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Summary The complex 16p11.2 deletion syndrome (16pdel) is accompanied by neurological disorders, including epilepsy, autism spectrum disorder, and intellectual disability. We demonstrated that 16pdel iPSC differentiated neurons from affected people show augmented local field potential activity and altered ceramide-related lipid species relative to unaffected. FAM57B, a poorly characterized gene in the 16p11.2 interval, has emerged as a candidate tied to symptomatology. We found that FAM57B modulates ceramide synthase (CerS) activity, but is not a CerS per se. In FAM57B mutant human neuronal cells and zebrafish brain, composition and levels of sphingolipids and glycerolipids associated with cellular membranes are disrupted. Consistently, we observed aberrant plasma membrane architecture and synaptic protein mislocalization, which were accompanied by depressed brain and behavioral activity. Together, these results suggest that haploinsufficiency of FAM57B contributes to changes in neuronal activity and function in 16pdel syndrome through a crucial role for the gene in lipid metabolism., Graphical abstract, Highlights • Augmented LFP activity and sex-specific differences in 16pdel neurons • 16pdel neuronal lipidome indicated altered ceramide related species • FAM57B is a ceramide synthase modulator essential for lipid regulation in the brain • FAM57B functions in synaptogenesis, synapse architecture, and composition, Cellular neuroscience; Developmental neuroscience; Molecular neuroscience; Neuroscience

ObjectiveHealth systems rely on multiple approaches for population-level risk stratification/management. However, they can under-represent members with rising risk and complex treatment needs. To address these gaps and broaden the coverage of members at risk, we present an accretive framework of six predictive models across complementary risk measures for population-level stratification/management.Materials and MethodsLogistic regression models were trained/tested for six outcomes across cost (rising and elevated cost), utilization (rising and elevated utilization), and chronic-disease related (multimorbidities and polypharmacy) risk measures in 2016 using claims-based features from 2015 for ∼8.97 million members in a nation-wide administrative claims database. Model performances were validated against a holdout cohort of ∼2.99 million members. The presence/absence of each outcome prediction for members was summed into an accretive predictive risk index (aPRI) for population-level risk stratification evaluation.ResultsIntegrating predictions from the six models enabled member stratification across risk measures including future costs, utilizations, and comorbidities. Each of the risk predictions is represented in aPRI levels 0– 6, and their underlying model probabilities/risk measures increase with increasing aPRI levels. ∼83% of members grouped into a “low risk” (aPRI = 0) or “rising risk” category (aPRI = 1 - 2) and ∼17% into a “high risk” (aPRI = 3 - 6) category. Overlap/correlation analyses of risk predictions and comparison of their drivers further support the complementarity of predictions within aPRI and its enhanced coverage of members at risk.DiscussionBy integrating targeted and complementary risk predictions, aPRI enhances current population-level risk stratification approaches.ConclusionWe have developed an accretive predictive modeling framework for enhanced population-level risk stratification/management.

ObjectivePredicting who is likely to become utilizers of specialty drugs allows care managers to have an early intervention and payers to have financial preparation for the upcoming spending. Our administrative claims-based predictive model is to predict the members who might use specialty drugs.Materials and MethodsA national database* and a commercial health plan claim data were used to select a total 6.5 million people who were not taking any specialty drugs before the Target Prediction Window. There were about 136,700 members who were older than 65 in the study. We extracted 81 features from past history of medical, pharmacy claims, and demographic data to predict the specialty drug use in the following year. Members having at least three-month continuous enrollment either under medical or pharmacy plan in the previous year immediately before the start of the target prediction window and with no specialty drug taking history were eligible for this study. We trained and tuned on 75% of the data using an extreme gradient boosting binary classifier. We used the remaining 25% of the data to predict the outcomes and evaluate the performance. We also recorded the performance for the age group older than 65 years old.ResultsThere were 3% of members who used specialty drugs in the cohort under the current study. The important features for prediction included age, monthly pharmacy payment, monthly medical payment, diseases, procedure, or drug-related codes. On the test data with members of all ages, model performance for the area under the receiving operator characteristics curve (AUROC) was 78.6%. For the test set on members older than 65 (prevalence rate 3.6%), we had an AUROC of 79.3%.DiscussionThere is no similar machine learning model in the field to predict specialty drug use. Our model provides an unparalleled opportunity to allow early intervention for people who might develop diseases that require specialty drug use. It is also important for health plans and providers to know their covered population who might use specialty drugs and predict the increased cost in the next year.ConclusionA predictive model of specialty drug use can be helpful for both payers and providers to prepare for a spending spike or have an early intervention. In return, this helps to improve patients’ overall satisfaction.

