How to Identify and Interpret Evolutionary Tree Diagrams

Evolutionary trees are key tools for modern biology and are commonly portrayed in textbooks to promote learning about biological evolution. However, many people have difficulty in understanding what evolutionary trees are meant to portray. In fact, some ideas that current professional biologists depict with evolutionary trees are neither clearly defined nor conveyed to students. To help biology teachers and students learn how to more deeply interpret, understand and gain knowledge from diagrams that represent ancestor–descendant relationships and evolutionary lineages, we describe the different rooted and unrooted evolutionary tree visualisations and explain how they are best read. Examples from a study of tree-shaped diagrams in the journal Science are used to illustrate how to distinguish evolutionary trees from other tree-shaped representations that are easily misunderstood as visualising evolutionary relationships. We end by making recommendations for how our findings may be implemented in teaching practice in this important area of biology education.     

Characters Are Key: The Effect of Synapomorphies on Cladogram Comprehension

Cladograms, phylogenetic trees that depict evolutionary relationships among a set of taxa, are one of the most powerful predictive tools in modern biology. They are usually depicted in one of two formats—tree or ladder. Previous research (Novick and Catley 2007) has found that college students have much greater difficulty understanding a cladogram’s hierarchical structure when it is depicted in the ladder format. Such understanding would seem to be a prerequisite for successful tree thinking. The present research examined the effect of a theoretically guided manipulation—adding a synapomorphy on each branch that supports two or more taxa—on students’ understanding of the hierarchical structure of ladder cladograms. Synapomorphies are characters shared by a group of taxa due to inheritance from a common ancestor. Thus, their depiction on a cladogram may facilitate the understanding of evolutionary relationships. Students’ comprehension was assessed in terms of success at translating relationships depicted in the ladder format to the tree format. The results indicated that adding synapomorphies provided powerful conceptual scaffolding that improved comprehension for students with both weaker and stronger backgrounds in biology. For stronger background students, the benefit of adding synapomorphies to the ladders was comparable to that of approximately two hours of instruction in phylogenetics that emphasized the ladder format.     

A valid assessment of students’ skill in determining relationships on evolutionary trees

Background

Evolutionary trees illustrate relationships among taxa. Interpreting these relationships requires developing a set of “tree-thinking” skills that are typically included in introductory college biology courses. One of these skills is determining relationships among taxa using the most recent common ancestor, yet many students instead use one or more alternate strategies to determine relationships. Several alternate strategies have been well documented and these include using superficial similarity, proximity at the tips of a tree, or the fewest intervening nodes in the tree to group taxa.

Results

We administered interviews (n = 16) and pencil-and-paper questionnaires (n = 205), and constructed a valid and reliable assessment that measured how well students determined relationships among taxa on an evolutionary tree. Our questions asked students to consider a focal taxon and identify which of two additional taxa is most closely related to it. We paired the use of most recent common ancestor with one of three alternative strategies (i.e., similarity, proximity, or node-counting) to explicitly test students’ understanding of the relationships among the taxa on each tree.

Conclusions

Our assessment enables us to identify students who are effectively distracted by an alternative strategy, those who use the most recent common ancestor inconsistently, or who are guessing in order to determine relationships among taxa. Our 18-question tool (see Additional file 1) can be used for formative assessment of student understanding of how to interpret relationships on evolutionary trees. Because our assessment tests for the same skill throughout, students who answer incorrectly, even once, likely have an incomplete understanding of how to determine relationships on evolutionary trees and should receive follow-up instruction.

     

On the use of median‐joining networks in evolutionary biology

Median‐joining (MJ) was proposed as a method for phylogeographical analysis and is enjoying increasing popularity. Herein, we evaluate the efficacy of the approach as originally intended. We show that median‐joining networks (MJNs) are theoretically untenable for evolutionary inference, and that confusion has afflicted their use for over 15 years. The approach has two obvious shortcomings: its reliance on distance‐based phenetics (overall similarity instead of character transformations) and the lack of rooting (no direction or history). Given that evolution involves both change and time, and the absence of rooting removes time (ancestor–descendant relationships) from the equation, the approach cannot yield defensible evolutionary interpretations. We also examine the impact of MJ analyses on evolutionary biology via an analysis of citations and conclude that the spread of MJNs through the literature is difficult to explain, especially given the availability of character‐based analyses.     

