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Review Article

Authors

  • Thomas S. Becker,

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    1. Brain and Mind Research Institute, Sydney Medical School, University of Sydney, 100 Mallett St, Camperdown, NSW 2050, Australia
    • Brain and Mind Research Institute, Sydney Medical School, University of Sydney, 100 Mallett St, Camperdown, NSW 2050, Australia
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  • Silke Rinkwitz

    1. Brain and Mind Research Institute, Sydney Medical School, University of Sydney, 100 Mallett St, Camperdown, NSW 2050, Australia
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  • First published: 10 February 2012Full publication history
  • DOI: 10.1002/dneu.20888View/save citation
  • Cited by: 11 articles
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Abstract

Whole exome sequencing and, to a lesser extent, genome-wide association studies, have provided unprecedented advances in identifying genes and candidate genomic regions involved in the development of human disease. Further progress will come from sequencing the entire genome of multiple patients and normal controls to evaluate overall mutational burden and disease risk. A major challenge will be the interpretation of the resulting data and distinguishing true pathogenic mutations from rare benign variants. While in model organisms such as the zebrafish, mutants are sought that disrupt the function of individual genes, human mutations that cause, or are associated with, the development of disease, are often not acting in a Mendelian fashion, are frequently of small effect size, are late onset, and may reside in noncoding parts of the genome. The zebrafish model is uniquely poised for understanding human coding- and noncoding variants because of its sequenced genome, a large body of knowledge on gene expression and function, rapid generation time, and easy access to embryos. A critical advantage is the ease of zebrafish transgenesis, both for the testing of human regulatory DNA driving expression of fluorescent reporter proteins, and the expression of mutated disease-associated human proteins in specific neurons to rapidly model aspects of neurological disorders. The zebrafish affords progress both through its model genome and it is rapidly developing transparent model vertebrate embryo. © 2011 Wiley Periodicals, Inc. Develop Neurobiol 72: 415–428, 2012

INTRODUCTION

The zebrafish is a popular model in biomedical research because as a vertebrate it has a body plan similar to humans, and uses an essentially identical gene complement for its embryonic development. The genomes of zebrafish and other teleosts, despite representing an evolutionary distance of several hundred millions years from mammals, display remarkable similarity to the human genome in terms of gene order in large regions of conserved synteny that are further characterized by the presence of long-range enhancers and their target genes (Kikuta et al.,2007a, b, reviewed by Canestro et al.,2007; Kikuta et al.,2007a, b; Navratilova and Becker,2009).

From the viewpoint of the developmental geneticist, mutations causing human diseases fall into three distinct categories. The classic phenotypes analyzed in model organisms are usually (and preferably) caused by homozygous loss of function mutations or complete knockdown of a gene's mRNA, with catastrophic consequences for the organism, often-embryonic lethality and/or severe malformations. The equivalent of this type of deleterious mutation in humans are the cause of Mendelian disease, where a homozygous, a hemizygous X-chromosomal, or a heterozygous, and haploinsufficient, mutation lead to a phenotype (= disease) in virtually every individual carrying the mutation. Because these highly penetrant mutations often result in reduced reproductive fitness, they tend to be rare because they are strongly selected against. In this category, individuals with the mutation are born with the disease, and many mutations identified are sporadic (de novo), as affected individuals are unlikely to reproduce [e.g., (Vissers et al.,2010)]. Great strides have been made in the identification of underlying mutations in Mendelian diseases through the successes of the human genome project and the development of associated genome technologies. In both, affected human families and model organisms, the genomic region containing the mutated gene is narrowed down by linkage studies (provided there are sufficient numbers of affected individuals), yielding a number of candidate genes, which are then individually sequenced until a deleterious mutation in the coding sequence is identified (Strachan and Read,1999). Further understanding of disease/phenotype development is then made through the recovery of mutations in the orthologous genes in model organisms and the investigation of the associated phenotypes.

However, many common human diseases, including those affecting the nervous system, fall into a second category: their onset may be at some point during adult life, and often after reproductive stages. In addition, mutations involved in the development of late onset disease such as Alzheimer's or frontotemporal dementia are usually not causing loss of function of a gene, but instead involve mutations that generate proteins that are toxic to neurons and accumulate over time, leading to neurodegeneration. The third category are mutations that often will not by themselves lead to a disease state unless the carrier has additional detrimental mutations elsewhere that further increase disease risk or lives in an environment that enhances risk. Examples are metabolic disorders such as type2 diabetes (T2D) and obesity, where a genetic disposition may be exacerbated by lack of exercise and a high fat diet. These common human diseases have a heritability of less than 100% and are affected by many loci. For example, for T2D, about 38 loci have been identified by genome-wide association studies (GWAS), each with a very small contribution toward disease risk (Billings and Florez,2010). Together with 11 loci that are known to cause dominant early onset diabetes (MODY) this adds up to roughly 50 loci that explain about 15% of the heritability of T2D. Much less progress has been made in the identification of risk loci for neurological disorders and psychiatric disease than for diabetes or cancer. In contrast, in X-linked mental retardation (XLMR) currently 90 loci explain about 50% of the heritability, and these are inherited in a Mendelian fashion (Gecz et al.,2009). Regardless of whether mutations are risk factors with low penetrance or are causing late onset of disease with high penetrance, it is likely that a large number of loci will emerge that are associated with human neurological disease, and it will be important to test these in reliable and fast assays. We discuss below how the zebrafish system can be used to interpret human sequence data, both at the protein coding and the noncoding level.

