Response to Comment on “Statistical binning enables an accurate coalescent-based estimation of the avian tree”

Mirarab, Siavash; Bayzid, Md. Shamsuzzoha; Boussau, Bastien; Warnow, Tandy

doi:10.1126/science.aaa7719

Cited by 6 publications

(3 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To address this, others have recommended restricting analyses of whole genome data to the most informative regions or combining regions with similar underlying topologies (e.g., Jarvis et al. 2015; Mirarab et al. 2015).…”

Section: Discussionmentioning

confidence: 99%

Phylogenomic Insights into Mouse Evolution Using a Pseudoreference Approach

Sarver

Keeble

Cosart

et al. 2017

Genome Biology and Evolution

View full text Add to dashboard Cite

Comparative genomic studies are now possible across a broad range of evolutionary timescales, but the generation and analysis of genomic data across many different species still present a number of challenges. The most sophisticated genotyping and down-stream analytical frameworks are still predominantly based on comparisons to high-quality reference genomes. However, established genomic resources are often limited within a given group of species, necessitating comparisons to divergent reference genomes that could restrict or bias comparisons across a phylogenetic sample. Here, we develop a scalable pseudoreference approach to iteratively incorporate sample-specific variation into a genome reference and reduce the effects of systematic mapping bias in downstream analyses. To characterize this framework, we used targeted capture to sequence whole exomes (∼54 Mbp) in 12 lineages (ten species) of mice spanning the Mus radiation. We generated whole exome pseudoreferences for all species and show that this iterative reference-based approach improved basic genomic analyses that depend on mapping accuracy while preserving the associated annotations of the mouse reference genome. We then use these pseudoreferences to resolve evolutionary relationships among these lineages while accounting for phylogenetic discordance across the genome, contributing an important resource for comparative studies in the mouse system. We also describe patterns of genomic introgression among lineages and compare our results to previous studies. Our general approach can be applied to whole or partitioned genomic data and is easily portable to any system with sufficient genomic resources, providing a useful framework for phylogenomic studies in mice and other taxa.

show abstract

Section: Discussionmentioning

confidence: 99%

Phylogenomic Insights into Mouse Evolution Using a Pseudoreference Approach

Sarver

Keeble

Cosart

et al. 2017

Genome Biology and Evolution

View full text Add to dashboard Cite

show abstract

“…Unlike the concatenation approach, the coalescence approach can efficiently account for differences in the evolutionary history among individual gene trees (Liu et al 2015). However, the coalescence approach can be sensitive to errors and biases in estimating individual gene trees (Mirarab et al 2015; Springer and Gatesy 2016), which in turn may mislead inference of the species phylogeny.…”

Section: Methodsmentioning

confidence: 99%

Reconstructing the Backbone of the Saccharomycotina Yeast Phylogeny Using Genome-Scale Data

Shen

Zhou

Kominek

et al. 2016

G3 Genes|Genomes|Genetics

202

159

View full text Add to dashboard Cite

Understanding the phylogenetic relationships among the yeasts of the subphylum Saccharomycotina is a prerequisite for understanding the evolution of their metabolisms and ecological lifestyles. In the last two decades, the use of rDNA and multilocus data sets has greatly advanced our understanding of the yeast phylogeny, but many deep relationships remain unsupported. In contrast, phylogenomic analyses have involved relatively few taxa and lineages that were often selected with limited considerations for covering the breadth of yeast biodiversity. Here we used genome sequence data from 86 publicly available yeast genomes representing nine of the 11 known major lineages and 10 nonyeast fungal outgroups to generate a 1233-gene, 96-taxon data matrix. Species phylogenies reconstructed using two different methods (concatenation and coalescence) and two data matrices (amino acids or the first two codon positions) yielded identical and highly supported relationships between the nine major lineages. Aside from the lineage comprised by the family Pichiaceae, all other lineages were monophyletic. Most interrelationships among yeast species were robust across the two methods and data matrices. However, eight of the 93 internodes conflicted between analyses or data sets, including the placements of: the clade defined by species that have reassigned the CUG codon to encode serine, instead of leucine; the clade defined by a whole genome duplication; and the species Ascoidea rubescens. These phylogenomic analyses provide a robust roadmap for future comparative work across the yeast subphylum in the disciplines of taxonomy, molecular genetics, evolutionary biology, ecology, and biotechnology. To further this end, we have also provided a BLAST server to query the 86 Saccharomycotina genomes, which can be found at http://y1000plus.org/blast.

show abstract

“…When ML-analysis is attempted on a “false supergene” (i.e., supergene that includes two or more discordant loci), the resulting ML tree cannot be accurate because the loci used to infer it do not share the same tree (i.e., only a single tree is inferred when there should be multiple). Recently, the validity of statistical binning and similar methods has been called into question based on both empirical and theoretical work suggesting that these methods can be unreliable when the input gene trees suffer from high estimation error [[13], [14], [15], [16]].…”

Section: Methods Detailsmentioning

confidence: 99%