Biology subjects

Kubatko, L.

Publications and source records attributed to Kubatko, L..

17 recordsLinked to original sources

bioRxiv2025

Composite Likelihood Adjustment in Bayesian Inference for Estimating Species Tree Parameters Under the Multispecies Coalescent

Composite likelihood methods have long been used in biology to facilitate efficient computation for the high-dimensional, dependent structures commonly present in genetic data. In species-level phylogenetic inference under the multispecies coalescent model, the full likelihood is computationally intractable, while the composite likelihood can be efficiently computed. However, using the composite likelihood instead of the full likelihood in Bayesian inference involves repeated use of data, resulting in overly concentrated posteriors. We develop a method that incorporates an adjustment to the composite likelihood in a Bayesian framework to adjust the approximated posterior distributions so that credible intervals achieve the correct coverage. Both simulated and empirical data are used to show that our method compares favorably with existing methods with respect to both computation time and accuracy.

evolutionary biology↗

bioRxiv2023

A Robust Combination Test Using the Normal Distribution, with Application to Phylogenetic Inference

Combination tests are used to combine P-values from individual studies to test a global null hypothesis. These types of tests can also be applied to combine P-values from testing separate null hypotheses within the same study in cases for which the procedure for testing a global null hypothesis is unavailable. One such application of a combination test is to detect the presence of hybrid species within a set of species. Although many combination tests have been proposed in the literature, there is no uniformly most powerful test applicable for all conditions. For instance, in the hybrid detection application, it is expected that only a few of the species within a set species might have truly arisen via hybridization, and thus when tested, only a few of the individual P-values are expected to be significant. Thus, a desirable property of a combination test for this situation is to be able to reject the global null hypothesis even if only a small fraction of the individual P-values are significant. In this paper, we propose a new combination test based on the normal distribution that assigns weight to each test adaptively, thereby providing powerful results even when only a small fraction of the individual null hypotheses are false. A comprehensive simulation study, as well as real data applications, demonstrate that the proposed test is powerful in detecting false global null hypotheses under several situations for which existing tests have low power.

genetics↗

bioRxiv2023

CLOCI: Unveiling cryptic gene clusters with generalized detection

Gene clusters are genomic loci that contain multiple genes that are functionally and genetically linked. Gene clusters collectively encode diverse functions, including small molecule biosynthesis, nutrient assimilation, metabolite degradation, and production of proteins essential for growth and development. Identifying gene clusters is a powerful tool for small molecule discovery and provides insight into the ecology and evolution of organisms. Current detection algorithms focus on canonical "core" biosynthetic functions many gene clusters encode, while overlooking uncommon or unknown cluster classes. These overlooked clusters are a potential source of novel natural products and comprise an untold portion of overall gene cluster repertoires. Unbiased, function-agnostic detection algorithms therefore provide an opportunity to reveal novel classes of gene clusters and more precisely define genome organization. We present CLOCI (Co-occurrence Locus and Orthologous Cluster Identifier), an algorithm that identifies gene clusters using multiple proxies of selection for coordinated gene evolution. Our approach generalizes gene cluster detection and gene cluster family circumscription, improves detection of multiple known functional classes, and unveils noncanonical gene clusters. CLOCI is suitable for genome-enabled small molecule mining, and presents an easily tunable approach for delineating gene cluster families and homologous loci.

genomics↗

bioRxiv2023

A Likelihood Ratio Test for Hybridization Under the Multispecies Coalescent

Several methods have been developed to carry out a statistical test for hybridization at the species level, including the ABBA-BABA test and HyDe. Here, we propose a new method for detecting hybridization and quantifying the extent of hybridization. Our test computes the likelihood of a species tree that is possibly subject to hybridization using site pattern frequencies from genomic-scale datasets under the multispecies coalescent. To do this, we extend the calculation of the likelihood for site pattern frequency data for the 4-taxon symmetric and asymmetric species trees proposed in Chifman and Kubatko (2015) by incorporating an inheritance parameter, resulting in efficient computation of the likelihood under a scenario of hybridization. We use this likelihood computation to construct a likelihood ratio test that a given species is a hybrid of two parental species. Simulations demonstrate that our test is more powerful than existing tests of hybridization, including HyDe, and that it achieves the desired type I error rate. We apply the method to two empirical data sets, one for which hybridization is believed to have occurred and one for which previous methods have failed to detect hybridization.

