Plastid genomes

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Plastid genomes

• A small structure occurring in the cytoplasm of
  plant cells. The most important are the
  chloroplasts. Other plastids contain red, orange,
  and yellow pigments, giving color to petals and
  fruits, and some contain starch, oil, etc.,
  acting as storage organelles.
• 30 finished for 29 organisms
• http//megasun.bch.umontreal.ca/ogmp/projects/othe
  r/cp_list.html

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Chloroplast DNA (cpDNA)

• circular double-helix 20-80 copies per chl.
• sequences for
• gene expression (tRNA, rRNA, etc.)
• for photosynthesis (prot.)
• no recombination
• uniparental inheritance
• conservative evolution
• nuclear genetic code

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Genomes

• The whole genomes of over 800 organisms can be
  found in Entrez Genomes. The genomes represent
  both completely sequenced organisms and those for
  which sequencing is in progress. All three main
  domains of life - bacteria, archaea, and
  eukaryota - are represented, as well as many
  viruses.

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Genome miniaturization

• Use and disuse philosophy
• Mt Genome size following endosymbiosis
• Reclinomonas (62 protein encoding genes)
• Plastid Genome size in parasites
• Epiphagus (Beech drop)

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Phylogenetic distribution of gene loss from
chloroplast genomes. Colour keys designating
frequency of parallel gene losses are given at
top right. Numbers below species names indicate
the number of protein coding genes and ycfs in
the corresponding chloroplast genome. Numbers
above gene columns represent the number of genes
lost which are accounted for in the figure for
the given genome. The symbols for primary and
secondary symbiosis are indicated. Five genes
were excluded from gene-loss analysis for reasons
indicated at the lower left. Some highly
divergent proteins may have escaped detection
with BLAST searches. Functional, transferred
nuclear homologues of chloroplast origin are
indicted in white rectangles. In Pinus, four ndh
genes are completely missing (ndhA, ndhF, ndhG,
ndhJ), the other seven are pseudogenes23 and are
scored as losses here
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Genes are just one of many types of DNA sequences

• single copy genes
• multiple copy genes
• noncoding repetitive sequences (often, most of
  genome!)

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increase in Genome size

• Regional (particular sequence is multiplied)
• Gene duplication, unequal crossing over
• Global (entire genome or chromosome is
  duplicated)
• Polyploidization
• Trasposons

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Polyploidy

• Allopolyploidy the combination off genetically
  distinct chromosome sets
• Autopolyploidy multiplication of one basic set
  of chromosomes

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Tetraploidy

• Genome doubling
• Most common
• Is found in most organisms

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Survive only rarely

• Prolongation of cell division time
• Increase the volume of the nucleous
• Increase of chromosome disjuctions
• Genetic imbalance
• Interference with sexual differentiation

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Arabidopsis

• 115.4 megabase out of 125 MB
• Whole genome duplication, gene loss and lateral
  transfer from plastid

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Arabidopsis genes
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Appearance of genomes
What does 50 kb of sequence look like?

• One to many chromosomes
• Repeat sequences common in some genomes e.g. 35
  of human are transposable elements
• Gene structure varies no. and length of introns

repeat
Pseudogene
Intron-exon components of a gene
Human very few genes - repeats
Yeast many genes (25) few repeats
Maize mostly repeats
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Gene Duplication

• Partial or internal gene duplication
• Complete gene duplication
• Partial chromosomal duplication
• Polyploidy or genome duplication

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Gene Duplication

• Duplicative transposition
• Unequal crossing-over
• Replication slippage
• Gene amplification (rolling circle replication)

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Antifreeze glycoprotein gene

• Fish living in Antarctic Ocean have body temps
  -1.0 to -0.7 C.
• Freezing resistance is due to a protein in the
  blood that adsorbs small ice crystals and
  inhibits their growth

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Internal Gene Duplication
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5
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5
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Ancestral trypsinogen gene
Deletion
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6
5
3
Thr Ala Ala Gly
4 fold duplication addition of spacer sequence
1
6
5
3
Internal duplications addition of intron
sequence
Spacer Gly

