TITLE: Roadmap to the bioinformatic study of gene and protein evolution
AUTHORS: florian.jacques  , Paulina Bolivar, Kristian Pietras, Emma Hammarlund

[DESCRIPTION]
We present a compilation of nucleic acid and protein databases and bioinformatic tools for phylogenetic reconstructions and a wide range of studies on molecular evolution and population genetics. We provide a protocol for information extraction from biological databases and simple phylogenetic reconstruction.

[STEPS]
SECTION: Sequence selection and comparisons
2. Identification of homologues

Studying the evolution of a family of genes or proteins requires the identification of homologues, i.e., genes or protein with shared ancestry. Homologues include orthologues, that are present in different species, and paralogues, that are present in the same genome. Bioinformatic tools can be used to identify gene or protein homology based on sequence similarity, in the genomes of any species (see the list below).

>Use the sequence of your gene of interest under fasta format to identify homologues in the genomes of other species using BLAST, for example. Paste the sequences of the homologues in a single fasta file and select the species or groups of species of interest (e.g. all animals and choanoflagellates). Download the sequences of the homologues covering the diversity of animals and paste them under fasta format in another fasta file.

Here is a list of tools that can be used to identify sequence homologues:
 
     Database      Features      Link        BLAST      Protein or DNA homology   search      https://blast.ncbi.nlm.nih.gov/Blast.cgi        Blat      Sequence search      https://genome.ucsc.edu/cgi-bin/hgBlat        Ensembl      DNA homology search      https://m.ensembl.org/index.html        FASTA      Sequence search and   alignment      https://www.ebi.ac.uk/Tools/sss/fasta/        HMMER      Protein homology search      http://hmmer.org/        Shaha      Sequence search and   alignment      https://www.sanger.ac.uk/tool/ssaha/   
 
SECTION: Sequence selection and comparisons
3. Sequence alignment

Phylogenetic analysis requires identification of homologue bases or amino acid residues of the different sequences. Homology is inferred by a sequence alignment. Sequences of different genes or proteins are put in every row one after the other to arrange every homologous base or amino acid in the same column.

Here is a list of tools for nucleic acid or amino acid sequence alignment. Use an appropriate tool (nucleic acid or amino acid) to generate an alignment of the sequences. Insertions and deletions are indicated by gaps "-" added to the sequences.

>It is sometimes recommended to check the alignment and, when necessary, to improve it manually or using GBlocks. Then, export the alignment using fasta format.
 
     Software      Features      Link        BAli-Phy      Bayesian alignment and   phylogenetic analysis      http://www.bali-phy.org        ClustalOmega      DNA or amino acid   sequence alignment      https://www.ebi.ac.uk/Tools/msa/clustalo/        ClustalW      DNA or amino acid   sequence alignment      https://www.genome.jp/tools-bin/clustalw        GBlocks      DNA or amino acid   alignment      http://molevol.cmima.csic.es/castresana/Gblocks_server.html        MAFFT      DNA or amino acid   sequence alignment      https://mafft.cbrc.jp/alignment/server/        Muscle      DNA or amino acid   sequence alignment      https://www.ebi.ac.uk/Tools/msa/muscle/        Prank      DNA or amino acid   sequence alignment      http://wasabiapp.org/software/prank/        Probcons      Amino acid sequence   alignment      http://probcons.stanford.edu/        T-Coffee      Sequence alignment      http://tcoffee.crg.cat/   
 
SECTION: Phylogenetic analysis
4. Phylogenetic inference

The evolutionary history of gene, protein or species is generally presented as a phylogenetic tree, a graphical illustration of the evolutionary relationships between the studied taxa. Several methods for phylogenetic inference exist: Maximum Parsimony, the distance-methods and the probabilistic methods. Choose an appropriate method to reconstruct the phylogenetic tree of the genes/proteins of interest. The probabilistic methods are nowadays the most widely used for molecular data, but many studies use other methods, distance methods in complement.

>Choose one or several of these methods to reconstruct the evolutionary history of your gene, protein or species of interest.

