Intro to phylogenetic trees

Dictionary

• invariant sites: sites (bases at specific loci/positions) that are identical for all the analysed isolates/sequences.

• polymorphic sites: sites that have variation between the bases

• Informative sites: are polymorphic sites that support one grouping of taxa over another grouping. You can read a bit about this concept derived from parsimony analysis here, in the IQ-TREE documentation (search for “LIKELIHOOD MAPPING STATISTIC” in the Command reference document here)

Introduction

The basic underlying procedure for making a phylogeny is the following:

• There are multiple organisms for which we have DNA sequences. There should be at least three. We will call each organism a taxon for this tutorial.

• Next, we align the sequences that we have. The main assumption is that the sequences that we align are homologous, i.e, they represent the “same” DNA in all of our taxons. The theory is then here that any mutations that are present are due to evolutionary changes. We are assuming that there was one evolutionary ancestor, which then “split” into two child taxons. Any changes we see between the two taxons should then have evolved since the split.

• We then examine the changes between taxons to try to reconstruct how the splits can have happened over time. This is done by applying an evolutionary model to the changes seen.

IQ-TREE - a tool for making trees

IQ-TREE is a software that use maximum likelihood algorithm to infer phylogenies. You can read the article here, the software and documentation are hosted here.

• Input: The input for IQ-TREE is a multiple sequence alignment (including invariant sites and polymorphic sites) OR a MSA consisting of only variants/SNPs (polymorphic sites). If the latter is used, more information regarding base frequencies etc should be provided. More on tools on getting an MSA is described below.

• Output: The output from IQTREE is a tree, or a consensus tree if you used bootstrap to estimate branch support. It should be noted that even if we often display support on nodes this is actually branch support. You should always have an idea of how branches are supported, because you cannot interpret your phylogeny if you do not know how reliable it is. Bootstrap support will allow you to determine which groups of taxa you can consider as likely true and which ones are undetermined.

How to get a multiple sequence alignment

There are many tools that do this, and each of them as their advantages and disadvantages.

Which tool to choose depends how closely related your samples to be aligned are. You can have a fast estimate using FastANI (installed in saga)

• For very closely related sequences (≥97% nucleotide identity): use either ParSNP or snippy (using a close reference). ParSNP is a good candidate if you are very uncertain on what reference to use. You can then use one of your own sequences as a “reference”. For practical purposes that will be discussed later, use the longest of your assemblies. Note, in some communities there are fixed procedures, we recommend looking at them before choosing a procedure (e.g. for Klebsiella, Snippy is used with a fixed reference genome).

• For more distantly related sequences (some isolates < 95%) you might want to consider obtaining an alignment of shared genes, for isntance extracted from Roary pangenome analysis. You might also want to consider Mauve/progressive Mauve (a nice reading to understand some problems with MSA of whole genome data). If you cannot use a reference, you can e.g. extract concatenated polymorphic sites with ksnp3

This is however NOT an EXHAUSTIVE list of possibilities.

In all cases: you need to understand the hypothesis and main idea on how the alignment is done, because this will influence which steps you perform, including whether to remove possible recombination (ie. with Gubbins).

NOTE: Never use Gubbins to remove recombinant sequences on concatenated genes alignment, or on MSAs of only SNPs!.

Possible workflow overview

How to create a tree with iqtree?

• You start with a multiple sequence alignment (MSA) with the method of your choice.

• If this is a complete alignment, use Gubbins to detect and filter out recombinant regions (NB: do not do this if your multiple alignment is a concatenated alignment of gene sequences)

• Then you have basically 3 options that will decide how you run IQ-TREE:

  1. You want to run iqtree with the MSA with only polymorphic sites (SNPs). This is the fastest way to do a phylogenetic tree. To do this you will have to perform a correction of branch length with +ASC option. This is the least recommended method because it uses an algorithm to estimate a correction to be applied on branch lengths. This the least recommended method because some model use frequencies of ATCG to estimates probabilities of nucleotide substitutions. Those probabilities of nucleotide substitutions can depend on the amount of ATCG you have originally in your genome, and models assume that changes are leading to a “neutral sequence” where each base is represented at 25%” - this is called the “equilibrium frequencies”. Some models estimate the probabilities of substitution for each base, depending on what is in your sequences (empirical), and the sequence composition at equilibrium. Consequently, those evolutionary models that depend on estimating the empirical frequencies in your dataset cannot do that on variable sites only, because it might introduce a strong bias in base composition - indeed you might have base composition difference between your monomorphic sites and variable sites.

  2. If you want to only use the MSA with only polymorphic sites, but get a better quality phylogeny, you can use the IQ-TREE fconst option without the ACS option. With fconst you should provide the count of each nucleotide at the invariant sites (which is used to compute empirical base frequencies, as discussed above).

  As mentioned in IQ-TREE command reference manual:

  -fconst 10,20,15,40 will add 10 constant sites of all A, 20 constant sites of all C, 15 constant sites of all G and 40 constant sites of all T into the alignment.

  This method then requires an additional step: that you find the count for each base. This can be done with snp-sites. This method can help iqtree run faster, because it does not need to go through the sequences to find variants while also estimating the invariant frequencies for each site. This means so you can use it when you have a lot of sequences with many different snps, but the gain might be marginal. NB: you can read more about fconst and ACS here)

  3. you provide the multiple alignment with recombinant masked (using N) and let IQ-TREE find the frequency of invariant base and polymorphic sites - this is the easiest option (I think)