Gene tree parsimony for incomplete gene trees: addressing true biological loss

Bayzid, Shamsuzzoha; Warnow, Tandy

doi:10.1186/s13015-017-0120-1

Cited by 30 publications

(38 citation statements)

References 36 publications

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“…Gene‐tree inference uncertainty and hybridization (including subsequent introgression and homoploid or polyploid speciation) are two additional possible sources of gene‐tree and gene‐species tree discordance that our methods do not take into account. Gene‐tree estimation error is also likely to occur with most biological data sets, but may be more challenging for multi‐copy genes spanning a large number of species (Bayzid and Warnow, ), and so may be a more minor source of discordance in our pilot 38‐taxon LSCN gene set. Hybridization is generally not well characterized for the lineages sampled here, except for the putative hybrid D .…”

Section: Discussionmentioning

confidence: 99%

A customized nuclear target enrichment approach for developing a phylogenomic baseline for Dioscorea yams (Dioscoreaceae)

Gomez

Pokorny

Kantar³

et al. 2019

Appl Plant Sci

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Premise We developed a target enrichment panel for phylogenomic studies of Dioscorea , an economically important genus with incompletely resolved relationships. Methods Our bait panel comprises 260 low‐ to single‐copy nuclear genes targeted to work in Dioscorea , assessed here using a preliminary taxon sampling that includes both distantly and closely related taxa, including several yam crops and potential crop wild relatives. We applied coalescent‐based and maximum likelihood phylogenomic inference approaches to the pilot taxon set, incorporating new and published transcriptome data from additional species. Results The custom panel retrieved ~94% of targets and >80% of full gene length from 88% and 68% of samples, respectively. It has minimal gene overlap with existing panels designed for angiosperm‐wide studies and generally recovers longer and more variable targets. Pilot phylogenomic analyses consistently resolve most deep and recent relationships with strong support across analyses and point to revised relationships between the crop species D. alata and candidate crop wild relatives. Discussion Our customized panel reliably retrieves targeted loci from Dioscorea , is informative for resolving relationships in denser samplings, and is suitable for refining our understanding of the independent origins of cultivated yam species; the panel likely has broader promise for phylogenomic studies across Dioscoreales.

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Section: Discussionmentioning

confidence: 99%

A customized nuclear target enrichment approach for developing a phylogenomic baseline for Dioscorea yams (Dioscoreaceae)

Gomez

Pokorny

Kantar³

et al. 2019

Appl Plant Sci

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“…We also note the surprising accuracy of both DupTree and MulRF, methods that, like ASTRAL, are not based on likelihood under a GDL model. Therefore, DynaDup [22,4] is also of potential interest, as it is similar to DupTree in seeking a tree that minimizes the duploss score (though the score is modified to reflect true biological loss), but has the potential to scale to larger datasets via its use of dynamic programming to solve the optimization problem in polynomial time within a constrained search space. In addition, other methods could also be explored, including more computationally intensive methods such as InferNetwork ML and InferNetwork MPL (maximum likelihood and maximum pseudo-likelihood methods in PhyloNet [32,36]) restricted so that they produce trees rather than reticulate phylogenies, or PHYLDOG [5], a Bayesian method for co-estimation of gene trees and the species tree under a GDL model.…”

Section: Discussionmentioning

confidence: 99%

Polynomial-Time Statistical Estimation of Species Trees under Gene Duplication and Loss

Legried

Molloy

Warnow

et al. 2019

Preprint

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Phylogenomics-the estimation of species trees from multilocus datasets-is a common step in many biological studies. However, this estimation is challenged by the fact that genes can evolve under processes, including incomplete lineage sorting (ILS) and gene duplication and loss (GDL), that make their trees different from the species tree. In this paper, we address the challenge of estimating the species tree under GDL. We show that species trees are identifiable under a standard stochastic model for GDL, and that the polynomial-time algorithm ASTRAL-multi, a recent development in the ASTRAL suite of methods, is statistically consistent under this GDL model. We also provide a simulation study evaluating ASTRAL-multi for species tree estimation under GDL.

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“…The algorithmic design (and corresponding theoretical results) in STELAR is structurally similar to ASTRAL. This sort of DP-based approach, which implicitly finds a maximum or minimum clique in a graph modelled from the input gene trees, was first used by [39] and later was used in Phylonet [40,41], DynaDup [35,42] and AS-TRAL. The key idea in STELAR is to find an equation for computing the number of triplets in the gene trees that agree with a given subtree in the species tree, which ultimately enables us to design a dynamic programming algorithm for estimating a species tree by maximizing the triplet agreement.…”

Section: Algorithmic Design Of Stelarmentioning

confidence: 99%

STELAR: A statistically consistent coalescent-based species tree estimation method by maximizing triplet consistency

Islam

Sarker

Das

et al. 2019

Preprint

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Background: Species tree estimation is frequently based on phylogenomic approaches that use multiple genes from throughout the genome. However, estimating a species tree from a collection of gene trees can be complicated due to the presence of gene tree incongruence resulting from incomplete lineage sorting (ILS), which is modelled by the multi-species coalescent process. Maximum likelihood and Bayesian MCMC methods can potentially result in accurate trees, but they do not scale well to large datasets. Results:We present STELAR (Species Tree Estimation by maximizing tripLet AgReement), a new fast and highly accurate statistically consistent coalescent-based method for estimating species trees from a collection of gene trees. We formalized the constrained triplet consensus (CTC) problem and showed that the solution to the CTC problem is a statistically consistent estimate of the species tree under the multi-species coalescent (MSC) model. STELAR is an efficient dynamic programming based solution to the CTC problem which is highly accurate and scalable. We evaluated the accuracy of STELAR in comparison with SuperTriplets, which is an alternate fast and highly accurate triplet-based supertree method, and with MP-EST and ASTRAL -two of the most popular and accurate coalescent-based methods. Experimental results suggest that STELAR matches the accuracy of ASTRAL and improves on MP-EST and SuperTriplets.Conclusions: Theoretical and empirical results (on both simulated and real biological datasets) suggest that STELAR is a valuable technique for species tree estimation from gene tree distributions.

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Gene tree parsimony for incomplete gene trees: addressing true biological loss

Cited by 30 publications

References 36 publications

A customized nuclear target enrichment approach for developing a phylogenomic baseline for Dioscorea yams (Dioscoreaceae)

A customized nuclear target enrichment approach for developing a phylogenomic baseline for Dioscorea yams (Dioscoreaceae)

Polynomial-Time Statistical Estimation of Species Trees under Gene Duplication and Loss

STELAR: A statistically consistent coalescent-based species tree estimation method by maximizing triplet consistency

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