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DEVELOPMENTAL DYNAMICS 235:2412–2423, 2006
SPECIAL ISSUE REVIEWS–A PEER REVIEWED FORUM
Uncovering the Uncharacterized and
Unexpected: Unbiased Phenotype-Driven
Screens in the Mouse
Tamara Caspary1* and Kathryn V. Anderson2
Phenotype-based chemical mutagenesis screens for mouse mutations have undergone a transformation in
the past five years from a potential approach to a practical tool. This change has been driven by the relative
ease of identifying causative mutations now that the complete genome sequence is available. These
unbiased screens make it possible to identify genes, gene functions and processes that are uniquely
important to mammals. In addition, because chemical mutagenesis generally induces point mutations, these
alleles often uncover previously unappreciated functions of known proteins. Here we provide examples of
the success stories from forward genetic screens, emphasizing the examples that illustrate the discovery of
mammalian-specific processes that could not be discovered in other model organisms. As the efficiency of
sequencing and mutation detection continues to improve, it is likely that forward genetic screens will
provide an even more important part of the repertoire of mouse genetics in the future. Developmental
Dynamics 235:2412–2423, 2006. © 2006 Wiley-Liss, Inc.
Key words: chemical mutagenesis; N-ethyl; N-nitrosourea; ENU; mammalian forward genetic screens
Accepted 26 April 2006
INTRODUCTION
Positional cloning projects in the
mouse discouraged some of the most
tenacious postdoctoral fellows and
graduate students in the 20th century. But no more. Thanks to the
availability of complete genome sequence, it is as straightforward to
identify mutations responsible for interesting phenotypes in the mouse as
it is in yeast, flies, and worms. The
techniques developed in the 1980s
that made it possible to manipulate
the mouse genome at will through homologous recombination allowed scientists to test their hypotheses about
gene function directly and revolutionized mouse genetics (Robertson et al.,
1986; Thomas and Capecchi, 1987;
Doetschman et al., 1988). After the
completion of the genome sequence, it
became straightforward to locate
point mutations induced by random
mutagenesis, further accelerating the
discovery of gene function. Forward
screens have become a common, complementary approach for the generation of mutations in mouse labs worldwide.
The current popularity of phenotype-based genetic screens in mouse is
driven by their ability to ask mammalian-specific questions and to learn
about unsuspected aspects of mammalian biology. As fewer than 10% of
the 30,000 genes in the mouse genome
1
have been characterized functionally,
it is still a daunting task to identify
the genes that regulate a particular
biological process of interest (Austin
et al., 2004). The strength of chemical
mutagenesis is that dozens of randomly-induced, gene-inactivating mutations can be screened simultaneously
and those rare mutations that affect
the process of interest can be identified on the basis of their phenotype.
An explosion of recent reviews that
describe mammalian forward genetic
screens reflects their current popularity. As these reviews describe the basic methods used in forward genetic
screens, including the types of screens
that can be done, the sophisticated
Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia
Developmental Biology Program, Sloan-Kettering Institute, New York, New York
*Correspondence to: Tamara Caspary, Department of Human Genetics, Emory University School of Medicine, 615 Michael St.,
Suite 301, Atlanta, GA 30322. E-mail: [email protected]
2
DOI 10.1002/dvdy.20853
Published online 24 May 2006 in Wiley InterScience (www.interscience.wiley.com).
© 2006 Wiley-Liss, Inc.
FORWARD GENETIC SCREENS IN THE MOUSE 2413
TABLE 1. Acceleration in the Generation of New ENU- Induced Alleles Has Outpaced That of Targeted Cells in
the Past 5 Yearsa
ENU alleles (affected genes)
All targeted alleles (affected genes)
Targeted knockout alleles (affected genes)
a
December 2001
January 2006
Fold increase
168 (83)
3,252 (1,188)
2,551 (1,335)
1,197 (1,023)
8,081 (4,037)
5,413 (3,537)
7.1 (12.3)
2.5 (3.4)
2.1 (2.6)
Source: curator assisted search of MGI database, request 24263.
manipulations one can build into a
screen to facilitate mapping, and the
benefits of having a easily discernible
phenotype, we will not focus on those
topics (for examples, see Clark et al.,
2004; Hoebe and Beutler, 2005; Kile
and Hilton, 2005; Papathanasiou and
Goodnow, 2005). Here, we first illustrate how genome sequence information provides a molecular grounding
for mouse forward genetics and then
focus on the new aspects of biology
that have been revealed in these
screens.
MUTANTS AND MORE
MUTANTS
Phenotype-based genetic screens start
by treating male mice of a specific
strain with a chemical mutagen, most
commonly N-ethyl, N-nitrosourea
(ENU), which generally induces single
nucleotide substitutions. These mice
are bred for one to three generations,
depending on whether dominant or recessive phenotypes are sought, and a
phenotype of interest is identified. In
order to find the causative mutation, a
mapping cross must be performed
with a different strain of mouse. By
using molecular markers that distinguish between the strain on which the
mutation was generated and the
strain used in the mapping cross, a
chromosomal location of the mutation
can be found. To narrow the interval
in which the mutation lies, additional
recombinant animals are generated,
scored for inheritance of the phenotype of interest, and the recombination breakpoints are defined with
polymorphic DNA markers. Finally,
when the interval is sufficiently narrowed, the open reading frames in the
interval are sequenced to identify the
causative mutation. In most cases, the
analysis of the mutant phenotype can
be completed at the same time the
affected gene is identified. For detailed information on methods, see
Justice (2000) and Taylor (2000).
ENU is a potent mutagen. The most
effective dose of ENU (that induces
the most mutations with the least lethality) creates one mutation every
0.1–1 MB, based on direct sequencing
data (Beier, 2000; Concepcion et al.,
2004; Sakuraba et al., 2005), or
roughly 3,000 nucleotide changes per
genome. The vast majority of these
mutations lie in non-coding DNA and
do not affect gene function. When
seven loci with visible phenotypes
were examined, ENU generated one
gene-inactivating mutation per locus
in 700 F1 progeny (the specific locus
test; Hitotsumachi et al., 1985). More
recent large-scale screens have not
uncovered multiple allele of single
genes as the 1/700 rate would predict
(Kile et al., 2003). It has been estimated that the average mutation rate
is likely to be half the rate seen in the
specific locus test, on the order of one
mutation per locus in 1,500 F1 progeny (Wilson et al., 2005). Knowing
there are !30,000 mouse genes, each
F1 animal in a forward genetic screen
is heterozygous for !20 gene-inactivating mutations, so that even a
small-scale screen can scan a meaningful number of functional mutations; for example, a screen of 150
lines would sample !10% of the genome.
The acceleration in the generation
of new ENU-induced alleles has outpaced that of targeted alleles in the
past five years (Table 1). According to
Mouse Genome Informatics at the
Jackson Laboratory, there were ENU
alleles of 83 genes in 2000. Today
there are ENU alleles of 1,023 genes,
more than 12 times as many. During
the same time period, the number of
genes targeted as knockout mutations
have increased less than threefold
from 1,335 to 3,537. There is some
overlap between the ENU-induced alleles and the targeted knockout alleles: 74 genes currently have alleles
in both categories (Table 2). The ENUinduced alleles have been found both
by chance and in directed searches for
new alleles of previously characterized genes (Vivian et al., 2002). Several of the ENU-induced alleles are
partial loss-of-function mutations that
have uncovered previously unappreciated functions of characterized genes
(see below).