Here is a list of tools for phylogenetic reconstruction using diverse methods, and visualization of phylogenetic trees that can be used in complement. For beginners, we recommend using SeaView or Mega with ML analyses, which are very user-friendly and include several tools for sequence alignment, phylogenetic inference including maximum parsimony, distance methods and probabilistic methods, and a tree visualization tool. Advanced users generally prefer the more complex PhyML or RaxML.
 
     Software      Features      Link        ETEToolkit      Visualization and   analysis of phylogenetic trees      http://etetoolkit.org/        FigTree      Graphic software for   phylogenetic trees      http://tree.bio.ed.ac.uk/software/figtree/        ITOL      Visualization and   annotation of phylogenetic trees      https://itol.embl.de/        Mega      Sequence alignment, model   selection, phylogenetic analysis (parsimony, distance methods)      https://www.megasoftware.net/        Mesquite      Comparative analyses and   statistics      http://www.mesquiteproject.org/        MrBayes      Bayesian phylogenetic   inference, ancestral states reconstruction, phylogenetic calibration…      http://nbisweden.github.io/MrBayes/        PAML      Maximum likelihood   phylogenetic inference, estimation of selection strength, ancestral states   reconstruction and other analyses      http://abacus.gene.ucl.ac.uk/software/paml.html        PAUP      Phylogenetic analyses      http://paup.phylosolutions.com/        PhyML      Maximum likelihood   phylogenetic inference, ancestral states reconstruction and other analyses      http://atgc.lirmm.fr/phyml/        RaxML      Maximum likelihood   phylogenetic inference      https://cme.h-its.org/exelixis/web/software/raxml/        SeaView      Sequence alignment and   phylogenetic analysis (parsimony, NJ, ML)      http://doua.prabi.fr/software/seaview   
 
 
     Software      Features      Link        Ape      R-written package for   molecular phylogenetics      http://ape-package.ird.fr        Arlequin      Population genetics   analyses      http://cmpg.unibe.ch/software/arlequin35/        BayesTraits      Evolutionary analyses using   Bayesian inference      http://www.evolution.rdg.ac.uk/BayesTraitsV3.0.5/BayesTraitsV3.0.5.html        BEAST      Phylogenetic calibration      http://www.beast.community        CAFE      Gene family evolution      https://github.com/hahnlab/CAFE5        CoGE      Comparative genomics   analyses      https://genomevolution.org/coge/        Copycat      Software for studying   coevolution      http://www.cophylogenetics.com/        Core-PA      Software for studying   coevolution      http://pacosy.informatik.uni-leipzig.de/49-1-CoRe-PA.html        DNAsp      Analysis of DNA   polymorphism      http://www.ub.edu/dnasp/         ETEToolkit      Visualization and   analysis of phylogenetic trees      http://etetoolkit.org/        FigTree      Graphic software for   phylogenetic trees      http://tree.bio.ed.ac.uk/software/figtree/        Genepop      Population genetics   analyses      https://genepop.curtin.edu.au/        HGT-Finder      Horizontal gene transfer   finding      http://cys.bios.niu.edu/HGTFinder/   HGTFinder.tar.gz        ITOL      Visualization and   annotation of phylogenetic trees      https://itol.embl.de/        Jane      Software for studying   coevolution      https://www.cs.hmc.edu/~hadas/jane/        Mega      Sequence alignment, model   selection, phylogenetic analysis (parsimony, distance methods)      https://www.megasoftware.net/        Mesquite      Comparative analyses and   statistics      http://www.mesquiteproject.org/        MrBayes      Bayesian phylogenetic   inference, ancestral states reconstruction, phylogenetic calibration…      http://nbisweden.github.io/MrBayes/        Ohnologs      Database of vertebrate   ohnologues, resulting from whole genome duplications      http://ohnologs.curie.fr/        PAML      Maximum likelihood   phylogenetic inference, estimation of selection strength, ancestral states   reconstruction and other analyses      http://abacus.gene.ucl.ac.uk/software/paml.html        PAUP      Phylogenetic analyses      http://paup.phylosolutions.com/        PhyML      Maximum likelihood   phylogenetic inference, ancestral states reconstruction and other analyses      http://atgc.lirmm.fr/phyml/        RASP      Ancestral states   reconstruction      http://mnh.scu.edu.cn/soft/blog/RASP/index.html        RaxML      Maximum likelihood   phylogenetic inference      https://cme.h-its.org/exelixis/web/software/raxml/        SeaView      Sequence alignment and   phylogenetic analysis (parsimony, NJ, ML)      http://doua.prabi.fr/software/seaview        SNiplay      SNP detection and other   population genetics analyses      https://sniplay.southgreen.fr/cgi-bin/home.cgi        Timetree      Tree calibration      http://www.timetree.org/        TreeMap      Software for studying co-evolution      https://sites.google.com/site/cophylogeny/treemap   
 
