Summary: MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types—e.g. morphological, nucleotide, and protein— and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.

/pdf/mrbayes-3-bayesian-phylogenetic-inference-under-mixed-models-4z1bzdo26e.pdf

MrBayes 3: Bayesian phylogenetic inference under mixed models

PAML, currently in version 4, is a package of programs for phylogenetic analyses of DNA and protein sequences using maximum likelihood (ML). The programs may be used to compare and test phylogenetic trees, but their main strengths lie in the rich repertoire of evolutionary models implemented, which can be used to estimate parameters in models of sequence evolution and to test interesting biological hypotheses. Uses of the programs include estimation of synonymous and nonsynonymous rates (d(N) and d(S)) between two protein-coding DNA sequences, inference of positive Darwinian selection through phylogenetic comparison of protein-coding genes, reconstruction of ancestral genes and proteins for molecular restoration studies of extinct life forms, combined analysis of heterogeneous data sets from multiple gene loci, and estimation of species divergence times incorporating uncertainties in fossil calibrations. This note discusses some of the major applications of the package, which includes example data sets to demonstrate their use. The package is written in ANSI C, and runs under Windows, Mac OSX, and UNIX systems. It is available at -- (http://abacus.gene.ucl.ac.uk/software/paml.html).

/pdf/paml-4-phylogenetic-analysis-by-maximum-likelihood-2gg19rsgos.pdf

PAML 4: Phylogenetic Analysis by Maximum Likelihood

Mesquite: a modular system for evolutionary analysis. Version 2.6

The ongoing revolution in high-throughput sequencing continues to democratize the ability of small groups of investigators to map the microbial component of the biosphere. In particular, the coevolution of new sequencing platforms and new software tools allows data acquisition and analysis on an unprecedented scale. Here we report the next stage in this coevolutionary arms race, using the Illumina GAIIx platform to sequence a diverse array of 25 environmental samples and three known “mock communities” at a depth averaging 3.1 million reads per sample. We demonstrate excellent consistency in taxonomic recovery and recapture diversity patterns that were previously reported on the basis of metaanalysis of many studies from the literature (notably, the saline/nonsaline split in environmental samples and the split between host-associated and free-living communities). We also demonstrate that 2,000 Illumina single-end reads are sufficient to recapture the same relationships among samples that we observe with the full dataset. The results thus open up the possibility of conducting large-scale studies analyzing thousands of samples simultaneously to survey microbial communities at an unprecedented spatial and temporal resolution.

/pdf/global-patterns-of-16s-rrna-diversity-at-a-depth-of-millions-5tcvnbw5d6.pdf

Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample

Summary
1. Here, I present a new, multifunctional phylogenetics package, phytools, for the R statistical computing environment.

2. The focus of the package is on methods for phylogenetic comparative biology; however, it also includes tools for tree inference, phylogeny input/output, plotting, manipulation and several other tasks.

3. I describe and tabulate the major methods implemented in phytools, and in addition provide some demonstration of its use in the form of two illustrative examples.

4. Finally, I conclude by briefly describing an active web-log that I use to document present and future developments for phytools. I also note other web resources for phylogenetics in the R computational environment.

/pdf/phytools-an-r-package-for-phylogenetic-comparative-biology-yli0omoidd.pdf

phytools: an R package for phylogenetic comparative biology (and other things)

As a discipline, phylogenetics is becoming transformed by a flood of molecular data. These data allow broad questions to be asked about the history of life, but also present difficult statistical and computational problems. Bayesian inference of phylogeny brings a new perspective to a number of outstanding issues in evolutionary biology, including the analysis of large phylogenetic trees and complex evolutionary models and the detection of the footprint of natural selection in DNA sequences.

