Phylogeny Inference Research Articles

SIEVE: joint inference of single-nucleotide variants and cell phylogeny from single-cell DNA sequencing data

We present SIEVE, a statistical method for the joint inference of somatic variants and cell phylogeny under the finite-sites assumption from single-cell DNA sequencing. SIEVE leverages raw read counts for all nucleotides and corrects the acquisition bias of branch lengths. In our simulations, SIEVE outperforms other methods in phylogenetic reconstruction and variant calling accuracy, especially in the inference of homozygous variants. Applying SIEVE to three datasets, one for triple-negative breast (TNBC), and two for colorectal cancer (CRC), we find that double mutant genotypes are rare in CRC but unexpectedly frequent in the TNBC samples.

The evolution of unique cranial traits in leporid lagomorphs.

The leporid lagomorphs (rabbits and hares) are adapted to running and leaping (some more than others) and consequently have unique anatomical features that distinguish them from ochotonid lagomorphs (pikas) and from their rodent relatives. Two traits that have received some attention are fenestration of the lateral wall of the maxilla and facial tilting. These features are known to correlate with specialised locomotory form in that the faster running species will generally have fenestration that occupies the dorsal and the anteroventral surface of the maxillary corpus and a more acute facial tilt angle. Another feature is an intracranial joint that circumscribes the back of the skull, thought to facilitate skull mobility. This joint separates the anterior portion of the cranium (including the dentition, rostrum and orbit) from the posterior portion of the cranium (which encompasses the occipital and the auditory complex). Aside from the observation that the intracranial joint is absent in pikas (generalist locomotors) and appears more elaborate in genera with cursorial and saltatorial locomotory habits, the evolutionary history, biomechanical function and comparative anatomy of this feature in leporids lacks a comprehensive evaluation. The present work analysed the intracranial joint, facial tilting and lateral fenestration of the wall of the maxilla in the context of leporid evolutionary history using a Bayesian inference of phylogeny (18 genera, 23 species) and ancestral state reconstruction. These methods were used to gather information about the likelihood of the presence of these three traits in ancestral groups. Our phylogenetic analyses found it likely that the last common ancestor of living leporids had some facial tilting, but that the last common ancestor of all lagomorphs included in the dataset did not. We found that it was likely that the last common ancestor of living leporids had fenestration that occupies the dorsal, but not the anteroventral, surface of the maxillary corpus. We also found it likely that the last common ancestor of living leporids had an intracranial joint, but that the last common ancestor of all living lagomorphs did not. These findings provide a broader context to further studies of evolutionary history and will help inform the formulation and testing of functional hypotheses.

Muscle5: High-accuracy alignment ensembles enable unbiased assessments of sequence homology and phylogeny

Multiple sequence alignments are widely used to infer evolutionary relationships, enabling inferences of structure, function, and phylogeny. Standard practice is to construct one alignment by some preferred method and use it in further analysis; however, undetected alignment bias can be problematic. I describe Muscle5, a novel algorithm which constructs an ensemble of high-accuracy alignment with diverse biases by perturbing a hidden Markov model and permuting its guide tree. Confidence in an inference is assessed as the fraction of the ensemble which supports it. Applied to phylogenetic tree estimation, I show that ensembles can confidently resolve topologies with low bootstrap according to standard methods, and conversely that some topologies with high bootstraps are incorrect. Applied to the phylogeny of RNA viruses, ensemble analysis shows that recently adopted taxonomic phyla are probably polyphyletic. Ensemble analysis can improve confidence assessment in any inference from an alignment.

MEDICC2: whole-genome doubling aware copy-number phylogenies for cancer evolution

Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.

KINN: An alignment-free accurate phylogeny reconstruction method based on inner distance distributions of k-mer pairs in biological sequences

Alignment-based methods have faced disadvantages in sequence comparison and phylogeny reconstruction due to their high computational complexity. Alignment-free methods for sequence comparison and phylogeny inference have attracted a great deal of attention in recent years. Here, we explore an alignment-free approach that uses inner distance distributions of k-mer pairs in biological sequences for phylogeny inference. For every sequence in a dataset, our method transforms the sequence into a numeric feature vector consisting of features each representing a specific k-mer pair’s contribution to the characterization of the sequentiality uniqueness of the sequence. This newly defined k-mer pair’s contribution is an integration of the reverse Kullback-Leibler divergence, pseudo mode and the classic entropy of an inner distance distribution of the k-mer pair in the sequence. Our method has been tested on datasets of complete genome sequences, complete protein sequences, and gene sequences of rRNA of various lengths. Our method achieves the best performance in comparison with state-of-the-art alignment-free methods as measured by the Robinson-Foulds distance between the reference and the constructed phylogeny trees.

Insertions and deletions as phylogenetic signal in an alignment-free context.