Othenio Abel (1875–1946) and “the phylogeny of the parts”1

The reconstruction of the evolutionary history of animal phyla was an integral part of Othenio Abel’s paleobiology (paleozoology). Abel took issue with those phylogeneticists who, following the lead of Haeckel, would draw up phylogenetic trees on the basis of transformation series of singular characters considered to be of particular importance. Abel highlighted Louis Dollo’s principle of the chevauchement des spécialisations (crossing of specializations), which transformed phylogenetics from a search for ancestor–descendant sequences to research into relative degrees of relationships. This replacement resolved the conflict, much discussed at the time, between the continuity of ancestor–descendant lineages and the discontinuity inherent in the natural (phylogenetic) system. Walter Zimmermann refined Abel’s methodology, which he called character‐phylogenetics (Merkmalsphylogenie), an approach that was eventually adopted by Willi Hennig.     

Inferring phylogenetic relationships avoiding forbidden rooted triplets

To construct a phylogenetic tree or phylogenetic network for describing the evolutionary history of a set of species is a well-studied problem in computational biology. One previously proposed method to infer a phylogenetic tree/network for a large set of species is by merging a collection of known smaller phylogenetic trees on overlapping sets of species so that no (or as little as possible) branching information is lost. However, little work has been done so far on inferring a phylogenetic tree/network from a specified set of trees when in addition, certain evolutionary relationships among the species are known to be highly unlikely. In this paper, we consider the problem of constructing a phylogenetic tree/network which is consistent with all of the rooted triplets in a given set C and none of the rooted triplets in another given set F. Although NP-hard in the general case, we provide some efficient exact and approximation algorithms for a number of biologically meaningful variants of the problem.     

Anchor-based whole genome phylogeny (ABWGP): a tool for inferring evolutionary relationship among closely related microorganisms [corrected

Phenotypic behavior of a group of organisms can be studied using a range of molecular evolutionary tools that help to determine evolutionary relationships. Traditionally a gene or a set of gene sequences was used for generating phylogenetic trees. Incomplete evolutionary information in few selected genes causes problems in phylogenetic tree construction. Whole genomes are used as remedy. Now, the task is to identify the suitable parameters to extract the hidden information from whole genome sequences that truly represent evolutionary information. In this study we explored a random anchor (a stretch of 100 nucleotides) based approach (ABWGP) for finding distance between any two genomes, and used the distance estimates to compute evolutionary trees. A number of strains and species of Mycobacteria were used for this study. Anchor-derived parameters, such as cumulative normalized score, anchor order and indels were computed in a pair-wise manner, and the scores were used to compute distance/phylogenetic trees. The strength of branching was determined by bootstrap analysis. The terminal branches are clearly discernable using the distance estimates described here. In general, different measures gave similar trees except the trees based on indels. Overall the tree topology reflected the known biology of the organisms. This was also true for different strains of Escherichia coli. A new whole genome-based approach has been described here for studying evolutionary relationships among bacterial strains and species.     

Anchor-Based Whole Genome Phylogeny (ABWGP): A Tool for Inferring Evolutionary Relationship among Closely Related Microorganims

Phenotypic behavior of a group of organisms can be studied using a range of molecular evolutionary tools that help to determine evolutionary relationships. Traditionally a gene or a set of gene sequences was used for generating phylogenetic trees. Incomplete evolutionary information in few selected genes causes problems in phylogenetic tree construction. Whole genomes are used as remedy. Now, the task is to identify the suitable parameters to extract the hidden information from whole genome sequences that truly represent evolutionary information. In this study we explored a random anchor (a stretch of 100 nucleotides) based approach (ABWGP) for finding distance between any two genomes, and used the distance estimates to compute evolutionary trees. A number of strains and species of Mycobacteria were used for this study. Anchor-derived parameters, such as cumulative normalized score, anchor order and indels were computed in a pair-wise manner, and the scores were used to compute distance/phylogenetic trees. The strength of branching was determined by bootstrap analysis. The terminal branches are clearly discernable using the distance estimates described here. In general, different measures gave similar trees except the trees based on indels. Overall the tree topology reflected the known biology of the organisms. This was also true for different strains of Escherichia coli. A new whole genome-based approach has been described here for studying evolutionary relationships among bacterial strains and species.     