https://science.sciencemag.org/content/sci/294/5550/2310.full.pdf

Bayesian inference of phylogeny and its impact on evolutionary biology

Character mapping on phylogenies has played an important, if not critical role, in our understanding of molecular, morphological, and behavioral evolution. Until very recently we have relied on parsimony to infer character changes. Parsimony has a number of serious limitations that are drawbacks to our understanding. Recent statistical methods have been developed that free us from these limitations enabling us to overcome the problems of parsimony by accommodating uncertainty in evolutionary time, ancestral states, and the phylogeny. SIMMAP has been developed to implement stochastic character mapping that is useful to both molecular evolutionists, systematists, and bioinformaticians. Researchers can address questions about positive selection, patterns of amino acid substitution, character association, and patterns of morphological evolution. Stochastic character mapping, as implemented in the SIMMAP software, enables users to address questions that require mapping characters onto phylogenies using a probabilistic approach that does not rely on parsimony. Analyses can be performed using a fully Bayesian approach that is not reliant on considering a single topology, set of substitution model parameters, or reconstruction of ancestral states. Uncertainty in these quantities is accommodated by using MCMC samples from their respective posterior distributions.

/pdf/simmap-stochastic-character-mapping-of-discrete-traits-on-556tu33rgt.pdf

SIMMAP: Stochastic character mapping of discrete traits on phylogenies

Many questions in evolutionary biology are best addressed by comparing traits in different species Often such studies involve mapping characters on phylogenetic trees Mapping characters on trees allows the nature, number, and timing of the transformations to be identified The parsimony method is the only method available for mapping morphological characters on phylogenies Although the parsimony method often makes reasonable reconstructions of the history of a character, it has a number of limitations These limitations include the inability to consider more than a single change along a branch on a tree and the uncoupling of evolutionary time from amount of character change We extended a method described by Nielsen (2002, Syst Biol 51:729-739) to the mapping of morphological characters under continuous-time Markov models and demonstrate here the utility of the method for mapping characters on trees and for identifying character correlation (Bayesian estimation; character correlation; character mapping; Markov chain Monte Carlo) The footprint of natural selection on organisms can of- ten be detected using phylogenetic methods Correlation in either molecular or morphological characters is taken as evidence of natural selection acting on those charac- ters (Harvey and Pagel, 1991) The correlation might be between a character and the environment, with the re- peated evolution of the character in a particular environ- ment indicating that the trait confers an advantage, or the correlation may be between one character and another In ribosomal RNA sequences, for example, correlated changes occur in nucleotides paired in the stem struc- tures; natural selection is acting to maintain Watson- Crick pairing of nucleotides in the functionally impor- tant stem structures In either case-correlation between different characters or the repeated evolution of a charac- ter in a particular environment-phylogenetic methods provide the best framework for the analysis of correlation because they allow the effects of a common phylogenetic history that simultaneously acts on all of the characters to be partitioned from the evolutionary processes gener- ating the character patterns (Felsenstein, 1985) Despite the importance of phylogenetic analysis of character change in evolutionary biology, detection of correlation in characters is fraught with difficulties One dilemma involves how characters should be mapped onto a phylogenetic tree Many methods for detecting correlations rely on mapping character changes on a phylogenetic tree using the parsimony method (Ridley, 1983; Maddison, 1990) The parsimony method provides the minimum number of transformations required to explain the evolution of the character on the tree and therefore necessarily underestimates the total number of changes Furthermore, some methods treat the par- simony mapping of a character as an observation in fur- ther statistical analyses (Ridley, 1983; Maddison, 1990) Although the parsimony method is expected to provide a reasonable mapping of a character when the rates of evolution are low, the fundamental problem with the method is that it does not account for the uncertainty in the process of character change In effect, the parsimony method wagers all on the mapping requiring the fewest changes, when in reality many other perhaps slightly less parsimonious mappings may be nearly as good or

https://www.jstor.org/stable/info/3651122

Stochastic mapping of morphological characters.