evolutionary biology↗

bioRxiv2023

A global test of hybrid ancestry fromgenome-scale data

Methods based on the multi-species coalescence have been widely used in phylogenetic tree estimation using genome-scale DNA sequence data to understand the underlying evolutionary relationship between the sampled species. Evolutionary processes such as hybridization, which creates new species through interbreeding between two different species, necessitate inferring a species network instead of a species tree. A species tree is strictly bifurcating and thus fails to incorporate hybridization events which require an internal node of degree three. Hence, it is crucial to decide whether a tree or network analysis should be performed given a DNA sequence data set, a decision that is based on the presence of hybrid species in the sampled species. Although many methods have been proposed for hybridization detection, it is rare to find a technique that does so globally while considering a data generation mechanism that allows both hybridization and incomplete lineage sorting. In this paper, we consider hybridization and coalescence in a unified framework and propose a new test that can detect whether there are any hybrid species in a given set of species. We propose that based on this global test of hybridization, one can decide whether a tree or network analysis is appropriate for a given data set.

bioinformatics↗

bioRxiv2023

Effects of phylogenetic variation on prioritization of species for conservation

Many questions in evolutionary biology require the specification of a phylogeny for downstream phylogenetic analyses. However, with the increasingly widespread availability of genomic data, phylogenetic studies are often confronted with conflicting signal in the form of genomic heterogeneity and incongruence between gene trees and the species tree. This raises the question of determining what data and phylogeny should be used in downstream analyses, and to what extent the choice of phylogeny (e.g., gene trees versus species trees) impacts the analyses and their outcomes. In this paper, we study this question in the realm of phylogenetic diversity indices, which provide ways to prioritize species for conservation based on their relative evolutionary isolation on a phylogeny, and are thus one example of downstream phylogenetic analyses. We use the Fair Proportion (FP) index, also known as the evolutionary distinctiveness score, and explore the variability in species rankings based on gene trees as compared to the species tree for several empirical data sets. Our results indicate that prioritization rankings among species vary greatly depending on the underlying phylogeny, suggesting that the choice of phylogeny is a major influence in assessing phylogenetic diversity in a conservation setting. While we use phylogenetic diversity conservation as an example, we suspect that other types of downstream phylogenetic analyses such as ancestral state reconstruction are similarly affected by genomic heterogeneity and incongruence. Our aim is thus to raise awareness of this issue and inspire new research on which evolutionary information (species trees, gene trees, or a combination of both) should form the basis for analyses in these settings.

evolutionary biology↗

bioRxiv2022

Inference of Phylogenetic Networks from Sequence Data using Composite Likelihood

While phylogenies have been essential in understanding how species evolve, they do not adequately describe some evolutionary processes. For instance, hybridization, a common phenomenon where interbreeding between two species leads to formation of a new species, must be depicted by a phylogenetic network, a structure that modifies a phylogeny by allowing two branches to merge into one, resulting in reticulation. However, existing methods for estimating networks are computationally expensive as the dataset size and/or topological complexity increase. The lack of methods for scalable inference hampers phylogenetic networks from being widely used in practice, despite accumulating evidence that hybridization occurs frequently in nature. Here, we propose a novel method, PhyNEST (Phylogenetic Network Estimation using SiTe patterns), that estimates phylogenetic networks directly from sequence data. PhyNEST achieves computational efficiency by using composite likelihood as well as accuracy by using the full genomic data to incorporate all sources of variability, rather than first summarizing the data by estimating a set of gene trees, as is required by most of the existing methods. To efficiently search network space, we implement both hill-climbing and simulated annealing algorithms. Simulation studies show that PhyNEST can accurately estimate parameters given the true network topology and that it has comparable accuracy to two popular methods that use composite likelihood and a set of gene trees as input, implemented in SNaQ and PhyloNet. For datasets with a large number of loci, PhyNEST is more efficient than SNaQ and PhyloNet when considering the time required for gene tree estimation. We applied PhyNEST to reconstruct the evolutionary relationships among Heliconius butterflies and Papionini primates, characterized by hybrid speciation and widespread introgression, respectively. PhyNEST is implemented in an open-source Julia package and publicly available at https://github.com/sungsik-kong/PhyNEST.jl.

evolutionary biology↗

bioRxiv2021

Site Pattern Probabilities Under the Multispecies Coalescent and a Relaxed Molecular Clock: Theory and Applications

