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1 Orthologs: Two genes, each from a different species, that descended from a single common ancestral gene Paralogs: Two or more genes, often thought of.

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Presentation on theme: "1 Orthologs: Two genes, each from a different species, that descended from a single common ancestral gene Paralogs: Two or more genes, often thought of."— Presentation transcript:

1 1 Orthologs: Two genes, each from a different species, that descended from a single common ancestral gene Paralogs: Two or more genes, often thought of as within the same species, that originated by one or more gene duplication events (note no regard to function! and does NOT require one-to-one relationships) Orthology & Paralogy (etc. etc.)

2 2 ABCDE SPECIES TREE A1B1C1D1E1 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 Ancestral Gene 1 Ancestral species

3 3 A1B1C1D1 E1 GENE TREE Ancestral Gene 1 C2D2 ABCDE SPECIES TREE Ancestral species 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? Gene duplication along this species branch

4 4 Orthologs: Two genes, each from a different species, that descended from a single common ancestral gene Paralogs: Two or more genes, within the same species, that originated by one or more gene duplication events (note no regard to function!) 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 Orthology & Paralogy (etc. etc.)

5 5 Phenology vs. Phylogeny Phenology: tree based on similarity of characteristics 1.Align protein & score alignment (# of identical and ‘conserved’ amino acids) 2.Build a tree based on sequence similarity A1B1C1C2 A1 is more similar to C1 than C2 - A1 & C1 are likely (* but not guaranteed!) more similar functionally Phylogeny: tree based on evolutionary history A1B1C1C2 But historically, A1 is equally distant to C1 and C2 1.Requires inferring history across the species

6 6 Species A Gene A1 Gene A2... Gene An Species B 1.BLAST Gene A1 against Species B genome 2.Take top BLAST hit in Species B and use as the query against Species A 3.If Gene A1 is the top blast hit in the genome, then call A1 & B4 orthologs Gene B1 Gene B2... Gene Bn Methods of orthology prediction 1. Reciprocal best-BLAST hits (RBH): simplest method

7 7 Methods of orthology prediction 1. Reciprocal best-BLAST hits (RBH): simplest method Species ASpecies B 1.BLAST Gene A1 against Species B genome 2.Take top BLAST hit in Species B and use as the query against Species A 3.If Gene A1 is the top blast hit in the genome, then call A1 & B4 orthologs Gene B1 Gene B2... Gene Bn Gene A1 Gene A2... Gene An

8 8 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

9 9 Methods of orthology prediction 2. Reciprocal Smallest Distance (RSD): slightly more complicated Species ASpecies B 1.BLAST Gene A1 against Species B genome 2.Take X number of top BLAST hits (user determined) Gene B1 Gene B2... Gene Bn Gene A1 Gene A2... Gene An

10 10 1.BLAST Gene A1 against Species B genome 2.Take X number of top BLAST hits (user determined) 3.Do a global multiple alignment - throw out proteins with >Y% gapped positions 2. Reciprocal Smallest Distance (RSD): slightly more complicated Methods of orthology prediction

11 11 1.BLAST Gene A1 against Species B genome 2.Take X number of top BLAST hits (user determined) 3.Do a global multiple alignment - throw out proteins with <Y% gapped positions 4.Take remaining proteins and find the single one with the closest evolutionary distance 2. Reciprocal Smallest Distance (RSD): slightly more complicated Methods of orthology prediction

12 12 Species ASpecies B Gene B1 Gene B2... Gene Bn Gene A1 Gene A2... Gene An 1.BLAST Gene A1 against Species B genome 2.Take X number of top BLAST hits (user determined) 3.Do a global multiple alignment - throw out proteins with <Y% gapped positions 4.Take remaining proteins and find the single one with the closest evolutionary distance 5.Final reciprocal BLAST using remaining gene in Species B as query against Genome A 2. Reciprocal Smallest Distance (RSD): slightly more complicated Methods of orthology prediction

13 13 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

14 14 3. Newest methods take synteny into account Methods of orthology prediction Syntenic = conserved gene/sequence order Gene A1A2A3A4 Gene B1B2B3B4

15 15 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

16 16 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 SpeciesABCD Several approaches can assign COGs across many species at once (InParanoid, Fuzzy RB)

17 Lots of different databases of orthologs (esp. for model organisms)

18 Of course, different methods of orthology assignment can give very different results

19 19 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

20 20 Why is orthology-paralogy so important? Allows us to study the history of protein evolution & infer constraints A1B1C1D1 E1 GENE TREE Ancestral Gene 1 C2D2 Gene duplication along this species branch A2 Separate gene duplication in Species A

21 21

22 22 Glucocorticoid Receptor (GR) Mineralocorticoid Receptor (MR) LigandGoverns CortisolStress Response Aldosterone (tetrapods) DOC (teleosts) Electrolyte Homeostasis * Teleosts don’t make aldosterone

23 23 Figure 1 Blue = Aldo binding Red = Cortisol ONLY

24 24 Two amino-acid changes in AncCR can alter specificity Blue = DOC Red = Cortisol Green = Aldo S106P likely occurred FIRST, then L111Q

25 25 Model for evolution of ligand binding & hormone response 1.Ancestral protein could bind Aldo, even though no Aldo present 2.Duplication ~450 mya = redundant receptors 3.Two successive changes in GR = switch to Cortisol Specificity 4.Emergence of Aldosterone Hormone


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