30 new species described in this paper and 18 new records for China. The currently most comprehensive backbone tree of Colletotrichum, comprising 16 species complexes (including a newly introduced C. bambusicola species complex) and 15 singleton species, is provided. Based on these analyses, 280 species with available molecular data are accepted in this genus, of which 139 have been reported in China, accounting for 49.6 % of the species. Colletotrichum siamense, C. karsti, C. fructicola, C. truncatum, C. fioriniae, and C. gloeosporioides were the most commonly detected species in China, as well as the species with the broadest host range. By contrast, 76 species were currently found to be associated with a single plant species or genus in China. To date, 33 Colletotrichum species have been exclusively reported as endophytes. Furthermore, we generated and assembled whole-genome sequences of the 30 new and a further 18 known species. The most comprehensive genome tree comprising 94 Colletotrichum species based on 1 893 single-copy orthologous genes was hence generated, with all nodes, except four, supported by 100 % bootstrap values. Collectively, this study represents the most comprehensive investigation of Colletotrichum diversity and host occurrence to date, and greatly enhances our understanding of the diversity and phylogenetic relationships in this genus.

Country distancing increase reveals the effectiveness of travel restrictions in stopping COVID-19 transmission

Despite a number of successful approaches in predicting the spatiotemporal patterns of the novel coronavirus (COVID-19) pandemic and quantifying the effectiveness of non-pharmaceutical interventions starting from data about the initial outbreak location, we lack an intrinsic understanding as outbreak locations shift and evolve. Here, we fill this gap by developing a country distance approach to capture the pandemic’s propagation backbone tree from a complex airline network with multiple and evolving outbreak locations. We apply this approach, which is analogous to the effective resistance in series and parallel circuits, to examine countries’ closeness regarding disease spreading and evaluate the effectiveness of travel restrictions on delaying infections. In particular, we find that 63.2% of travel restrictions implemented as of 1 June 2020 are ineffective. The remaining percentage postponed the disease arrival time by 18.56 days per geographical area and resulted in a total reduction of 13,186,045 infected cases. Our approach enables us to design optimized and coordinated travel restrictions to extend the delay in arrival time and further reduce more infected cases while preserving air travel.

APPLES-2: Faster and More Accurate Distance-based Phylogenetic Placement using Divide and Conquer

Phylogenetic placement of query samples on an existing phylogeny is increasingly used in microbiome analyses and other biological studies. As the size of available reference trees used in microbiome analyses continues to grow, there is a growing need for methods that place sequences on ultra-large trees with high accuracy. In this paper, we build on our previous work and introduce APPLES-2, a distance-based phylogenetic placement method. In extensive studies, we show that APPLES-2 is more accurate and much more scalable than APPLES and even some of the leading maximum likelihood methods. This scalability is owed to a divide-and-conquer technique that limits distance calculation and phylogenetic placement to parts of the tree most relevant to each query. The increased scalability and accuracy enables us to study the effectiveness of APPLES-2 for placing microbial genomes on a dataset of 10,575 microbial species using subsets of 381 marker genes. APPLES-2 has very high accuracy in this setting, placing 97% of query genomes within three branches of the optimal position in the species tree using 50 marker genes. As a proof of concept, we also tested APPLES-2 for placing scaffolds produced by metagenomic assembly. It was able to place 3318 scaffolds on the backbone tree with 10575 taxa in less than 3 hours. The accuracy of these placement was high as long as a scaffold included tens of marker genes.

Country distancing increase reveals the effectiveness of travel restrictions in stopping COVID-19 transmission

Non-pharmaceutical interventions are the current central strategy to stop transmitting the novel coronavirus disease (COVID-19) globally. Despite remarkably successful approaches in predicting the ongoing pandemic's spatiotemporal patterns, we lack an intrinsic understanding of the travel restrictions' efficiency and effectiveness. We fill this gap by examining the countries' closeness based on disease spread using country distancing that is analogical to the effective resistance in series and parallel circuits and captures the propagation backbone tree from the outbreak locations globally. Our method estimates that 53.6\% of travel restrictions as of June 1, 2020, are ineffective. Our analytical results unveil that the optimal and coordinated travel restrictions postpone per geographical area by 22.56 [95\% credible interval (CI), 18.57 to 26.59] days of the disease's arrival time and protect the world by reducing 1,872,295 (95\% CI, 216,029 to 23,606,312) infected cases till June 1, 2020, which are significantly better than the existing travel restrictions achieving 12.87 (95\% CI, 10.59 to 15.17) days of arrival time delay and 861,867 (95\% CI, 238,250 to 3,879,638) infected cases reduction. Our approach offers a practical guide that indicates when and where to implement travel restrictions, tailed to the real-time national context.