SECTION: Working with phylogenies
5. Reconstruct the evolution of the gene or protein

Sequence alignments and phylogenetic trees can be used to reconstruct diverse aspects of the evolutionary history of genes, proteins and species, as well as the study the genetic structures within populations. In this last section, we provide a brief and non-exhaustive overview of the main evolutionary studies that can be performed using bioinformatic tools.
SECTION: Sequence selection and comparisons
1. State of the art on genes and proteins

Evolutionary analyses on molecular data, (genes, genomes or proteins), generally require retrieving information from public biological databases. Several dozens of databases store information about the state of the art on genes and proteins. In particular, many of them provide the sequences in fasta format, which is necessary for evolutionary studies. Other information and annotations, including structure, activity, biological function, tissue expression, subcellular location and polymorphism can also prove relevant.

Here is a non-exhaustive list of nucleic acid databases, and a list of the main protein databases, with their main features. 

>Retrieve the sequence from one of the following databases (e.g. NCBI or Uniprot) and paste the sequence in a fasta file using fasta format, using .fasta as filename extension.

Fasta format includes a headline starting with ">", and the nucleic acid or amino acid sequence.

For example:

>sp|P04637|P53_HUMAN Cellular tumor antigen p53 OS=Homo sapiens OX=9606 GN=TP53 PE=1 SV=4 MEEPQSDPSVEPPLSQETFSDLWKLLPENNVLSPLPSQAMDDLMLSPDDIEQWFTEDPGP DEAPRMPEAAPPVAPAPAAPTPAAPAPAPSWPLSSSVPSQKTYQGSYGFRLGFLHSGTAK SVTCTYSPALNKMFCQLAKTCPVQLWVDSTPPPGTRVRAMAIYKQSQHMTEVVRRCPHHE RCSDSDGLAPPQHLIRVEGNLRVEYLDDRNTFRHSVVVPYEPPEVGSDCTTIHYNYMCNS SCMGGMNRRPILTIITLEDSSGNLLGRNSFEVRVCACPGRDRRTEEENLRKKGEPHHELP PGSTKRALPNNTSSSPQPKKKPLDGEYFTLQIRGRERFEMFRELNEALELKDAQAGKEPG GSRAHSSHLKSKKGQSTSRHKKLMFKTEGPDSD

 
     Database      Features      Link        BAR      Database of plant genes and proteins      http://bar.utoronto.ca/        Bgee      Gene expression patterns      https://bgee.org/        Ensembl      Genome browser of vertebrates, includes tools for   identification of homology      https://www.ensembl.org/index.html        Entrez      Gene sequences and structures      https://www.ncbi.nlm.nih.gov/Web/Search/entrezfs.html        FigTree      Vizualization tool for phylogenetic trees      https://github.com/rambaut/figtree/releases        FlyBase      Genome and proteins of the model insect D.   melanogaster      https://flybase.org/        GenBank      Annotated DNA sequences      https://www.ncbi.nlm.nih.gov/genbank/        PomBase      Genes and proteins of the model yeast S. pombe      https://www.pombase.org/        TAIR      Genome and proteins of the model plant A.   thaliana      https://www.arabidopsis.org/        WormBase      Genome and proteins of the model nematode C.   elegans      https://wormbase.org//#012-34-5        Xenbase      Genome and proteins of the model amphibian X.   laevis      http://www.xenbase.org/entry/   
  
