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Detecting Orthologs
Using Molecular
Phenotypes
a case study: human and mouse
Alice S Weston
What is a “molecular phenotype”?

mRNA expression patterns

detected using microarray techniques

can reveal the co-expression of two
genes in the same tissue or sample
Hypothesis
It is speculated that orthologous genes
between Human and Mouse will be coexpressed with a similar set of partners
compared to a pair of non-orthologous genes
that are similar at the sequence level.
Why do we care?

categorize the biological function of
mammalian core proteins

learn about the similarity of genes with
little sequence homology

see how orthologous genes have
changed since their divergence
evolutionary sequence
changes can mask orthologs
BLAST hit #2
true ortholog!
BLAST hit #1
paralog
active site
coding region
= mutation
Methods
calculated Spearman correlations
 used z-Fisher transform because of
missing data—consider dimension
 built co-expression neighborhood for
each human gene (center), 100 each
 found related genes in neighborhoods
of top two BLAST hits in mouse for
the central human gene

Example
6814
7375
8888
10270h
51763
9092
9646
20912
20912
22258
22258
54387
54387
54194m
56399m
19062
19062
20227
22083
BLAST hit #1
20227
22083
BLAST hit #2
Methods (cont.)
determined the ranks of the neighbors
in relation to their central mouse gene
 used a sign system to tell which
mouse gene was more co-expressed
with the human gene


asked: Are there any instances where
BLAST hit #2 is the true ortholog?
Results
Comparison of Neighbor Gene Ranks for Top Two Mouse Genes
600
400
300
200
100
Rank
Mouse Gene 1
Mouse Gene 2
496
481
466
451
436
421
406
391
376
361
346
331
316
301
286
271
256
241
226
211
196
181
166
151
136
121
106
91
76
61
46
31
16
0
1
Number of Genes
500
Results
Percentage of Neighbor Genes that Ranked Better in Top Mouse Gene
120
100
80
60
40
20
Percentage of Neighbor Genes
100
96
92
88
84
80
76
72
68
64
60
56
52
48
44
40
36
32
28
24
20
16
12
8
4
0
0
Number of Top Mouse Genes
140
Results
cases where the second best mouse gene
in BLAST has the best co-expression with
the human gene
 the best mouse gene in BLAST has the
best co-expression with the human gene
~62.9% of the time
 results look promising if sample size is
increased

problems along the way….
not enough microarray co-expression
data to rank most of the neighbors
 some human genes have no predicted
orthologs in mouse—for building mouse

neighborhoods

limited sample size: some human
genes do not have two orthologs in
mouse—to test hypothesis
….solutions
do more microarray experiments,
increase amount of data
 compare human genes to another
species with more known orthologs

Acknowledgments
Josh Stuart
Reading:
Barak A Cohen, Yitzhak Pilpel, Robi D. Mitra, and George M. Church.
(2002) Discrimination between Paralogs using Microarray Analysis:
Application to the Yap1p and Yap2p Transcriptional Networks.
Molecular Biology of the Cell. 13, 1608 – 1614.
Happy
Spring Break!!!