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

Legried, Brandon; Molloy, Erin K.; Warnow, Tandy; Roch, Sébastien

doi:10.1007/978-3-030-45257-5_8

Cited by 9 publications

(11 citation statements)

References 40 publications

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“…2019 ) and only use the 400–800 single-copy gene trees. A recent result by Legried et al. (2020) asserts that treating gene copies as alleles of a same gene, a feature ASTRAL supports ( Rabiee et al.…”

Section: Introductionmentioning

confidence: 99%

ASTRAL-Pro: Quartet-Based Species-Tree Inference despite Paralogy

Zhang

Scornavacca

Molloy

et al. 2020

Molecular Biology and Evolution

163

175

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Phylogenetic inference from genome-wide data (phylogenomics) has revolutionized the study of evolution because it enables accounting for discordance among evolutionary histories across the genome. To this end, summary methods have been developed to allow accurate and scalable inference of species trees from gene trees. However, most of these methods, including the widely used ASTRAL, can only handle single-copy gene trees and do not attempt to model gene duplication and gene loss. As a result, most phylogenomic studies have focused on single-copy genes and have discarded large parts of the data. Here, we first propose a measure of quartet similarity between single-copy and multicopy trees that accounts for orthology and paralogy. We then introduce a method called ASTRAL-Pro (ASTRAL for PaRalogs and Orthologs) to find the species tree that optimizes our quartet similarity measure using dynamic programing. By studying its performance on an extensive collection of simulated data sets and on real data sets, we show that ASTRAL-Pro is more accurate than alternative methods.

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Section: Introductionmentioning

confidence: 99%

ASTRAL-Pro: Quartet-Based Species-Tree Inference despite Paralogy

Zhang

Scornavacca

Molloy

et al. 2020

Molecular Biology and Evolution

163

175

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“…Besides our method, one can attempt to sample single-copy gene trees [41], an approach that we plan to test in the future. Most recently, there has been theoretical and empirical evidence that simply treating gene copies as alleles may be sufficient [40]. We showed that this alternative, although attractive in theory, is less accurate and less scalable than A-Pro.…”

Section: Discussionmentioning

confidence: 97%

“…ASTRAL-multi [39] is a feature of ASTRAL designed for handling multiple individuals. A recent paper (concurrently submitted) proposes to use ASTRAL-multi for multi-copy data [40]. Due to its high memory requirements, we were able to include it in only one experiment of S25.…”

Section: Methods Comparedmentioning

confidence: 99%

“…For example, two studies on plant transcriptomes had to restrict species tree analyses with ASTRAL to the 400-800 putative single-copy gene trees, discarding thousands of available multi-copy genes [37,38]. A surprising result asserts that treating gene copies as alleles of a same gene, a feature ASTRAL supports [39], is statistically consistent under a standard parametric model of gene duplication and loss and may be accurate [40]. Others have shown that random sampling of leaves works well empirically [41].…”

Section: Introductionmentioning

confidence: 99%

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ASTRAL-Pro: quartet-based species tree inference despite paralogy

Zhang

Scornavacca

Molloy

et al. 2019

Preprint

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Species tree inference via summary methods that combine gene trees has become an increasingly common analysis in recent phylogenomic studies. This broad adoption has been partly due to the greater availability of genome-wide data and ample recognition that gene trees and species trees can differ due to biological processes such as gene duplication and gene loss. This increase has also been encouraged by the recent development of accurate and scalable summary methods, such as ASTRAL. However, most of these methods, including ASTRAL, can only handle single-copy gene trees and do not attempt to model gene duplication and gene loss. In this paper, we introduce a measure of quartet similarity between single-copy and multi-copy trees (accounting for orthology and paralogy relationships) that can be optimized via a scalable dynamic programming similar to the one used by ASTRAL. We then present a new quartet-based species tree inference method: ASTRAL-Pro (ASTRAL for PaRalogs and Orthologs). By studying its performance on an extensive collection of simulated datasets and on a real plant dataset, we show that ASTRAL-Pro is more accurate than alternative methods when gene trees differ from the species tree due to the simultaneous presence of gene duplication, gene loss, incomplete lineage sorting, and estimation errors.

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“…By definition, orthologs are always found in different species, though paralogs can be found in either the same or different species (e.g., when duplication precedes a speciation event; Supplementary Figure S1). Identifying orthologous genes across species is important for many tasks, including the inference of species relationships (but see [14,33,56]).…”

Section: Introductionmentioning

confidence: 99%

The Ortholog Conjecture Revisited: the Value of Orthologs and Paralogs in Function Prediction

Stamboulian

Guerrero

Hahn

et al. 2019

Preprint

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The computational prediction of gene function is a key step in making full use of newly sequenced genomes. Function is generally predicted by transferring annotations from homologous genes or proteins for which experimental evidence exists. The "ortholog conjecture" proposes that orthologous genes should be preferred when making such predictions, as they evolve functions more slowly than paralogous genes. Previous research has provided little support for the ortholog conjecture, though the incomplete nature of the data cast doubt on the conclusions. Here we use experimental annotations from over 40,000 proteins, drawn from over 80,000 publications, to revisit the ortholog conjecture in two pairs of species: (i) Homo sapiens and Mus musculus and (ii) Saccharomyces cerevisiae and Schizosaccharomyces pombe. By making a distinction between questions about the evolution of function versus questions about the prediction of function, we find strong evidence against the ortholog conjecture in the context of function prediction, though questions about the evolution of function remain difficult to address. In both pairs of species, we quantify the amount of data that must be ignored if paralogs are discarded, as well as the resulting loss in prediction accuracy. Taken as a whole, our results support the view that the types of homologs used for function transfer are largely irrelevant to the task of function prediction. Aiming to maximize the amount of data used for this task, regardless of whether it comes from orthologs or paralogs, is most likely to lead to higher prediction accuracy.

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

Cited by 9 publications

References 40 publications

ASTRAL-Pro: Quartet-Based Species-Tree Inference despite Paralogy

ASTRAL-Pro: Quartet-Based Species-Tree Inference despite Paralogy

ASTRAL-Pro: quartet-based species tree inference despite paralogy

The Ortholog Conjecture Revisited: the Value of Orthologs and Paralogs in Function Prediction

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