Dataset Information

Weighted Statistical Binning: Enabling Statistically Consistent Genome-Scale Phylogenetic Analyses.

ABSTRACT: Because biological processes can result in different loci having different evolutionary histories, species tree estimation requires multiple loci from across multiple genomes. While many processes can result in discord between gene trees and species trees, incomplete lineage sorting (ILS), modeled by the multi-species coalescent, is considered to be a dominant cause for gene tree heterogeneity. Coalescent-based methods have been developed to estimate species trees, many of which operate by combining estimated gene trees, and so are called "summary methods". Because summary methods are generally fast (and much faster than more complicated coalescent-based methods that co-estimate gene trees and species trees), they have become very popular techniques for estimating species trees from multiple loci. However, recent studies have established that summary methods can have reduced accuracy in the presence of gene tree estimation error, and also that many biological datasets have substantial gene tree estimation error, so that summary methods may not be highly accurate in biologically realistic conditions. Mirarab et al. (Science 2014) presented the "statistical binning" technique to improve gene tree estimation in multi-locus analyses, and showed that it improved the accuracy of MP-EST, one of the most popular coalescent-based summary methods. Statistical binning, which uses a simple heuristic to evaluate "combinability" and then uses the larger sets of genes to re-calculate gene trees, has good empirical performance, but using statistical binning within a phylogenomic pipeline does not have the desirable property of being statistically consistent. We show that weighting the re-calculated gene trees by the bin sizes makes statistical binning statistically consistent under the multispecies coalescent, and maintains the good empirical performance. Thus, "weighted statistical binning" enables highly accurate genome-scale species tree estimation, and is also statistically consistent under the multi-species coalescent model. New data used in this study are available at DOI: http://dx.doi.org/10.6084/m9.figshare.1411146, and the software is available at https://github.com/smirarab/binning.

SUBMITTER: Bayzid MS

PROVIDER: S-EPMC4472720 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Weighted Statistical Binning: Enabling Statistically Consistent Genome-Scale Phylogenetic Analyses.

Bayzid Md Shamsuzzoha MS Mirarab Siavash S Boussau Bastien B Warnow Tandy T

PloS one 20150618 6

Because biological processes can result in different loci having different evolutionary histories, species tree estimation requires multiple loci from across multiple genomes. While many processes can result in discord between gene trees and species trees, incomplete lineage sorting (ILS), modeled by the multi-species coalescent, is considered to be a dominant cause for gene tree heterogeneity. Coalescent-based methods have been developed to estimate species trees, many of which operate by combi ...[more]

PMID: 26086579

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Project description:Type I and type-II functional divergences have been stated to highlight specific residues carrying out differential functions in evolutionary-divergent protein clusters from a single common ancestor. Briefly, type I analysis is based on residue constraints reflecting a gain of function just in one cluster of an entire family of proteins; while the type-II approach is based on residue constraints showing a different chemical nature in every cluster of a protein family. This last evidence is understood as differential functionality among clusters. The Receptor Activity-Modifying Proteins constitute a family characterized by its paralogous distribution in vertebrates. They are known as G-Protein Coupled Receptor modulators. Although several studies have determined their involvement in ligand binding, specificity, and enhancement of signal transduction, the responsible residues supporting those functions are unclear. Using different bioinformatic approaches, we predicted residues involved in different RAMP functional tasks. Many residues localized in an extracellular coil of RAMP proteins were predicted to be under functional divergence suggesting a gain of function in their respective proteins. Interestingly, the transmembrane region also showed important results for residues playing relevant roles where most of them showed a biased distribution on the structure. A relevant role was conferred by the enrichment of type-II residues observed in their sequences. We show a collection of residues explaining possible gain of function and differential functionality in RAMP proteins. These residues are still experimentally unexplored with regards to functionality. Finally, an evolutionary history could be discerned. Mainly, the RAMP2 cluster has evolved in a higher manner than other RAMP clusters. However, a deacceleration in the aminoacid substitution rate of RAMP2 was observed in mammals. Such effect could be caused by the co-evolution of ligands and receptors interacting with RAMP2 through evolution and/or the specialization of this cluster in GPCR modulation.

Dataset Information

Weighted Statistical Binning: Enabling Statistically Consistent Genome-Scale Phylogenetic Analyses.

Publications

Weighted Statistical Binning: Enabling Statistically Consistent Genome-Scale Phylogenetic Analyses.

Similar Datasets

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