This document provides an overview of phylogeny and constructing phylogenetic trees. It defines phylogeny as models of evolutionary relationships among species based on sequence similarities, often illustrated as phylogenetic trees. It describes how to construct phylogenetic trees, including choosing marker genes, aligning sequences, calculating evolutionary distances, performing phylogenetic analysis, and dealing with complexities like long-branch attraction. It also discusses species definitions in microbes and operational species concepts based on metrics like 16S rRNA sequence identity.

1. Phylogeny
MICROBIO 590B Bioinformatics Lab: Bacterial Genomics
Professor Kristen DeAngelis
UMass Amherst
Fall 2022
1

2. Lecture Learning Goals
• Define phylogeny, and describe what a phylogenetic tree can reveal
about the taxa that they model.
• Explain how phylogenetic methods can allow us to make inferences
about groups of organisms and ancestors
• Describe how to construct a phylogenetic tree, and the complexities
that create mistakes.
• Contrast the different phylogenetic marker genes or concatenations
of genes that are available depending on the sequencing technology.
• Define the species concept for microbes.
• Make a phylogenetic tree.
2

3. Phylogeny
• Phylogeny is a model of
evolutionary relationships
among species based on
sequence similarities.
• Phylogeny may also refer to a
phylogenetic tree, the
illustration of these
relationships.
Woesian ToL: Pace NR, Science 1997
3

4. Read trees like mobiles
4

5. Read trees like mobiles
5
In a tree like this, these blue branches have lengths that are
meaningful. Their distance should be described by the
value of changes in a scale bar.
In a tree like this, these red distances have lengths that are
NOT meaningful. They are spacers whose distance are only
meant to make room for labels or pictures.

6. Descent with modifica;on
6

7. Who was the last universal common ancestor?

8. 8
The root of the ToL represents the
last universal common ancestor

9. The root of the ToL represents the
last universal common ancestor
• One cannot rely on nucleotide gene sequences alone because these
would have mutated beyond recognition
• Amino acid sequences mutate more slowly because neutral
mutations leave the amino acid sequence fixed
• The tertiary folded structure of a protein is even more strongly
conserved than the secondary structure
9

10. Sequence homology
• Homologous genes have a shared ancestry.
• Orthologs arise because of a speciation event.
• Paralogs arise because of duplication event.
10

11. Paralogs are used to root the ToL
• Elongation Factors duplicated prior to divergence of the three
Domains
• One gene tree can be rooted with the other gene
• Both trees yield the same relationship and are rooted in the
same location.
11

12. Root the tree of life using paralogs
• The genes for the protein synthesis elongation factors Tu
(EF-Tu) and G (EF-G) are the products of an ancient gene
duplication, which appears to predate the divergence of all
extant organismal lineages.
• Most phylogenetic methods place the root of the ToL in the
Bacteria
• A combined data set of EF-Tu and EF-G sequences favors
placement of the eukaryotes within the Archaea, as the
sister group to the Crenarchaeota
12
Baladuf, Palmer, & Doolittle, 1996

13. Protein-based models of evolution
13
Kim and Caetano-Anollés BMC Evolutionary Biology 2011

14. Protein-based models of evolu7on
• Traits here are proteins, NOT DNA sequence
• Based on 420 modern organisms, looking for structures
that were common to all.
• 5 to 11 per cent were universal-- conserved enough to have
originated in LUCA
• This perspective gives us new information about LUCA
• LUCA had enzymes to break down and extract energy from
nutrients, and some protein-making equipment
• LUCA lacked the enzymes for making and reading DNA
molecules
14

15. Bacteria
Archaea Eukaryotes
Bacteria Archaea Eukaryotes
15
The root moves depending on what trait you use!

16. The root moves depending on whether you use
nucleic acids or protein!
• RNA sequence-based rooting of the
tree of life puts the root within the
Bacteria.
• usually derived from analyses of the
sequence of ancient gene paralogs e.g.,
ATPases, elongation factors
• Proteomic analyses for many proteins
puts the root of the tree of life within
the Archaea.
• Archaeal rooting has been observed for
phylogenetic analyses of tRNA, 5S, &
Rnase P
16
Bacteria
Archaea Eukaryotes
Bacteria Archaea Eukaryotes

17. The last universal common ancestor, aka LUCA
• 4 – 3.5 Ga (Ga = 109 years ago)
• Almost certainly a dispersed
population of variable cells
• Features
• DNA, the universal code, and most genes
• Transcription and RNA polymerase
• RNAs of all kinds
• Translation and translational machinery
• Most proteins and metabolisms
• Membrane and cellular structure
17
Bacteria
Archaea Eukaryotes
Bacteria Archaea Eukaryotes
LUCA
also LUCA !

