Orthology Analysis

Erik Sonnhammer

Center for Genomics and Bioinformatics

Karolinska Institutet, Stockholm

Outline

• Basic concepts

• BLAST-based approaches to orthology

• Tree-based approaches to orthology

• Domain-level orthology

Homologs

= genes with a common origin

• May be genes in the same or in different organisms

• Does not say that function is identical

• Can only be true or false, and not a percentage!

• Homologs have the same 3D-structure layout

Homologs

Orthologs Paralogs

Gene Y1 in human

Gene Y in rat

Gene Y2 in human

DGene X in ancient animal

Gene Yin ancient mammal

In-paralogs

Orthologs: Orthologs: separated by speciationseparated by speciation

Gene Xin ancient mammal

Gene Xin human

Gene X in rat

Time

Orthologs

Orthologs

Out-paralogs

paralogs

speciation

D

S

S

In/Out-paralog definition

In-paralogs ~ co-orthologsparalogs that were duplicated after the speciation and hence are orthologs to a cluster in the other species

Out-paralogs = not co-orthologsparalogs that were duplicated before the speciation. Not necessarily in the same species.

Sonnhammer & Koonin, Trends Genet. 18:619-620 (2002)

Orthologs for functional genomicsOrthologs for functional genomics• Co-orthologs / inparalogs are more likely than outparalogs to

have identical biochemical functions and biological roles.

• Co-orthologs can be used to discover human gene function via model organism experiments

• Co-orthologs are key to exploit functional genomics/proteomics data in in model organisms

Orthology and function conservation

• Orthology does not say anything about evolutionary distance.

• Close orthologs, e.g. human-mouse are very likely to have the same biological role in the organism.

• Distant orthologs, e.g. human-worm are less likely to have the same phenotypical role, but may have the same role in the corresponding pathway.

Ortholog DatabasesSequence database Orthology

detection methodOrtholog database

SwTrembl proteomes Inparanoid (blast) Inparanoid

proteomes COGs (blast) COGs / KOGs

TIGR gene index COGs (blast) TOGA/EGO

proteomes OrthoMCL (blast) OrthoMCL

Pfam Orthostrapper (tree) HOPS

Pfam RIO (tree)

How to find orthologs?How to find orthologs?

1. Calculate phylogenetic tree, look for orthologs in the tree (Orthostrapper, Rio):

2. Two-way best matches between two species can be used to find orthologs without trees.

[However, in-paralogs are harder to find this way]

Two-way best match approachto finding orthologs

COGsCOG2813:

Out-

paralogs

orthologs

Inpara-n-oidInparalog ‘n ortholog identification

Blue = species 1

Red = species 2

Inparanoid

Blue = species 1

Red = species 2

No overlap - no problems:

Partial overlap - separate:

Complete overlap - merge:

Resolve overlapping clustersResolve overlapping clusters

Inparalog score

Score for inparalog P = (scoreAP - scoreAB) / (scoreAA - scoreAB)

0 20 40 60 80 100%

A

P

B

Confidence values for main orthologs from sampling

TVHIVDDEEPVR---KSLAFM---LTMNGFAT+ ++DD +R K L M +T+ G ATILLIDDHPMLRTGVKQLISMAPDITVVGEA

Sampling with replacement; insertions kept intact

GAFDEP---LVTHVR..........GA + ++T +RGAEEHMAPDILTLLR..........

“Bootstrap alignment” -> “bootstrap score”

Confidence = (bootstrap alignments best-best matches / nr of bootstraps)

http://inparanoid.cgb.ki.se

inparanoid.cgb.ki.se

Remm et al, J. Mol. Biol. 314:1041-1052 (2001)

Homo Sapiens vs. C. elegans

Ortholog group sizes, human vs XVersion 2.5:

08-apr-03151360 sequences from Swissprot-TREMBL

44996 sequences from Homo sapiens26674 sequences from Mus musculus20316 sequences from Drosophila melanogaster20997 sequences from Caenorhabditis elegans36751 sequences from Arabidopsis thaliana6910 sequences from Saccharomyces cerevisiae8709 sequences from Escherichia coli

Species

Number of orthologs (orthologous groups) in H.sapiens

Number of sequences (in-paralogs) from H.sapiens in orthologous groups

Number of sequences (in-paralogs) from this species in orthologous groups

M.musculus 12458 19532 17055D.melanogaster 5549 15259 9854C.elegans 4541 14222 6537A.thaliana 3258 10863 12178S.cerevisiae 2175 7265 2751E.coli 599 2144 1037

Nr of inparalogs per ortholog group

Species Avg. inparalogs in model organism ortholog groups

Avg. inparalogs in human

ortholog groups

Mouse 1.36 1.56

Fly 1.77 2.75

Worm 1.44 3.13

Mustard weed 3.73 3.33

Yeast 1.26 3.34

E. coli 1.73 3.57

• No guarantee that the same segment is used in different sequences

• No evolutionary distance model

• Does not take multiple domains into account

Drawbacks of Blast-basedorthology assignment

Domain orthology• Inparanoid Human-Fly ortholog pairs with domains in

Pfam-A 13.0: 20335

• Different domain architectures: 5411– Many of these are minor differences, e.g. 22 vs 21 Spectrin repeats