Compared to the number of labs
that use reverse genetics, relatively
few labs are working with the existing
chemically induced alleles. Indeed,
the majority of the 1,000" ENU-induced alleles in the database have not
been studied in detail and are not yet
cloned. Hopefully, as researchers realize how tractable positional cloning
has become and that many of the
chemically induced alleles are publicly available, these mutations will be
characterized. Two main issues dissuade many from trying to clone such
mutations: the ability to locate a mutation that is likely to be responsible
for the phenotype and, subsequently,
being able to prove that mutation is
responsible for the phenotype of interest. Complete genome sequence information has made it straightforward to
identify the putative mutation (see below). There are several ways to prove
that a mutation that lies in the correct
genomic interval is responsible for the
phenotype: demonstrating the affected protein is absent or inactive;
rescuing the phenotype by introduction of a wild type copy of the gene; or
by performing a complementation test
with another mutant allele. Until recently, there have not been mutant
alleles of most mouse genes available,
but the increased number of publicly
available gene trap alleles, and the
2414 CASPARY AND ANDERSON
TABLE 2. Seventy-four Genes in the MGI Database That Have Both Chemically Induced and Targeted
Knockout Alleles Are Listed by Their Gene Abbreviation With the Number of Alleles Available in the
Respective Categories Specifieda
a
Gene
Chemically
induced
allele(s)
Targeted
knockout
allele(s)
Aff1
Apc
Cacn#1a
Cacn#2d2
Card11
Cd36
Cd83
Celsr1
Col4a1
Cry#a
Disp1
Dmd
Dst
Dync1h1
Egfr
Emx2
Fah
Fech
Foxf2
Frap1
Gck
Ggt1
Gja1
Gja8
Gjb2
Gna11
Gnaq
Gnas
Grid2
Hb#
Hb%
Hr
Ift88
Itpkb
Jag1
Jak3
Kcne1
1
1
2
1
1
1
1
2
4
1
1
4
4
2
3
1
2
1
1
1
12
1
1
2
3
1
2
2
1
2
4
1
1
1
3
1
1
1
6
2
1
2
2
1
1
1
1
4
2
1
1
3
2
1
1
1
2
4
1
2
1
1
1
2
9
1
1
2
1
1
1
2
4
1
Gene
Chemically
induced
allele(s)
Targeted
knockout
allele(s)
Kcnj11
Kcnq1
Kif3a
Lama2
Lepr
Myb
Nf$B2
Npr3
Pax3
Pax6
Pkd1
Plcg2
Pmp22
Polq
Pten
Ptprc
Rab3a
Rasgrf1
Rgs2
Rs1h
Rxr#
Ryrt
Slc4a1
Smad2
Smad4
Smo
Spn%4
Stat1
Tbx6
Tcfap2#
Ticam1
Tlr9
Trp53
Twist1
Zfpm2
Zfpn1a1
Zic2
2
1
1
1
1
3
1
1
2
21
1
1
3
1
1
1
1
2
2
1
1
1
1
1
4
1
1
1
1
1
1
1
2
3
1
1
1
2
4
2
1
2
2
4
1
1
2
5
1
1
1
4
3
1
9
1
1
5
1
2
9
5
2
1
2
1
2
1
1
7
1
2
2
1
Source: Mouse Genome informatics at http://www.informatics.jax.org.
promise of additional alleles from the
Knock Out Mouse Project (KOMP),
now makes the identification of a second allele the approach of choice to
confirm gene identity (Austin et al.,
2004; Raymond and Soriano, 2006). In
addition, the existence of ENU-induced mutations should help guide
the choice of which gene traps and
knockout cell lines should be made
into mice. This and other uses of gene
trap alleles are discussed in great
depth in “Engineering Mutations: Deconstructing the Mouse Gene by
Gene” on page 2424 of this issue (Raymond and Soriano, 2006).
The driving force behind the explosion in the number of ENU alleles
available is the compelling biology
that can be discovered; forward and
reverse genetics differ in what we
learn. Reverse genetics is constrained
by the ability to infer what a gene does
based on its sequence and by the interest of a researcher in the process it affects. While it is likely that all knockout
mice do have a phenotype if one looks
hard enough, many targeted mutations
that do not have the predicted phenotype are not adequately analyzed because their phenotypes are outside the
area of expertise of the investigator.
The success of forward genetic
screens stems from the starting point
being the disruption of a process of
interest, and the ability to identify a
set of genes that all affect a common
process. By using forward genetics in
the mouse, researchers have been able
to ask questions they couldn’t ask in
other genetic model organisms such as
those related to adaptive immunity,
FORWARD GENETIC SCREENS IN THE MOUSE 2415
behavior, fertility, and organogenesis.
For mutations that affect early development, the effects of single gene mutations are often more striking in the
mouse than in zebrafish, the other favorite model for vertebrate genetics,
because zygotic transcription starts
early in mouse development and there
is little maternal contribution to
postimplantation development. Finally, even in well-studied processes,
ENU-induced mutations have uncovered mammalian-specific steps and
proteins that have never been suspected. Thus, the discoveries being
made with forward genetics are unprecedented and exciting both because of the questions being asked
and the surprises provided by biology.
THE RISE OF THE
FOCUSED PHENOTYPEBASED SCREEN
In the past, mouse forward genetic
screens were only performed at large
centers such as Oak Ridge National
Laboratory, The Jackson Laboratory,
the GSF Research Center, and Harwell (Hrabe de Angelis et al., 2000;
Nolan et al., 2000). Recently, many
mutations have been made by small
labs that are interested in specific biological questions. Such grass-roots
screens are performed on a small scale
in terms of cage numbers and cost and
have proven to be cost-efficient. In
some cases, these screens have been
carried out in individual labs (Kasarskis et al., 1998; Herron et al., 2002;
Zarbalis et al., 2004; Garcia-Garcia et
al., 2005; Hoebe and Beutler, 2005;
Papathanasiou and Goodnow, 2005).
In other cases, collaborations among
neighboring labs that are interested
in complementary phenotypes have
been particularly productive (Pask et
al., 2005; Timmer et al., 2005;
Kennedy et al., 2006).
Based on our rough calculations, the
time and cost to generate one mutation
is about the same in forward and reverse genetic approaches. Using reverse
genetics, once a targeting construct is
built, it takes approximately one year to
target a gene and to breed the allele to
homozygosity. Subsequently, the phenotypic analysis can be performed. In a
forward genetic approach, once the heritability of a new mutation has been
confirmed, our experience is that it gen-
Fig. 1. Schematic of meiotic recombination opportunities in a recessive screen. Each G2 offspring
represents one meiotic recombination opportunity (from the gamete of the father); the average litter
size is 8 pups causing !8 opportunities to be analyzed per G2 generation. Each G3 animal
represents 2 meiotic recombination opportunities (from the gamete of both parents). Each breeding
pair of a wild type female and a carrier male that is set up will produce a litter every month. In a
screen for a recessive, embryonic phenotype, the G3 progeny can be screened every month
starting in month 4. Thus, each carrier male will generate one litter every month for 8 months or 320
meiotic opportunities per year. As 1,500 opportunities are needed for the causative mutation to be
identified, only five carrier males need to be set up to produce enough meiotic opportunities.
erally takes one worker less than a year
to identify the causative mutation and
analyze the phenotype. Thus, the time
to make a mutation in a defined gene is
similar in the two methods, while the
forward genetic approach guarantees a
phenotype that affects the biological
process of choice.
Labs that routinely do their own
targeting and ES cell injection inhouse can generate chimeras for
around $3,000. Those that generate a
construct and use a facility to perform
the targeting in cell culture and the
subsequent injection pay upwards of
$4,000. Companies that provide allinclusive services, from construct design to the delivery of a germ line
transmitting line, offer packages that
start around $20,000.
The mouse costs associated with an
identification of the mutation responsible for an ENU-induced phenotype
can also be estimated with reasonable
precision. Gene identification requires
the analysis of between 1,000 and
1,500 meiotic recombination opportunities. In a recessive screen for an embryonic phenotype, for every carrier
male that is bred, 40 meiotic opportunities are analyzed using 3 cages (Fig.
1). If 5 carrier males are set up, within
the year their G3 offspring could be
analyzed for 8 months, meaning that
the 15 total cages would produce
enough offspring for !1,600 meiotic
opportunities to be analyzed. At the
same time, these same cages would
produce !4 affected offspring per generation or !160 total affected individuals for phenotypic analysis. The cost
of the 15 cages over the year would be
around $3,000 assuming cage costs of
$0.55/day. This would rise to around
$7,000 for an adult phenotype since the
G3 animals must be weaned and separated for phenotypic analysis. These
numbers fit with our own experience
and mouse care costs. Thus, the costs of
the forward and reverse approaches are
comparable, a fact that surprises many.
For more information about the logistics of mouse screen husbandry see
Siepka and Takahashi (2005).
THE POWERS OF THE
SEQUENCE
There are four major steps to identify
a causative mutation in a mutant
mouse line: (1) identification of animals carrying the phenotype of interest, (2) generation of recombinant animals, (3) narrowing the interval with
molecular markers, and (4) sequencing all of the genes in the interval. In
the past, the dearth of polymorphic
DNA molecular markers (for Step 3)
2416 CASPARY AND ANDERSON
limited an investigator’s ability to
narrow the interval and was the major
bottleneck in the identification of the
causative mutation. The primary rationale behind the genome project was
to identify the sequence of all of the
genes. But since the coding sequence is
only 1.3% of the total genome, it was
clear there would be benefits from
knowing the sequence of the other
98.7% of the genome, such as the identification of regulatory sequences and
other elements of the genome. As a bonus, the sequence of the non-coding portions of the genome has greatly aided in
positional cloning efforts because that
sequence increases the number of DNA
polymorphisms available that can be
used for genetic mapping. Now, armed
with the complete genome sequence,
one can generate mapping markers at
will, exactly where one wishes.
There are two common methods
currently used to make new mapping
markers. One way is to amplify short
repetitive sequences in the genome
and compare the size of the repeats in
the two strains of mice being used in
the mapping cross. This is similar to
how the original markers (MIT markers) were generated (Love et al.,
1990); however, instead of generating
random markers and then locating
them in the genome, researchers now
can locate a repeat and test whether it
is polymorphic. This saves time as the
researcher only generates new markers that will help them locate the mutation they are studying. In the SloanKettering mouse project, about 10% of
all repeats tested are polymorphic
between the strains C57/BL6 and
C3H/HeJ using this method (our
unpublished data, see also http://
mouse.ski.mskcc.org). The degree of
polymorphism varies depending on
the genomic location, with some regions having rates around 50%. This
method is quite inexpensive as it requires only the detection of PCR-amplified bands on agarose gels.
