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Orthologs Detection and Applications

Marcus Lechner

Bioinformatics Leipzig

2009-10-23

Marcus Lechner (Bioinformatics Leipzig) Orthologs Detection and Applications 2009-10-23 1 / 25

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Table of contents

.. .1 Background on homology

.. .2 Proteinortho

.. .3 Domain wide commons

.. .4 Annotation pipeline

.. .5 References

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Definitions

.Homologous genes..

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have derived from a common ancestor

.Orthology..

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evolved by speciation

thought to have a similar function

.Paralogy..

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homologous genes within the same species

thought to have a related function (neo-/subfunctionalization)

out-paralogs arose form a duplication preceding a speciation

in-paralogs evolved by duplication subsequent to speciation

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Example

Figure: Illustration of relationships: Three species with orthologs, xeno-, in- andout-paralogs. Adapted from [1].

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Problems

.Interpretation..

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original definition of homology (1843):’the same organ under every variety of form and function’ [2]

still a very good quantitative indication

but neither essential nor sufficient

Homology of two proteins is not equivalent with a common function,sequence nor structure!

Marcus Lechner (Bioinformatics Leipzig) Orthologs Detection and Applications 2009-10-23 5 / 25

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Problems

.Interpretation..

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original definition of homology (1843):’the same organ under every variety of form and function’ [2]

still a very good quantitative indication

but neither essential nor sufficient

Homology of two proteins is not equivalent with a common function,sequence nor structure!

Marcus Lechner (Bioinformatics Leipzig) Orthologs Detection and Applications 2009-10-23 5 / 25

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Problems

.Interpretation..

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original definition of homology (1843):’the same organ under every variety of form and function’ [2]

still a very good quantitative indication

but neither essential nor sufficient

Homology of two proteins is not equivalent with a common function,sequence nor structure!

Marcus Lechner (Bioinformatics Leipzig) Orthologs Detection and Applications 2009-10-23 5 / 25

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Problems

.Relative definition..

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in-/out-paralog definition only in subjection to a certain species

greatly dependent on available data

no absolute view

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Problems

Figure: Illustration of relationships: Complete view needed.

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Problems

Figure: Illustration of relationships: Complete view needed.

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Problems

.Information benefit..

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duplications are known to be a major source of innovation in evolution

proteins are homologs per definition, if they have a common ancestor

irrespective of their actual similarity or function

most proteins are anciently related but have evolved far

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Problems

Figure: Multiple gene duplications: All are homologs per definition but smallergroups may be more of use.

Marcus Lechner (Bioinformatics Leipzig) Orthologs Detection and Applications 2009-10-23 10 / 25

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Problems

.Information benefit..

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duplications are known to be a major source of innovation in evolution

proteins are homologs per definition, if they have a common ancestor

irrespective of their actual similarity or function

most proteins are anciently related but have evolved far

Up to which point is the homology information useful?

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Conclusion

.Proteinortho approach..

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arose from the same ancestor + similar function ⇒ similar sequence

should return a useful subset of homologs (isofunctional aimed)

reciprocal best blast(s)

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Reciprocal best blast(s) for homologs detection

Figure: Homology detection using blast

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Proteinortho

.Features..

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orthologs and paralogs assignment for proteins/protein coding genes

designed for large-scale application

behaves nicely in memory consumption

capable of distributed computing

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Workflow

Figure: Proteinortho workflow: 1) Reciprocal blasts 2) Transformation into graphrepresentation 3) Coloring and decomposition 4) Reconversion and mapping tospecies with encoded proteins

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Distributed computing

Figure: a) Multiple PCs running Proteinortho, cooperating dynamically using anN-way technique b) Workflow of synchronization

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Challenge

.Application to all bacteria available on NCBI..

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710 species, 1.5 million proteins

took about two weeks on 50 CPU-cores (Intel Xenon 2.33 GHz)

peak of only 2.5 GB RAM, but 300 GB hard disk

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Challenge

.Application to all bacteria available on NCBI..

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710 species, 1.5 million proteins

took about two weeks on 50 CPU-cores (Intel Xenon 2.33 GHz)

peak of only 2.5 GB RAM, but 300 GB hard disk

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Results

400 450 500 550 600 650 700# of species covered

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25

50

75

100

125

150

175

200

225

250

275

300#

of c

onne

cted

com

pone

nts

originalblastedblasted filtered

Coverage overviewcumulative

Figure: Number of common proteins. Sets with over 5% paralogs where filtered.

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Results

.Common proteins..

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30S ribosomal proteins S2-5, S7, S8, S10-13, S17, S19

50S ribosomal proteins L1-3, L5, L6, L11, L14, L22, L23

tRNA synthetases for seryl, arginyl, phenylalanyl (alpha chain)

preprotein translocase, SecY subunit

peptidase M22, O-sialoglycoprotein endopeptidase

transcription elongation/termination factor NusA

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Annotation pipeline

.Application for annotation..

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in: newly sequenced bacterial genome

out: annotation of protein coding genescandidates for non-coding genes

no previous knowledge required

runs in 10 to 90 minutes

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Relatives discovery

Figure: Relatives detection using reference proteins and tree.

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Relatives discovery with colors

Figure: Advanced relatives detection using colors.

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Seeding

Figure: Pipeline seeding with proteins.

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Pipeline overview

Figure: Pipline seeding with proteins.

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The end

Thank you for listening!

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W M Fitch.Homology a personal view on some of the problems.Trends Genet, 16(5):227–31, May 2000.

Richard Owen, Cooper, and William White.Lectures on the comparative anatomy and physiology of theinvertebrate animals.London :Longman, Brown, Green, and Longmans, 1843.http://www.biodiversitylibrary.org/bibliography/6788.

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