How To Build A Phylogenetic Tree

Building a phylogenetic tree is a fascinating journey into evolutionary history. It allows us to visualize the relationships between different organisms based on their shared ancestry and accumulated changes over time. Whether you're a student, researcher, or simply curious about the connections between species, understanding the process of constructing a phylogenetic tree unlocks a deeper understanding of the tree of life.

What is a Phylogenetic Tree?

A phylogenetic tree, also known as an evolutionary tree, is a diagram that illustrates the evolutionary relationships among different biological entities—species, populations, genes, etc.—that are believed to have a common ancestor. These trees are visual representations of hypotheses about the evolutionary history of these entities. The patterns on a phylogenetic tree can be used to study the evolution of traits, track the spread of diseases, and classify organisms.

The basic components of a phylogenetic tree are:

Root: Represents the common ancestor of all taxa in the tree.
Branches: Represent evolutionary lineages changing over time.
Nodes: Represent common ancestors; a branching point where a single lineage evolves into two or more.
Leaves (Tips): Represent the taxa for which data have been collected. These are the operational taxonomic units (OTUs), which could be species, genes, or other entities.

Phylogenetic trees are constructed using various types of data, including morphological features, biochemical characteristics, and, most commonly, molecular data like DNA and protein sequences. The goal is to group organisms that are more closely related to each other than to others in the tree.

Why Build Phylogenetic Trees?

Building phylogenetic trees is a cornerstone of evolutionary biology, providing valuable insights into the history of life on Earth. Here's why they are so important:

Understanding Evolutionary Relationships: Phylogenetic trees depict the evolutionary relationships between different organisms, showing how they are related through common ancestry. This helps us understand the patterns of evolution and the processes that have shaped the diversity of life.
Classification of Organisms: Phylogenetic trees are used to classify organisms based on their evolutionary relationships. This system of classification, known as phylogenetic taxonomy, reflects the evolutionary history of organisms and provides a more accurate and informative way to organize the diversity of life.
Studying the Evolution of Traits: By mapping traits onto a phylogenetic tree, we can study how traits have evolved over time. This can help us understand the adaptive significance of different traits and how they have contributed to the success of different lineages.
Tracking the Spread of Diseases: Phylogenetic trees can be used to track the spread of infectious diseases, such as viruses and bacteria. By analyzing the genetic sequences of pathogens, we can reconstruct their evolutionary history and identify the sources of outbreaks.
Conservation Efforts: Understanding the evolutionary relationships between species can inform conservation efforts. By identifying species that are closely related to endangered species, we can prioritize conservation efforts to preserve the genetic diversity of life.

Data Acquisition and Preparation

The first step in building a phylogenetic tree is to gather the data you'll use to infer evolutionary relationships. This often involves molecular data, such as DNA or protein sequences, but can also include morphological or behavioral data.

1. Choosing the Data

Molecular Data: DNA sequences (e.g., from specific genes or entire genomes) and protein sequences are commonly used due to their abundance and ease of comparison.
Morphological Data: Physical characteristics (e.g., bone structures, flower shapes) can be used, particularly when molecular data is limited.
Behavioral Data: Behavioral traits (e.g., mating rituals, feeding strategies) can also provide insights into evolutionary relationships.

2. Collecting the Data

DNA/Protein Sequencing: Obtain sequences from public databases (e.g., GenBank) or perform your own sequencing.
Morphological Measurements: Collect detailed measurements and descriptions of physical traits.
Behavioral Observations: Record detailed observations of relevant behaviors.

3. Data Alignment

Sequence Alignment: If using molecular data, align the sequences to identify homologous positions. This is crucial for identifying shared ancestry. Software like MUSCLE, ClustalW, or MAFFT are commonly used for multiple sequence alignment.
- Open your chosen alignment software.
- Import your sequences.
- Choose alignment parameters (usually defaults work well).
- Run the alignment.
- Inspect the alignment for errors and make manual adjustments if necessary.
Character Coding: If using morphological or behavioral data, create a character matrix where each character represents a trait and each state represents a different form of that trait.

Choosing a Phylogenetic Method

Several methods can be used to construct phylogenetic trees, each with its own assumptions and limitations. The choice of method depends on the type of data, the size of the dataset, and the specific research question.

1. Distance-Based Methods

Distance-based methods, such as the neighbor-joining method, use a matrix of pairwise distances between taxa to construct the tree. These methods are computationally efficient but may not be as accurate as other methods.

Neighbor-Joining: This method starts with a star-like tree and iteratively joins the closest pairs of taxa until all taxa are connected.

2. Character-Based Methods

Character-based methods, such as maximum parsimony and maximum likelihood, use the characters (e.g., DNA sequences, morphological traits) directly to construct the tree. These methods are more computationally intensive but generally more accurate than distance-based methods.

