Using ENU Mutagenesis for Phenotype-Driven Analysis of the Mouse

C H A P T E R

S E V E N T E E N

Using ENU Mutagenesis for Phenotype-Driven Analysis of the Mouse Rolf W. Stottmann and David R. Beier Contents 330 331 332 334 335 335 335 336 336 339 340 343 345 345

1. Introduction 2. ENU Screen Design 2.1. Developmental phenotypes 2.2. Metabolic phenotypes 2.3. Physiological phenotypes 2.4. Cellular phenotypes 2.5. Behavioral phenotypes 2.6. Suppressor/enhancer phenotypes 3. ENU Treatment 4. Mutant Ascertainment 5. Mutation Identification 6. Mutation Validation 7. Summary References

Abstract The use of mutagenesis in invertebrates to generate phenotypic variants has a long and productive history. Despite the conclusive demonstration by Russell and colleagues in the 1970s that the chemical N-ethyl-N-nitrosourea (ENU) is a highly effective mutagen in mice, the application of phenotypic-driven mutagenesis as a method to study mammalian biology proceeded slowly. With the development of tools for genomic analysis, the task of positional cloning ENUinduced mutations has become quite feasible, and this approach has recently been widely applied and highly productive. It has specifically lived up to its theoretical utility as means to provide insight into the biological roles of genes that is not biased by presumptions of their function. While the power of this approach is indisputable, the effort necessary for its success remains Division of Genetics, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA Methods in Enzymology, Volume 477 ISSN 0076-6879, DOI: 10.1016/S0076-6879(10)77017-8

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2010 Elsevier Inc. All rights reserved.

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substantial, requiring careful attention to aspects including ENU treatment, mouse husbandry, screen assay design, genetic mapping, positional cloning, and mutation validation. In this chapter we discuss practical aspects of implementing a phenotype-driven analysis of an ENU-mutagenized mouse population.

1. Introduction Treatment with N-ethyl-N-nitrosourea (ENU) is an effective tool for generating DNA sequence variation with low morbidity and/or mortality in several model organisms. The first studies of mutagenesis using ENU as a mutagen in the mouse were some of the most informative; in these Russell et al. (1979) characterized the effectiveness of ENU using the specific locus test to quantify its mutation rate. These investigations determined that intraperitoneal (i.p.) injection of ENU could efficiently generate germ cell mutations without causing systemic morbidity. Analysis of the timing of the effects suggested that it is the spermatogonial stem cells that are sensitive to this agent. Additional studies determined that the efficiency of mutagenesis could be optimized by use of a fractionated dose (Russell et al., 1982). In this fashion, frequencies of 6–15
10 4 mutations per locus per gamete can be obtained, greater than that obtained using radiation mutagenesis and 1000-fold higher than the spontaneous rate of mutation of 0.5
10 6. Characterization of ENU mutations in Drosophila revealed that the molecular basis of these mutants were single-base changes; many recent studies have confirmed that this is the case in mammalian cells as well (e.g., Coghill et al., 2002). Russell’s pioneering studies were then followed by Bode’s elegant characterization of the breeding strategy for uncovering recessive mutations (see Fig. 17.1) and the practical

G0

ENU

G1

G2

G3

Figure 17.1 Three-generation strategy for generating recessive mutations.

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demonstration of its utility by generating mouse models of hyperphenylalaninemia (McDonald and Bode, 1988; McDonald et al., 1990). However, despite the very clear demonstration of the efficacy of ENU, it was not readily adopted as a means to study mammalian biology, primarily due to the difficulty at the time of identifying loci that were mutated as a consequence of a single-base change. Fortunately, the technology was maintained and applied by investigators in a few laboratories; notably, that of Dove, who used it to generate the widely used Min mouse model of APC (Moser et al., 1990), Favor (Favor et al., 1991), and Guenet (Montagutelli et al., 1994; Tutois et al., 1991). As development of the tools for genomic analysis made it feasible to pursue the positional cloning of ENU-induced mutant loci, there was an increased appreciation of the potential utility of this approach for phenotype-driven analysis of mouse biology. The past 15 years have seen a remarkable resurgence in the application of ENU mutagenesis to all manner of biological processes in the mouse. These have been done both as large consortium efforts with broad phenotypic aims (Hrabe de Angelis et al., 2000; Nolan et al., 2000a) and by individual investigators focusing on specific problems (Herron et al., 2002; Kasarskis et al., 1998). The design and outcomes of these diverse efforts are the subject of numerous reviews (e.g., Acevedo-Arozena et al., 2008; Cook et al., 2006; Georgel et al., 2008; Godinho and Nolan, 2006). The aim of this chapter is to facilitate the consideration of using ENU mutagenesis investigation of mammalian biology by discussing the practical aspects of this approach.