The Zebrafish as a Genetic Neurobiological Model

One prerequisite for the analysis of human neurological diseases in animal model systems is a comparable neuroanatomy as well as genetics/genomics capabilities. At the gross level morphology and major nuclei of the zebrafish brain are similar to human, even though the telencephalon does not develop into a layered cortex. However, there are genetic similarities in its development, for example the deployment of foxg1 to specify dorsal telencephalon/pallium (Danesin et al.,2009). In addition, regions homologous to two major mammalian structures, the basal ganglia and the striatum (Mueller et al.,2004; Rink and Wullimann,2004; Wullimann and Mueller,2004a, b) and the homologues of the mammalian lateral habenula have been identified in zebrafish (Amo et al.,2010). Since a layered structure of the cerebellum is retained in zebrafish, studies of neuronal migration and mutations of genes expressed in the cerebellum have given insights into its formation and the underlying genetic mechanisms (Koster and Fraser,2006; Bae et al.,2009; Volkmann et al.,2010). Development of the hypothalamus employs essentially the same genes as in mammals and its neuroendocrine systems are conserved in zebrafish (Kurrasch et al.,2007; Szarek et al.,2010). In addition, most of the neurotransmitters and neuropeptidergic systems are present in zebrafish [for review see (Panula et al.,2010)]. For example, the catecholaminergic system including dopamine releasing neurons and a set of dopamine receptors has been described and genetically analyzed (Rink and Wullimann,2002; Chen et al.,2009; Filippi et al.,2010; Kastenhuber et al.,2010; Yamamoto et al.,2010). For the hypocretin/orexin system a role in regulating the slee-wake cycle of zebrafish could be established (Yokogawa et al.,2007; Appelbaum et al.,2009). For a more in-depth discussion of human-zebrafish comparative neuroanatomy and -genomics see our recent review (Rinkwitz et al.,2011).

The transparency of zebrafish embryos makes fluorescent reporters especially useful to label neurons for morphological analysis and perturbations. The establishment of the Tol2 transposon system has revolutionized the generation of transgenic zebrafish (Kawakami et al.,2000; Kawakami et al.,2004). The Tol2 transposon can now also be used for the integration of bacterial artificial chromosomes containing (so far) up to 150 kb vertebrate genome sequence (Suster et al.,2009a, b), adding considerable power to the zebrafish model. There are multiple reporters in use: In addition to GFP, red fluorescent (mCherry) and photoconvertible reporters (Sato et al.,2006) have been developed for multiple color labeling of organs, tissues, neurons, and cellular structures and a multisite Gateway®-based Tol2 Kit for efficient modular vector design has been established (Kwan et al.,2007). Many transgenic lines expressing fluorescent proteins have been created through gene-trap/enhancer detection screens (Balciunas et al.,2004; Kawakami et al.,2004; Parinov et al.,2004; Ellingsen et al.,2005; Komisarczuk et al.,2008; Nagayoshi et al.,2008), whereas others have used single promoter/enhancer sequences to drive reporter genes (Komisarczuk et al.,2009; Navratilova and Becker,2009; Navratilova et al.,2010; Punnamoottil et al.,2010). These technologies are now routine, and human enhancers can be used reliably to generate transgenic lines of zebrafish with patterns equivalent to those generated with the same sequences in the mouse [reviewed by (Rinkwitz et al.,2011)]. Further important advances consist of GFP fusion proteins that selectively localize to synapses and dendrites, such as PSD95-GFP (Niell et al.,2004), and synapthophysin-GFP (Meyer and Smith,2006). A variegated UAS:GFP, in addition, allows imaging of single retinal ganglion cell axons and their branching in the optic tectum in live animals (Hua et al.,2005). A similar approach to label single neurons and their axonal projections was the combination of the Gal4/UAS and the Cre/loxP systems in a transient expression approach (Sato et al.,2007). The utility of the variegated GFP and photoconvertible Kaede for the tracing of neuronal circuits was further demonstrated in an enhancer detection screen (Scott et al.,2007; Scott and Baier,2009; reviewed by Scott,2009). A recent study created an optimized KalTA4GI sequence that was used in a feedback loop system to maintain the expression of Gal4 once activated (Distel et al.,2009). This system will be especially useful for the fate mapping of embryonic neuronal lineages to the adult brain, and for the generation of artificial enhancers driving persistent adult brain expression. This abundance of transgenic tools, along with the advantages of zebrafish in terms of neuroanatomical and genomic similarity with human will undoubtedly aid in the use of this system to model aspects of human disorders of the brain. We have below highlighted a few areas where the zebrafish has already contributed and others where we predict significant progress over the coming years.

