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Phylotranscriptomic consolidation of the jawed vertebrate timetree

Authors :
Irisarri, Iker
Baurain, Denis
Brinkmann, Henner
Delsuc, Frédéric
Sire, Jean-Yves
Kupfer, Alexander
Petersen, Jörn
Jarek, Michael
Meyer, Axel
Vences, Miguel
Philippe, Hervé
Irisarri, Iker
Baurain, Denis
Brinkmann, Henner
Delsuc, Frédéric
Sire, Jean-Yves
Kupfer, Alexander
Petersen, Jörn
Jarek, Michael
Meyer, Axel
Vences, Miguel
Philippe, Hervé
Publication Year :
2017

Abstract

Phylogenomics is extremely powerful but introduces new challenges as no agreement exists on ‘standards’ for data selection, curation and tree inference. We use jawed vertebrates (Gnathostomata) as a model to address these issues. Despite considerable efforts in resolving their evolutionary history and macroevolution, few studies have included a full phylogenetic diversity of gnathostomes, and some relationships remain controversial. We tested a new bioinformatic pipeline to assemble large and accu- rate phylogenomic datasets from RNA sequencing and found this phylotranscriptomic approach to be successful and highly cost- effective. Increased sequencing effort up to about 10 Gbp allows more genes to be recovered, but shallower sequencing (1.5 Gbp) is sufficient to obtain thousands of full-length orthologous transcripts. We reconstruct a robust and strongly supported timetree of jawed vertebrates using 7,189 nuclear genes from 100 taxa, including 23 new transcriptomes from previously unsampled key species. Gene jackknifing of genomic data corroborates the robustness of our tree and allows calculating genome-wide divergence times by overcoming gene sampling bias. Mitochondrial genomes prove insufficient to resolve the deepest relationships because of limited signal and among-lineage rate heterogeneity. Our analyses emphasize the importance of large, curated, nuclear datasets to increase the accuracy of phylogenomics and provide a reference framework for the evolutionary history of jawed vertebrates.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1235173096
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.1038.s41559-017-0240-5