Search

New technologies enabling genome-wide interrogation have led to a large and rapidly growing number of autism spectrum disorder (ASD) candidate genes. Although encouraging, the volume and complexity of these data make it challenging for scientists, particul

Study is conducted to show that heterozygous loss-of-function mutations in the human GDF1 gene contribute to cardiac defects ranging from tetralogy of Fallot to transposition of the great arteries. The findings implicate perturbations of the TGF-[beta] signaling pathway in the causation of a major subclass of human congenial heart defects (CHDs).

Abstract Background In the post-genomic era, multi-faceted research on complex disorders such as autism has generated diverse types of molecular information related to its pathogenesis. The rapid accumulation of putative candidate genes/loci for Autism Spectrum Disorders (ASD) and ASD-related animal models poses a major challenge for systematic analysis of their content. We previously created the Autism Database (AutDB) to provide a publicly available web portal for ongoing collection, manual annotation, and visualization of genes linked to ASD. Here, we describe the design, development, and integration of a new module within AutDB for ongoing collection and comprehensive cataloguing of ASD-related animal models. Description As with the original AutDB, all data is extracted from published, peer-reviewed scientific literature. Animal models are annotated with a new standardized vocabulary of phenotypic terms developed by our researchers which is designed to reflect the diverse clinical manifestations of ASD. The new Animal Model module is seamlessly integrated to AutDB for dissemination of diverse information related to ASD. Animal model entries within the new module are linked to corresponding candidate genes in the original "Human Gene" module of the resource, thereby allowing for cross-modal navigation between gene models and human gene studies. Although the current release of the Animal Model module is restricted to mouse models, it was designed with an expandable framework which can easily incorporate additional species and non-genetic etiological models of autism in the future. Conclusions Importantly, this modular ASD database provides a platform from which data mining, bioinformatics, and/or computational biology strategies may be adopted to develop predictive disease models that may offer further insights into the molecular underpinnings of this disorder. It also serves as a general model for disease-driven databases curating phenotypic characteristics of corresponding animal models.

While prenatal maternal infection has received attention as a preventable and treatable risk factor for autism, findings have been inconsistent. This paper presents the results of a meta-analysis to determine whether the weight of the evidence supports such an association. Studies with a categorical diagnosis of autism as the outcome and an assessment of its association with prenatal maternal infection or fever (or the data necessary to compute this association) were included. A total of 36 studies met these criteria. Two independent reviewers extracted data on study design, methods of assessment, type of infectious agent, site of infection, trimester of exposure, definition of autism, and effect size. Analyses demonstrated a statistically significant association of maternal infection/fever with autism in offspring (OR = 1.32; 95% CI = 1.20-1.46). Adjustment for evident publication bias slightly weakened this association. There was little variation in effect sizes across agent or site of infection. Small differences across trimester of exposure were not statistically significant. There was some evidence that recall bias associated with status on the outcome variable leads to differential misclassification of exposure status. Nonetheless, the overall association is only modestly reduced when studies potentially contaminated by such bias are removed. Although causality has not been firmly established, these findings suggest maternal infection during pregnancy confers an increase in risk for autism in offspring. Given the prevalence of this risk factor, it is possible that the incidence of autism would be reduced by 12%-17% if maternal infections could be prevented or safely treated in a timely manner. LAY SUMMARY: This study is a meta-analysis of the association of maternal infection during pregnancy and subsequent autism in offspring. In combining the results from 36 studies of this association we find that a significant relationship is present. The association does not vary much across the types of infections or when they occur during pregnancy. We conclude that the incidence of autism could be substantially reduced if maternal infections could be prevented or safely treated in a timely manner., (© 2021 International Society for Autism Research, Wiley Periodicals LLC.)

Autism (MIM 209850) is a multifactorial disorder with a broad clinical presentation. A number of high-confidence ASD risk genes are known; however, the contribution of non-genetic environmental factors towards ASD remains largely uncertain. Here, we present a bioinformatics resource of genetic and induced models of ASD developed using a shared annotation platform. Using this data, we depict the intricate trends in the research approaches to analyze rodent models of ASD. We identify the top 30 most frequently studied phenotypes extracted from rodent models of ASD based on 787 publications. As expected, many of these include animal model equivalents of the "core" phenotypes associated with ASD, such as impairments in social behavior and repetitive behavior, as well as several comorbid features of ASD including anxiety, seizures, and motor-control deficits. These phenotypes have also been studied in models based on a broad range of environmental inducers present in the database, of which gestational exposure to valproic acid (VPA) and maternal immune activation models comprising lipopolysaccharide (LPS) and poly I:C are the most studied. In our unique dataset of rescue models, we identify 24 pharmaceutical agents tested on established models derived from various ASD genes and CNV loci for their efficacy in mitigating symptoms relevant for ASD. As a case study, we analyze a large collection of Shank3 mouse models providing a high-resolution view of the in vivo role of this high-confidence ASD gene, which is the gateway towards understanding and dissecting the heterogeneous phenotypes seen in single-gene models of ASD. The trends described in this study could be useful for researchers to compare ASD models and to establish a complete profile for all relevant animal models in ASD research., Competing Interests: Not applicableNot applicableThe authors declare that they have no competing interests.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