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5
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6
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Antifreeze glycoprotein gene
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Theory of gene duplication
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Gene trees vs species trees
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Gene trees vs species trees
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Gene trees vs species trees
A
C
B
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1
2
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A
G
C
T
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Rates of Nucleotide Substitution

• Basic quantity in studying molecular evolution
• Among genes
• Within genes
• Among organisms
• Among codon positions or 2nd structure

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Different Gene Regions

• Coding regions
• Nondegenerate sites
• Twofold degenerate sites
• Fourfold degenerate sites
• Noncoding regions
• 5 3 untranslated regions
• Introns
• Psuedogenes

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Table 4.1 Rates of synonymous and nonsynonymous
nucleotide sustitutions ( standard errors) in
various mammalian protein-coding genesa
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Table 4.2 Rates of transitional and
transversional substitutions (per site per 109
years) at nondegenerate, twofold degenerate, and
fourfold degenerate codon sitesa
aThe rates are averages over the genes in Table
4.1.
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Noncoding regions
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Causes of Rate Variation

• Functional constraints

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Causes of Rate Variation

• Synonymous vs. Nonsynonymous rates
• Should be similar in rate (Ka/Ks1)
• Why not?
• Selection
• Advantageous
• Purifying

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Causes of Rate Variation
Variation within a gene
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Causes of rate Variation

• Variation among genes
• Rate of mutation
• The intensity of selection (1000 fold in Ks)
• Intensity of purifying selection (functional
  cont)
• Partial loss of function
• Relaxation of selection

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Nucleotide Substitution rates in Eukaryotic
Genomes
Genome
Ks rate
Relative Ks rate
Ka rate
Angiosperm mt 0.5 1 0.1 Angiosperm
cp single copy 1.5 3 0.2 inverted
Repeat 0.3 0.6 0.1 Angiosperm
nuc. 5.4 12 0.4 Mammalian
nuc. 2-8 4-16 0.5-1.3 Mammalian mt
20-50 40-100 2-3
Estimated rate of substitutions/site/10 9 years.
From Palmer, 1991
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Phylogenetic trees are about visualizing
evolutionary relationships
Nothing in Biology Makes Sense Except in the
Light of Evolution Theodosius
Dobzhansky (1900-1975)
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Trees

• Diagram consisting of branches and nodes

A
B
C
D
E
terminal node (leaf)
interior node (vertex)
split (bipartition) also written ABCDE or
portrayed ---
branch (edge)
root of tree
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Trees

• Species tree (how are my species related?)
• contains only one representative from each
  species
• when did speciation take place?
• all nodes indicate speciation events
• Gene tree (how are my genes related?)
• normally contains a number of genes from a single
  species
• nodes relate either to speciation or gene
  duplication events

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Cladogram
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Phenogram or Phylogram
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Number of unrooted trees
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Terms

• Clade A set of species which includes all of
  the species derived from a single common ancestor
• Monophyly
• Polyphyly
• Paraphyly

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Monophyletic
Paraphyletic
A A A B
B C
BRANCH
NODE
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Polyphyletic (Reptiles)
A A A B
B C
BRANCH
NODE
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Phylogeny Estimation
Camin-Sokal Parsimony Wagner Parsimony Fitch
Parsimony Transversion Parsimony Generalized
Parsimony
Transition/transversion bias Nucleotide
composition Among-site rate variation Synonymous/n
onsynonymous Relaxed clock models
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Distance methods

• Calculate the distance CORRECTING FOR MULTIPLE
  HITS
• The Distance Matrix
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• Rat 0.0000 0.0646 0.1434 0.1456
  0.3213 0.3213 0.7018
• Mouse 0.0646 0.0000 0.1716 0.1743
  0.3253 0.3743 0.7673
• Rabbit 0.1434 0.1716 0.0000 0.0649
  0.3582 0.3385 0.7522
• Human 0.1456 0.1743 0.0649 0.0000
  0.3299 0.2915 0.7116
• Oppossum 0.3213 0.3253 0.3582 0.3299
  0.0000 0.3279 0.6653
• Chicken 0.3213 0.3743 0.3385 0.2915
  0.3279 0.0000 0.5721
• Frog 0.7018 0.7673 0.7522 0.7116
  0.6653 0.5721 0.0000

