Verbruggen, H., Maggs, C., Saunders, G.W., Le Gall, L., Yoon, H.S. and De Clerck, O., 2010. Data mining approach identifies research priorities and data requirements for resolving the red algal tree of life. BMC Evolutionary Biology, 10, 16 - ?.
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Abstract
BACKGROUND: The assembly of the tree of life has seen significant progress in recent years but algae and protists have been largely overlooked in this effort. Many groups of algae and protists have ancient roots and it is unclear how much data will be required to resolve their phylogenetic relationships for incorporation in the tree of life. The red algae, a group of primary photosynthetic eukaryotes of more than a billion years old, provide the earliest fossil evidence for eukaryotic multicellularity and sexual reproduction. Despite this evolutionary significance, their phylogenetic relationships are understudied. This study aims to infer a comprehensive red algal tree of life at the family level from a supermatrix containing data mined from GenBank. We aim to locate remaining regions of low support in the topology, evaluate their causes and estimate the amount of data required to resolve them. RESULTS: Phylogenetic analysis of a supermatrix of 14 loci and 98 red algal families yielded the most complete red algal tree of life to date. Visualization of statistical support showed the presence of five poorly supported regions. Causes for low support were identified with statistics about the age of the region, data availability and node density, showing that poor support has different origins in different parts of the tree. Parametric simulation experiments yielded optimistic estimates of how much data will be needed to resolve the poorly supported regions (ca. 103 to ca. 104 nucleotides for the different regions). Nonparametric simulations gave a markedly more pessimistic image, some regions requiring more than 2.8 105 nucleotides or not achieving the desired level of support at all. The discrepancies between parametric and nonparametric simulations are discussed in light of our dataset and known attributes of both approaches. CONCLUSIONS: Our study takes the red algae one step closer to meaningful inclusion in the tree of life. In addition to the recovery of stable relationships, the recognition of five regions in need of further study is a significant outcome of this work. Based on our analyses of current availability and future requirements of data, we make clear recommendations for forthcoming research.
Item Type: | Article |
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ISSN: | 1471-2148 |
Uncontrolled Keywords: | Bayes Theorem ; DNA, Algal ; Data Mining ; Evolution, Molecular ; Likelihood Functions ; Models, Genetic ; Phylogeny ; Rhodophyta ; Sequence Alignment ; Sequence Analysis, DNA |
Group: | Faculty of Science & Technology |
ID Code: | 24478 |
Deposited By: | Symplectic RT2 |
Deposited On: | 08 Aug 2016 15:01 |
Last Modified: | 14 Mar 2022 13:57 |
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