Evolutionary Trees

Question 1

Mitochondrial DNA

Answer 1

Powerhouse of the cell
Originally independent organism captured by eukaryotic cell
Contain their own DNA
Inherited through the mother's ova
Reproduce asexually

Question 2

Asexual Inheritance - Reasons for a common ancestor

Answer 2

Easier to study

Populations will share a common ancestor because of natural coalescence and going through a bottleneck(leaving Africa)
Natural coalescence happens by chance but is enhanced by selection

Far enough back in time and asexual population will have a common ancestor

Question 3

Cross-Breeding (Hominids)

Answer 3

Some cross-breeding between modern man and other hominids

Numbers not large and due to coalescence time being small, Neanderthal mitochondrial DNA vanished

Question 4

DNA

Answer 4

Evolves sexually

Question 5

Selfish Gene

Answer 5

Cannot build tree of life as you inherit from two parents
Each gene can be mapped to its own ancestral tree (assuming no crossover disruption)
Lots of different genes which come from different origins survive (different fitness)
Humans have DNA from Neanderthals and other hominids which have been selected for

Question 6

Horizontal Gene Transfer

Answer 6

Bacteria and Archaea reproduce asexually
Exchange of plasmids (Loops of DNA)
Lead to antibiotic resistance

Doesn’t create a tree shape

Question 7

Modelling evolution at species level

Answer 7

Cross-breeds have reduced fertility (1 sex is inviable/sterile)
Lack of significant cross-breeding allows for evolution to be modelled at the species level by a tree

Question 8

Importance of modelling evolution

Answer 8

Understanding and controlling diseases like HIV which evolved over decades(HIV evolves asexually so we can build an evolution tree)
Understanding the development of cancer (disrupted genome -> tumours -> cells accumulate mutations which replicate faster than other cells) Normally cells in higher organisms reproduce asexually

Question 9

Orthologues

Answer 9

Genes which diverge due to speciation

Useful for understanding the relationships between species

Question 10

Paralogues

Answer 10

Genes which diverge due to gene duplication

Interested in different types of haemoglobins

Question 11

Three camps of evolutionary trees

Answer 11

Evolutionary Taxonomy
Phenetics or numerical taxonomy
Cladistics

Question 12

Modern approaches for building evolutionary trees

Answer 12

aka phylogenetic trees
Need some measure of evolutionary distance
Traditionally use of morphological features, now use sequence edit distance
Many plausible trees which can explain the data
All current algorithms are compromises for finding the best evolutionary trees

Question 13

Molecular clock

Answer 13

Use of accumulation of mutations to see when species separated.
Mutations random and strongly affected by selection pressure. Can also involve a duplication of a stretch of DNA
Need to use as large a sequence as possible

Question 14

Two types of evolutionary trees

Answer 14

Distance-based trees

Sequence based trees

Question 15

Distance based trees

Answer 15

Table of distances between species and we wish to find a tree explaining these distances

Question 16

Sequence based trees

Answer 16

Given a set of sequences and we want to find a tree with the minimum number of mutations per link (maximum parsimony) which explains the data

Question 17

Perfect molecular clock

Answer 17

Evolutionary trees to existing species will have an ultrametric structure
For any three nodes, with 3 distances, two of the distances will be identical and one will be smaller than these (binary trees)

Question 18

Issues with ultrametric trees

Answer 18

Cannot accurately measure divergence time, unlikely that the table of distances can be modelled with an ultrametric tree

Question 19

UPGMA

Answer 19

Unweighted Pair Group Method using Arithmetic averaging
Build an ultrametric tree using a clustering (from the leaves upwards)
Select two closest subtrees, remove all nodes and replace the two joined subtree with a new subtree

Question 20

Issues with UPGMA

Answer 20

UPGMA imposes ultrametric structure (assumes mutations accumulate at a constant rate)
If distances aren’t ultrametric then UPGMA can give poor trees
Even though some organisms are quite close, can be distorted by the tree

Question 21

Assumptions for UPGMA

Answer 21

Assumes mutations accumlate at a constant rate for an ultrametric structure
In reality mutations experience selection and are often “non-trivial” (genome copy mutations)

Question 22

“junk” DNA

Answer 22

Stretches of DNA where mutations appear to accumulate at a reasonable constant rate
Not well studied or stable regions

Question 23

Additivity of Distances

Answer 23

Ultrametricity is a very strong condition dependent on a perfect molecular clock
Additivity of Distances is a less strong condition
Doesn’t assume constant mutation rate, only that they do accumulate (Distances consistent with an evolutionary graph)
True if all mutations independent of each other

Question 24

Broken Additivity

Answer 24

Additivity assumes mutations just accumulate
Backward mutations or two species finding the same mutation break additivity
For additivity to be used, need to look at large parts of the genome so not affected by chance events like backward mutations

Question 25

Maximum Parsimony Trees

Answer 25

Explain evolutionary history of set of sequences with as few mutations as possible
Most commonly used trees (sequences not distances)

Question 26

Algorithms for Parsimony

Answer 26

Given aligned protein sequences
No efficient algorithm
Check all possible trees (branch & bound)
Feasible for moderate number of sequences (<50)
Need to cost and iterate through each tree

Question 27

Parsimony Problem

Answer 27

Many different possible trees with different costs for a set of sequences
Finding tree with the smallest cost

Question 28

Enumeration of trees

Answer 28

Method for systematically trying out all possible trees for the set of sequences

Question 29

Branch & Bound

Answer 29

Any tree generated from a partial tree will have at least as high a cost as the partial tree
If the cost of the partial tree is >= the best cost so far, no point continuing further
Reduces search space

Question 30

Assessing trees (Maximum Parsimony)

Answer 30

Difficult to assess directly
Use of bootstrapping (Trying different orders/duplicating certain items)
See if the maximum parsimony trees found look similar

Question 31

Hein Algorithm

Answer 31

To score trees, we want to know the alignment
To do an alignment, we want to find related sequences
Can do both together but is very involved