Unified modeling of gene duplication, loss, and coalescence using a locus tree

Rasmussen, Matthew D.; Kellis, M

doi:10.1101/gr.123901.111

Cited by 165 publications

(278 citation statements)

References 61 publications

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“…On the contrary, we observe that PHYLDOG can also erase a weak signal for ILS in gene trees. Refinements such as proposed in Rasmussen and Kellis (2012), in which a model of DL is combined with a model of incomplete lineage sorting could be implemented in PHYLDOG to study both population-level phenomena as well as the dynamics of gene family evolution.…”

Section: Discussionmentioning

confidence: 99%

“…In the case of the mammalian phylogeny, the role of ILS seems particularly problematic and could yield PHYLDOG to overestimate the number of DLs in gene histories. In order to evaluate the impact of ILS on the inference made by PHYLDOG, we performed two additional experiments: first, we used the simulated data set of gene trees from Rasmussen and Kellis (2012) to simulate sequences and run PHYLDOG (Supplemental subsection S6.2). This data set simulates the joint effect of ILS and DL on the evolution of gene families, under 24 conditions spanning a large range of parameters.…”

Section: Sensitivity To Incomplete Lineage Sortingmentioning

confidence: 99%

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Genome-scale coestimation of species and gene trees

et al. 2012

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Comparisons of gene trees and species trees are key to understanding major processes of genome evolution such as gene duplication and loss. Because current methods to reconstruct phylogenies fail to model the two-way dependency between gene trees and the species tree, they often misrepresent gene and species histories. We present a new probabilistic model to jointly infer rooted species and gene trees for dozens of genomes and thousands of gene families. We use simulations to show that this method accurately infers the species tree and gene trees, is robust to misspecification of the models of sequence and gene family evolution, and provides a precise historic record of gene duplications and losses throughout genome evolution. We simultaneously reconstruct the history of mammalian species and their genes based on 36 completely sequenced genomes, and use the reconstructed gene trees to infer the gene content and organization of ancestral mammalian genomes. We show that our method yields a more accurate picture of ancestral genomes than the trees available in the authoritative database Ensembl.[Supplemental material is available for this article.]The reconstruction of gene phylogenies based on sequences alone is difficult. First, homologous sequences are often hard to align unambiguously (Wong et al. 2008), which leads to incorrect gene trees and erroneous predictions of events of duplications and losses. Second, sequence alignments generally contain insufficient information to accurately model gene evolution and thus understand their history, as suggested by the positive correlation found between sequence length and congruence to the species tree (Galtier 2007). However, knowing the relationships among the species in which these sequences have evolved can improve gene tree inference. Several methods have successfully implemented this idea by combining sequence evolution models with a model of gene evolution that accounts for duplication and loss (DL) (Vilella et al. 2008;Akerborg et al. 2009;Flicek et al. 2010; Kellis 2010, 2012). Provided the species tree is known, these methods yield significantly better gene trees than other molecular phylogenetic methods. However, because reference species trees themselves generally rely on molecular data, they can be also affected by phylogenetic reconstruction uncertainties and unidentified events of gene duplication and loss. This reveals a circular problem: the reconstruction of a species tree requires identifying events of gene family evolution such as DLs, and both the reconstruction of gene trees and the identification of duplications and losses requires a known species tree. The solution to the conundrum is to explicitly consider this two-way dependence and jointly reconstruct the species phylogeny and the histories of all gene families present in their genomes.The coestimation of gene and species trees requires that several gene families be analyzed simultaneously. This represents a significant departure from existing methods (Vilella et al. 2008;Akerborg et al. 200...

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Section: Discussionmentioning

confidence: 99%

Section: Sensitivity To Incomplete Lineage Sortingmentioning

confidence: 99%

Genome-scale coestimation of species and gene trees

et al. 2012

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“…Those mathematical models, which allow gene trees to vary across genes, are the generalization to the concatenation model by relaxing the assumption that all genes have the same history. A variety of mathematical models have been developed along this line (Liu et al, 2008;Kubatko, 2009;Bloomquist & Suchard, 2010;Rasmussen & Kellis, 2012), among which the multispecies coalescent model (Rannala & Yang, 2003) has become most popular for phylogenomic data analysis. In this paper, we describe the multispecies coalescent model, and summarize the statistical and computational properties of the coalescent-based methods for estimating species trees.…”

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confidence: 99%

Coalescent methods for estimating species trees from phylogenomic data

Liu

2015

J of Sytematics Evolution

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Genome-scale sequence data have become increasingly available in the phylogenetic studies for understanding the evolutionary histories of species. However, it is challenging to develop probabilistic models to account for heterogeneity of phylogenomic data. The multispecies coalescent model describes gene trees as independent random variables generated from a coalescence process occurring along the lineages of the species tree. Since the multispecies coalescent model allows gene trees to vary across genes, coalescent-based methods have been popularly used to account for heterogeneous gene trees in phylogenomic data analysis. In this paper, we summarize and evaluate the performance of coalescent-based methods for estimating species trees from genomescale sequence data. We investigate the effects of deep coalescence and mutation on the performance of species tree estimation methods. We found that the coalescent-based methods perform well in estimating species trees for a large number of genes, regardless of the degree of deep coalescence and mutation. The performance of the coalescent methods is negatively correlated with the lengths of internal branches of the species tree.

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“…In particular, if a distribution on estimated gene trees is obtained, say { p i }, then this distribution can be used in equations (1) and (2), and the relative efficiency of different numbering schemes can be compared on different distributions of estimated trees. Similarly, effects of other processes, such as horizontal gene transfer, 24 gene duplication, 25,26 and hybridization 27,28 can be studied as long as distributions of gene tree topologies can be obtained (either theoretically or estimated through simulations).…”

Section: Discussionmentioning

confidence: 99%

Evaluating Variations on the Star Algorithm for Relative Efficiency and Sample Sizes Needed to Reconstruct Species Trees

Degnan

2012

Biocomputing 2013

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Many methods for inferring species trees from gene trees have been developed when incongruence among gene trees is due to incomplete lineage sorting. A method called STAR , assigns values to nodes in gene trees based only on topological information and uses the average value of the most recent common ancestor node for each pair of taxa to construct a distance matrix which is then used for clustering taxa into a tree. This method is very efficient computationally, scaling linearly in the number of loci and quadratically in the number of taxa, and in simulations has shown to be highly accurate for moderate to large numbers of loci as well as robust to molecular clock violations and misestimation of gene trees from sequence data. The method is based on a particular choice of numbering nodes in the gene trees; however, other choices for numbering nodes in gene trees can also lead to consistent inference of the species tree. Here, expected values and variances for average pairwise distances and differences between average pairwise distances in the distance matrix constructed by the STAR algorithm are used to analytically evaluate efficiency of different numbering schemes that are variations on the original STAR numbering for small trees.

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Unified modeling of gene duplication, loss, and coalescence using a locus tree

Cited by 165 publications

References 61 publications

Genome-scale coestimation of species and gene trees

Genome-scale coestimation of species and gene trees

Coalescent methods for estimating species trees from phylogenomic data

Evaluating Variations on the Star Algorithm for Relative Efficiency and Sample Sizes Needed to Reconstruct Species Trees

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