Biology subjects

Simmons, M. P.

Publications and source records attributed to Simmons, M. P..

3 recordsLinked to original sources

bioRxiv2022

Iterative deletion of gene trees detects extreme biases in distance-based phylogenomic coalescent analyses

Summary coalescent methods offer an alternative to the concatenation (supermatrix) approach for inferring phylogenetic relationships from genome-scale datasets. Given huge datasets, broad congruence between contrasting phylogenomic paradigms is often obtained, but empirical studies commonly show some well supported conflicts between concatenation and coalescence results and also between species trees estimated from alternative coalescent methods. Partitioned support indices can help arbitrate these discrepancies by pinpointing outlier loci that are unjustifiably influential at conflicting nodes. Partitioned coalescence support (PCS) recently was developed for summary coalescent methods, such as ASTRAL and MP-EST, that use the summed fits of individual gene trees to estimate the species tree. However, PCS cannot be implemented when distance-based coalescent methods (e.g., STAR, NJst, ASTRID, STEAC) are applied. Here, this deficiency is addressed by automating computation of partitioned coalescent branch length (PCBL), a novel index that uses iterative removal of individual gene trees to assess the impact of each gene on every clade in a distance-based coalescent tree. Reanalyses of five phylogenomic datasets show that PCBL for STAR and NJst trees helps quantify the overall stability/instability of clades and clarifies disagreements with results from optimality-based coalescent analyses. PCBL scores reveal severe missing taxa, apical nesting, misrooting, and basal dragdown biases. Contrived examples demonstrate the gross overweighting of outlier gene trees that drives these biases. Because of interrelated biases revealed by PCBL scores, caution should be exercised when using STAR and NJst, in particular when many taxa are analyzed, missing data are non-randomly distributed, and widespread gene-tree reconstruction error is suspected. Similar biases in the optimality-based coalescent method MP-EST indicate that congruence among species trees estimated via STAR, NJst, and MP-EST should not be interpreted as independent corroboration for phylogenetic relationships. Such agreements among methods instead might be due to the common defects of all three summary coalescent methods.

evolutionary biology↗

bioRxiv2018

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

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.

evolutionary biology↗

bioRxiv2016

Anchored Phylogenomics of Angiosperms I: Assessing the Robustness of Phylogenetic Estimates

An important goal of the angiosperm systematics community has been to develop a shared approach to molecular data collection, such that phylogenomic data sets from different focal clades can be combined for meta-studies across the entire group. Although significant progress has been made through efforts such as DNA barcoding, transcriptome sequencing, and whole-plastid sequencing, the community current lacks a cost efficient methodology for collecting nuclear phylogenomic data across all angiosperms. Here, we leverage genomic resources from 43 angiosperm species to develop enrichment probes useful for collecting ~500 loci from non-model taxa across the diversity of angiosperms. By taking an anchored phylogenomics approach, in which probes are designed to represent sequence diversity across the group, we are able to efficiently target loci with sufficient phylogenetic signal to resolve deep, intermediate, and shallow angiosperm relationships. After demonstrating the utility of this resource, we present a method that generates a heat map for each node on a phylogeny that reveals the sensitivity of support for the node across analysis conditions, as well as different locus, site, and taxon schemes. Focusing on the effect of locus and site sampling, we use this approach to statistically evaluate relative support for the alternative relationships among eudicots, monocots, and magnoliids. Although the results from supermatrix and coalescent analyses are largely consistent across the tree, we find support for this deep relationship to be more sensitive to the particular choice of sites and loci when a supermatrix approach as employed. Averaged across analysis approaches and data subsampling schemes, our data support a eudicot-monocot sister relationship, which is supported by a number of recent angiosperm studies.

evolutionary biology↗