PT  - JOURNAL ARTICLE
AU  - Stephen M Crotty
AU  - Bui Quang Minh
AU  - Nigel G Bean
AU  - Barbara R Holland
AU  - Jonathan Tuke
AU  - Lars S Jermiin
AU  - Arndt von Haeseler
TI  - GHOST: Recovering Historical Signal from Heterotachously-evolved Sequence Alignments
AID  - 10.1101/174789
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 174789
4099  - http://biorxiv.org/content/early/2017/08/10/174789.short
4100  - http://biorxiv.org/content/early/2017/08/10/174789.full
AB  - Molecular sequence data that have evolved under the influence of heterotachous evolutionary processes are known to mislead phylogenetic inference. We introduce the General Heterogeneous evolution On a Single Topology (GHOST) model of sequence evolution, implemented under a maximum-likelihood framework in the phylogenetic program IQ-TREE. Extensive simulations show that the GHOST model can accurately recover the tree topology, branch lengths, substitution rate and base frequency parameters from heterotachously-evolved sequences. We apply our model to an electric fish dataset and identify a subtle component of the historical signal, linked to the previously established convergent evolution of the electric organ in two geographically distinct lineages of electric fish. We compare the GHOST model to the partition model and show that, owing to the minimization of model constraints, the GHOST model is able to offer unique biological insights when applied to empirical data.