Robert Lanfear

PartitionFinder: Combined Selection of Partitioning Schemes and Substitution Models for Phylogenetic Analyses

In phylogenetic analyses of molecular sequence data, partitioning involves estimating independent models of molecular evolution for different sets of sites in a sequence alignment. Choosing an appropriate partitioning scheme is an important step in most analyses because it can affect the accuracy of phylogenetic reconstruction. Despite this, partitioning schemes are often chosen without explicit statistical justification. Here, we describe two new objective methods for the combined selection of best-fit partitioning schemes and nucleotide substitution models. These methods allow millions of partitioning schemes to be compared in realistic time frames and so permit the objective selection of partitioning schemes even for large multilocus DNA data sets. We demonstrate that these methods significantly outperform previous approaches, including both the ad hoc selection of partitioning schemes (e.g., partitioning by gene or codon position) and a recently proposed hierarchical clustering method. We have implemented these methods in an open-source program, PartitionFinder. This program allows users to select partitioning schemes and substitution models using a range of information-theoretic metrics (e.g., the Bayesian information criterion, akaike information criterion [AIC], and corrected AIC). We hope that PartitionFinder will encourage the objective selection of partitioning schemes and thus lead to improvements in phylogenetic analyses. PartitionFinder is written in Python and runs under Mac OSX 10.4 and above. The program, source code, and a detailed manual are freely available from www.robertlanfear.com/partitionfinder.

PartitionFinder 2: New Methods for Selecting Partitioned Models of Evolution for Molecular and Morphological Phylogenetic Analyses

PartitionFinder 2 is a program for automatically selecting best-fit partitioning schemes and models of evolution for phylogenetic analyses. PartitionFinder 2 is substantially faster and more efficient than version 1, and incorporates many new methods and features. These include the ability to analyze morphological datasets, new methods to analyze genome-scale datasets, new output formats to facilitate interoperability with downstream software, and many new models of molecular evolution. PartitionFinder 2 is freely available under an open source license and works on Windows, OSX, and Linux operating systems. It can be downloaded from www.robertlanfear.com/partitionfinder. The source code is available at https://github.com/brettc/partitionfinder.

Selecting optimal partitioning schemes for phylogenomic datasets

BackgroundPartitioning involves estimating independent models of molecular evolution for different subsets of sites in a sequence alignment, and has been shown to improve phylogenetic inference. Current methods for estimating best-fit partitioning schemes, however, are only computationally feasible with datasets of fewer than 100 loci. This is a problem because datasets with thousands of loci are increasingly common in phylogenetics.MethodsWe develop two novel methods for estimating best-fit partitioning schemes on large phylogenomic datasets: strict and relaxed hierarchical clustering. These methods use information from the underlying data to cluster together similar subsets of sites in an alignment, and build on clustering approaches that have been proposed elsewhere.ResultsWe compare the performance of our methods to each other, and to existing methods for selecting partitioning schemes. We demonstrate that while strict hierarchical clustering has the best computational efficiency on very large datasets, relaxed hierarchical clustering provides scalable efficiency and returns dramatically better partitioning schemes as assessed by common criteria such as AICc and BIC scores.ConclusionsThese two methods provide the best current approaches to inferring partitioning schemes for very large datasets. We provide free open-source implementations of the methods in the PartitionFinder software. We hope that the use of these methods will help to improve the inferences made from large phylogenomic datasets.

The Extent and Consequences of P-Hacking in Science

A focus on novel, confirmatory, and statistically significant results leads to substantial bias in the scientific literature. One type of bias, known as “p-hacking,” occurs when researchers collect or select data or statistical analyses until nonsignificant results become significant. Here, we use text-mining to demonstrate that p-hacking is widespread throughout science. We then illustrate how one can test for p-hacking when performing a meta-analysis and show that, while p-hacking is probably common, its effect seems to be weak relative to the real effect sizes being measured. This result suggests that p-hacking probably does not drastically alter scientific consensuses drawn from meta-analyses.

Population size and the rate of evolution

Does evolution proceed faster in larger or smaller populations? The relationship between effective population size (Ne) and the rate of evolution has consequences for our ability to understand and interpret genomic variation, and is central to many aspects of evolution and ecology. Many factors affect the relationship between Ne and the rate of evolution, and recent theoretical and empirical studies have shown some surprising and sometimes counterintuitive results. Some mechanisms tend to make the relationship positive, others negative, and they can act simultaneously. The relationship also depends on whether one is interested in the rate of neutral, adaptive, or deleterious evolution. Here, we synthesize theoretical and empirical approaches to understanding the relationship and highlight areas that remain poorly understood.