The other common method to find a
new marker is to identify a single nucleotide polymorphism (SNP) and detect the base pair difference. The genome projects are now focused on
strain-specific sequencing and these
“SNP reads” are becoming dense
enough to be useful in any part of the
genome in diverse strains of mouse
(Petkov et al., 2004a,b). The challenge
is no longer to find a base pair change
in a useful location; rather, it is finding a cheap method to detect that
difference. Methods such as singlestranded length polymorphism (SSLP)
analysis, or various methods incorporating the polymorphism into primer
design, are inexpensive but can be
quite laborious to implement. SNP
readers such as the Illumina or Affimatrix platforms are cheap in terms
of cost per reaction but require an upfront investment in expensive equipment. However, because the forward
genetics community is reaching a critical mass, mapping services are now
being offered (Moran et al., 2006).
Whichever type of polymorphism is
used, both define the critical interval
in which the mutation must lie. The
complete sequence means that for any
size interval, all the genes are known.
Gene density varies throughout the
genome: some large intervals contain
few genes and some small intervals
include many genes. The decision to
start sequencing genes in the interval
can be aided by the expression databases. Within a given interval, the
genes expressed in an affected tissue
receive a high priority for sequencing.
The ability to generate and analyze
sequence data has been and will continue to be the technology that allows
the cloning of ENU-induced alleles.
Our own experience reflects the power
of sequence data. The Sloan-Kettering
Mouse project had identified the molecular lesion in two lines at the beginning of 2002, when the sequence
first became readily usable; one year
later, the affected gene had been
found in 12 lines and today the number stands around 30. The future
promises to simplify and accelerate
the molecular identification of mutants further. There is a clear expectation that intervals of 1 MB will be
cheaply and quickly sequenced in the
next few years. Technological improvements promise to deliver the
$1,000 genome in a reasonable time
frame (Shendure et al., 2004, 2005;
Margulies et al., 2005; Zwick, 2005).
THE BIOLOGY OF
MAMMALS: SCREENING
STRATEGIES
The clearest justification for forward
genetics screens in the mouse is the
identification of the genes important
in mammalian-specific biological processes. Mammals develop, reproduce,
behave, nurse their young, and protect themselves from infection differently from other vertebrates. Each aspect of biology to be examined
requires specific expertise and special
screening strategies.
Immunology
Two groups have performed screens
that have provided important new information about mammalian immunity. At The Scripps Research Institute, the Beutler laboratory has
identified both dominant and recessive mouse lines with defects in the
innate immune system. The Goodnow
Laboratory at The Australian National University has designed
screens focused on the adaptive immune response.
The Beutler group exemplifies the
transition of forward genetics in the
mouse from the obsession of the few to
the tool of the many. In 1998, the lab
positionally cloned the spontaneous
mutant, Lps, and showed it was an
allele of TLR4 (Poltorak et al., 1998).
The Toll-like receptors (TLRs) are innate immune receptors that detect microbial infection in all animals. Lps
mice are susceptible to gram-negative
infection as they lack the receptor for
lipopolysaccaride (Lps). The link of
TLR4 to immunity set the stage for
the other labs to use reverse genetics
to test the role of the other TLRs in
mammalian innate immunity, highlighting the complementary nature of
forward and reverse genetics.
Since 2000, by challenging mice
from an ENU screen with a variety of
TLR stimuli, the Beutler group has
identified 56 lines with a defective innate immune response (Hoebe and
Beutler, 2005). They have mapped 17
of the lines, identified the causative
mutation in 12 lines, and three quarters of these have filled in gaps in
what is known about the innate immune system. For example, the TLR4
response to Lps had been shown to
signal through a protein called
MyD88, but its phenotype suggested
there was a MyD88-independent
pathway as well (Kawai et al., 1999).
In the course of their ongoing screen,
the Beutler lab identified Lps2,
showed it functions independently of
FORWARD GENETIC SCREENS IN THE MOUSE 2417
MyD88, and explained how distinct
stimuli could affect the same downstream pathway through distinct
TLRs (Hoebe et al., 2003a,b). This
screen has been so successful in identifying mutant lines in a single process that the Beutler group can now
estimate the total number of proteins
in the mammalian host that are involved in resisting infection (Beutler
et al., 2005).
The screen in the Goodnow lab underscores the power of forward genetics in understanding the complexity of
mammalian systems. The Goodnow
lab’s first screen identified 11 mutant
lines with defective T-cell formation
and all 11 lines have molecularly identified the responsible gene variant
(Nelms and Goodnow, 2001; Jun et al.,
2003; Papathanasiou and Goodnow,
2005). Several of these have revealed
unsuspected players. The screen identified a hypomorphic allele of Slp76,
which bypassed its earlier requirement in development and thus revealed a specific function in T-cells
(Papathanasiou and Goodnow, 2005).
Another T-cell immunity mutant affected a protein that was previously
only known for a function in chromosome maintenance (Papathanasiou
and Goodnow, 2005).
Mammalian Behavior
Although mammalian behavior is one
of the most challenging problems to
study, in 1997 the Takahashi lab at
Northwestern University published a
landmark report that used an ENU
mutagenesis approach to identify
Clock, the first single gene mutation
affecting circadian rhythm in mice
(King et al., 1997). They went on to
show the Clock gene encoded a basic
helix loop helix-PAS transcription factor mutated in their mutant line, and
that reintroduction of the gene via a
bacterial artificial chromosome (BAC)
transgene could rescue the mutant
phenotype (Antoch et al., 1997). For
years, the Clock mutant mouse was
the example researchers pointed to in
justifying the feasibility of their own
mutagenesis screens.
Mammalian behavior is difficult to
study because so many genes can influence a behavior even if they do not
directly cause it. In a mutagenesis
screen focused on genes that control
behavior, special attention must be
paid to genetic background, as the
phenotype must be visible in the mapping cross on a different genetic background, so that the gene can be identified. Another challenge is to infer
how human behavior would be mirrored in the mouse. Indeed, even when
a defined, causative human genetic
mutation is generated in mouse it can
be hard to know what phenotypes
should be examined (Moy et al., 2006).
Screens for recessive behavioral mutations require an especially large
amount of cage space as the phenotype must be seen in the adult G3
offspring. Therefore, a concerted effort
among several institutions has been
undertaken so that mice can be
screened for a number of quantifiable
behaviors (Goldowitz et al., 2004). The
groups are identifying mutant lines
with altered learning, memory, response to, or preference for alcohol
and drugs as well as exploratory behavior and fear conditioning. More
information is available at http://www.
neuromice.org.
Specific behaviors are also being explored in smaller-scale screens. Psychiatric disorders such as depression
and schizophrenia have been linked to
serotonergic and dopaminergic neurotransmission. In mice, serotonin responsiveness can be assayed and
quantified by examining head twitching when the mice are exposed to serotonin (Weiss et al., 2003). In a pilot
screen for dominant mutations that
affect the head-twitching response,
one mutant line that is hyper-responsive to serotonin was identified. By
scaling up the screen, more genes
should be identified that will aid in
the development of therapies for psychiatric disorders.
Because behavioral phenotypes can
be difficult to assay, one useful strategy to identify more important genes
is to look for mutations that modify
known regulators. One such screen to
discover genes that influence the dopaminergic response took advantage
of a mouse background that is already
hyperactive due to homozygous mutation of the dopamine transporter
(DAT) gene. This screen identified
four mutant lines with altered locomotor activity and showed the phenotype
of two lines was only visible on the
DAT null background, indicating they
would not have been identified in a
non-sensitized screen (Speca et al.,
2006). As has been true in other model
organisms, enhancer and suppressor
screens promise to be powerful in the
mouse.
Epigenetics
Several groups have tackled the problem of epigenetic gene regulation in
mammals through forward genetics.
In female mammals, dosage compensation is achieved by randomly inactivating one of the X chromosomes in
every cell. Several mutant mouse
lines have been found in which the
inactivation choice is not random
(Percec et al., 2002, 2003). These mutations map to autosomes and do not
affect imprinted X-inactivation or autosomal genomic imprinting. While
the affected genes have not yet been
reported, the phenotype suggests that
they are important regulators of an
early step specific to X inactivation.
Two groups have found mutants
that affect gene silencing by using visible reporter lines in their screen. In a
directed approach, the agouti coat
color marker was inserted in an imprinted locus (Tsai et al., 2002). Several lines were identified that affected
abdominal coloring of the resulting
mice. One line recapitulated the imprinting defects seen in Angelman’s
syndrome, a maternally inherited developmental disorder associated with
the syntenic locus in humans. This
mutant was found to affect the translation start site of a bicistronic message in the imprinted region revealing
an important component of gene regulation at the locus.