2. ENU Screen Design Treatment with a mutagenic dose of ENU results in a period of infertility. Recovery from this occurs after 8–12 weeks, and the treated mice (designated G0 for Generation 0) are then bred. Dominantly or semidominantly inherited phenotypes can be assayed in their first generation (G1) progeny (Fig. 17.1). A number of screens have focused on this population, as it is logistically feasible to very screen large numbers of mice (Hrabe de Angelis et al., 2000; Nolan et al., 2000a). The productivity of this approach can be further enhanced by analyzing each mouse using a battery of tests (Gailus-Durner et al., 2005; Nolan et al., 2000b). However, because most mutations in the mouse have no or only subtle effects in heterozygotes, it is frequently necessary to employ a multigeneration breeding scheme to uncover recessive mutations. This is particularly the case for developmental mutations: consider that haploinsufficiency for Sonic hedgehog (Shh) causes holoprosencephaly in humans (Roessler et al., 1996), but heterozygous mice appear essentially normal even though homozygous embryos have profound patterning defects (Chiang et al., 1996).

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Additionally, recessive screens can identify mutations that result in lethality. Also, establishing that an observed phenotype is heritable and monogenic is facilitated by the design of a recessive screen, as it would be expected (and in fact is required) that multiple affected mice are obtained from a G1 male. While the husbandry demands make it less feasible to test large numbers of G1 mice than in a screen for dominant mutations, this is offset by the fact that each G1 male carries many mutations. Russell’s studies demonstrate that the per-locus mutation frequency of optimized fractionated dose ENU treatment is about 1/1000. The nature of the specific locus test that Russell employed would uncover primarily mutations that were effectively null. Assuming 25,000 genes in the mouse genome, one can therefore conclude a G1 male carries 25 null mutations, and potentially many more with hypomorphic effects. Finally, by performing the screen as an outcross, genetic informativeness is introduced such that the mutations can be mapped as they are obtained (as opposed to establishing a separate mapping cross after mutation ascertainment). The general strategy of husbandry described by Bode is the most commonly used means for recovering recessive mutations; this is discussed in more detail below (McDonald and Bode, 1988). There is indisputable evidence that ENU mutagenesis is efficient (with respect to generating single nucleotide changes), that these mutations can be readily mapped (assuming reasonable penetrance) and that they can ultimately be identified using straight-forward approaches of positional cloning. Thus, the only unknown in determining the success of a mutagenesis experiment is the likelihood that a heritable phenotypic variant will be identified. At one level, this is a function of the number of genes that are required for the generation or maintenance of ‘‘normal,’’ with respect to the phenotype in question. If, for example, it is a single gene, the probability of ascertaining this in a standard mutagenesis analysis is low. If, however, tens to hundreds of genes are required to generate or maintain the wild-type state, the likelihood of their discovery in a modest-size screen is quite reasonable. Given the latter scenario, the key determinant for success is whether the phenotype to be screened is amenable to reasonably high-throughput analysis (as even a modest-size screen still requires the analysis of hundreds to thousands of progeny) and whether the assay will unambiguously discriminate between normal variation and a truly mutant phenotype (as the latter will still be rare relative to the number of normal mice). With this general principle in mind, ENU mutagenesis can be applied for investigation of a wide variety of biological processes, as discussed in the following sections.

2.1. Developmental phenotypes ENU mutagenesis has arguably been most successful in discovering genes required for normal development. This is likely due to a number of factors: the biological complexity of the process (such that there are many target loci),