Watching the clock: Studying variation in rates of molecular evolution between species

Evidence is accumulating that rates of molecular evolution vary substantially between species, and that this rate variation is partly determined by species characteristics. A better understanding of how and why rates of molecular evolution vary provides a window on evolutionary processes, and might facilitate improvements in DNA sequence analysis. Measuring rates of molecular evolution and identifying the correlates of rate variation present a unique set of challenges. We describe and compare recent methodological advances that have been proposed to deal with these challenges. We provide a guide to the theoretical basis and practical application of the methods, outline the types of data on which they can be used, and indicate the types of questions they can be used to ask.

Ancestral Notch-mediated segmentation revealed in the cockroach Periplaneta americana

Through division into segments, animal bodies can reach higher degrees of complexity and functionality during development and evolution. The segmentation mechanisms of insects and vertebrates have been seen as fundamentally different at the anatomical and molecular levels, and consequently, independently evolved. However, this conclusion was mostly based on observations of derived insects such as Drosophila. We have cloned the Delta, Notch, and hairy genes in the cockroach Periplaneta americana, a basal insect with short germ-band development, and carried out functional assays of Notch activity during its segmentation. Our results show that, in more basal insects, segmentation involves a similar developmental mechanism to that in vertebrates, including induction of segment formation by cyclic segmental stripes of hairy and Delta expression. This result indicates that Notch-mediated segmentation is the ancestral segmentation mechanism of insects, and together with previous results in the literature [Stollewerk A, Schoppmeier M, Damen WGM (2003) Nature 423:863–865], of arthropods as well. The similarity with vertebrate segmentation might suggest that Notch-mediated segmentation is an ancient developmental mechanism inherited from a common ancestor of insects and vertebrates.

A generation time effect on the rate of molecular evolution in invertebrates

The rate of genome evolution varies significantly between species. Evidence is growing that at least some of this variation is associated with species characteristics, such as body size, diversification rate, or population size. One of the strongest correlates of the rate of molecular evolution in vertebrates is generation time (GT): Species with faster generation turnover tend to have higher rates of molecular evolution, presumably because their genomes are copied more frequently and therefore collect more DNA replication errors per unit time. But the GT effect has never been tested for nonvertebrate animals. Here, we present the first general test of the GT effect in invertebrates, using 15 genes from 143 species spread across the major eumetazoan superphyla (including arthropods, nematodes, molluscs, annelids, platyhelminthes, cnidarians, echinoderms, and urochordates). We find significant evidence that rates of molecular evolution are correlated with GT in invertebrates and that this effect applies consistently across genes and taxonomic groups. Furthermore, the GT effect is evident in nonsynonymous substitutions, whereas theory predicts (and most previous evidence has supported) a relationship only in synonymous changes. We discuss both the practical and theoretical implications of these findings.

Mutation rate is linked to diversification in birds

How does genome evolution affect the rate of diversification of biological lineages? Recent studies have suggested that the overall rate of genome evolution is correlated with the rate of diversification. If true, this claim has important consequences for understanding the process of diversification, and implications for the use of DNA sequence data to reconstruct evolutionary history. However, the generality and cause of this relationship have not been established. Here, we test the relationship between the rate of molecular evolution and net diversification with a 19-gene, 17-kb DNA sequence dataset from 64 families of birds. We show that rates of molecular evolution are positively correlated to net diversification in birds. Using a 7.6-kb dataset of protein-coding DNA, we show that the synonymous substitution rate, and therefore the mutation rate, is correlated to net diversification. Further analysis shows that the link between mutation rates and net diversification is unlikely to be the indirect result of correlations with life-history variables that may influence both quantities, suggesting that there might be a causal link between mutation rates and net diversification.

Metabolic rate does not calibrate the molecular clock

Rates of molecular evolution vary widely among lineages, but the causes of this variation remain poorly understood. It has been suggested that mass-specific metabolic rate may be one of the key factors determining the rate of molecular evolution, and that it can be used to derive “corrected” molecular clocks. However, previous studies have been hampered by a paucity of mass-specific metabolic rate data and have been largely limited to vertebrate taxa. Using mass-specific metabolic rate measurements and DNA sequence data for >300 metazoan species for 12 different genes, we find no evidence that mass-specific metabolic rate drives substitution rates. The mechanistic basis of the metabolic rate hypothesis is discussed in light of these findings.