Measuring branch support in species trees obtained by gene tree parsimony

Species delimitation and evolutionary reconstruction within an integrative taxonomic framework: A case study on Rhinolophus macrotis complex (Chiroptera: Rhinolophidae)

Species delimitation and evolutionary reconstruction remain challenging for non-model species that have experienced reticulate evolution and exhibit conflicting patterns of differentiation among multiple lines of evidence, such as mitochondrial and nuclear data and phenotypes. Here, we applied an integrative taxonomic approach to a case study of Rhinolophus macrotis complex, whose taxonomic status remains controversial, to provide insight into the systematics and evolutionary history of these species. By integrating traditional genetic markers with different modes of inheritance, genome-wide SNPs as well as phenotypic characteristics, we clarified the presence of three closely related species, R. episcopus, R. siamensis, and R. osgoodi, within this complex, and proposed a new taxonomic treatment for R. osgoodi. Our results suggested that hybridization and introgression are the main causes of low mtDNA divergence in these species. Combined with the demographic inference, we deduced that glacial-interglacial cycles drove geographic isolation and secondary contacts of these species, then promoted hybridization and lineage fusion among them, finally resulting in a reticulate evolutionary pattern. Overall, our study highlights the importance of combining multiple types of data to delimit species, especially those with conserved morphology, and to reveal the sophisticated processes of speciation.

Efficient error correction algorithms for gene tree reconciliation based on duplication, duplication and loss, and deep coalescence

Background

Gene tree - species tree reconciliation problems infer the patterns and processes of gene evolution within a species tree. Gene tree parsimony approaches seek the evolutionary scenario that implies the fewest gene duplications, duplications and losses, or deep coalescence (incomplete lineage sorting) events needed to reconcile a gene tree and a species tree. While a gene tree parsimony approach can be informative about genome evolution and phylogenetics, error in gene trees can profoundly bias the results.

Results

We introduce efficient algorithms that rapidly search local Subtree Prune and Regraft (SPR) or Tree Bisection and Reconnection (TBR) neighborhoods of a given gene tree to identify a topology that implies the fewest duplications, duplication and losses, or deep coalescence events. These algorithms improve on the current solutions by a factor of n for searching SPR neighborhoods and n² for searching TBR neighborhoods, where n is the number of taxa in the given gene tree. They provide a fast error correction protocol for ameliorating the effects of gene tree error by allowing small rearrangements in the topology to improve the reconciliation cost. We also demonstrate a simple protocol to use the gene rearrangement algorithm to improve gene tree parsimony phylogenetic analyses.

Conclusions

The new gene tree rearrangement algorithms provide a fast method to address gene tree error. They do not make assumptions about the underlying processes of genome evolution, and they are amenable to analyses of large-scale genomic data sets. These algorithms are also easily incorporated into gene tree parsimony phylogenetic analyses, potentially producing more credible estimates of reconciliation cost.

Turning the crown upside down: gene tree parsimony roots the eukaryotic tree of life

The first analyses of gene sequence data indicated that the eukaryotic tree of life consisted of a long stem of microbial groups "topped" by a crown-containing plants, animals, and fungi and their microbial relatives. Although more recent multigene concatenated analyses have refined the relationships among the many branches of eukaryotes, the root of the eukaryotic tree of life has remained elusive. Inferring the root of extant eukaryotes is challenging because of the age of the group (∼1.7-2.1 billion years old), tremendous heterogeneity in rates of evolution among lineages, and lack of obvious outgroups for many genes. Here, we reconstruct a rooted phylogeny of extant eukaryotes based on minimizing the number of duplications and losses among a collection of gene trees. This approach does not require outgroup sequences or assumptions of orthology among sequences. We also explore the impact of taxon and gene sampling and assess support for alternative hypotheses for the root. Using 20 gene trees from 84 diverse eukaryotic lineages, this approach recovers robust eukaryotic clades and reveals evidence for a eukaryotic root that lies between the Opisthokonta (animals, fungi and their microbial relatives) and all remaining eukaryotes.

JML: testing hybridization from species trees

I introduce the software JML that tests for the presence of hybridization in multispecies sequence data sets by posterior predictive checking following Joly, McLenachan and Lockhart (2009, American Naturalist 174, e54). Although their method could potentially be applied on any data set, the lack of appropriate software made its application difficult. The software JML thus fills a need for an easy application of the method but also includes improvements such as the possibility to incorporate uncertainty in the species tree topology. The JML software uses a posterior distribution of species trees, population sizes and branch lengths to simulate replicate sequence data sets using the coalescent with no migration. A test quantity, defined as the minimum pairwise sequence distance between sequences of two species, is then evaluated on the simulated data sets and compared to the one estimated from the original data. Because the test quantity is a good predictor of hybridization events, departure from the bifurcating species tree model could be interpreted as evidence of hybridization. Software performance in terms of computing time is evaluated for several parameters. I also show an application example of the software for detecting hybridization among native diploid North American roses.

Survey of branch support methods demonstrates accuracy, power, and robustness of fast likelihood-based approximation schemes

Phylogenetic inference and evaluating support for inferred relationships is at the core of many studies testing evolutionary hypotheses. Despite the popularity of nonparametric bootstrap frequencies and Bayesian posterior probabilities, the interpretation of these measures of tree branch support remains a source of discussion. Furthermore, both methods are computationally expensive and become prohibitive for large data sets. Recent fast approximate likelihood-based measures of branch supports (approximate likelihood ratio test [aLRT] and Shimodaira–Hasegawa [SH]-aLRT) provide a compelling alternative to these slower conventional methods, offering not only speed advantages but also excellent levels of accuracy and power. Here we propose an additional method: a Bayesian-like transformation of aLRT (aBayes). Considering both probabilistic and frequentist frameworks, we compare the performance of the three fast likelihood-based methods with the standard bootstrap (SBS), the Bayesian approach, and the recently introduced rapid bootstrap. Our simulations and real data analyses show that with moderate model violations, all tests are sufficiently accurate, but aLRT and aBayes offer the highest statistical power and are very fast. With severe model violations aLRT, aBayes and Bayesian posteriors can produce elevated false-positive rates. With data sets for which such violation can be detected, we recommend using SH-aLRT, the nonparametric version of aLRT based on a procedure similar to the Shimodaira–Hasegawa tree selection. In general, the SBS seems to be excessively conservative and is much slower than our approximate likelihood-based methods.