     Database      Features      Link        Gene ontology      Unified annotation of   molecular function, biological processes, and cellular components of proteins      http://geneontology.org/        Interpro      Classification of   proteins domains and functional sites      https://www.ebi.ac.uk/interpro/        KEGG      Protein function and   biological pathways      https://www.genome.jp/kegg/        PDB      3-dimensional structures   of proteins      https://www.rcsb.org/        Pfam      Information about protein   families and domains, includes tools for identification of homology      http://pfam.xfam.org/        Pharos      Centralizes literature   for human proteins      https://pharos.nih.gov/        Prints      Protein fingerprints   classification database      http://www.bioinf.man.ac.uk/dbbrowser/PRINTS/        Prosite      Protein family database      https://prosite.expasy.org/        Scop      Classification of protein   based on their structure      https://scop.mrc-lmb.cam.ac.uk/        Superfamily      Protein structure and   functions      https://supfam.org/        The human protein atlas      Information on human   protein and their link with diseases      https://www.proteinatlas.org/        Uniprot      General information on   proteins      https://www.uniprot.org/uniprot/P04637   
 
SECTION: Sequence selection and comparisons
1.1. Protein classification

Using protein classification can also be relevant for evolutionary studies. Proteins are classified into different categories based on structural and functional similarity, evolutionary relationship, or both. Retrieving the classification of a protein of interest, and identifying the main protein domains, often provides valuable insight on its  biodiversity and evolutionary origin. Several classification systems are published and listed in the table above.

>Use a classification system (e.g. Pfam or Interpro) to identify the main domains of a protein. Pfam presents also their occurrence in living organisms as a sunburst plot.

This figure displays the diversity of the domain P53 that can be retrieved from Pfam. It shows that this domain is present in virtually all animals, and some of their close relatives, such as choanoflagellates, and suggests that this domain appeared before the divergence between animals and these protists.  

SECTION: Working with phylogenies
5.1. Reconstitution of ancestral states

Retracing the functional evolution of genes, proteins, or biological traits often requires the reconstitution of ancestral states. Ancestral states can be inferred from a phylogenetic tree using maximum of parsimony, maximum likelihood, or Bayesian inference; and requires the aligned sequences and the model of molecular evolution that has been used for the phylogenetic analysis (when using probabilistic methods only).

 
     Software      Features      Link        BayesTraits      Evolutionary analyses using   Bayesian inference      http://www.evolution.rdg.ac.uk/BayesTraitsV3.0.5/BayesTraitsV3.0.5.html        BEAST      Phylogenetic calibration      http://www.beast.community        Mega      Sequence alignment, model   selection, phylogenetic analysis (parsimony, distance methods)      https://www.megasoftware.net/        Mesquite      Comparative analyses and   statistics      http://www.mesquiteproject.org/        MrBayes      Bayesian phylogenetic   inference, ancestral states reconstruction, phylogenetic calibration…      http://nbisweden.github.io/MrBayes/        PAML      Maximum likelihood   phylogenetic inference, estimation of selection strength, ancestral states   reconstruction and other analyses      http://abacus.gene.ucl.ac.uk/software/paml.html        RASP      Ancestral states   reconstruction      http://mnh.scu.edu.cn/soft/blog/RASP/index.html   
 

 
     Software      Features      Link        ETEToolkit      Visualization and   analysis of phylogenetic trees      http://etetoolkit.org/        FigTree      Graphic software for   phylogenetic trees      http://tree.bio.ed.ac.uk/software/figtree/        ITOL      Visualization and   annotation of phylogenetic trees      https://itol.embl.de/        Mega      Sequence alignment, model   selection, phylogenetic analysis (parsimony, distance methods)      https://www.megasoftware.net/        MrBayes      Bayesian phylogenetic   inference, ancestral states reconstruction, phylogenetic calibration…      http://nbisweden.github.io/MrBayes/        PAML      Maximum likelihood   phylogenetic inference, estimation of selection strength, ancestral states   reconstruction and other analyses      http://abacus.gene.ucl.ac.uk/software/paml.html        PAUP      Phylogenetic analyses      http://paup.phylosolutions.com/        PhyML      Maximum likelihood   phylogenetic inference, ancestral states reconstruction and other analyses      http://atgc.lirmm.fr/phyml/        RaxML      Maximum likelihood   phylogenetic inference      https://cme.h-its.org/exelixis/web/software/raxml/        SeaView      Sequence alignment and   phylogenetic analysis (parsimony, NJ, ML)      http://doua.prabi.fr/software/seaview   
 
