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An In Silico Comparison of Protocols for Dated Phylogenomics

In the age of genome-scale DNA sequencing, choice of molecular marker arguably remains an important decision in planning a phylogenetic study. Using published genomes from 23 primate species, we make a standardized comparison of four of the most frequently used protocols in phylogenomics, , targeted... Full description

Journal Title: Systematic biology 2018-07-01, Vol.67 (4), p.633-650
Main Author: Collins, Rupert A
Other Authors: Hrbek, Tomas
Format: Electronic Article Electronic Article
Language: English
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Publisher: England: Oxford University Press
ID: ISSN: 1063-5157
Link: https://www.ncbi.nlm.nih.gov/pubmed/29319797
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recordid: cdi_proquest_miscellaneous_1989564865
title: An In Silico Comparison of Protocols for Dated Phylogenomics
format: Article
creator:
  • Collins, Rupert A
  • Hrbek, Tomas
subjects:
  • REGULAR ARTICLES
ispartof: Systematic biology, 2018-07-01, Vol.67 (4), p.633-650
description: In the age of genome-scale DNA sequencing, choice of molecular marker arguably remains an important decision in planning a phylogenetic study. Using published genomes from 23 primate species, we make a standardized comparison of four of the most frequently used protocols in phylogenomics, , targeted sequence-enrichment using ultraconserved element and exon-capture probes, and restriction-site-associated DNA sequencing (RADseq and ddRADseq). Here, we present a procedure to perform extractions from genomes and create directly comparable data sets for each class of marker. We then compare these data sets in terms of both phylogenetic resolution and ability to consistently and precisely estimate clade ages using fossil-calibrated molecular-clock models. Furthermore, we were also able to directly compare these results to previously published data sets from Sanger-sequenced nuclear exons and mitochondrial genomes under the same analytical conditions. Our results show—although with the exception of the mitochondrial genome data set and the smallest ddRADseq data set—that for uncontroversial nodes all data classes performed equally well, that is they recovered the same well supported topology. However, for one difficult-to-resolve node comprising a rapid diversification, we report well supported but conflicting topologies among the marker classes consistent with the mismodeling of gene tree heterogeneity as demonstrated by species tree analyses of single nucleotide polymorphisms. Likewise, clade age estimates showed consistent discrepancies between data sets under strict and relaxed clock models; for recent nodes, clade ages estimated by nuclear exon data sets were younger than those of the UCE, RADseq and mitochondrial data, but for the deepest nodes in the primate phylogeny. This observation is explained by temporal differences in phylogenetic informativeness (PI), with the data sets with strong PI peaks toward the present underestimating the deepest node ages. Finally, we conclude by emphasizing that while huge numbers of loci are probably not required for uncontroversial phylogenetic questions—for which practical considerations such as ease of data generation, sharing, and aggregating, therefore become increasingly important—accurately modeling heterogeneous data remains as relevant as ever for the more recalcitrant problems.
language: eng
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identifier: ISSN: 1063-5157
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  • 1063-5157
  • 1076-836X
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descriptionIn the age of genome-scale DNA sequencing, choice of molecular marker arguably remains an important decision in planning a phylogenetic study. Using published genomes from 23 primate species, we make a standardized comparison of four of the most frequently used protocols in phylogenomics, , targeted sequence-enrichment using ultraconserved element and exon-capture probes, and restriction-site-associated DNA sequencing (RADseq and ddRADseq). Here, we present a procedure to perform extractions from genomes and create directly comparable data sets for each class of marker. We then compare these data sets in terms of both phylogenetic resolution and ability to consistently and precisely estimate clade ages using fossil-calibrated molecular-clock models. Furthermore, we were also able to directly compare these results to previously published data sets from Sanger-sequenced nuclear exons and mitochondrial genomes under the same analytical conditions. Our results show—although with the exception of the mitochondrial genome data set and the smallest ddRADseq data set—that for uncontroversial nodes all data classes performed equally well, that is they recovered the same well supported topology. However, for one difficult-to-resolve node comprising a rapid diversification, we report well supported but conflicting topologies among the marker classes consistent with the mismodeling of gene tree heterogeneity as demonstrated by species tree analyses of single nucleotide polymorphisms. Likewise, clade age estimates showed consistent discrepancies between data sets under strict and relaxed clock models; for recent nodes, clade ages estimated by nuclear exon data sets were younger than those of the UCE, RADseq and mitochondrial data, but for the deepest nodes in the primate phylogeny. This observation is explained by temporal differences in phylogenetic informativeness (PI), with the data sets with strong PI peaks toward the present underestimating the deepest node ages. Finally, we conclude by emphasizing that while huge numbers of loci are probably not required for uncontroversial phylogenetic questions—for which practical considerations such as ease of data generation, sharing, and aggregating, therefore become increasingly important—accurately modeling heterogeneous data remains as relevant as ever for the more recalcitrant problems.
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2The Author(s) 2018. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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abstractIn the age of genome-scale DNA sequencing, choice of molecular marker arguably remains an important decision in planning a phylogenetic study. Using published genomes from 23 primate species, we make a standardized comparison of four of the most frequently used protocols in phylogenomics, , targeted sequence-enrichment using ultraconserved element and exon-capture probes, and restriction-site-associated DNA sequencing (RADseq and ddRADseq). Here, we present a procedure to perform extractions from genomes and create directly comparable data sets for each class of marker. We then compare these data sets in terms of both phylogenetic resolution and ability to consistently and precisely estimate clade ages using fossil-calibrated molecular-clock models. Furthermore, we were also able to directly compare these results to previously published data sets from Sanger-sequenced nuclear exons and mitochondrial genomes under the same analytical conditions. Our results show—although with the exception of the mitochondrial genome data set and the smallest ddRADseq data set—that for uncontroversial nodes all data classes performed equally well, that is they recovered the same well supported topology. However, for one difficult-to-resolve node comprising a rapid diversification, we report well supported but conflicting topologies among the marker classes consistent with the mismodeling of gene tree heterogeneity as demonstrated by species tree analyses of single nucleotide polymorphisms. Likewise, clade age estimates showed consistent discrepancies between data sets under strict and relaxed clock models; for recent nodes, clade ages estimated by nuclear exon data sets were younger than those of the UCE, RADseq and mitochondrial data, but for the deepest nodes in the primate phylogeny. This observation is explained by temporal differences in phylogenetic informativeness (PI), with the data sets with strong PI peaks toward the present underestimating the deepest node ages. Finally, we conclude by emphasizing that while huge numbers of loci are probably not required for uncontroversial phylogenetic questions—for which practical considerations such as ease of data generation, sharing, and aggregating, therefore become increasingly important—accurately modeling heterogeneous data remains as relevant as ever for the more recalcitrant problems.
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