AutDB is a deeply annotated resource for exploring the impact of genetic variations associated with autism spectrum disorders (ASD). First released in 2007, AutDB has evolved into a multi-modular resource of diverse types of genetic and functional evidence related to ASD. Current modules include: Human Gene, which annotates all ASD-linked genes and their variants; Animal Model, which catalogs behavioral, anatomical and physiological data from rodent models of ASD; Protein Interaction (PIN), which builds interactomes from direct relationships of protein products of ASD genes; and Copy Number Variant (CNV), which catalogs deletions and duplications of chromosomal loci identified in ASD. A multilevel data-integration strategy is utilized to connect the ASD genes to the components of the other modules. All information in this resource is manually curated by expert scientists from primary scientific publications and is referenced to source articles. AutDB is actively maintained with a rigorous quarterly data release schedule. As of June 2017, AutDB contains detailed annotations for 910 genes, 2197 CNV loci, 1060 rodent models and 38 296 PINs. With its widespread use by the research community, AutDB serves as a reference resource for analysis of large datasets, accelerating ASD research and potentially leading to targeted drug treatments. AutDB is available at http://autism.mindspec.org/autdb/Welcome.do., (© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Background: The search for genetic factors underlying autism spectrum disorders (ASD) has led to the identification of hundreds of genes containing thousands of variants that differ in mode of inheritance, effect size, frequency, and function. A major challenge involves assessing the collective evidence in an unbiased, systematic manner for their functional relevance., Methods: Here, we describe a scoring algorithm for prioritization of candidate genes based on the cumulative strength of evidence for each ASD-associated variant cataloged in AutDB (also known as SFARI Gene). We retrieved data from 889 publications to generate a dataset of 2187 rare and 711 common variants distributed across 461 genes implicated in ASD. Each individual variant was manually annotated with multiple attributes extracted from the original report, followed by score assignment using a set of standardized parameters yielding a single score for each gene., Results: There was a wide variation in scores; SHANK3 , CHD8 , and ADNP had distinctly higher scores than all other genes in the dataset. Our gene scores were significantly correlated with other recently published rankings of ASD genes ( R Spearman  = 0.40-0.63; p<  0.0001), providing support for our scoring algorithm., Conclusions: This new resource, which is freely available, for the first time aggregates on one-platform variants identified from various study types (simplex, multiplex, multigenerational, and consanguineous families), from both common and rare variants, and also incorporates their putative functional consequences to arrive at a genetically and biologically driven ranking scheme. This work represents a major step in moving from simply cataloging autism variants to using data-driven approaches to gain insight into their significance.

Background: Autism spectrum conditions (ASC) are a group of conditions characterized by difficulties in communication and social interaction, alongside unusually narrow interests and repetitive, stereotyped behaviour. Genetic association and expression studies have suggested an important role for the GABAergic circuits in ASC. Syntaxin 1A (STX1A) encodes a protein involved in regulation of serotonergic and GABAergic systems and its expression is altered in autism., Methods: In this study, the association between three single nucleotide polymorphisms (SNPs) (rs4717806, rs941298 and rs6951030) in STX1A gene and Asperger syndrome (AS) were tested in 650 controls and 479 individuals with AS, all of Caucasian ancestry., Results: rs4717806 (P = 0.00334) and rs941298 (P = 0.01741) showed a significant association with AS, replicating previous results. Both SNPs putatively alter transcription factor binding sites both directly and through other variants in high linkage disequilibrium., Conclusions: The current study confirms the role of STX1A as an important candidate gene in ASC. The exact molecular mechanisms through which STX1A contributes to the etiology remain to be elucidated.

New technologies enabling genome-wide interrogation have led to a large and rapidly growing number of autism spectrum disorder (ASD) candidate genes. Although encouraging, the volume and complexity of these data make it challenging for scientists, particularly non-geneticists, to comprehensively evaluate available evidence for individual genes. Described here is the Gene Scoring module within SFARI Gene 2.0 (https://gene.sfari.org/autdb/GS&#95;Home.do), a platform developed to enable systematic community driven assessment of genetic evidence for individual genes with regard to ASD.