Drawing Rooted Phylogenetic Networks

The evolutionary history of a collection of species is usually represented by a phylogenetic tree. Sometimes, phylogenetic networks are used as a means of representing reticulate evolution or of showing uncertainty and incompatibilities in evolutionary datasets. This is often done using unrooted phylogenetic networks such as split networks, due in part, to the availability of software (SplitsTree) for their computation and visualization. In this paper we discuss the problem of drawing rooted phylogenetic networks as cladograms or phylograms in a number of different views that are commonly used for rooted trees. Implementations of the algorithms are available in new releases of the Dendroscope and SplitsTree programs.     

Efficient FPT Algorithms for (Strict) Compatibility of Unrooted Phylogenetic Trees

In phylogenetics, a central problem is to infer the evolutionary relationships between a set of species X; these relationships are often depicted via a phylogenetic tree—a tree having its leaves labeled bijectively by elements of X and without degree-2 nodes—called the “species tree.” One common approach for reconstructing a species tree consists in first constructing several phylogenetic trees from primary data (e.g., DNA sequences originating from some species in X), and then constructing a single phylogenetic tree maximizing the “concordance” with the input trees. The obtained tree is our estimation of the species tree and, when the input trees are defined on overlapping—but not identical—sets of labels, is called “supertree.” In this paper, we focus on two problems that are central when combining phylogenetic trees into a supertree: the compatibility and the strict compatibility problems for unrooted phylogenetic trees. These problems are strongly related, respectively, to the notions of “containing as a minor” and “containing as a topological minor” in the graph community. Both problems are known to be fixed parameter tractable in the number of input trees k, by using their expressibility in monadic second-order logic and a reduction to graphs of bounded treewidth. Motivated by the fact that the dependency on k of these algorithms is prohibitively large, we give the first explicit dynamic programming algorithms for solving these problems, both running in time \(2^{O(k^2)} \cdot n\), where n is the total size of the input.     

Deep Phylogeny��How a Tree Can Help Characterize Early Life on Earth

The Darwinian concept of biological evolution assumes that life on Earth shares a common ancestor. The diversification of this common ancestor through speciation events and vertical transmission of genetic material implies that the classification of life can be illustrated in a tree-like manner, commonly referred to as the Tree of Life. This article describes features of the Tree of Life, such as how the tree has been both pruned and become bushier throughout the past century as our knowledge of biology has expanded. We present current views that the classification of life may be best illustrated as a ring or even a coral with tree-like characteristics. This article also discusses how the organization of the Tree of Life offers clues about ancient life on Earth. In particular, we focus on the environmental conditions and temperature history of Precambrian life and show how chemical, biological, and geological data can converge to better understand this history.

“You know, a tree is a tree.  How many more do you need to look at?”–Ronald Reagan (Governor of California), quoted in the Sacramento Bee, opposing expansion of Redwood National Park, March 3, 1966

The following article addresses a period in life most removed from life’s origins compared with other articles in this collection. The article discusses an advanced form of life that seems to have lived on the order of 3.5–4.0 billion years ago, around the time when life as we know it began to diversify in a Darwinian sense. The life from this geological period is located deep within an illustrated taxonomic tree of life. The hope is that by understanding how early life evolved, we can better understand how life originated. In this sense, the article attempts to travel backwards in time, starting from modern organisms, to understand life’s origin.The Darwinian concept of evolution suggests that all modern life shares a single common ancestor, often referred to as the last universal common ancestor (LUCA). Throughout evolutionary history, this ancestor has for the most part generated descendants as successive bifurcations in a tree-like manner. This so called Tree of Life, and phylogenetics in general provides much of the framework for the field of molecular evolution. Taxonomic trees allow us to better understand relationships and commonalities shared by life. For instance, a tree may tell us whether a trait or phenotype shared between two organisms is the result of shared-common ancestry (termed homologous traits) or whether the trait has evolved multiple times independent of ancestry (analogous traits such as wings).Taxonomic trees can be built using diverse sources of information. These can include morphological and phenotypic data at the macro-level down to DNA and protein sequence data at the micro-level. Ideally, trees built from multiple sources of input have identical taxonomic relationships and branching patterns, and such trees are said to be congruent. In practice, however, trees built from morphological data (say, presence or absence of wings) are often different than a tree built from molecular data (DNA or protein sequences). This requires the biologist to determine which of the two data sets is misleading and/or which taxonomic tree-building algorithm is most appropriate to use for a particular data set. Such an artform is common in the field of molecular evolution because rarely are trees congruent when built from two sources of input data.In light of this fact, we have provided the quote at the beginning of this article as a reflection about the field of molecular evolution and its interpretations of taxonomic trees. Although Reagan was not speaking about taxonomic trees in his quote, the same sort of disconnect exists between evolutionary biologists and molecular biologists (Woese and Goldenfeld 2009), as it did between conservationists and Ronald Reagan. A molecular biologist may be inclined to say that once you have seen one phylogenetic tree, you have seen them all. And in fairness, there is some validity to such a notion because historically a phylogenetic tree could not help a molecular biologist to better describe their system. An evolutionary biologist, however, will argue that individual trees have nuances that can dramatically alter our interpretation of evolutionary processes.We intend to show in this article that not all (taxonomic) trees look similar and describe identical evolutionary scenarios. We will discuss how our concept of the Tree of Life has changed over the past couple of decades, how trees can be interpreted, and what a tree can tell us about early life. In particular, the article will focus on the temperature conditions of early life because this topic has received much attention over the past few years as a direct result of improved DNA sequencing technology and a better understanding of molecular evolutionary processes. We will also describe how trees can be used to guide laboratory experiments in our attempt to understand ancient life. Lastly, we will discuss how phylogenetic trees will serve as the foundation for an “evolutionary synthetic biology” that should allow us to better understand the evolution of cellular pathways, macromolecular machines such as the ribosome, and other emergent properties of early life.     