18. So you’re making a phylogenetic tree…
• Assume you have chosen which species to analyze
• (1) Decide which gene to use …
• Ribosomal RNA genes
• A concatenaZon of single copy housekeeping genes
18

19. SSU ribosomal RNA
gene is a common
phylogenetic marker
+ Short, only 1500 base pairs
+ InformaZon-dense because it
is a non-coding, structural RNA
+ EssenZal for life so probably
not horizontally transferred
- MulZple copies per genome
- Cannot resolve close
relaZonships
19
Xie, Tian, Qin, Bu, 2008

20. 20

21. Sensitivity and correlation of hypervariable regions
in 16S rRNA genes in phylogenetic analysis
• Distance between trees based
on sub-regions (V2 through
V8) and trees based on all the
sub-regions (VT)
• Sequence analyses including
V4 are favored because of this
21
Yang, Wang, Qian. BMC Bioinformatics, 2016

22. So you’re making a phylogene;c tree…
• (2) Align the gene sequences
22

23. So you’re making a phylogene;c tree…
• (2) Align the gene sequences
• We want evolutionary distance but it cannot be directly
measured, so it must be estimated
• Each vertical column in the alignment is a “trait” in
calculating the distance matrix
• Distance matrix is based on observed (measurable)
differences, but we assume parsimony
• There can be more than one evolutionary change at a single position
(e.g., A à G à U)
• Positions can change and change back (A à G à A)
23

24. So you’re making a phylogenetic tree…
• (3) Make an evolutionary distance matrix based on sequence
similarity, using Jukes-Cantor Method.
24

25. So you’re making a phylogenetic tree…
• Jukes Cantor method relates sequence similarity to
evolutionary distance
• If all sequences are the same, distance is zero
• Distances increase as sequence similarity decreases, which
means that one or two bases difference does not change
the distance much
• The lowest sequence similarity is about 0.25 because all
sequences are about 25% similar by chance; there are 4
bases in the genetic code so the chance that one base will
match another is 1 in 4
25

26. So you’re making a phylogenetic tree…
• (4) Perform phylogeneZc analysis.
• This is an example of the neighbor
joining method
26
Distance Matrix (%)

27. So you’re making a phylogene;c tree…
• How can you determine the branch lengths?
• In other words, you need to place the node “u”, which defines
a common ancestor
• You know how far apart a & b are from each other
• You know how far apart a is from something else, say c, so
measure b from c and you can estimate where node u should
be
• (5, optional) Create a visualization of the tree.
• Let’s look at some nice trees …
27

28. So you’re making a phylogene;c tree…
• (4) Perform phylogenetic analysis.
28
Yang & Rannala, Nat Rev Gen, 2012

29. So you’re making a phylogenetic tree…
• (4) Perform phylogeneZc analysis.
29
Yang & Rannala, Nat Rev Gen, 2012

30. Some nice trees: Metatranscriptomic reconstruc1on reveals
RNA viruses with the poten1al to shape carbon cycling in soil
30
Starr et al., 2019

31. A nice tree: bacterial
isolates in the our lab
culture collection
The colored branches are unique
for each taxonomy Family, and the
colored labels refer to strains that
belong to the same Genus.
The outer blue/red indicates if
each strain is from the heated or
control plots.
And the stars mean we have a
genome sequenced.
Choudoir, unpublished

32. So you’re
making a
phylogenetic
tree…
• There are many
(free) programs
to make trees…
https://evolution.genetics.
washington.edu/phylip/soft
ware.html
32
Yang & Rannala, Nat Rev Gen, 2012