1The first step in statistical inference of the evolutionary histories of species is developing a probability model that describes the mutation process as accurately and realistically as possible. A major complication of this inference is that different loci on the genome can have histories that diverge from the common species history and each other. The multispecies coalescent process is commonly used to model one source of this divergence, incomplete lineage sorting, or ILS. Chifman and Kubatko (2015) computed the site pattern probabilities for four taxa under a full probability model based on the Jukes-Cantor substitution model when the molecular clock holds. This paper generalizes that work to a relaxed clock model, allowing for mutation rates to differ among species. This will enable better phylogentic inference in cases where the molecular clock does not hold.

evolutionary biology↗

bioRxiv2021

Phylogenetics of a Rapid, Continental Radiation: Diversification, Biogeography, and Circumscription of the Beardtongues (Penstemon; Plantaginaceae)

Penstemon (Plantaginaceae), the largest genus of plants native to North America, represents a recent continental evolutionary radiation. We investigated patterns of diversification, phylogenetic relationships, and biogeography, and determined the age of the lineage using 43 nuclear gene loci. We also assessed the current taxonomic circumscription of the ca. 285 species by developing a phylogenetic taxonomic bootstrap method. Penstemon originated during the Pliocene/Pleistocene transition. Patterns of diversification and biogeography are associated with glaciation cycles during the Pleistocene, with the bulk of diversification occurring from 1.0-0.5 mya. The radiation across the North American continent tracks the advance and retreat of major and minor glaciation cycles during the past 2.5 million years with founder-event speciation contributing the most to diversification of Penstemon. Our taxonomic bootstrap analyses suggest the current circumscription of the genus is in need of revision. We propose rearrangement of subgenera, sections, and subsections based on our phylogenetic results. Given the young age and broad distribution of Penstemon across North America, it offers an excellent system for studying a rapid evolutionary radiation in a continental setting.

evolutionary biology↗

bioRxiv2021

Distinct Patterns of Emergence of SARS-CoV-2 Spike Variants including N501Y in Clinical Samples in Columbus Ohio

Following the worldwide emergence of the p.Asp614Gly shift in the Spike (S) gene of SARS-CoV-2, there have been few recurring pathogenic shifts occurring during 2020, as assessed by genomic sequencing. This situation has evolved in the last several months with the emergence of several distinct variants (first identified in the United Kingdom and South Africa) that manifest multiple changes in the S gene, particularly p.Asn501Tyr (N501Y), that likely have clinical impact. We report here the emergence in Columbus, Ohio in December 2020 of two novel SARS-CoV-2 clade 20G variants. One variant, that has become the predominant virus found in nasopharyngeal swabs in the December 2020-January 2021 period, harbors S p.Gln677His (Q677H), affecting a consensus QTQTN domain near the S1/S2 furin cleavage site, nucleocapsid (N) p.Asp377Tyr (D377Y) and membrane glycoprotein (M) p.Ala85Ser (A85S) mutations, with additional S mutations in subsets. The other variant present in two samples, contains S N501Y, which is a marker of the UK-B.1.1.7 (clade 20I/501Y.V1) strain, but lacks all other mutations from that virus. The Ohio variant is from a different clade and shares multiple mutations with the clade 20G viruses circulating in the area prior to December 2020. These two SARS-CoV-2 viruses, which we show are also present and evolving currently in several other parts of North America, add to the diversity of S gene shifts occurring worldwide. These and other shifts in this period of the pandemic support multiple independent acquisition of functionally significant and potentially complementing mutations affecting the S QTQTN site (Q675H or Q677H) and certain receptor binding domain mutations (e.g., E484K and N501Y).

genomics↗

bioRxiv2020

Identifiability of speciation times under the multispecies coalescent

The advent of rapid and inexpensive sequencing technologies has necessitated the development of computationally efficient methods for analyzing sequence data for many genes simultaneously in a phylogenetic framework. The coalescent process is the most commonly used model for linking the underlying genealogies of individual genes with the global species-level phylogeny, but inference under the coalescent model is computationally daunting in the typical inference frameworks (e.g., the likelihood and Bayesian frameworks) due to the dimensionality of the space of both gene trees and species trees. Here we consider estimation of the branch lengths in fixed species trees with three or four taxa, and show that these branch lengths are identifiable. We also show that for three and four taxa simple estimators for the branch lengths can be derived based on observed site pattern frequencies. Properties of these estimators, such as their asymptotic variances and large-sample distributions, are examined, and performance of the estimators is assessed using simulation. Finally, we use these estimators to develop a hypothesis test that can be used to delimit species under the coalescent model for three or four putative taxa.