Country distancing reveals the effectiveness of travel restrictions during COVID-19

Travel restrictions are the current central strategy to globally stop the transmission of the novel coronavirus disease (COVID-19). Despite remarkably successful approaches in predicting the spatiotemporal patterns of the ongoing pandemic, we lack an intrinsic understanding of the travel restriction's effectiveness. We fill this gap by developing a surprisingly simple measure, country distancing, that is analogical to the effective resistance in series and parallel circuits and captures the propagation backbone tree from the outbreak locations globally. This approach enables us to map the effectiveness of travel restrictions to arrival time delay (ATD) or infected case reduction (ICR) systematically. Our method estimates that 50.8\% of travel restrictions as of Apr-4 are ineffective, resulting in zero ATD or ICR worldwide. Instead, by imposing Hubei's lockdown on Jan-23 and national lockdown on Feb-8, mainland China alone leads to 11.66 [95\% credible interval (CI), 9.71 to 13.92] days of ATD per geographic area and 1,012,233 (95\% CI, 208,210 -4,959,094) ICR in total as of Apr-4. Our result unveils the trade-off between the country distancing increase and economic loss, offering practical guidance for strategic action about when and where to implement travel restrictions, tailed to the real-time national context.

A Molecular Phylogenetic Study of the Genus Phedimus for Tracing the Origin of “Tottori Fujita” Cultivars

It is very important to confirm and understand the genetic background of cultivated plants used in multiple applications. The genetic background is the history of crossing between maternal and paternal plants to generate a cultivated plant. If the plant in question was generated from a simple origin and not complicated crossing, we can easily confirm the history using a phylogenetic tree based on molecular data. This study was conducted to trace the origin of “Tottori Fujita 1gou” and “Tottori Fujita 2gou”, which are registered as cultivars originating from Phedimus kamtschaticus. To investigate the phylogenetic position of these cultivars, the backbone tree of the genus Phedimus needed to be further constructed because it retains inarticulate phylogenetic relationships among the wild species. We performed molecular phylogenetic analysis for P. kamtschaticus, Phedimus takesimensis, Phedimus aizoon, and Phedimus middendorffianus, which are assumed as the species of origin for “Tottori Fujita 1gou” and “Tottori Fujita 2gou”. The molecular phylogenetic tree based on the internal transcribed spacer (ITS) and psbA-trnH sequences showed the monophyly of the genus Phedimus, with P. takesimensis forming a single clade. However, P. kamtschaticus and P. aizoon were scattered in the tree. It was verified that “Tottori Fujita 1gou” and “Tottori Fujita 2gou” were embedded in a clade with P. takesimensis and not P. kamtschaticus. Therefore, origination from P. takesimensis was strongly supported. Based on these results, molecular phylogenetic analysis is suggested as a powerful tool for clearly tracing the origin of cultivated plants.

Empirical Performance of Tree-based Inference of Phylogenetic Networks

Phylogenetic networks extend the phylogenetic tree structure and allow for modeling vertical and horizontal evolution in a single framework. Statistical inference of phylogenetic networks is prohibitive and currently limited to small networks. An approach that could significantly improve phylogenetic network space exploration is based on first inferring an evolutionary tree of the species under consideration, and then augmenting the tree into a network by adding a set of “horizontal” edges to better fit the data.In this paper, we study the performance of such an approach on networks generated under a birth-hybridization model and explore its feasibility as an alternative to approaches that search the phylogenetic network space directly (without relying on a fixed underlying tree). We find that the concatenation method does poorly at obtaining a “backbone” tree that could be augmented into the correct network, whereas the popular species tree inference method ASTRAL does significantly better at such a task. We then evaluated the tree-to-network augmentation phase under the minimizing deep coalescence and pseudo-likelihood criteria. We find that even though this is a much faster approach than the direct search of the network space, the accuracy is much poorer, even when the backbone tree is a good starting tree.Our results show that tree-based inference of phylogenetic networks could yield very poor results. As exploration of the network space directly in search of maximum likelihood estimates or a representative sample of the posterior is very expensive, significant improvements to the computational complexity of phylogenetic network inference are imperative if analyses of large data sets are to be performed. We show that a recently developed divide-and-conquer approach significantly outperforms tree-based inference in terms of accuracy, albeit still at a higher computational cost.