Zebrafish as a Model for Neurodegenerative Disease

A general advantage of zebrafish for neurodegeneration is not only the accessibility and transparency of the larvae, but also that mutations that may lead to early embryonic death and resorption in mammalian embryos can still be examined. Zebrafish larvae with lethal mutations will still develop and can be examined for phenotypes in the nervous system for several days. For example, in zebrafish with loss of function of the nrf1 gene (encoding nuclear respiratory factor 1) degeneration of photoreceptors and central neurons can be observed (Becker et al.,1998), while the mouse knockout leads to lethality at the time of embryo implantation (Huo and Scarpulla,2001), thus precluding identification of any neuronal phenotype. Recently, it was found that down regulation of NRF1 occurs downstream of loss of function of Parkin, and that this contributes to neurodegeneration in Parkinson's disease (Shin et al.,2011). Neurons can be visualized in transgenic animals, and can be observed in real time, allowing to record changes in morphology and connectivity after genetic or chemical perturbations. For example, motor neurons are visible at 1 day post fertilization (dpf) (Myers et al.,1986) and are readily observed in transgenic lines expressing GFP under the control of regulatory sequences of the islet1 transcription factor gene (Higashijima et al.,2000; Flanagan-Steet et al.,2005). These transgenes have been used to identify genes that, when mutated or their expression is knocked down, lead to aberrant motor neuron development (Birely et al.,2005; Schweitzer et al.,2005; Feldner et al.,2007; Tanaka et al.,2007). Because of the early differentiation and the visibility of GFP-expressing motor neurons, it is straightforward to assay the effect of injection of synthetic mRNA or antisense morpholino (MO) oligonucleotides on the motor system. Human disease-associated mutations can be rapidly tested by either injecting the human mutant RNA and/or a MO, targeting the zebrafish orthologous mRNA, into the one cell stage (Bandmann and Burton,2010; Kabashi et al.,2010a, b). For example mutations in TARDBP, encoding TDP-43, a protein that is found in neuronal inclusion bodies in patients with amyotrophic lateral sclerosis (ALS), and frontotemporal dementia, were identified in ALS (Valdmanis et al.,2009). Three TARDBP missense mutations were tested in zebrafish (Kabashi et al.,2010a, b). Antisense MO injections resulted in a specific motor neuron phenotype with shortened motor axons and increased branching and a locomotor phenotype. Simultaneous overexpression of wt TARDBP mRNA versus mRNAs carrying the mutations showed that the wt mRNA could rescue the phenotype whereas the mutant mRNAs could not (Kabashi et al.,2010a, b). Mutations in the ubiquitously expressed gene encoding superoxide dismutase (SOD1) are a leading cause of ALS and have been shown to cause motor neuron loss in mice and zebrafish (Gurney et al.,1994; Lemmens et al.,2007). The endogenous promoter was used in zebrafish BAC transgenesis to over-express the wt versus mutated coding sequence, and fish with up to fourfold higher sod1 expression in the spinal cord demonstrated that mutant sod1 recapitulated the ALS phenotype including defects of the neuromuscular endplate, loss of motor neurons, and muscle degeneration (Ramesh et al.,2010). A recent report on the toxic effects of mutated tau protein (a cause of early onset Alzheimer's disease) showed that expression of the human mutated gene in zebrafish larvae allowed real time observation of neurodegenerative processes in zebrafish, and, importantly, that this transgenic line of zebrafish could be used to subsequently design small molecules that can interfere with this process (Paquet et al.,2009). Increased cell death in TAU expressing neurons and morphological and behavioral abnormalities (e.g., reduced escape response) are key features in these transgenic larvae. A theme that emerges is that, instead of accurate modeling of a given disease (e.g., generating a mouse or zebrafish that would suffer from motor neuron loss in the second half of life), one can use proxies that will rapidly replicate certain aspects of the disease. This would allow to get at the genetic and/or cell biological mechanisms of motor neuron loss (or loss of function of associated cells of the cerebellum or spinal cord), and preferably during a much shorter time span (in this case inside a week), to define the crucial steps in disease development and find ways to interfere, in such a model, with the development of early hallmarks of the disease, rather than to exactly replicate the (likely later) symptoms. The examples above constitute promising results, and it can be hoped that the speed and ease with which gene defects can be modeled in the zebrafish, in conjunction with large-scale chemical screens, will lead to new therapeutic drugs that can ameliorate ALS and frontotemporal dementia or at least delay onset.

