Biology subjects

Lanfear, R.

Publications and source records attributed to Lanfear, R..

At least 37 records · Page 2Linked to original sources

bioRxiv2021

The Influence of Model Violation on Phylogenetic Inference: A Simulation Study

AO_SCPLOWBSTRACTC_SCPLOWPhylogenetic inference typically assumes that the data has evolved under Stationary, Reversible and Homogeneous (SRH) conditions. Many empirical and simulation studies have shown that assuming SRH conditions can lead to significant errors in phylogenetic inference when the data violates these assumptions. Yet, many simulation studies focused on extreme non-SRH conditions that represent worst-case scenarios and not the average empirical dataset. In this study, we simulate datasets under various degrees of non-SRH conditions using empirically derived parameters to mimic real data and examine the effects of incorrectly assuming SRH conditions on inferring phylogenies. Our results show that maximum likelihood inference is generally quite robust to a wide range of SRH model violations but is inaccurate under extreme convergent evolution.

evolutionary biology↗

bioRxiv2021

Pandemic-Scale Phylogenomics Reveals Elevated Recombination Rates in the SARS-CoV-2 Spike Region

Accurate and timely detection of recombinant lineages is crucial for interpreting genetic variation, reconstructing epidemic spread, identifying selection and variants of interest, and accurately performing phylogenetic analyses. During the SARS-CoV-2 pandemic, genomic data generation has exceeded the capacities of existing analysis platforms, thereby crippling real-time analysis of viral recombination. Low SARS-CoV-2 mutation rates make detecting recombination difficult. Here, we develop and apply a novel phylogenomic method to exhaustively search a nearly comprehensive SARS-CoV-2 phylogeny for recombinant lineages. We investigate a 1.6M sample tree, and identify 606 recombination events. Approximately 2.7% of sequenced SARS-CoV-2 genomes have recombinant ancestry. Recombination breakpoints occur disproportionately in the Spike protein region. Our method empowers comprehensive real time tracking of viral recombination during the SARS-CoV-2 pandemic and beyond.

evolutionary biology↗

bioRxiv2021

A phylogeny-based metric for estimating changes in transmissibility from recurrent mutations in SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in late 2019 and spread globally to cause the COVID-19 pandemic. Despite the constant accumulation of genetic variation in the SARS-CoV-2 population, there was little evidence for the emergence of significantly more transmissible lineages in the first half of 2020. Starting around November 2020, several more contagious and possibly more virulent Variants of Concern (VoCs) were reported in various regions of the world. These VoCs share some mutations and deletions that haven arisen recurrently in distinct genetic backgrounds. Here, we build on our previous work modelling the association of mutations to SARS-CoV-2 transmissibility and characterise the contribution of individual recurrent mutations and deletions to estimated viral transmissibility. We then assess how patterns of estimated transmissibility in all SARS-CoV-2 clades have varied over the course of the COVID-19 pandemic by summing transmissibility estimates for all individual mutations carried by any sequenced genome analysed. Such an approach recovers the Delta variant (21A) as the most transmissible clade currently in circulation, followed by the Alpha variant (20I). By assessing transmissibility over the time of sampling, we observe a tendency for estimated transmissibility within clades to slightly decrease over time in most clades. Although subtle, this pattern is consistent with the expectation of a decay in transmissibility in mainly non-recombining lineages caused by the accumulation of weakly deleterious mutations. SARS-CoV-2 remains a highly transmissible pathogen, though such a trend could conceivably play a role in the turnover of different global viral clades observed over the pandemic so far. CaveatsO_LIThis work is not about the severity of disease. We do not analyse the severity of disease. We do not present any evidence that SARS-CoV-2 has decreased in severity. C_LIO_LILineage replacement dynamics are affected by many factors. The trend we recover for a decrease in inferred transmissibility of a clade over time is a small effect. We caution against over-interpretation. This result would not affect the management of the SARS-CoV-2 pandemic: for example, we make no claims about any impact on the efficacy of particular non-pharmaceutical interventions (NPIs). C_LIO_LIOur phylogeny-based method to infer changes in estimated transmissibility due to recurrent mutations and deletions makes a number of simplifying assumptions. These may not all be valid. The consistent trend for the slight decrease we report might be due to an as-yet-unidentified systematic bias. C_LI