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the relative simplicity and qualitative nature of the assay (which may often require only inspection), and the fact that compensatory changes in gene expression are unlikely to ‘‘correct’’ a developmental defect and thus mask its occurrence (as compared to physiological/ metabolic parameters, as discussed below). Furthermore, the present wealth of knowledge regarding the genetic basis of development often allows investigators to rapidly integrate novel findings into existing paradigms. This is crucial, as the entire premise of a phenotype-driven approach is that genes that are previously entirely uncharacterized or would not necessarily be presumed to play a role in a specific biological process will be identified. The ability to assign mechanism to genes of unexpected consequence can rapidly enlarge our understanding of functional interactions. However, integrating a novel gene with limited functional annotation into a mechanistic understanding of the developmental phenotype will often be a significant task. This success is best exemplified by the role that mutagenesis has had in delineating the importance of primary cilia in mediating Hedgehog signaling. Much of this insight has been obtained from studies by Anderson and colleagues of mutants ascertained at midgestation with morphological defects (Caspary et al., 2007; Garcia-Garcia et al., 2005; Huangfu et al., 2003; Liem et al., 2009; Ocbina and Anderson, 2008; Weatherbee et al., 2009). These were examined for abnormalities in neural tube patterning, and then more specifically by genetic and biochemical analysis for perturbation of the Hedgehog pathway. Unexpectedly, many of these proved to be genes previously implicated in flagellar function in Chlamydomonas, and, by extension, cilial function in vertebrates. Genes uncovered in mutagenesis studies by other investigators have contributed to understanding this pathway as well (Endoh-Yamagami et al., 2009; Ermakov et al., 2009; May et al., 2005; Tran et al., 2008). A method to increase the sensitivity of developmental phenotyping is to highlight a structure of interest beyond what one can assess by inspection. This can be done in a tissue-specific fashion in situ using immunohistochemistry or RNA hybridization (Mar et al., 2005). However, this will require a significant increase in effort as well as the amount of time necessary for determining which animals have a phenotype of interest. The latter is not a trivial concern as a major challenge to an efficient screen is the speed with which a determination can be made that a given line is worthy of interest. One way to significantly decrease the assay time for tissue-specific analysis is to use a genetic model that carries either a transgene or ‘‘knock-in’’ allele that expresses a reporter in an informative pattern. While a modest amount of additional effort is required to genotype carriers for use during the husbandry, this can be readily justified by the marked increase in sensitivity (Zarbalis et al., 2004). Ideally, these reporters are from inbred strains with a uniform background, although some genetic

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heterogeneity can be tolerated. In the use of a reporter strain, investigators must be aware of the possibility that an ENU mutation could affect the expression of the transgene/‘‘knock-in’’ itself without directly changing the nature of the tissue normally expressing the transgene (i.e., a regulatory mutation affecting the reporter locus). As such, an independent method to validate the presumptive phenotype of any potential mutations would be useful (e.g., immunohistochemical analysis of a protein expressed in the same spatiotemporal domain). Most reporter alleles take advantage of either green fluorescent protein (GFP) or beta-galactosidase (bgal). If GFP is the reporter of choice, investigators should be aware that the phenotype analysis will likely have to be done immediately upon embryo or tissue harvesting. This requires significant periods of access to a fluorescent microscope and may be difficult to do in addition to dissections and tissue preparation in any given work session. If bgal reporters are used, the tissue must be lightly fixed and the X-gal stain added. However, the analysis of the bgal expression pattern can be done in a separate work session as the substrate is stable for some time. Additionally, bgal staining can be seen more clearly in thicker blocks of tissue whereas the GFP is more useful in early embryos or transparent organs. If a reporter allele is to be used, a test cross to show that the reporter can indeed highlight a phenotype of interest is a desirable early step in evaluation of the allele. Crossing of the reporter with a previously characterized mutation known to perturb the tissue of interest should allow the investigator to ascertain putative homozygous mutants by examination for altered expression of the reporter. These can then be verified by genotyping to test the sensitivity and reliability of the reporter.

2.2. Metabolic phenotypes These have been the focus of a number of screening efforts, with a mixed history of success. These screens have been particularly compelling given the relevance of many of the screened phenotypes to human disease. Further, highly sensitive assays have been developed for many clinically relevant traits, and the importance of these for diagnostic testing has facilitated their translation into technically simple and/or automated tests that are amenable for high-throughput analysis. Application of these assays to mutagenesis screens has yielded a wealth of mutations affecting basic metabolic processes, which often serve as models of corresponding human diseases (Aigner et al., 2009a). Interestingly, some traits appear less amenable to perturbation using mutagenesis (Aigner et al., 2009b). This is likely due either to the fact that such perturbations are not tolerated, leading to early lethality, or that compensatory metabolic changes make allelic variants difficult to detect.

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2.3. Physiological phenotypes This class is similar to the metabolic class, with respect to medical relevance and the existence of sensitive assays that have been adapted for analysis of rodent models. However, there are some important differences. Firstly, these assays are often time, labor, and resource-intensive, making them less amenable to analysis of large numbers of mice. Secondly, physiological traits may show considerable normal variation, making it more difficult to distinguish new mutants. This may be further compounded during the mapping analysis, as strain-specific effects may result in additional variation in intercross or backcross progeny. Despite this, there have been notable efforts to develop systematic high-throughput protocols to achieve efficiency and consistency (Hardisty-Hughes et al., 2010).