X-linked Mental Retardation

The human X chromosome constitutes a special case because mutations in it will be hemizygous in male individuals, while females are usually not or much less affected. This means that it is easier than in the rest of the genome to estimate the disease load of mutations on the X in the human population. The X chromosome is relatively gene poor (currently 858 genes) and constitutes 5% of the total human genome sequence, but disease-associated mutations on it are disproportionately represented. X-linked mental retardation (XLMR) is a Mendelian neurodevelopmental disorder that affects about 1/1000 males and in about half, there are no other associated phenotypes that segregate with the intellectual disability, (termed nonsyndromic XLMR) making it difficult to distinguish between different subtypes other than by identifying the underlying mutation (Gecz et al.,2009). For syndromic and nonsyndromic XLMR, so far, over 90 causative genes have been identified, which represent 11% of the total gene number on the X chromosome (Gecz et al.,2009; Raymond et al.,2009; Tarpey et al.,2009). These 90 genes account only for a small proportion of disease each, and together they explain about half the cases of XLMR (Gecz et al.,2009). A recent large-scale effort sequenced the coding exons of 718 X chromosomal genes [of the 858 currently annotated in ENSEMBL (Flicek et al.,2011)] in over 200 families with XLMR (Tarpey et al.,2009). This unbiased screen, however, identified only nine additional genes associated with XLMR (included in the above 90), of which some, for example synaptophysin, underlie just 0.3% of XLMR, suggesting that more very rare variants with large effect must exist (Tarpey et al.,2009). Since this screen only examined coding exons, it did not detect noncoding changes, which will only be found through direct sequencing of regions with linkage to XLMR. A further source of genetic perturbations are copy number variants, which can be determined using sequence frequencies compared to control (Stankiewicz and Lupski,2010). In addition, it is difficult to ascertain whether missense mutations, rather than more straightforward protein truncations, play a role in disease without further biological insight. For example, Tarpey et al.(2009) found several missense mutations in CASK, and association with XLMR was made only because truncating mutations had been found previously to be lethal in males and to cause severe brain malformation in heterozygous females (Najm et al.,2008). CASK encodes a postsynaptic membrane protein, and in zebrafish is expressed throughout the brain (Thisse and Thisse,2004). Interestingly, truncating mutations in a number of X-chromosomal genes were also found in the healthy control population and so finding a deleterious mutation in a patient does not mean it is causative (Tarpey et al.,2009). Thus, it will be critical to test all possible candidates to identify those that are true causative mutations.

Of the 858 genes on the human X-chromosome about 600 have orthologs in teleost genomes (Flicek et al.,2011), dispersed in groups over several chromosomes (Kohn et al.,2004), and normally a direct correlation can be made. For example the orthologs of the human ARX (aristaless-related homeobox gene) are expressed in telencephalon and diencephalon in zebrafish and mouse (Miura et al.,1997), and mutation of human ARX causes XLMR (Kitamura et al.,2002; Stromme et al.,2002). Another example are the X chromosomal Neuroligin 3 and 4 genes (NLGN3 and NLGN4), which encode cell adhesion molecules thought to act in formation and maturation of synaptic connections that are located at the postsynaptic density (Ichtchenko et al.,1996; Irie et al.,1997). Mutations in NLGN3 and NLGN4 have been found in patients with XLMR and autism (Jamain et al.,2003; Laumonnier et al.,2004). The orthologs of NLGN3 and NLGN4 are expressed specifically both in the developing and adult zebrafish brain (Davey et al.,2010). The ortholog of the XLMR associated SOX3 gene regulates both neural fate and neuronal differentiation in zebrafish, and knockdown of sox3 leads to decreased brain size (Dee et al.,2008). The X-chromosomal SHANK3 encodes a scaffolding protein expressed in the postsynaptic density of excitatory synapses on dendritic spines, and mutations in this gene have been identified in patients with schizophrenia (Gauthier et al.,2010). Using zebrafish, these authors showed that knockdown of either of the two shank3 orthologs resulted in impaired swimming in response to touch, and that this impairment could be recued by coinjection of the wild type rat mRNA, but not a mutated version. A further example of a gene involved in XLMR encodes the histone demethylase PHF8, the zebrafish ortholog of which was found to directly regulate msx1/msxb and to be essential for neuronal survival in the zebrafish brain (Qi et al.,2010). These results suggest that zebrafish is a good model system for the examination of Mendelian loci involved in brain development and XLMR. However, since only about half of the XLMR cases are explained to date despite the sequencing of most of the X chromosomal exons, there is a good possibility that additional mutations are hiding in noncoding DNA, and it is noncoding mutations that we turn to next.

