lecture24 bacterialenviro algenomics ericalm

8/3/2019 Lecture24 Bacterialenviro Algenomics Ericalm

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Genome Dynamics and

Environmental Adaptation in

Bacteria

Eric AlmDepts. Of Biological Eng. And Civil and

Environmental Eng., MITBroad Institute of MIT and Harvard

The Modern View of Bacterial

Genome Dynamics

Horizontal Gene Transfer is rampant

Closely related strains harbor lots of newly

acquired DNA HGT is a key mechanism for niche adaptation

native genes are insulated from dynamics at

the periphery of networks

Uptake of Foreign DNA

Transformation

Phage

Conjugation

Genomic islands as reservoirs of new

DNA

Colemann et al., Science 2006

How Common Is It?

Marine isolates of co-existing microdiversity

Large variation in genome

size among closely relatedstrains

Thompson et al., Science 2005

From: Lerat et al. (2005) PLoS Biol 3(5): e130

Genome Dynamics (HGT) at the

Periphery

Pal, Papp & Lercher,Nature Genetics, 2005.*horizontal gene transfer into the E. colilineage since itssplit from the Vibrio lineage.


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(gene family) - Principle # 2 & 3: More important proteins evolve

slowly. (e.g. Ribosome)

(genome) - Principle #1: Molecular clock. Rate of changedepends on mutation rate, population size, etc.

(gene,genome) - Principle #5: Positive or negative selection?

rt = (gene family) (genome) (gene,genome) t

Evolutionary Distance =

?

Overview of the Method

Seed possible orthologs:

Single copy ubiquitous COGs

Align and build trees

Compare to species phylogeny

KH-test

Reject outliers

Normalize against family

rate

and molecular clock

Read out terminal

branch lengths

~1000 gene families

744 gene families

rt = (gene family) (genome) (gene,genome) t

Evolutionary Distance =

=

Clock Explain Most Distance

Variation

Predicted branch length log2(t)

Observedbranchlengthlog2

(r

t)

-10 -5 0 5

-10

-5

0

5

Residual variation is an estimate of

What Can We Learn From

Residual Variation?

Noise? Environment-specific selective

pressures

Positive selection

Negative selection

Relaxed negative selection

Similar patterns in similar genes?

FAST

Lost ?

Fisher's exact test:Odds Ratio = 3.1,P = 2.4e-7

Odds Ratio = 0.55,P = 0.01

Fast: > 4.0

Slow: < 0.25

Outgroup

Negative Selection


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Selective Sweeps

P=0.05

Positive Selection?

Hypergeometric test for enrichment of COG functions in

fast/slow (top 10% of genes)


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Type II secretory pathway,prepilin signal

peptidase PulO and related peptidases

*PulO1989

Tfp pilus assembly protein, major pilin*PilA4969

Tfp pilus assembly protein, pilus retraction

ATPase

**PilT2805

Flagellar hook basal body protein*FliE1677

Flagellar basal body P-ring protein*FlgI1706

Flagellar basal body rod protein*FlgG4786

Flagellin-specific chaperone**FliS1516

Flagellar capping protein*FliD1345

Flagellar basal body protein*FlgB1815

Tfp pilus assembly protein**PilV4967

Flagellar biosynthesis protein*FliO3190

Flagellar basal body P-ring biosynthesis

protein

**FlgA1261

Flagellar basal body rod protein**FlgF4787

Flagellar biosynthesis/type III secretory

pathway chaperone

***FlgN3418

Flagellar biosynthesis pathway**FliR1684

Flagellar biosynthesis pathway**FlhB1377

YersiniaPhotor.E. coliNameCOG

Analysis of Patterns of Selection

Genomes/Experiments

Gene

s

Do correlations in between rows (genes) indicate

similar functional roles?

Selection Acts Coherently Across

Pathways/FunctionsAnalysis of Patterns of Selection

Genomes/Experiments

Gene

s

Do correlations in between columns (genomes)

indicate similar ecology?

