Next Article in Journal
Management of Dyslipidemia in Type 2 Diabetes: Recent Advances in Nonstatin Treatment
Next Article in Special Issue
Treatment of Major Depressive Disorder in Pediatric Populations
Previous Article in Journal
Viral Vectors in Gene Therapy
Previous Article in Special Issue
Revisiting CD28 Superagonist TGN1412 as Potential Therapeutic for Pediatric B Cell Leukemia: A Review
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Diseases
Volume 6
Issue 2
10.3390/diseases6020043
diseases-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Zebrafish Models of Rare Hereditary Pediatric Diseases

by
Máté Varga
1,2,*,
Dorottya Ralbovszki
1,
Eszter Balogh
2,3,
Renáta Hamar
1,
Magdolna Keszthelyi
2,3 and
Kálmán Tory
2,3,*
1
Department of Genetics, ELTE Eötvös Loránd University, 1117 Budapest, Hungary
2
MTA-SE Lendület Nephrogenetic Laboratory, 1083 Budapest, Hungary
3
Ist Department of Pediatrics, Semmelweis University, 1083 Budapest, Hungary
*
Authors to whom correspondence should be addressed.
Diseases 2018, 6(2), 43; https://doi.org/10.3390/diseases6020043
Submission received: 27 April 2018 / Revised: 17 May 2018 / Accepted: 19 May 2018 / Published: 22 May 2018
(This article belongs to the Special Issue Pediatric Diseases)
Browse Figure
Versions Notes

Abstract

:
Recent advances in sequencing technologies have made it significantly easier to find the genetic roots of rare hereditary pediatric diseases. These novel methods are not panaceas, however, and they often give ambiguous results, highlighting multiple possible causative mutations in affected patients. Furthermore, even when the mapping results are unambiguous, the affected gene might be of unknown function. In these cases, understanding how a particular genotype can result in a phenotype also needs carefully designed experimental work. Model organism genetics can offer a straightforward experimental setup for hypothesis testing. Containing orthologs for over 80% of the genes involved in human diseases, zebrafish (Danio rerio) has emerged as one of the top disease models over the past decade. A plethora of genetic tools makes it easy to create mutations in almost any gene of the zebrafish genome and these mutant strains can be used in high-throughput preclinical screens for active molecules. As this small vertebrate species offers several other advantages as well, its popularity in biomedical research is bound to increase, with “aquarium to bedside” drug development pipelines taking a more prevalent role in the near future.

1. Introduction

Rare diseases, namely conditions with incidence rates lower than 1:2000 affect an estimated 350 million people worldwide. More than 7000 such diseases have already been described, and 80% of these are thought to have genetic origins [1,2,3,4]. Approximately one out of 15 infants born worldwide will be affected by a rare hereditary disease during their lifetime [5]. 50–75% of these diseases affect children, and one third of children born with such a condition die before their fifth birthday [1].
The advent of novel methodologies (e.g., next-generation sequencing (NGS)) has made efforts to identify the genetic causes of rare diseases easier, faster and cheaper, yet an accurate molecular diagnosis is still far from trivial with our current knowledge [4]. Disease mapping with current technologies will often yield multiple hits. Many of the flagged alleles are rare variants with unknown effects of genes with known function, or deleterious-looking variants of unknown genes. Deciding which one of these hits is the causative mutation behind the observed phenotype can be a formidable challenge, but often these hard questions can be successfully tackled with the help of model organism genetics [6].
Over the past four decades zebrafish has become one of the most in-demand genetic organisms [7,8,9,10]. Researchers have realized early on that this small freshwater fish species bears several characteristics of an ideal vertebrate genetic model organism (it is cheap to maintain, has a small size, is transparent in the embryonic stage, has an external fertilization and a relatively short generation time). But it was the advent of an easy-to-use and ever expanding genetic toolkit that made the zebrafish hugely popular.
The first successful large-scale forward genetic screens [11,12] resulted in a treasure trove of important mutants and demonstrated that this approach can be applied to find mutations with biomedical relevance [13]. Publication of the first detailed genetic maps [14,15,16,17] and sequencing the full diploid zebrafish genome [18] has made the previously challenging and tedious positional mapping of the mutations much more straightforward [19]. Recent systematic efforts, such as the Zebrafish Mutation Project (ZMP) coordinated by the Sanger Institute (UK), aim to mutate every gene in the zebrafish genome (up to date 37,624 alleles of 14,934 genes have been created) [20] and advances in NGS technology offer a far more rapid and straightforward solution for the mapping of novel mutations [21,22].
While zebrafish has been used primarily in developmental studies, over the past two decades it has also become one of the most relevant model organisms used in human pathogenetic studies [5,6,23,24,25].
As a vertebrate organism, zebrafish shares many anatomical features with humans. Furthermore, a high level of genetic conservation can be observed between the two species. Sequencing of the zebrafish genome revealed that 71% of all human proteins and 82% of disease causing ones have a zebrafish ortholog [5,18]. Compared with the genes included in the recently published PedAM database of pediatric disease annotation [26] we found that ~75% (13,217/17,727) of PedAM genes have a clear zebrafish ortholog (Figure 1).
All these advantages, supplemented with an advanced genetic toolkit (see below) make zebrafish uniquely suited for studying human diseases, and for the screening of potential drugs [5,6]. Accordingly, the use of zebrafish features prominently in several large international collaborations (e.g., Undiagnosed Diseases Network (UDN) and Rare Diseases Models and Mechanisms (RDMM)) that aim to study potential disease causing genes with the help of model organisms [6].

2. The Zebrafish Genetic Toolkit

Forward genetic approaches, which are used for the identification of mutated genes underpinning specific phenotypes of interest are complemented by reverse genetic approaches, of which antisense morpholino oligonucleotides, morpholinos (MOs) have been the most popular [27]. While the expansion of the zebrafish genetic toolbox has increased the model’s appeal, it is important to keep in mind the limits of the model and some experimental approaches.
For example, when designing experiments with zebrafish orthologs of particular human disease genes it is worth remembering that due to a whole genome duplication in the Teleost lineage, some human genes have two zebrafish paralogs ([18]). Often, but not always, these paralogs show signs of subfunctionalization ([28,29,30]). Therefore, while for some disease models the knock-down of both paralogs will be necessary, in other cases knocking down a single paralog could give a phenotype that is equivalent to the one observed in human patients.

2.1. Transient Genetic Approaches

Synthetic MO oligos are very stable and can be easily injected into embryos at 1–2 cell stage, where they interfere with gene expression. MOs can bind and mask the translational start site of mRNAs, or can interfere with splicing, in effect creating loss-of-function phenotypes. This straightforward and simple approach became extremely popular among researchers looking for quick assays to test candidate genes from NGS/Genome Wide Association Studies (GWAS), and in numerous studies MO-based experiments and the resulting morphant phenotypes provided the necessary proof to validate the identification of disease genes (Table 1). They can be also used as genetic proof by phenocopy when mapping mutants from forward genetic screens.
Although MO technology was enthusiastically adopted by the zebrafish field and morphant phenotypes were often used in human genetic studies to provide independent proof for the involvement of particular genes in the observed pathologies, the approach has important limitations. For example, MO injections (just like mRNA injections) will have transient effects (see later). But just as important is the fact that MOs can elicit strong, specific p53-dependent effects [31] and recent analysis has also shown that the activation of an innate immune response and off-target miss-splicing are common side effects of MO usage [32]. Furthermore, some early studies of genome-edited lines have raised serious questions about the veracity of many results that were based on MO-effects only ([33]). All these findings resulted in a reconsideration of the use of MOs in the zebrafish field and paved the way to stringent new guidelines [34,35].
It would be easy to conclude that a morphant phenotype should be considered specific only if it is able to phenocopy a mutation. However, recent research suggests that the unaltered phenotype in many zebrafish mutants could be the result of either genomic compensation triggered by non-sense mediated decay [36,37] or altered mRNA processing [38,39]. These compensatory effects are not apparent in transcriptional knock-downs, such as MOs and CRISPR-interference (CRISPRi). Overall, the current consensus in the field is to consider MO results specific not only when there is a mutant allele with an identical phenotype, but also if the injection of the MO into the mutant background has no visible phenotypic effects, even though there are differences between the phenotypes of the morphants and mutants of a particular gene.
If a bona fide mutant for the gene of interest is not available, it is of utmost importance to use proper controls when working with MOs. These include the use of multiple MOs, their careful titration and the demonstration that the gene of interest is successfully targeted (either by Western blot if antibodies are available, or at least by RT-PCR to monitor altered splicing in the case of a splice blocking MO).
Similarly to MOs, in vitro synthesized mRNAs can be introduced easily into early stage embryos. These methodologically easy and quick gain-of-function experiments have been widely used to decipher the role of genes during early development. As mRNA injection can be used to express dominant-negative or constitutively active constructs, too, in combination with MOs, it has been successfully applied for epistasis analysis experiments [40]. (Co)injection of mRNAs has been also widely used as genetic proof to validate the specificity of morphant and mutant phenotypes.

2.2. Stable Genetic Approaches

Only with the application of TALEN-based [114,115,116] and, more recently, CRISPR/Cas9-based genome editing technologies in zebrafish [117,118,119,120,121,122] has the use of MOs seen a decline. These new methodological approaches have already revolutionized zebrafish genetics [123] and provided independent means to test the veracity of the morphant phenotypes (see above). While most of the novel genome edited lines are loss-of-function alleles that arise due to the indel mutations resulting from erroneous non-homologous end joining (NHEJ) DNA repair mechanisms, efforts have been made to create precise knock-in alleles exploiting the alternative, homologous recombination (HR) repair pathway [124,125,126]. While the excitement caused by these early results seemed justified, later results suggested that the knock-in efficiency is highly locus- (and template-) dependent.
Of the existing programmable nuclease techniques TALENs, albeit slower and more expensive to assembly, are usually considered superior, due to their higher specificity. The off-target effects of CRISPR can be, however, considerably reduced with the right choice of sgRNAs and with the use of rationally engineered Cas-variants [127,128].
As the problems with MOs became apparent, many people opted to complement or supplement MO studies with the description of “crispant” phenotypes (see Table 1). In crispants CRISPR/Cas9 technology was used to introduce mutation(s) with gene-specific sgRNA. In case of embryonic- or larval-lethal mutations, this approach could provide a quick and cost-effective way to test the function of the genes of interest. Due to the very nature of this method, however, most embryos will be highly mosaic for the mutations they carry, and only careful analysis can reveal if they indeed have biallelic mutations in most of their cells. Therefore, we should tread carefully and only accept crispant phenotypes as specific if constitutive mutants show the same phenotype. (Ideally, one should aim to conduct studies in F2 or F3 generations, where the possible confounding effects of off-target mutations can be minimized). It will be also important to compile databases of proven and effective sgRNA target sequences with low off-target effects, so that targeting of particular genes with CRISPR-based methods can become more standardized [129].
The advantages of bona fide mutants over morphants and crispants are numerous, however, as mentioned above, the phenomenon of genetic compensation can hinder the characterization of mutant phenotypes [36,37,38,39].
The transparency of zebrafish embryos and larvae has been long considered one of the most advantageous attributes of the model. Organs, tissues or specific cells can be labeled with fluorescent dyes and markers and followed in vivo under a microscope. Transgenic lines have been instrumental in characterizing the effects of specific mutations (e.g., [44,52,58,130]), highlighting the power of this approach. The modular, easy-to-use “Tol2-kit”, based on the Gateway technology has made the creation of transgenic lines a mundane task [131]. Efficient transgenesis techniques have been also used for enhancer-trap and gene-trap screens [132,133], and a wide array of tissue-specific Gal4 and CreERT2 lines have been established, paving the way for intricate genetic manipulations [134,135,136].
Finally, the combination of transgenesis and genome editing techniques enabled researchers to create the conditional knock-out methodology that previously eluded the zebrafish field [137,138].

