Gene Orthology/Paralogy prediction method

The gene orthology and paralogy predictions are generated by a pipeline where maximum likelihood phylogenetic gene trees (generated by NJTREE) play a central role. They aim to represent the evolutionary history of gene families, i.e. genes that diverged from a common ancestor. These gene trees reconciled with their species tree have their internal nodes annotated to distinguish duplication or speciation events.

There is a clear concordance with reciprocal best approaches in the simple case of unique orthologous genes. However, the gene tree pipeline is able to find more complex one-to-many and many-to-many relations. This for instance significantly raises the number of Teleost (bony fish) to Mammal orthologs and has even more dramatic effects on Fly/Mammal or Worm/Mammal orthologous gene predictions. Using this approach, we are also able to "time" duplication events which produce paralogs by identifying the most recent common ancestor (=taxonomy level) for a given internal node of the tree.

The gene orthology and paralogy prediction pipeline has 7 basic steps:

1. Load the longest translation of each gene from all species used in Ensembl

2. run WUBlastp+SmithWaterman of every gene against every other (both self and non-self species) in a genome-wise manner

3. Build a graph of gene relations based on Best Reciprocal Hits (BRH1) and Best Score Ratio (BSR)2 values

4. Extract the connected components (=single linkage clusters), each cluster representing a gene family.

5. For each cluster, build a multiple alignment based on the protein sequences using MUSCLE3

6. For each aligned cluster, build a phylogenetic tree using NJTREE4 using the CDS sequences of the multiple alignment. An rooted tree with internal duplication tags is obtained at this stage, reconciling it with the species tree in 'ensembl-compara/scripts/pipeline/species_tree_njtree.taxon_id.nh'.

7. From each gene tree, infer gene pairwise relations of orthology and paralogy types.

Orthologues : any gene pairwise relation where the ancestor node is a speciation event.
We predict several descriptions of orthologues.
 ortholog_one2one
 ortholog_one2many
 ortholog_many2many
 apparent_ortholog_one2one (is a special case, see below)

Paralogues : any gene pairwise relation where the ancestor node is a duplication event.
We predict several descriptions of paralogues.
 within_species_paralog
 between_species_paralog
tree_example1

A within_species_paralog corresponds to a relation between 2 genes of the SAME species where the ancestor node has been labelled as a duplication node e.g. H2:H2', M2:M2' but does not necessarily mean that the duplication event has occurred in this species only. For example, M2':M3' are also within_species_paralog but the duplication event has occurred in the common ancestor between species H and species M. If H is human and M Mouse, the taxonomy level "times" the duplication event to the ancestor of "Euarchontoglires".

A between_species_paralog corresponds to a relation between 2 genes of DIFFERENT species where the ancestor node has been labelled as a duplication node e.g. M1:H2 or M1:H3.
Special cases of between_species_paralog can be singled out where they can be characterised as one2one relations. Such cases are then relabelled apparent_ortholog_one2one. Apparent orthologs can be the results of real duplication followed by gene loss (as shown in the picture below), but can also be the results of a wrong gene tree topology and wrong duplication node labelling.

tree_example2

Notes and References

1 BRH: Best Reciprocal Hit. When a query gene translation has an unambiguous 'best' hit to a target translation, and that particular target translation has an unambiguous 'best' hit back to the starting query translation. The discrimination function for 'best' is a simple sort of blastp >score, %identity, >%positivity.

2 BSR: Blast Score Ratio. When 2 proteins P1 and P2 are compared, BSR=scoreP1P2/max(self-scoreP1 or self-scoreP2). The default threshold used in the initial clustering step is 0.33.

3 Edgar RC "MUSCLE: a multiple sequence alignment method with reduced time and space complexity" BMC Bioinformatics 2004 Aug 19;5:113.

4 Li H et al. NJTREE: http://treesoft.sourceforge.net/njtree.shtml. Manuscript in preparation.