ObjectiveWe recently reported that hypertension (HTN) patients having at least three rounds of distinct treatment options (atl_three_roto) in a 12-month window have elevated risk of next-year complications. However, early identification of these “challenge to treat” patients is non-trivial and “drivers” of complications in these vs remaining HTN patients are not fully defined. To address these challenges/gaps, we present predictive models for preceding outcomes, delineate their “drivers”, and highlight value of their integration for population level risk stratification/management of HTN patients.Materials and Methods2.47 million HTN patients enrolled through 2015-2016 were selected from a nation-wide commercial claims database. Features associated with their treatment patterns, comedications, and comorbidities were extracted for 2015 and used to model/predict 2016 outcomes of atl_three_roto status and/or HTN complications. Logistic regression-derived odds-ratios were used to delineate drivers of each outcome.ResultsPrior year treatment patterns, specific hypertension drugs (anti-hypertensives, calcium channel blockers, beta blockers), and congestive heart failure most increased future odds of atl_three_roto status. Regardless of prior year atl_three_roto status, specific comorbidities (renal disease, congestive heart failure, myocardial infarction, vascular disease, diabetes with chronic complications) and comedications (beta blockers, cardiac agents, anti-lipidemics) most increased future odds of HTN complications. Proof-of-concept analysis with an independent dataset demonstrated that integrating these model predictions/drivers thereof can be leveraged for risk stratification/management of HTN patients.DiscussionIntegrating predictions and their “drivers” from above models supports early identification and targeted management of “at-risk” HTN patients.ConclusionWe have developed a predictive modeling based approach for risk stratification and management of HTN patients.

The complex 16p11.2 Deletion Syndrome (16pdel) is accompanied by neurological disorders, including epilepsy, autism spectrum disorder and intellectual disability. We demonstrate that 16pdel iPSC differentiated neurons showed augmented local field potential activity and altered ceramide-related lipid species relative to unaffected. FAM57B, a poorly characterized gene in the 16p11.2 interval, has emerged as a candidate tied to symptomatology. We found that FAM57B modulates ceramide synthase (CerS) activity, but is not a CerS per se. In FAM57B mutant human neuronal cells and zebrafish brain, composition and levels of sphingolipids and glycerolipids associated with cellular membranes are disrupted. Consistently, we observed aberrant plasma membrane architecture and synaptic protein mislocalization, which were accompanied by depressed brain and behavioral activity. Together, these results suggest that haploinsufficiency of FAM57B contributes to changes in neuronal activity and function in 16pdel Syndrome, through a crucial role for the gene in lipid metabolism.

The complex 16p11.2 Deletion Syndrome (16pdel) is accompanied by neurological disorders, including epilepsy, autism spectrum disorder and intellectual disability. We demonstrated that 16pdel iPSC differentiated neurons show augmented local field potential activity and altered ceramide-related lipid species relative to unaffected. FAM57B, a poorly characterized gene in the 16p11.2 interval, has emerged as a candidate tied to symptomatology. We found that FAM57B modulates ceramide synthase (CerS) activity, but is not a CerS per se. In FAM57B mutant human neuronal cells and zebrafish brain, composition and levels of sphingolipids and glycerolipids associated with cellular membranes are disrupted. Consistently, we observed aberrant plasma membrane architecture and synaptic protein mislocalization, which were accompanied by depressed brain and behavioral activity. Together, these results suggest that haploinsufficiency of FAM57B contributes to changes in neuronal activity and function in 16pdel Syndrome, through a crucial role for the gene in lipid metabolism.

