Experimental Models to Study Autism Spectrum Disorders: hiPSCs, Rodents and Zebrafish

genes G C A T T A C G G C A T Review Experimental Models to Study Autism Spectrum Disorders: hiPSCs, Rodents and Zebrafish Alba Pensado-López 1,2,†, Sara Veiga-Rúa1,2,†,Ángel Carracedo 2,3, Catarina Allegue 2,* and Laura Sánchez 1,* 1Department of Zoology, Genetics and Physical Anthropology, Universidade de Santiago de Compostela, Campus de Lugo, 27002 Lugo, Spain; [email protected] (A.P.-L.); [email protected] (S.V.-R.) 2Genomic Medicine Group, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidade de Santiago de Compostela, 15706 Santiago de Compostela, Spain; [email protected] 3Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), CIMUS, Universidade de Santiago de Compostela, 15706 Santiago de Compostela, Spain *Correspondence: [email protected] (C.A.); [email protected] (L.S.) †These authors contributed equally to this work. Received: 9 October 2020; Accepted: 18 November 2020; Published: 20 November 2020   Abstract: Autism Spectrum Disorders (ASD) affect around 1.5% of the global population, which manifest alterations in communication and socialization, as well as repetitive behaviors or restricted interests. ASD is a complex disorder with known environmental and genetic contributors; however, ASD etiology is far from being clear. In the past decades, many efforts have been put into developing new models to study ASD, both in vitro and in vivo . These models have a lot of potential to help to validate some of the previously associated risk factors to the development of the disorder, and to test new potential therapies that help to alleviate ASD symptoms. The present review is focused on the recent advances towards the generation of models for the study of ASD, which would be a useful tool to decipher the bases of the disorder, as well as to conduct drug screenings that hopefully lead to the identification of useful compounds to help patients deal with the symptoms of ASD. Keywords: autism spectrum disorders (ASD); animal models; cellular models; genome editing; human induced pluripotent stem cells (hiPSCs); neurodevelopmental disorders (NDDs); rodents; zebrafish 1. Introduction 1.1. Definition and Epidemiology of Autism Spectrum Disorders Autism Spectrum Disorders (ASD)-affected individuals are characterized by the presence of social and communication impairments and the lack of common skills in developing, maintaining, and understanding relationships. In addition to these symptoms, patients might also develop stereotyped or repetitive patterns of behavior, interests and/or activities. According to the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), the ASD category includes the following neurodevelopmental disorders (NDDs): early infantile autism, childhood autism, Kanner’s autism, high functioning autism, atypical autism, pervasive developmental disorder not otherwise specified (PDD-NOS), childhood disintegrative disorder, and Asperger’s disorder [1]. The prevalence of ASD is estimated to be around 1.5% [ 2 – 4 ], although these data vary depending on the year and the country dataset consulted (Figure 1). Differences among datasets could be associated with real differences on ASD prevalence, but also with errors due to diagnostic difficulties or lack of trustworthy data [5]. Genes 2020,11, 1376; doi:10.3390/genes11111376 www.mdpi.com/journal/genes Genes 2020,11, 1376 2 of 45 Genes 2020, 11, x FOR PEER REVIEW 2 of 45 The prevalence of ASD is estimated to be around 1.5% [2–4], although these data vary depending on the year and the country dataset consulted (Figure 1). Differences among datasets could be associated with real differences on ASD prevalence, but also with errors due to diagnostic difficulties or lack of trustworthy data [5]. Figure 1. Map of the prevalence of Autism Spectrum Disorders (ASD) around the world in 2017. Light green: prevalence between 0–0.4%; blue: prevalence between 0.4–0.6%; green: prevalence between 0.6–0.8%; dark green: prevalence between 0.8–1%. Countries from which no data are available are plotted in grey. The figure was elaborated using R software (R Core Team, Vienna, Austria) to represent open access data which have been previously standardized to age and sex [2,4,6]. 1.2. Aetiology of Autism Spectrum Disorders Depending on whether the origin of ASD is known or not, the disorder can be classified into two subgroups: syndromic and non-syndromic ASD. Syndromic ASD includes those cases with a well-characterized etiology, whereas non-syndromic ASD cases have a less defined etiology, with multiple factors contributing to the development of the disorder [7]. ASD can be linked to prenatal, perinatal and postnatal risk factors, which can be either genetic or environmental [8]. Several environmental factors have been found strongly correlated with ASD development, such as advanced parental age, pregnancy and birth complications, vitamin D deficiency and heavy metal exposition [8–10]. Regarding genetics, their relevance in ASD risk development has been known for over 50 years, mainly due to the results observed in twin studies. The first twin studies indicated that ASD concordance could be around ~90% in monozygotic twins, in comparison with a 30% concordance observed in dizygotic twins [11–13]. However, recent data seem to indicate that ASD concordance in monozygotic twins might be lower (~50%) [10]. Despite the obvious challenges associated with the identification of ASD causes, many susceptibility genes have been identified by genetic analysis, including exome sequencing and genome-wide association studies (GWAS). ASD-associated genes are frequently involved in the regulation of neural and synaptic development and its alteration can lead to dysfunctions in brain areas that regulate high cognitive functions [13–16]. In addition, molecular alterations in excitatory cortical neurons, microglia and cortico-cortical projection neurons have also been associated with ASD severity [17]. Both common and rare genetic variants have been associated with ASD development. Available data suggest that de novo mutations in coding regions are among the most frequent variants Figure 1. Map of the prevalence of Autism Spectrum Disorders (ASD) around the world in 2017. Light green: prevalence between 0–0.4%; blue: prevalence between 0.4–0.6%; green: prevalence between 0.6–0.8%; dark green: prevalence between 0.8–1%. Countries from which no data are available are plotted in grey. The figure was elaborated using R software (R Core Team, Vienna, Austria) to represent open access data which have been previously standardized to age and sex [2,4,6]. 