2.4. Cellular phenotypes One area of considerable success is the utilization of cell-based assays for screening. While the extraction and preparation of the cells themselves requires effort, the assays themselves are frequently amenable to large-scale analysis. The identification of variants in immune function has been particularly productive (Cook et al., 2006; Georgel et al., 2008). This is due in part to the routine use of cell-based assays as part of immunological investigation, the relative ease of sample preparation, and the fact that, for analyses using peripheral blood, the mutant mice can continue to be bred after phenotyping. However, even more complex cell-based assays, such as those analyzing genome stability and DNA replication, have been successful as well (Shima et al., 2003). One caveat for this approach is that the rationale for organismal mutagenesis to obtain a cellular phenotype must be carefully considered, given the ability to directly knockdown gene expression in cells using RNAi technology (Nybakken et al., 2005).

2.5. Behavioral phenotypes There has been considerable interest in obtaining behavioral mutants using mouse mutagenesis, as modeling human cerebral function is not readily done in lower organisms. However, behavioral assays have unique challenges with respect to throughput and reproducibility (Crabbe et al., 1999; Mandillo et al., 2008). That said, the identification and characterization of the clock mutant by Takahashi and colleagues is notable both for its importance to our understanding of the molecular basis of circadian rhythm, and its success at a time when genomic tools for positional cloning were not yet well developed (Vitaterna et al., 1994). The key to this experiment was having a sensitive and highly reproducible quantitative assay, as well as a

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relatively narrow range of normal variation. Thus, a well-designed assay for behavioral traits is amenable to application in a mutagenesis screen.

2.6. Suppressor/enhancer phenotypes A strategy well proven in lower organisms that has been productively translated to mouse mutagenesis is the generation of modifier loci. This is done by including mice carrying a known mutation in a mutagenesis experiment, and then screening for loci that enhance or diminish the phenotypic effect of the mutant locus (Kauppi et al., 2008; Matera et al., 2008). The fact that unlinked genetic loci affect phenotypic expression in mice has long been evident by virtue of the fact that this can vary substantially depending upon strain background. However, efforts to identify the specific modifying loci using genetic analysis have had limited success, due to the difficulty in obtaining a high degree of genetic resolution, coupled with the large number of strain-specific DNA sequence variants. While it may seem at first glance that the effort required to generate modifier loci by de novo mutagenesis is inefficient, the fact that, once obtained, they can be unambiguously identified using positional cloning techniques makes this approach compelling, especially as these techniques are constantly being enhanced as genomic technology advances. A limitation of this approach is that mutagenesis will more likely create loss-of-function mutations, so certain classes of modifying loci (i.e., gain of function or those caused by increased expression) will be less efficiently uncovered. Furthermore, if a novel phenotype is seen, it will be necessary to determine if indeed this is truly dependent on the sensitizing locus by testing whether it segregates with the mutation.

3. ENU Treatment ENU is a potent mutagen and one should take care to use all appropriate personal protective equipment. Injections are best done in a hardducted fume hood and protocols should be discussed with animal facility staff and supervisory personnel. ENU obtained from Sigma comes within an ISOPAC unit; to ensure maximal ENU effectiveness, a fresh ISOPAC should be used for each session of ENU treatment and injections performed within a few hours of preparing the solution. Initially, dissolve the ENU by injecting 10 ml of 95% ethanol with a 10-ml syringe and 16-gauge needle. To relieve pressure in the ISOPAC, vent the container using a second 16gauge needle. Hand-warm the solution and inspect to insure the ENU is fully dissolved—the solution will be completely clear and yellow. Further dilute the ENU with 90 ml of the phosphate/citrate diluent buffer (100 mM