TREEasy: An automated workflow to infer gene trees,species trees,and phylogenetic networks from multilocus data

Multilocus genomic data sets can be used to infer a rich set of information about the evolutionary history of a lineage, including gene trees, species trees, and phylogenetic networks. However, user‐friendly tools to run such integrated analyses are lacking, and workflows often require tedious reformatting and handling time to shepherd data through a series of individual programs. Here, we present a tool written in Python—TREEasy—that performs automated sequence alignment (with MAFFT), gene tree inference (with IQ‐Tree), species inference from concatenated data (with IQ‐Tree and RaxML‐NG), species tree inference from gene trees (with ASTRAL, MP‐EST, and STELLS2), and phylogenetic network inference (with SNaQ and PhyloNet). The tool only requires FASTA files and nine parameters as inputs. The tool can be run as command line or through a Graphical User Interface (GUI). As examples, we reproduced a recent analysis of staghorn coral evolution, and performed a new analysis on the evolution of the “WGD clade” of yeast. The latter revealed novel patterns that were not identified by previous analyses. TREEasy represents a reliable and simple tool to accelerate research in systematic biology ( https://github.com/MaoYafei/TREEasy ).     

Stochastic mapping of morphological characters

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.     

Fifty years of character compatibility concepts at work

In the mid 19th century,systematic biologists realized that observable similarities and differences among a group of related species could be the basis for hypotheses about the evolutionary relationships among the species and their ancestors.Such hypotheses Can be expressed as characters.A character is comprised of two or more character states of species considered to be similar with respect to a basis for comparison.The states of a character may also be arranged into a character state tree to hypothesize speciation events associated with changes from one character state to another.In the mid 20th century.some systematists realized that sometimes paxrs of characters(or character state trees)could be incompatible as hypotheses,i.e.,they could not both be true.Through the 1950s,'60s and'70s,tests for,and ways to resolve,incompatibilities were used to estimate an ancestor relation based on mutually compatible characters.An estimate was often shown as a diagram connecting ancestors to their immediate descendants(not quite correctly)called a phylogenetic tree.More recently,other applications of compatibility concepts have been developed,including:identify characters that appear to be random in the context of their data set;combine estimates of ancestor relations for subsets of taxa in a larger collection into a single estimate(a so-called supertree)for the whole collection;and interpret geographic patterns in an evolutionary context.     

ON CONSENSUS, COLLAPSIBILITY, AND CLADE CONCORDANCE

Abstract — Consensus in cladistics is reviewed. Consensus trees, which summarize the agreement in grouping among a set of cladograms, are distinguished from compromise trees, which may contain groups that do not appear in all the cladograms being compared. Only a strict or Nelson tree is an actual consensus. This distinction has implications for the concept of support for cladograms: only those branches supported under all possible optimizations are unambiguously supported. We refer to such cladograms as strictly supported, in contrast to the semistrictly (ambiguously) supported cladograms output by various current microcomputer programs for cladistic analysis. Such semistrictly supported cladograms may be collapsed, however, by a variety of options in various programs. Consideration of collapsibility and optimization on multifurcations leads to some conclusions on the use of consensus. Consensus tree length provides information about character conflict that occurs between, not within, cladograms. We propose the clade concordance index, which employs the consensus tree length to measure inter-cladogram character conflict for all characters among a set of cladograms.     