A genome-wide screen identified
six dominant mutant lines that alter
the expression of a green fluorescent
protein (GFP) transgene that is normally expressed in 55% of erythrocytes (Blewitt et al., 2005). As gene
silencing in mammals is not restricted to transgenes, the mutant
lines affecting GFP expression were
subsequently tested for their effect
on retrotransposon silencing using a
visible coat color marker. This tester
strain permitted the mutation to be
analyzed when inherited either maternally or paternally, an inheritance pattern essential to examine
when studying imprinting and one
2418 CASPARY AND ANDERSON
that is logistically difficult to perform in the initial screen. These
screens have yielded mutants that
clearly affect genome-wide epigenetic reprogramming with parent of
origin and sex-specific effects that
are likely to help explain these
unique areas of mammalian biology.
Fertility
The Schimenti lab at Cornell University has identified mutants with defects in both male and female fertility
(Ward et al., 2003). They employ two
strategies to generate chemically induced mutations mice: by injection of
ENU in males or by treating embryonic stem (ES) cells with another potent point mutagen ethylmethanesulphonate (EMS). Although the ES cell
method requires generation of chimeric animals, ES cells can tolerate a
higher mutation load. In addition,
EMS-treated ES cells lines can be
screened through sequence-based
methods to find alleles in genes of interest in a gene-based rather than
phenotype-based strategy (Chen et
al., 2000; Munroe et al., 2000; Vivian
et al., 2002).
The Schimenti lab has compared
two methods of detecting fertility defects. One strategy looks directly for
infertility by mating the mice and
looking for progeny. The second
strategy screens for morphological
defects in sperm (Ward et al., 2003).
Fertility testing only identified one
mutant that would not have been detected by gamete inspection (from 60
lines screened) and took much more
space and time. However, fertility
testing is the only method currently
available to identify oogenesis-specific mutants.
Fertility mutants are a good example of a phenotype that can be noticed
even when it is not the primary focus
of the screen. In Australia, collaborators of the immunity-focused Goodnow lab were able to identify 14 recessive lines from the Goodnow screen
that affected fertility (Kennedy et al.,
2006). Many of these display phenotypes similar to those seen in human
fertility clinics where 40% of cases are
of unknown etiology, so these mutations should help in understanding
the biology behind infertility.
Development
Organogenesis
The fundamental differences in
mammalian development from embryogenesis in other model organisms are emphasized by the distinct
phenotypes observed in mutants
that have been identified in forward
genetic screens in the mouse. Zygotic
transcription in the mouse embryo
begins several days prior to the specification of the body plan. The absence of large stores of maternal
products provides an advantage of
mouse screens for mutations that alter the body plan, in comparison with
other animals used to study the genetics of embryonic patterning. The phenotypes of Smoothenedbnb (Smobnb)
and Dispatched1icb (Disp1icb) appear
to represent loss of all activity of the
vertebrate Hedgehog pathways, and
these strong phenotypes facilitated
their identification in our screen for
embryos that display a morphological
defect at midgestation (Caspary et al.,
2002). In Drosophila, there is a large
maternal contribution of smo and
disp, and null phenotypes are seen
only when both maternal and zygotic
components are removed (Alcedo et
al., 1996; Chen and Struhl, 1996; van
den Heuvel and Ingham, 1996; Burke
et al., 1999; Amanai and Jiang, 2001).
Similarly, there is a substantial maternal contribution of Smo and Disp1
in zebrafish, which may account for
the weaker phenotype of zebrafish
Smo and disp1 mutants (van Eeden et
al., 1996; Nagai et al., 2000; Chen et
al., 2001; Varga et al., 2001; Nakano
et al., 2004) than mouse Smo and
disp1 mutants (Zhang et al., 2001;
Caspary et al., 2002; Kawakami et al.,
2002; Ma et al., 2002).
In the course of our screen at SloanKettering, we have identified 43 recessive mutations that display abnormal
morphology at midgestation (e9.5);
these mutations defined 38 previously
uncharacterized genes (Garcı́a-Garcı́a
et al., 2005). The most common phenotypes are associated with abnormal
neural tube closure (Zohn et al., 2005).
Screening at e9.5 also permitted the
identification of mutant lines that arrest at earlier stages and affect gastrulation or early morphogenesis
(Garcı́a-Garcı́a and Anderson, 2003).
Dissecting the developmental requirements of organs is crucial in the treatment of many human diseases, but
organogenesis in mice cannot be modeled well in other organisms, as many
organs have evolved substantially
from invertebrates or fish to mammals. Several screens have, therefore,
focused on identifying mutants with
defects in organ development. At Baylor, a large screen combined marker
balancer chromosomes with ENU mutagenesis to identify mutations in a
segment of chromosome 11 (Kile et al.,
2003). A broad spectrum of phenotypes was observed but the most common affected a specific organ or tissue.
These included mutant lines with defects in the heart, skeleton, placenta,
and hematopoetic cells. Because of the
use of the balancer, no mapping
crosses were required to map these
mutations to a chromosome region.
Another screen has identified mutants at embryonic day 18.5, just prior
to the embryos reaching term. In 54
lines analyzed, 15 mutants lines were
found with defects in a variety of organs (Herron et al., 2002). One of
these lines displays pulmonary hypoplasia and a thin diaphragm, which
was due to a mutation in Fog2 (Ackerman et al., 2005). Fog2 had not been
previously associated with lung and
diaphragm development, but this
mouse mutant linked the gene to a
human disorder. A child who died of
respiratory failure at birth had an
early stop codon in her FOG2 gene,
demonstrating the conservation of
function between the mouse and human genes. As many human genetic
diseases are associated with point mutations, this result highlights the
mouse ENU-induced mutations as
models to understand human health.
TYPES OF MUTATIONS
AND ALLELIC SERIES
A number of ENU-induced mutations
have revealed previously unappreciated functions of previously characterized proteins. For example, the oblivious mutant line was identified in the
Beutler lab innate immunity screen
because the animals are insensitive to
specific immune stimuli and turned
out to be a null allele of CD36 (Hoebe
FORWARD GENETIC SCREENS IN THE MOUSE 2419
et al., 2005). While CD36 had previously been deleted from the germ line
through homologous recombination, it
had been linked to fatty acid uptake
and recognition of oxidized LDL particles and not to immunity (Aitman et
al., 1999; Glazier et al., 2002). The
link between CD36 to TLRs found in
the obl mutant was not appreciated in
the analysis of the targeted CD36 mutant mice because of preconceived
ideas about CD36 function.
The adaptive immunity screen in
the Goodnow lab identified a novel allele of the transcription factor, Ikaros
(Papathanasiou et al., 2003). Ikaros
had been previously targeted and
analysis of a null allele, a hypomorphic allele, and a dominant negative
allele had shown that Ikaros was involved in lymphocyte, B cell, and natural killer cell development (Georgopoulos et al., 1994; Wang et al., 1996;
Kirstetter et al., 2002). The ENU-induced allele, Ikarosplastic, showed defects in the formation of additional
blood cell types including erythrocytes, granulocytes, and macrophages.
By comparing the Ikarosplastic allele in
combination with the null and dominant negative alleles as well as biochemical studies, it was found that the
Ikarosplastic allele abolished the DNA
binding ability of Ikaros but not its
ability to dimerize with other proteins. In this case, the single base pair
change led to a more severe phenotype
than that of the deletion alleles. Another mutant from this screen caused
a reduction in the number of circulating B cells due to a point mutation in
the transcription factor nuclear factor
NF-$B2, which had not been previously known to control cell number
(Miosge et al., 2002). Such examples
suggest that ENU mutagenesis is especially useful for revealing the complexity of protein function.
The power of allelic series to dissect
complex gene function has long been
appreciated. To date, more than 10
chemically-induced alleles of the c-Kit
receptor and Steel ligand have been
identified. Along with the many spontaneous alleles in these genes, these
alleles have demonstrated in vivo
functions of the pathway in stem cell
migration and proliferation in distinct
developmental contexts such as melanocytes, hemotopoetic stem cells, and
germ cell development (Geissler et al.,
1988; Matsui et al., 1990). Additionally, individual mutations have defined functions for specific residues in
vivo (Koshimizu et al., 1994; El-Nahas
et al., 2002).
Three mutant alleles of the essential eed gene were generated in a region-specific screen, based on failure
to complement a large deletion that
included a visible coat color marker,
albino (Rinchik et al., 1990). By biasing a forward genetic screen to a particular region, it is possible to efficiently generate multiple alleles in the
same gene (Justice et al., 1997; Schimenti and Bucan, 1998; Kile et al.,
2003). The alleles of the essential eed
include both null and partial loss-offunction alleles (Rinchik and Carpenter, 1999). This range of alleles has
been exploited to define separate functions of eed in gastrulation, the subsequent specification of the embryonic
anterior-posterior axis, and in the regulation of X-inactivation and genomic
imprinting (Schumacher et al., 1996;
Wang et al., 2001; Mager et al., 2003;
Kalantry et al., 2006).