Author(s): Binladen, Jonas; Gilbert, M Thomas P; Bollback, Jonathan P; Panitz, Frank; Bendixen, Christian; Nielsen, Rasmus; Willerslev, Eske | Abstract: BackgroundThe invention of the Genome Sequence 20 DNA Sequencing System (454 parallel sequencing platform) has enabled the rapid and high-volume production of sequence data. Until now, however, individual emulsion PCR (emPCR) reactions and subsequent sequencing runs have been unable to combine template DNA from multiple individuals, as homologous sequences cannot be subsequently assigned to their original sources.MethodologyWe use conventional PCR with 5'-nucleotide tagged primers to generate homologous DNA amplification products from multiple specimens, followed by sequencing through the high-throughput Genome Sequence 20 DNA Sequencing System (GS20, Roche/454 Life Sciences). Each DNA sequence is subsequently traced back to its individual source through 5'tag-analysis.ConclusionsWe demonstrate that this new approach enables the assignment of virtually all the generated DNA sequences to the correct source once sequencing anomalies are accounted for (miss-assignment ratel0.4%). Therefore, the method enables accurate sequencing and assignment of homologous DNA sequences from multiple sources in single high-throughput GS20 run. We observe a bias in the distribution of the differently tagged primers that is dependent on the 5' nucleotide of the tag. In particular, primers 5' labelled with a cytosine are heavily overrepresented among the final sequences, while those 5' labelled with a thymine are strongly underrepresented. A weaker bias also exists with regards to the distribution of the sequences as sorted by the second nucleotide of the dinucleotide tags. As the results are based on a single GS20 run, the general applicability of the approach requires confirmation. However, our experiments demonstrate that 5'primer tagging is a useful method in which the sequencing power of the GS20 can be applied to PCR-based assays of multiple homologous PCR products. The new approach will be of value to a broad range of research areas, such as those of comparative genomics, complete mitochondrial analyses, population genetics, and phylogenetics.

/pdf/the-use-of-coded-pcr-primers-enables-high-throughput-37k45uqa0w.pdf

The use of coded PCR primers enables high-throughput sequencing of multiple homolog amplification products by 454 parallel sequencing.

Several methods have been proposed to infer the states at the ancestral nodes on a phy- logeny. These methods assume a speciec tree and set of branch lengths when estimating the ancestral character state. Inferences of the ancestral states, then, are conditioned on the tree and branch lengths being true. We develop a hierarchical Bayes method for inferring the ancestral states on a tree. The method integrates over uncertainty in the tree, branch lengths, and substitution modelparameters by usingMarkovchainMonteCarlo.WecomparethehierarchicalBayesinferencesofancestralstateswith inferencesof ancestralstates made under theassumption that aspeciectreeiscorrect. We end that the methods arecorrelated,butthataccommodating uncertainty inparametersof thephylogenetic model can make inferences of ancestral states even more uncertain than they would be in an empiricalBayes analysis. (Ancestral state reconstruction; Bayesian estimation; empirical Bayes; hierarchical Bayes.) The reconstruction of ancestral states on a phylogeny remains an important endeavor in evolutionary biology. The comparative method, for example, looks for evidence of correlated change in two or more characters; in the course of such analyses, the ances- tral states are often reconstructed on a tree (Harvey and Pagel, 1991). Other studies ex- amine the properties of ancient molecules (Malcolm et al., 1990; Stackhouse et al., 1990; Adey et al., 1994; Jermann et al., 1995). The amino acidsequence ofthe ancient protein is estimatedandthensynthesizedinthelabora- tory.Thepropertiesoftheancientproteincan then be measured in vivo or in vitro with the goal of demonstrating a change in the func- tion ofthe protein. Similar studies have been performed for morphological or behavioral traits.Forexample, Ryanand Rand(1995) re- constructed the mating calls ofthe hypothet- ical ancestors of a group of frogs and then examined the response of the extant females to the ancient calls. The inferences made in such studies depend on the reliability of the ancestral state reconstructions. Several methods have been proposed to reconstruct the states present in the hypo- theticalancestors on a phylogenetic tree. The parsimony method, probably the most fre- quentlyusedmethodtoinferancestralstates, ends the combination of ancestral states at an interior node of a phylogeny that mini- mizes the number ofchanges over the whole tree.Theresultofaparsimonyanalysisofan-

Jonathan P. Bollback

Papers

Bayesian inference of phylogeny and its impact on evolutionary biology

SIMMAP: Stochastic character mapping of discrete traits on phylogenies

Stochastic mapping of morphological characters.

The use of coded PCR primers enables high-throughput sequencing of multiple homolog amplification products by 454 parallel sequencing.

Empirical and hierarchical Bayesian estimation of ancestral states.