genomics↗

bioRxiv2021

A test statistic to quantify treelikeness in phylogenetics

Most phylogenetic analyses assume that the evolutionary history of an alignment (either that of a single locus, or of multiple concatenated loci) can be described by a single bifurcating tree, the so-called the treelikeness assumption. Treelikeness can be violated by biological events such as recombination, introgression, or incomplete lineage sorting, and by systematic errors in phylogenetic analyses. The incorrect assumption of treelikeness may then mislead phylogenetic inferences. To quantify and test for treelikeness in alignments, we develop a test statistic which we call the tree proportion. This statistic quantifies the proportion of the edge weights in a phylogenetic network that are represented in a bifurcating phylogenetic tree of the same alignment. We extend this statistic to a statistical test of treelikeness using a parametric bootstrap. We use extensive simulations to compare tree proportion to a range of related approaches. We show that tree proportion successfully identifies non-treelikeness in a wide range of simulation scenarios, and discuss its strengths and weaknesses compared to other approaches. The power of the tree-proportion test to reject non-treelike alignments can be lower than some other approaches, but these approaches tend to be limited in their scope and/or the ease with which they can be interpreted. Our recommendation is to test treelikeness of sequence alignments with both tree proportion and mosaic methods such as 3Seq. The scripts necessary to replicate this study are available at https://github.com/caitlinch/treelikeness

evolutionary biology↗

bioRxiv2021

Mutation rates and selection on synonymous mutations in SARS-CoV-2

AO_SCPLOWBSTRACTC_SCPLOWThe COVID-19 pandemic has seen an unprecedented response from the sequencing community. Leveraging the sequence data from more than 140,000 SARS-CoV-2 genomes, we study mutation rates and selective pressures affecting the virus. Understanding the processes and effects of mutation and selection has profound implications for the study of viral evolution, for vaccine design, and for the tracking of viral spread. We highlight and address some common genome sequence analysis pitfalls that can lead to inaccurate inference of mutation rates and selection, such as ignoring skews in the genetic code, not accounting for recurrent mutations, and assuming evolutionary equilibrium. We find that two particular mutation rates, G[->]U and C[->]U, are similarly elevated and considerably higher than all other mutation rates, causing the majority of mutations in the SARS-CoV-2 genome, and are possibly the result of APOBEC and ROS activity. These mutations also tend to occur many times at the same genome positions along the global SARS-CoV-2 phylogeny (i.e., they are very homoplasic). We observe an effect of genomic context on mutation rates, but the effect of the context is overall limited. While previous studies have suggested selection acting to decrease U content at synonymous sites, we bring forward evidence suggesting the opposite.

evolutionary biology↗

bioRxiv2021

Cancer phylogenetics using single-cell RNA-seq data

Phylogenetic methods are emerging as a useful tool to understand cancer evolutionary dynamics, including tumor structure, heterogeneity, and progression. Most currently used approaches utilize either bulk whole genome sequencing (WGS) or single-cell DNA sequencing (scDNA-seq) and are based on calling copy number alterations and single nucleotide variants (SNVs). scRNA-seq is commonly applied to explore differential gene expression of cancer cells throughout tumor progression. The method exacerbates the single-cell sequencing problem of low yield per cell with uneven expression levels. This accounts for low and uneven sequencing coverage and makes SNV detection and phylogenetic analysis challenging. In this paper, we demonstrate for the first time that scRNA-seq data contains sufficient evolutionary signal and can also be utilized in phylogenetic analyses. We explore and compare results of such analyses based on both expression levels and SNVs called from scRNA-seq data. Both techniques are shown to be useful for reconstructing phylogenetic relationships between cells, reflecting the clonal composition of a tumor. Both standardized expression values and SNVs appear to be equally capable of reconstructing a similar pattern of phylogenetic relationship. This pattern is stable even when phylogenetic uncertainty is taken in account. Our results open up a new direction of somatic phylogenetics based on scRNA-seq data. Further research is required to refine and improve these approaches to capture the full picture of somatic evolutionary dynamics in cancer.

cancer biology↗

bioRxiv2020

Ultrafast Sample Placement on Existing Trees (UShER) Empowers Real-Time Phylogenetics for the SARS-CoV-2 Pandemic