evolutionary biology↗

bioRxiv2020

Comparative Performance of Popular Methods for Hybrid Detection using Genomic Data

AO_SCPLOWBSTRACTC_SCPLOWInterspecific hybridization is an important evolutionary phenomenon that generates genetic variability in a population and fosters species diversity in nature. The availability of large genome scale datasets has revolutionized hybridization studies to shift from the examination of the presence or absence of hybrids in nature to the investigation of the genomic constitution of hybrids and their genome-specific evolutionary dynamics. Although a handful of methods have been proposed in an attempt to identify hybrids, accurate detection of hybridization from genomic data remains a challenging task. The available methods can be classified broadly as site pattern frequency based and population genetic clustering approaches, though the performance of the two classes of methods under different hybridization scenarios has not been extensively examined. Here, we use simulated data to comparatively evaluate the performance of four tools that are commonly used to infer hybridization events: the site pattern frequency based methods HyDe and the D-statistic (i.e., the ABBA-BABA test), and the population clustering approaches structure and ADMIXTURE. We consider single hybridization scenarios that vary in the time of hybridization and the amount of incomplete lineage sorting (ILS) for different proportions of parental contributions ({gamma}); introgressive hybridization; multiple hybridization scenarios; and a mixture of ancestral and recent hybridization scenarios. We focus on the statistical power to detect hybridization, the false discovery rate (FDR) for the D-statistic and HyDe, and the accuracy of the estimates of{gamma} as measured by the mean squared error for HyDe, structure, and ADMIXTURE. Both HyDe and the D-statistic demonstrate a high level of detection power in all scenarios except those with high ILS, although the D-statistic often has an unacceptably high FDR. The estimates of{gamma} in HyDe are impressively robust and accurate whereas structure and ADMIXTURE sometimes fail to identify hybrids, particularly when the proportional parental contributions are asymmetric (i.e., when{gamma} is close to 0). Moreover, the posterior distribution estimated using structure exhibits multimodality in many scenarios, making interpretation difficult. Our results provide guidance in selecting appropriate methods for identifying hybrid populations from genomic data.

bioinformatics↗

bioRxiv2020

A Phylogenetic Approach to Inferring the Order in Which Mutations Arise during Cancer Progression

SO_SCPLOWUMMARYC_SCPLOWAlthough the role of evolutionary process in cancer progression is widely accepted, increasing attention is being given to the evolutionary mechanisms that can lead to differences in clinical outcome. Recent studies suggest that the temporal order in which somatic mutations accumulate during cancer progression is important. Single-cell sequencing provides a unique opportunity to examine the mutation order during cancer progression. However, the errors associated with single-cell sequencing complicate this task. We propose a new method for inferring the order in which somatic mutations arise within a tumor using noisy single-cell sequencing data that incorporates the errors that arise from the data collection process. Using simulation, we show that our method outperforms existing methods for identifying mutation order in most cases, especially when the number of cells is large. Our method also provides a means to quantify the uncertainty in the inferred mutation order along a fixed phylogeny. We apply our method to empirical data from colorectal and prostate cancer patients.

evolutionary biology↗

bioRxiv2019

Estimation of Speciation Times Under the Multispecies Coalescent

MotivationThe multispecies coalescent model is now widely accepted as an effective model for incorporating variation in the evolutionary histories of individual genes into methods for phylogenetic inference from genome-scale data. However, because model-based analysis under the coalescent can be computationally expensive for large data sets, a variety of inferential frameworks and corresponding algorithms have been proposed for estimation of species-level phylogenies and associated parameters, including speciation times and effective population sizes. ResultsWe consider the problem of estimating the timing of speciation events along a phylogeny in a coalescent framework. We propose a maximum a posteriori estimator based on composite likelihood (MAPCL) for inferring these speciation times under a model of DNA sequence evolution for which exact site pattern probabilities can be computed under the assumption of a constant{theta} throughout the species tree. We demonstrate that the MAPCL estimates are statistically consistent and asymptotically normally distributed, and we show how this result can be used to estimate their asymptotic variance. We also provide a more computationally efficient estimator of the asymptotic variance based on the nonparametric bootstrap. We evaluate the performance of our method using simulation and by application to an empirical dataset for gibbons. Availability and implementationThe method has been implemented in the PAUP* program, freely available at https://paup.phylosolutions.com for Macintosh, Windows, and Linux operating systems. Contactpeng.650@osu.edu Supplementary informationSupplementary data are available at Bioinformatics online.

