Contradictory phylogenetic signals in the laurasiatheria anomaly zone
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Relationships among laurasiatherian clades represent one of the most highly disputed topics in mammalian phylogeny. In this study, we attempt to disentangle laurasiatherian interordinal relationships using two independent genome-level approaches: (1) quantifying retrotransposon presence/absence patterns, and (2) comparisons of exon datasets at the levels of nucleotides and amino acids. The two approaches revealed contradictory phylogenetic signals, possibly due to a high level of ancestral incomplete lineage sorting. The positions of Eulipotyphla and Chiroptera as the first and second earliest divergences were consistent across the approaches. However, the phylogenetic relationships of Perissodactyla, Cetartiodactyla, and Ferae, were contradictory. While retrotransposon insertion analyses suggest a clade with Cetartiodactyla and Ferae, the exon dataset favoured Cetartiodactyla and Perissodactyla. Future analyses of hitherto unsampled laurasiatherian lineages and synergistic analyses of retrotransposon insertions, exon and conserved intron/intergenic sequences might unravel the conflicting patterns of relationships in this major mammalian clade.
Doronina , L , Hughes , G M , Moreno-Santillan , D , Lawless , C , Lonergan , T , Ryan , L , Jebb , D , Kirilenko , B M , Korstian , J M , Dávalos , L M , Vernes , S C , Myers , E W , Teeling , E C , Hiller , M , Jermiin , L S , Schmitz , J , Springer , M S & Ray , D A 2022 , ' Contradictory phylogenetic signals in the laurasiatheria anomaly zone ' , Genes , vol. 13 , no. 5 , 766 . https://doi.org/10.3390/genes13050766
Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/4.0/).
DescriptionG.M.H. was funded by a UCD Ad Astra Fellowship. C.L. was funded by a UCD Ad Astra studentship. L.R. was funded by an SFI Centre for Research Training in Genomics Data Science grant (18/CRT/6214). L.M.D. was supported in part by NSF awards 1838273 and 2032063. E.C.T. and T.L. were funded by an SFI Frontiers for the Future Programme grant (19/FFP/6790).
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