Maximum Parsimony: This method seeks the tree that requires the fewest evolutionary changes to explain the observed data. It's based on the principle of Occam's razor, which states that the simplest explanation is usually the best.
Maximum Likelihood: This method seeks the tree that maximizes the probability of observing the data, given a specific model of evolution. It takes into account the rate and pattern of evolutionary change.

3. Bayesian Inference

Bayesian inference is a statistical method that uses Bayes' theorem to estimate the probability of different phylogenetic trees, given the data and a prior probability distribution. This method is computationally intensive but can provide more accurate and robust results than other methods. Bayesian inference provides a posterior probability distribution of trees, which reflects the uncertainty in the estimated phylogeny.

Building the Tree

Once you've chosen a phylogenetic method, you can use a software program to construct the tree. Several programs are available, including:

MEGA: A user-friendly program with a graphical interface that supports a variety of phylogenetic methods.
PAUP*: A powerful program with a command-line interface that supports a wide range of phylogenetic methods.
MrBayes: A program specifically designed for Bayesian inference of phylogenies.
BEAST: Another program for Bayesian inference, particularly useful for incorporating time into phylogenetic analyses.

Here’s a more detailed look at the steps involved in using these programs:

MEGA (Molecular Evolutionary Genetics Analysis)

MEGA is a popular, user-friendly software that provides a comprehensive toolkit for molecular evolutionary analysis.

Install and Launch MEGA:
- Download MEGA from the official website () and install it on your computer.
- Launch the MEGA application.
Import Data:
- Click on "Align" then “Edit/Build Alignment”.
- Create a new alignment.
- Import your sequence data by clicking on "Data" then "Import Alignment from File". Supported formats include FASTA, MEGA, and others.
Align Sequences:
- Use the MUSCLE or ClustalW alignment tool within MEGA.
- Adjust parameters as necessary or use default settings.
- Compute the alignment.
Construct the Phylogenetic Tree:
- Go to the main MEGA window and click on "Phylogeny".
- Choose the method you want to use (e.g., Maximum Likelihood, Neighbor-Joining).
- Configure the parameters such as the substitution model (e.g., Kimura 2-parameter, GTR) and gamma distribution.
- Run the analysis.
View and Export the Tree:
- MEGA will display the resulting phylogenetic tree.
- You can customize the tree appearance (e.g., branch lengths, labels) and export it in various formats (e.g., Newick, Nexus, PDF).

PAUP* (Phylogenetic Analysis Using Parsimony)

PAUP* is a powerful, albeit command-line driven, software package for phylogenetic analysis.

Install PAUP*:
- PAUP* is a commercial software. Obtain a license and download the software from the Sinauer Associates website.
- Install it on your computer.

Prepare the Data File:

Create a Nexus file containing your sequence data. This file includes data, character definitions, and PAUP* commands.

Example Nexus File Structure:

#NEXUS
BEGIN DATA;
    DIMENSIONS NTAX=4 NCHAR=10;
    FORMAT DATATYPE=DNA MISSING=? GAP=-;
    MATRIX
    Taxon1 ATGCATGCAT
    Taxon2 ATGCATGCGC
    Taxon3 ATGCGTGCGC
    Taxon4 TTGCGTGCGC
    ;
END;

BEGIN PAUP;
    SET criterion=parsimony;
    HSEARCH;
    SAVETREES file=result.tre;
END;

Run PAUP*:
- Open PAUP* and execute the Nexus file.
```
paup < nexusfile.nex
```
Analyze the Results:
- PAUP* will generate a tree file (e.g., result.tre) that you can view with tree visualization software like FigTree.

MrBayes

MrBayes is specifically designed for Bayesian inference of phylogenetic trees.

Install MrBayes:
- Download MrBayes from its official website () and install it on your computer.

Prepare the Data File:

Create a Nexus file containing your sequence data.

Example MrBayes Nexus File:

#NEXUS
BEGIN DATA;
    DIMENSIONS NTAX=4 NCHAR=10;
    FORMAT DATATYPE=DNA MISSING=? GAP=-;
    MATRIX
    Taxon1 ATGCATGCAT
    Taxon2 ATGCATGCGC
    Taxon3 ATGCGTGCGC
    Taxon4 TTGCGTGCGC
    ;
END;

BEGIN MRBAYES;
    SET autoclose=yes;
    LSET nst=6 rates=invgamma;
    MCMC ngen=1000000 samplefreq=1000;
    SUMT burnin=250;
END;

Run MrBayes:
- Open MrBayes and execute the Nexus file.
```
mb nexusfile.nex
```
Analyze the Results:
- MrBayes will generate tree files and summary files. Use software like FigTree to view the consensus tree and examine posterior probabilities.

