Investigating Difficult Nodes in the Placental Mammal Tree with Expanded Taxon Sampling and Thousands of Ultraconserved Elements

Esselstyn, Jacob A.; Oliveros, Carl H.; Swanson, Mark T.; Faircloth, Brant C.

doi:10.1093/gbe/evx168

Cited by 112 publications

(133 citation statements)

References 89 publications

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“…10. The development of partitioned support measures for distance-based coalescence methods (STAR, STEAC, NJ-ST, ASTRID: Liu et al, 2009b, Liu andYu, 2011;Vachaspati and Warnow, 2015) should be a priority to make sense of conflicting relationships favored by different phylogenomic coalescence methods (e.g., Esselstyn et al, 2017;Liu et al, 2017). Figure 1.…”

Section: Discussionmentioning

confidence: 99%

Partitioned coalescence support reveals biases in species-tree methods and detects gene trees that determine phylogenomic conflicts

Gatesy

Sloan

Warren

et al. 2018

Preprint

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Genomic datasets sometimes support unconventional or conflicting phylogenetic relationships when different tree-building methods are applied. Coherent interpretations of such results are enabled by partitioning support for controversial relationships among the constituent genes of a phylogenomic dataset. For the supermatrix (= concatenation) approach, several simple methods that measure the distribution of support and conflict among loci were introduced over 15 years ago. More recently, partitioned coalescence support (PCS) was developed for phylogenetic coalescence methods that account for incomplete lineage sorting and use the summed fits of gene trees to estimate the species tree. Here, we automate computation of PCS to permit application of this index to genome-scale matrices that include hundreds of loci. Reanalyses of four phylogenomic datasets for amniotes, land plants, skinks, and angiosperms demonstrate how PCS scores can be used to: 1) compare conflicting results favored by alternative coalescence methods, 2) identify outlier gene trees that have a disproportionate influence on the resolution of contentious relationships, 3) assess the effects of missing data in species-trees analysis, and 4) clarify biases in commonly-implemented coalescence methods and support indices. We show that key phylogenomic conclusions from these analyses often hinge on just a few gene trees and that results can be driven by specific biases of a particular coalescence method and/or the extreme weight placed on gene trees with high taxon sampling. Attributing exceptionally high weight to some gene trees and very low weight to other gene trees counters the basic logic of phylogenomic coalescence analysis; even clades in species trees with high support according to commonly used indices (likelihood-ratio test, bootstrap, Bayesian local posterior probability) can be unstable to the removal of only one or two gene trees with high PCS. Computer simulations cannot adequately describe all of the contingencies and complexities of empirical genetic data. PCS scores complement simulation work by providing specific insights into a particular dataset given the assumptions of the phylogenetic coalescence method that is applied. In combination with standard measures of nodal support, PCS provides a more complete understanding of the overall genomic evidence for contested evolutionary relationships in species trees.

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Section: Discussionmentioning

confidence: 99%

Partitioned coalescence support reveals biases in species-tree methods and detects gene trees that determine phylogenomic conflicts

Gatesy

Sloan

Warren

et al. 2018

Preprint

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“…For birds and mammals, aligned reads were not available, so we 148 downloaded raw reads and followed the procedures taken by the previous authors to 149 create our aligned matrices. In the case of the mammal dataset (Esselstyn et al 2017), 150…”

Section: Genomic Characterization Of Uces Across the Tree Of Life 107mentioning

confidence: 99%

Genomic characterization and curation of UCEs improves species tree reconstruction