1.2. Aetiology of Autism Spectrum Disorders Depending on whether the origin of ASD is known or not, the disorder can be classified into two subgroups: syndromic and non-syndromic ASD. Syndromic ASD includes those cases with a well-characterized etiology, whereas non-syndromic ASD cases have a less defined etiology, with multiple factors contributing to the development of the disorder [7]. ASD can be linked to prenatal, perinatal and postnatal risk factors, which can be either genetic or environmental [ 8 ]. Several environmental factors have been found strongly correlated with ASD development, such as advanced parental age, pregnancy and birth complications, vitamin D deficiency and heavy metal exposition [8–10]. Regarding genetics, their relevance in ASD risk development has been known for over 50 years, mainly due to the results observed in twin studies. The first twin studies indicated that ASD concordance could be around ~90% in monozygotic twins, in comparison with a 30% concordance observed in dizygotic twins [ 11 – 13 ]. However, recent data seem to indicate that ASD concordance in monozygotic twins might be lower (~50%) [10]. Despite the obvious challenges associated with the identification of ASD causes, many susceptibility genes have been identified by genetic analysis, including exome sequencing and genome-wide association studies (GWAS). ASD-associated genes are frequently involved in the regulation of neural and synaptic development and its alteration can lead to dysfunctions in brain areas that regulate high cognitive functions [ 13 – 16 ]. In addition, molecular alterations in excitatory cortical neurons, microglia and cortico-cortical projection neurons have also been associated with ASD severity [17]. Both common and rare genetic variants have been associated with ASD development. Available data suggest that de novo mutations in coding regions are among the most frequent variants associated with ASD. However, other genetic alterations such as copy number variations (CNVs) and chromosomal alterations have also been associated with the development of the disorder [7,13,18,19]. One of the most complete recompilation of ASD-associated genes is the SFARI Gene Database [ 20 , 21 ]. In the 2020 database release, genes are classified according to a gene score (1, 2 or 3) that takes into account the amount of information supporting the implication of a certain gene in ASD development. Genes with score 1 are high confidence ASD-associated genes with a minimum of three de novo disrupting mutations linked in patients to the development of the disorder. Genes with score 2 are Genes 2020,11, 1376 3 of 45 strong candidates with two de novo disrupting mutations associated with ASD development. Finally, genes with score 3 are those with one reported de novo disrupting mutation linked to ASD, but the results have not been replicated yet. A total of 913 genes have been registered into the SFARI Gene Database (https://gene.sfari.org/, latest release 2020) as ASD-associated genes with their corresponding score following the previously mentioned criteria (Figure 2a) [ 20 , 21 ]. These genes are not evenly distributed throughout the genome, for instance, high confidence ASD-associated genes (gene score 1) are particularly abundant in the chromosome X (Figure 2b,c). Some authors have linked this observation with the male-to-female ASD ratio which is about 4 to 1 [11,22]. Genes 2020, 11, x FOR PEER REVIEW 3 of 45 associated with ASD. However, other genetic alterations such as copy number variations (CNVs) and chromosomal alterations have also been associated with the development of the disorder [7,13,18,19]. One of the most complete recompilation of ASD-associated genes is the SFARI Gene Database [20,21]. In the 2020 database release, genes are classified according to a gene score (1, 2 or 3) that takes into account the amount of information supporting the implication of a certain gene in ASD development. Genes with score 1 are high confidence ASD-associated genes with a minimum of three de novo disrupting mutations linked in patients to the development of the disorder. Genes with score 2 are strong candidates with two de novo disrupting mutations associated with ASD development. Finally, genes with score 3 are those with one reported de novo disrupting mutation linked to ASD, but the results have not been replicated yet. A total of 913 genes have been registered into the SFARI Gene Database (https://gene.sfari.org/, latest release 2020) as ASD-associated genes with their corresponding score following the previously mentioned criteria (Figure 2a) [20,21]. These genes are not evenly distributed throughout the genome, for instance, high confidence ASD-associated genes (gene score 1) are particularly abundant in the chromosome X (Figure 2b,c). Some authors have linked this observation with the male-to-female ASD ratio which is about 4 to 1 [11,22]. (a) (b) (c) Figure 2. Human ASD-associated genes according to the SFARI Gene Database (2020). Gene score 1: high confidence genes with a minimum of three de novo likely gene disrupting mutations associated to ASD. Gene score 2: strong candidate genes with two de novo gene-disrupting mutations associated to ASD. Gene score 3: suggestive evidence of the association of the gene with ASD development, due to one reported de novo likely gene-disrupting mutation. ( a ) Classification of the 913 ASD-associated genes in the SFARI Gene Database according to the gene score and their presence in syndromic or non-syndromic ASD patients (NS =non-specified); ( b ) ASD-associated genes distribution in the human genome; ( c ) Percentage of ASD-associated genes identified on each human chromosome. The figure was elaborated using open-access data from SFARI Gene Database (obtained in January 2020) and R software [6,20,21]. Genes 2020,11, 1376 4 of 45 1.3. Diagnostic of Autism Spectrum Disorders Nowadays, ASD diagnosis is based on standard clinical criteria (Table 1) that evaluate the symptoms and their severity in each case [ 1 ]. However, ASD symptoms can vary a lot between individuals. In the most severe cases, an accurate diagnosis is usually made at an early age (1–2% of the population), but milder phenotypes can be harder to identify for clinicians, as different NDDs can co-occur and symptoms might be very similar [1,7,23]. Table 1. Standard clinical criteria for the identification and diagnosis of ASD in the population according to the DSM-5 [1]. Clinical Diagnosis Criteria for ASD Deficits in social communication and interaction Restricted and repetitive patterns of behavior, interests, or activities Symptoms present during early development Presence of impairments in important areas of an individual’s functioning Symptoms are not better explained by other mental disorder ASD: Autism Spectrum Disorders; DSM-5: the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders. The current approach to diagnose and treat ASD patients is far from optimal. To improve this situation, it is essential to broaden the current knowledge of ASD bases, which could give us new insights to improve the diagnosis and treatment of patients. 1.4. Treatment of Autism Spectrum Disorders Treatment for ASD patients is essentially focused on ameliorating the symptoms of the disorder to reduce the impact it has on the daily activities of the affected individuals. To this end, it is frequent that patients receive a combination of therapeutic approaches, including behavioral therapy and/or medication (see Table 2for a list of ASD-related therapies). There is no medication that can completely alleviate ASD symptoms or cure the disorder. However, some compounds—such as α 2-adrenergic agonists and olanzapine—have been approved to ameliorate some symptoms of the disorder, but their efficiency is limited [24,25]. Genes 2020,11, 1376 5 of 45 Table 2. Therapeutic options available to treat ASD symptoms. Available therapeutic approaches can be classified into three groups: psychosocial therapies, pharmacology and complementary alternative medicine. In the table below, it can be found a list of the available therapies divided into these three categories, including a brief explanation on which ASD symptoms can be ameliorated by their use, as well as their previously reported side effects [24,25]. Type of Therapy Therapy Procedure Areas with Improvement Side Effects Psychosocial therapies Applied behavior analysis (ABA) Repetition of learning trials (positive reinforcement) Intellectual functioning, language, daily living skills and socialization Long-term and costly therapy, need patient’s cooperation and motivation Pivotal Response Treatment (PRT) Targets specific skills and motivations Improve communication skills and less disruptive behaviors compared to ABA No significant side effects Parent-mediated early interventions Interventions that can be applied at home by parents Socialization and communication No significant side effects Social skills interventions Interventions to improve