Disentangling sources of gene tree discordance in phylogenomic datasets: testing ancient hybridizations in Amaranthaceae s.l.
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https://datadryad.org/dataset/doi:10.5061/dryad.ns1rn8pq4
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Gene tree discordance in large genomic datasets can be caused by
evolutionary processes such as incomplete lineage sorting and
hybridization, as well as model violation, and errors in data processing,
orthology inference, and gene tree estimation. Species tree methods that
identify and accommodate all sources of conflict are not available, but a
combination of multiple approaches can help tease apart alternative
sources of conflict. Here, using a phylotranscriptomic analysis in
combination with reference genomes, we test a hypothesis of ancient
hybridization events within the plant family Amaranthaceae s.l. that was
previously supported by morphological, ecological, and Sanger-based
molecular data. The dataset included seven genomes and 88 transcriptomes,
17 generated for this study. We examined gene-tree discordance using
coalescent-based species trees and network inference, gene tree
discordance analyses, site pattern tests of introgression, topology tests,
synteny analyses, and simulations. We found that a combination of
processes might have generated the high levels of gene tree discordance in
the backbone of Amaranthaceae s.l. Furthermore, we found evidence that
three consecutive short internal branches produce anomalous trees
contributing to the discordance. Overall, our results suggest that
Amaranthaceae s.l. might be a product of an ancient and rapid lineage
diversification, and remains, and probably will remain, unresolved. This
work highlights the potential problems of identifiability associated with
the sources of gene tree discordance including, in particular,
phylogenetic network methods. Our results also demonstrate the importance
of thoroughly testing for multiple sources of conflict in phylogenomic
analyses, especially in the context of ancient, rapid radiations. We
provide several recommendations for exploring conflicting signals in such
situations.
提供机构:
Dryad
创建时间:
2020-08-16