3. Modeling Disease with Homologs and Phenologs

In the past few decades zebrafish has emerged as a powerful model of congenital disorders (Table 1). This development is partly due to the advantages of the model (embryonic development is fast and external, therefore, the emergence of particular impairments can be followed effectively in real time and phenotypes can be identified early), but also to the limitation of the tools used. For example, although MOs can bring almost complete knock-down, their effect is temporary, and after 3–5 days it diminishes sharply [139]. mRNAs are equally unstable (or even more so), thus their effect is limited to the first 2–3 days of development. Importantly, unlike many disease alleles in humans, the majority of zebrafish alleles for the respective genes isolated in previous screens or created recently with novel editing methods are embryonic-lethal null-alleles.
Despite these limitations MO-based knockdowns (lately backed up by crispant phenotypes, resulting from the injection of CRISPR/Cas9 RNPs into embryos) have been very successfully used in identifying driver genes for particular diseases. In a recent study of DiGeorge syndrome fish models have been essential to demonstrate that haplo-insufficiency of CRKL is the main cause of the kidney pathologies observed in patients with this syndrome [44].
Due to the high levels of genetic and anatomical conservation between the two species, zebrafish models often display highly similar phenotypes to the human condition. For example, models of coloboma, generalized arterial calcification of infancy (GACI), X-linked adrenoleukodystrophy (ALD), Duchenne’s muscular dystrophy or Dravet syndrome all display features that are highly similar to the characteristics of the human pathologies (see Table 1 for references).
In certain cases prior in-depth knowledge about zebrafish development helps to create highly informative disease models through orthologous phenotypes, or phenologs [140]. For example, zebrafish models have been instrumental in deciphering the role of several genes in ciliopathies, such as Bardet-Biedl Syndrome (BBS) or Joubert syndrome (Table 1). The popularity of zebrafish in ciliopathy research can be at least partly explained by the fact that dysfunction of the cilia results in easily recognizable developmental phenotypes, including curved body axis, hydrocephalus and laterality defects [141].
Another excellent example for the use of phenologs in modeling pediatric disorders is fibrodysplasia ossificans progressiva (FOP). In-depth knowledge about the molecular mechanism of early dorso-ventral (DV) patterning in zebrafish development, including the phenotype of ventralized embryos, has been helpful both in the identification of the causative mutations of FOP [63,64] and that of putative drugs [142].
Constitutively active mutations, such as the ones observed in ACVR1 in patients with FOP, can be modeled using mRNA injections and transgenic approaches. This approach can substitute or complement transient expression studies when necessary [65]. Overexpression experiments can be also informative in modeling microduplications or trisomies [70,90].
Finally, although MOs are usually injected in significant excess to obtain functional knock-downs, they can be also titrated to suboptimal concentrations to mimic the additive effects of hypomorphic mutations. A nice example for this approach is provided by the modeling of the Charcot-Marie-Tooth syndrome, where the “mutational burden” hypothesis of neuropathy genes was tested [53].

4. Drug Discovery Using Zebrafish

Its small size, allowing for semi-high-throughput screening, has made zebrafish a prominent model in drug screens over the past decade. In addition, due to the aforementioned high level of genetic conservation between zebrafish and humans, several drugs have similar targets (and thus similar effects) in both species. It is, therefore, no wonder that over the past decade zebrafish has emerged as the model organism of choice for high-throughput screening of chemical libraries for potential drugs [5] and several compounds picked up in these screens have made their ways into clinical trials [143].
Several models of pediatric disorders have been used in such screens, and these experiments confirm that both homologous and orthologous phenotypes can be successfully used in drug discovery/testing experiments (Table 2). For example, a recent model of childhood-onset parkinsonism-dystonia, characterized by mutations in a Mn-transporter, was successfully used to show that the symptoms of the disease can be ameliorated using Na2CaEDTA as a chelator–and this treatment also alleviates the patients’ symptoms [54].
Identification of the causative FOP mutations in the ACVR1 gene and the validation of the orthologous ventralized phenotypes in zebrafish led to the later discovery of dorsomorphin and its derivatives [142]. These molecules with dorsalizing effects are currently being tested in clinical trials for FOP treatment. An even more impressive recent “aquarium to bedside” story involves a zebrafish model of Dravet syndrome: a high-throughput drug screen identified clemizole and lorcaserine as potential drugs with anti-serotonin effects. These drugs have been approved by the FDA earlier as an antihistamine and a weight-loss aid, respectively. It was, therefore, possible to register them as potential treatment without having to repeat the expensive, time-consuming clinical trials that enabled them to be approved. When applied directly to patients with Dravet syndrome, these repurposed drugs outperformed conventional anticonvulsants [144].
While zebrafish studies will not always substitute pre-clinical tests in mammalian models, they can save time and money by pre-filtering the compounds that enter the more advanced phases of drug development ([5,145]).

5. Outlook

Overall, despite the aforementioned limitations that can be overcome with proper controls or novel technologies, zebrafish models of rare pediatric diseases (and diseases in general) are set to probably become even more important assets of preclinical research and drug discovery in the coming years. We can almost certainly expect a proliferation of the repurposing studies of FDA-approved drugs, as zebrafish is the ideal model to conduct such studies. The increasing relevance of fish models will be also apparent in the study of childhood leukemias and other forms of cancer (for comprehensive reviews on this subject see [148,149,150]) and zebrafish “avatars” for the development of personalized chemotherapies could also become prominent in the near future ([151,152,153]).
With the proliferation of base-editor tools that are often based on synthetic versions of Cas-nucleases with altered PAM recognition sites, genome editing has entered a new phase, often referred as “CRISPR 2.0” ([154,155,156,157]). We can routinely engineer A to G and C to T transitions with high precision in the genome, and as zebrafish has been at the forefront of the CRISPR-revolution, it is almost certain that the coming years will see a proliferation in the use of these base editors. This technological breakthrough will help us create exact or almost exact mimics of hypomorphic human disease alleles (instead of nulls), making the new disease model strains even more relevant in examining particular aspects of human pathologies. We can also expect the proliferation of “humanized” zebrafish lines as well, where zebrafish carrying mutations in particular genes are supplemented with a transgenic cassette expressing the human ortholog of the gene ([158]). Zebrafish models created with precision base-editing methods could also help understanding how rare variants of Mendelian genes contribute significantly to complex disease phenotypes, as suggested by recent research [159].
Finally—and somewhat counterintuitively—even the fact that zebrafish mutants often lack an overt phenotype could be exploited to better understand human diseases [39]. Recent studies suggest that in certain unaffected individuals who are homozygotes or compound heterozygotes for null alleles, the effect of these loss-of-function alleles can be negligible [160]. The study of mutant zebrafish strains that are phenotypically normal could reveal how their robustness is achieved by translational plasticity [161], providing important insights into the context dependency of genetic risk factors.

Author Contributions

All authors contributed to the drafting of the paper and approved of the final manuscript.

Funding

This study was supported by grants MTA-SE Lendület Research Grant (LP2015-11/2015) of the Hungarian Academy of Sciences to K.T. and NRDI-FK124230 financed by the Hungarian National Research, Development and Innovation Office to M.V., M.V. is supported by the ÚNKP-17-4 New National Excellence Program of the Ministry of Human Capacities.