Most methods for phylogenetic tree reconstruction are based on sequence alignments; they infer phylogenies from substitutions that may have occurred at the aligned sequence positions. Gaps in alignments are usually not employed as phylogenetic signal. In this paper, we explore an alignment-free approach that uses insertions and deletions (indels) as an additional source of information for phylogeny inference. For a set of four or more input sequences, we generate so-called quartet blocks of four putative homologous segments each. For pairs of such quartet blocks involving the same four sequences, we compare the distances between the two blocks in these sequences, to obtain hints about indels that may have happened between the blocks since the respective four sequences have evolved from their last common ancestor. A prototype implementation that we call Gap-SpaM is presented to infer phylogenetic trees from these data, using a quartet-tree approach or, alternatively, under the maximum-parsimony paradigm. This approach should not be regarded as an alternative to established methods, but rather as a complementary source of phylogenetic information. Interestingly, however, our software is able to produce phylogenetic trees from putative indels alone that are comparable to trees obtained with existing alignment-free methods.

Reconstructing tumor clonal lineage trees incorporating single-nucleotide variants, copy number alterations and structural variations.

MotivationCancer develops through a process of clonal evolution in which an initially healthy cell gives rise to progeny gradually differentiating through the accumulation of genetic and epigenetic mutations. These mutations can take various forms, including single-nucleotide variants (SNVs), copy number alterations (CNAs) or structural variations (SVs), with each variant type providing complementary insights into tumor evolution as well as offering distinct challenges to phylogenetic inference.ResultsIn this work, we develop a tumor phylogeny method, TUSV-ext, which incorporates SNVs, CNAs and SVs into a single inference framework. We demonstrate on simulated data that the method produces accurate tree inferences in the presence of all three variant types. We further demonstrate the method through application to real prostate tumor data, showing how our approach to coordinated phylogeny inference and clonal construction with all three variant types can reveal a more complicated clonal structure than is suggested by prior work, consistent with extensive polyclonal seeding or migration.Availability and implementation https://github.com/CMUSchwartzLab/TUSV-ext.Supplementary information Supplementary data are available at Bioinformatics online.

The unstable evolutionary position of Korarchaeota and its relationship with other TACK and Asgard archaea.

The applications of marker gene concatenation have been advanced to resolve the key questions in the Tree of Life. However, the interphylum evolutionary relationship between Korarchaeota of TACK (Thaumarchaeota, Aigarchaeota, Crenarchaeota, Korarchaeota) and Asgard archaea remains uncertain. We applied a marker gene ranking procedure to examine their evolutionary history. Our updated trees showed confident placements of (1) Korarchaeota as the basal branch to other TACK archaea and as a sister group to Asgard archaea; (2) Njordarchaeota at basal branch to Korarchaeota instead of within Asgard archaea. They highlight the importance of evaluating marker genes for phylogeny inference of the Archaea domain.

In preprints: the fast-paced field of single-cell lineage tracing

In preprints: the fast-paced field of single-cell lineage tracing

Phylogenies from unaligned proteomes using sequence environments of amino acid residues.

Alignment-free methods for sequence comparison and phylogeny inference have attracted a great deal of attention in recent years. Several algorithms have been implemented in diverse software packages. Despite the great number of existing methods, most of them are based on word statistics. Although they propose different filtering and weighting strategies and explore different metrics, their performance may be limited by the phylogenetic signal preserved in these words. Herein, we present a different approach based on the species-specific amino acid neighborhood preferences. These differential preferences can be assessed in the context of vector spaces. In this way, a distance-based method to build phylogenies has been developed and implemented into an easy-to-use R package. Tests run on real-world datasets show that this method can reconstruct phylogenetic relationships with high accuracy, and often outperforms other alignment-free approaches. Furthermore, we present evidence that the new method can perform reliably on datasets formed by non-orthologous protein sequences, that is, the method not only does not require the identification of orthologous proteins, but also does not require their presence in the analyzed dataset. These results suggest that the neighborhood preference of amino acids conveys a phylogenetic signal that may be of great utility in phylogenomics.

PhyloHerb: A high-throughput phylogenomic pipeline for processing genome skimming data.

PremiseThe application of high‐throughput sequencing, especially to herbarium specimens, is rapidly accelerating biodiversity research. Low‐coverage sequencing of total genomic DNA (genome skimming) is particularly promising and can simultaneously recover the plastid, mitochondrial, and nuclear ribosomal regions across hundreds of species. Here, we introduce PhyloHerb, a bioinformatic pipeline to efficiently assemble phylogenomic data sets derived from genome skimming.Methods and ResultsPhyloHerb uses either a built‐in database or user‐specified references to extract orthologous sequences from all three genomes using a BLAST search. It outputs FASTA files and offers a suite of utility functions to assist with alignment, partitioning, concatenation, and phylogeny inference. The program is freely available at https://github.com/lmcai/PhyloHerb/.ConclusionsWe demonstrate that PhyloHerb can accurately identify genes using a published data set from Clusiaceae. We also show via simulations that our approach is effective for highly fragmented assemblies from herbarium specimens and is scalable to thousands of species.