ObjectiveA challenge in hypertension-related risk management is identifying which people are likely to develop future complications. To address this, we present administrative-claims based predictive models for hypertension-related complications.Materials and MethodsWe used a national database to select 1,767,559 people with hypertension and extracted 112 features from past claims data based on their ability to predict hypertension complications in the next year. Complications affecting kidney, brain, and heart were grouped by clinical severity into three stages. Extreme gradient boosting binary classifiers for each stage were trained and tuned on 75% of the data, and performance on predicting outcomes for the remaining data and an independent dataset was evaluated.ResultsIn the cohort under study, 6%, 17%, and 7% of people experienced a hypertension-related complication of stage 1, stage 2, or stage 3 severity, respectively. On an independent dataset, models for all three stages performed competitively with other published algorithms by the most commonly reported metric, area under the receiver operating characteristic curve, which ranged from 0.82-0.89. Features that were important across all models for predictions included total medical cost, cost related to hypertension, age, and number of outpatient visits.DiscussionThe model for stage 1 complications, such as left ventricular hypertrophy and retinopathy, is in contrast to other offerings in the field, which focus on more serious issues such as heart failure and stroke, and affords unique opportunities to intervene during earlier stages.ConclusionPredictive analytics for hypertension outcomes can be leveraged to help mitigate the immense healthcare burden of uncontrolled hypertension.LAY SUMMARYAs the leading preventable risk factor for morbidity and mortality in the world, identifying which people with hypertension are likely to exacerbate is critically important for development of effective intervention strategies. Here we present a suite of predictive models that can predict future risk of development of hypertension-related complications. To have utility for triaging as well as identifying mild cases before they progress to critical end phases, the models predict three different stages of severity of hypertension-related complications. Our algorithms utilize variables calculated for the most recent 12 months, and predict probability of a hypertension-related complication for the next 12 months using administrative claims as the data source. Because the types of complications that have been analyzed can also result from comorbidities besides hypertension, such as diabetes and hyperlipidemia, these diagnoses are included as variables. Other variables pertain to demographic characteristics, prescription information, relevant procedures, and utilization patterns. Overall, all three models exhibited strong predictive performance. The ability to use straightforward variables found in claims data to predict future risk of disease-related complications, complemented with targeted clinical intervention strategies, has the potential to reduce cost of care and improve health outcomes for the many people living with hypertension.

ObjectiveAlthough treatment patterns’ analyses at scale can provide insights into associated health outcomes, they remain relatively uncharacterized for most chronic diseases, including hypertension (HTN). To address this gap, we analyzed HTN treatment patterns among US health-insured patients.Materials and MethodsNew (n = 200,786) or all (n = 4.1 million) HTN patients were identified from 2015, 2016 enrollments in a nationwide administrative claims’ database and compared for HTN-specific treatment (Rx) choices, Rx count, and distinct roundsof treatmentoptions (ROTO), respectively. Selected treatment patterns were risk-assessed using predictive modeling and/or literature-based recommendations.ResultsFor 2016, ACE inhibitors/ARBs were most frequent choices in new HTN patients’ vs more diverse Rx-choices among all HTN patients. All HTN patients had ∼3-fold and ∼5-fold-higher prevalence of (same-year) polytherapy and Rx interventions, respectively.New HTN patients with ≥2 rounds of treatment options (vs single/initial round) were associated with ∼5-fold or higher predicted HTN complications’ risk (p-value < 0.0001). All HTN patients with ≥3 rounds of treatment options (vs single/initial round) had 3.8-fold higher next-year HTN complications’ risk (p-value < 0.0001). Co-morbidities/persistence of ≥3 rounds of treatment options over 2 years further increased these odds and total medications/chronic disease score correlated with ROTO counts.Discussion∼95% of new HTN patients in 2016 did not start treatment with current literature-recommended first option, Thiazides. Assuming “sticky” prescription patterns, opportunity exists to improve (current) initial HTN treatments. Additionally, ROTO counts can inform HTN complications’ risk/management thereof.ConclusionWe highlight opportunities to improve initial HTN treatments and treatment patterns associated with higher risk among HTN patients.