Acknowledgments

The authors would like to thank Gaia Gestri, Julianna Víg and one anonymous reviewer for useful comments on the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Rode, J. Rare Diseases: Understanding this Public Health Priority; EURORDIS: Paris, France, 2005. [Google Scholar]
  2. Amberger, J.S.; Bocchini, C.A.; Schiettecatte, F.; Scott, A.F.; Hamosh, A. OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders. Nucleic Acids Res. 2015, 43, D789–D798. [Google Scholar] [CrossRef] [PubMed]
  3. Rath, A.; Olry, A.; Dhombres, F.; Brandt, M.M.; Urbero, B.; Ayme, S. Representation of rare diseases in health information systems: The Orphanet approach to serve a wide range of end users. Hum. Mutat. 2012, 33, 803–808. [Google Scholar] [CrossRef] [PubMed]
  4. Wright, C.F.; FitzPatrick, D.R.; Firth, H.V. Paediatric genomics: Diagnosing rare disease in children. Nat. Rev. Genet. 2018, 10, e0123081. [Google Scholar]
  5. Strynatka, K.A.; Gurrola-Gal, M.C.; Berman, J.N.; McMaster, C.R. How Surrogate and Chemical Genetics in Model Organisms Can Suggest Therapies for Human Genetic Diseases. Genetics 2018, 208, 833–851. [Google Scholar] [CrossRef] [PubMed]
  6. Wangler, M.F.; Yamamoto, S.; Chao, H.-T.; Posey, J.E.; Westerfield, M.; Postlethwait, J.H.; Members of the Undiagnosed Diseases Network (UDN); Hieter, P.; Boycott, K.M.; Campeau, P.M.; et al. Model Organisms Facilitate Rare Disease Diagnosis and Therapeutic Research. Genetics 2017, 207, 9–27. [Google Scholar] [CrossRef] [PubMed]
  7. Kinth, P.; Mahesh, G.; Panwar, Y. Mapping of zebrafish research: A global outlook. Zebrafish 2013, 10, 510–517. [Google Scholar] [CrossRef] [PubMed]
  8. Grunwald, D.J.; Eisen, J.S. Headwaters of the zebrafish—Emergence of a new model vertebrate. Nat. Rev. Genet. 2002, 3, 717–724. [Google Scholar] [CrossRef] [PubMed]
  9. Varga, M. The Doctor of Delayed Publications: The Remarkable Life of George Streisinger (1927–1984). Zebrafish 2018. [Google Scholar] [CrossRef] [PubMed]
  10. Lieschke, G.J.; Currie, P.D. Animal models of human disease: Zebrafish swim into view. Nat. Rev. Genet. 2007, 8, 353–367. [Google Scholar] [CrossRef] [PubMed]
  11. Driever, W.; Solnica-Krezel, L.; Schier, A.F.; Neuhauss, S.C.; Malicki, J.; Stemple, D.L.; Stainier, D.Y.; Zwartkruis, F.; Abdelilah, S.; Rangini, Z.; et al. A genetic screen for mutations affecting embryogenesis in zebrafish. Development 1996, 123, 37–46. [Google Scholar] [PubMed]
  12. Haffter, P.; Granato, M.; Brand, M.; Mullins, M.C. The identification of genes with unique and essential functions in the development of the zebrafish, Danio rerio. Development 1996, 123, 1–36. [Google Scholar] [PubMed]
  13. Patton, E.E.; Zon, L.I. The art and design of genetic screens: Zebrafish. Nat. Rev. Genet. 2001, 2, 956–966. [Google Scholar] [CrossRef] [PubMed]
  14. Postlethwait, J.H.; Yan, Y.-L.; Gates, M.A.; Horne, S.; Amores, A.; Brownlie, A.; Donovan, A.; Egan, E.S.; Force, A.; Gong, Z.; et al. Vertebrate genome evolution and the zebrafish gene map. Nat. Genet. 1998, 18, 345–349. [Google Scholar] [CrossRef] [PubMed]
  15. Knapik, E.W.; Goodman, A.; Ekker, M.; Chevrette, M.; Delgado, J.; Neuhauss, S.; Shimoda, N.; Driever, W.; Fishman, M.C.; Jacob, H.J. A microsatellite genetic linkage map for zebrafish (Danio rerio). Nat. Genet. 1998, 18, 338–343. [Google Scholar] [CrossRef] [PubMed]
  16. Gates, M.A.; Kim, L.; Egan, E.S.; Cardozo, T.; Sirotkin, H.I.; Dougan, S.T.; Lashkari, D.; Abagyan, R.; Schier, A.F.; Talbot, W.S. A genetic linkage map for zebrafish: Comparative analysis and localization of genes and expressed sequences. Genome Res. 1999, 9, 334–347. [Google Scholar] [PubMed]
  17. Shimoda, N.; Knapik, E.W.; Ziniti, J.; Sim, C.; Yamada, E.; Kaplan, S.; Jackson, D.; de Sauvage, F.; Jacob, H.; Fishman, M.C. Zebrafish genetic map with 2000 microsatellite markers. Genomics 1999, 58, 219–232. [Google Scholar] [CrossRef] [PubMed]
  18. Howe, K.; Clark, M.D.; Torroja, C.F.; Torrance, J.; Berthelot, C.; Muffato, M.; Collins, J.E.; Humphray, S.; McLaren, K.; Matthews, L.; et al. The zebrafish reference genome sequence and its relationship to the human genome. Nature 2013, 496, 498–503. [Google Scholar] [CrossRef] [PubMed]
  19. Talbot, W.S.; Schier, A.F. Chapter 15 Positional Cloning of Mutated Zebrafish Genes. In The Zebrafish: Genetics and Genomics; Methods in Cell Biology; Elsevier: New York, NY, USA, 1998; Volume 60, pp. 259–286. [Google Scholar]
  20. Kettleborough, R.N.W.; Busch-Nentwich, E.M.; Harvey, S.A.; Dooley, C.M.; de Bruijn, E.; van Eeden, F.; Sealy, I.; White, R.J.; Herd, C.; Nijman, I.J.; et al. A systematic genome-wide analysis of zebrafish protein-coding gene function. Nature 2013, 496, 494–497. [Google Scholar] [CrossRef] [PubMed]
  21. Minevich, G.; Park, D.S.; Blankenberg, D.; Poole, R.J.; Hobert, O. CloudMap: A cloud-based pipeline for analysis of mutant genome sequences. Genetics 2012, 192, 1249–1269. [Google Scholar] [CrossRef] [PubMed]
  22. Schneeberger, K. Using next-generation sequencing to isolate mutant genes from forward genetic screens. Nat. Rev. Genet. 2014, 15, 662–676. [Google Scholar] [CrossRef] [PubMed]
  23. Ablain, J.; Zon, L.I. Of fish and men: Using zebrafish to fight human diseases. Trends Cell Biol. 2013, 23, 584–586. [Google Scholar] [CrossRef] [PubMed]
  24. Phillips, J.B.; Westerfield, M. Zebrafish models in translational research: Tipping the scales toward advancements in human health. Dis. Models Mech. 2014, 7, 739–743. [Google Scholar] [CrossRef] [PubMed]
  25. Baxendale, S.; van Eeden, F.; Wilkinson, R. The Power of Zebrafish in Personalised Medicine. Adv. Exp. Med. Biol. 2017, 1007, 179–197. [Google Scholar] [PubMed]
  26. Jia, J.; An, Z.; Ming, Y.; Guo, Y.; Li, W.; Li, X.; Liang, Y.; Guo, D.; Tai, J.; Chen, G.; et al. PedAM: A database for Pediatric Disease Annotation and Medicine. Nucleic Acids Res. 2018, 46, D977–D983. [Google Scholar] [CrossRef] [PubMed]
  27. Nasevicius, A.; Ekker, S.C. Effective targeted gene “knockdown” in zebrafish. Nat. Genet. 2000, 26, 216–220. [Google Scholar] [CrossRef] [PubMed]
  28. Kleinjan, D.A.; Bancewicz, R.M.; Gautier, P.; Dahm, R.; Schonthaler, H.B.; Damante, G.; Seawright, A.; Hever, A.M.; Yeyati, P.L.; van Heyningen, V.; et al. Subfunctionalization of duplicated zebrafish pax6 genes by cis-regulatory divergence. PLoS Genet. 2008, 4, e29. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  29. Force, A.; Lynch, M.; Pickett, F.B.; Amores, A.; Yan, Y.L.; Postlethwait, J. Preservation of duplicate genes by complementary, degenerative mutations. Genetics 1999, 151, 1531–1545. [Google Scholar] [PubMed]
  30. Lambert, M.J.; Cochran, W.O.; Wilde, B.M.; Olsen, K.G.; Cooper, C.D. Evidence for widespread subfunctionalization of splice forms in vertebrate genomes. Genome Res. 2015, 25, 624–632. [Google Scholar] [CrossRef] [PubMed]
  31. Robu, M.E.; Larson, J.D.; Nasevicius, A.; Beiraghi, S.; Brenner, C.; Farber, S.A.; Ekker, S.C. p53 activation by knockdown technologies. PLoS Genet. 2007, 3, e78. [Google Scholar] [CrossRef] [PubMed]
  32. Gentsch, G.E.; Spruce, T.; Monteiro, R.S.; Owens, N.D.L.; Martin, S.R.; Smith, J.C. Innate Immune Response and Off-Target Mis-splicing Are Common Morpholino-Induced Side Effects in Xenopus. Dev. Cell 2018, 44, 597–610. [Google Scholar] [CrossRef] [PubMed]
  33. Kok, F.O.; Shin, M.; Ni, C.-W.; Gupta, A.; Grosse, A.S.; van Impel, A.; Kirchmaier, B.C.; Peterson-Maduro, J.; Kourkoulis, G.; Male, I.; et al. Reverse genetic screening reveals poor correlation between morpholino-induced and mutant phenotypes in zebrafish. Dev. Cell 2015, 32, 97–108. [Google Scholar] [CrossRef] [PubMed]
  34. Schulte-Merker, S.; Stainier, D.Y.R. Out with the old, in with the new: Reassessing morpholino knockdowns in light of genome editing technology. Development 2014, 141, 3103–3104. [Google Scholar] [CrossRef] [PubMed]
  35. Stainier, D.Y.R.; Raz, E.; Lawson, N.D.; Ekker, S.C.; Burdine, R.D.; Eisen, J.S.; Ingham, P.W.; Schulte-Merker, S.; Yelon, D.; Weinstein, B.M.; et al. Guidelines for morpholino use in zebrafish. PLoS Genet. 2017, 13, e1007000. [Google Scholar] [CrossRef] [PubMed]