social skills Emotional regulation, communication and socialization No significant side effects Pharmacology Risperidone Atypical Antipsychotics Irritability, socialization and communication Weight gain, increased appetite and somnolence Aripiprazole Atypical Antipsychotics Irritability Weight gain and somnolence Olanzapine Atypical Antipsychotics Irritability Weight gain Ziprasidone Atypical Antipsychotics Irritability Cardiovascular alterations and somnolence Paliperidone Atypical Antipsychotics Irritability Weight gain and extrapyramidal symptoms Haloperidol Typical Antipsychotics Hyperactivity, stereotypical behaviors and learning on discrimination tasks Somnolence, irritability and dystonic reactions Antidepressants: venlafaxine Typical Antipsychotics Repetitive behaviors, socialization and communication Hyperactivity, inattention, nausea and polyuria Antidepressants: clomipramine Typical Antipsychotics Stereotypical behavior and anger management No significant side effects Divalproex sodium Mood stabilizers Irritability and repetitive behaviors No significant side effects Methylphenidate Stimulants/atomoxetine/α-2 agonists Hyperactivity Appetite decrease, insomnia, irritability and emotional outbursts Atomoxetine Stimulants/atomoxetine/α-2 agonists Hyperactivity and impulsivity No significant side effects α-2 agonists: clonidine and guanfacine Stimulants/atomoxetine/α-2 agonists Hyperactivity Somnolence Naltrexone Other medications Hyperactivity and impulsivity No significant side effects Complementary alternative medicine Melatonin Sleep disturbances No significant side effects Genes 2020,11, 1376 6 of 45 2. Genome Editing Systems, a Promising Tool for Modeling Human Disorders As mentioned before, both genetic and environmental risk factors contribute to ASD development. Due to this complexity, deciphering the individual impact of each risk factor on the development of ASD was a difficult task for researchers for a long time, and it is still a challenge. This scenario recently changed due to the development of improved genetic edition systems which allow simplifying the study of the function of selected genes and their relationship with disease-related phenotypes. To date, there are three main types of genetic editing systems available: Zinc Finger Nucleases (ZFNs), Transcription Activator-Like Effector Nucleases (TALENs) and CRISPR/Cas (Clustered Regularly Interspaced Short Palindromic Repeats). The first editing tools available were ZFNs, in 1996 [ 26 ] and TALENs, in 2010 [ 27 ], both based on the recognition between a DNA sequence and a protein. A new editing system based on DNA-RNA recognition was developed in 2013, which received the name of CRISPR/Cas [ 28 ]. This technology supposed a revolution in the field of genome editing, which is now accessible to almost every laboratory worldwide. The increased accessibility of CRISPR/Cas system makes it a powerful tool in many research areas, from agriculture to ecological vector control or biomedicine. To the purpose of the present review, it is especially interesting to mention the broad applications of CRISPR/Cas system in biomedical research, ranging from targeted genome editing to the regulation of gene expression or even the labeling of endogenous sequences. This technology has a great potential to generate pre-clinical models of many human disorders, both in vitro and in vivo , that could help to understand the molecular pathways that lead to the development of a certain pathology [29–31]. Fundamentals of Genomic Editing All three systems (Figure 3) create specific breaks into the DNA, which in turn trigger the cellular DNA repair mechanisms. Eukaryotic cells have two main routes of DNA repair: non-homologous end joining (NHEJ) and homology-directed repair (HDR). NHEJ pathway is faster, but also prone to error, generating insertions or deletions (indels) due to its activity. NHEJ often alters gene’s reading frame or inserts stop codons at unusual places, generating truncated proteins that are unable to properly function. HDR pathway is more precise as it can correct alterations using a donor sequence as a template. Taking advantage of the HDR system allows the introduction of specific modifications in the genome, which can be as small as one single nucleotide [32]. Genes 2020, 11, x FOR PEER REVIEW 7 of 45 2. Genome Editing Systems, a Promising Tool for Modeling Human Disorders As mentioned before, both genetic and environmental risk factors contribute to ASD development. Due to this complexity, deciphering the individual impact of each risk factor on the development of ASD was a difficult task for researchers for a long time, and it is still a challenge. This scenario recently changed due to the development of improved genetic edition systems which allow simplifying the study of the function of selected genes and their relationship with disease-related phenotypes. To date, there are three main types of genetic editing systems available: Zinc Finger Nucleases (ZFNs), Transcription Activator-Like Effector Nucleases (TALENs) and CRISPR/Cas (Clustered Regularly Interspaced Short Palindromic Repeats). The first editing tools available were ZFNs, in 1996 [26] and TALENs, in 2010 [27], both based on the recognition between a DNA sequence and a protein. A new editing system based on DNA-RNA recognition was developed in 2013, which received the name of CRISPR/Cas [28]. This technology supposed a revolution in the field of genome editing, which is now accessible to almost every laboratory worldwide. The increased accessibility of CRISPR/Cas system makes it a powerful tool in many research areas, from agriculture to ecological vector control or biomedicine. To the purpose of the present review, it is especially interesting to mention the broad applications of CRISPR/Cas system in biomedical research, ranging from targeted genome editing to the regulation of gene expression or even the labeling of endogenous sequences. This technology has a great potential to generate pre-clinical models of many human disorders, both in vitro and in vivo, that could help to understand the molecular pathways that lead to the development of a certain pathology [29–31]. Fundamentals of Genomic Editing All three systems (Figure 3) create specific breaks into the DNA, which in turn trigger the cellular DNA repair mechanisms. Eukaryotic cells have two main routes of DNA repair: non-homologous end joining (NHEJ) and homology-directed repair (HDR). NHEJ pathway is faster, but also prone to error, generating insertions or deletions (indels) due to its activity. NHEJ often alters gene’s reading frame or inserts stop codons at unusual places, generating truncated proteins that are unable to properly function. HDR pathway is more precise as it can correct alterations using a donor sequence as a template. Taking advantage of the HDR system allows the introduction of specific modifications in the genome, which can be as small as one single nucleotide [32]. (a) (b) (c) Figure 3. The main genomic editing systems available at the moment. (a) Zinc Finger Nucleases—ZFNs: two zinc finger nucleases act as a dimer, each one harboring a DNA binding domain and a DNA cleaving domain FokI; (b) Transcription Activator-Like Effector Nucleases—TALENs: TALENs act as a dimer, each one harboring a DNA binding domain (TAL effectors) and a DNA cleaving domain FokI; (c) CRISPR/Cas9: a sgRNA binds to the DNA and to the Cas9 endonuclease, facilitating the creation of double-strand breaks (DSBs) in the DNA. The image is original and was created by the authors of the present review. ZFNs are a type of DNA-binding proteins that can be used to create double-strand breaks (DSBs) at desired positions in the genome. To function, this edition system requires two zinc finger Figure 3. The main genomic editing systems