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sodium phosphate dibasic (14.2 g/l solution), 50 mM sodium citrate (14.7 g sodium citrate dihydrate per liter solution), adjust pH to 5.0 using phosphoric acid). This dilution is most easily done with two injections of 45 ml. Again, be aware of the pressure inside the ISOPAC and pause at approximately each 10 ml of injection to allow pressure to vent. ENU is light sensitive so the container should be covered in foil. The actual concentration of ENU needs to be determined experimentally to ensure appropriate dosage. Use a 1-ml syringe and 27-gauge needle to remove 200 ml of the ENU solution from the ISOPAC and add 800 ml of diluent buffer (a 1:5 dilution). Prepare a blank solution of 20 ml 95% ethanol and 980 ml diluent buffer and prepare spectrophotometer. Transfer the diluted ENU solution to a disposable spectrophotometer cuvette and perform a wavelength scan from 350 to 450 nm. An effective preparation of ENU will have a peak centered at 398 nm. Measure the absorbance at 398 nm; a typical reading will be 1.3–1.5. Calculate the concentration of ENU with the reference point of 1 mg/ml at OD398 ¼ 0.72. Concentration in mg/ml ¼ (OD at 398 nm/0.72)
5 [to correct for the dilution]. Each mouse should be weighed and the required injection volume calculated according to the following formula: Injection volume ¼ ðmass of animalÞ
ðENU doseÞ
ð0:001Þ=ENU stock concentration The ENU solution is injected intraperitoneally. Shortly after injection, the mice may appear wobbly due to alcoholic solvent of ENU. After injection, inactivate remaining ENU solution by injecting 20–30 ml of alkaline thiosulfate inactivating solution (0.1 M NaOH (4 g/l solution), 20% (w/v) sodium thiosulfate (200 g/l solution)) into the ISOPAC. Leave one syringe in ISOPAC vessel in fume hood to allow gas to escape and leave in the fume hood overnight. Soak all equipment coming into contact with ENU with inactivating solution and dispose of as biohazardous materials. Mice should stay within the fume hood 24–48 h to allow for the ENU to become inactivated before returning to standard colony housing. Any ENU not absorbed by the tissues will be excreted and disposed of with all bedding. Before returning treated animals, transfer to a new cage and mix old bedding with the inactivating solution before disposal. An important consideration is the choice of mouse strain to be mutagenized. The ideal strain is one which is known to breed well, able to tolerate ENU treatment, and does not have strain-specific effects on the tissue of interest. Fortunately, work has been done in this area to determine which strains are most tolerant of ENU treatments ( Justice et al., 2000; Weber et al., 2000). Popular choices include A/J, C3H, and C57BL/6. In our lab, we generally use A/J and outcross to FVB to take advantage of

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the tolerance of A/J to ENU treatment and the high fecundity of FVB. We have avoided mutagenizing B6, as we often introduce the mutation into this background by serial backcross, and the A/J alleles linked to the mutant locus provide a convenient means to identify carriers prior to mutation identification. However, the possibility of mutation identification using high-throughput sequencing, which we discuss below, may make this less necessary. Male mice treated with a mutagenic dose of ENU will lose fertility, which will return 8–12 weeks after treatment as the gamete cell lineage is repopulated. The long-term survival of these animals is compromised as compared to untreated animals due to somatic mutations induced by ENU, so treated animals have a somewhat limited time to pass on the mutations. In our experience, however, survival is sufficient to create an adequate number of offspring (Fig. 17.2). We generally treat 20 G0 mice and aim to obtain 75–100 G1 males. While there are standardized doses of ENU likely to be mutagenic that can be employed (Weber et al., 2000), we have had success using an empirical strategy to determine the most effective treatment regimen. In this approach, we treat G0 mice with a range of doses (e.g., with i.p. injections of 3
90, 3
95, or 3
100 mg ENU/g body weight), test injected males for recovery of fertility, and then use those treated with the highest doses for generation of G1 progeny.

120

Percent survival

100 80 60 40 20 0

1

4

7

10 13 16 19 22 25 28 31 34 37 40 43 46 49 Weeks postinjection

Figure 17.2 Percent survival of G0 male mice treated with ENU over time. Results of two mutagenesis experiments are shown (solid and broken lines).

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When breeding the mutagenized (G0) males, it is important to try and preserve offspring from as many different productive G0 males as possible. This is necessary in order to capture as broad a range of ENU mutations as possible and not to limit this to the set of mutations present in the germ line from any given mutagenized male, which is repopulated by a finite (and potentially small) cohort of spermatagonial stem cells. The G1 progeny generated by breeding the G0 males are either examined directly (for detection of mutations which have their effects as heterozygotes) or the males are further bred, such that each of these is the ‘‘founder’’ of an individual line or family. As noted, genetic informativeness for mapping purposes can be introduced by mating G0 or G1 males with females from a different inbred strain. Also, screens requiring utilization of specific mutant loci (transgenic reporters, sensitizing loci) can be introduced at these breeding steps. An alternative to the breeding strategy described above is to intercross G1 mice and then intercross their G2 progeny. The third generation is then examined for mutants. This approach has the virtue of introducing twice as many mutants into a pedigree (because both G1 parents are mutagenized) (Silver et al., 2007). However, as any two G2 mice have only a 25% chance of both being heterozygous, a large number of mating pairs are necessary to comprehensively test a single family for the presence of a mutation of interest (compared to the three to four litters required for a conventional analysis, as discussed below).