– Sometimes the difference is big:

ef-hand UCH

TBC UCH

Tree-based approaches

Distance-based tree building

• Bootstrapping: – randomly pick columns to bootstrap alignment, calculate tree

– Repeat 1000 times, frequency of node = bootstrap support

A2 A3

A1 4 8

A2 10

A1

A2

A3

1

3

5

2

A1 MKFYSLPNFPEN

A2 MKYYKLPDLPDE

A3 MRFYTACENPRS

Distance matrix

Orthology by tree reconciliation

Species tree

Gene tree

Infer 2 duplications and 2 losses

• Assumption that the species tree is fully known

• Does not give confidence values

• Gene trees become unreliable when involving a lot of sequences (more data -> less certainty)

• Computationally expensive

Drawbacks of tree reconciliationfor orthology assignment

Partial tree reconciliation

• Find pairwise orthologs by computer parsing of tree.

99

45

85

100

82

99

C14F5.4

AAF49194.1

AH6.2

F37H8.4

Y6E2A.9

C47D12.3

T04F8.1

AAF52138.1

PIR-S67168

Pairwise orthology confidence by ‘orthostrapping’

The original tree with bootstrap support values

C14F5.4

AAF49194.1

AH6.2

F37H8.4

Y6E2A.9

C47D12.3

T04F8.1

AAF52138.1

PIR-S67168

Pairwise orthology confidence by ‘orthostrapping’

01C14F5.4

10T04F8.1

00C47D12.3

00Y6E2A.9

00F37H8.4

00AH6.2

AAF52138.1

AAF49194.1

FlyWorm

C14F5.4

AAF49194.1

AH6.2

F37H8.4

Y6E2A.9

C47D12.3

T04F8.1

AAF52138.1

PIR-S67168

Pairwise orthology confidence by ‘orthostrapping’

02C14F5.4

20T04F8.1

10C47D12.3

00Y6E2A.9

00F37H8.4

00AH6.2

AAF52138.1

AAF49194.1

FlyWorm

99

45

85

100

82

99

C14F5.4

AAF49194.1

AH6.2

F37H8.4

Y6E2A.9

C47D12.3

T04F8.1

AAF52138.1

PIR-S67168

Pairwise orthology confidence by ‘orthostrapping’

099C14F5.4

980T04F8.1

810C47D12.3

770Y6E2A.9

770F37H8.4

770AH6.2

AAF52138.1

AAF49194.1

FlyWorm

orthostrapper.cgb.ki.se

Orthology is not transitive!

Multiple species at different distances may give erroneous groups, that includes out-paralogs

Orthology is not transitive!

-> Orthology strictly defined for only 2 species/clades

Combining species of different distances is very dangerous

But OK to combine multiple equidistant ones

YH1D1H2D2

D1 H2

Y

Domain-level orthology

HOPS - Hierarchy of Orthologs and Paralogs

eukaryota

metazoa

viridiplantae

fungi

nematoda

arthropoda

chordata

1. All species in Pfam are bundled in groups according to scheme:

2. Apply Orthostrapper to groups at same level in Pfam families

3. Display results in NIFAS

Pfam

Pfam in brief:

Profile-HMMHMMer-2.0

FULL alignment

Search database

Manually curated Automatically made

SEED alignmentrepresentative members

Description file

• Release 13.0 (April 2004):– 7426 families Pfam-A domain families

– Based on 1160000 sequences (Swissprot & Trembl)– 21980 unique Pfam-A domain architectures– 73% of all proteins have >=1 Pfam-A domain

HOPS results

Pfam 10, 6190 families:

• 2450 families (40%) have HOPS orthologs

• 1319 families (21%) have HOPS orthologs in all 6 pairwise comparisons

• 286356 pairwise orthology assignments (> 75% orthostrap)

Storm and Sonnhammer, Genome Research 13:2353-2362 (2003)

Ways to access HOPS

• NIFAS graphical browser

• By sequence ID at Pfam.cgb.ki.se/HOPS

• Flatfiles (Orthostrap tables of 2 clades)

Pfam.cgb.ki.se/HOPS

Evolution of Domain Architectures

NIFAS:

ATP sulfurylase /APS kinase

Orthologous shuffled domains?

ATP sulfurylase domain, metazoa vs fungi

APS kinase domain

HOPS orthologs of PPS1_HUMAN (ATP sulfurylase/APS kinase)

Summary of ATP sulfurylases/APS kinases:

Shuffled non-orthologous domains

Fungi

Metazoa

Conclusions

• Orthologs can be detected by – Blast: fast– tree: slow but less error-prone

• Species at different evolutionary distances should not be combined in orthology analysis

• Inparanoid and Orthostrapper were designed to find inparalogs but not outparalogs

• HOPS/NIFAS can be used to find domain orthologs and analyze domain architecture evolution

Future perspectives

• Multiparanoid – multiple species merging of pairwise Inparalogs.

• Functional divergence among inparalogs

Acknowledgments

– Christian Storm

– Maido Remm

– Andrey Alexeyenko

– Volker Hollich

– Mats Jonsson

http://sonnhammer.cgb.ki.se