Dam

Henderson

Esposito

et al. 2019

Preprint

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19Ultraconserved genomic elements (UCEs), are generally treated as independent 20 loci in phylogenetic analyses. The identification pipeline for UCE probes is agnostic to 21 genetic identity, only selecting loci that are highly conserved, single copy, without 22 repeats, and of a particular length. Here we characterized UCEs from 12 phylogenomic 23 studies across the animal tree of life, from birds to marine invertebrates. We found that 24 within vertebrate lineages, UCEs are mostly intronic and intergenic, while in 25 invertebrates, the majority are in exons. We then curated 4 different sets of UCE 26 markers by genomic category from 5 different studies including; birds, mammals, fish, 27Hymenoptera (ants, wasps and bees) and Coleoptera (beetles). Of genes captured by 28UCEs, we find that many are represented by 2 or more UCEs, corresponding to non-29 overlapping segments of a single gene. We considered these UCEs to be non-30 independent, merged all UCEs that belonged to a particular gene, constructed gene and 31 species trees, and then evaluated the subsequent effect of merging co-genic UCEs on 32 gene and species tree reconstruction. Average bootstrap support for merged UCE gene 33 trees were significantly improved across all datasets. Increased loci length appears to 34 drive this increase in bootstrap support. Additionally, we found that gene trees 35 generated from merged UCEs were more accurate than those generated by unmerged 36 and randomly merged UCEs, based on our simulation study. This modest degree of 37 UCE characterization and curation impacts downstream analyses and demonstrates the 38 advantages of incorporating basic genomic characterizations into phylogenomic 39 analyses. 40 41 3

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“…The first UCEs were identified by Bejerano et al (2004) in the human genome and have been shown to be conserved in mammals, birds, and even ray-finned fish. Thanks to their large-scale sequence conservation, UCEs are particularly well-suited for sequence capture experiments and have become popular for phylogenomic reconstruction of diverse animals groups (Guschanski et al 2013;Blaimer et al 2015;Esselstyn, Oliveros, Swanson, & Faircloth 2017). Initially restricted to a few vertebrate groups such as mammals ) and birds (McCormack et al 2013a), new UCE probe sets have been designed to target thousands of loci in arthropods such as hymenopterans (Blaimer et al 2015;Branstetter et al 2017a;Faircloth, Branstetter, White, & Brady 2015), coleopterans (Baca, Alexander, Gustafson, & Short 2017), and arachnids (Starrett et al 2017).…”

Section: Introductionmentioning

confidence: 99%

MitoFinder: efficient automated large-scale extraction of mitogenomic data in target enrichment phylogenomics

Allio

Schomaker-Bastos

Romiguier

et al. 2019

Preprint

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AbstractThanks to the development of high-throughput sequencing technologies, target enrichment sequencing of nuclear ultraconserved DNA elements (UCEs) now allows routinely inferring phylogenetic relationships from thousands of genomic markers. Recently, it has been shown that mitochondrial DNA (mtDNA) is frequently sequenced alongside the targeted loci in such capture experiments. Despite its broad evolutionary interest, mtDNA is rarely assembled and used in conjunction with nuclear markers in capture-based studies. Here, we developed MitoFinder, a user-friendly bioinformatic pipeline, to efficiently assemble and annotate mitogenomic data from hundreds of UCE libraries. As a case study, we used ants (Formicidae) for which 501 UCE libraries have been sequenced whereas only 29 mitogenomes are available. We compared the efficiency of four different assemblers (IDBA-UD, MEGAHIT, MetaSPAdes, and Trinity) for assembling both UCE and mtDNA loci. Using MitoFinder, we show that metagenomic assemblers, in particular MetaSPAdes, are well suited to assemble both UCEs and mtDNA. Mitogenomic signal was successfully extracted from all 501 UCE libraries allowing confirming species identification using COI barcoding. Moreover, our automated procedure retrieved 296 cases in which the mitochondrial genome was assembled in a single contig, thus increasing the number of available ant mitogenomes by an order of magnitude. By leveraging the power of metagenomic assemblers, MitoFinder provides an efficient tool to extract complementary mitogenomic data from UCE libraries, allowing testing for potential mito-nuclear discordance. Our approach is potentially applicable to other sequence capture methods, transcriptomic data, and whole genome shotgun sequencing in diverse taxa.

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Investigating Difficult Nodes in the Placental Mammal Tree with Expanded Taxon Sampling and Thousands of Ultraconserved Elements

Cited by 112 publications

References 89 publications

Partitioned coalescence support reveals biases in species-tree methods and detects gene trees that determine phylogenomic conflicts

Partitioned coalescence support reveals biases in species-tree methods and detects gene trees that determine phylogenomic conflicts

Genomic characterization and curation of UCEs improves species tree reconstruction

MitoFinder: efficient automated large-scale extraction of mitogenomic data in target enrichment phylogenomics

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