available at the moment. ( a ) Zinc Finger Nucleases—ZFNs: two zinc finger nucleases act as a dimer, each one harboring a DNA binding domain and a DNA cleaving domain FokI; ( b ) Transcription Activator-Like Effector Nucleases—TALENs: TALENs act as a dimer, each one harboring a DNA binding domain (TAL effectors) and a DNA cleaving domain FokI; ( c ) CRISPR/Cas9: a sgRNA binds to the DNA and to the Cas9 endonuclease, facilitating the creation of double-strand breaks (DSBs) in the DNA. The image is original and was created by the authors of the present review. ZFNs are a type of DNA-binding proteins that can be used to create double-strand breaks (DSBs) at desired positions in the genome. To function, this edition system requires two zinc finger nucleases, Genes 2020,11, 1376 7 of 45 each one harboring two essential domains: a DNA binding domain and a DNA cleaving domain. The DNA binding domain is composed of protein modules, each one able to recognize a specific nucleotide triplet. The second essential domain of a ZFN is the sequence-independent cleaving domain, which is derived from the endonuclease FokI (Figure 3a). The combination of both domains allows the ZFN to act as a site-specific nuclease [ 26 , 33 ]. ZFNs are an efficient editing system that can be applied to multiple experimental models, including cell cultures and animal models [ 34 – 37 ]. However, despite their efficiency, the use of ZFNs has not been widespread due to the difficulty of the experimental design and the required validation. TALENs emerged in 2010 as an alternative to ZFNs. TALENs function is based on the combination of FokI cleavage activity and transcription activator-like effectors (TALEs) (Figure 3b) which target individual base pairs. In comparison with ZFNs, TALENs are easier to synthesize, but the required protein design is still challenging [27,38]. As mentioned above, the most recently developed genomic editing system was CRISPR/Cas9 which is based on bacterial immune systems CRISPR type II. In comparison with ZFN and TALENs, CRISPR/Cas9 stands out for its relative simplicity, as it only needs two elements to function. The first one is the Cas9 nuclease, which contains two endonuclease domains, HNH and RuvC-like, which create DSBs in the DNA. The other essential element of this system is the single guide (sgRNA), which is composed of two regions: trans-activating CRISPR RNA (tracrRNA) and CRISPR RNA (crRNA). The tracrRNA, allows the binding between the Cas9 nuclease and the guide itself, whereas the crRNA is fundamental for the recognition of a specific target site in the genome (Figure 3c) [28–31]. The original model has been modified over the years, introducing modifications and improvements in its functioning. Nowadays, Cas9 can be substituted by other enzymes, expanding the applications of the technique. CRISPR/Cas immune systems have been found in a wide range of prokaryotes, both bacteria and archaea. This indicates that there might be a broad number of Cas-like proteins that remain undiscovered to date, which could have new characteristics and/or properties of interest for genetic engineering purposes [ 39 ]. Some of them have already been characterized such as Cas13 family members, which are able to introduce breaks into RNA, opening the possibility of mRNA manipulation using the CRISPR system [40,41]. New types of Cas nucleases could be useful in order to broaden our battery of CRISPR/Cas modifying enzymes, but the possibility of engineering known nucleases, such as Cas9, is also interesting. For instance, a lot of effort has been put into the development of inducible forms of Cas9, as well as into altering its recognition site (PAM sequence) and improving its fidelity [ 42 , 43 ]. In addition, it is also intriguing the development of versions of Cas9 with one (Cas9 nickases, nCas9) or two (dead Cas9, dCas9) non-active catalytic domains. These modified Cas9s can be in turn fused with other enzymatic domains, which is the functional base of CRISPR interference (CRISPRi) [ 44 ], CRISPR activation (CRISPRa) [45], base editing [46] and prime editing [47]. One important drawback of CRISPR/Cas technology is the presence of off-target effects in the genome of the edited cells, which can be especially dangerous for clinical applications. Notwithstanding, there are mechanisms that can help to evaluate the occurrence of non-specific effects, such as whole-exome sequencing (WES) or whole-genome sequencing (WGS), although the latter generates a huge amount of data to be analyzed and biologically interpreted. Remarkably, the results of the studies carried to date seem to indicate that the occurrence of off-targets is, in fact, similar to the normal mutation rate of cells [48,49]. Genetic edition by CRISPR/Cas system has been applied successfully on many model organisms, including Caenorhabditis elegans [ 50 ], Drosophila melanogaster [ 51 ], zebrafish [ 52 ], rodents [ 53 ], and even primates [ 54 ]. CRISPR/Cas has also been used in human cell cultures, both of somatic [ 28 ] and embryonic cell lines [55]. Genes 2020,11, 1376 8 of 45 Both the introduction of indels (knockout, KO) and specific genetic modifications (knock-in, KI) can be a powerful tool to model gene–base disorders, as it allows researchers to precisely study the association between genes or genetic variants and the development of an altered phenotype. 3. In Vitro Models of ASD: The Stem Cell Revolution Cellular models are very useful for studying diseases with an important genetic contribution, especially if these diseases cause alterations in cell types easy to maintain in the laboratory. As it was previously mentioned, ASD often has a strong genetic component, and its effects are primarily seen on cells of the central nervous system associated with high cognitive functions. These cell types cannot be obtained from biopsies, which supposes an obstacle for the study of ASD bases using cell cultures as a model. In addition, neurons are a highly specialized cell type with a low proliferation rate, so they cannot be cultured for the long term, and thus, model cell lines are hard to establish [7,56,57]. However, this scenario changed in 2006, when Yamanaka and his collaborators identified mechanisms that allow reprogramming adult somatic cells representing new perspectives in molecular biology and biomedicine. These techniques allow the transformation of differentiated cell lines into induced pluripotent stem cells (hiPSCs) by expressing four genes, known as the Yamanaka factors (Oct3/4, Sox2, Klf4, c-Myc) [ 58 ]. The main advantages of hiPSCs are their self-renewal capability and their differentiation potential. A new and exciting possibility for the study of neurodevelopmental disorders was then born, as hiPSCs can afterwards be differentiated into cell types from the nervous system. The development of novel reprogramming methods and differentiation protocols makes it now possible to generate cell lines directly from patients, obtaining, as a result, specialized in vitro models to study the cause of the disorder in a particular individual [57,59]. Cellular models directly derived from patients have several advantages in comparison with other in vitro models, such as embryonic cell lines. With this approximation, models for disorders caused by rare variations can be created, which is the case for ASD (Table 3). Cellular models obtained from patients have proven to be highly robust, reliable and realistic, conserving the genetic background of the source. As they match the genetic background of the patients, the biological base of their respective disorders can be analyzed. An additional advantage of these cellular models is that they can be used to revert potentially pathogenic genetic variants, which can help to validate the association between the detected genotype