Evolution of Evolutionary Rates

Correlation of across all

genes (orthologs) for eachpair of genomes

Deep-branching clades show

significant correlation in

genome-wide selectivepatterns

No Correlation With Phylogeny

Over Shorter Timespans


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EnvironmentEnvironment

Novel genes

retained in genome

gene evolutionary rate

variation


variation

Responses to Natural Selection

Native genes

HGT

A critique of the adaptionist programmeGould & Lewontin, 1979

Front legs a puzzle: how

Tyrannosaurus used its tiny front

legs is a scientific puzzle; theywere too short even to reach the

mouth. They may have been

used to help the animal rise from

a lying position.

- Explanatory information,

Museum of Science, Boston

c. 1979

EnvironmentEnvironment

Novel genes

retained in genome


variation


variation

Direct vs. Indirect Selection

HGT Direct selectionDirect

selection

Indirect selection

QuickTime andaTIFF(Uncompressed)decompressor

areneededtosee this picture.

Gene Content Influences Selection on

Genes?

0.020.11(v X time | g-c)

ns0.09(v X dist | g-c)


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ac groun : e own ass

Algorithm in Phylogenetic

Inference

What information ispassed from leaves to

parents?

sequence and score

Reconciliation proceeds by labeling each node ingene tree as HGT, Dup, or Speciation (loss isimplied)

Pass LCA (and score) of each subtree fromleaves to root

A Downpass Algorithm for Reconciliation

5

42

4414

5

42

441 4

Species Gene

1 2 3 4 1 2 41 4

The Algorithm

Calculate optimal scenario resulting in each possible LCA

1 2 3 4

1 1 2 4 4

0 3 33

3

3

1

Species tree

Gene tree

Downpass species tree

The Algorithm


1 2 3 4

1 1 2 4 4

Species tree

Gene tree

The Algorithm


1 2 3 4

1 1 2 4 4

Species tree

Gene tree

For all LCAs at parent:

For allLCAs at left child:

For all LCAs at right child:

O(ngns3)

Real Data

COG100: 30S ribosomal subunit proteinS11


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Species Species Gene

32 transfers!!

Even with a good species phylogeny, gene trees may havesignificant uncertainty

Bootstrap trees are a convenient but very limited sample ofdifferent topologies

Consensus trees discard information

Uncertainty in Gene Trees Love the Bootstrap

Dont fear the bootstrap -embrace it!

ReconcileALL bootstraps: For each subtree

reconciliation, check other

bootstraps for more

efficient reconciliation

The Idea The Idea


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The Idea

Reconciliation as a tool fortree construction

Incorporation of bootstrapsubtrees explores a very

large region of plausibletree space

Constructed tree is mostparsimonious, plausiblegene tree

Reconciliation meets construction

Each internal node of eachbootstrap has three

potential parents

For each node, threetables of potential LCAs

must be maintained

The Algorithm The Algorithm

Bootstrap trees1. Reconcile children

The Algorithm


2. Reconcile same node

in bootstrap trees

The Algorithm



in bootstrap trees 3. Return best answer

and merge tables


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The Algorithm



in bootstrap trees 3. Return best answer

and merge tables

4. Return table to parent

link subtrees across bootstraps Find path through all bootstrap trees optimizing

reconciliation

After all subtrees reconciled, select bestreconciliation to represent linked subtrees.

It Gets Messy

different entries in the same table can have different

subtree topologies!

5

42

4414

Iterate through all branches Root at branch with best reconciliation

Rooting trees is easy! Real Data Revisited!

COG100: 30S ribosomal subunit protein

S11

Species

Reconciliation

7 transfers

Reconciliation events


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Possible to reconcile gene andspecies trees efficiently

Uncertainty in gene trees can hamperreconciliation

Use bootstraps to sample reasonablesubsets of tree space

Are there 7 transfers for COG100? Wrong species phylogeny Need more bootstraps Gold-standard?

Next steps? All metabolic genes Co-evolution among genes with similar

function?

SummaryAcknowledgements

Jesse Shapiro (Evolutionary rates)

Lawrence David (Reconciliation)

Sonia Timberlake (Evolution of regulation)

Sean Clarke (HGT in the laboratory)

Arne materna (Experimental evolution)

lecture24 bacterialenviro algenomics ericalm

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