4. Mutant Ascertainment As previously noted, the appropriate population for screening to identify recessive mutations are the G3 progeny of (G1
G2) mice (Fig. 17.1). If the phenotype of interest is not likely to be compatible with postnatal survival, one would sacrifice pregnant G2 females on day 18 of pregnancy (immediately before birth in most strains) or earlier and examine the G3 fetuses. The embryos to be analyzed can be staged to the investigator’s preference by examinations of G2 matings for vaginal plugs (‘‘timed pregnancies’’). Abnormalities that may be readily identified by this embryonic analysis include neural tube defects (both exencephaly and spina bifida), limb or other skeletal defects, facial clefting, eye anomalies such as micropthalmia or open eyelids, or paleness (secondary to anemia). Further, an internal exam can be performed to identify abnormalities in patterning and specific defects in organogenesis, or to obtain tissue for histological studies. For phenotypes that are compatible with postnatal survival, the G2 female can either be left with its G1 mate, as it will go into estrus after giving birth, facilitating the generation of additional G3 mice for analysis, or the G1 mating can be renewed after the G3 progeny are weaned.

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An important consideration is the estimation of how many litters from any G1 parent should be analyzed. For a highly penetrant phenotype, one can recommend that at least three litters from each G1 male be examined. The rationale for this is as follows: If one obtains at least three G2 daughters from each G1 male, there is an 87.5% chance that at least one of them is a heterozygote like the father. (For each G2 female resulting from a cross between a heterozygous mutant (m/þ) G1 male with a þ/þ female, there is a 50% chance that she will be m/þ. With three such G2 females, the likelihood of at least one heterozygote being produced is unity less the probability that none will be produced, or 1
0.53 ¼ 0.875.) If you examine a litter of eight from a cross between a G1 male m/þ and a G2 m/þ female, you will have a 90% chance of producing at least one homozygous m/m G3 animal. (This figure again is obtained by subtracting from 1 the probability that none will be produced; i.e., 1  0.758 ¼ 0.90). Therefore, if by looking at three G2 females you have a 87.5% likelihood of successfully producing at least one heterozygote and by looking at eight G3 animals you have a 90% likelihood of producing at least one m/m G3 animal (given that the mother is a heterozygote), then the overall likelihood of identifying a mutation carried by the G1 male is the product of these two probabilities, or nearly 80% (0.875
0.90 ¼ 0.79). Thus, an analysis of three litters provides reasonable confidence one will identify a fully penetrant mutation, and examination of additional litters adds only modest power. That this approach may be biased to ascertainment of highly penetrant mutations may be considered an advantage, as these will be more efficiently mapped and characterized. Note that this calculation does not factor in the use of transgenic or mutant lines in the analysis; this will reduce power (unless every mouse in the screen is a carrier) and appropriate correction should be made. When an abnormal phenotype of interest is identified, the G1 male should be crossed to additional G2 daughters in order to validate the phenotype and begin the mapping process. A phenotype found in a single litter may be due to multigenic or somatically determined causes. However, because of the multigeneration nature of the cross, a phenotype found reproducibly in G3 litters obtained from different G2 mothers is statistically likely to be monogenic, which is supported by our empirical experience. Once an abnormal phenotype is found in multiple G3 litters, the cross should be maintained and expanded in order to obtain sufficient affected mice for further analysis.

5. Mutation Identification Once a mutant line has been established, it is necessary to pursue genetic mapping in order to facilitate positional cloning (although rapid developments in sequencing technology may make this optional, as discussed below).

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If a mutant screen has been performed in an inbred strain, it will be necessary to set up a standard mapping cross; for example, crossing the mutant to a different strain and intercrossing heterozygous carriers. If the mutant is not viable or fertile, progeny testing is required to identify the carrier mice. However, as noted above, introduction of a different strain into the screening protocol will introduce genetic informativeness, such that the mutant locus can be mapped using the same mice in which the mutation was identified. This is because, for a recessive mutation, all of the affected mice will be homozygous for the mutagenized parental background at the causal locus, while the (unlinked) remainder of the genome will segregate randomly. Indeed, the breeding strategy described by Bode adds an additional generation to that used in a standard mapping cross, which, if done as an outcross, further decreases the representation of mutagenized parental alleles, and makes identification of the mutant locus more efficient. Specifically, in any single mouse, the likelihood that a recessive mutant locus is homozygous for the parental mutagenized background is 100%, while the likelihood of an unlinked locus being homozygous is only 12.5%. Taking advantage of this, we have been able to map mutants with as few as three affected mice (in which the likelihood of a single locus being homozygous for the parental mutagenized background by random chance is 0.2%). In any case, the technical task of genetic mapping (at least to moderate resolution) has been hugely simplified by the development of automated genome-wide SNP analysis methods (Moran et al., 2006). There exists sufficient diversity between most inbred strains that a fixed panel provides ample marker density (i.e., selection of specific markers is unnecessary), and map resolution is usually limited more by the number of mice tested than by SNP informativeness. These assays are routinely performed at genotyping centers and core facilities, and the per-sample cost is modest for the number of loci tested. A primary goal of genetic mapping is to identify and exclude remutations in well-characterized genes. This can be done by examining the recombinant interval for genes known to have mutant phenotypes that are comparable to the mapped mutation. This obviously will not be conclusive, as it would require comprehensive knowledge of the mutant phenotypes of large numbers of loci. In addition to the literature, there are resources to facilitate this approach, such as the phenotype query function of the Mouse Genome Database: http://www.informatics.jax.org. The reason to rapidly identify remutations is to avoid the unnecessary commitment of resources to high-resolution mapping crosses. This is not to say that remutations in known genes are of no interest, as the determination of the specific base change can potentially be informative with respect to gene structure– function relationships (Bialek et al., 2004). A problem for genetic mapping analysis is that initial localization via a genome-wide SNP panel often defines a moderate-size chromosomal interval