and an altered phenotype [57,59,60]. Cell lines obtained from patients are versatile models, in which analyses to establish the cell and molecular mechanism implied in the curse of the disorder, can be conducted. When addressing neurological disorders, it is possible to study alterations in neuronal morphology, synaptic transmission, cell migration and differentiation capability, among others [56,59,60]. These models are useful to establish a relationship between a genotype and a phenotype, but also to develop new therapeutic approaches, including cell therapy and pharmacological treatments. This can be achieved by studies for the identification of new therapeutic targets or biomarkers, as well as drug sensibility assays, which are helpful to validate the action of the selected drugs prior to clinical assays [57,59]. For all the stated reasons, this approach opens new possibilities for the study of the molecular bases of complex disorders, such as ASD. Several research groups have been working in this field to study both syndromic and non-syndromic forms of ASD. In Table 3, a list of ASD-associated genes that have been studied using this approach can be found. Some long non-coding RNAs (lncRNAs), such as PTCHD1-AS or COSMOC [61,62] are also included. Further information about recent studies that implicate lncRNAs, other non-coding mutations, and regulatory variants in ASD susceptibility can be found in the excellent review by Ross et al. [63]. Despite the advantages of in vitro models, it is undeniable that cell culture cannot fully recapitulate all the complexity behind the development of ASD, for this reason, animal models are still a fundamental tool to fully understand them. Genes 2020,11, 1376 9 of 45 Table 3. Types of alterations observed in neural-like cell lines with a lack of expression of ASD-associated genes. Neural-like cell lines developed to study ASD have been obtained by the differentiation of human induced pluripotent stem cells (hiPSCs) from patients or by the inactivation of the selected ASD-associated gene in controls, using genomic editing systems. Cell Lines Derived from hiPSCs ASD-Associated Gene Alterations Due to the Lack of Expression of ASD-Associated Gene References Cortical neurons EHMT1 Reduced neurite length and complexity Altered neuronal activity Increased expression of proliferation genes Decreased expression of maturation and migration genes [64] MECP2 Increased synaptogenesis and dendritic complexity Altered neuronal network synchronization [65] NRXN1 Altered ion transport and calcium signaling [66] PTCHD1 Decreased frequency of miniature excitatory postsynaptic currents N-methyl-D-aspartate receptor (NMDARs) hypofunction [61] PTCHD1-AS Decreased frequency of miniature excitatory postsynaptic currents [61] SHANK2 Increased number of synapses, dendritic length and complexity Increased frequency of spontaneous excitatory postsynaptic currents Altered expression of genes associated to neuronal morphogenesis, plasticity and synapse [67] SHANK3 Synaptic alteration and decreased dendritic spines [68,69] TSC2 Mitochondria disorganization and altered mitophagy Increased soma size and neurite number mTORC1 signaling pathway hyperactivation Increased neuronal activity and upregulation of cell adhesion genes [70,71] Dopaminergic neurons RELN Altered neuronal migration [72] Glutamatergic neurons AFF2 Alteration in genes associated with neuronal development Decreased synaptic activity: reduced spontaneous excitatory postsynaptic currents [73] ASTN2 Alteration in genes associated with neuronal development Decreased synaptic activity: reduced spontaneous excitatory postsynaptic currents [73] ATRX Alteration in genes associated with neuronal development Decreased synaptic activity: reduced spontaneous excitatory postsynaptic currents [73] CNTN5 Increased neuronal activity [74] KCNQ2 Decreased synaptic activity: reduced spontaneous excitatory postsynaptic currents [73] SCN2A Alteration in genes associated with morphogenesis Decreased synaptic activity: reduced spontaneous excitatory postsynaptic currents [73] Genes 2020,11, 1376 16 of 45 Table 5. Cont. ASD-Associated Gene/Mus musculus Gene Modification Technique Main Phenotypical Observations Reference SHANK2/Shank2 Conditional LOF in Purkinje cells Targeted KO Altered synaptic currents Increased anxiety and hyperactivity Reduced coordination Increased repetitive behaviors Reduced social approach Decreased spatial learning and memory [144–148] TAOK2/Taok2 Targeted KO by Cre-LoxP Abnormal brain morphology and spine density Reduced dendritic length and complexity Reduced cortical lamination and thickness Impaired memory of context [149] TBR1/Tbr1 Conditional LOF in neurons of cortical layer 6 and subplate Targeted KO by homologous recombination Altered brain morphology Reduced neuronal connectivity Reduced number of interneurons Altered differentiation of brain cells Altered cortical organization Altered synaptic currents Increased anxiety aggressiveness Increased aggressive [146,150–153] UPF3B/Upf3b Targeted KO by gene trap Reduced spine density Altered morphology of cortical neurons Poor differentiation of neural progenitors Impaired sensorimotor gating Abnormal clasping reflex Abnormal sleep pattern Impaired startle response to acoustic stimuli [154] Genes 2020,11, 1376 17 of 45 Table 6. Phenotype observed in Rattus norvegicus models of ASD-associated genes. The table includes the developed models to study the function and implication in ASD of genes classified with score 1 (high confidence) or gene score 2 (strong candidate) in the SFARI Gene database [ 20 , 21 ]. In the cases in which several models have been developed, the phenotype column only includes their common characteristics. ASD-Associated Gene/Rattus norvegicus Gene Modification Technique Main Phenotypical Observations Reference BCKDK/Bckdk KO by spontaneous mutation Neuronal alterations Reduced protein phosphorylation Infertility Altered development [155] CACNA1C/Cacna1c KO by ZFN Altered social behavior and reduced USVs Increased perseverative behaviors [156,157] CNTNAP2/Cntnap2 KO by ZFN Seizures Hyperactivity Altered audition and sleep routines [158,159] CYFIP1/Cyfip1 KO by CRISPR/Cas9 Neuronal alterations Altered behavioral flexibility in learning tasks [160] FMR1/Fmr1 KO by ZFN Increased repetitive behaviors and social alterations. Altered sensorimotor gating Memory difficulties Neuronal alterations Altered auditory responses [161–163] MECP2/Mecp2 KO by ZFN High mortality Malocclusion Neuronal alterations Hypoactivity Altered social interaction and speech responses. Memory alterations Decreased grip strength [164,165] NLGN2/Nlgn2 Overexpression in the hippocampus Decreased response to new stimuli and aggressive behavior [166] NLGN3/Nlgn3 KO by ZFN Increased repetitive behaviors Hyperactivity and altered sleep routines Decreased body weight Altered juvenile play behavior and startle response Altered sensorimotor gating [162,167] NRXN1/Nrxn1 KO by biallelic deletion Hyperactivity Altered startle response Memory alterations [168] Genes 2020,11, 1376 18 of 45 Table 6. Cont. ASD-Associated Gene/Rattus norvegicus Gene Modification Technique Main Phenotypical Observations Reference PTEN/Pten Heterozygous KO by ZFN Neuronal alterations [169] SCN1A/Scn1a KO by ENU mutagenesis Increased repetitive behaviors Hyperactivity and anxiety Learning and memory difficulties Motor alterations Reduced dopamine levels [170] SHANK2/Shank2 KO by ZFN Alterations in social behavior Hyperactivity and increased repetitive behavior Memory alterations Neuronal alterations [171] SHANK3/Shank3 KO by ZFN Alterations in social behavior Neuronal alterations [172] TCF4/Tcf4 KO by CRISPR/Cas9 and knockdown by shRNA in the prefrontal cortex Altered electrophysiological properties in neurons [173] TSC2/Tsc2 