  36. Rossi, A.; Kontarakis, Z.; Gerri, C.; Nolte, H.; Hölper, S.; Krüger, M.; Stainier, D.Y.R. Genetic compensation induced by deleterious mutations but not gene knockdowns. Nature 2015, 524, 230–233. [Google Scholar] [CrossRef] [PubMed]
  37. El-Brolosy, M.A.; Stainier, D.Y.R. Genetic compensation: A phenomenon in search of mechanisms. PLoS Genet. 2017, 13, e1006780. [Google Scholar] [CrossRef] [PubMed]
  38. Anderson, J.L.; Mulligan, T.S.; Shen, M.-C.; Wang, H.; Scahill, C.M.; Tan, F.J.; Du, S.J.; Busch-Nentwich, E.M.; Farber, S.A. mRNA processing in mutant zebrafish lines generated by chemical and CRISPR-mediated mutagenesis produces unexpected transcripts that escape nonsense-mediated decay. PLoS Genet. 2017, 13, e1007105. [Google Scholar] [CrossRef] [PubMed]
  39. Balciunas, D. Fish mutant, where is thy phenotype? PLoS Genet. 2018, 14, e1007197. [Google Scholar] [CrossRef] [PubMed]
  40. Maegawa, S.; Varga, M.; Weinberg, E.S. FGF signaling is required for {beta}-catenin-mediated induction of the zebrafish organizer. Development 2006, 133, 3265–3276. [Google Scholar] [CrossRef] [PubMed]
  41. Danilova, N.; Wilkes, M.; Bibikova, E.; Youn, M.-Y.; Sakamoto, K.M.; Lin, S. Innate immune system activation in zebrafish and cellular models of Diamond Blackfan Anemia. Sci. Rep. 2018, 8, 5165. [Google Scholar] [CrossRef] [PubMed]
  42. Danilova, N.; Sakamoto, K.M.; Lin, S. Ribosomal protein L11 mutation in zebrafish leads to haematopoietic and metabolic defects. Br. J. Haematol. 2011, 152, 217–228. [Google Scholar] [CrossRef] [PubMed]
  43. Heijnen, H.F.; van Wijk, R.; Pereboom, T.C.; Goos, Y.J.; Seinen, C.W.; van Oirschot, B.A.; van Dooren, R.; Gastou, M.; Giles, R.H.; van Solinge, W.; et al. Ribosomal Protein Mutations Induce Autophagy through S6 Kinase Inhibition of the Insulin Pathway. PLoS Genet. 2014, 10, e1004371. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Lopez-Rivera, E.; Liu, Y.P.; Verbitsky, M.; Anderson, B.R.; Capone, V.P.; Otto, E.A.; Yan, Z.; Mitrotti, A.; Martino, J.; Steers, N.J.; et al. Genetic Drivers of Kidney Defects in the DiGeorge Syndrome. N. Engl. J. Med. 2017, 376, 742–754. [Google Scholar] [CrossRef] [PubMed]
  45. Pannicke, U.; Hönig, M.; Hess, I.; Friesen, C.; Holzmann, K.; Rump, E.-M.; Barth, T.F.; Rojewski, M.T.; Schulz, A.; Boehm, T.; et al. Reticular dysgenesis (aleukocytosis) is caused by mutations in the gene encoding mitochondrial adenylate kinase 2. Nat. Genet. 2009, 41, 101–105. [Google Scholar] [CrossRef] [PubMed]
  46. Fernández-Murray, J.P.; Prykhozhij, S.V.; Dufay, J.N.; Steele, S.L.; Gaston, D.; Nasrallah, G.K.; Coombs, A.J.; Liwski, R.S.; Fernandez, C.V.; Berman, J.N.; et al. Glycine and Folate Ameliorate Models of Congenital Sideroblastic Anemia. PLoS Genet. 2016, 12, e1005783. [Google Scholar] [CrossRef] [PubMed]
  47. Brownlie, A.; Donovan, A.; Pratt, S.J.; Paw, B.H.; Oates, A.C.; Brugnara, C.; Witkowska, H.E.; Sassa, S.; Zon, L.I. Positional cloning of the zebrafish sauternes gene: A model for congenital sideroblastic anaemia. Nat. Genet. 1998, 20, 244–250. [Google Scholar] [CrossRef] [PubMed]
  48. Mahmood, F.; Fu, S.; Cooke, J.; Wilson, S.W.; Cooper, J.D.; Russell, C. A zebrafish model of CLN2 disease is deficient in tripeptidyl peptidase 1 and displays progressive neurodegeneration accompanied by a reduction in proliferation. Brain 2013, 136, 1488–1507. [Google Scholar] [CrossRef] [PubMed]
  49. Wager, K.; Zdebik, A.A.; Fu, S.; Cooper, J.D.; Harvey, R.J.; Russell, C. Neurodegeneration and Epilepsy in a Zebrafish Model of CLN3 Disease (Batten Disease). PLoS ONE 2016, 11, e0157365. [Google Scholar] [CrossRef] [PubMed]
  50. Madsen, E.C.; Morcos, P.A.; Mendelsohn, B.A.; Gitlin, J.D. In vivo correction of a Menkes disease model using antisense oligonucleotides. Proc. Natl. Acad. Sci. USA 2008, 105, 3909–3914. [Google Scholar] [CrossRef] [PubMed]
  51. Elmonem, M.A.; Khalil, R.; Khodaparast, L.; Khodaparast, L.; Arcolino, F.O.; Morgan, J.; Pastore, A.; Tylzanowski, P.; Ny, A.; Lowe, M.; et al. Cystinosis (ctns) zebrafish mutant shows pronephric glomerular and tubular dysfunction. Sci. Rep. 2017, 7, 42583. [Google Scholar] [CrossRef] [PubMed]
  52. Strachan, L.R.; Stevenson, T.J.; Freshner, B.; Keefe, M.D.; Miranda Bowles, D.; Bonkowsky, J.L. A zebrafish model of X-linked adrenoleukodystrophy recapitulates key disease features and demonstrates a developmental requirement for abcd1 in oligodendrocyte patterning and myelination. Hum. Mol. Genet. 2017, 26, 3600–3614. [Google Scholar] [CrossRef] [PubMed]
  53. Gonzaga-Jauregui, C.; Harel, T.; Gambin, T.; Kousi, M.; Griffin, L.B.; Francescatto, L.; Ozes, B.; Karaca, E.; Jhangiani, S.N.; Bainbridge, M.N.; et al. Exome Sequence Analysis Suggests that Genetic Burden Contributes to Phenotypic Variability and Complex Neuropathy. Cell Rep. 2015, 12, 1169–1183. [Google Scholar] [CrossRef] [PubMed]
  54. Tuschl, K.; Meyer, E.; Valdivia, L.E.; Zhao, N.; Dadswell, C.; Abdul-Sada, A.; Hung, C.Y.; Simpson, M.A.; Chong, W.K.; Jacques, T.S.; et al. Mutations in SLC39A14 disrupt manganese homeostasis and cause childhood-onset parkinsonism-dystonia. Nat. Commun. 2016, 7, 11601. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Baraban, S.C.; Dinday, M.T.; Hortopan, G.A. Drug screening in Scn1a zebrafish mutant identifies clemizole as a potential Dravet syndrome treatment. Nat. Commun. 2013, 4, 2410. [Google Scholar] [CrossRef] [PubMed]
  56. Bassett, D.I.; Bryson-Richardson, R.J.; Daggett, D.F.; Gautier, P.; Keenan, D.G.; Currie, P.D. Dystrophin is required for the formation of stable muscle attachments in the zebrafish embryo. Development 2003, 130, 5851–5860. [Google Scholar] [CrossRef] [PubMed]
  57. Schubert, J.; Siekierska, A.; Langlois, M.; May, P.; Huneau, C.; Becker, F.; Muhle, H.; Suls, A.; Lemke, J.R.; de Kovel, C.G.F.; et al. Mutations in STX1B, encoding a presynaptic protein, cause fever-associated epilepsy syndromes. Nat. Genet. 2014, 46, 1327–1332. [Google Scholar] [CrossRef] [PubMed]
  58. See, K.; Yadav, P.; Giegerich, M.; Cheong, P.S.; Graf, M.; Vyas, H.; Lee, S.G.P.; Mathavan, S.; Fischer, U.; Sendtner, M.; et al. SMN deficiency alters Nrxn2 expression and splicing in zebrafish and mouse models of spinal muscular atrophy. Hum. Mol. Genet. 2014, 23, 1754–1770. [Google Scholar] [CrossRef] [PubMed]
  59. Boon, K.-L.; Xiao, S.; McWhorter, M.L.; Donn, T.; Wolf-Saxon, E.; Bohnsack, M.T.; Moens, C.B.; Beattie, C.E. Zebrafish survival motor neuron mutants exhibit presynaptic neuromuscular junction defects. Hum. Mol. Genet. 2009, 18, 3615–3625. [Google Scholar] [CrossRef] [PubMed]
  60. Norton, N.; Li, D.; Rieder, M.J.; Siegfried, J.D.; Rampersaud, E.; Züchner, S.; Mangos, S.; Gonzalez-Quintana, J.; Wang, L.; McGee, S.; et al. Genome-wide studies of copy number variation and exome sequencing identify rare variants in BAG3 as a cause of dilated cardiomyopathy. Am. J. Hum. Genet. 2011, 88, 273–282. [Google Scholar] [CrossRef] [PubMed]
  61. Ruparelia, A.A.; Oorschot, V.; Vaz, R.; Ramm, G.; Bryson-Richardson, R.J. Zebrafish models of BAG3 myofibrillar myopathy suggest a toxic gain of function leading to BAG3 insufficiency. Acta Neuropathol. 2014, 128, 821–833. [Google Scholar] [CrossRef] [PubMed]
  62. Ramachandran, K.V.; Hennessey, J.A.; Barnett, A.S.; Yin, X.; Stadt, H.A.; Foster, E.; Shah, R.A.; Yazawa, M.; Dolmetsch, R.E.; Kirby, M.L.; et al. Calcium influx through L-type CaV1.2 Ca2+ channels regulates mandibular development. J. Clin. Investig. 2013, 123, 1638–1646. [Google Scholar] [CrossRef] [PubMed]
  63. Shen, Q.; Little, S.C.; Xu, M.; Haupt, J.; Ast, C.; Katagiri, T.; Mundlos, S.; Seemann, P.; Kaplan, F.S.; Mullins, M.C.; et al. The fibrodysplasia ossificans progressiva R206H ACVR1 mutation activates BMP-independent chondrogenesis and zebrafish embryo ventralization. J. Clin. Investig. 2009, 119, 3462–3472. [Google Scholar] [CrossRef] [PubMed]
