The Genome Gamble, Knowledge or Carnage?

1
The Genome Gamble, Knowledge or Carnage?

• Comparative Genomics Leading the Way _at_ Organon

Tim Hulsen, Oss, November 11, 2003
2
Summary

• (1) An introduction to orthology and paralogy
• (2) Orthology determination within eukaryotes
• (3) Testing the advantages of our ortholog set
• (4) Using evolutionary conservation of
  co-expression for function prediction
• (5) Evolutionary conservation of chromosomal
  distance and orientation

3
(1) An introduction to orthology and paralogy

• Homologous genes genes that have a common
  ancestor
• Orthologous genes genes that evolved from a
  common ancestor through a speciation event (?
  equivalents in different species)
• Paralogous genes genes that evolved from a
  common ancestor through a duplication event

4
Orthology and paralogy explained graphically
(from http//www.ncbi.nlm.nih.gov/Education/BLASTi
nfo/Orthology.html)
5
The importance of orthology and paralogy

• Orthology relationships especially important for
  function prediction orthologous genes generally
  have the same function but in different species
• Paralogy relationships can be used for function
  prediction too paralogous genes are often
  involved in the same process, but have different
  molecular functions (e.g. globins)

6
(2) Orthology determination within eukaryotes

• Not much eukaryotic orthology available at this
  moment
• euKaryotic Orthologous Groups (KOG,NCBI)
• Inparanoid
• OrthoMCL
• Existing databases are either too inclusive or
  too restrict
• Most methods rely on best bidirectional hit
  (E-value), while orthology is an evolutionary
  principle.. should be determined using
  phylogenetic trees!

7
Our orthology determination
within eukaryotes

• Hs
• 
  At, Ce, Dm, Ec, Gt, Hs, Mm, Sc, Sp
• Zgt20, RHgt0.5QL
• 24,263 groups

GENOME
Hs-Mm 85,848 pairs Hs-Dm 55,934 pairs etc.
TREE SCANNING
8
Our orthology determination using phylogenetic
trees

• Example BMP6 (Bone Morphogenetic Protein 6) ? 5
  orthologous relations are defined, all Hs-Mm

9
The ortholog database Eukaryortho
http//t2.teras.sara.nl4086
(only accessible from Organon, CMBI and SARA)
10
(3) Testing the advantages of our ortholog set

• Quality of orthology difficult to test
• Orthologs should have more or less the same
  function --gt use conservation of function as an
  orthology benchmark
• Gene Ontology (GO) database hierarchical system
  of function and location descriptions
• Orthologs are in same functional category when
  they are in the same 4th level GO Molecular
  Function class

11
GO molecular function benchmark

• 0
• 1
• 2
• 3
• 4
• Molecular function one of the three subroots
  (together with biological process and cellular
  location)
• True orthologs should share a 4th level
  molecular function (here GO0019912)
• Our Hs-Mm ortholog set 67
• KOG Hs-Mm ortholog set 51

12
Co-expression benchmark

• Second method comparing expression profiles of
  each orthologous gene pair
• Using GeneLogic Expressor data set
• Human chips 3269 samples, 44792 fragments, 115
  tissue categories, 15 SNOMED tissue categories
• Mouse chips 859 samples, 36701 fragments, 25
  tissue categories, 12 SNOMED tissue categories

13
SNOMED tissue categories used for co-expression
calculation
HUMAN MOUSE
1 Blood vessel 1 Blood vessel
2 Cardiovascular system 2 Cardiovascular system
3 Digestive organs 3 Digestive organs
4 Digestive system 4 Digestive system
5 Endocrine gland -
6 Female genital system 5 Female genital system
7 Hematopoietic system 6 Hematopoietic system
8 Integumentary system 7 Integumentary system
HUMAN MOUSE
9 Male genital system 8 Male genital system
10 Musculoskeletal system 9 Musculoskeletal system
11 Nervous system 10 Nervous system
12 Product of conception -
13 Respiratory system 11 Respiratory system
14 Topographic region -
15 Urinary tract 12 Urinary tract
14
Calculating the correlation

• N?xy (?x)(?y)
• r ----------------------------------------------
  ---
• sqrt( (N?x2 - (?x)2)(N?y2 (?y)2) )

Human gene 1 206316_s_at Mouse gene 1 162926_at Tissue category Human gene 2 205428_s_at Mouse gene 2 97166_at
41.04 83.56 1 62.95 49.11
30.78 61.11 2 67.72 45.18
74.73 92.95 3 93.2 40.76
43.9 78.85 4 68.48 41.2
39.23 88.93 5 54.8 41.24
88.72 100.7 6 52.16 49.64
39.71 83.15 7 73.56 42.84
135.42 169.28 8 46.59 49.58
55.98 79.91 9 205.58 0
0 59.05 10 142.9 34.7
54.78 97.37 11 48.57 48.04
68.11 87.85 12 48.97 46.26
? High correlation 0.914167 ? High correlation 0.914167 ? Low correlation -0.935731 ? Low correlation -0.935731
15
Co-expression comparison of our ortholog set to
the KOG set
16
(4) Using evolutionary conservation of
co-expression for function prediction
Human
Gene A Gene B
Co-expression Cab (-1ltcorr.lt1)
(Co-expression calculated over 115 tissues in
human, 25 in mouse)
Human/Mouse
Gene A Gene B
Cab gt Cab
? Increases probability that A and B are involved
in the same process
17
GO biological process benchmark

• 0
• 1
• 2
• 3
• 4
• Biological process one of the three subroots
  (together with cellular location and molecular
  function)
• Both orthologs and paralogs are often involved in
  the same process/pathway (sharing a 4th level
  biological process, here GO0007584)

18
Conservation of co-expression used in function
prediction
19
The importance of (conserved) co-expression for
function prediction

• Co-expression without conservation can already be
  used for function prediction
• Paralogous conservation gives a 2x higher
  accuracy
• Orthologous conservation gives a 3x or 4x higher
  accuracy
• Alternative for GO Biological Process KEGG
  Pathway database ? similar results

20
(5) Evolutionary conservation of chromosomal
distance and orientation
Human
Gene A Gene B
Distance Dab ( bp) Orientation Oab
(??,??,??) Co-expression Cab (-1ltcorr.lt1)
Dab lt Dab Oab Oab Cab gt Cab
(Co-expression calculated over 115 tissues in
human, 25 in mouse)
Human/Mouse
Gene A Gene B
? Increases probability that A and B are involved
in the same process
21
Function prediction using co-expression and
chromosomal distance (without conservation)
22
Conservation of chromosomal distance used in
function prediction
23
The importance of chromosomal distance and
orientation for function prediction

• Chromosomal distance in eukaryotes less important
  than in prokaryotes (due to the absence of
  operons)
• Only genes with distance lt 1 Mbp seem to be
  coregulated
• Conservation of relative orientation seems to be
  important only for very close gene pairs
• Limited number of genes can be functional
  annotated using the conservation of chromosomal
  distance and orientation

24
Conclusions

• Orthologous and paralogous relations can be used
  to improve function prediction
• Our orthologous pairs of Protein World proteins
  perform better than KOG, in terms of
  co-expression and involvement in the same process
• Chromosomal distance and relative orientation
  between genes can be used for function prediction
  too, in a limited number of cases
• Future plans find examples where the function of
  a protein can be predicted using these methods

25
Credits

• Martijn Huynen
• Peter Groenen
• Others at Comics
• Others at Organon Bioinf.