Loading...
Thumbnail Image
Publication

Phylotranscriptomic consolidation of the jawed vertebrate timetree.

Irisarri, Iker
Baurain, Denis
Brinkmann, Henner
Delsuc, Frédéric
Sire, Jean-Yves
Kupfer, Alexander
Petersen, Jörn
Jarek, Michael
Meyer, Axel
Vences, Miguel
... show 1 more
Citations
Altmetric:
Advisors
Editors
Other Contributors
Issue Date
2017-09-01
Submitted date
Other Titles
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 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 novel bioinformatic pipeline to assemble large and accurate phylogenomic datasets from RNA sequencing and find this phylotranscriptomic approach successful and highly cost-effective. Increased sequencing effort up to ca. 10Gbp allows recovering more genes, but shallower sequencing (1.5Gbp) 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.
Citation
Publisher
Journal
PubMed ID
PubMed Central ID
Embedded video
Type
Article
Language
Description
Series/Report no.
ISSN
2397-334X
EISSN
ISBN
ISMN
Gov't Doc #
Sponsors
License
Attribution-NonCommercial-ShareAlike 3.0 United States