NOVEL PROTEINS AND
UNSUSPECTED
MECHANISMS
Some of the most exciting discoveries
from ENU screens have unveiled unsuspected mechanisms that drive biological processes. The Sloan-Kettering
Mouse project identified alleles of several different proteins that affect the
process called intraflagellar transport
(IFT) based on their effects on neural
patterning (Huangfu et al., 2003). Genetic analysis showed that the IFT
mutations disrupted the Hedgehog
signaling pathway, which is essential
for specifying the cell types of the ventral neural tube. IFT proteins are required for the production of cilia, and
these studies indicate that cilia are
required for normal Hedgehog signaling in the mouse. The role of IFT proteins in Hedgehog signaling is vertebrate-specific, as these genes exist in
the Drosophila genome but do not affect Drosophila Hedgehog signaling
(Huangfu et al., 2003; Huangfu and
Anderson, 2005; May et al., 2005).
Spurred on by the success of their
T-cell screen, the Goodnow lab has
screened for more of the poorly characterized processes that control resis-
tance like self-tolerance and autoimmunity. The first mutant from this
screen, san roque, affects a previously unstudied protein, Roquin, that
does not involve any of the previously
identified self-tolerance mechanisms
(Vinuesa et al., 2005). Thus, by looking for a specific disruption in a biological process, the use of an unbiased
screen has revealed an unsuspected
mechanism to repress antibody response to self.
One of the Schimenti lab mutants,
mei1, is infertile due to meiotic arrest
of the gametes. Despite the extensive
studies of meiosis in yeast and invertebrates, this gene had not been identified because mei1 is a vertebratespecific gene (Libby et al., 2002, 2003).
Another infertile line, mei8 disrupts
the Rec8 protein, which has been previously shown in yeast to be involved
in several steps of synapsis (Bannister
et al., 2004). Analysis of mei8 mutants
showed that while some of the steps of
synapsis that Rec8 regulates are conserved in mice, its localization is not
required for the assembly of axial elements as it is in yeast. In the SloanKettering Screen, the lazy mesoderm
mutation, which affects UDP glucose
dehydrogenase, an enzyme required
for the production of proteoglycans,
was found to specifically affect fibroblast growth factor (Fgf) signaling in
the early embryo (Garcı́a-Garcı́a and
Anderson, 2003). This was surprising
as the orthologous gene in Drosophila
affects the Fgf, Wnt, and Hh signaling
pathways. All these examples emphasize the necessity of studying mammalian processes in the mouse rather
than in other model organisms.
PERSPECTIVE
By now, the popularity of mouse mutagenesis screens has approached that
of forward genetic screens in other favorite genetically tractable organisms. As the ability to clone the affected genes has gotten easier, more
labs have used the approach. Genetic
screens are the still the gold standard
in generating mutants in flies and
worms, where reverse genetics is a
more recent technology. In zebrafish,
the initial screens were done for the
community in Tübingen and in Boston
and today individual labs perform
screens looking for their phenotype of
2420 CASPARY AND ANDERSON
interest (Driever et al., 1996; Haffter
et al., 1996). The mouse community is
now experiencing the parallel shift.
Large-scale mouse screens at Harwell,
GSFG, The Jackson Labs, and The
Oak Ridge National Laboratory initially provided mutant lines (Hrabe de
Angelis et al., 2000; Nolan et al.,
2000), but in recent years more individual labs have started their own
screens.
Current mouse screens parallel
what has proven useful in other model
organisms in other ways as well. Modifier screens have proven extremely
powerful in yeast, worms, and flies to
dissect complex biological questions. A
dominant modifier screen in the
mouse found two alleles that suppressed the lack of platelets found in
Mpl homozygous deletion mice
(Carpinelli et al., 2004). Modifier
screens take time and careful planning, as mouse production must be
ramped up so that there are enough
animals available for the screening
crosses.
Reporter lines have also been extremely useful in identifying phenotypes in other model organisms. Some
developmental phenotypes are not visible morphologically and need to be
visualized with molecular techniques.
In order to identify genes important in
cortical development, one screen took
advantage of a Dlx-lacZ reporter
transgene and looked for alterations
in its expression in the ganglionic eminences (Zarbalis et al., 2004). While
morphological phenotypes were also
visible in some lines, some could only
be identified because of aberrant lacZ
staining. In a more direct approach,
another screen has looked at cranial
nerve development by immunohistochemistry using an antibody against
neurofilament (Mar et al., 2005). As
individual nerves are highlighted using this approach, mutations with specific effects can be recovered.
The challenge in incorporating reporter lines in a screen is that established lines are usually on a mixed
genetic background. In theory, mapping against a mixed background
poses difficulties as the chance that
DNA from distinct strains can be distinguished decreases as the number of
strains in the cross increases. This
challenge could be overcome by regenerating the reporter on pure genetic
backgrounds, but this involves a significant investment of time. It also
may not prove necessary, if a high
density of mapping markers can reveal the genetic background of the
specific interval of interest (Bannister
et al., 2004).
Sequencing technology will continue to improve the ability to identify
the lesions responsible for chemicallyinduced mutations. Resequencing
technology already has reduced the
cost of sequencing. A few years ago it
cost $450 for 30 – 60 KB, and that
price has already fallen to $300 per
300kB today (M.E. Zwick, personal
communication). All projections expect the costs to continue to fall,
meaning that it is not unrealistic that
we will soon clone causative mutations by sequencing megabase intervals of DNA.
In addition to saving time and
money, the ability to sequence across
a narrowed interval has clear scientific advantages. The DNA sample can
be prepared from either heterozygous
carrier or homozygous mutant animals. The ability to sequence from the
heterozygotes provides more information than from homozygotes as it allows all the variation in the interval to
be identified. Along with the identification of the causative mutation, this
will identify any linked polymorphisms that will be fixed in the mutant line and these can be analyzed for
potential functional roles.
As improved resequencing technology changes how mutations are detected, forward genetic screens will
reach their potential for teaching us
about mammalian biology. Currently,
causative mutations are identified by
analyzing recombinant animals with
markers and sequencing candidate
genes. Resequencing will reduce this
equation to generating recombinants
and sequencing, which is likely to improve the utility of ENU-induced mutant lines that already exist and are
available without cost to academic researchers.
The recent discoveries outlined here
using forward genetics in the mouse
demonstrate that the screens are out
of their infancy and are making real
contributions to biomedical science.
We look forward to fully integrated
mouse genetics, with complementary
contributions from targeted muta-
tions, ENU screens, gene trap alleles,
and transposon insertion mutations
(Raymond and Soriano, 2006). As we
look ahead, we believe reviews such as
this one will be obsolete as forward
genetic screens in the mouse lose their
novelty and transform into a generic
tool, just as targeted mutagenesis has
done. We look forward to many exciting discoveries as scientists better understand the complexity that underlies mammalian biology.
ACKNOWLEDGMENTS
We thank all the participants in the
Sloan-Kettering Mouse Mutagenesis
project for their helpful discussions,
diligent database entries and cloning
success.
REFERENCES
Ackerman KG, Herron BJ, Vargas SO,
Huang H, Tevosian SG, Kochilas L, Rao
C, Pober BR, Babiuk RP, Epstein JA,
Greer JJ, Beier DR. 2005. Fog2 is required for normal diaphragm and lung
development in mice and humans. PLoS
Genet 1:58 –65.
Aitman TJ, Glazier AM, Wallace CA, Cooper LD, Norsworthy PJ, Wahid FN, AlMajali KM, Trembling PM, Mann CJ,
Shoulders CC, Graf D, St Lezin E, Kurtz
TW, Kren V, Pravenec M, Ibrahimi A,
Abumrad NA, Stanton LW, Scott J.
1999. Identification of Cd36 (Fat) as an
insulin-resistance gene causing defective
fatty acid and glucose metabolism in hypertensive rats. Nat Genet 21:76 –83.
Alcedo J, Ayzenzon M, Von Ohlen T, Noll
M, Hooper JE. 1996. The Drosophila
smoothened gene encodes a seven-pass
membrane protein, a putative receptor
for the hedgehog signal. Cell 86:221–232.
Amanai K, Jiang J. 2001. Distinct roles of
central missing and dispatched in sending the Hedgehog signal. Development
128:5119 –5127.
Antoch MP, Song EJ, Chang AM, Vitaterna MH, Zhao Y, Wilsbacher LD,
Sangoram AM, King DP, Pinto LH, Takahashi JS. 1997. Functional identification of the mouse circadian Clock gene by
transgenic BAC rescue. Cell 89:655–667.
Austin CP, Battey JF, Bradley A, Bucan M,
Capecchi M, Collins FS, Dove WF, Duyk
G, Dymecki S, Eppig JT, Grieder FB,
Heintz N, Hicks G, Insel TR, Joyner A,
Koller BH, Lloyd KC, Magnuson T,
Moore MW, Nagy A, Pollock JD, Roses
AD, Sands AT, Seed B, Skarnes WC,
Snoddy J, Soriano P, Stewart DJ, Stewart F, Stillman B, Varmus H, Varticovski
L, Verma IM, Vogt TF, von Melchner H,
Witkowski J, Woychik RP, Wurst W,
Yancopoulos GD, Young SG, Zambrowicz
B. 2004. The knockout mouse project.
Nat Genet 36:921–924.