As the SARS-CoV-2 virus spreads through human populations, the unprecedented accumulation of viral genome sequences is ushering a new era of "genomic contact tracing" - that is, using viral genome sequences to trace local transmission dynamics. However, because the viral phylogeny is already so large - and will undoubtedly grow many fold - placing new sequences onto the tree has emerged as a barrier to real-time genomic contact tracing. Here, we resolve this challenge by building an efficient, tree-based data structure encoding the inferred evolutionary history of the virus. We demonstrate that our approach improves the speed of phylogenetic placement of new samples and data visualization by orders of magnitude, making it possible to complete the placements under real-time constraints. Our method also provides the key ingredient for maintaining a fully-updated reference phylogeny. We make these tools available to the research community through the UCSC SARS-CoV-2 Genome Browser to enable rapid cross-referencing of information in new virus sequences with an ever-expanding array of molecular and structural biology data. The methods described here will empower research and genomic contact tracing for laboratories worldwide. Software AvailabilityUSHER is available to users through the UCSC Genome Browser at https://genome.ucsc.edu/cgi-bin/hgPhyloPlace. The source code and detailed instructions on how to compile and run UShER are available from https://github.com/yatisht/usher.

genomics↗

bioRxiv2020

Assessing Confidence in Root Placement on Phylogenies: An Empirical Study Using Non-Reversible Models

AO_SCPLOWBSTRACTC_SCPLOWUsing time-reversible Markov models is a very common practice in phylogenetic analysis, because although we expect many of their assumptions to be violated by empirical data, they provide high computational efficiency. However, these models lack the ability to infer the root placement of the estimated phylogeny. In order to compensate for the inability of these models to root the tree, many researchers use external information such as using outgroup taxa or additional assumptions such as molecular-clocks. In this study, we investigate the utility of non-reversible models to root empirical phylogenies and introduce a new bootstrap measure, the rootstrap, which provides information on the statistical support for any given root position. Availability and implementationrootstrap support is implemented in IQ-TREE 2 and a tutorial is available at the iqtree webpage http://www.iqtree.org/doc/Rootstrap. In addition, a python script is available at https://github.com/suhanaser/Rootstrap. [phylogenetic inference, root estimation, bootstrap, non-reversible models]

evolutionary biology↗

bioRxiv2020

sangeranalyseR: simple and interactive analysis of Sanger sequencing data in R

SummarysangeranalyseR is an interactive R/Bioconductor package and two associated Shiny applications designed for analysing Sanger sequencing from data from the ABIF file format in R. It allows users to go from loading reads to saving aligned contigs in a few lines of R code. sangeranalyseR provides a wide range of options for a number of commonly-performed actions including read trimming, detecting secondary peaks, viewing chromatograms, and detecting indels using a reference sequence. All parameters can be adjusted interactively either in R or in the associated Shiny applications. sangeranalyseR comes with extensive online documentation, and outputs detailed interactive HTML reports. Availability and implementationsangeranalyseR is implemented in R and released under an MIT license. It is available for all platforms on Bioconductor (https://bioconductor.org/packages/sangeranalyseR) and on Github (https://github.com/roblanf/sangeranalyseR). Contactkuanhao.chao@gmail.com Supplementary informationDocumentation at https://sangeranalyser.readthedocs.io/.

bioinformatics↗

bioRxiv2020

Primate phylogenomics uncovers multiple rapid radiations and ancient interspecific introgression

Our understanding of the evolutionary history of primates is undergoing continual revision due to ongoing genome sequencing efforts. Bolstered by growing fossil evidence, these data have led to increased acceptance of once controversial hypotheses regarding phylogenetic relationships, hybridization and introgression, and the biogeographical history of primate groups. Among these findings is a pattern of recent introgression between species within all major primate groups examined to date, though little is known about introgression deeper in time. To address this and other phylogenetic questions, here we present new reference genome assemblies for three Old World Monkey species: Colobus angolensis ssp. palliatus (the black and white colobus), Macaca nemestrina (southern pig-tailed macaque), and Mandrillus leucophaeus (the drill). We combine these data with 23 additional primate genomes to estimate both the species tree and individual gene trees using thousands of loci. While our species tree is largely consistent with previous phylogenetic hypotheses, the gene trees reveal high levels of genealogical discordance associated with multiple primate radiations. We use strongly asymmetric patterns of gene tree discordance around specific branches to identify multiple instances of introgression between ancestral primate lineages. In addition, we exploit recent fossil evidence to perform fossil-calibrated molecular dating analyses across the tree. Taken together, our genome-wide data help to resolve multiple contentious sets of relationships among primates, while also providing insight into the biological processes and technical artifacts that led to the disagreements in the first place.

evolutionary biology↗

bioRxiv2020

QMaker: Fast and accurate method to estimate empirical models of protein evolution