Deletion of the 16p11.2 CNV affects 25 core genes and is associated with multiple symptoms affecting brain and body, including seizures, hyperactivity, macrocephaly, and obesity. Available data suggest that most symptoms are controlled by haploinsufficiency of two or more 16p11.2 genes. To identify interacting 16p11.2 genes, we used a pairwise partial loss of function antisense screen for embryonic brain morphology, using the accessible zebrafish model. fam57ba, encoding a ceramide synthase, was identified as interacting with the doc2a gene, encoding a calcium-sensitive exocytosis regulator, a genetic interaction not previously described. Using genetic mutants, we demonstrated that doc2a+/− fam57ba+/− double heterozygotes show hyperactivity and increased seizure susceptibility relative to wild-type or single doc2a−/− or fam57ba−/− mutants. Additionally, doc2a+/− fam57ba+/− double heterozygotes demonstrate the increased body length and head size. Single doc2a+/− and fam57ba+/− heterozygotes do not show a body size increase; however, fam57ba−/− homozygous mutants show a strongly increased head size and body length, suggesting a greater contribution from fam57ba to the haploinsufficient interaction between doc2a and fam57ba. The doc2a+/− fam57ba+/− interaction has not been reported before, nor has any 16p11.2 gene previously been linked to increased body size. These findings demonstrate that one pair of 16p11.2 homologs can regulate both brain and body phenotypes that are reflective of those in people with 16p11.2 deletion. Together, these findings suggest that dysregulation of ceramide pathways and calcium sensitive exocytosis underlies seizures and large body size associated with 16p11.2 homologs in zebrafish. The data inform consideration of mechanisms underlying human 16p11.2 deletion symptoms.

The treatment of psychiatric disorders presents three major challenges to the research and clinical community: defining a genotype associated with a disorder, characterizing the molecular pathology of each disorder and developing new therapies. This Review addresses how cellular and animal systems can help to meet these challenges, with an emphasis on the role of the zebrafish. Genetic changes account for a large proportion of psychiatric disorders and, as gene variants that predispose to psychiatric disease are beginning to be identified in patients, these are tractable for study in cellular and animal systems. Defining cellular and molecular criteria associated with each disorder will help to uncover causal physiological changes in patients and will lead to more objective diagnostic criteria. These criteria should also define co-morbid pathologies within the nervous system or in other organ systems. The definition of genotypes and of any associated pathophysiology is integral to the development of new therapies. Cell culture-based approaches can address these challenges by identifying cellular pathology and by high-throughput screening of gene variants and potential therapeutics. Whole-animal systems can define the broadest function of disorder-associated gene variants and the organismal impact of candidate medications. Given its evolutionary conservation with humans and its experimental tractability, the zebrafish offers several advantages to psychiatric disorder research. These include assays ranging from molecular to behavioural, and capability for chemical screening. There is optimism that the multiple approaches discussed here will link together effectively to provide new diagnostics and treatments for psychiatric patients., Summary: In this review, we discuss strengths and limitations of prevalent laboratory models that are used for understanding psychiatric disorders and developing therapeutics, with emphasis on the zebrafish.

Vertebrate segmentation is controlled by the segmentation clock, a molecular oscillator that regulates gene expression and cycles rapidly. The expression of many genes oscillates during segmentation, including hairy/Enhancer of split-related ( her or Hes ) genes, which encode transcriptional repressors that auto-inhibit their own expression, and deltaC ( dlc ), which encodes a Notch ligand. We previously identified the tortuga (tor) locus in a zebrafish forward genetic screen for genes involved in cyclic transcript regulation and showed that cyclic transcripts accumulate post-splicing in tor mutants. Here we show that cyclic mRNA accumulation in tor mutants is due to loss of pnrc2 , which encodes a proline-rich nuclear receptor co-activator implicated in mRNA decay. Using an inducible in vivo reporter system to analyze transcript stability, we find that the her1 3’UTR confers Pnrc2-dependent instability to a heterologous transcript. her1 mRNA decay is Dicer-independent and likely employs a Pnrc2-Upf1-containing mRNA decay complex. Surprisingly, despite accumulation of cyclic transcripts in pnrc2 -deficient embryos, we find that cyclic protein is expressed normally. Overall, we show that Pnrc2 promotes 3’UTR-mediated decay of developmentally-regulated segmentation clock transcripts and we uncover an additional post-transcriptional regulatory layer that ensures oscillatory protein expression in the absence of cyclic mRNA decay.

Advances in genome-editing technology have made creation of zebrafish mutant lines accessible to the community. Experimental validation of protein knockout is a critical step in verifying null mutants, but this can be a difficult task. Absence of protein can be confirmed by Western blotting; however, this approach requires target-specific antibodies that are generally not available for zebrafish proteins. We address this issue using in vitro translation assays, a fast and standard procedure that can be easily implemented.