evolutionary biology↗

bioRxiv2019

Consistency of SVDQuartets and Maximum Likelihood for Coalescent-based Species Tree Estimation

AbtractNumerous methods for inferring species-level phylogenies under the coalescent model have been proposed within the last 20 years, and debates continue about the relative strengths and weaknesses of these methods. One desirable property of a phylogenetic estimator is that of statistical consistency, which means intuitively that as more data are collected, the probability that the estimated tree has the same topology as the true tree goes to 1. To date, consistency results for species tree inference under the multispecies coalescent have been derived only for summary statistics methods, such as ASTRAL and MP-EST. These methods have been found to be consistent given true gene trees, but may be inconsistent when gene trees are estimated from data for loci of finite length (Roch et al., 2019). Here we consider the question of statistical consistency for four taxa for SVDQuartets for general data types, as well as for the maximum likelihood (ML) method in the case in which the data are a collection of sites generated under the multispecies coalescent model such that the sites are conditionally independent given the species tree (we call these data Coalescent Independent Sites (CIS) data). We show that SVDQuartets is statistically consistent for all data types (i.e., for both CIS data and for multilocus data), and we derive its rate of convergence. We additionally show that ML is consistent for CIS data under the JC69 model, and discuss why a proof for the more general multilocus case is difficult. Finally, we compare the performance of maximum likelihood and SDVQuartets using simulation for both data types.

evolutionary biology↗

bioRxiv2018

Evolutionary insights into Bean common mosaic necrosis virus and Cowpea aphid borne mosaic virus using global isolates and thirteen new near complete genomes from Kenya

Plant viral diseases are one of the major limitations in legume production within sub Saharan Africa (SSA), as they account for up to 100 % in production losses within smallholder farms. In this study, field surveys were conducted in the western highlands of Kenya with viral symptomatic leaf samples collected. Subsequently, next-generation sequencing was carried out. The main aim was to gain insights into the selection pressure and evolutionary relationships of Bean common mosaic necrosis virus (BCMNV) and Cowpea aphid-borne mosaic virus (CABMV), within symptomatic common beans and cowpeas. Eleven near complete genomes of BCMNV and two for CABMV sequences were obtained from SSA. Bayesian phylogenomic analysis and tests for differential selection pressure within sites and across tree branches of the viral genomes was carried out. Three distinct well-supported clades were identified across the whole genome tree, and were in agreement with individual gene trees. Selection pressure analysis within sites and across phylogenetic branches suggested both viruses were evolving independently, but under strong purifying selection, with a slow evolutionary rate. These findings provide valuable insights on the evolution of BCMNV and CABMV genomes and their relationship to other viral genomes globally. These results will contribute greatly to the knowledge gap surrounding the phylogenomic relationship of these viruses, particularly for CABMV, for which there are few genome sequences available, and support the current breeding efforts towards resistance for BCMNV and CABMV.

evolutionary biology↗

bioRxiv2017

SNP genotyping and parameter estimation in polyploids using low-coverage sequencing data

MotivationGenotyping and parameter estimation using high throughput sequencing data are everyday tasks for population geneticists, but methods developed for diploids are typically not applicable to polyploid taxa. This is due to their duplicated chromosomes, as well as the complex patterns of allelic exchange that often accompany whole genome duplication (WGD) events. For WGDs within a single lineage (auto polyploids), inbreeding can result from mixed mating and/or double reduction. For WGDs that involve hybridization (allopolyploids), alleles are typically inherited through independently segregating subgenomes.\n\nResultsWe present two new models for estimating genotypes and population genetic parameters from genotype likelihoods for auto- and allopolyploids. We then use simulations to compare these models to existing approaches at varying depths of sequencing coverage and ploidy levels. These simulations show that our models typically have lower levels of estimation error for genotype and parameter estimates, especially when sequencing coverage is low. Finally, we also apply these models to two empirical data sets from the literature. Overall, we show that the use of genotype likelihoods to model non-standard inheritance patterns is a promising approach for conducting population genomic inferences in polyploids.\n\nAvailabilityA C++ program, EBG, is provided to perform inference using the models we describe. It is available under the GNU GPLv3 on GitHub:\n\nhttps://github.com/pblischak/polyploid-genotyping.\n\nContact: blischak.4@osu.edu.

bioinformatics↗