33. Tree Construc;on Complexi;es
1. Choice of substitution model
2. GC bias
3. Choice of tree-making algorithm
4. Long-branch attraction
5. Bootstrapping
33

34. Choice of subs;tu;on model
• Pairwise sequence distances are calculated assuming a Markov chain model of
nucleotide substitution. Several commonly used models are illustrated in FIG. 1.
34
Yang & Rannala, Nature Reviews GeneYcs, 2012

35. 35
“GC bias”
• The more GC-rich a
region is, the higher the
recombination rates.
• That means that GC-rich
regions, or GC-rich
genomes, evolve faster
naturally.
• Including High GC gram
positives (like
Actinobacteria) in the
same tree as Low GC
gram positives (like
Firmicutes) can be
misleading.

36. Choice of tree algorithm can affect tree structure
• Neighbor-joining starts with a radial tree and joins
neighbors
• Parsimony makes a bunch of trees and find the one
that is the most simple, usually based on the fewest
mutaWons
• Maximum likelihood trees are based on probability
• the best & most computaZonally intensive
• Bayesian inference starts with random tree structure
& random parameters, then iterates unWl an
“opWmal” tree is found
36

37. Long-branch attraction
• Very long branches can someZmes cluster arZficially
• Usually due to bad sequence, poor alignment, or not enough Zps
• The erroneous new phylogeny implies a common ancestor and
can result in different rates of evoluZon
37

38. Long-branch aPrac;on
• …
38
Yang & Rannala, Nature Reviews GeneYcs, 2012

39. Long-branch attraction in theory and in practice
• Panels a and b show the four-species case by Felsenstein. If the correct tree (T in a) has
two long branches separated by a short internal branch, parsimony (as well as model-
based methods such as likelihood and Bayesian methods under simplistic models) tends
to recover a wrong tree (T2 in b), in which the two long branches are grouped together.
• Panels c and d show a similar phenomenon in a real data set, concerning the phylogeny
of seed plants. The Gnetales is a morphologically and ecologically diverse group of
Gymnosperms including three genera (Ephedra, Gnetum and Welwitschia), but its
phylogenetic position has been controversial.
• Maximum likelihood analysis of 56 chloroplast proteins produced the GneCup tree (d), in
which the Gnetales are grouped with Cupressophyta, apparently owing to a long-branch
attraction artefact.
• However, the Gnepine tree (c), in which the Gnetales joins the Pinaceae, was inferred by
excluding the fastest-evolving 18 proteins as well as three proteins (namely, psbC, rpl2
and rps7) that had experienced many parallel substitutions between the Cryptomeria
branch and the branch ancestral to the Gnetales. The Gnepine tree (c) is also supported
by two proteins from the nuclear genome and appears to be the correct tree.
• Branch lengths and bootstrap proportions are all calculated using RAxML.
39
Yang & Rannala, Nature Reviews Genetics, 2012

40. Bootstrapping
• Random sampling with
replacement to create new
trees
• A measure of confidence in
your sequence alignment
• Numbers are from 0-100, with
100 being perfect confidence
40

41. Bootstrapping
• …
41

42. What is a species?
The following terms represent similar concepts and are sometimes used
interchangeably.
• Species = related organisms that share common characteristics and are capable of
interbreeding
• Taxa = a group of one or more populations of an organism, usually with a name and rank,
and seen by taxonomists to form a unit
• Operational taxonomic unit = Usually defined as the number of distinct 16S ribosomal
RNA sequences (or distinct phylogenetic marker genes or concatenations) at a certain
cut-off level of sequence diversity.
• Lineage = temporal series of populations, organisms, cells, or genes connected by a
continuous line of descent from ancestor to descendant, determined by the techniques
of molecular systematics.
• Strain = a genetic variant, a subtype or a culture within a biological species
42