Genome-Wide Association Studies (GWAS)

GWAS are based on the “common disease, common variant” hypothesis (Reich and Lander,2001) and type from several hundred thousand to 1.5 million single nucleotide polymorphisms (SNPs) in the genomes of different individuals and aim to statistically associate individual SNPs with disease risk, comparing many (usually several thousand) patients versus normal controls (Hindorff et al.,2009). Hundreds of GWAS [there were, at the time of this writing, 810 articles and just under 4000 SNPs associated with disease in the NHGRI GWAS catalogue (Hindorff et al.,2011)] over the past 4 years have returned only a limited tally of associations, typically with small individual contributions. For example schizophrenia has an estimated heritability of 80%, according to meta-analysis of twin studies (Sullivan et al.,2003), yet a recent review estimated the combined results of genome-wide linkage studies and GWAS, which identified a handful of associated genes, at only a few percent (Girard et al., 2011). Because GWAS can only tag a genomic region (a so-called haplotype) and because most associated SNPs fall into noncoding sequence, a significant complication in the interpretation of GWAS data is to assign a tag SNP to a gene. Usually one or two genes flanking the associated SNPs are listed as candidates, or, if the SNP(s) fall into an intron, then the gene in which this intron resides is associated with the disease (McClellan and King,2010). As McClellan and King pointed out, “In the human genome, approximately 35% of base pairs lie in introns, and therefore approximately the same proportion of SNPs lie ‘in’ genes. In this context, ‘in’ is a tautology, not a proof of biological relevance.” (McClellan and King,2010).

In reality, it is very difficult to predict which gene is targeted by a given regulatory element, be it in an intron or intergenic. Further confounding factors are that the number of known and confirmed cis-regulatory elements is low, and that GWAS is dependent on human haplotype structure, meaning that typically several SNPs within the same haplotype block are associated with a given trait/disease, making it impossible, without considerable experimentation, to predict whether any of them or an as yet undiscovered SNP constitutes the variant underlying the trait. There are, however, a few hundred regions in vertebrate genomes where one can at least predict whether a genomic region falls within the regulatory domain of a specific gene. This is based on comparative genomics between mammalian and teleost genomes, and concerns regions that have been largely conserved in terms of gene content and -order and that typically contain higher than average numbers of highly conserved noncoding elements (Kikuta et al.,2007a, b). A salient point here is that the human-teleost conserved synteny is used as an indicator of the extent of a regulatory region and not necessarily as a source of potential regulatory elements, the majority of which are not conserved over these extreme vertebrate evolutionary distances.

“Off-target” Disease Mutations and Vertebrate Gene Regulation

It had been noted in a number of cases that mutations in an intron of a gene neighboring the disease gene can have a similar phenotype as a heterozygous mutation in the coding region of the disease gene itself. For example, mutations in an intron in (rather than “of”) ELP4, a gene neighboring PAX6 (encoding a transcription factor regulating eye and forebrain development, mutations in which cause the dominant eye defect aniridia) can cause aniridia in the absence of any coding mutations in PAX6 itself [reviewed by (Kleinjan and van Heyningen,2005)]. It was shown that introns in Elp4/elp4 contain enhancers that target Pax6/pax6b in mouse and zebrafish (Kleinjan and van Heyningen,2005; Navratilova et al.,2009). Navratilova et al. showed, in addition, that introns in another gene in the region, IMMP1L, also contain PAX6 enhancers and therefore that these introns should be considered as being within the PAX6/Pax6/pax6 regulatory domain in all sequenced vertebrate genomes (Navratilova et al.,2009) [see Fig. 1(A)]. Another often cited example is a form of preaxial polydactyly, caused by point mutations in an enhancer that drives expression of sonic hedgehog (SHH) in the zone of polarizing activity of the limb bud (Lettice et al.,2002). These mutations drive ectopic expression of SHH, and lead to mirror image duplications in digit formation (Lettice et al.,2008). The identification of this enhancer was complicated by the fact that it is located in an intron in the unrelated LMBR1 gene, about 1 Mb away from the SHH promoter (Lettice et al.,2002) [see Fig. 1(B)]. Many developmental regulatory genes, of which PAX6 and SHH are examples, have extended regulatory regions around them, including in introns in other genes, and these regions were termed genomic regulatory blocks (GRBs) (Engstrom et al.,2007; Kikuta et al.,2007a, b; Engstrom et al.,2008; Akalin et al.,2009; Navratilova et al.,2009, 2010). In GRBs, it is possible to predict with some confidence which gene is likely affected by noncoding mutations (see Fig. 1, for examples of notable GRBs). A recent example came from GWAS for type2 diabetes, where the CDKAL1 and FTO genes had been associated with the disease because the tag SNPs reside in introns in these genes (Frayling et al.,2007; Steinthorsdottir et al.,2007). However, CDKAL1 lies close to SOX4, and FTO close to IRX3 [see Fig. 1(C, D)], both encoding transcriptional regulators active in the developing pancreas (Wilson et al.,2005; Ragvin et al.,2010), and it was subsequently shown that the introns in CDKAL1 and FTO contain enhancers regulating SOX4 and IRX3, respectively (Ragvin et al.,2010). There are many more examples where such annotations have been made based simply on the finding of an associated SNP in an intron. Because such associations are almost as difficult to disprove as they are to prove, we only point out one below where the (likely) correct association is straightforward.