Amino acid substitution models play a crucial role in phylogenetic analyses. Maximum likelihood (ML) methods have been proposed to estimate amino acid substitution models, however, they are typically complicated and slow. In this paper, we propose QMaker, a new ML method to estimate a general time-reversible Q matrix from a large protein dataset consisting of multiple sequence alignments. QMaker combines an efficient ML tree search algorithm, a model selection for handling the model heterogeneity among alignments, and the consideration of rate mixture models among sites. We provide QMaker as a user-friendly function in the IQ-TREE software package (http://www.iqtree.org) supporting the use of multiple CPU cores so that biologists can easily estimate amino acid substitution models from their own protein alignments. We used QMaker to estimate new empirical general amino acid substitution models from the current Pfam database as well as five clade-specific models for mammals, birds, insects, yeasts, and plants. Our results show that the new models considerably improve the fit between model and data and in some cases influence the inference of phylogenetic tree topologies.

evolutionary biology↗

bioRxiv2019

IQ-TREE 2: New models and efficient methods for phylogenetic inference in the genomic era

IQ-TREE (http://www.iqtree.org) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.

evolutionary biology↗

bioRxiv2019

A phylogenomic approach reveals a low somatic mutation rate in a long-lived plant

Somatic mutations can have important effects on the life history, ecology, and evolution of plants, but the rate at which they accumulate is poorly understood, and has been very difficult to measure directly. Here, we demonstrate a novel method to measure somatic mutations in individual plants and use this approach to estimate the somatic mutation rate in a large, long-lived, phenotypically mosaic Eucalyptus melliodora tree. Despite being 100 times larger than Arabidopsis, this tree has a per-generation mutation rate only ten times greater, which suggests that this species may have evolved mechanisms to reduce the mutation rate per unit of growth. This adds to a growing body of evidence that illuminates the correlated evolutionary shifts in mutation rate and life history in plants.

genomics↗

bioRxiv2019

Stable and widespread structural heteroplasmy in chloroplast genomes revealed by a new long-read quantification method

The chloroplast genome usually has a quadripartite structure consisting of a large single copy region and a small single copy region separated by two long inverted repeats. It has been known for some time that a single cell may contain at least two structural haplotypes of this structure, which differ in the relative orientation of the single copy regions. However, the methods required to detect and measure the abundance of the structural haplotypes are labour-intensive, and this phenomenon remains understudied. Here we develop a new method, Cp-hap, to detect all possible structural haplotypes of chloroplast genomes of quadripartite structure using long-read sequencing data. We use this method to conduct a systematic analysis and quantification of chloroplast structural haplotypes in 61 land plant species across 19 orders of Angiosperms, Gymnosperms and Pteridophytes. Our results show that there are two chloroplast structural haplotypes which occur with equal frequency in most land plant individuals. Nevertheless, species whose chloroplast genomes lack inverted repeats or have short inverted repeats have just a single structural haplotype. We also show that the relative abundance of the two structural haplotypes remains constant across multiple samples from a single individual plant, suggesting that the process which maintains equal frequency of the two haplotypes operates rapidly, consistent with the hypothesis that flip-flop recombination mediates chloroplast structural heteroplasmy. Our results suggest that previous claims of differences in chloroplast genome structure between species may need to be revisited.\n\nSignificance StatementChloroplast genome consists of a large single copy region, a small single copy region, and two inverted repeats. Some decades ago, a discovery showed that there are two types chloroplast genome in some plants, which differ the way that the four regions are put together. However, this phenomenon has been shown in just a small number of species, and many open questions remain. Here, we develop a fast method to measure the chloroplast genome structures, based on long-reads. We show that almost all plants we analysed contain two possible genome structures, while a few plants contain only one structure. Our findings hint at the causes of the phenomenon, and provide a convenient new method with which to make rapid progress.

plant biology↗

bioRxiv2019

The draft nuclear genome assembly of Eucalyptus pauciflora: new approaches to comparing de novo assemblies

