Phylogenomic species tree estimation in the presence of incomplete lineage sorting and horizontal gene transfer

Davidson, Ruth; Vachaspati, Pranjal; Mirarab, Siavash; Warnow, Tandy

doi:10.1186/1471-2164-16-s10-s1

Cited by 69 publications

(44 citation statements)

References 57 publications

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“…This coincides with the reason ASTRAL is statistically consistent under the MSC as well as under a model for random HGT [28,8]. Furthermore, previous studies have shown that ASTRAL has good accuracy in simulation studies where both ILS and HGT are present [9]. Hence ASTRAL, which was originally designed for species tree estimation in the presence of ILS, has good accuracy and theoretical guarantees under different sources of gene tree heterogeneity.…”

Section: Discussionsupporting

confidence: 76%

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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Section: Discussionsupporting

confidence: 76%

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

Legried

Molloy

Warnow

et al. 2019

Preprint

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“…Another direction for future research entails characterizing the conditions under which species tree inference under the MSC is robust to the presence of paralogs in the data.Finally, while we did not discuss or incorporate gene flow in our study, it is possible that all three processes-ILS, GDL, and gene flow-are simultaneously involved in some phylogenomic analyses. Studies of the robustness of MSCbased species tree inference under some models of gene flow exist(Davidson et al, 2015;Roch 2012;Solís-Lemus et al, 2016;Steel…”

mentioning

confidence: 99%

Species Tree Inference on Data with Paralogs is Accurate Using Methods Intended to Deal with Incomplete Lineage Sorting

Yan¹,

Smith

Hahn

et al. 2018

Preprint

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Received ...; reviews returned ...; accepted ...Abstract.---The multispecies coalescent (MSC) has emerged as a powerful and desirable framework for species tree inference in phylogenomic studies. Under this framework, the data for each locus is assumed to consist of orthologous, single-copy genes, and heterogeneity across loci is assumed to be due to incomplete lineage sorting (ILS). These assumptions have led biologists that use ILS-aware inference methods, whether based directly on the MSC or proven to be statistically consistent under it (collectively referred to here as MSC-based methods), to exclude all loci that are present in more than a single copy in any of the studied genomes. Furthermore, such analyses entail orthology assignment to avoid the potential of hidden paralogy in the data. The question we seek to answer in this study is: What happens if one runs such species tree inference methods on data where paralogy is present, in addition to or without ILS being present? Through simulation studies and analyses of two biological data sets, we show that running such methods on data with paralogs provide very accurate results, either by treating all gene copies within a family as alleles from multiple individuals or by randomly selecting one copy per species. Our results have significant implications for the use of MSC-based phylogenomic analyses, demonstrating that they do not have to be restricted to single-copy loci, thus greatly increasing the amount of data that can be used. [Multispecies coalescent; incomplete lineage sorting; gene duplication and loss; orthology; paralogy.]

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“…The benefit of such an approach is that it would utilize one of a wide array of species tree inference methods that are both accurate and efficient, thus drastically reducing the space of phylogenetic networks to explore by limiting them to those "based" on inferred trees. Indeed, the question of whether a species tree can be accurately inferred in the presence of reticulation has been partially explored from theoretical [12] as well as empirical [4] angles. An extensive simulation study on small data sets demonstrated the problems with inferring "the" species tree in the presence of high rates of gene flow [13].…”

Section: Introductionmentioning

confidence: 99%

“…One potential approach to tackling the computational requirements of phylogenetic network inference is based on first inferring a "species tree" and then adding a set of reticulation edges to it, in the hope of obtaining the true network. Indeed, as discussed above, the plausibility of this approach has been addressed, albeit in a limited fashion [4,12,6,29,13]. If this approach works in practice, it would tremendously reduce the phylogenetic network space to search and, consequently, scale phylogenetic network inference to much larger data sets.…”

Section: Introductionmentioning

confidence: 99%

Empirical Performance of Tree-based Inference of Phylogenetic Networks

Cao¹,

Nakhleh²

2019

Preprint

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Phylogenetic networks extend the phylogenetic tree structure and allow for modeling vertical and horizontal evolution in a single framework. Statistical inference of phylogenetic networks is prohibitive and currently limited to small networks. An approach that could significantly improve phylogenetic network space exploration is based on first inferring an evolutionary tree of the species under consideration, and then augmenting the tree into a network by adding a set of "horizontal" edges to better fit the data.In this paper, we study the performance of such an approach on networks generated under a birth-hybridization model and explore its feasibility as an alternative to approaches that search the phylogenetic network space directly (without relying on a fixed underlying tree). We find that the concatenation method does poorly at obtaining a "backbone" tree that could be augmented into the correct network, whereas the popular species tree inference method ASTRAL does significantly better at such a task. We then evaluated the tree-tonetwork augmentation phase under the minimizing deep coalescence and pseudo-likelihood criteria. We find that even though this is a much faster approach than the direct search of the network space, * the accuracy is much poorer, even when the backbone tree is a good starting tree.Our results show that tree-based inference of phylogenetic networks could yield very poor results. As exploration of the network space directly in search of maximum likelihood estimates or a representative sample of the posterior is very expensive, significant improvements to the computational complexity of phylogenetic network inference are imperative if analyses of large data sets are to be performed. We show that a recently developed divide-and-conquer approach significantly outperforms tree-based inference in terms of accuracy, albeit still at a higher computational cost.

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Phylogenomic species tree estimation in the presence of incomplete lineage sorting and horizontal gene transfer

Cited by 69 publications

References 57 publications

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

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

Species Tree Inference on Data with Paralogs is Accurate Using Methods Intended to Deal with Incomplete Lineage Sorting

Empirical Performance of Tree-based Inference of Phylogenetic Networks

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