  64. Mucha, B.E.; Hashiguchi, M.; Zinski, J.; Shore, E.M.; Mullins, M.C. Variant BMP receptor mutations causing fibrodysplasia ossificans progressiva (FOP) in humans show BMP ligand-independent receptor activation in zebrafish. Bone 2018, 109, 225–231. [Google Scholar] [CrossRef] [PubMed]
  65. LaBonty, M.; Pray, N.; Yelick, P.C. A Zebrafish Model of Human Fibrodysplasia Ossificans Progressiva. Zebrafish 2017, 14, 293–304. [Google Scholar] [CrossRef] [PubMed]
  66. Zhou, Q.; Yang, D.; Ombrello, A.K.; Zavialov, A.V.; Toro, C.; Zavialov, A.V.; Stone, D.L.; Chae, J.J.; Rosenzweig, S.D.; Bishop, K.; et al. Early-onset stroke and vasculopathy associated with mutations in ADAN2. Engl. J. Med. 2014, 370, 911–920. [Google Scholar] [CrossRef] [PubMed]
  67. Mangos, S.; Lam, P.-Y.; Zhao, A.; Liu, Y.; Mudumana, S.; Vasilyev, A.; Liu, A.; Drummond, I.A. The ADPKD genes pkd1a/b and pkd2 regulate extracellular matrix formation. Dis. Model Mech. 2010, 3, 354–365. [Google Scholar] [CrossRef] [PubMed]
  68. Bisgrove, B.W.; Snarr, B.S.; Emrazian, A.; Yost, H.J. Polaris and Polycystin-2 in dorsal forerunner cells and Kupffer's vesicle are required for specification of the zebrafish left-right axis. Dev. Biol. 2005, 287, 274–288. [Google Scholar] [CrossRef] [PubMed]
  69. Schottenfeld, J.; Sullivan-Brown, J.; Burdine, R.D. Zebrafish curly up encodes a Pkd2 ortholog that restricts left-side-specific expression of southpaw. Development 2007, 134, 1605–1615. [Google Scholar] [CrossRef] [PubMed]
  70. Golzio, C.; Willer, J.; Talkowski, M.E.; Oh, E.C.; Taniguchi, Y.; Jacquemont, S.; Reymond, A.; Sun, M.; Sawa, A.; Gusella, J.F.; et al. KCTD13 is a major driver of mirrored neuroanatomical phenotypes of the 16p11.2 copy number variant. Nature 2012, 485, 363–367. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  71. Rooryck, C.; Diaz-Font, A.; Osborn, D.P.S.; Chabchoub, E.; Hernandez-Hernandez, V.; Shamseldin, H.; Kenny, J.; Waters, A.; Jenkins, D.; Kaissi, A.A.; et al. Mutations in lectin complement pathway genes COLEC11 and MASP1 cause 3MC syndrome. Nat. Genet. 2011, 43, 197–203. [Google Scholar] [CrossRef] [PubMed]
  72. Lu, H.; Galeano, M.C.R.; Ott, E.; Kaeslin, G.; Kausalya, P.J.; Kramer, C.; Ortiz-Brüchle, N.; Hilger, N.; Metzis, V.; Hiersche, M.; et al. Mutations in DZIP1L, which encodes a ciliary-transition-zone protein, cause autosomal recessive polycystic kidney disease. Nat. Genet. 2017, 49, 1025–1034. [Google Scholar] [CrossRef] [PubMed]
  73. Hendee, K.E.; Sorokina, E.A.; Muheisen, S.S.; Reis, L.M.; Tyler, R.C.; Markovic, V.; Cuturilo, G.; Link, B.A.; Semina, E.V. PITX2 deficiency and associated human disease: Insights from the zebrafish model. Hum. Mol. Genet. 2018, 27, 1675–1695. [Google Scholar] [CrossRef] [PubMed]
  74. Ross, A.J.; May-Simera, H.; Eichers, E.R.; Kai, M.; Hill, J.; Jagger, D.J.; Leitch, C.C.; Chapple, J.P.; Munro, P.M.; Fisher, S.; et al. Disruption of Bardet-Biedl syndrome ciliary proteins perturbs planar cell polarity in vertebrates. Nat. Genet. 2005, 37, 1135–1140. [Google Scholar] [CrossRef] [PubMed]
  75. Yen, H.-J.; Tayeh, M.K.; Mullins, R.F.; Stone, E.M.; Sheffield, V.C.; Slusarski, D.C. Bardet-Biedl syndrome genes are important in retrograde intracellular trafficking and Kupffer’s vesicle cilia function. Hum. Mol. Genet. 2006, 15, 667–677. [Google Scholar] [CrossRef] [PubMed]
  76. Badano, J.L.; Leitch, C.C.; Ansley, S.J.; May-Simera, H.; Lawson, S.; Lewis, R.A.; Beales, P.L.; Dietz, H.C.; Fisher, S.; Katsanis, N. Dissection of epistasis in oligogenic Bardet-Biedl syndrome. Nature 2006, 439, 326–330. [Google Scholar] [CrossRef] [PubMed]
  77. Stoetzel, C.; Laurier, V.; Davis, E.E.; Muller, J.; Rix, S.; Badano, J.L.; Leitch, C.C.; Salem, N.; Chouery, E.; Corbani, S.; et al. BBS10 encodes a vertebrate-specific chaperonin-like protein and is a major BBS locus. Nat. Genet. 2006, 38, 521–524. [Google Scholar] [CrossRef] [PubMed]
  78. Chiang, A.P.; Beck, J.S.; Yen, H.-J.; Tayeh, M.K.; Scheetz, T.E.; Swiderski, R.E.; Nishimura, D.Y.; Braun, T.A.; Kim, K.-Y.A.; Huang, J.; et al. Homozygosity mapping with SNP arrays identifies TRIM32, an E3 ubiquitin ligase, as a Bardet-Biedl syndrome gene (BBS11). Proc. Natl. Acad. Sci. USA 2006, 103, 6287–6292. [Google Scholar] [CrossRef] [PubMed]
  79. Stoetzel, C.; Muller, J.; Laurier, V.; Davis, E.E.; Zaghloul, N.A.; Vicaire, S.; Jacquelin, C.; Plewniak, F.; Leitch, C.C.; Sarda, P.; et al. Identification of a novel BBS gene (BBS12) highlights the major role of a vertebrate-specific branch of chaperonin-related proteins in Bardet-Biedl syndrome. Am. J. Hum. Genet. 2007, 80, 1–11. [Google Scholar] [CrossRef] [PubMed]
  80. Jindal, G.A.; Goyal, Y.; Yamaya, K.; Futran, A.S.; Kountouridis, I.; Balgobin, C.A.; Schüpbach, T.; Burdine, R.D.; Shvartsman, S.Y. In vivo severity ranking of Ras pathway mutations associated with developmental disorders. Proc. Natl. Acad. Sci. USA 2017, 114, 510–515. [Google Scholar] [CrossRef] [PubMed]
  81. French, C.R.; Stach, T.R.; March, L.D.; Lehmann, O.J.; Waskiewicz, A.J. Apoptotic and proliferative defects characterize ocular development in a microphthalmic BMP model. Investig. Ophthalmol. Vis. Sci. 2013, 54, 4636–4647. [Google Scholar] [CrossRef] [PubMed]
  82. Deml, B.; Kariminejad, A.; Borujerdi, R.H.R.; Muheisen, S.; Reis, L.M.; Semina, E.V. Mutations in MAB21L2 result in ocular Coloboma, microcornea and cataracts. PLoS Genet. 2015, 11, e1005002. [Google Scholar] [CrossRef] [PubMed]
  83. Lee, J.; Willer, J.R.; Willer, G.B.; Smith, K.; Gregg, R.G.; Gross, J.M. Zebrafish blowout provides genetic evidence for Patched1-mediated negative regulation of Hedgehog signaling within the proximal optic vesicle of the vertebrate eye. Dev. Biol. 2008, 319, 10–22. [Google Scholar] [CrossRef] [PubMed]
  84. Miesfeld, J.B.; Gestri, G.; Clark, B.S.; Flinn, M.A.; Poole, R.J.; Bader, J.R.; Besharse, J.C.; Wilson, S.W.; Link, B.A. Yap and Taz regulate retinal pigment epithelial cell fate. Development 2015, 142, 3021–3032. [Google Scholar] [CrossRef] [PubMed]
  85. Sanna-Cherchi, S.; Sampogna, R.V.; Papeta, N.; Burgess, K.E.; Nees, S.N.; Perry, B.J.; Choi, M.; Bodria, M.; Liu, Y.; Weng, P.L.; et al. Mutations in DSTYK and dominant urinary tract malformations. N. Engl. J. Med. 2013, 369, 621–629. [Google Scholar] [CrossRef] [PubMed]
  86. Patten, S.A.; Jacobs-McDaniels, N.L.; Zaouter, C.; Drapeau, P.; Albertson, R.C.; Moldovan, F. Role of Chd7 in zebrafish: A model for CHARGE syndrome. PLoS ONE 2012, 7, e31650. [Google Scholar] [CrossRef] [PubMed]
  87. Prykhozhij, S.V.; Steele, S.L.; Razaghi, B.; Berman, J.N. A rapid and effective method for screening, sequencing and reporter verification of engineered frameshift mutations in zebrafish. Dis. Models Mech. 2017, 10, 811–822. [Google Scholar] [CrossRef] [PubMed]
  88. Lee, S.-H.; Nam, T.-S.; Li, W.; Kim, J.H.; Yoon, W.; Choi, Y.-D.; Kim, K.-H.; Cai, H.; Kim, M.J.; Kim, C.; et al. Functional validation of novel MKS3/TMEM67 mutations in COACH syndrome. Sci. Rep. 2017, 7, 10222. [Google Scholar] [CrossRef] [PubMed]
  89. Leitch, C.C.; Zaghloul, N.A.; Davis, E.E.; Stoetzel, C.; Diaz-Font, A.; Rix, S.; Alfadhel, M.; Al-Fadhel, M.; Lewis, R.A.; Eyaid, W.; et al. Hypomorphic mutations in syndromic encephalocele genes are associated with Bardet-Biedl syndrome. Nat. Genet. 2008, 40, 443–448. [Google Scholar] [CrossRef] [PubMed]
  90. Edie, S.; Zaghloul, N.A.; Leitch, C.C.; Klinedinst, D.K.; Lebron, J.; Thole, J.F.; McCallion, A.S.; Katsanis, N.; Reeves, R.H. Survey of human chromosome 21 gene expression effects on early development in Danio rerio. bioRxiv 2018. [Google Scholar] [CrossRef] [PubMed]
  91. Pereboom, T.C.; van Weele, L.J.; Bondt, A.; MacInnes, A.W. A zebrafish model of dyskeratosis congenita reveals hematopoietic stem cell formation failure resulting from ribosomal protein-mediated p53 stabilization. Blood 2011, 118, 5458–5465. [Google Scholar] [CrossRef] [PubMed]
