Motivation Rooted species trees are a basic model with multiple applications throughout biology, including understanding adaptation, biodiversity, phylogeography and co-evolution. Because most species tree estimation methods produce unrooted trees, methods for rooting these trees have been developed. However, most rooting methods either rely on prior biological knowledge or assume that evolution is close to clock-like, which is not usually the case. Furthermore, most prior rooting methods do not account for biological processes that create discordance between gene trees and species trees. Results We present Quintet Rooting (QR), a method for rooting species trees based on a proof of identifiability of the rooted species tree under the multi-species coalescent model established by Allman, Degnan and Rhodes (J. Math. Biol., 2011). We show that QR is generally more accurate than other rooting methods, except under extreme levels of gene tree estimation error. Availability and implementation Quintet Rooting is available in open source form at https://github.com/ytabatabaee/Quintet-Rooting. The simulated datasets used in this study are from a prior study and are available at https://www.ideals.illinois.edu/handle/2142/55319. The biological dataset used in this study is also from a prior study and is available at http://gigadb.org/dataset/101041. Supplementary information Supplementary data are available at Bioinformatics online.
DNA is emerging as an increasingly attractive medium for data storage due to a number of important and unique advantages it offers, most notably the unprecedented durability and density. While
Rooted species trees are used in several downstream applications of phylogenetics. Most species tree estimation methods produce unrooted trees and additional methods are then used to root these unrooted trees. Recently, Quintet Rooting (QR) (Tabatabaee et al., ISMB and Bioinformatics 2022), a polynomial-time method for rooting an unrooted species tree given unrooted gene trees, was introduced. QR, which is based on a proof of identifiability of rooted 5-taxon trees in the presence of incomplete lineage sorting, was shown to have good accuracy, improving over other methods for rooting species trees when incomplete lineage sorting was the only cause of gene tree discordance, except when gene tree estimation error was very high. However, that study left the statistical consistency of QR as an open question. We present QR-STAR, a polynomial-time variant of QR that has an additional step for determining the rooted shape of each quintet tree. We prove that QR-STAR is statistically consistent under the multi-species coalescent (MSC) model. Our simulation study under a variety of model conditions shows that QR-STAR matches or improves on the accuracy of QR. QR-STAR is available in open source form at https://github.com/ytabatabaee/Quintet-Rooting.
Genes evolve under processes such as gene duplication and loss (GDL), so that gene family trees are multi-copy, as well as incomplete lineage sorting (ILS); both processes produce gene trees that differ from the species tree. The estimation of species trees from sets of gene family trees is challenging, and the estimation of rooted species trees presents additional analytical challenges. Two of the methods developed for this problem are STRIDE (Emms and Kelly, MBE 2017), which roots species trees by considering GDL events, and Quintet Rooting (Tabatabaee et al., ISMB 2022 and Bioinformatics 2022), which roots species trees by considering ILS. We present DISCO+QR, a new method for rooting species trees in the presence of both GDL and ILS. DISCO+QR, operates by taking the input gene family trees and decomposing them into single-copy trees using DISCO (Willson et al., Systematic Biology 2022) and then roots the given species tree using the information in the single-copy gene trees using Quintet Rooting (QR). We show that the relative accuracy of STRIDE and DISCO+QR depend on properties of the dataset (number of species, genes, rate of gene duplication, degree of ILS, and gene tree estimation error), and that each provides advantages over the other under some conditions. Availability: DISCO and QR are available in github. The supplementary materials are available at http://tandy.cs.illinois.edu/discoqr-suppl.pdf.
Genes evolve under processes such as gene duplication and loss (GDL), so that gene family trees are multi-copy, as well as incomplete lineage sorting (ILS); both processes produce gene trees that differ from the species tree. The estimation of species trees from sets of gene family trees is challenging, and the estimation of rooted species trees presents additional analytical challenges. Two of the methods developed for this problem are STRIDE (Emms and Kelly, MBE 2017), which roots species trees by considering GDL events, and Quintet Rooting (Tabatabaee et al., ISMB 2022 and Bioinformatics 2022), which roots species trees by considering ILS. We present DISCO+QR, a new approach to rooting species trees that first uses DISCO to address GDL and then uses QR to perform rooting in the presence of ILS. DISCO+QR operates by taking the input gene family trees and decomposing them into single-copy trees using DISCO (Willson et al., Systematic Biology 2022) and then roots the given species tree using the information in the single-copy gene trees using Quintet Rooting (QR). We show that the relative accuracy of STRIDE and DISCO+QR depend on properties of the dataset (number of species, genes, rate of gene duplication, degree of ILS, and gene tree estimation error), and that each provides advantages over the other under some conditions. Availability: DISCO and QR are available in github.
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