 
       Software         Features         Link            BayesTraits         Evolutionary analyses using   Bayesian inference         http://www.evolution.rdg.ac.uk/BayesTraitsV3.0.5/BayesTraitsV3.0.5.html            BEAST         Phylogenetic calibration         http://www.beast.community            Mesquite         Comparative analyses and   statistics         http://www.mesquiteproject.org/            MrBayes         Bayesian phylogenetic   inference, ancestral states reconstruction, phylogenetic calibration…         http://nbisweden.github.io/MrBayes/            PAML         Maximum likelihood   phylogenetic inference, estimation of selection strength, ancestral states   reconstruction and other analyses         http://abacus.gene.ucl.ac.uk/software/paml.html            PhyML         Maximum likelihood   phylogenetic inference, ancestral states reconstruction and other analyses         http://atgc.lirmm.fr/phyml/            RASP         Ancestral states   reconstruction         http://mnh.scu.edu.cn/soft/blog/RASP/index.html      
 
SECTION: Working with phylogenies
5.2. Measure of selection strength

The strength of selection on protein coding genes can be calculated by evaluating the ration of the number of non-synonymous mutations (mutations changing the protein sequence) per non-synonymous site (dN) and the number of synonymous mutations (mutations with no effect on the protein sequence due to the redundancy of the genetic code) per synonymous site (dS). The ratio dN/dS reveals, if >1, that non-synonymous mutations are higher than expected and the gene is under positive selection. If dN/dS<1, the gene is under purifying selection and if dN/dS=1, the selection is neutral. Selection strength can be calculated by sequence alignment programs such as Mega.
SECTION: Working with phylogenies
5.5. Phylogenetic comparative analysis

Evolutionary biology often employs the so-called phylogenetic comparative methods to study the adaptive significance of biological traits. These methods aim at identifying biological characters, in terms of morphology, physiology, or ecology, that result from a shared ancestry. Comparative analyses can be done for quantitative or qualitative variables. A very appropriate tool for comparative analysis and to compute statistics on phylogenetic trees is Mesquite.´BayesTraits can also be used.
SECTION: Working with phylogenies
5.4. Study of coevolution

Evolutionary ecology and parasitology often study the evolution of hosts and parasites association through an approach of coevolution, or reciprocal genetic change between different species. Coevolution can also be used to study associations of genes or proteins. Studying coevolution consists in identifying evolutionary events such as co-speciation, host change, and duplication or loss of interaction from the phylogenetic trees of the hosts and the parasites.

In our second example, we used Maximum likelihood to reconstruct the evolution of cyclins and CDKs, two families of proteins involved in cell cycle control and closely interacting. We used Jane and TreeMap to reconstruct coevolutionary scenarios between the two families.

In both figures, the clustering of cyclins and CDKs indicate an interaction (in this case, that the cyclin can bind the CDK). Red spots indicate significant events of coevolution between the two families of proteins. Co-speciation (hollow red circle), duplications (solid red circle), duplications with host switch (yellow circle), loss of interaction (dashed lines), failures to diverge (jagged lines) are indicated on the cophylogeny.

 
     Software      Features      Link        Copycat      Software for studying   coevolution      http://www.cophylogenetics.com/        Core-PA      Software for studying   coevolution      http://pacosy.informatik.uni-leipzig.de/49-1-CoRe-PA.html        Jane      Software for studying   coevolution      https://www.cs.hmc.edu/~hadas/jane/        TreeMap      Software for studying co-evolution      https://sites.google.com/site/cophylogeny/treemap   
 

  

SECTION: Working with phylogenies
5.3. Phylogenetic calibration

Phylogenetic calibration consists in estimating the age of speciation events with events with a known age, i.e., using fossil and other geological data (that can only give minimal ages) as calibration points. Alternatively, mutation rates can be used to calculate the divergence time between two sequences.