Figure 1.

Figure 1.

Examples of five genomic regulatory blocks (GRBs) associated with human disease, as seen using the Ancora Genome Browser (Engstrom et al., 2008). The regions are comparative views of human versus mouse genomes that also exhibit conserved synteny between all sequenced vertebrate genomes. In each case, the gene targeted by multiple highly conserved noncoding elements (HCNEs) is underlined by a red block. For clarity, only the gene bounds are shown, not the intron exon structures. HCNE density across the region is shown at two different thresholds, and individual HCNEs are shown below as colored blocks. CpG islands are shown below the gene bounds, and are characteristically enriched across the target gene regions (Akalin et al., 2009). A: A 500 kb window of the human PAX6 region. PAX6 mutations are associated with the dominant disorder aniridia, as are intronic deletions in ELP4 that remove critical PAX6 enhancers (Kleinjan and van Heyningen, 2005). The Ancora browser shows multiple HCNEs within the gene bounds of the ELP4 and IMMP1L genes. B: A 1.2 Mb window encompassing the human SHH gene, with HCNEs within the gene bound of LMBR1. Intronic mutations in a specific HCNE within a LMBR1 intron cause preaxial polydactyly by ectopic activation of SHH in the limb bud (Lettice et al., 2002). C: A 1.5 Mb window including the human SOX4 gene. Many of the HCNEs in the region are within the gene bound of CDKAL1, and intronic SNPs of this gene have been associated with type 2 diabetes (Steinthorsdottir et al., 2007), while point mutations in Sox4 in the mouse have been shown to cause a defect in insulin secretion (Goldsworthy et al., 2008), and an enhancer from the T2D associated intronic region in CDKAL1 drives a SOX4-like pattern (Ragvin et al., 2010). D: A 1 Mb window of the IRX3 region, where mutiple HCNEs are seen within the FTO gene bound. Note how the highest density of HCNEs is found towards the 3′ end of FTO. SNPs in intron 1 in FTO have been associated with T2D and obesity (Frayling et al., 2007), and enhancers from this region in which the SNPs occur were shown to drive pancreatic expression in transgenic zebrafish (Ragvin et al., 2010). E: A 3 Mb window of the GRB of MEIS2 encoding, a transcription factor involved in lens development through regulation of PAX6 (Zhang et al., 2002). Intergenic SNPs near GJA9 and ACTC1 have been associated with myopia through GWAS (Solouki et al., 2010). Conserved synteny between this region and MEIS2 suggest that the associated region identified by GWAS is involved in regulation of MEIS2 in the lens.

A GWAS Signal Associated With Myopia

A recent report on a GWAS for risk factors for myopia identified 14 variants on 15q14 in a 9.2 Kb region (Solouki et al.,2010) [Fig. 1(E)]. This regions lies within a distance of 50 Kb to the GJD2 (a.k.a GJA9) gene, which encodes a gap junction protein, and 100 Kb from the ACTC1 gene, encoding a cardiac muscle actin. The author's report that the region containing the associated SNPs is near conserved noncoding elements, which they hypothesize may influence transcription of these genes, leading to refractive errors of the lens. However, based on conserved synteny within this region between human and zebrafish, the conserved elements in question likely regulate MEIS2, encoding a transcription factor regulating lens development in the PAX6 pathway (Zhang et al.,2002). Human PAX6 mutations have also been linked to myopia (Hewitt et al.,2007). This connection was likely overlooked because of the large distance (∼ 2 Mb) between the associated region and MEIS2. In the zebrafish, the distance of the GJD2 orthologue (cx35) from meis2.1 is just over 100 Kb. Further recent evidence for MEIS2 in lens development comes from experiments showing that the microRNA mir-204 targets Meis2 and is required for lens development (Conte et al.,2010). As this GWAS example shows, associated SNPs are often anchored to the closest gene(s) at the expense of better candidates further away, for no reason other than that regulatory elements are believed to be close to their target genes. It thus becomes clear that, to understand GWAS data, one needs to understand vertebrate gene regulation, and the zebrafish, because of the ease of transgenesis and its vertebrate anatomy, is a system in which human disease-associated regions can be interrogated at a medium throughput.

