Extracting Phylogenetic Signal from Phylogenomic Data: Higher-Level Relationships of the Nightbirds (Strisores).

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ID: 43868
2019
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Abstract
A well-resolved phylogeny would facilitate study of adaptation to nocturnality in the avian superorder Strisores, a group that includes both nocturnal and diurnal lineages. Based on previous estimates, it could be hypothesized that there were multiple independent origins of nocturnality in this group. In order to refine the Strisores phylogeny, we generated genome-scale datasets of 2,289 - 4,243 ultra-conserved elements for 23 taxa representing all major living lineages in the group. Among the considerations for using genome-scale, molecular sequence data in phylogenomic analysis are issues related to GC content, GC variance and their effects on model selection. In this study, we employed a variety of analytical techniques to empirically investigate those issues in our data, as well as biases and errors resulting from alignment trimming, taxon selection, matrix completeness and evolutionary rate variation among sites and across lineages. Extensive analyses revealed conflict within the data, especially in regard to variation in GC content, that would not have been detected with more cursory study. Our results indicate that readily available models of molecular evolution are insufficient to encapsulate all phenomena present in genome-scale matrices, and that this problem may be at the root of many current issues in phylogenomic analysis. The analytical methods employed in this study are relevant to phylogenomic analysis of any large, heterogeneous matrix. In conclusion, we present a strongly supported estimate of the Strisores tree, and discuss visual adaptations for and potential evolutionary pathways to nocturnality in this clade.
Reference Key
white2019extractingmolecular Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors White, Noor D;Braun, Michael J;
Journal Molecular phylogenetics and evolution
Year 2019
DOI
S1055-7903(19)30351-3
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