  92. Zhang, Y.; Morimoto, K.; Danilova, N.; Zhang, B.; Lin, S. Zebrafish models for dyskeratosis congenita reveal critical roles of p53 activation contributing to hematopoietic defects through RNA processing. PLoS ONE 2012, 7, e30188. [Google Scholar] [CrossRef] [PubMed]
  93. Braun, D.A.; Rao, J.; Mollet, G.; Schapiro, D.; Daugeron, M.-C.; Tan, W.; Gribouval, O.; Boyer, O.; Revy, P.; Jobst-Schwan, T.; et al. Mutations in KEOPS-complex genes cause nephrotic syndrome with primary microcephaly. Nat. Genet. 2017, 49, 1529–1538. [Google Scholar] [CrossRef] [PubMed]
  94. Mackay, E.W.; Apschner, A.; Schulte-Merker, S. Vitamin K reduces hypermineralisation in zebrafish models of PXE and GACI. Development 2015, 142, 1095–1101. [Google Scholar] [CrossRef] [PubMed]
  95. Apschner, A.; Huitema, L.F.A.; Ponsioen, B.; Peterson-Maduro, J.; Schulte-Merker, S. Zebrafish enpp1 mutants exhibit pathological mineralization, mimicking features of generalized arterial calcification of infancy (GACI) and pseudoxanthoma elasticum (PXE). Dis. Models Mech. 2014, 7, 811–822. [Google Scholar] [CrossRef] [PubMed]
  96. Li, Q.; Sadowski, S.; Frank, M.; Chai, C.; Váradi, A.; Ho, S.-Y.; Lou, H.; Dean, M.; Thisse, C.; Thisse, B.; et al. The abcc6a gene expression is required for normal zebrafish development. J. Investig. Dermatol. 2010, 130, 2561–2568. [Google Scholar] [CrossRef] [PubMed]
  97. Hoff, S.; Halbritter, J.; Epting, D.; Frank, V.; Nguyen, T.-M.T.; van Reeuwijk, J.; Boehlke, C.; Schell, C.; Yasunaga, T.; Helmstädter, M.; et al. ANKS6 is a central component of a nephronophthisis module linking NEK8 to INVS and NPHP3. Nat. Genet. 2013, 45, 951–956. [Google Scholar] [CrossRef] [PubMed]
  98. Xu, W.; Jin, M.; Hu, R.; Wang, H.; Zhang, F.; Yuan, S.; Cao, Y. The Joubert Syndrome Protein Inpp5e Controls Ciliogenesis by Regulating Phosphoinositides at the Apical Membrane. J. Am. Soc. Nephrol. 2017, 28, 118–129. [Google Scholar] [CrossRef] [PubMed]
  99. Valente, E.M.; Logan, C.V.; Mougou-Zerelli, S.; Lee, J.H.; Silhavy, J.L.; Brancati, F.; Iannicelli, M.; Travaglini, L.; Romani, S.; Illi, B.; et al. Mutations in TMEM216 perturb ciliogenesis and cause Joubert, Meckel and related syndromes. Nat. Genet. 2010, 42, 619–625. [Google Scholar] [CrossRef] [PubMed]
  100. Simms, R.J.; Hynes, A.M.; Eley, L.; Inglis, D.; Chaudhry, B.; Dawe, H.R.; Sayer, J.A. Modelling a ciliopathy: Ahi1 knockdown in model systems reveals an essential role in brain, retinal, and renal development. Cell. Mol. Life Sci. 2012, 69, 993–1009. [Google Scholar] [CrossRef] [PubMed]
  101. Cantagrel, V.; Silhavy, J.L.; Bielas, S.L.; Swistun, D.; Marsh, S.E.; Bertrand, J.Y.; Audollent, S.; Attié-Bitach, T.; Holden, K.R.; Dobyns, W.B.; et al. Mutations in the cilia gene ARL13B lead to the classical form of Joubert syndrome. Am. J. Hum. Genet. 2008, 83, 170–179. [Google Scholar] [CrossRef] [PubMed]
  102. Bachmann-Gagescu, R.; Phelps, I.G.; Stearns, G.; Link, B.A.; Brockerhoff, S.E.; Moens, C.B.; Doherty, D. The ciliopathy gene cc2d2a controls zebrafish photoreceptor outer segment development through a role in Rab8-dependent vesicle trafficking. Hum. Mol. Genet. 2011, 20, 4041–4055. [Google Scholar] [CrossRef] [PubMed]
  103. Ferrante, M.I.; Romio, L.; Castro, S.; Collins, J.E.; Goulding, D.A.; Stemple, D.L.; Woolf, A.S.; Wilson, S.W. Convergent extension movements and ciliary function are mediated by ofd1, a zebrafish orthologue of the human oral-facial-digital type 1 syndrome gene. Hum. Mol. Genet. 2009, 18, 289–303. [Google Scholar] [CrossRef] [PubMed]
  104. Van De Weghe, J.C.; Rusterholz, T.D.S.; Latour, B.; Grout, M.E.; Aldinger, K.A.; Shaheen, R.; Dempsey, J.C.; Maddirevula, S.; Cheng, Y.-H.H.; Phelps, I.G.; et al. Mutations in ARMC9, which Encodes a Basal Body Protein, Cause Joubert Syndrome in Humans and Ciliopathy Phenotypes in Zebrafish. Am. J. Hum. Genet. 2017, 101, 23–36. [Google Scholar] [CrossRef] [PubMed]
  105. Khanna, H.; Davis, E.E.; Murga-Zamalloa, C.A.; Estrada-Cuzcano, A.; Lopez, I.; den Hollander, A.I.; Zonneveld, M.N.; Othman, M.I.; Waseem, N.; Chakarova, C.F.; et al. A common allele in RPGRIP1L is a modifier of retinal degeneration in ciliopathies. Nat. Genet. 2009, 41, 739–745. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  106. Frosk, P.; Arts, H.H.; Philippe, J.; Gunn, C.S.; Brown, E.L.; Chodirker, B.; Simard, L.; Majewski, J.; Fahiminiya, S.; Russell, C.; et al. A truncating mutation in CEP55 is the likely cause of MARCH, a novel syndrome affecting neuronal mitosis. J. Med. Genet. 2017, 54, 490–501. [Google Scholar] [CrossRef] [PubMed]
  107. Wan, J.; Yourshaw, M.; Mamsa, H.; Rudnik-Schöneborn, S.; Menezes, M.P.; Hong, J.E.; Leong, D.W.; Senderek, J.; Salman, M.S.; Chitayat, D.; et al. Mutations in the RNA exosome component gene EXOSC3 cause pontocerebellar hypoplasia and spinal motor neuron degeneration. Nat. Genet. 2012, 44, 704–708. [Google Scholar] [CrossRef] [PubMed]
  108. Hjeij, R.; Lindstrand, A.; Francis, R.; Zariwala, M.A.; Liu, X.; Li, Y.; Damerla, R.; Dougherty, G.W.; Abouhamed, M.; Olbrich, H.; et al. ARMC4 mutations cause primary ciliary dyskinesia with randomization of left/right body asymmetry. Am. J. Hum. Genet. 2013, 93, 357–367. [Google Scholar] [CrossRef] [PubMed]
  109. Becker-Heck, A.; Zohn, I.E.; Okabe, N.; Pollock, A.; Lenhart, K.B.; Sullivan-Brown, J.; McSheene, J.; Loges, N.T.; Olbrich, H.; Haeffner, K.; et al. The coiled-coil domain containing protein CCDC40 is essential for motile cilia function and left-right axis formation. Nat. Genet. 2011, 43, 79–84. [Google Scholar] [CrossRef] [PubMed]
  110. Zariwala, M.A.; Gee, H.Y.; Kurkowiak, M.; Al-Mutairi, D.A.; Leigh, M.W.; Hurd, T.W.; Hjeij, R.; Dell, S.D.; Chaki, M.; Dougherty, G.W.; et al. ZMYND10 is mutated in primary ciliary dyskinesia and interacts with LRRC6. Am. J. Hum. Genet. 2013, 93, 336–345. [Google Scholar] [CrossRef] [PubMed]
  111. Person, A.D.; Beiraghi, S.; Sieben, C.M.; Hermanson, S.; Neumann, A.N.; Robu, M.E.; Schleiffarth, J.R.; Billington, C.J.; van Bokhoven, H.; Hoogeboom, J.M.; et al. WNT5A mutations in patients with autosomal dominant Robinow syndrome. Dev. Dyn. 2010, 239, 327–337. [Google Scholar] [PubMed]
  112. Otto, E.A.; Hurd, T.W.; Airik, R.; Chaki, M.; Zhou, W.; Stoetzel, C.; Patil, S.B.; Levy, S.; Ghosh, A.K.; Murga-Zamalloa, C.A.; et al. Candidate exome capture identifies mutation of SDCCAG8 as the cause of a retinal-renal ciliopathy. Nat. Genet. 2010, 42, 840–850. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  113. Van Karnebeek, C.D.M.; Bonafé, L.; Wen, X.-Y.; Tarailo-Graovac, M.; Balzano, S.; Royer-Bertrand, B.; Ashikov, A.; Garavelli, L.; Mammi, I.; Turolla, L.; et al. NANS-mediated synthesis of sialic acid is required for brain and skeletal development. Nat. Genet. 2016, 48, 777–784. [Google Scholar] [CrossRef] [PubMed]
  114. Sander, J.D.; Cade, L.; Khayter, C.; Reyon, D.; Peterson, R.T.; Joung, J.K.; Yeh, J.-R.J. Targeted gene disruption in somatic zebrafish cells using engineered TALENs. Nat. Biotechnol. 2011, 29, 697–698. [Google Scholar] [CrossRef] [PubMed]
  115. Bedell, V.M.; Wang, Y.; Campbell, J.M.; Poshusta, T.L.; Starker, C.G.; Krug, R.G.; Tan, W.; Penheiter, S.G.; Ma, A.C.; Leung, A.Y.H.; et al. In vivo genome editing using a high-efficiency TALEN system. Nature 2012, 491, 114–118. [Google Scholar] [CrossRef] [PubMed]
  116. Reyon, D.; Tsai, S.Q.; Khayter, C.; Foden, J.A.; Sander, J.D.; Joung, J.K. FLASH assembly of TALENs for high-throughput genome editing. Nat. Biotechnol. 2012, 30, 460–465. [Google Scholar] [CrossRef] [PubMed]
  117. Jao, L.-E.; Wente, S.R.; Chen, W. Efficient multiplex biallelic zebrafish genome editing using a CRISPR nuclease system. Proc. Natl. Acad. Sci. USA 2013, 110, 13904–13909. [Google Scholar] [CrossRef] [PubMed]