Indole-3-carbinol (I3C), a phytochemical derived from cruciferous vegetables such as broccoli and Brussels sprouts, has potent anti-proliferative effects in human breast cancer cells and has been shown to decrease metastatic spread of tumors in experimental animals. Using chemotaxis and fluorescent-bead cell motility assays, we demonstrated that I3C significantly decreased the in vitro migration of MDA-MB-231 cells, a highly invasive breast cancer cell line. Immunofluorescence staining of the actin cytoskeleton revealed that concurrent with the loss of cell motility, I3C treatment significantly increased stress fiber formation. Furthermore, I3C induced the localization of the focal adhesion component vinculin and tyrosine-phosphorylated proteins to the cell periphery, which implicates an indole-dependent enhancement of focal adhesions within the outer boundary of the cells. Co-immunoprecipitation analysis of focal adhesion kinase demonstrated that I3C stimulated the dynamic formation of the focal adhesion protein complex without altering the total level of individual focal adhesion proteins. The RhoA-Rho kinase pathway is involved in stress fiber and focal adhesion formation, and I3C treatment stimulated Rho kinase enzymatic activity, and cofilin phosphorylation, which is a downstream target of Rho kinase signaling, but did not increase the level of active GTP-bound RhoA. Exposure of MDA-MB-231 cells to the Rho kinase inhibitor Y-27632, or expression of dominant negative RhoA ablated the I3C induced formation of stress fibers and of peripheral focal adhesions. Expression of constitutively active RhoA mimicked the I3C effects on both processes. Taken together, our data demonstrate that I3C induces stress fibers and peripheral focal adhesions in a Rho kinase-dependent manner that leads to an inhibition of motility in human breast cancer cells.

We describe here the use of zinc finger nucleases (ZFNs) for somatic and germline disruption of genes in zebrafish (Danio rerio), where targeted mutagenesis was previously intractable. ZFNs induce a targeted double-strand break in the genome that is repaired to generate small insertions and deletions. We designed ZFNs targeting the zebrafish golden and no tail/Brachyury genes. In both cases, injection of ZFN-encoding mRNA into 1-cell embryos yielded a high percentage of animals carrying distinct mutations at the ZFN-specified position and exhibiting expected loss-of-function phenotypes. Disrupted ntl alleles were transmitted from ZFN mRNA-injected founder animals in over half the adults tested at frequencies averaging 20%. The frequency and precision of gene disruption events observed, in combination with the ability to design ZFNs against any locus, open fundamentally novel avenues of experimentation, and suggest that ZFN technology may be widely applied to many organisms that allow mRNA delivery into the fertilized egg.

Mental health disorders are notoriously difficult to diagnose and treat for a variety of reasons, including genetic heterogeneity, comorbidities, and qualitative diagnostic criteria. Discovery of the molecular pathology underlying these disorders is crucial to the development of quantitative biomarkers and novel therapeutics. In this review, we discuss contributions to the mental health field of different cellular and whole-animal approaches in characterizing psychiatric genetics and molecular pathology. These approaches include mammalian cell and neuronal culture, cerebral organoids, induced pluripotent stem cells, and the whole-animal models of nematodes, flies, mollusks, frogs, mice, and zebrafish, on the last of which we place extra emphasis. Integrative use of these cellular and animal systems in a complementary and informative fashion maximizes the potential contributions to the mental health field as a whole.

Deletion or duplication of one copy of the human 16p11.2 interval is tightly associated with impaired brain function, including autism spectrum disorders (ASDs), intellectual disability disorder (IDD) and other phenotypes, indicating the importance of gene dosage in this copy number variant region (CNV). The core of this CNV includes 25 genes; however, the number of genes that contribute to these phenotypes is not known. Furthermore, genes whose functional levels change with deletion or duplication (termed 'dosage sensors'), which can associate the CNV with pathologies, have not been identified in this region. Using the zebrafish as a tool, a set of 16p11.2 homologs was identified, primarily on chromosomes 3 and 12. Use of 11 phenotypic assays, spanning the first 5 days of development, demonstrated that this set of genes is highly active, such that 21 out of the 22 homologs tested showed loss-of-function phenotypes. Most genes in this region were required for nervous system development - impacting brain morphology, eye development, axonal density or organization, and motor response. In general, human genes were able to substitute for the fish homolog, demonstrating orthology and suggesting conserved molecular pathways. In a screen for 16p11.2 genes whose function is sensitive to hemizygosity, the aldolase a (aldoaa) and kinesin family member 22 (kif22) genes were identified as giving clear phenotypes when RNA levels were reduced by ~50%, suggesting that these genes are deletion dosage sensors. This study leads to two major findings. The first is that the 16p11.2 region comprises a highly active set of genes, which could present a large genetic target and might explain why multiple brain function, and other, phenotypes are associated with this interval. The second major finding is that there are (at least) two genes with deletion dosage sensor properties among the 16p11.2 set, and these could link this CNV to brain disorders such as ASD and IDD., Simons Foundation (Grant Number 95091)

