How and Why Overcome the Impediments to Resolution: Lessons from rhinolophid and hipposiderid Bats

Foley, Nicole M.; Thong, Vu Dinh; Soisook, Pipat; Goodman, Steven M.; Armstrong, Kyle N.; Jacobs, David S.; Puechmaille, Sébastien J.; Teeling, Emma C.

Single gene fragments were then re-aligned using the T-Coffee web server. The analysis was carried out with default parameters using a comparison of the Mafft, Clustal W, Muscle, and T-Coffee algorithms (Notredame et al. 2000) , and any ambiguous regions of the single gene alignments identified by the programs color coded system as bad or average were removed to optimize the alignment. An appropriate model of sequence evolution was chosen for each gene fragment using jModeltest (Posada 2008) as selected by the AIC (see supplementary table S1, Supplementary Material online, for selected models). Preliminary gene trees for each gene fragment were generated in Beast v.1.7.2 . The Markov chain Monte Carlo (MCMC) chain was run for 10 million generations sampling every 1,000 generations. Tracer v1.5 ) was used to check for convergence. Effective sample sizes values were all more than 200 for all parameters, suggesting the MCMC run was sufficient to obtain valid estimates of the parameters . The resulting trees were collated using TreeAnnotator v1.7.2 with 10% discarded as burn-in to obtain a single representative tree for each gene fragment.