FORWARD GENETIC SCREENS IN THE MOUSE 2421
Bannister LA, Reinholdt LG, Munroe RJ,
Schimenti JC. 2004. Positional cloning
and characterization of mouse mei8, a
disrupted allelle of the meiotic cohesin
Rec8. Genesis 40:184 –194.
Beier DR. 2000. Sequence-based analysis
of mutagenized mice. Mamm Genome 11:
594 –597.
Beutler B, Crozat K, Koziol JA, Georgel P.
2005. Genetic dissection of innate immunity to infection: the mouse cytomegalovirus model. Curr Opin Immunol 17:36 –
43.
Blewitt ME, Vickaryous NK, Hemley SJ,
Ashe A, Bruxner TJ, Preis JI, Arkell R,
Whitelaw E. 2005. An N-ethyl-N-nitrosourea screen for genes involved in variegation in the mouse. Proc Natl Acad Sci
USA 102:7629 –7634.
Burke R, Nellen D, Bellotto M, Hafen E,
Senti KA, Dickson BJ, Basler K. 1999.
Dispatched, a novel sterol-sensing domain protein dedicated to the release of
cholesterol-modified hedgehog from signaling cells. Cell 99:803–815.
Carpinelli MR, Hilton DJ, Metcalf D, Antonchuk JL, Hyland CD, Mifsud SL, Di
Rago L, Hilton AA, Willson TA, Roberts
AW, Ramsay RG, Nicola NA, Alexander
WS. 2004. Suppressor screen in Mpl&/&
mice: c-Myb mutation causes supraphysiological production of platelets in
the absence of thrombopoietin signaling.
Proc Natl Acad Sci USA 101:6553–6558.
Caspary T, Garcı́a-Garcı́a MJ, Huangfu D,
Eggenschwiler JT, Wyler MR, Rakeman
AS, Alcorn HL, Anderson KV. 2002.
Mouse Dispatched homologue1 is required for long-range, but not juxtacrine,
Hh signaling. Curr Biol 12:1628 –1632.
Chen W, Burgess S, Hopkins N. 2001.
Analysis of the zebrafish smoothened
mutant reveals conserved and divergent
functions of hedgehog activity. Development 128:2385–2396.
Chen Y, Struhl G. 1996. Dual roles for
patched in sequestering and transducing
Hedgehog. Cell 87:553-563.
Chen Y, Yee D, Dains K, Chatterjee A,
Cavalcoli J, Schneider E, Om J, Woychik
RP, Magnuson T. 2000. Genotype-based
screen for ENU-induced mutations in
mouse embryonic stem cells. Nat Genet
24:314 –317.
Clark AT, Goldowitz D, Takahashi JS, Vitaterna MH, Siepka SM, Peters LL,
Frankel WN, Carlson GA, Rossant J,
Nadeau JH, Justice MJ. 2004. Implementing large-scale ENU mutagenesis
screens in North America. Genetica 122:
51–64.
Concepcion D, Seburn KL, Wen G, Frankel
WN, Hamilton BA. 2004. Mutation rate
and predicted phenotypic target sizes in
ethylnitrosourea-treated mice. Genetics
168:953–959.
Doetschman T, Maeda N, Smithies O.
1988. Targeted mutation of the Hprt
gene in mouse embryonic stem cells.
Proc Natl Acad Sci U S A 85:8583-8587.
Driever W, Solnica-Krezel L, Schier AF,
Neuhauss SC, Malicki J, Stemple DL,
Stainier DY, Zwartkruis F, Abdelilah S,
Rangini Z, Belak J, Boggs C. 1996. A
genetic screen for mutations affecting
embryogenesis in zebrafish. Development 123:37–46.
El-Nahas A, El-Shazly S, El-Fiky S, Watanab T. 2002. Differential effects of the
KitW mutation with other Kit allelic
combinations on male sterility among inter- or intrasubspecific hybrids in mice.
Biochem Genet 40:13–25.
Garcı́a-Garcı́a MJ, Anderson KV. 2003. Essential role of glycosaminoglycans in Fgf
signaling during mouse gastrulation.
Cell 114:727–737.
Garcı́a-Garcı́a MJ, Eggenschwiler JT,
Caspary T, Alcorn HL, Wyler MR,
Huangfu D, Rakeman AS, Lee JD, Feinberg EH, Timmer JR, Anderson KV.
2005. Analysis of mouse embryonic patterning and morphogenesis by forward
genetics. Proc Natl Acad Sci U S A 102:
5913–5919.
Geissler EN, Ryan MA, Housman DE.
1988. The dominant-white spotting (W)
locus of the mouse encodes the c-kit
proto-oncogene. Cell 55:185–192.
Georgopoulos K, Bigby M, Wang JH, Molnar A, Wu P, Winandy S, Sharpe A.
1994. The Ikaros gene is required for the
development of all lymphoid lineages.
Cell 79:143–156.
Glazier AM, Scott J, Aitman TJ. 2002. Molecular basis of the Cd36 chromosomal
deletion underlying SHR defects in insulin action and fatty acid metabolism.
Mamm Genome 13:108 –113.
Goldowitz D, Frankel WN, Takahashi JS,
Holtz-Vitaterna M, Bult C, Kibbe WA,
Snoddy J, Li Y, Pretel S, Yates J, Swanson DJ. 2004. Large-scale mutagenesis
of the mouse to understand the genetic
bases of nervous system structure and
function. Brain Res Mol Brain Res 132:
105–115.
Haffter P, Granato M, Brand M, Mullins
MC, Hammerschmidt M, Kane DA,
Odenthal J, van Eeden FJ, Jiang YJ,
Heisenberg CP, Kelsh RN, FurutaniSeiki M, Vogelsang E, Beuchle D, Schach
U, Fabian C, Nusslein-Volhard C. 1996.
The identification of genes with unique
and essential functions in the development of the zebrafish, Danio rerio. Development 123:1–36.
Herron BJ, Lu W, Rao C, Liu S, Peters H,
Bronson RT, Justice MJ, McDonald JD,
Beier DR. 2002. Efficient generation and
mapping of recessive developmental mutations using ENU mutagenesis. Nat
Genet 30:185–189.
Hitotsumachi S, Carpenter DA, Russell
WL. 1985. Dose-repetition increases the
mutagenic effectiveness of N-ethyl-N-nitrosourea in mouse spermatogonia. Proc
Natl Acad Sci U S A 82:6619 –6621.
Hoebe K, Beutler B. 2005. Unraveling innate immunity using large scale N-ethylN-nitrosourea mutagenesis. Tissue Antigens 65:395–401.
Hoebe K, Du X, Georgel P, Janssen E, Tabeta K, Kim SO, Goode J, Lin P, Mann N,
Mudd S, Crozat K, Sovath S, Han J, Beutler B. 2003a. Identification of Lps2 as a
key transducer of MyD88-independent
TIR signalling. Nature 424:743–748.
Hoebe K, Du X, Goode J, Mann N, Beutler
B. 2003b. Lps2: a new locus required for
responses to lipopolysaccharide, revealed by germline mutagenesis and
phenotypic screening. J Endotoxin Res
9:250 –255.
Hoebe K, Georgel P, Rutschmann S, Du X,
Mudd S, Crozat K, Sovath S, Shamel L,
Hartung T, Zahringer U, Beutler B.
2005. CD36 is a sensor of diacylglycerides. Nature 433:523–527.
Hrabe de Angelis MH, Flaswinkel H,
Fuchs H, Rathkolb B, Soewarto D, Marschall S, Heffner S, Pargent W, Wuensch
K, Jung M, Reis A, Richter T, Alessandrini F, Jakob T, Fuchs E, Kolb H, Kremmer E, Schaeble K, Rollinski B, Roscher
A, Peters C, Meitinger T, Strom T, Steckler T, Holsboer F, Klopstock T, Gekeler
F, Schindewolf C, Jung T, Avraham K,
Behrendt H, Ring J, Zimmer A,
Schughart K, Pfeffer K, Wolf E, Balling
R. 2000. Genome-wide, large-scale production of mutant mice by ENU mutagenesis. Nat Genet 25:444 –447.
Huangfu D, Anderson KV. 2005. Cilia
and Hedgehog responsiveness in the
mouse. Proc Natl Acad Sci USA 102:
11746 –11750.
Huangfu D, Liu A, Rakeman AS, Murcia
NS, Niswander L, Anderson KV. 2003.
Hedgehog signalling in the mouse requires intraflagellar transport proteins.
Nature 426:83–-87.
Jun JE, Wilson LE, Vinuesa CG, Lesage S,
Blery M, Miosge LA, Cook MC, Kucharska EM, Hara H, Penninger JM, Domashenz H, Hong NA, Glynne RJ, Nelms
KA, Goodnow CC. 2003. Identifying the
MAGUK protein Carma-1 as a central
regulator of humoral immune responses
and atopy by genome-wide mouse mutagenesis. Immunity 18:751–762.