KO by spontaneous mutation Enhanced episodic-like memory Enhanced seizure-induced plasticity Increased induction of phospho-p42-MAPK in the hippocampus Increased basal oxygen consumption in the brain [174,175] UBE3A/Ube3a KO by CRISPR/Cas9 Motor, learning and memory difficulties [176] Genes 2020,11, 1376 19 of 45 4.2. Zebrafish and the Modeling of Human Disorders In recent years, the zebrafish has been postulated as an ideal animal model for the study of the genetic background of several human diseases and remarkably, more than 800 laboratories around the world use nowadays zebrafish as a model [ 177 ]. The introduction of the zebrafish as an animal model dates back to the early 1960s, initially used to study vertebrate development and genetics [ 178 ]. Since then, researchers have progressively drawn on this animal in several human scientific fields, from genetic diseases, regeneration pathways or toxicology assays to high-throughput drug screenings [ 179 ]. Zebrafish is a freshwater fish, native from the streams of the south-eastern Himalayan region, and it owns its name due to its fusiform morphology and the horizontal stripes on each side of the body. There is a notorious sexual dimorphism, which allows the distinction between males and females [ 180 ]. Although this fish is able to survive in a range of temperatures from 12 ◦ C to 39 ◦ C in nature, its optimal temperature in controlled conditions is 28.5 ◦ C [ 181 , 182 ]. The biological features that help to explain its use in laboratories, as well as its success as a translational model in biomedical research, in particular in neurosciences [ 96 , 99 , 183 ], have been increasingly listed since the 1990s [ 178 ]. It is worth highlighting the frequent reproduction (once a week), producing between 200 and 400 embryos per couple, enabling the performance of high-throughput assays. The external fertilization and optical transparency of embryos and larvae allow researchers to easily manipulate animals and observe their development, specifically imaging of neurodevelopmental processes and neural activity, even at a single-cell level without using invasive techniques [ 179 ]. In addition, zebrafish nearly completes basic development within 24 h, has rapid growth and sexual maturation (3–5 months), and interestingly, zebrafish has delayed development of the adaptive immune system (10–14 days), which is the main basis of its use in cancer research, and possesses an extraordinary tissue regeneration ability [ 184 – 186 ]. Furthermore, there are some other practical issues that make zebrafish stand out when compared with rodents, such as the relatively easy and cost-effective maintenance or the small size of adult individuals, which allows breeding a high number of animals in the facility. 4.2.1. Zebrafish and Mammals: Conservation throughout Evolution Comparative studies have revealed that the order of neurodevelopmental events across species is highly conserved, even also in zebrafish, although time points, complexity and organization differ, mainly regarding morphogenesis and neurogenesis. In this sense, morphogenesis of zebrafish brain is completed within 3 days and mechanisms behind the formation of different brain structures, such as the neural tube or the telencephalon, differ with respect to those in mammals [ 187 – 189 ]. Nevertheless, the most significant brain regions and major subdivisions, as well as cell types, differentiation, connectivity, signaling pathways and gene expression patterns, are highly conserved [ 190 – 192 ]. Additionally, there are some structural and functionally equivalent neuroanatomic regions such as zebrafish lateral, dorsal and medial pallium, which share characteristics with the human hippocampus, neocortex and amygdala, respectively [ 193 ]. While this review will not explain in depth zebrafish and mammals neural structures development and their conservation, we refer the reader to the excellent review by Kozol et al., 2018 [194]. Regarding structural homology and ASD, an interesting example of a critical period is the cerebellar structure and its development. In zebrafish, the cerebellar primordial becomes evident at 22 h post-fertilization (hpf) [ 189 ], and the differentiation of excitatory or inhibitory neurons, glutamatergic and GABAergic respectively, begins at 3 days post-fertilization (dpf) and layers are detectable at 5 dpf [ 195 ]. Equivalent to mammals, although in distinct expression domains, the expression by cerebellar progenitors of atoh1 genes gives rise to the excitatory cells and the expression ptf1a leads to the formation of inhibitory cells [ 196 ]. Glutamatergic neurons include granule cells and GABAergic neurons include Purkinje cells and in the adult zebrafish such cells are arranged in three layers: molecular, Purkinje cell and granule layer [ 195 ]. Purkinje cells are fundamental for the cerebellar neural circuit and its function as they receive synaptic information, process it and relay such information through their efferent projections to the cerebellar nuclei which, in turn, connect Genes 2020,11, 1376 20 of 45 the cerebellum to the brain and spinal cord, regulating several cognitive, language, motor, sensory and emotional functions [ 197 ]. It becomes then evident the importance that these cells have in the proper function of the nervous system and precisely, in the majority of ASD cases, one of the most reproducible and apparent observations is the significant reduction in Purkinje cells number and size [ 198 – 200 ]. Guissart et al., identified several mutations in a nuclear receptor (ROR α ), essential for cerebellar development, in families with variable neurodevelopmental delay and intellectual disability, including cognitive, motor and behavioral phenotypes. They developed a zebrafish mutant model by CRISPR/Cas9 and were able to recapitulate the neuroanatomical features of patients, showing a reduction of Purkinje and granule cells [ 201 ]. This is only an example that provides a rationale for using zebrafish as a model to study neurodevelopmental disorders such as ASD. Nevertheless, the specific role that Purkinje cells have in the development of ASD-like phenotypes is still unclear. With regard to genetics, the zebrafish genome-sequencing project was initiated at the Welcome Trust Sanger Institute in 2001 and in 2013, Howe et al., released a high-quality sequence assembly of the zebrafish genome, showing that approximately 70% of the human genes have one zebrafish orthologue, being >80% human disease-related genes [ 202 ]. Regarding development, as mentioned before, expression patterns in early developmental genes are homologous in both zebrafish and humans and major neurotransmitter systems such as GABA, glutamate, norepinephrine, cholinergic and dopaminergic pathways as well as glial cells are conserved between both species [ 190 , 191 , 203 , 204 ]. In addition, Lovett-Barron et al. established a novel method to discover behavioral-related cellular elements and evidenced evolutionarily conserved cellular and molecular systems involved in basic neuromodulatory circuits [205]. In regards to behavior, it has also been demonstrated that zebrafish shares behavioral patterns with humans, including physiological, emotional and social responses [99]. Altogether, these data reaffirm the suitability of the zebrafish as a biomedical research model and its relevance to our understanding of genes, neural circuits and the physiopathology behind neurodevelopmental disorders as ASD. Henceforth, we will focus on the available genetic strategies applicable in zebrafish in order to develop reliable models to functionally validate ASD-candidate genes, and the techniques that might be utilized to characterize morphological, molecular and behavioral features. 