Download Gen660_Lecture3A_Ortho

Orthology & Paralogy (etc. etc.)
Orthologs: Two genes, each from a different species, that descended from
a single common ancestral gene
(note no regard to function! and does NOT require one-to-one relationships)
Paralogs: Two or more genes, often thought of as within the same species,
that originated by one or more gene duplication events
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Ancestral
species
A
B
C
D
SPECIES TREE
Ancestral
Gene 1
E
A1
B1 C1
D1
E1
GENE TREE
Clear case of orthology: each gene 1 in each species is an ortholog
Of the others - all descended from a single common ancestor
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Ancestral
species
Ancestral
Gene 1
Gene duplication along
this species branch
A
B
C
D
SPECIES TREE
E
A1
B1 C1 C2 D1 D2 E1
GENE TREE
Duplication event along branch to species C & D
C1 and C2 are paralogs, D1 and D2 are paralogs
What about A1 to C1? To C2?
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Orthology & Paralogy (etc. etc.)
Orthologs: Two genes, each from a different species, that descended from
a single common ancestral gene
(note no regard to function!)
Paralogs: Two or more genes, within the same species, that originated
by one or more gene duplication events
Also now many subtle variants:
Outparalogs: cross-species paralogs (i.e. gene duplication BEFORE speciation)
Inparalogs: lineage-specific duplication (i.e. duplication AFTER speciation)
Ohnolog: duplicates originating from a whole-genome duplication (WGD)
Xenolog: genes related by horizontal gene transfer between species
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Phenology vs. Phylogeny
Phenology: tree based on
similarity of characteristics
1. Align protein & score alignment
(# of identical and ‘conserved’ amino acids)
2.
Phylogeny: tree based
on evolutionary history
1.
Requires inferring history
across the species
Build a tree based on sequence similarity
A1
B1 C1 C2
A1 is more similar to C1 than C2 A1 & C1 are likely (* but not guaranteed!)
more similar functionally
A1
B1 C1 C2
But historically, A1 is
equally distant to C1 and C2
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Methods of orthology prediction
1. Reciprocal best-BLAST hits (RBH): simplest method
Species A
Gene A1
Gene A2
1.
2.
3.
Gene B1
Gene B2
...
...
Gene An
Species B
Gene Bn
BLAST Gene A1 against Species B genome
Take top BLAST hit in Species B and use as the query against Species A
If Gene A1 is the top blast hit in the genome, then call A1 & B4 orthologs
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Methods of orthology prediction
1. Reciprocal best-BLAST hits (RBH): simplest method
Species A
Gene A1
Gene A2
1.
2.
3.
Gene B1
Gene B2
...
...
Gene An
Species B
Gene Bn
BLAST Gene A1 against Species B genome
Take top BLAST hit in Species B and use as the query against Species A
If Gene A1 is the top blast hit in the genome, then call A1 & B4 orthologs
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Problems with RBH
* Clear cases where the top BLAST hit is NOT the ortholog
e.g. top hits can be highly conserved common domains
* Gene duplications in one species can completely obscure orthologous hits
* Orthologs with very low sequence homology can be missed altogether
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Methods of orthology prediction
2. Reciprocal Smallest Distance (RSD): slightly more complicated
Species A
Species B
Gene A1
Gene A2
1.
2.
...
...
Gene An
Gene B1
Gene B2
Gene Bn
BLAST Gene A1 against Species B genome
Take X number of top BLAST hits (user determined)
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Methods of orthology prediction
2. Reciprocal Smallest Distance (RSD): slightly more complicated
1.
2.
3.
BLAST Gene A1 against Species B genome
Take X number of top BLAST hits (user determined)
Do a global multiple alignment - throw out proteins with >Y% gapped positions
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Methods of orthology prediction
2. Reciprocal Smallest Distance (RSD): slightly more complicated
1.
2.
3.
4.
BLAST Gene A1 against Species B genome
Take X number of top BLAST hits (user determined)
Do a global multiple alignment - throw out proteins with <Y% gapped positions
Take remaining proteins and find the single one with the closest evolutionary distance
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Methods of orthology prediction
2. Reciprocal Smallest Distance (RSD): slightly more complicated
Species A
Gene A1
Gene A2
1.
2.
3.
4.
5.
Gene B1
Gene B2
...
...
Gene An
Species B
Gene Bn
BLAST Gene A1 against Species B genome
Take X number of top BLAST hits (user determined)
Do a global multiple alignment - throw out proteins with <Y% gapped positions
Take remaining proteins and find the single one with the closest evolutionary distance
Final reciprocal BLAST using remaining gene in Species B as query against Genome A
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Problems with RSD
* Clear cases where the top BLAST hit is NOT the ortholog
e.g. top hits can be highly conserved common domains
* Gene duplications in one species can completely obscure orthologous hits
* Orthologs with very low sequence homology can be missed altogether
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Methods of orthology prediction
3. Newest methods take synteny into account
Syntenic = conserved gene/sequence order
Gene A1
A2
A3
A4
Gene B1
B2
B3
B4
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Problems with Synteny-based Methods
* Clear cases where the top BLAST hit is NOT the ortholog
e.g. top hits can be highly conserved common domains
* Gene duplications in one species less likely to obscure things
* Orthologs with low sequence homology not part of a larger duplication
could still be missed
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Methods of orthology prediction
4. Clusters of Orthologs (COG) approach:
- Addresses the restriction of 1:1 orthologs
- Identifies inparalogs and then id’s orthologous relationships between groups
Species
A
B
C
D
Several approaches can assign COGs across many species at once
(InParanoid, Fuzzy RB)
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Lots of different databases of orthologs (esp. for model organisms)
Of course, different methods of orthology assignment can give very different results
AND … genome errors can really obscure things
Bad genome annotations can affect orthology & paralogy relationships
- missing genes, fused genes, incorrect start/stop annotations
Bad assembly can affect ortho clusters:
- amplifications or decreases of gene family numbers
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Why is orthology-paralogy so important?
Allows us to study the history of protein evolution & infer constraints
Ancestral
Gene 1
Gene duplication along
this species branch
Separate gene duplication
in Species A
A1 A2 B1 C1 C2 D1 D2 E1
GENE TREE
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Ligand
Glucocorticoid Receptor (GR)
Cortisol
Aldosterone (tetrapods)
DOC (teleosts)
* Teleosts don’t make aldosterone
Mineralocorticoid Receptor (MR)
Governs
Stress Response
Electrolyte
Homeostasis
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Figure 1
Blue = Aldo binding
Red = Cortisol ONLY
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Two amino-acid changes in AncCR can alter specificity
Blue = DOC
Red = Cortisol
Green = Aldo
S106P likely occurred FIRST, then L111Q
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Model for evolution of ligand binding & hormone response
1.
2.
3.
4.
Ancestral protein could bind Aldo, even though no Aldo present
Duplication ~450 mya = redundant receptors
Two successive changes in GR = switch to Cortisol Specificity
Emergence of Aldosterone Hormone
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