Justice MJ. 2000. Mutagenesis of the
mouse germline. In: Jackson IJ, Abbott
Cm, editors. Mouse genetics and tansgenics: a practical approach. Oxford: Oxford University Press. p 185-216.
Justice MJ, Zheng B, Woychik RP, Bradley
A. 1997. Using targeted large deletions
and high-efficiency N-ethyl-N-nitrosourea mutagenesis for functional analyses of the mammalian genome. Methods 13:423–436.
Kalantry S, Mills KC, Yee D, Otte AP, Panning B, Magnuson T. 2006. The Polycomb
group protein Eed protects the inactive Xchromosome from differentiation-induced
reactivation. Nat Cell Biol 8:195–202.
Kasarskis A, Manova K, Anderson KV.
1998. A phenotype-based screen for embryonic lethal mutations in the mouse.
Proc Natl Acad Sci USA 95:7485–7490.
Kawai T, Adachi O, Ogawa T, Takeda K,
Akira S. 1999. Unresponsiveness of
MyD88-deficient mice to endotoxin. Immunity 11:115–122.
Kawakami T, Kawcak T, Li YJ, Zhang W,
Hu Y, Chuang PT. 2002. Mouse dispatched mutants fail to distribute hedgehog proteins and are defective in hedgehog signaling. Development 129:5753–
5765.
2422 CASPARY AND ANDERSON
Kennedy CL, O’Connor A E, Sanchez-Partida LG, Holland MK, Goodnow CC, de
Kretser DM, O’Bryan M K. 2006. A repository of ENU mutant mouse lines and
their potential for male fertility research. Mol Hum Reprod 11:871– 880.
Kile BT, Hilton DJ. 2005. The art and design of genetic screens: mouse. Nat Rev
Genet 6:557–567.
Kile BT, Hentges KE, Clark AT, Nakamura H, Salinger AP, Liu B, Box N,
Stockton DW, Johnson RL, Behringer
RR, Bradley A, Justice MJ. 2003. Functional genetic analysis of mouse chromosome 11. Nature 425:81–86.
King DP, Zhao Y, Sangoram AM, Wilsbacher LD, Tanaka M, Antoch MP,
Steeves TD, Vitaterna MH, Kornhauser
JM, Lowrey PL, Turek FW, Takahashi
JS. 1997. Positional cloning of the mouse
circadian clock gene. Cell 89:641–653.
Kirstetter P, Thomas M, Dierich A, Kastner P, Chan S. 2002. Ikaros is critical for
B cell differentiation and function. Eur
J Immunol 32:720 –730.
Koshimizu U, Tsujimura T, Isozaki K, Nomura S, Furitsu T, Kanakura Y, Kitamura
Y, Nishimune Y. 1994. Wn mutation of
c-kit receptor affects its post-translational
processing and extracellular expression.
Oncogene 9:157–162.
Libby BJ, De La Fuente R, O’Brien MJ,
Wigglesworth K, Cobb J, Inselman A,
Eaker S, Handel MA, Eppig JJ, Schimenti JC. 2002. The mouse meiotic
mutation mei1 disrupts chromosome
synapsis with sexually dimorphic consequences for meiotic progression. Dev Biol
242:174 –187.
Libby BJ, Reinholdt LG, Schimenti JC.
2003. Positional cloning and characterization of Mei1, a vertebrate-specific
gene required for normal meiotic chromosome synapsis in mice. Proc Natl
Acad Sci USA 100:15706 –15711.
Love JM, Knight AM, McAleer MA, Todd
JA. 1990. Towards construction of a high
resolution map of the mouse genome using PCR-analysed microsatellites. Nucleic Acids Res 18:4123–4130.
Ma Y, Erkner A, Gong R, Yao S, Taipale J,
Basler K, Beachy PA. 2002. Hedgehogmediated patterning of the mammalian
embryo requires transporter-like function of dispatched. Cell 111:63–75.
Mager J, Montgomery ND, de Villena FP,
Magnuson T. 2003. Genome imprinting
regulated by the mouse Polycomb group
protein Eed. Nat Genet 33:502–507.
Mar L, Rivkin E, Kim DY, Yu JY, Cordes
SP. 2005. A genetic screen for mutations
that affect cranial nerve development in
the mouse. J Neurosci 25:11787–11795.
Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, Berka J,
Braverman MS, Chen YJ, Chen Z, Dewell SB, Du L, Fierro JM, Gomes XV, Godwin BC, He W, Helgesen S, Ho CH, Irzyk
GP, Jando SC, Alenquer ML, Jarvie TP,
Jirage KB, Kim JB, Knight JR, Lanza
JR, Leamon JH, Lefkowitz SM, Lei M, Li
J, Lohman KL, Lu H, Makhijani VB, McDade KE, McKenna MP, Myers EW,
Nickerson E, Nobile JR, Plant R, Puc BP,
Ronan MT, Roth GT, Sarkis GJ, Simons
JF, Simpson JW, Srinivasan M, Tartaro
KR, Tomasz A, Vogt KA, Volkmer GA,
Wang SH, Wang Y, Weiner MP, Yu P,
Begley RF, Rothberg JM. 2005. Genome
sequencing in microfabricated high-density picolitre reactors. Nature 437:376 –
380.
Matsui Y, Zsebo KM, Hogan BL. 1990. Embryonic expression of a haematopoietic
growth factor encoded by the Sl locus
and the ligand for c-kit. Nature 347:667–
669.
May SR, Ashique AM, Karlen M, Wang B,
Shen Y, Zarbalis K, Reiter J, Ericson J,
Peterson AS. 2005. Loss of the retrograde motor for IFT disrupts localization
of Smo to cilia and prevents the expression of both activator and repressor functions of Gli. Dev Biol 287:378 –389.
Miosge LA, Blasioli J, Blery M, Goodnow
CC. 2002. Analysis of an ethylnitrosourea-generated mouse mutation defines a cell intrinsic role of nuclear factor
kappaB2 in regulating circulating B cell
numbers. J Exp Med 196:1113–1119.
Moran JL, Bolton AD, Tran PV, Brown A,
Dwyer ND, Manning DK, Bjork BC, Li C,
Montgomery K, Siepka SM, Vitaterna
MH, Takahashi JS, Wiltshire T, Kwiatkowski DJ, Kucherlapati R, Beier DR.
2006. Utilization of a whole genome SNP
panel for efficient genetic mapping in the
mouse. Genome Res 16:436 – 440.
Moy SS, Nadler JJ, Magnuson TR, Crawley JN. 2006. Mouse models of autism
spectrum disorders: The challenge for
behavioral genetics. Am J Med Genet C
Semin Med Genet 142:40 –51.
Munroe RJ, Bergstrom RA, Zheng QY,
Libby B, Smith R, John SW, Schimenti
KJ, Browning VL, Schimenti JC. 2000.
Mouse mutants from chemically mutagenized embryonic stem cells. Nat
Genet 24:318 –321.
Nagai T, Aruga J, Minowa O, Sugimoto T,
Ohno Y, Noda T, Mikoshiba K. 2000. Zic2
regulates the kinetics of neurulation.
Proc Natl Acad Sci USA 97:1618 –1623.
Nakano Y, Kim HR, Kawakami A, Roy S,
Schier AF, Ingham PW. 2004. Inactivation of dispatched 1 by the chameleon
mutation disrupts Hedgehog signalling
in the zebrafish embryo. Dev Biol 269:
381–392.
Nelms KA, Goodnow CC. 2001. Genomewide ENU mutagenesis to reveal immune regulators. Immunity 15:409 –418.
Nolan PM, Peters J, Strivens M, Rogers D,
Hagan J, Spurr N, Gray IC, Vizor L,
Brooker D, Whitehill E, Washbourne R,
Hough T, Greenaway S, Hewitt M, Liu X,
McCormack S, Pickford K, Selley R,
Wells C, Tymowska-Lalanne Z, Roby P,
Glenister P, Thornton C, Thaung C,
Stevenson JA, Arkell R, Mburu P, Hardisty R, Kiernan A, Erven A, Steel KP,
Voegeling S, Guenet JL, Nickols C, Sadri
R, Nasse M, Isaacs A, Davies K, Browne
M, Fisher EM, Martin J, Rastan S,
Brown SD, Hunter J. 2000. A systematic,
genome-wide, phenotype-driven mutagenesis programme for gene function
studies in the mouse. Nat Genet 25:440 –
443.
Papathanasiou P, Goodnow CC. 2005. Connecting mammalian genome with phenome by ENU mouse mutagenesis: gene
combinations specifying the immune
system. Annu Rev Genet 39:241–262.
Papathanasiou P, Perkins AC, Cobb BS,
Ferrini R, Sridharan R, Hoyne GF,
Nelms KA, Smale ST, Goodnow CC.
2003. Widespread failure of hematolymphoid differentiation caused by a recessive niche-filling allele of the Ikaros
transcription factor. Immunity 19:131–
144.