Animal models, including the zebrafish, without a reliable embryonic stem cell system are not easily amenable to targeted mutagenesis for studying gene function. Three recent publications have shown that zinc finger nucleases (ZFNs) have circumvented this shortcoming in zebrafish. Similar to restriction enzymes, ZFNs can introduce site-specific double-strand breaks (DSBs); moreover, they can be designed to recognize virtually any target sequence. Because the preferred DSB repair pathway in zebrafish embryos, non-homologous end joining, is error-prone, ZFNs can be used to create mutations in a gene of interest. Here we review the protocols for a yeast-based assay to detect effective ZFNs. Additionally, we detail the procedures for synthesis and injection of ZFN-encoding mRNA into zebrafish embryos, screening of injected embryos for induced mutations in the soma, and recovery of germline mutations.

Animal models, including the zebrafish, without a reliable embryonic stem cell system are not easily amenable to targeted mutagenesis for studying gene function. Three recent publications have shown that zinc finger nucleases (ZFNs) have circumvented this shortcoming in zebrafish. Similar to restriction enzymes, ZFNs can introduce site-specific double-strand breaks (DSBs); moreover, they can be designed to recognize virtually any target sequence. Because the preferred DSB repair pathway in zebrafish embryos, non-homologous end joining, is error-prone, ZFNs can be used to create mutations in a gene of interest. Here we review the protocols for a yeast-based assay to detect effective ZFNs. Additionally, we detail the procedures for synthesis and injection of ZFN-encoding mRNA into zebrafish embryos, screening of injected embryos for induced mutations in the soma, and recovery of germline mutations.

While the experimental tools developed for zebrafish have continued to advance the organism as a laboratory model, techniques for reverse genetics remain somewhat limited in scope. Zinc finger nucleases (ZFNs), chimeric fusions between DNA-binding zinc finger proteins and the non-specific cleavage domain of the FokI endonuclease, hold great promise for targeted mutagenesis in zebrafish, as demonstrated by two recent publications (Doyon et al., 2008, Nat Biotechnol. 26, 702-708; Meng et al., 2008, Nat Biotechnol. 26, 695-701). Because ZFNs can be designed to recognize a unique sequence in the genome, they can specifically bind and cleave a target locus, creating a double-strand break (DSB) that is repaired by one of two major DNA repair pathways. Repair by one of these pathways, non-homologous end joining, is often mutagenic, allowing one to screen for induced mutations in the target locus. By injecting into zebrafish embryos RNA encoding ZFNs that target three different loci, two groups have shown that ZFNs work efficiently to induce somatic and germline mutations (reviewed in (3)). We review here protocols for injection of ZFN-encoding mRNA into zebrafish embryos, screening of injected fish for induced mutations, and subsequent recovery of the induced mutations.

While the experimental tools developed for zebrafish have continued to advance the organism as a laboratory model, techniques for reverse genetics remain somewhat limited in scope. Zinc finger nucleases (ZFNs), chimeric fusions between DNA-binding zinc finger proteins and the non-specific cleavage domain of the FokI endonuclease, hold great promise for targeted mutagenesis in zebrafish, as demonstrated by two recent publications (Doyon et al., 2008, Nat Biotechnol. 26, 702-708; Meng et al., 2008, Nat Biotechnol. 26, 695-701). Because ZFNs can be designed to recognize a unique sequence in the genome, they can specifically bind and cleave a target locus, creating a double-strand break (DSB) that is repaired by one of two major DNA repair pathways. Repair by one of these pathways, non-homologous end joining, is often mutagenic, allowing one to screen for induced mutations in the target locus. By injecting into zebrafish embryos RNA encoding ZFNs that target three different loci, two groups have shown that ZFNs work efficiently to induce somatic and germline mutations (reviewed in (3)). We review here protocols for injection of ZFN-encoding mRNA into zebrafish embryos, screening of injected fish for induced mutations, and subsequent recovery of the induced mutations.