BEAST (Bayesian Evolutionary Analysis Sampling Trees)

BEAST is used for Bayesian evolutionary analysis, particularly when incorporating time-scaled phylogenies.

Install BEAST:
- Download BEAST from its official website () and install it along with its dependencies (e.g., Java).
Prepare the Data File:
- Create an XML file that specifies the data, models, and priors. This can be done using BEAUti, a program included with BEAST.
- Open BEAUti and load your sequence data.
- Set up the evolutionary models, priors, and MCMC parameters.
- Save the configuration as an XML file.
Run BEAST:
- Open BEAST and load the XML file.
- Run the analysis.
```
java -jar beast.jar -beast -seed  nexusfile.xml
```
Analyze the Results:
- BEAST will generate tree files and log files. Use TreeAnnotator (included with BEAST) to summarize the tree samples and create a maximum clade credibility tree.
- Visualize the resulting tree with FigTree.

Tree Interpretation and Evaluation

Once you've constructed a phylogenetic tree, it's important to interpret and evaluate it to assess its reliability and biological significance.

1. Tree Topology

The topology of a tree refers to the branching pattern and relationships among the taxa. Examine the tree to identify the major clades (groups of taxa that share a common ancestor) and their relationships to each other.

2. Branch Lengths

The branch lengths of a tree can represent the amount of evolutionary change that has occurred along each lineage. In some trees, branch lengths are proportional to time, allowing you to estimate the timing of evolutionary events.

3. Support Values

Support values indicate the statistical support for each branch in the tree. Common support values include bootstrap values (from bootstrapping) and posterior probabilities (from Bayesian inference). Branches with high support values are considered more reliable.

Bootstrap Values: These are calculated by resampling your original dataset, creating many slightly different datasets, and building a tree for each. The bootstrap value represents the percentage of trees in which a particular clade appears. Values above 70% are generally considered good support.
Posterior Probabilities: These values come from Bayesian analyses and represent the probability that a clade is real, given the data and the model. Values above 0.95 are typically considered strong support.

4. Rooting the Tree

The root of a phylogenetic tree represents the common ancestor of all taxa in the tree. If the root is not known a priori, you can use an outgroup to root the tree. An outgroup is a taxon that is known to be more distantly related to the taxa of interest than they are to each other.

5. Evaluating Tree Accuracy

Compare with Existing Data: Compare your tree with existing phylogenetic hypotheses based on other data sources.
Assess Sensitivity to Assumptions: Evaluate how sensitive your tree is to different assumptions, such as the choice of phylogenetic method or the model of evolution.
Perform Statistical Tests: Use statistical tests, such as the Shimodaira-Hasegawa test, to compare different tree topologies and assess their statistical significance.

Common Pitfalls and Considerations

Long Branch Attraction: Taxa with long branches (i.e., high rates of evolution) may be incorrectly grouped together due to convergent evolution.
Incomplete Lineage Sorting: Gene trees may differ from species trees due to incomplete lineage sorting, where ancestral polymorphisms are sorted differently in different lineages.
Horizontal Gene Transfer: Horizontal gene transfer (the transfer of genetic material between organisms that are not directly related) can complicate phylogenetic analyses, particularly in bacteria and archaea.
Data Quality: Ensure that your data is accurate and free from errors. Errors in the data can lead to inaccurate phylogenetic trees.
Model Selection: Choose an appropriate model of evolution for your data. Incorrect model selection can lead to biased results.

Applications of Phylogenetic Trees

Phylogenetic trees have a wide range of applications in biology and other fields, including:

Taxonomy and Systematics: Classifying organisms and understanding their evolutionary relationships.
Epidemiology: Tracking the spread of infectious diseases and identifying the sources of outbreaks.
Conservation Biology: Prioritizing conservation efforts and understanding the evolutionary history of endangered species.
Drug Discovery: Identifying potential drug targets by studying the evolution of proteins and genes in pathogens.
Agriculture: Improving crop yields and resistance to pests and diseases by understanding the evolutionary relationships of crop plants and their relatives.
Forensic Science: Tracing the origins of biological evidence, such as DNA samples, using phylogenetic methods.

Conclusion

Building a phylogenetic tree is a complex but rewarding process that provides valuable insights into the evolutionary history of life. By carefully collecting and analyzing data, choosing appropriate phylogenetic methods, and evaluating the results, you can construct accurate and informative trees that shed light on the relationships between different organisms. Whether you're a student, researcher, or simply curious about the connections between species, understanding the process of constructing a phylogenetic tree unlocks a deeper understanding of the tree of life.