1. BLAST program selection guide

2. Orthology, Paralogy, Xenology
Homology
Orthology, Paralogy, Xenology

3. Fitch WM.  Trends Genet. 2000 May;16(5):227-31. 

4. Analogy vs Homology Analogy
The relationship of any two characters that have descended convergently from unrelated ancestors.
Homology
The relationship of any two characters that have descended, usually with divergence, from a common ancestral character.

5. Orthology
The relationship of any two homologous characters whose common ancestor lies in the cenancestor of the taxa from which the two sequences were obtained.
Paralogy
The relationship of any two homologous characters arising from a duplication of the gene for that character.
Xenology
The relationship of any two homologous characters whose history, since their common ancestor, involves an interspecies (horizontal) transfer of the genetic material for at least one of those characters.

6. A classic example (Figure from NCBI)

7. Test Yourself
A1 – B1
A1 – B2
A1 – C3
B1 – C2
C2 – C3
B2 – C3
C3 – AB1

8. Test Yourself A1 – B1 = Ortho A1 – B2 = Ortho A1 – C3 = Ortho
B1 – C2 = Para (out)
C2 – C3 = Para (in)
B2 – C3 = Ortho
C3 – AB1= Xeno

9. Homology on a Genome-Scale
How many and which genes are common to two or more organisms?
Which genes differentiate one organism from another?
How is homology related to function?

10. Orthologs are the set of genes/proteins with gene trees identical to the species tree.
We can understand other types of homology relationships by comparison to the species tree.
But often we don’t know the species tree, and phylogenetic methods are complex

11. Consider two genomes
Use BLASTP to compare one set of proteins (proteome) to the other
Which set will you use as the query and which as the database?
What criteria will you use to define “a match”?
GenomeA – gene 1
GenomeB– gene 1
A1, A3, B2 and B3 are homologs (assuming the aligned regions overlap)
GenomeA – gene 2
GenomeB – gene 2
GenomeA – gene 3
GenomeB – gene 3

12. Reciprocal Best Hits
Use BLASTP to compare sets of proteins (proteome) to each other
First using GenomeA to query against GenomeB
Then using GenomeB to query against GenomeA
Save only one best match for each query
Save only the reciprocal best matches as “orthologs”
GenomeA – gene 1
GenomeB– gene 1
GenomeA – gene 2
GenomeB – gene 2
GenomeA – gene 3
GenomeB – gene 3
GenomeA – gene 1
GenomeB– gene 1
GenomeA – gene 2
GenomeB – gene 2
GenomeA – gene 3
GenomeB – gene 3
GenomeA – gene 1
GenomeB– gene 1
Lose A3-B2 and A1-B3 homology
GenomeA – gene 2
GenomeB – gene 2
GenomeA – gene 3
GenomeB – gene 3

13. One case where RBH works
GenomeA – gene 1
GenomeB– gene 1
GenomeA – gene 2
GenomeB – gene 2
GenomeA – gene 3
GenomeB – gene 3
One case where RBH works
GenomeA – gene 1
GenomeB– gene 1
GenomeA – gene 2
GenomeB – gene 2
GenomeA – gene 3
GenomeB – gene 3
GenomeA – gene 1
GenomeB– gene 1
GenomeA – gene 2
GenomeB – gene 2
GenomeA – gene 3
GenomeB – gene 3
GenomeA – gene 1
Glucose transport
GenomeB – gene 2
Glucose transport
GenomeA – gene 3
Fructose transport
GenomeB – gene 3
Galactose transport

14. One case where RBH fails
GenomeA – gene 1
GenomeB– gene 1
GenomeA – gene 2
GenomeB – gene 2
GenomeA – gene 3
GenomeB – gene 3
One case where RBH fails
GenomeA – gene 1
GenomeB– gene 1
GenomeA – gene 2
GenomeB – gene 2
GenomeA – gene 3
GenomeB – gene 3
GenomeA – gene 1
GenomeB– gene 1
GenomeA – gene 2
GenomeB – gene 2
GenomeA – gene 3
GenomeB – gene 3
In paralogs- duplication since speciation
GenomeA – gene 1
Glucose transport
GenomeA– gene 3
Glucose transport
GenomeB– gene 2
Fructose transport
GenomeB – gene 3
Galactose transport

15. Software/Methods for Predicting Orthologs from Genome Sequences
RBH
RSD (Reciprocal Shortest Distance)
INPARANOID
RIO
Orthostrapper
Ortholuge
TribeMCL
OrthoMCL

17. Li L, Stoeckert CJ Jr, Roos DS
Li L, Stoeckert CJ Jr, Roos DS. OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res Sep;13(9):

18. Pre-computed OrthoMCL results

19. Evaluating performance
No “gold standard” set of true orthologs
Latent Class Analysis
Agreement between methods provides confidence
27,562 proteins from 6 eukarotes assigned to Pfams

20. Performance Metrics actual \ predicted negative positive Negative TN
Accuracy – Proportion correct
TN+TP/total
TPR (Recall) – Proportion of predicted positives that are correct
TP/FP+TP
Sensitivity – Proportion of positives correctly predicted
TP/FN+TP
Specificity – Proportion of negatives correctly predicted
TN/TN+FP
actual     \    
predicted
negative
positive
Negative TN FP
Positive FN TP

21. Chen F, Mackey AJ, Vermunt JK, Roos DS
Chen F, Mackey AJ, Vermunt JK, Roos DS. Assessing performance of orthology detection strategies applied to eukaryotic genomes. PLoS ONE Apr 18;2(4):e383.

22. Method Comparison

23. Is context useful for assigning homology type?
Prokaryotes vs eukaryotes
Evolutionary origin
Paralogs that arise as tandem repeats of single genes
Parlogs that arise from duplication of larger regions
Xenologs that arise from acquisition of a similar gene from another lineage

24. Example: pectate lyases of soft-rot enterobactia may be SymBets, but genome context suggests they may not be orthologs