To better determine the history of modern birds, we performed a genome-scale phylogenetic analysis of 48 species representing all orders of Neoaves using phylogenomic methods created to handle genome-scale data. We recovered a highly resolved tree that confirms previously controversial sister or close relationships. We identified the first divergence in Neoaves, two groups we named Passerea and Columbea, representing independent lineages of diverse and convergently evolved land and water bird species. Among Passerea, we infer the common ancestor of core landbirds to have been an apex predator and confirm independent gains of vocal learning. Among Columbea, we identify pigeons and flamingoes as belonging to sister clades. Even with whole genomes, some of the earliest branches in Neoaves proved challenging to resolve, which was best explained by massive protein-coding sequence convergence and high levels of incomplete lineage sorting that occurred during a rapid radiation after the Cretaceous-Paleogene mass extinction event about 66 million years ago.

Species tree estimation is complicated by processes, such as gene duplication and loss and incomplete lineage sorting (ILS), that cause discordance between gene trees and the species tree. Furthermore, while concatenation, a traditional approach to tree estimation, has excellent performance under many conditions, the expectation is that the best accuracy will be obtained through the use of species tree estimation methods that are specifically designed to address gene tree discordance. In this article, we report on a study to evaluate MP-EST-one of the most popular species tree estimation methods designed to address ILS-as well as concatenation under maximum likelihood, the greedy consensus, and two supertree methods (Matrix Representation with Parsimony and Matrix Representation with Likelihood). Our study shows that several factors impact the absolute and relative accuracy of methods, including the number of gene trees, the accuracy of the estimated gene trees, and the amount of ILS. Concatenation can be more accurate than the best summary methods in some cases (mostly when the gene trees have poor phylogenetic signal or when the level of ILS is low), but summary methods are generally more accurate than concatenation when there are an adequate number of sufficiently accurate gene trees. Our study suggests that coalescent-based species tree methods may be key to estimating highly accurate species trees from multiple loci.

Supplementary data are available at Bioinformatics online.

Because biological processes can result in different loci having different evolutionary histories, species tree estimation requires multiple loci from across multiple genomes. While many processes can result in discord between gene trees and species trees, incomplete lineage sorting (ILS), modeled by the multi-species coalescent, is considered to be a dominant cause for gene tree heterogeneity. Coalescent-based methods have been developed to estimate species trees, many of which operate by combining estimated gene trees, and so are called "summary methods". Because summary methods are generally fast (and much faster than more complicated coalescent-based methods that co-estimate gene trees and species trees), they have become very popular techniques for estimating species trees from multiple loci. However, recent studies have established that summary methods can have reduced accuracy in the presence of gene tree estimation error, and also that many biological datasets have substantial gene tree estimation error, so that summary methods may not be highly accurate in biologically realistic conditions. Mirarab et al. (Science 2014) presented the "statistical binning" technique to improve gene tree estimation in multi-locus analyses, and showed that it improved the accuracy of MP-EST, one of the most popular coalescent-based summary methods. Statistical binning, which uses a simple heuristic to evaluate "combinability" and then uses the larger sets of genes to re-calculate gene trees, has good empirical performance, but using statistical binning within a phylogenomic pipeline does not have the desirable property of being statistically consistent. We show that weighting the re-calculated gene trees by the bin sizes makes statistical binning statistically consistent under the multispecies coalescent, and maintains the good empirical performance. Thus, "weighted statistical binning" enables highly accurate genome-scale species tree estimation, and is also statistically consistent under the multi-species coalescent model. New data used in this study are available at DOI: http://dx.doi.org/10.6084/m9.figshare.1411146, and the software is available at https://github.com/smirarab/binning.