4.2.2. Gene Targeting in Zebrafish One of the main attractions of zebrafish as the disease-model animal is the relative ease and versatility to conduct genetic manipulations in embryos, from transient downregulation or overexpression of a certain gene to permanent gene-targeted mutations [52,206]. Regarding transient reverse genetic approaches, the most commonly used in zebrafish is morpholino-based (MO) expression silencing. MOs are small modified oligonucleotides that are able to bind a selected target by complementary knocking down the gene function without altering the sequence. MOs can either bind the translation start site of the mRNA and thus, interfere with the progression of the ribosomal initiation complex, or to the splicing sites of the pre-mRNAs, leading to abnormal mature mRNAs [ 207 ]. Since the release of these antisense oligos in the latest 1990s [ 208 ], and given their relatively low cost and ease of use, several zebrafish models have been developed in order to unravel the implication of specific genes in many human diseases. In Table 7, several examples of morpholino-based studies for ASD-candidate genes are shown. Nevertheless, despite its extended use in biomedical research and although the majority of zebrafish studies of neurodevelopmental disorder genes have been based on MOs, these molecules present important disadvantages that should be considered. Firstly, their transient effect (up to 4 dpf) do not allow to study the gene function beyond the early developmental stages [ 209 ]. In addition, it has been reported MOs may lead to off-target effects, resulting in non-specific phenotypes for the gene of study or triggering apoptosis through p53 pathway activation, so a careful design must be carried out, it is recommended to use a control Genes 2020,11, 1376 21 of 45 MO, rescue experiments with RNA might be performed to confirm MO specificity and when possible, morphant phenotypes should be confirmed in genetic mutants [210,211]. With respect to the generation of stable zebrafish mutant lines, the Targeted Induced Local Lesions in Genomes (TILLING) has been largely used. This technique is based on the exposure to a mutagen known as ethylnitrosourea (ENU), an alkylating agent which, by ethylating oxygen or nitrogen atoms in DNA bases, induces error-prone replication and in turn, leading to random point mutations in the genome. Next, sequencing is performed in order to identify loss of function mutations. From the beginning of its use [ 212 ], this procedure has been successfully applied to generate several models of KO zebrafish. This methodology has been quite useful to correlate specific genes with observed phenotypes, although the generation of a stable mutant line for a gene of interest is relatively limited as it is difficult to identify the desired mutation, costs are substantial and screening zebrafish libraries takes a long time [ 213 ]. Some zebrafish ENU knockout models for ASD-candidate genes are listed in Table 7. In order to solve TILLING drawbacks, nuclease-based technologies were later introduced, speeding up the zebrafish knockout generation and, as previously mentioned, these techniques include TALEN and ZFN, whose functioning is basically the same [ 214 , 215 ]. Despite both techniques enabled researchers to improve the generation of zebrafish mutant lines, it is challenging to specifically design such systems, there is a high ratio of off-target and they are still time and cost consuming. Examples of knockout zebrafish models for ASD-candidate genes are shown in Table 7. Recently, due to the development and optimization of new genetic editing protocols based on CRISPR/Cas system more accurate mutant zebrafish lines were achieved, as the system offers superior efficiency and flexibility with respect to the previously mentioned gene-editing methods [ 52 , 216 , 217 ]. With regard to CRISPR and neurodevelopmental disorders and in order to highlight its large applicability and utility, it is worth mentioning the extraordinary study recently performed by Thyme et al. They focused on more than 100 genomic loci at which common variants exhibited genome-wide significant associations in a schizophrenia case/control analysis and performed high-throughput CRISPR/Cas9 (132 genes) in zebrafish. By doing so, they were able to observe and describe a phenotypic landscape of schizophrenia-associated genes, to prioritize more than 30 candidates and to provide hypotheses to associate specific genes with biological mechanisms [ 218 ]. In Table 7, some examples of CRISPR/Cas9 zebrafish models are listed. Genes 2020,11, 1376 22 of 45 Table 7. Phenotype observed in Danio rerio ASD-associated genes models. Genes are classified with score 1 (high confidence) or score 2 (strong candidate) following the SFARI Gene database [20,21]. In the cases in which several models have been developed, phenotype refers to the characteristics shared by all of them. ASD-Linked Gene/Danio rerio Gene Modification Technique Main Phenotypical Observations Reference ARID1B/arid1b Knockdown by MOs Reduced body length Altered expression of chondrogenic/osteogenic genes [219] ARX/arxa Knockdown by MOs Altered brain development Neuronal alterations [220] AUTS2/auts2a and auts2b Knockdown by MOs Microcephaly Altered jaw development Motor alterations Neuronal alterations [221] CACNA1C/cacna1c Knockdown by MOs Cardiac alterations Altered jaw development [222] CEP41/cep41 Knockdown by MOs Neuronal alterations Social behavior alterations [223] CHD2/chd2 Knockdown by MOs Altered development Microcephaly, abnormal body curvature Swim bladder absence Motor difficulties [224] CHD8/chd8 Knockout by CRISPR/Cas9 and knockdown by MOs Macrocephaly Reduction in post-mitotic enteric neurons [225,226] CNTNAP2/cntnap2a and cntap2b Knockout by ZFN Altered development Microcephaly Neuronal alterations Motor alterations [36] CTNND2/ctnnd2b Knockdown by MOs Reduced body length Notochord alterations [227] DYRK1A/dyrk1a Knockout by TALENs Altered response to social stimuli [228] FMR/fmr1 Knockout by ENU-mutagenesis and CRISPR/Cas9 Altered cephalic development Hyperactivity Increased anxiety Altered social behavior Learning difficulties [229–231] Genes 2020,11, 1376 23 of 45 Table 7. Cont. ASD-Linked Gene/Danio rerio Gene Modification Technique Main Phenotypical Observations Reference KCNJ10/kcnj10 Knockdown by MOs Motor alterations Altered development [232] KDM6A/kdm6a Knockdown by MOs Reduced body length Altered development Notochord alterations Neuronal alterations [233,234] MECP2/mecp2 Knockout by ENU-mutagenesis and knockdown by MOs Altered immune response Neuronal alterations [235–237] MET/met Knockdown by MOs High mortality Neuronal alterations [238] MYT1L/mytl1a and mytl1b Knockdown by MOs Reduced levels of oxytocin [239] NBEA/nbea Knockout by ENU-mutagenesis and TALENs Neuronal alterations Altered response to startle stimuli [240] NR3C2/nr3c2 Knockout by CRISPR/Cas9 Altered social behavior Altered sleep routines [241] OXTR/oxtr Knockout by TALENs Altered oxytocin signaling pathway Memory alterations in social and non-social recognition [242] RELN/reln Knockout by TALENs Altered social behavior Altered serotonin signaling pathway [243] RERE/rerea and rereb Knockout by ENU-mutagenesis Altered startle response to stimuli Vision and hearing difficulties [244] SHANK3/shank3a and shankb Knockout by CRISPR/Cas9 Altered development Neuronal alterations Reduced social behavior, hypoactivity [245,246] SYNGAP1/syngap1a and syngap1b Knockdown by MOs Delayed development High mortality Neuronal alterations Motor difficulties [245] Genes 2020,11, 1376 24 of 45 Aside from these genome-editing techniques, several transgenic zebrafish lines fluorescently labeled have been developed throughout the last years, enabling researchers to better characterize neurodevelopmental zebrafish models. Table 8summarizes