Enhancers Act in a Redundant Fashion

A number of studies that tested putative enhancer sequences in the mouse and zebrafish have found that, frequently, more than one enhancer of a given gene directs reporter expression to any one specific tissue in zebrafish (Navratilova et al.,2009, 2010) as well as in the mouse [e.g., (Werner et al.,2007)]. For example, fibroblast growth factor 8 (fgf8) is expressed in the apical ectodermal ridge of the zebrafish fin bud, and analysis of cis-regulatory elements from the fgf8a locus in zebrafish showed that there are as many as eight different enhancers that direct reporter expression to this tissue (Komisarczuk et al.,2009). Similar redundancy was also found in Drosophila, where different enhancers active during early embryonic development showed almost complete overlap in their activity (Hong et al.,2008). Recently two independent studies showed that, while one of two overlapping enhancers can be deleted in the fruit fly without apparent effect under normal laboratory conditions, both were needed for accurate embryonic development at elevated temperatures (Frankel et al.,2010; Perry et al., 2010) thus providing the organism with robustness to develop under adverse or suboptimal conditions. Recently Bickel et al. (2011) demonstrated in Drosophila that several cis regulatory polymorphisms, in this case in a promoter, in a cis-regulatory element, and in a polycomb-binding element, could combine to generate a quantitative trait locus affecting pigmentation. Such overlapping activity of enhancers and cumulative effect of cis-regulatory polymorphisms may explain why even ultraconserved elements with experimentally demonstrated enhancer activity can be deleted in the mouse without phenotypic effect under laboratory conditions (Ahituv et al.,2007) even though these elements are evidently under evolutionary pressure (Bejerano et al.,2004; McLean and Bejerano,2008). These findings suggest that multiple cis-regulatory elements directing similar expression patterns may provide a buffer for differing environmental conditions. Hence, mutations in this type of enhancers should contribute to polygenic inheritance depending on environmental conditions, rather than to Mendelian inheritance. It is also possible that many noncoding regulatory mutations to date have not been identified simply because often only coding sequence is searched for mutations. For either or both of these reasons, Mendelian effects of mutations in cis-regulatory elements are exceedingly rare, the most prominent example to date perhaps being the Shh limb enhancer located within an intron of the Lmbr1 gene (Amano et al.,2009). This enhancer is, as far as is known, nonredundant, and thus perhaps more vulnerable to mutation or deletion (Sagai et al.,2005).

Many Enhancers do not Display Evolutionary Conservation

The testing of cis-regulatory elements has used the classic promoter approach, in which a length of sequence, often several kb upstream of the transcription start site, is fused to a reporter gene (LacZ, GFP, etc.) to generate reporter lines, for example, (Long et al.,1997). In some cases, this approach does not work because regulatory sequences are located downstream of the target gene [e.g., (Higashijima et al.,2000)]. With the advent of multiple sequenced genomes, it became possible to identify conserved noncoding sequences (CNEs) at various evolutionary depths (Sandelin et al.,2004; Woolfe et al.,2005), and thus a more targeted approach became feasible, where CNEs could be cloned upstream or downstream of a basal promoter driving a reporter gene and were used to generate transgenic fish or mice. For example, Uemura et al. (2005) revisited two 15 kb regions downstream of isl1 that they had previously shown to direct GFP expression to motor neurons and sensory neurons, respectively (Higashijima et al.,2000) and identified enhancers conserved among vertebrates that were sufficient to drive reporter expression in cranial and spinal motor neurons in mice and zebrafish. However, when testing a zebrafish enhancer of isl1 and its human orthologous sequence in mice, Uemura et al. (2005) observed that only the zebrafish enhancer was able to drive reporter expression in sensory neurons. This was found to be due to a nonconserved sequence present in the zebrafish enhancer (Uemura et al.,2005). There are now many examples of tissue-specific enhancers that are not or only weakly conserved between species as close as human and mouse (Blow et al.,2010), and the next stage of enhancer identification is afforded by chromatin immunoprecipitation followed by next generation sequencing (ChIP-SEQ), [e.g., (Visel et al.,2009; Soler et al.,2010)]. Experimental testing of all human regulatory elements identified through diverse methods will be a daunting task even using a medium throughput system such as zebrafish, and will, at least in the foreseeable future, have to be guided by the results from whole genome sequencing in human patient cohorts.

