Biology Reference
In-Depth Information
curated in public databases, most obviously in WormBase
[76,77]
, and now any researcher interested in a specific
gene can, within a few clicks, identify the set of known
RNAi phenotypes for that gene as well as identifying all
other genes that share similar RNAi phenotypes; for around
1000 genes one can even view detailed time-lapse movies
showing the effect of removing that gene on early
embryogenesis. This wealth of functional data is a source
for many systems-level analyses, several of which are
covered in subsequent sections.
Despite the power of RNAi, no technology is perfect
and no screen is ideal
yield the same RNAi phenotype (thus excluding any
possibility of off-target effects) or, more convincingly, by
confirming any RNAi phenotype by using a genetic mutant.
In this regard, the large-scale ongoing efforts to generate
loss-of-function genetic alleles for all C. elegans genes are
immensely useful. These methods either use random
mutagenesis and PCR-based methods to identify substan-
tial deletions within coding regions (and thus presumptive
null alleles) (reviewed in
[85]
) or, more recently, efforts are
under way to use the immense power of next-generation
sequencing to identify nonsense mutations in each and
every gene following high doses of mutagen treatment
[86]
.
Together with pre-existing alleles isolated in forward
genetic screens and freely available from the C. elegans
stock center (CGC, https: //cgcdb.msi.umn.edu/), such
mutant collections mean that for a large proportion of hits
in any RNAi screen, one can simply order the corre-
sponding deletion allele; combining this with Mos1-based
methods, it is possible to extend this to follow up essen-
tially all the hits from any RNAi screen with genetic
mutants in a fairly rapid manner, a major advance for the
field. Note that in this chapter we have not discussed in any
depth the impact that these deletion collections have made
on C. elegans systems biology, since to date there has been
little systematic phenotypic characterization of these
deletion lines beyond the identification of essential genes,
but this is likely to come in the future. For now, being able
to move rapidly from finding a hit in an RNAi screen to
getting a genetic mutant in that gene simply by sending an
email is already a huge impact.
RNAi screens provide a rapid way to systematically
assess gene function in vivo, and it is worth returning
briefly to compare their strengths with classical genetics
screens. Classical genetics screens had several problems
discussed above: the difficulty of examining the roles of
essential genes in early embryogenesis due to maternal
contribution; difficulty in assessing saturation; and
complications arising from genetic interactions, both
because of problems with de novo identification of
synthetic genetic interactions and because of difficulties in
assessing the specificity of genetic interactions. RNAi, in
each of these areas, is highly complementary to classical
genetics. First, RNAi targets all mRNAs whether derived
maternally or zygotically. RNAi is thus an ideal tool to
investigate the roles of all genes in the key processes of
early embryogenesis. Several groups have carried out
genome-scale screens to identify all genes required for
early embryogenesis, and have gone on to examine in great
detail the precise nature of their role through time-lapse
observation of developing embryos
[64,87
false positives and false negatives
can confound many systems analyses if they are not
measured. In a typical RNAi screen the false negative rate
can be estimated based on recovery of previously known
genes
e
typically false negative rates are ~50%
[66]
.For
some screens this is higher, either because of the difficulty
of the assay or because the process being examined is
partially refractory to RNAi. Certain tissues, most specifi-
cally neurons, are partially protected from RNAi
[66]
owing to reduced efficiency in dsRNA uptake, and this
leads to a greater false negative rate due to insufficient
knockdown. These issues can be largely circumvented,
however, either by using mutants that have increased RNAi
efficiency such as rrf-3
[78]
or lin-35
[74,79]
or by engi-
neering worms to increase dsRNA uptake in neuronal
tissues
[80]
. The intrinsic false positive rate of RNAi in the
worm appears very low
e
estimates from genome-scale
RNAi screens place the level of false positives due to off-
target effects that cannot be trivially excluded at well under
5%
[66]
. At first sight this appears puzzling, given the large
confounding issues with off-target effects in mammalian
RNAi screens. However, RNAi in mammals and RNAi in
worms are fundamentally different. In mammals, typically
a single siRNA (or at best a small pool) is used to target
a transcript in any individual assay
[81]
; that siRNA affects
more transcripts than the intended target and hence has off-
target effects at the concentrations required to generate
efficient knockdown. In the worm, however, the dsRNAs
used to target a gene are large, typically in the range of
1
e
84]
to yield a complex mix of siRNAs. Each siRNA has
a different set of off-targets; all share the same 'true' target.
The key is that unlike in mammals, where an individual
siRNA is delivered at concentrations sufficient to generate
knockdown, in the worm any single siRNA is present at
extremely low concentrations
e
1.5 kb
e
these were processed in vivo by Dicer
[82
e
knockdown is achieved by
the additive effect of all siRNAs. In this way off-targets are
at undetectable levels (since off-targets are siRNA-
specific), whereas knockdown of the intended target is
efficient (since all siRNAs target the same transcript).
As with any screening technology, hits need to be
validated, which can either be done quickly by testing that
two non-overlapping dsRNAs targeting the identified hit
e
90]
. In this way
the exact defects leading to embryonic lethality can be
pinpointed
e
polarity defects, cytokinesis failures, errors in
spindle orientation and so on. This level of detail has
allowed the construction of complex models of
e
the