43. What is a species?
43
The species concept in microbes is hotly debated.
• ‘‘A species could be described as a monophyleZc and genomically coherent
cluster of individual organisms that show a high degree of overall similarity in
many independent characterisZcs, and is diagnosable by a discriminaZve
phenotypic property.’’ (ReF. 9)
• ‘‘Species are considered to be an irreducible cluster of organisms diagnosably
different from other such clusters and within which there is a parental palern of
ancestry and descent.’’ (ReF. 82)
• ‘‘A species is a group of individuals where the observed lateral gene transfer
within the group is much greater than the transfer between groups.’’ (ReF. 83)
• ‘‘Microbes ... do not form natural clusters to which the term “species” can be
universally and sensibly applied.’’ (ReF. 84)
• ‘‘Species are (segments of) metapopulaZon lineages.’’ (ReF. 7)
Achtman & Wagner, Nat. Rev. Micro. 2008

44. 44
Achtman & Wagner, Nat. Rev. Micro. 2008
Species definition should be guided by a method-free
species concept based on cohesive evolutionary forces

45. Species defini7ons
• Five types of ecotype models have been described in detail. E1 and E2 represent ecotypes; G1 and G2
represent genotypes. Colours reflect genetic ancestry. Solid lines indicate extant lineages that exist today,
whereas dotted lines indicate extinct lineages that have disappeared owing to overgrowth during episodes
of periodic selection.
45
Achtman & Wagner, Nat. Rev. Micro. 2008

46. Species definitions
• …
46
Achtman & Wagner, Nat. Rev. Micro. 2008
Salmonella enterica subsp.
enterica serovar Typhi
Yersinia pestis Neisseria meningitidis
serogroup A subgroup III

47. Opera;onal species defini;ons
• pairwise DNA re-association values are ≥70% in DNA–DNA
hybridization experiments under standardized conditions and their
∆Tm (melting temperature) is ≤5°C
• 16S ribosomal RNAs (rRNAs) that are ≤98.7% identical are always
members of different species
• strong differences in rRNA correlate with <70% DNA–DNA similarity
• distinct species have been occasionally described with 16S rRNAs that are
>98.7% identical
• multilocus sequence analysis (MLSA) based on multiple (typically 6–8)
protein-coding core genes
• average nucleotide identity (ANI) of all orthologous genes
• …
47

48. NCBI BLAST 16S ribosomal RNA genes
>GP101
CGGCAGCGGGGGTAGCTTGCTACTTGCCGGCGAGTGGCGAACGGGTGAGTAATACATCGGAACGTGCCCTGTAGTGGGGG
ATAACTAGTCGAAAGACTGGCTAATACCGCATACGACCTGAGGGTGAAAGTGGGGGACCGCAAGGCCTCATGCTATAGGAG
CGGCCGATGTCTGATTAGCTAGTTGGTGGGGTAAAGGCCCACCAAGGCGACGATCAGTAGCTGGTCTGAGAGGACGATCAG
CCACACTGGGACTGAGACACGGCCCAGACTCCTACGGGAGGCAGCAGTGGGGAATTTTGGACAATGGGGGCAACCCTGAT
CCAGCAATGCCGCGTGTGTGAAGAAGGCCTTCGGGTTGTAAAGCACTTTTGTCCGGAAAGAAATCGCTTCGGTTAATACCTG
GAGTGGATGACGGTACCGGAAGAATAAGGACCGGCTAACTACGTGCCAGCAGCCGCGGTAATACGTAGGGTCCAAGCGTTA
ATCGGAATTACTGGGCGTAAAGCGTGCGCAGGCGGTTGTGCAAGACCGATGTGAAATCCCCGGGCTTAACCTGGGAATTGC
ATTGGTGACTGCACGGCTAGAGTGTGTCAGAGGGGGGTAGAATTCCACGTGTAGCAGTGAAATGCGTAGAGATGTGGAGG
AATACCGATGGCGAAGGCAGCCCCCTGGGATAACACTGACGCTCATGCACGAAAGCGTGGGGAGCAAACAGGATTAGATAC
CCTGGTAGTCCACGCCCTAAACGATGTCAACTAGTTGTTGGGGATTCATTTTCTTAGTAACGTAGCTAACGCGTGAAGTTGAC
CGCCTGGGGAGTACGGTCGCAAGATTAAAACTCAAAGGAATTGACGGGGACCCGCACAAGCGGTGGATGATGTGGATTAA
TTCGATGCAACGCGAAAAACCTTACCTACCCTTGACATGCCACTAACGAAGCAGAGATGCATTAGGTGCTCGAAAGAGAAA
GTGGACACAGGTGCTGCATGGCTGTCGTCAGCTCGTGTCGTGAGATGTTGGGTTAAGTCCCGCAACGAGCGCAACCCTTGT
CTCTAGTTGCTACGAAAGGGCACTCTAGAGAGACTGCCGGTGACAAACCGGAGGAAGGTGGGGATGACGTCAAGTCCTCA
TGGCCCTTATGGGTAGGGCTTCACACGTCATACAATGGTGCATACAGAGGGTTGCCAAGCCGCGAGGTGGAGCTAATCCCA
GAAAATGCATCGTAGTCCGGATCGTAGTCTGCAACTCGACTACGTGAAGCTGGAATCGCTAGTAATCGCGGATCAGCATGCC
GCGGTGAATACGTTCCCGGGTCTTGTACACACCGCCCGTCACACCTTGGGAGTGGGCTTTACCAGAAGTAGTTAGCCTAACC
GCAAGGAGGGCGATACCACGTAGT
48