  118. Gagnon, J.A.; Valen, E.; Thyme, S.B.; Huang, P.; Ahkmetova, L.; Pauli, A.; Montague, T.G.; Zimmerman, S.; Richter, C.; Schier, A.F. Efficient mutagenesis by Cas9 protein-mediated oligonucleotide insertion and large-scale assessment of single-guide RNAs. PLoS ONE 2014, 9, e98186. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  119. Hwang, W.Y.; Fu, Y.; Reyon, D.; Maeder, M.L.; Tsai, S.Q.; Sander, J.D.; Peterson, R.T.; Yeh, J.-R.J.; Joung, J.K. Efficient genome editing in zebrafish using a CRISPR-Cas system. Nat. Biotechnol. 2013, 31, 227–229. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  120. Hwang, W.Y.; Fu, Y.; Reyon, D.; Maeder, M.L.; Kaini, P.; Sander, J.D.; Joung, J.K.; Peterson, R.T.; Yeh, J.-R.J. Heritable and Precise Zebrafish Genome Editing Using a CRISPR-Cas System. PLoS ONE 2013, 8, e68708. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  121. Talbot, J.C.; Amacher, S.L. A Streamlined CRISPR Pipeline to Reliably Generate Zebrafish Frameshifting Alleles. Zebrafish 2014, 11, 583–585. [Google Scholar] [CrossRef] [PubMed]
  122. Hruscha, A.; Krawitz, P.; Rechenberg, A.; Heinrich, V.; Hecht, J.; Haass, C.; Schmid, B. Efficient CRISPR/Cas9 genome editing with low off-target effects in zebrafish. Development 2013, 140, 4982–4987. [Google Scholar] [CrossRef] [PubMed]
  123. Varshney, G.K.; Sood, R.; Burgess, S.M. Understanding and Editing the Zebrafish Genome. Adv. Genet. 2015, 92, 1–52. [Google Scholar] [PubMed]
  124. Irion, U.; Krauss, J.; Nüsslein-Volhard, C. Precise and efficient genome editing in zebrafish using the CRISPR/Cas9 system. Development 2014, 141, 4827–4830. [Google Scholar] [CrossRef] [PubMed]
  125. Hisano, Y.; Sakuma, T.; Nakade, S.; Ohga, R.; Ota, S.; Okamoto, H.; Yamamoto, T.; Kawahara, A. Precise in-frame integration of exogenous DNA mediated by CRISPR/Cas9 system in zebrafish. Sci. Rep. 2015, 5, 8841. [Google Scholar] [CrossRef] [PubMed]
  126. Hoshijima, K.; Jurynec, M.J.; Grunwald, D.J. Precise Editing of the Zebrafish Genome Made Simple and Efficient. Dev. Cell 2016, 36, 654–667. [Google Scholar] [CrossRef] [PubMed]
  127. Koo, T.; Lee, J.; Kim, J.-S. Measuring and Reducing Off-Target Activities of Programmable Nucleases Including CRISPR-Cas9. Mol. Cells 2015, 38, 475–481. [Google Scholar] [CrossRef] [PubMed]
  128. Kulcsár, P.I.; Tálas, A.; Huszár, K.; Ligeti, Z.; Tóth, E.; Weinhardt, N.; Fodor, E.; Welker, E. Crossing enhanced and high fidelity SpCas9 nucleases to optimize specificity and cleavage. Genome Biol. 2017, 18, 190. [Google Scholar] [CrossRef] [PubMed]
  129. Varshney, G.K.; Zhang, S.; Pei, W.; Adomako-Ankomah, A.; Fohtung, J.; Schaffer, K.; Carrington, B.; Maskeri, A.; Slevin, C.; Wolfsberg, T.; et al. CRISPRz: A database of zebrafish validated sgRNAs. Nucleic Acids Res. 2016, 44, D822–D826. [Google Scholar] [CrossRef] [PubMed]
  130. Peterson, R.T.; Shaw, S.Y.; Peterson, T.A.; Milan, D.J.; Zhong, T.P.; Schreiber, S.L.; Macrae, C.A.; Fishman, M.C. Chemical suppression of a genetic mutation in a zebrafish model of aortic coarctation. Nat. Biotechnol. 2004, 22, 595–599. [Google Scholar] [CrossRef] [PubMed]
  131. Kwan, K.M.; Fujimoto, E.; Grabher, C.; Mangum, B.D.; Hardy, M.E.; Campbell, D.S.; Parant, J.M.; Yost, H.J.; Kanki, J.P.; Chien, C.-B. The Tol2kit: A multisite gateway-based construction kit for Tol2 transposon transgenesis constructs. Dev. Dyn. 2007, 236, 3088–3099. [Google Scholar] [CrossRef] [PubMed]
  132. Kawakami, K. Tol2: A versatile gene transfer vector in vertebrates. Genome Biol. 2007, 8, S7. [Google Scholar] [CrossRef] [PubMed]
  133. Kikuta, H.; Kawakami, K. Chapter 5—Transient and Stable Transgenesis Using Tol2 Transposon Vectors. In Zebrafish; Humana Press: New York, NY, USA, 2009. [Google Scholar]
  134. Urasaki, A.; Kawakami, K. Chapter 6—Analysis of Genes and Genome by the Tol2-Mediated Gene and Enhancer Trap Methods. In Zebrafish; Humana Press: New York, NY, USA, 2009. [Google Scholar]
  135. Kawakami, K.; Abe, G.; Asada, T.; Asakawa, K.; Fukuda, R.; Ito, A.; Lal, P.; Mouri, N.; Muto, A.; Suster, M.L.; et al. zTrap: Zebrafish gene trap and enhancer trap database. BMC Dev. Biol. 2010, 10, 105. [Google Scholar] [CrossRef] [PubMed]
  136. Jungke, P.; Hans, S.; Brand, M. The Zebrafish CreZoo: An Easy-to-Handle Database for Novel CreER T2-Driver Lines. Zebrafish 2013, 10, 259–263. [Google Scholar] [CrossRef] [PubMed]
  137. Ablain, J.; Durand, E.M.; Yang, S.; Zhou, Y.; Zon, L.I. A CRISPR/Cas9 vector system for tissue-specific gene disruption in zebrafish. Dev. Cell 2015, 32, 756–764. [Google Scholar] [CrossRef] [PubMed]
  138. Di Donato, V.; De Santis, F.; Auer, T.O.; Testa, N.; Sánchez-Iranzo, H.; Mercader, N.; Concordet, J.-P.; Del Bene, F. 2C-Cas9: A versatile tool for clonal analysis of gene function. Genome Res. 2016, 26, 681–692. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  139. Bill, B.R.; Petzold, A.M.; Clark, K.J.; Schimmenti, L.A.; Ekker, S.C. A primer for morpholino use in zebrafish. Zebrafish 2009, 6, 69–77. [Google Scholar] [CrossRef] [PubMed]
  140. McGary, K.L.; Park, T.J.; Woods, J.O.; Cha, H.J.; Wallingford, J.B.; Marcotte, E.M. Systematic discovery of nonobvious human disease models through orthologous phenotypes. Proc. Natl. Acad. Sci. USA 2010, 107, 6544–6549. [Google Scholar] [CrossRef] [PubMed]
  141. Song, Z.; Zhang, X.; Jia, S.; Yelick, P.C.; Zhao, C. Zebrafish as a Model for Human Ciliopathies. J. Genet. Genom. 2016, 43, 107–120. [Google Scholar] [CrossRef] [PubMed]
  142. Yu, P.B.; Hong, C.C.; Sachidanandan, C.; Babitt, J.L.; Deng, D.Y.; Hoyng, S.A.; Lin, H.Y.; Bloch, K.D.; Peterson, R.T. Dorsomorphin inhibits BMP signals required for embryogenesis and iron metabolism. Nat. Chem. Biol. 2008, 4, 33–41. [Google Scholar] [CrossRef] [PubMed]
  143. Kaufman, C.K.; White, R.M.; Zon, L. Chemical genetic screening in the zebrafish embryo. Nat. Protoc. 2009, 4, 1422–1432. [Google Scholar] [CrossRef] [PubMed]
  144. Griffin, A.; Hamling, K.R.; Knupp, K.; Hong, S.; Lee, L.P.; Baraban, S.C. Clemizole and modulators of serotonin signalling suppress seizures in Dravet syndrome. Brain 2017, 140, 669–683. [Google Scholar] [CrossRef] [PubMed]
  145. Ekins, S. Industrializing rare disease therapy discovery and development. Nat. Biotechnol. 2017, 35, 117–118. [Google Scholar] [CrossRef] [PubMed]
  146. Danilova, N.; Bibikova, E.; Covey, T.M.; Nathanson, D.; Dimitrova, E.; Konto, Y.; Lindgren, A.; Glader, B.; Radu, C.G.; Sakamoto, K.M.; et al. The role of the DNA damage response in zebrafish and cellular models of Diamond Blackfan anemia. Dis. Model Mech. 2014, 7, 895–905. [Google Scholar] [CrossRef] [PubMed]
  147. Li, M.; Andersson-Lendahl, M.; Sejersen, T.; Arner, A. Muscle dysfunction and structural defects of dystrophin-null sapje mutant zebrafish larvae are rescued by ataluren treatment. FASEB J. 2014, 28, 1593–1599. [Google Scholar] [CrossRef] [PubMed]
  148. Rasighaemi, P.; Basheer, F.; Liongue, C.; Ward, A.C. Zebrafish as a model for leukemia and other hematopoietic disorders. J. Hematol. Oncol. 2015, 8, 29. [Google Scholar] [CrossRef] [PubMed]
  149. Deveau, A.P.; Bentley, V.L.; Berman, J.N. Using zebrafish models of leukemia to streamline drug screening and discovery. Exp. Hematol. 2017, 45, 1–9. [Google Scholar] [CrossRef] [PubMed]
  150. He, S.; Jing, C.-B.; Look, A.T. Zebrafish models of leukemia. Methods Cell Biol. 2017, 138, 563–592. [Google Scholar] [PubMed]
  151. Fior, R.; Póvoa, V.; Mendes, R.V.; Carvalho, T.; Gomes, A.; Figueiredo, N.; Ferreira, M.G. Single-cell functional and chemosensitive profiling of combinatorial colorectal therapy in zebrafish xenografts. Proc. Natl. Acad. Sci. USA 2017, 114, E8234–E8243. [Google Scholar] [CrossRef] [PubMed]
  152. Lin, J.; Zhang, W.; Zhao, J.-J.; Kwart, A.H.; Yang, C.; Ma, D.; Ren, X.; Tai, Y.-T.; Anderson, K.C.; Handin, R.I.; et al. A clinically relevant in vivo zebrafish model of human multiple myeloma to study preclinical therapeutic efficacy. Blood 2016, 128, 249–252. [Google Scholar] [CrossRef] [PubMed]
  153. Gaudenzi, G.; Albertelli, M.; Dicitore, A.; Würth, R.; Gatto, F.; Barbieri, F.; Cotelli, F.; Florio, T.; Ferone, D.; Persani, L.; et al. Patient-derived xenograft in zebrafish embryos: A new platform for translational research in neuroendocrine tumors. Endocrine 2017, 57, 214–219. [Google Scholar] [CrossRef] [PubMed]
