Greg Carter Galitski Lab Institute for Systems Biology (Seattle)

Greg Carter

Galitski LabInstitute for Systems Biology (Seattle)

Maximal Extraction of Biological Information from

Genetic Interaction Data

Genetic Interaction

Pairwise perturbation

two genes combine to affect phenotype

Hereford & Hartwell 1974

Measure a phenotype for 4 strains:

1. Wild-type reference genotype

2. Perturbation of gene A

3. Perturbation of gene B

4. Double perturbation of A and B

• Loss-of-function, gain-of-function, dominant-negative, etc.

• Interaction depends on phenotype measured.

Example: flo11 and sfl1 for yeast invasion.

WT flo11 sfl1 flo11sfl1

pre-

was

hpo

st-w

ash

Invasion Assay

~2000 interactions measured

(Drees et al, 2005)

Genetic Interaction

45 possible phenotype inequalities

Classified into 9 rules (Drees, et al. 2005)

Classification of Interactions

WT=A=B=AB, WT=A<B=AB, A=B=WT<AB, A<B<WT=AB, AB<A<WT=B, WT=A=AB<B, WT=A=AB<B, A<B<WT<AB, etc…

Distribution of Rules

2000 interactions among 130 genes

Yeast Invasion Network

Extracting Biological Statements

Statistical associations of a gene interacting with a function

PhenotypeGenetics plug-in for Cytoscape

www.cytoscape.org

WT=A=B=AB, WT=A<B=AB, A=B<WT<AB, A<B<WT=AB, AB<A<WT=B, WT=A=AB<B, WT=A=AB<B, A<B<WT<AB, etc…

?

Can the 45 interactions be classified in a more informative way?

How many rules?

Distribution of interactions?

Classification Problem

Requirements for a complexity metric :

1. Adding a gene with random interactions adds no information

2. Duplicating a gene adds no information

3. Should depend on

(i) the information content of each gene’s interactions, and

(ii) the information content of all gene-gene relationships.

General requirements for biological information (see poster).

Context-dependent Complexity

= Ki mij (1 – mij )

Ki is the information of node i,

mij is the mutual information between i and j,

0 ≤ mij ≤ 1and

0 ≤ ≤ 1

Applied to (see poster):

• Sets of bit strings (sequences)• Network architecture• Dynamic Boolean networks• Genetic interaction networks…

pairs ij

Context-dependent Complexity

Genetic Interaction Networks

• Invasion network of Drees, et al. Genome Biology 2005

130 genes, 2000 interactions

• MMS fitness network of St Onge, et al. Nature Genetics 2007

26 genes, 325 interactions

Determined networks of maximum complexity .

Network Classification Scheme

Invasion Data MMS Fitness Data

biological

statements

biological statements

Drees, et al. 0.57 52 0.27 28Segré, et al. 0.52 47 0.32 19St Onge, et al. - - 0.16 10Maximum 0.79 72 0.62 32

Complexity and Biological Information

Number of biological statements is correlated with

115k possible MMS fitness networks, r = 0.80

Genetic Interaction Networks

Maximally complex MMS fitness network

Rule Frequency InequalitiesClassical Interpretation

(Drees et al. 2005)

1 120 PAB = PA < PB < PWTepistatic

2 55 PAB < PA = PB < PWTadditive

3 92 PAB < PA < PB < PWTadditive

4 30PAB = PA = PB < PWT

PAB = PA < PB = PWT

asynthetic

non-interactive

5 26

PAB < PA = PB = PWT

PA < PAB = PB < PWT

PAB = PA = PB = PWT

PAB < PA < PB = PWT

PA < PAB < PB < PWT

synthetic

epistatic

non-interactive

conditional

single-nonmonotonic

gene interacts via with genes P

SGS1 Rule 5 error-free DNA repair 0.00014

SWC5 Rule 2 error-free DNA repair 0.00056CSM2 Rule 4 error-free DNA repair 0.0026

SHU2 Rule 4 error-free DNA repair 0.0030SHU1 Rule 4 error-free DNA repair 0.0065

Genetic Interaction Networks

Biological statements from the

maximally complex MMS fitness network

gene interacts via with genes P

PSY3 Rule 1 meiotic recombination 0.0011

St Onge, et al. Figure 5d

Conclusion and Future Work

For a given data set, maximizing facilitates unsupervised, maximal information extraction by balancing over-generalized and over-specific classifications schemes.

Need network-based methods to interpret the maximally complex interaction rules. Interpretations will depend on the system, specific to phenotype measured and perturbations performed.

See poster for more details

Becky DreesAlex Rives

Marisa RaymondIliana Avila-Campillo

Paul ShannonJames TaylorSusanne Prinz

Vesteinn ThorssonTim Galitski

Matti NykterNathan Price

Ilya ShmulevichDavid Galas

Thanks to