Databases such as Timetree, also implemented in Mega, compute the estimated divergence time between species. Mesquite also provides tools to calibrate phylogenetic trees in geological times using fossil data. Ohnologs can also be used to estimate the divergence time between homologues resulting from whole genome duplications in vertebrates.
 
     Software      Features      Link        BayesTraits      Evolutionary analyses using   Bayesian inference      http://www.evolution.rdg.ac.uk/BayesTraitsV3.0.5/BayesTraitsV3.0.5.html        BEAST      Phylogenetic calibration      http://www.beast.community        Mega      Sequence alignment, model   selection, phylogenetic analysis (parsimony, distance methods)      https://www.megasoftware.net/        Mesquite      Comparative analyses and   statistics      http://www.mesquiteproject.org/        MrBayes      Bayesian phylogenetic   inference, ancestral states reconstruction, phylogenetic calibration…      http://nbisweden.github.io/MrBayes/        Ohnologs      Database of vertebrate   ohnologues, resulting from whole genome duplications      http://ohnologs.curie.fr/        Timetree      Tree calibration      http://www.timetree.org/   
 
SECTION: Working with phylogenies
5.6. Genome evolution

Evolutionary events, such as mutations, insertions, deletions, gene or whole genome duplications, genome reorganization, and genetic exchanges can be identified using phylogenetic trees in complement with genomics tools and databases. Here is a list of databases tools to study diverse aspects of genome evolution, including genome browsers of diverse lineages and tools for comparative genomics and evolutionary genomics:

 
     Software      Features      Link        BAR      Database of plant genes and proteins      http://bar.utoronto.ca/        Bgee      Gene expression patterns      https://bgee.org/        CAFE      Gene   family evolution      https://github.com/hahnlab/CAFE5        CoGE      Comparative   genomics analyses      https://genomevolution.org/coge/        Ensembl      Genome browser of vertebrates, includes tools for   identification of homology      https://www.ensembl.org/index.html        Entrez      Gene sequences and structures      https://www.ncbi.nlm.nih.gov/Web/Search/entrezfs.html        FlyBase      Genome and proteins of the model insect D.   melanogaster      https://flybase.org/        GenBank      Annotated DNA sequences      https://www.ncbi.nlm.nih.gov/genbank/        HGT-Finder      Horizontal   gene transfer finding      http://cys.bios.niu.edu/HGTFinder/   HGTFinder.tar.gz        Ohnologs      Database   of vertebrate ohnologues, resulting from whole genome duplications      http://ohnologs.curie.fr/        PomBase      Genes and proteins of the model yeast S. pombe      https://www.pombase.org/        TAIR      Genome and proteins of the model plant A.   thaliana      https://www.arabidopsis.org/        WormBase      Genome and proteins of the model nematode C.   elegans      https://wormbase.org//#012-34-5        Xenbase      Genome and proteins of the model amphibian X.   laevis      http://www.xenbase.org/entry/   
 
SECTION: Working with phylogenies
5.7. Population genetics

Genetic diversity can also be explored at the population level by analyzing polymorphism between members of the same species. Gene polymorphisms studies allele diversity within a population, including single nucleotide polymorphisms (SNP), indels, microsatellites or transposable elements. Mathematical models have been developed to describe polymorphism. Several programs are suitable for population genetics studies.

 
       Software         Features         Link            Arlequin         Population genetics   analyses         http://cmpg.unibe.ch/software/arlequin35/            DNAsp         Analysis of DNA   polymorphism         http://www.ub.edu/dnasp/             Genepop         Population genetics   analyses         https://genepop.curtin.edu.au/            SNiplay         SNP detection and other   population genetics analyses         https://sniplay.southgreen.fr/cgi-bin/home.cgi      
 
SECTION: Working with phylogenies
5.8. Study of protein structure and function evolution
Studying the functional evolution of proteins can require structure alignments, that can be realized by appropriate programs such as PyMol, and the mean distance in Å between homologous residues can be calculated.

Other programs allow to identify and study structures conservation between proteins and infer a structures from a protein sequence. These analyses and a phylogenetic tree of the protein families, together with the reconstruction of ancestral states, can facilitate the study of the evolution of protein functions within the family.