Using Genomic Information to Generate Transgenic Zebrafish

Transgenic zebrafish expressing reporter genes or Gal4 have emerged as very powerful tools because of the possibility to genetically mark and modify any desired cell type in the context of a live behaving animal. Importantly, while regulatory elements tend to be similar within the vertebrates, no similarity is found with nonchordate invertebrates, such as Drosophila (Woolfe et al.,2005; Engstrom et al.,2007). As a result of these pan-vertebrate similarities, human DNA regions that have been associated with disease can be tested in the zebrafish with the purpose of either expressing a human cDNA in specific cell types, or to find out which gene is regulated by a given genomic region, and where expression is directed by it. If one intends to simply make a transgene that recapitulates the expression pattern of a given gene then a first step is to use a few kilobases of the gene's promoter, which has worked in a few applications; for example, the complete expression pattern of hypocretin was recapitulated by a 1.5 kb promoter fragment (Appelbaum et al.,2009). However, very often this approach does not yield the desired result and only a partial pattern is recovered, as was shown for a promoter fragment of pro-opiomelanocortin (Liu et al.,2003). Such cases can be circumvented through the use of BACs, which often contain enough cis-regulatory sequence to generate a complete or near complete pattern (Yang et al.,2006) and can be conveniently inserted into the germline through Tol2 transgenesis (Suster et al.,2009b). The use of GFP-recombineered BACs is an invaluable resource for neuroscience in the mouse (Gong et al.,2003), and one can expect large numbers of BAC transgenic zebrafish lines in the near future. However, as the examples of genomic loci in Figure 1 can attest, not all loci will be amenable to this approach, because they are much larger (up to several Mb) than the cargo capacity of a BAC (about 200 kb). In these cases, one approach is to use overlapping BACs, as was shown for the Shh locus in the mouse (Jeong et al.,2006), or use BACs from the much more compact Fugu genome, as Fugu enhancers have also been shown to direct correct expression patterns in zebrafish (Suster et al.,2009a). Alternatively, one can use conserved synteny between teleost and mammalian genomes to narrow down the likely regulatory domain of a gene in the Ancora genome browser (Engstrom et al.,2008), and perform a systematic search for conserved noncoding elements or sequences identified through chromatin precipitation, such as p300 binding sites (Visel et al.,2009) and use these to generate individual transgenic lines (Komisarczuk et al.,2009; Navratilova et al.,2009, 2010; Punnamoottil et al.,2010). A further possibility is to use GWAS results to narrow the search to a block of linkage disequilibrium and then test individual sequences in this block for their cis-regulatory activity in transgenic lines. This also allows identification of the cell type that is affected in a given disease, for example testing of multiple sequences in a 50 kb block associated with obesity in the first intron in the FTO gene [which is part of the regulatory domain of IRX3; see also Fig. 1(D)] resulted in transgenic zebrafish with expression in the pancreatic region (Ragvin et al.,2010). Further experiments then revealed that knockdown of irx3a in zebrafish resulted in reduction of the number of insulin-producing beta cells, and an increase in epsilon cells expressing the hunger factor ghrelin (Ragvin et al.,2010), suggesting that IRX3 affects body mass through the regulation of metabolic peptide hormones. Likewise, one would expect to find eye-specific enhancers regulating MEIS2 to reside within the region associated with myopia near GJA9 and ACTC1 [Fig. 1(E)].

CONCLUSIONS

Many recent advances have made the zebrafish the vertebrate model of choice for the analysis of mutations that affect vertebrate nervous system development. Furthermore, since zebrafish develop into a free-swimming larva in 5 days, functional assays can also be performed at high throughput. The ease of transgenesis and the large number of transgenic lines in existence will likely translate into more studies in which specific cell types are interrogated for their role in the development of not only neurodegenerative disease, but also for psychiatric illnesses, where the understanding of basic mechanisms and the cell types affected is still rudimentary. The challenge that lies ahead will be to model aspects of specific neurological or psychiatric disorders in mouse or zebrafish to identify signaling pathways that could, in the not so distant future, result in the identification of drug targets, or, in the case of zebrafish, models that can be used for high throughput small molecule screens (see Rihel and Schier, 2012).

Acknowledgements

We thank Dr. Hugues Roest Crollius for advice on the genomics of the X chromosome.

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Article Information

DOI

10.1002/dneu.20888
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Keywords

  • transgenes;
  • cis-regulation;
  • human enhancers;
  • GWAS;
  • regulatory mutations

Publication History

  • Issue online: 10 February 2012
  • Version of record online: 10 February 2012
  • Accepted manuscript online: 4 April 2011
  • Manuscript Accepted: 26 March 2011
  • Manuscript Received: 5 March 2011

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