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(30 Mb in our experience), and ‘‘bench-top’’ technologies for finemapping using SNPs are inefficient. We have developed a Web-based tool, SNP2RFLP, which can extract region-specific SNPs from the dbSNP database and identify those that create restriction fragment length polymorphisms (RFLPs) (Beckstead et al., 2008; http://genetics.bwh.harvard.edu/snp2rflp). This information can then be used to develop an RFLP assay and further refine the region containing the mutation of interest. Alternatively, microsatellite markers can be identified using genome databases (such as the UCSC genome browser; http://genome.ucsc.edu/), and allele variation can be queried using resources such as MGI (http://www.informatics.jax.org). Finally, it may be simplest to identify SNPs in the region using database or browser queries, and sequence these directly in the set of mice for which the recombinant interval remains indeterminate. A tool for positional cloning that has been perhaps underutilized in ENU mutagenesis studies is the use of microarray analysis as a means to identify candidate genes for mutational analysis. This is probably the case because one might not expect the single-base changes induced by ENU to affect mRNA expression. However, many ENU-induced mutations affect splicing, and ENU-induced mutations in coding regions can result in nonsense-mediated decay of mRNA. This approach has the virtue that it can be employed even when the mapping resolution is moderate, is low cost, and may allow one to identify a candidate locus without the husbandry required for a high-resolution analysis. Since the recombinant interval containing the mutation is known, one can examine specifically expression differences in that region; that is, genomewide thresholds for significance do not need to be applied. Furthermore, while an initial characterization of a microarray dataset would focus on differential mRNA expression to identify the causal locus, this expression data could also become useful when trying to determine the molecular mechanism underlying the phenotype at later stages of analysis. One caveat for this approach is that the expression differences may exist in the recombinant interval that are strainspecific, and unrelated to the mutation. These will be discovered if one compares mutant and wild-type littermates from an outcross, as they will be discordant for strain background around the mutant locus. Consequently, presumptive differential expression should be validated using comparison to wild-type mice of the mutagenized parental background. Once a mutant locus has been localized, it is necessary to identify sequence variants in candidate genes. This is an area of such rapidly evolving technology that one can be sure what is written here will be dated by the time it is published. Historically, one selected candidate genes based on examination of the recombinant interval and inferences from data on gene expression and function. This has been recently facilitated by databases of tissue- or temporal-specific expression data, usually obtained from microarray analysis. Genes of interest would then be sequenced, using either genomic templates and analysis of exons and their flanking splice junctions,

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and/or cDNA templates and analysis of transcripts. While it is certainly possible that a causal mutation will occur in nontranscribed sequences, there is presently only one report documenting an ENU-induced mutation occurring in a regulatory region (Sagai et al., 2004). There is also a recent report describing an ENU-induced mutation in a microRNA seed region (Lewis et al., 2009). There is clearly bias in the conclusion that exons and their flanking regions are likely to contain the mutated nucleotide, as nontranscribed regions are rarely examined in detail. However, in the characterization of ENU mutants mapped to loci where known candidates exist, presumptively causal sequence variants can usually be found in coding regions or splice sites (Hart et al., 2005). Using the above approach, a necessary task was to narrow the recombinant interval as much as possible to constrain the number of candidate genes. This would typically require the analysis of hundreds of intercross or backcross progeny, which was both costly and slow. With the development of means for efficient sequencing of exons, generally by hybridization capture, as well as improved gene annotation, high-resolution mapping is less compelling. That is, it is feasible to sequence the entire predicted exon complement from any specified region (or the entire genome). Furthermore, there are sufficient SNPs in coding regions that this analysis can be used to delineate the map position directly from the sequence characterization of a pooled sample (in which all mice will be homozygous for the mutagenized parental background in the region of the mutant locus); that is, a separate mapping analysis may be unnecessary (but perhaps still advisable, given the low cost). Further, whole exome sequencing may make it unnecessary to map at all. That is, one can contemplate sequencing a pooled sample of affected mice that were never outcrossed; while there will be many mutations segregating in the population, only one (or a few tightly linked variants) will be homozygous in all affected mice, and will appear as a difference from a reference genome. Finally, it seems inevitable that decreasing costs for whole genome sequencing will eventually make the exon capture step unnecessary, and one will proceed very rapidly from ascertaining mutants to querying their entire genome for mutations. A caution for this utopian vision is the computational task required for managing the data from these analyses will be immense, and the technical limitations that will qualify its application (such as error rates and coverage issues) still need to be addressed.