Here is a list of tools that can be used for analyses on protein structures in an evolutionary framework:

 
     Software      Features      Link        PyMol      3D visualization of   molecules      http://www.mesquiteproject.org/        I-Tasser      Protein structure   prediction      https://zhanglab.dcmb.med.umich.edu/I-TASSER/        Forsa      Protein structure   prediction      http://www.bo-protscience.fr/forsa/        HHPred      Protein structure   prediction      https://toolkit.tuebingen.mpg.de/tools/hhpred   
 
SECTION: Phylogenetic analysis
4.1. Option 1: Maximum parsimony

Maximum parsimony is a classic and simple method, that calculates the minimum number of evolutionary steps, including nucleotide insertions, deletions or substitutions, between species.

However, this method ignores hidden mutations and does not take into account branch lengths, potentially leading to long branch attraction, which is an incorrect clustering of unrelated taxa. Furthermore, it does not consider the possibility of hidden mutations, making it not relevant for distant taxa. While maximum parsimony is still used for morphological data, it is no longer considered relevant for molecular data.

SECTION: Phylogenetic analysis
4.2. Option 2: Distance methods

The Unweighted Pair Group Method with Arithmetic mean (UPGMA), Neighbor Joining (NJ), and Minimum Evolution (ME) are all based on the overall  molecular distance, defined by the number of differences between the sequences.

However, this method also ignores hidden mutations and is also subject to long branch attraction. These methods, in particular NJ and ME, are still often used in complement to probabilistic methods in scientific studies.
SECTION: Phylogenetic analysis
4.3. Option 3: Probabilistic methods

The strength of probabilistic methods is the use of specified models of molecular evolution. Probabilistic methods  take into account different mutation rates between sites to avoid mutation saturation. Nowadays, almost all studies of phylogenetic reconstruction use probabilistic methods. 

They include Maximum Likelihood (ML) and Bayesian inference (BI). ML calculates the probability of observing the data (in this case, the sequence alignment) under different explicit models of molecular evolution. ML aims to identify the best fit model by exploring multiple combinations of model parameters. BI evaluates the probability of each model of molecular evolution given the data. We recommend using different methods of phylogenetic reconstruction, including ML and BI.

In our example, we used Maximum likelihood to build the phylogenetic tree of the P53 family (including the p73, p63 and p53 proteins of different animal species), and FigTree for a graphical representation of the phylogenetic tree.


  

SECTION: Phylogenetic analysis
4.4. Model prediction

Probabilistic methods require a selection of the best model of molecular evolution for the data. Several models of nucleotide evolution exist, differing in their number of parameters like mutation rates between sites. Models of protein evolution also exist. A few programs can be used to calculate a criterion (AIC or BIC) to evaluate the likelihood of different published model for the alignment. Use one of them to select the best fit model for your alignment, which is the model with the lowest AIC or BIC criterion.

>If you are using probabilistic methods, use the aligned sequences and a model prediction tool to determine the best model of nucleotide or aminoacid substitution.

Here is a list of tools for selection of models of molecular evolution:
Model selectors are also implemented in software for evolutionary analysis such as Mega.
 
     Software      Features      Link        ModelTest / JModelTest      Nucleotide substitution   model selection      http://evomics.org/resources/software/molecular-evolution-software/modeltest/        ProtTest      Aminoacid substitution   model selection      https://github.com/ddarriba/prottest3        SMS      Nucleotide or aminoacid   model selection included in PhyML      http://www.atgc-montpellier.fr/sms/   
 
SECTION: Phylogenetic analysis
4.5. Tree rooting

Phylogenetic trees can be unrooted or rooted. Rooting a tree consists in identifying ancestral and derived states. This is useful to study the direction of the evolution and interpret the evolution of the studied taxa. 
Diverse methods have been developed to root phylogenetic trees:

-Including outgroups (taxa that do not belong to the studied ingroup but are closely related) in the analysis. It is recommended to choose two outgroups, one being more closely related to the ingroup than to the other outgroup. If outgroups are available, this method can be preferred.

-Midpoint rooting, which corresponds to setting the root at the mid-point of the longest branches.

-Molecular clock rooting, a method that assumes that evolution speed is constant between the sequences. Since evolution speed can vary lot between lineages, this method should be restricted to close species.