Ways to Find Homologous Genes

The focus of this commentary is sequence homology defined as shared ancestry between two segments of sequences. It includes two broad classes of relations between genes - orthology and paralogy. Lately Ken Wolffe added a new term ‘ohnology’ to describe paralogous genes, whose shared ancestry is from whole genome duplication events. As an example, bladderwort genome paper presents very informative analysis of various whole genome duplication event in plants. Check their Fig. 1 for example.

Orthology

Orthology refers to shared ancestry of a gene in two species. For example, human hox genes in four genomic clusters have orthologies with four sets of hox genes.

Paralogy

Paralogy refers to shared ancestry caused by gene duplication. Hox1, Hox2, Hox3 and Hox4 clusters in human genome are paralogous to each other.

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Now that large number of complete genome sequences are being published online, we checked for best approaches to find orthologous genes in those genomes and came across a very informative Biostars thread.

What is the best method to find orthologous genes of a species?

Rest of this commentary is our lame attempt to summarize excellent discussions in the above thread.

Bioinformatics approaches for finding orthologies

They fall into two categories - reciprocal BLAST and construction of phylogenetic trees. Reciprocal BLAST approach is fast and less accurate, and phylogenetic tree approach is slow and more accurate.

BlastO is a BLAST web-service developed by Princeton researcher Yi Zhou to allow you to do BLAST on orthologous genes.

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Databases

Several online databases exist, from where researchers can download pre- computed orthology tables for a set of organisms.

MetaPhOrs

MetaPhOrs can be described as a orthology database of orthology databases. It combines results from many other BLAST- based orthology databases using phylogeny-based method and develops more accurate tables.

MetaPhOrs is a public repository of phylogeny-based orthology and paralogy predictions that were computed using resources available in seven popular homology prediction services (PhylomeDB, EnsemblCompara, EggNOG, OrthoMCL, COG, Fungal Orthogroups, and TreeFam).

MetaPhOrs data can be downloaded from this ftp site. We do not know how often they update their tables, because keeping up with the newly released genomes is the biggest challenge faced by all groups maintaining orthology databases. Currently it includes 863 organisms, but a large number of them are prokaryotes.

COG and eggNOG

COG database is maintained at NCBI.

Clusters of Orthologous Groups of proteins (COGs) were delineated by comparing protein sequences encoded in complete genomes, representing major phylogenetic lineages. Each COG consists of individual proteins or groups of paralogs from at least 3 lineages and thus corresponds to an ancient conserved domain.

FTP site for COG eukaryotic data is here. Its eukaryotic cluster includes only seven organisms.

EggNOG is EMBL’s improvement over COG.

EggNOG (evolutionary genealogy of genes: Non-supervised Orthologous Groups) is a database of orthologous groups of genes. The orthologous groups are annotated with functional description lines (derived by identifying a common denominator for the genes based on their various annotations), with functional tags: [] categories (i.e derived from the original COG/KOG categories).

eggNOG’s database currently counts 721,801 orthologous groups in 1133 species, covering 4,396,591 proteins (built from 5,214,234 proteins).

Their data can be downloaded from here.

EnsemblCompara

EnsemblCompara does very extensive work of building trees for orthologous genes. We do not know how much they differ from eggNOG, because we are too lazy to read the papers. Biostars thread says that Ensembl is phylogeny based and eggNOG is BLAST- based, but the download page of eggNOG does list some trees.

Gene trees are constructed using a representative protein for every gene in Ensembl: proteins are clustered using hcluster_sg based on WU-BLAST scores, and each cluster of proteins is aligned using M-Coffee. Finally, TreeBeST is used to produce a gene tree from each multiple alignment, reconciling it with the species tree to call duplication events. Homologues are deduced from these trees. We also determine gene gain and loss events using the CAFE software.

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Possibly not being updated:

InParanoid and MultiParanoid

InParanoid was last updated in June 2009, when nobody expected more than five Illumina machines to be sold. MultiParanoid was last updated three years prior to that. Oh well.

OrthoMCL, phylofacts, TreeFam, PHOG - are they being updated?

If we like to use a database being updated regularly with arrival of new genomes from all kinds of places, which one should we use?