Genetic Networks - Systems Biology Concepts and Insights - page 114

phenotypic signature indicative of gene function [3] .As
a result, grouping genes according to their genetic inter-
action profiles, using standard clustering algorithms [31] ,is
an effective and powerful way to precisely predict gene
function [3] ( Figure 6.1B ).
Genetic interaction profile similarity has been expanded
beyond synthetic lethal interaction profiles to include
profiles derived from large-scale quantitative screens
composed of both negative and positive interactions
( Figure 6.1B ). These quantitative genetic interaction
profiles enabled the construction of a global network in
which genes with similar interactions patterns are located
next to one another while genes sharing less similar inter-
action profiles are further apart in the network [2] . The
resulting network provides a multi-scale view of the func-
tional organization within a cell ( Figure 6.2 ). Globally,
genes displaying tightly correlated profiles formed large
and readily discernable clusters corresponding to distinct
biological processes ( Figure 6.2A ). The relative distance
between these clusters appeared to reflect shared functions
highlighting the interdependencies of general cellular
processes and the inherent functional organization of
the cell. When observed in greater resolution, the genetic
map enables dissection of broad biological processes
into

but rather in larger 'blocks' that define specific functional
modules ( Figure 6.1B ). For example, three genes, A, B and
C, belonging to the same pathway or protein complex,
should exhibit negative genetic interactions with a second
pathway or complex composed of genes X, Y and Z if both
pathways/complexes regulate a common essential function
( Figure 6.3A ). In general, this local network structure
reveals genes that belong to the same functional module and
the genetic relationships between separate modules that
share partially redundant functions. Compromising the
function of either non-essential module leaves the cell
viable, but simultaneously compromising both results in cell
death ( Figure 6.3A ). This relationship is aptly illustrated by
genetic interactions between the Elongator (ELP) complex
and the evolutionarily conserved URMylation pathway,
revealing that these functional modules share distinct yet
redundant roles in tRNA processing [33] . Several previous
studies have highlighted the prevalence of this type of
structure based on systematic mining of genetic interaction
networks in S. cerevisiae, and it has been referred to as
a 'between-pathway' network structure [18,34 36] .A

recent survey of the yeast genetic network revealed that 58%
of observed negative genetic interactions appear in struc-
tures involving at least nine total interactions (a minimum
3

e

distinct yet interdependent gene functions 3 gene matrix) ( Figure 6.3B ) and estimated that the true

fraction may be as high as 75% if experimental false nega-
tives and false positives are taken into account [36] .
This modular structure suggests a fundamental prin-
ciple of genetic redundancy: redundancy between genes
appears to be more frequently the result of module-level
compensation rather than single gene buffering, at least for
yeast. The alternative situation is where redundancy is
mainly encoded at the single gene level, which would
instead produce mostly isolated negative interactions
throughout the genome. It should be noted that while the
latter case appears to be infrequent, at least in the context of
the yeast genome [36] , there are instances where single
gene redundancy produces negative genetic interactions,
particularly among pairs of gene duplicates (see Genetic
Interactions as a Means of Studying the Evolution of Gene
Duplicates). The degree to which module-level redundancy
extends beyond yeast to genetic networks of higher
eukaryotes remains unclear. Nonetheless, we anticipate that
the functional relationships between modules may be
conserved, and a detailed understanding of network struc-
ture may ultimately affect our ability to assess the conser-
vation of genetic networks.
In addition to the 'between-pathway' structure, another
type of genetic interaction network motif includes a set of
negative interactions that connect a common set of genes
(a 'clique-like' structure in graph theory terms). In this
structure, known as 'within-pathway', a set of genes (D, E and
F) all exhibit negative genetic interactions with each other
( Figure 6.3A ). Although the within-pathway structures

( Figure 6.2B C ). In one region of the global network,

separate gene clusters involved in various processes such as
DNA replication, recombination and repair, microtubule
biogenesis, RNA processing and RNA decay are readily
distinguishable ( Figure 6.2B ). Finally, at its most detailed
level and consistent with theoretical studies [32] , the
network is composed of highly organized modules corre-
sponding to discrete biological pathways and/or protein
complexes connected almost exclusively by a single type of
genetic interaction (only negative or only positive interac-
tions) and reveals a functional wiring diagram of the cell
( Figure 6.2D

e

E ). At this level of scrutiny, the modular
organization of the genetic network also enables precise
functional predictions for previously uncharacterized
genes. Indeed, genetic analysis implicated three novel
genes in the regulation of the general amino acid permease,
GAP1 [2] ( Figure 6.2E ).

e

EXPLORING GENETIC INTERACTION
NETWORKS

Modular Network Structures Identify
Functional Relationships between Pathways
and Complexes
The ability of genetic interaction profiles to define func-
tionally coherent clusters is possible because these networks
are highly structured: interactions rarely occur in isolation