Molecular evolution of rodent insulins

Several trees of amino acid sequences of rodent insulins were derived with the maximum-parsimony procedure. Possible orthologous and paralogous relationships were investigated. Except for a recent gene duplication in the ancestor of rat and mouse, there are no strong arguments for other paralogous relationships. Therefore, a tree in agreement with other biological data is the most reasonable one. According to this tree, the capacity to form zinc-binding hexamers was lost once in the ancestor of the hystricomorph rodents, followed by moderately increased evolutionary rates in the lineages to African porcupine and chinchilla but highly increased rates in at least three independent lines to other taxa of this suborder: guinea pig, cuis, and Octodontoidea (coypu and casiragua).      

Phylogenetics and the future of helminth systematics

Phylogenetic systematics is a relatively new formal technique that increases the precision with which one can make direct estimates of the history of phylogenetic descent. These estimates are made in the form of phylogenetic trees, or cladograms. Cladograms may be converted directly into classifications or they may be used to test various hypotheses about the evolutionary process. More than 20 phylogenetic analyses of helminth groups have been published already, and these have been used to investigate evolutionary questions in developmental biology, biogeography, speciation, coevolution, and evolutionary ecology.     

GENE TREES AND ORGANISMAL HISTORIES: A PHYLOGENETIC APPROACH TO POPULATION BIOLOGY

A “gene tree” is the phylogeny of alleles or haplotypes for any specified stretch of DNA. Gene trees are components of population trees or species trees; their analysis entails a shift in perspective from many of the familiar models and concepts of population genetics, which typically deal with frequencies of phylogenetically unordered alleles. Molecular surveys of haplotype diversity in mitochondrial DNA (mtDNA) have provided the first extensive empirical data suitable for estimation of gene trees on a microevolutionary (intraspecific) scale. The relationship between phylogeny and geographic distribution constitutes the phylogeographic pattern for any species. Observed phylogeographic trees can be interpreted in terms of historical demography by comparison to predictions derived from models of gene lineage sorting, such as inbreeding theory and branching-process theory. Results of such analyses for more than 20 vertebrate species strongly suggest that the demographies of populations have been remarkably dynamic and unsettled over space and recent evolutionary time. This conclusion is consistent with ecological observations documenting dramatic population-size fluctuations and range shifts in many contemporary species. By adding an historical perspective to population biology, the gene-lineage approach can help forge links between the disciplines of phylogenetic systematics (and macroevolutionary study) and population genetics (microevolution). Preliminary extensions of the “gene tree” methodology to haplotypes of nuclear genes (such as Adh in Drosophila melanogaster) demonstrate that the phylogenetic perspective can also help to illuminate molecular-genetic processes (such as recombination or gene conversion), as well as contribute to knowledge of the origin, age, and molecular basis of particular adaptations.     

Tree thinking for all biology: the problem with reading phylogenies as ladders of progress

Phylogenies are increasingly prominent across all of biology, especially as DNA sequencing makes more and more trees available. However, their utility is compromised by widespread misconceptions about what phylogenies can tell us, and improved "tree thinking" is crucial. The most-serious problem comes from reading trees as ladders from "left to right"--many biologists assume that species-poor lineages that appear "early branching" or "basal" are ancestral--we call this the "primitive lineage fallacy". This mistake causes misleading inferences about changes in individual characteristics and leads to misrepresentation of the evolutionary process. The problem can be rectified by considering that modern phylogenies of present-day species and genes show relationships among evolutionary cousins. Emphasizing that these are extant entities in the 21(st) century will help correct inferences about ancestral characteristics, and will enable us to leave behind 19(th) century notions about the ladder of progress driving evolution.     

Homology and hominid phylogeny: Problems and potential solutions

This paper addresses the problem of how to reconstruct accurately the hominid evolutionary tree from skeletal remains. Few would disagree that DNA is generally better than bone as a source of data for assessing phylogenetic relationships. To be sure, DNA base pairs present their own special headaches for phylogenetic reconstruction,¹ not the least of which is that only four possible characters exist at any locus. But base pairs satisfy all the criteria for good phylogenetic data (see Box 1): By definition, they are discrete, heritable, quantifiable, and natural units of phylogenetic information that pass directly from ancestor to descendant. © 1999 Wiley-Liss, Inc.