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Comparative GenomicsComparative Genomics

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OverviewOverview

• Orthologues and paralogues

• Protein families

• Genome-wide DNA alignments

• Syntenic blocks

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Comparative GenomicsComparative Genomics

• Allows us to achieve a greater understanding of vertebrate evolution

• Tells us what is common and what is unique between different species at the genome level

• The function of human genes and other regions may be revealed by studying their counterparts in lower organisms

• Helps identify both coding and non-coding genes and regulatory elements

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Species in EnsemblSpecies in Ensembl

CAMBRI ORDO SIL DEV CARBON PER TRIA JURA CRETAC TERTIA

57

0

50

5

43

8

40

8

36

0

28

6

24

5

20

8

14

4

65

MY

BP

FISHES

BIRDSREPTILES

MAMMALS PLACENTALS

MONOTREMES

MARSUPIALS

OTHER BIRDS

PALEOGNATHS

PASSERINES

CROCODILES

TURTLES

LIZARDS

AMPHIBIANS

TELEOSTS

SHARKS

RAYS

LATIMERIA

BICHIR/POLYPTERUS

LUNGFISHES

AGNATHANS

NON-VERTEBRATES

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Orthologue / Paralogue Prediction Orthologue / Paralogue Prediction AlgorithmAlgorithm

(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 (BRH) and Blast Score Ratio (BSR) 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 MUSCLE.

(6) For each aligned cluster, build a phylogenetic tree using PHYML. An unrooted tree is obtained at this stage.

(7) Reconcile each gene tree with the species tree to call duplication event on internal nodes and root the tree, using RAP.

(8) From each gene tree, infer gene pairwise relations of orthology and paralogy types.

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• Orthologues :any gene pairwise relation where the ancestor node is a speciation event

• Paralogues :any gene pairwise relation where the ancestor node is a duplication event

Homologue RelationshipsHomologue Relationships

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Orthologue and Paralogue TypesOrthologue and Paralogue Types

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Orthologue and Paralogue typesOrthologue and Paralogue types

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GeneView

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GeneView

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GeneTreeView

GeneTree

MUSCLEprotein alignment

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GeneTreeView

Duplication node (red)

Speciation node (blue)

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Protein DatasetProtein Dataset

More than 1,500,000 proteins clustered:

• All Ensembl protein predictions from all species supported~ 670,000 protein predictions

• All metazoan (animal) proteins in UniProt:~ 80,000 UniProt/Swiss-Prot~ 830,000 UniProt/TrEMBL

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Clustering StrategyClustering Strategy

• BLASTP all-versus-all comparison

• Markov clustering

• For each cluster:• Calculation of multiple sequence

alignments with ClustalW• Assignment of a consensus description

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Link to FamilyView

GeneView / TransView / ProtView

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Ensembl family members

within human

UniProt family members

Ensembl family members in

other species

Consensus annotation

JalView multiple alignments

FamilyView

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JalView

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Whole Genome AlignmentsWhole Genome Alignments

• Functional sequences evolve more slowly than non-functional sequences, therefore sequences that remain conserved may perform a biological function.

• Comparing genomic sequences from species at different evolutionary distances allows us to identify:• Coding genes• Non-coding genes• Non-coding regulatory sequences

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Selection of Species for DNA Selection of Species for DNA comparisonscomparisons

Both coding and non-coding sequences

~70-75%

~150 MYA

4.2

Opossum

0.42.53.0Size (Gbp)

~65%~80%>99%Sequence

conservation (in coding regions)

Primarily coding

sequences

Both coding and non-coding sequences

Recently changed

sequences and genomic

rearrangements

Aids identification of…

~450 MYA~ 65 MYA~5 MYATime since divergence

PufferfishMouseChimpanzeeHuman vs..

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Alignment AlgorithmAlignment Algorithm

• Should find all highly similar regions between two sequences

• Should allow for segments without similarity, rearrangements etc.

• Issues• Heavy process• Scalability, as more and more genomes are

sequenced• Time constraint

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BLASTZ-net, tBLAT and PECANBLASTZ-net, tBLAT and PECAN

• BLASTZ-net (comparison on nucleotide level) is used for species that are evolutionary close, e.g. human - mouse

• Translated BLAT (comparison on amino acid level) is used for evolutionary more distant species, e.g. human - zebrafish

• PECAN is used for multispecies alignments• 7 eutherian mammals• 10 amniota vertebrates

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BLASTZ-net, tBLAT and PECANBLASTZ-net, tBLAT and PECANFor which combinations of species whole genome alignments have been done is shown on the Comparative Genomics page(Help & Documentation > Genomic Data > Comparative Genomics):

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ContigView

Constrained elements

Conservation score

Blastz mouse

tBLAT zebrafish

PECAN alignments

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Conserved sequences

human

Conserved sequences

dog

MultiContigView

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Human

AlignSliceView

Rat

Dog

Mouse

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MultiContigView vs. AlignSliceView

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AlignView

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GeneSeqalignView

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GeneSeqalignView

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Syntenic BlocksSyntenic Blocks

• Genome alignments are refined into larger syntenic regions

• Alignments are clustered together when the relative distance between them is less than 100 kb and order and orientation are consistent

• Any clusters less than 100 kb are discarded

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Human chromosome

Mouse chromosomes

Mouse chromosomes

SyntenyView

Orthologues

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CytoView

Syntenic blocks

Orientation Chromosome

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