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Distance methods

• Normally fast and simple
• e.g. UPGMA, Neighbour Joining, Minimum Evolution,
  Fitch-Margoliash

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Correction for multiple hits

• Only differences can be observed directly not
  distances
• All distance methods rely (crucially) on this
• A great many models used for nucleotide sequences
  (e.g. JC, K2P, HKY, Rev, Maximum Likelihood)
• aa sequences are infinitely more complicated!
• Accuracy falls off drastically for highly
  divergent sequences

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Maximum Parsimony

• Occams Razor
• Entia non sunt multiplicanda praeter
  necessitatem.
• William of Occam (1300-1349)

The best tree is the one which requires the least
number of substitutions
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Maximum Likelihood

• Require a model of evolution
• Each substitution has an associated likelihood
  given a branch of a certain length
• A function is derived to represent the likelihood
  of the data given the tree, branch-lengths and
  additional parameters

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The Likelihood Criterion

• Given two trees, the one maximizing the
  probability of the observed data is best
• Site likelihood probability of the data for one
  site conditional on the assumed model of
  evolution
• Site log-likelihood natural logarithm of the site
  likelihood (often abbreviated lnL)
• Tree score sum of site log-likelihoods (term
  score also general term for the derivative of the
  lnL)
• Unlike parsimony tree lengths, log-likelihoods
  are comparable across models as well as trees

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Models can be made more parameter rich to
increase their realism

• The most common additional parameters are
• A correction to allow different substitution
  rates for each type of nucleotide change
• A correction for the proportion of sites which
  are unable to change
• A correction for variable site rates at those
  sites which can change
• The values of the additional parameters will be
  estimated in the process (e.g. PAUP)

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A gamma distribution can be used to model site
rate heterogeneity
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Comparison of methods

• Inconsistency
• Neighbour Joining (NJ) is very fast but depends
  on accurate estimates of distance. This is more
  difficult with very divergent data
• Parsimony suffers from Long Branch Attraction.
  This may be a particular problem for very
  divergent data
• NJ can suffer from Long Branch Attraction
• Parsimony is also computationally intensive
• Codon usage bias can be a problem for MP and NJ
• Maximum Likelihood is the most reliable but
  depends on the choice of model and is very slow
• Methods may be combined

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How confident am I that my tree is correct?

• Bootstrap values
• Bootstrapping is a statistical technique that
  can use random resampling of data to determine
  sampling error for tree topologies

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Bootstrapping phylogenies

• Characters are resampled with replacement to
  create many bootstrap replicate data sets
• Each bootstrap replicate data set is analysed
  (e.g. with parsimony, distance, ML etc.)
• Agreement among the resulting trees is summarized
  with a majority-rule consensus tree
• Frequencies of occurrence of groups, bootstrap
  proportions (BPs), are a measure of support for
  those groups

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Bootstrapping - an example
Ciliate SSUrDNA - parsimony bootstrap
Ochromonas (1)
Symbiodinium (2)
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Prorocentrum (3)
Euplotes (8)
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Tetrahymena (9)
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Loxodes (4)
100
Tracheloraphis (5)
100
Spirostomum (6)
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Gruberia (7)
Majority-rule consensus
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Bootstrapping
Majority-rule consensus (with minority components)
Wim de Grave et al. Fiocruz bioinformatics
training course
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Bootstrap - interpretation

• Bootstrapping is a very valuable and widely used
  technique (it is demanded by some journals)
• BPs give an idea of how likely a given branch
  would be to be unaffected if additional data,
  with the same distribution, became available
• BPs are not the same as confidence intervals.
  There is no simple mapping between bootstrap
  values and confidence intervals. There is no
  agreement about what constitutes a good
  bootstrap value (gt 70, gt 80, gt 85 ????)
• Some theoretical work indicates that BPs can be a
  conservative estimate of confidence intervals
• If the estimated tree is inconsistent all the
  bootstraps in the world wont help you..