PASTA with many application-aware optimization criteria for alignment based phylogeny inference

Multiple sequence alignment (MSA) is a prerequisite for several analyses in bioinformatics, such as, phylogeny estimation, protein structure prediction, etc. PASTA (Practical Alignments using SATé and TrAnsitivity) is a state-of-the-art method for computing MSAs, well-known for its accuracy and scalability. It iteratively co-estimates both MSA and maximum likelihood (ML) phylogenetic tree. It attempts to exploit the close association between the accuracy of an MSA and the corresponding tree while finding the output through multiple iterations from both directions. Currently, PASTA uses the ML score as its optimization criterion which is a good score in phylogeny estimation but cannot be proven as a necessary and sufficient criterion to produce an accurate phylogenetic tree. Therefore, the integration of multiple application-aware objectives into PASTA, which are carefully chosen considering their better association to the tree accuracy, may potentially have a profound positive impact on its performance. This paper has employed four application-aware objectives alongside ML score to develop a multi-objective (MO) framework, namely, PMAO that leverages PASTA to generate a bunch of high-quality solutions that are considered equivalent in the context of conflicting objectives under consideration. our experimental analysis on a popular biological benchmark reveals that the tree-space generated by PMAO contains significantly better trees than stand-alone PASTA. To help the domain experts further in choosing the most appropriate tree from the PMAO output (containing a relatively large set of high-quality solutions), we have added an additional component within the PMAO framework that is capable of generating a smaller set of high-quality solutions. Finally, we have attempted to obtain a single high-quality solution without using any external evidences and have found that summarizing the few solutions detected through the above component can serve this purpose to some extent.

Bayesian inference of phylogeny is robust to substitution model over-parameterization

Bayesian inference of phylogeny is robust to substitution model over-parameterization

Bayesian inference of phylogeny is robust to substitution model over-parameterization

Bayesian inference of phylogeny is robust to substitution model over-parameterization

RiboGrove: a database of full-length prokaryotic 16S rRNA genes derived from completely assembled genomes

16S rRNA gene is frequently used for the identification of prokaryotic organisms and for phylogeny inference. Several specialized public databases exist that contain complete and partial sequences of 16S rRNA genes. In this paper, we present RiboGrove: the first publicly available database that comprises only full-length sequences of 16S rRNA genes originating from completely assembled prokaryotic genomes deposited in RefSeq. Despite being strongly biased towards frequently sequenced genomes, RiboGrove is a useful complement to existing 16S rRNA resources and allows for analyses that would not be possible using amplicon-derived gene sequences. For instance, the absence of partial gene sequences in RiboGrove allowed us to make a summary of prokaryotic organisms, which lack core anti-Shine-Dalgarno sequence in their 16S rRNA genes. In this study, we describe the collected sequence data and present the results of exploratory data analysis of 16S rRNA gene sequences.

CellPhy: accurate and fast probabilistic inference of single-cell phylogenies from scDNA-seq data

We introduce CellPhy, a maximum likelihood framework for inferring phylogenetic trees from somatic single-cell single-nucleotide variants. CellPhy leverages a finite-site Markov genotype model with 16 diploid states and considers amplification error and allelic dropout. We implement CellPhy into RAxML-NG, a widely used phylogenetic inference package that provides statistical confidence measurements and scales well on large datasets with hundreds or thousands of cells. Comprehensive simulations suggest that CellPhy is more robust to single-cell genomics errors and outperforms state-of-the-art methods under realistic scenarios, both in accuracy and speed. CellPhy is freely available at https://github.com/amkozlov/cellphy.

Modular evolution of secretion systems and virulence plasmids in a bacterial species complex