  154. Komor, A.C.; Kim, Y.B.; Packer, M.S.; Zuris, J.A.; Liu, D.R. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 2016, 533, 420–424. [Google Scholar] [CrossRef] [PubMed]
  155. Kim, Y.B.; Komor, A.C.; Levy, J.M.; Packer, M.S.; Zhao, K.T.; Liu, D.R. Increasing the genome-targeting scope and precision of base editing with engineered Cas9-cytidine deaminase fusions. Nat. Biotechnol. 2017, 35, 371–376. [Google Scholar] [CrossRef] [PubMed]
  156. Gaudelli, N.M.; Komor, A.C.; Rees, H.A.; Packer, M.S.; Badran, A.H.; Bryson, D.I.; Liu, D.R. Programmable base editing of A•T to G•C in genomic DNA without DNA cleavage. Nature 2017, 551, 464–471. [Google Scholar] [CrossRef] [PubMed]
  157. Li, X.; Wang, Y.; Liu, Y.; Yang, B.; Wang, X.; Wei, J.; Lu, Z.; Zhang, Y.; Wu, J.; Huang, X.; et al. Base editing with a Cpf1-cytidine deaminase fusion. Nat. Biotechnol. 2018, 36, 324–327. [Google Scholar] [CrossRef] [PubMed]
  158. Poon, K.L.; Wang, X.; Ng, A.S.; Goh, W.H.; McGinnis, C.; Fowler, S.; Carney, T.J.; Wang, H.; Ingham, P.W. Humanizing the zebrafish liver shifts drug metabolic profiles and improves pharmacokinetics of CYP3A4 substrates. Arch. Toxicol. 2017, 91, 1187–1197. [Google Scholar] [CrossRef] [PubMed]
  159. Bastarache, L.; Hughey, J.J.; Hebbring, S.; Marlo, J.; Zhao, W.; Ho, W.T.; Van Driest, S.L.; McGregor, T.L.; Mosley, J.D.; Wells, Q.S.; et al. Phenotype risk scores identify patients with unrecognized Mendelian disease patterns. Science 2018, 359, 1233–1239. [Google Scholar] [CrossRef] [PubMed]
  160. Sulem, P.; Helgason, H.; Oddson, A.; Stefansson, H.; Gudjonsson, S.A.; Zink, F.; Hjartarson, E.; Sigurdsson, G.T.; Jonasdottir, A.; Jonasdottir, A.; et al. Identification of a large set of rare complete human knockouts. Nat. Genet. 2015, 47, 448–452. [Google Scholar] [CrossRef] [PubMed]
  161. Jagannathan, S.; Bradley, R.K. Translational plasticity facilitates the accumulation of nonsense genetic variants in the human population. Genome Res. 2016, 26, 1639–1650. [Google Scholar] [CrossRef] [PubMed]
Diseases 06 00043 g001 550
Figure 1. A high level of genetic conservation makes zebrafish an ideal genetic model organism to study pediatric disease. (OMIM–Online Mendelian Inheritance in Man database). Data sources: [18,26]. (Note that the PedAM database contains 4542 unique disease concepts, but the majority of them are associated with multiple genes.).
Figure 1. A high level of genetic conservation makes zebrafish an ideal genetic model organism to study pediatric disease. (OMIM–Online Mendelian Inheritance in Man database). Data sources: [18,26]. (Note that the PedAM database contains 4542 unique disease concepts, but the majority of them are associated with multiple genes.).
Diseases 06 00043 g001
Table
Table 1. A representative list of existing zebrafish pediatric disease models.
Table 1. A representative list of existing zebrafish pediatric disease models.
Disease NameICD-10Genes Targeted in ModelsOMIM IDsModel TypeReferences
Diseases of the blood and blood forming organs
Blackfan-Diamond anemiaD61.0RPS19, RPL11, RPS7105650, 612562, 603658MO, mutant[41,42,43]
DiGeorge syndromeD82.1SNAP29, AIFM3, CRKL604202, 617298, 602007MO, crispant[44]
Reticular dysgenesisD81.0AK2267500MO[45]
Sideroblastic anemia (AR)D64.0SLC25A38205950MO[46]
X-linked sideroblastic anemiaD64.0ALAS2300751mutant[47]
Endocrine and metabolic diseases
Batten disease (Juvenile neuronal ceroid lipofuscinosis)E75.4CLN3, TPP1204200, 204500mutant, MO[48,49]
Menkes diseaseE83.0ATP7A309400mutant[50]
Nephropatic infantile cystinosisE72.0CTNS219800mutant[51]
X-linked adrenoleukodystrophy (ALD)E71.3ABCD1300100mutant[52]
Diseases of the nervous system
Charcot-Marie-Tooth syndromeG60.0MFN2, GDAP1, ABHD12, MED25, HSPB1, WNK1608507, 606598, 613599, 610197, 602195, 605232MO[53]
Childhood-onset parkinsonism-dystonia SLC39A14617013mutant[54]
Dravet syndromeG40.4SCN1A182389mutant[55]
Duchenne muscular dystrophyG71.0DMD310200mutant[56]
Generalized epilepsy with febrile seizures-plusG40.3STX1B616172MO[57]
Spinal muscular atrophyG12SMN1600354MO, mutant[58,59]
Diseases of the circulatory system
Dilated cardiomyopathyI42.0BAG3603883MO, transgenic[60,61]
Timothy syndromeI45.8CACNA1C601005MO[62]
Diseases of the musculoskeletal system
Fibrodysplasia ossificans progressiva (FOP)M61.1ACVR1135100mRNA, transgenic[63,64,65]
Vasculitis due to ADA2 deficiencyM30.8ADA2615688MO[66]
Diseases of the genitourinary system
Polycystic kidney disease (PKD) PKD1, PKD2173900, 613095MO, mutant[67,68,69]
Congenital malformations
16p11.2 microdeletion/microduplication syndrome KCTD13608947MO, mRNA[70]
3MC syndromeQ87.8COLEC11, MASP1265050, 257920 MO[71]
Autosomal recessive polycistic kidney diseaseQ61.1DZIP1L617610MO, mutant[72]
Axenfeld-Rieger syndromeQ13.8PITX2180500mutant[73]
Bardet-Biedl syndrome (BBS)Q87.8BBS1, BBS2, BBS4, BBS5, BBS6, BBS7, BBS8, BBS10, BBS11, BBS12, CCDC28B20991, 600374, 605231, 615981, 615983, 615984, 615985, 615987, 615988, 615989, 610162MO, [74,75,76,77,78,79]
Cardiofaciocutaneous syndromeQ87.8MEK1615279mRNA[80]
Coloboma GDF6, MAB21L2, PTCH1, YAP1601147, 615877, 601309, 120433mutant[81,82,83,84]
Congenital anomalies of kidney and urinary tract (CAKUT) DSTYK612666MO[85]
CHARGE syndromeQ87.8CHD7608892MO, mutant[86,87]
COACH syndromeQ04.3MKS3/TMEM67216360MO[88,89]
Down syndromeQ9021q22.3190685mRNA[90]
Dyskeratosis congenitaQ82.8DKC1, NOLA3/NOP10305000, 224230MO, mutant[91,92]
Galloway-Mowat syndromeQ04.3OSGEP, TPRKB617729, 617731crispant[93]
Generalized arterial calcification in infancy (GACI)Q28.8ABCC6, ENPP1614473, 208000MO, mutants[94,95,96]
Infantile nephronophthisisQ61.5ANKS6615382MO[97]
Joubert syndromeQ04.3JBTS1/INPP5E, JBTS2/TMEM216, JBTS3/AHI1, JBTS5/CEP290, JBTS7/RPGRIP1L, JBTS8/ARL13B, JBTS9/CC2D2A, JBTS10/OFD1, ARMC9213300, 608091, 608629, 610188, 611560, 610688, 612291, 612285, 300804, 617612MO, mutant[89,98,99,100,101,102,103,104,105]
MARCH syndrome CEP55610000MO, crispant[106]
Pontocerebellar hypoplasia (1B)Q04.3EXOSC3614678MO[107]
Primary ciliary dyskenesiaQ34.8ARMC4, CCDC40, ZMYND10615451, 613799, 615444MO, mutant[108,109,110]
Robinow syndrome (AD)Q87.1WNT5A180700mRNA[111]
Senior-Løken syndromeQ61.5SDCCAG8613615MO[112]
Spondyloepimetaphyseal dysplasiaQ77.7NANS610442MO[113]
Table
Table 2. Some examples for the use/test of drugs with human relevance in zebrafish disease models.
Table 2. Some examples for the use/test of drugs with human relevance in zebrafish disease models.
SyndromeDrug/Small Molecule UsedTarget/FunctionReferences
Aortic coarctationGS4012VEGF inducer[130]
Blackfan-Diamond anemiaPF477736CHK1 inhibitor[146]
Childhood-onset parkinsonism-dystoniaNa2CaEDTAMn chelator[54]
Dravet syndromeclemizoleSerotonin modulators[55,144]
lorcaserin
Duchenne muscular dystrophyAtaluren (PTC124)Translational readthrough agonist[147]
Fibrodysplasia ossificans progressiva (FOP)Dorsomorphin (and derivatives)BMP Type 1 Receptor inhibitor[142]
Generalized arterial calcification in infancy (GACI)EtidronatePPi analog[95]
Sideroblastic anemia (AR)Glycine and folatesupplement[46]
Spondyloepimetaphyseal dysplasiaSialic acidsupplement[113]

Share and Cite

MDPI and ACS Style

Varga, M.; Ralbovszki, D.; Balogh, E.; Hamar, R.; Keszthelyi, M.; Tory, K. Zebrafish Models of Rare Hereditary Pediatric Diseases. Diseases 2018, 6, 43. https://doi.org/10.3390/diseases6020043

AMA Style

Varga M, Ralbovszki D, Balogh E, Hamar R, Keszthelyi M, Tory K. Zebrafish Models of Rare Hereditary Pediatric Diseases. Diseases. 2018; 6(2):43. https://doi.org/10.3390/diseases6020043

Chicago/Turabian Style

Varga, Máté, Dorottya Ralbovszki, Eszter Balogh, Renáta Hamar, Magdolna Keszthelyi, and Kálmán Tory. 2018. "Zebrafish Models of Rare Hereditary Pediatric Diseases" Diseases 6, no. 2: 43. https://doi.org/10.3390/diseases6020043

APA Style

Varga, M., Ralbovszki, D., Balogh, E., Hamar, R., Keszthelyi, M., & Tory, K. (2018). Zebrafish Models of Rare Hereditary Pediatric Diseases. Diseases, 6(2), 43. https://doi.org/10.3390/diseases6020043

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop