A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood

Abstract

The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximum-likelihood principle, which clearly satisfies these requirements. The core of this method is a simple hill-climbing algorithm that adjusts tree topology and branch lengths simultaneously. This algorithm starts from an initial tree built by a fast distance-based method and modifies this tree to improve its likelihood at each iteration. Due to this simultaneous adjustment of the topology and branch lengths, only a few iterations are sufficient to reach an optimum. We used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance of distance-based and parsimony approaches. The reduction of computing time is dramatic in comparison with other maximum-likelihood packages, while the likelihood maximization ability tends to be higher. For example, only 12 min were required on a standard personal computer to analyze a data set consisting of 500 rbcL sequences with 1,428 base pairs from plant plastids, thus reaching a speed of the same order as some popular distance-based and parsimony algorithms. This new method is implemented in the PHYML program, which is freely available on our web page:

Updating the evolutionary history of Carnivora (Mammalia): a new species-level supertree complete with divergence time estimates

“…The applicability of a molecular clock was tested using a likelihood ratio test with a nominal P of 0.05 corrected for multiple comparisons using a sequential Holm-Bonferroni correction [124]. Thereafter, the sequence data were fitted to the topology of the main supertree under the optimal evolutionary model (see Additional file 6; and [125,126]) using PAUP* and the Perl script seqFitter.pl v1.0. Gene trees for those data sets for which the molecular clock hypothesis could not be rejected were regarded as being rooted; all other gene trees were unrooted.…”

Insight into the population structure of hardhead silverside,Atherinomorus stipes(Teleostei: Atherinidae), in Belize and the Florida Keys usingnd2

“…The model of best fit of sequence evolution for all haplotypes was GTR + I based on AIC and BIC indices (jModelTest v2.1.4; Guindon & Gascuel, 2003; Darriba, Taboada, Doallo, & Posada, 2012). This model was used to produce maximum‐likelihood (ML) and Bayesian phylogenetic trees.…”

Comparative population structure of two dominant species, Shinkaia crosnieri (Munidopsidae: Shinkaia) and Bathymodiolus platifrons (Mytilidae: Bathymodiolus), inhabiting both deep‐sea vent and cold seep inferred from mitochondrial multi‐genes

“…Genetic diversity is reflected in the measures of nucleotide diversity ( π ) and haplotype diversity ( h ) (Nei 1987), and the values for each population were calculated using DnaSP 5.10 (Librado and Rozas 2009). The maximum likelihoods (ML) for phylogenetic analyses were assembled in PhyML 3.0 (Guindon and Gascuel 2003) with 1000 replicates, and the most appropriate model of DNA substitution, which is TIM2+I+G for S. crosnieri and HKY+I for B. platifrons , was identified by ModelTest 3.7 (Posada and Crandall 1998). Alvinocaris longirostris (GenBank: AB821296) and Geothelphusa dehaani (GenBank: AB187570) were set as outgroups for S. crosnieri .…”