BackgroundMany named species as defined in current bacterial taxonomy correspond to species complexes. Uncertainties regarding the organization of their genetic diversity challenge research efforts. We utilized the Agrobacterium tumefaciens species complex (a.k.a. Agrobacterium biovar 1), a taxon known for its phytopathogenicity and applications in transformation, as a study system and devised strategies for investigating genome diversity and evolution of species complexes.ResultsWe utilized 35 genome assemblies, including 14 newly generated ones, to achieve a phylogenetically balanced sampling of A. tumefaciens. Our genomic analysis suggested that the 10 genomospecies described previously are distinct biological species and supported a quantitative guideline for species delineation. Furthermore, our inference of gene content and core-genome phylogeny allowed for investigations of genes critical in fitness and ecology. For the type VI secretion system (T6SS) involved in interbacterial competition and thought to be conserved, we detected multiple losses and one horizontal gene transfer. For the tumor-inducing plasmids (pTi) and pTi-encoded type IV secretion system (T4SS) that are essential for agrobacterial phytopathogenicity, we uncovered novel diversity and hypothesized their involvement in shaping this species complex. Intriguingly, for both T6SS and T4SS, genes encoding structural components are highly conserved, whereas extensive diversity exists for genes encoding effectors and other proteins.ConclusionsWe demonstrate that the combination of a phylogeny-guided sampling scheme and an emphasis on high-quality assemblies provides a cost-effective approach for robust analysis in evolutionary genomics. We show that the T6SS VgrG proteins involved in specific effector binding and delivery can be classified into distinct types based on domain organization. The co-occurrence patterns of VgrG-associated domains and the neighboring genes that encode different chaperones/effectors can be used to infer possible interacting partners. Similarly, the associations between plant host preference and the pTi type among these strains can be used to infer phenotype-genotype correspondence. Our strategies for multi-level investigations at scales that range from whole genomes to intragenic domains and phylogenetic depths from between- to within-species are applicable to other bacteria. Furthermore, modularity observed in the molecular evolution of genes and domains is useful for inferring functional constraints and informing experimental works.

Crouching TIGER, hidden structure: Exploring the nature of linguistic data using TIGER values

AbstractIn recent years, techniques such as Bayesian inference of phylogeny have become a standard part of the quantitative linguistic toolkit. While these tools successfully model the tree-like component of a linguistic dataset, real-world datasets generally include a combination of tree-like and nontree-like signals. Alongside developing techniques for modeling nontree-like data, an important requirement for future quantitative work is to build a principled understanding of this structural complexity of linguistic datasets. Some techniques exist for exploring the general structure of a linguistic dataset, such as NeighborNets, δ scores, and Q-residuals; however, these methods are not without limitations or drawbacks. In general, the question of what kinds of historical structure a linguistic dataset can contain and how these might be detected or measured remains critically underexplored from an objective, quantitative perspective. In this article, we propose TIGER values, a metric that estimates the internal consistency of a genetic dataset, as an additional metric for assessing how tree-like a linguistic dataset is. We use TIGER values to explore simulated language data ranging from very tree-like to completely unstructured, and also use them to analyze a cognate-coded basic vocabulary dataset of Uralic languages. As a point of comparison for the TIGER values, we also explore the same data using δ scores, Q-residuals, and NeighborNets. Our results suggest that TIGER values are capable of both ranking tree-like datasets according to their degree of treelikeness, as well as distinguishing datasets with tree-like structure from datasets with a nontree-like structure. Consequently, we argue that TIGER values serve as a useful metric for measuring the historical heterogeneity of datasets. Our results also highlight the complexities in measuring treelikeness from linguistic data, and how the metrics approach this question from different perspectives.

The first third-generation HIV-1 circulating recombinant form (CRF114_0155) identified in central China.

A novel circulating recombinant form (CRF) was identified in eight HIV-1-infected patients without direct epidemiological relationships in Henan Province, Central China. Recombination analysis indicated that the genome of this novel CRF comprises five segments: three inherited from CRF01_AE cluster-4 and two from CRF55_01B. Therefore, the CRF was designated CRF114_0155. It is not only the first novel CRF identified in Henan Province but also the first third-generation CRF of HIV-1 and the first CRF descendant of CRF55_01B. Bayesian inference of phylogeny dated the most recent common ancestor of the CRF114_0155 cluster to 2010. The emergence of CRF114_0155 reflects that the genotype constitution of HIV-1 has become more complex and that stricter intervention measures should be implemented in central China.

Accounting for the Biological Complexity of Pathogenic Fungi in Phylogenetic Dating.

In the study of pathogen evolution, temporal dating of phylogenies provides information on when species and lineages may have diverged in the past. When combined with spatial and epidemiological data in phylodynamic models, these dated phylogenies can also help infer where and when outbreaks occurred, how pathogens may have spread to new geographic locations and/or niches, and how virulence or drug resistance has developed over time. Although widely applied to viruses and, increasingly, to bacterial pathogen outbreaks, phylogenetic dating is yet to be widely used in the study of pathogenic fungi. Fungi are complex organisms with several biological processes that could present issues with appropriate inference of phylogenies, clock rates, and divergence times, including high levels of recombination and slower mutation rates although with potentially high levels of mutation rate variation. Here, we discuss some of the key methodological challenges in accurate phylogeny reconstruction for fungi in the context of the temporal analyses conducted to date and make recommendations for future dating studies to aid development of a best practices roadmap in light of the increasing threat of fungal outbreaks and antifungal drug resistance worldwide.