6. Mutation Validation A significant issue with respect to chemical mutagenesis is the fact that, for many mutant loci, only the single ENU-induced allele may exist. Thus, a validation step is necessary to prove that the presumptive mutant gene is

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indeed causal for the observed phenotype. This will increasingly be an issue to the extent that advances in sequencing technologies will not require that the mutant locus be resolved to high resolution by genetic mapping. Given that the mutation rate of ENU treatment is 0.5–2 Mb 1, sequencing will uncover many variants within recombinant intervals of moderate resolution (Boles et al., 2009). While causality can be suggested by functional studies, a formal proof requires either correcting the defect by complementation or identifying independent alleles. The former can be achieved by BAC transgenesis; however, this is expensive and time-consuming. Further, if it is necessary to create novel mouse strains, it will generally be more useful to generate a conditional or reporter-tagged allele by homologous recombination, despite the additional work this may entail. This is particularly the case for hypomorphic mutations, since it will be of interest to determine the null phenotype. Recent developments in gene targeting technologies have made it practical to propose to do this on significant numbers of mutant lines. The generation of targeted mutants is being hugely facilitated by international mouse knockout projects such as KOMP, EuCOMM, and NorCOMM that are on target to generate their combined goal of 14,000 mutant ES cells (Int’l_Mouse_Knockout_Consortium, 2007). Genes of interest can be queried using the IKMC (http://www.knockoutmouse.org/) database, and cells and mice are available from mutant respositories (e.g., Mutant Mouse Regional Resource Centers; http://www.mmrrc.org/). However, not all genes will be targeted, many will not have conditional alleles, and germ-line potential of clones, while high, is not 100%. To address this, we have pursued a strategy of embryonic expression of ‘‘transient’’ transgenic RNAi as a means to validate candidate mutations as causal. In this case, ‘‘transient’’ means that the microinjected embryos are directly examined, and not grown to generate stable transgenic lines. This is a common strategy for the in vivo analysis of enhancers, as it is often necessary to examine many deletion variants. This approach is theoretically ideal for mutation validation, as one could evaluate knockdown phenotypes within several weeks of microinjection, obviating the need for the establishment of permanent knockout lines. The major obstacles are the variability of expression knockdown, and the efficiency of generating mice expressing the dsRNA. The former is possibly less of a problem, as one can screen for dsRNA constructs that generate efficient knockdown by testing them in vitro. Further, some variation in knockdown could be highly informative, as many ENU-induced mutations are hypomorphic, and a complete null may prove to have a more severe phenotype that is not readily comparable to the ENU mutant. However, this makes the latter problem of efficiency all the more compelling, as it is necessary to generate reasonably large numbers of knockdown embryos in order to assess the range of phenotypes in a population.

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Given this, the traditional strategy of microinjection to make transient transgenic mice, which may yield 10–20% positive embryos, is unattractive. We have taken advantage of the observation that transposable elements such as Sleeping Beauty or PiggyBac can facilitate transgenesis. We have found that injection of a vector carrying PiggyBac transposon that expresses an shRNA driven by the U6 Pol III promoter, along with transposase mRNA can achieve a high degree of transgenesis (> 50%) along with efficient gene knockdown and phenotypic reproducibility (unpublished data).

7. Summary Phenotype-driven analysis in the mouse has been enabled by the pioneering efforts of a small cohort of mouse geneticists coupled with the more recent application of genomic analysis to this approach by investigators with specific interests in mammalian biology. The technique has lived up to its promise as a means to provide novel and unexpected insight into the role of specific genes in a myriad of biological processes. Continuing progress in genomic technology makes this method even more compelling, and it will serve as a productive complement to genotype-driven strategies employing, for example, knockout mice. As many of the components of a mutagenesis approach have been well proven, the key to its success is primarily the selection of a phenotype screen that is definitive and applicable to high-throughput analysis. In addition, careful attention to the logistic task of characterizing large numbers of mice and pursuing genetic analysis in the subset of phenotypic interest will facilitate a productive effort.

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