some of the available transgenic lines and their specific expression pattern. Table 8. Examples of developed zebrafish transgenic lines. Transgenic Line Expression Pattern Reference ath5:GFP Retinal ganglion cells [247] brn3c:GFP Retinal ganglion cells [248] dat:EGFP Dopaminergic neurons [249] elavl3:lynTagRFP Post-mitotic neurons [250] En-1:GFP Circumferential ascending interneurons [251] flk1:GFP Endothelial cells [252] gad1b:RFP Gabaergic neurons [253] gfap:GFP Radial glial cells [254] glyt2:GFP Glycinergic neurons [255] gsx1:GFP Gabaergic neurons [253] isl1:GFP Cranial motor neurons [256] kctd15a:GFP Torus lateralis [257] mnx1:GFP Motor neurons [258] neurod:EGFP Immature neurons [259] neurog1:GFP Primary neurons [260] olig2:EGFP Oligodendrocytes [261] pet1:GFP Serotonergic neurons [262] qrfp:GFP Rostral hipothalamus [263] sox10:GFP Neural crest cells/Neurocranium cartilague [264] tbx2b:EGFP Cone photoreceptor cells [265] Vglut2a:GFP Glutamatergic neurons [253] vmat2:GFP Monoaminergic neurons [266] 4.2.3. Characterization of Zebrafish Models Once the zebrafish knockdown or knockout model to study ASD-candidate genes is generated (with or without transgenic lines), there are several techniques that might be utilized to its accurate characterization, being mainly focused on morphological, molecular and behavioral features. Regarding morphological characterization, the parameters to be analyzed may include a series of general observations such as body, heart, head, eyes otolith or jaw malformations, yolk deformation or edema and tail bending. Secondly, in order to determine if there exists a delay or abnormality in development some measures might be taken, such as body length, head, eye and yolk sac area or otolith–eye and jaw–eye distance, as well as the different brain regions thickness, area and weight [ 246 , 267 , 268 ]. This characterization is image-based and might be performed manually, or with available commercial image software. To molecularly characterize zebrafish knockdown or knockdown embryos, researchers can draw upon several techniques, but some of the most commonly applied when it comes to functionally validate candidate genes in the zebrafish model are summarized below. With regard to gene expression patterns, many of the genes mentioned in transgenic lines in Table 8can serve as markers in qPCR assays, which offer information about how much the gene is expressed, or in in situ hybridization (ISH) assays with RNA probes, which allow localizing where the gene is being expressed in a precise time point. Other markers to perform ISH or qPCR with, that may be useful in neurodevelopment research are sox2 (neural stem cells self-renewal and pluripotency cells), vglut2.2 (glutamatergic marker), th1 (dopaminergic marker), neurog1 (neuronal determination marker), c-fos (neuronal activator marker), crh (paraventricular nucleus neurons), c-myc (tectal proliferation zone and retina), emx1 (telencephalon) or otx2a and pax2a (diencephalon and midbrain–hindbrain boundary) [ 267 , 269 , 270 ]. In addition, immunofluorescence leads the researchers to know where the Genes 2020,11, 1376 25 of 45 protein is acting, and if there are differences in the amount of protein among individuals, although these assays are relatively limited in zebrafish due to the absence of several specific antibodies. Nevertheless, some have been successfully used such as anti-serotonin (serotonergic neurons), anti-GFAP (radial glia cells) [ 267 ], acetylated antiα -tubulin (brain axonal tracts), anti-sox10 (neural crest cells migration) [ 223 ], anti-homer1 (post-synaptic protein), antisynaptophysin (pre-synaptic terminals) [ 246 ], znp-1 (primary motor neurons) [ 269 ], anti-phosphohistone H3 (M-phase, cell proliferation) [ 36 , 226 ], anti-PCNA (cell proliferation) [270], anti-caspase3 (apoptotic cells) [228] or anti-PSD95 (synaptic marker) [271]. Transcriptomic analyses may be performed in-depth with RNA-sequencing (RNA-seq), although it requires a great amount and high-quality material. Excellent research with RNA-seq, which in addition highlights the suitability of zebrafish to study the implication of environmental factors in ASD-risk, was performed by Lee et al. They exposed embryos to valproic acid—known to induce autism-like effects—and further performed RNA-seq, finding a direct correlation between zebrafish transcriptome and several ASD-associated genes [ 272 ]. This technique may also be useful to assess genetic compensation among individuals with phenotypic variability [273]. Concerning behavioral characterization, the precocious behaviors that embryo and larvae display [ 274 ] have led to the development of many tests that have proven to be valuable and accurate in zebrafish models. In this sense, different research groups have already study alterations in learning abilities [ 275 ], decision-making [ 276 ], sensorial capabilities [ 277 , 278 ], emotional responses [ 279 , 280 ] and social interactions [ 107 , 281 , 282 ], among others. These mechanisms are especially relevant when using zebrafish as a model for studying ASD, as many of these responses are altered in humans suffering from these disorders. Finally, due to the possibility to use large numbers of the individual to test different drugs or chemicals and the ease of the delivery of the substance—diluted in water [ 283 ]—zebrafish has been proposed to conduct high-throughput screenings of neuroactive compounds. This approach would enable the identification of novel compounds with the potential to be used in new treatments for ASD and other NDDs, and additionally, allow the evaluation of their toxicity [284,285]. 4.2.4. Limitations of Zebrafish to Model Human Disorders As stated throughout this section, not only can zebrafish be used to study the genetic bases of ASD, but also to highlight the relevance of environmental factors on autism-like phenotypes development [ 285 ]. Nevertheless, there are some drawbacks that should be considered when using zebrafish to study human diseases, mainly related to the retention of many duplicate genes due to the whole genome duplication [ 286 ]. This means that in some cases, researchers ought to study both genes at the same time. However, this issue might be overcome if the planning of projects is accurately carried out. 5. Future Challenges The present review has been focused on the need of developing reliable models to study the complex genetic background of ASD. These models could be useful to improve our knowledge of the disorder and also to lead the way to the discovery of new potential treatments for patients. In a disorder as complex as ASD, with individuals having such a diverse genetic background, the possibility of creating personalized models could be very useful in the clinic. Due to the accessibility of the genome editing technologies, such as CRISPR/Cas, it is now more feasible to consider the possibility of creating models that recapitulate the causal mutations detected on patients, and in turn determine which drug therapy is more adequate for each case, which represents one of the first steps towards personalized medicine. Another interesting approach that has recently been postulated is the possibility of conducting direct reprogramming in vivo [ 287 ]. Basically, this technology could allow differentiating adult somatic cells into other cell types without the need for a hiPSC intermediate state. This methodology could be very interesting as a cell therapy option for many diseases and disorders. An imbalance of excitatory Genes 2020,11, 1376 32 of 45 38. Joung, J.K.; Sander, J.D. TALENs: A widely applicable technology for targeted genome editing. Nat. Rev. Mol. Cell Biol. 2013,14, 49–55. [CrossRef] [PubMed] 39. Wright, A.V.; Nuñez, J.K.; Doudna, J.A. 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