Pask AJ, Kanasaki H, Kaiser UB, Conn
PM, Janovick JA, Stockton DW, Hess
DL, Justice MJ, Behringer RR. 2005. A
novel mouse model of hypogonadotrophic
hypogonadism: N-ethyl-N-nitrosoureainduced gonadotropin-releasing hormone receptor gene mutation. Mol Endocrinol 19:972–981.
Percec I, Plenge RM, Nadeau JH, Bartolomei MS, Willard HF. 2002. Autosomal dominant mutations affecting X inactivation choice in the mouse. Science
296:1136 –1139.
Percec I, Thorvaldsen JL, Plenge RM,
Krapp CJ, Nadeau JH, Willard HF, Bartolomei MS. 2003. An N-ethyl-N-nitrosourea mutagenesis screen for epigenetic
mutations in the mouse. Genetics 164:
1481–1494.
Petkov PM, Cassell MA, Sargent EE, Donnelly CJ, Robinson P, Crew V, Asquith S,
Haar RV, Wiles MV. 2004a. Development of a SNP genotyping panel for genetic monitoring of the laboratory
mouse. Genomics 83:902–911.
Petkov PM, Ding Y, Cassell MA, Zhang W,
Wagner G, Sargent EE, Asquith S, Crew
V, Johnson KA, Robinson P, Scott VE,
Wiles MV. 2004b. An efficient SNP system for mouse genome scanning and elucidating strain relationships. Genome
Res 14:1806 –1811.
Poltorak A, He X, Smirnova I, Liu MY, Van
Huffel C, Du X, Birdwell D, Alejos E,
Silva M, Galanos C, Freudenberg M, Ricciardi-Castagnoli P, Layton B, Beutler B.
1998. Defective LPS signaling in C3H/
HeJ and C57BL/10ScCr mice: mutations
in Tlr4 gene. Science 282:2085–2088.
Raymond CS, Soriano P. 2006. Engineering mutations: Deconstructing the
mouse gene by gene. Dev Dyn 235:2424 –
2436.
Rinchik EM, Carpenter DA. 1999. N-ethylN-nitrosourea mutagenesis of a 6- to
11-cM subregion of the Fah-Hbb interval
of mouse chromosome 7: Completed testing of 4557 gametes and deletion mapping and complementation analysis of 31
mutations. Genetics 152:373–383.
Rinchik EM, Carpenter DA, Selby PB.
1990. A strategy for fine-structure functional analysis of a 6- to 11-centimorgan
region of mouse chromosome 7 by highefficiency mutagenesis. Proc Natl Acad
Sci USA 87:896 –900.
Robertson E, Bradley A, Kuehn MR, Evans
MJ. 1986. Germ-line transmission of
genes introduced into cultured pluripo-
FORWARD GENETIC SCREENS IN THE MOUSE 2423
tential cells by a retroviral vector. Nature 323:445–448.
Sakuraba Y, Sezutsu H, Takahasi KR,
Tsuchihashi K, Ichikawa R, Fujimoto N,
Kaneko S, Nakai Y, Uchiyama M, Goda
N, Motoi R, Ikeda A, Karashima Y, Inoue
M, Kaneda H, Masuya H, Minowa O,
Noguchi H, Toyoda A, Sakaki Y, Wakana
S, Noda T, Shiroishi T, Gondo Y. 2005.
Molecular characterization of ENU
mouse mutagenesis and archives. Biochem Biophys Res Commun 336:609 –
616.
Schimenti J, Bucan M. 1998. Functional
genomics in the mouse: phenotype-based
mutagenesis screens. Genome Res 8:698 –
710.
Schumacher A, Faust C, Magnuson T.
1996. Positional cloning of a global regulator of anterior-posterior patterning in
mice. Nature 384:648.
Shendure J, Mitra RD, Varma C, Church
GM. 2004. Advanced sequencing technologies: methods and goals. Nat Rev Genet
5:335–344.
Shendure J, Porreca GJ, Reppas NB, Lin
X, McCutcheon JP, Rosenbaum AM,
Wang MD, Zhang K, Mitra RD, Church
GM. 2005. Accurate multiplex polony sequencing of an evolved bacterial genome.
Science 309:1728 –1732.
Siepka SM, Takahashi JS. 2005. Forward
genetic screens to identify circadian
rhythm mutants in mice. Methods Enzymol 393:219 –229.
Speca DJ, Rabbee N, Chihara D, Speed TP,
Peterson AS. 2006. A genetic screen for
behavioral mutations that perturb dopaminergic homeostasis in mice. Genes
Brain Behav 5:19 –28.
Taylor BA. 2000. Mapping phenotypic trait
loci. In: Jackson IJ, Abbott C, editors.
Mouse genetics and transgenics: a practical approach. Oxford: Oxford University Press. p 87–120.
Thomas KR, Capecchi MR. 1987. Site-directed mutagenesis by gene targeting in
mouse embryo-derived stem cells. Cell
51:503–512.
Timmer JR, Mak TW, Manova K, Anderson KV, Niswander L. 2005. Tissue morphogenesis and vascular stability require the Frem2 protein, product of the
mouse myelencephalic blebs gene. Proc
Natl Acad Sci USA 102:11746 –11750.
Tsai TF, Chen KS, Weber JS, Justice MJ,
Beaudet AL. 2002. Evidence for translational regulation of the imprinted SnurfSnrpn locus in mice. Hum Mol Genet
11:1659 –1668.
van den Heuvel M, Ingham PW. 1996.
smoothened encodes a receptor-like serpentine protein required for hedgehog
signalling. Nature 382:547–551.
van Eeden FJ, Granato M, Schach U,
Brand M, Furutani-Seiki M, Haffter P,
Hammerschmidt M, Heisenberg CP,
Jiang YJ, Kane DA, Kelsh RN, Mullins
MC, Odenthal J, Warga RM, NussleinVolhard C. 1996. Genetic analysis of fin
formation in the zebrafish, Danio rerio.
Development 123:255–262.
Varga ZM, Amores A, Lewis KE, Yan YL,
Postlethwait JH, Eisen JS, Westerfield
M. 2001. Zebrafish smoothened functions
in ventral neural tube specification and
axon tract formation. Development 128:
3497–3509.
Vinuesa CG, Cook MC, Angelucci C, Athanasopoulos V, Rui L, Hill KM, Yu D,
Domaschenz H, Whittle B, Lambe T,
Roberts IS, Copley RR, Bell JI, Cornall
RJ, Goodnow CC. 2005. A RING-type
ubiquitin ligase family member required
to repress follicular helper T cells and
autoimmunity. Nature 435:452–458.
Vivian JL, Chen Y, Yee D, Schneider E,
Magnuson T. 2002. An allelic series of
mutations in Smad2 and Smad4 identified in a genotype-based screen of Nethyl-N-nitrosourea-mutagenized mouse
embryonic stem cells. Proc Natl Acad Sci
USA 99:15542–15547.
Wang J, Mager J, Chen Y, Schneider E,
Cross JC, Nagy A, Magnuson T. 2001.
Imprinted X inactivation maintained by
a mouse Polycomb group gene. Nat
Genet 28:371–375.
Wang JH, Nichogiannopoulou A, Wu L,
Sun L, Sharpe AH, Bigby M, Georgopoulos K. 1996. Selective defects in the development of the fetal and adult lymphoid system in mice with an Ikaros null
mutation. Immunity 5:537–549.
Ward JO, Reinholdt LG, Hartford SA, Wilson LA, Munroe RJ, Schimenti KJ, Libby
BJ, O’Brien M, Pendola JK, Eppig J,
Schimenti JC. 2003. Toward the genetics
of mammalian reproduction: induction
and mapping of gametogenesis mutants
in mice. Biol Reprod 69:1615–1625.
Weiss KC, Kim DY, Pawson CT, Cordes
SP. 2003. A genetic screen for mouse mutations with defects in serotonin responsiveness. Brain Res Mol Brain Res 115:
162–172.
Wilson L, Ching YH, Farias M, Hartford
SA, Howell G, Shao H, Bucan M, Schimenti JC. 2005. Random mutagenesis of
proximal mouse chromosome 5 uncovers
predominantly embryonic lethal mutations. Genome Res 15:1095–1105.
Zarbalis K, May SR, Shen Y, Ekker M,
Rubenstein JL, Peterson AS. 2004. A focused and efficient genetic screening
strategy in the mouse: identification of
mutations that disrupt cortical development. PLoS Biol 2:E219.
Zhang XM, Ramalho-Santos M, McMahon
AP. 2001. Smoothened mutants reveal
redundant roles for Shh and Ihh signaling including regulation of L/R symmetry by the mouse node. Cell 106:781–792.
Zohn IE, Anderson KV, Niswander L.
2005. Using genomewide mutagenesis
screens to identify the genes required for
neural tube closure in the mouse. Birth
Defects Res A Clin Mol Teratol 73:583–
590.
Zwick ME. 2005. A genome sequencing
center in every lab. Eur J Hum Genet
13:1167–1168.