49. NCBI BLAST 16S ribosomal RNA genes
• The Basic Local
Alignment Search Tool (BLAST)
finds regions of local similarity
between sequences.
• Default database is ‘nr/nt’, the
non-redundant nucleotide
collection
• Update date: 2021/08/01
• Number of sequences:
72,191,653
• For phylogeny & taxonomy, we
want to use the ribosomal RNA
(rRNA) intergenic transcribed
spacer (ITS) database
• 21,856 sequences
49

50. What if we cannot detect the usual phylogenetic
marker genes?
• Inferring phylogeny for genomes newly discovered from
metagenomes is useful for identification (aka genotyping)
• 16S ribosomal RNA genes are the “gold standard,” but sometimes
resist assembly due to high degrees of sequence similarity across
lineages
• Any shared genomic trait is a candidate for a phylogenetic marker
• Single copy marker genes
50

51. Single copy marker genes
• ezTree is a program that can extract single
copy genes for phylogeneZc analysis
51
Wu, BMC Genomics. 2018

52. Taxonomy versus phylogeny
• Taxonomy bins organization based on classified levels
• Linnaean classification is still used
• 97% identity of the 16S rRNA gene or greater are the same species
• 95% identity of the 16S rRNA gene or greater are the same genus
• THERE ARE MANY EXCEPTIONS!
• Linnaean classification
• Kingdom
• Phylum
• Class
• Order
• Family
• Genus
• Species
52

53. Linnaeus and Race
• Linnaeus’ work forms one of the 18th-century roots of modern scientific racism.
• Linnaeus was the first naturalist to classify man as an animal in Systema naturae in 1735
• ’man’ was divided into four ”varieties” (he did not use the word ”race”)
• based on the then known four continents of the world: Europe, America, Asia and Africa
• By the 10th edition, he expanded this idea to add the four ‘humours’ or temperaments, as
well as a hierarchy of the ‘varieties’
53
https://www.linnean.org/learning/who-was-linnaeus/linnaeus-and-race

54. Taxonomy via NCBI
• Order
• Family
• Genus
• Species
• Subspecies
54

55. Genome Taxonomy Database (GTDB)
• Phylogenomic classificaWon based on a set of conserved proteins
55

56. Insert Genome into Species Tree
• species tree using a set of 49 core, universal genes defined by COG
(Clusters of Orthologous Groups) gene families
• COGs domains used in the estimate of relatedness are listed on the
website. For example:
• GTPase, tRNA synthetases, Ribosomal proteins, and other proteins involved in
Translation, ribosomal structure and biogenesis
• Nucleotide transport and metabolism
• 3-phosphoglycerate kinase [Carbohydrate transport and metabolism]
56

57. Lecture Learning Goals
• Define phylogeny, and describe what a phylogenetic tree can reveal
about the taxa that they model.
• Explain how phylogenetic methods can allow us to make inferences
about groups of organisms and ancestors
• Describe how to construct a phylogenetic tree, and the complexities
that create mistakes.
• Contrast the different phylogenetic marker genes or concatenations
of genes that are available depending on the sequencing technology.
• Define the species concept for microbes.
• Make a phylogenetic tree.
57

58. 58