BackgroundSelecting the best genome assembly from a collection of draft assemblies for the same species remains a difficult task. Here, we combine new and existing approaches to help to address this, using the non-model plant Eucalyptus pauciflora (snow gum) as a test case. Eucalyptus pauciflora is a long-lived tree with high economic and ecological importance. Currently, little genomic information for Eucalyptus pauciflora is available.\n\nFindingsWe generated high coverage of long-(Nanopore, 174x) and short-(Illumina, 228x) read data from a single Eucalyptus pauciflora individual and compared assemblies from four assemblers with a variety of settings: Canu, Flye, Marvel, and MaSuRCA. A key component of our approach is to keep a randomly selected collection of ~10% of both long- and short-reads separate from the assemblies to use as a validation set with which to assess the assemblies. Using this validation set along with a range of existing tools, we compared the assemblies in eight ways: contig N50, BUSCO scores, LAI scores, assembly ploidy, base-level error rate, computing genome assembly likelihoods, structural variation and genome sequence similarity. Our result showed that MaSuRCA generated the best assembly, which is 594.87 Mb in size, with a contig N50 of 3.23 Mb, and an estimated error rate of ~0.006 errors per base.\n\nConclusionsWe report a draft genome of Eucalyptus pauciflora, which will be a valuable resource for further genomic studies of eucalypts. These approaches for assessing and comparing genomes should help in assessing and choosing among many potential genome assemblies for a single species.

genomics↗

bioRxiv2018

New methods to calculate concordance factors for phylogenomic datasets

We implement two measures for quantifying genealogical concordance in phylogenomic datasets: the gene concordance factor (gCF) and the novel site concordance factor (sCF). For every branch of a reference tree, gCF is defined as the percentage of "decisive" gene trees containing that branch. This measure is already in wide usage, but here we introduce a package that calculates it while accounting for variable taxon coverage among gene trees. sCF is a new measure defined as the percentage of decisive sites supporting a branch in the reference tree. gCF and sCF complement classical measures of branch support in phylogenetics by providing a full description of underlying disagreement among loci and sites. An easy to use implementation and tutorial is freely available in the IQ-TREE software package (http://www.iqtree.org).

bioinformatics↗

bioRxiv2018

Linking Branch Lengths Across Loci Provides the Best Fit for Phylogenetic Inference

Evolution leaves heterogeneous patterns of nucleotide variation across the genome, with different loci subject to varying degrees of mutation, selection, and drift. Appropriately modelling this heterogeneity is important for reliable phylogenetic inference. One modelling approach in statistical phylogenetics is to apply independent models of molecular evolution to different groups of sites, where the groups are usually defined by locus, codon position, or combinations of the two. The potential impacts of partitioning data for the assignment of substitution models are well appreciated. Meanwhile, the treatment of branch lengths has received far less attention. In this study, we examined the effects of linking and unlinking branch-length parameters across loci. By analysing a range of empirical data sets, we find that the best-fitting model for phylogenetic inference is consistently one in which branch lengths are proportionally linked: gene trees have the same pattern of branch-length variation, but with varying absolute tree lengths. This model provided a substantially better fit than those that either assumed identical branch lengths across gene trees or that allowed each gene tree to have its own distinct set of branch lengths. Using simulations, we show that the fit of the three different models of branch lengths varies with the length of the sequence alignment and with the number of taxa in the data set. Our findings suggest that a model with proportionally linked branch lengths across loci is likely to provide the best fit under the conditions that are most commonly seen in practice. In future work, improvements in fit might be afforded by models with levels of complexity intermediate to proportional and free branch lengths. The results of our study have implications for model selection, computational efficiency, and experimental design in phylogenomics.

evolutionary biology↗

bioRxiv2018

The Prevalence and Impact of Model Violations in Phylogenetics

In phylogenetic inference we commonly use models of substitution which assume that sequence evolution is stationary, reversible and homogeneous (SRH). Although the use of such models is often criticized, the extent of SRH violations and their effects on phylogenetic inference of tree topologies and edge lengths are not well understood. Here, we introduce and apply the maximal matched-pairs tests of homogeneity to assess the scale and impact of SRH model violations on 3,572 partitions from 35 published phylogenetic datasets. We show that many partitions (39.5%) reject the SRH assumptions, and that for most datasets, the topologies of trees inferred from all partitions differ significantly from those inferred using the subset of partitions that do not reject the SRH assumptions. These results suggest that the extent and effects of model violation in phylogenetics may be substantial. They highlight the importance of testing for model violations and possibly excluding partitions that violate models prior to tree reconstruction. They also suggest that further effort in developing models that do not require SRH assumptions could lead to large improvements in the accuracy of phylogenomic inference. The scripts necessary to perform the analysis are available in https://github.com/roblanf/SRHtests, and the new tests we describe are available as a new option in IQ-TREE (http://www.iqtree.org).

molecular biology↗