Copy number variants (CNVs) are thought to play an important role in the predisposition to autism spectrum disorder (ASD). However, their relatively low frequency and widespread genomic distribution complicates their accurate characterization and utilization for clinical genetics purposes. Here we present a comprehensive analysis of multi-study, genome-wide CNV data from AutDB (http://mindspec.org/autdb.html), a genetic database that accommodates detailed annotations of published scientific reports of CNVs identified in ASD individuals. Overall, we evaluated 4,926 CNVs in 2,373 ASD subjects from 48 scientific reports, encompassing ∼2.12×10(9) bp of genomic data. Remarkable variation was seen in CNV size, with duplications being significantly larger than deletions, (P  =  3×10(-105); Wilcoxon rank sum test). Examination of the CNV burden across the genome revealed 11 loci with a significant excess of CNVs among ASD subjects (P<7×10(-7)). Altogether, these loci covered 15,610 kb of the genome and contained 166 genes. Remarkable variation was seen both in locus size (20 - 4950 kb), and gene content, with seven multigenic (≥3 genes) and four monogenic loci. CNV data from control populations was used to further refine the boundaries of these ASD susceptibility loci. Interestingly, our analysis indicates that 15q11.2-13.3, a genomic region prone to chromosomal rearrangements of various sizes, contains three distinct ASD susceptibility CNV loci that vary in their genomic boundaries, CNV types, inheritance patterns, and overlap with CNVs from control populations. In summary, our analysis of AutDB CNV data provides valuable insights into the genomic characteristics of ASD susceptibility CNV loci and could therefore be utilized in various clinical settings and facilitate future genetic research of this disorder.

Autism spectrum disorder (ASD) is one of the most prevalent and highly heritable neurodevelopmental disorders in humans. There is significant evidence that the onset and severity of ASD is governed in part by complex genetic mechanisms affecting the normal development of the brain. To date, a number of genes have been associated with ASD. However, the temporal and spatial co-expression of these genes in the brain remain unclear. To address this issue, we examined the co-expression network of 26 autism genes from AutDB (http://mindspec.org/autdb.html), in the framework of 3,041 genes whose expression energies have the highest correlation between the coronal and sagittal images from the Allen Mouse Brain Atlas database (http://mouse.brain-map.org). These data were derived from in situ hybridization experiments conducted on male, 56-day old C57BL/6J mice co-registered to the Allen Reference Atlas, and were used to generate a normalized co-expression matrix indicating the cosine similarity between expression vectors of genes in this database. The network formed by the autism-associated genes showed a higher degree of co-expression connectivity than seen for the other genes in this dataset (Kolmogorov-Smirnov P = 5×10⁻²⁸). Using Monte Carlo simulations, we identified two cliques of co-expressed genes that were significantly enriched with autism genes (A Bonferroni corrected P<0.05). Genes in both these cliques were significantly over-expressed in the cerebellar cortex (P = 1×10⁻⁵) suggesting possible implication of this brain region in autism. In conclusion, our study provides a detailed profiling of co-expression patterns of autism genes in the mouse brain, and suggests specific brain regions and new candidate genes that could be involved in autism etiology.

Background: In the post-genomic era, multi-faceted research on complex disorders such as autism has generated diverse types of molecular information related to its pathogenesis. The rapid accumulation of putative candidate genes/loci for Autism Spectrum Disorders (ASD) and ASD-related animal models poses a major challenge for systematic analysis of their content. We previously created the Autism Database (AutDB) to provide a publicly available web portal for ongoing collection, manual annotation, and visualization of genes linked to ASD. Here, we describe the design, development, and integration of a new module within AutDB for ongoing collection and comprehensive cataloguing of ASD-related animal models., Description: As with the original AutDB, all data is extracted from published, peer-reviewed scientific literature. Animal models are annotated with a new standardized vocabulary of phenotypic terms developed by our researchers which is designed to reflect the diverse clinical manifestations of ASD. The new Animal Model module is seamlessly integrated to AutDB for dissemination of diverse information related to ASD. Animal model entries within the new module are linked to corresponding candidate genes in the original "Human Gene" module of the resource, thereby allowing for cross-modal navigation between gene models and human gene studies. Although the current release of the Animal Model module is restricted to mouse models, it was designed with an expandable framework which can easily incorporate additional species and non-genetic etiological models of autism in the future., Conclusions: Importantly, this modular ASD database provides a platform from which data mining, bioinformatics, and/or computational biology strategies may be adopted to develop predictive disease models that may offer further insights into the molecular underpinnings of this disorder. It also serves as a general model for disease-driven databases curating phenotypic characteristics of corresponding animal models.

Molecular underpinnings of complex psychiatric disorders such as autism spectrum disorders (ASD) remain largely unresolved. Increasingly, structural variations in discrete chromosomal loci are implicated in ASD, expanding the search space for its disease etiology. We exploited the high genetic heterogeneity of ASD to derive a predictive map of candidate genes by an integrated bioinformatics approach. Using a reference set of 84 Rare and Syndromic candidate ASD genes (AutRef84), we built a composite reference profile based on both functional and expression analyses. First, we created a functional profile of AutRef84 by performing Gene Ontology (GO) enrichment analysis which encompassed three main areas: 1) neurogenesis/projection, 2) cell adhesion, and 3) ion channel activity. Second, we constructed an expression profile of AutRef84 by conducting DAVID analysis which found enrichment in brain regions critical for sensory information processing (olfactory bulb, occipital lobe), executive function (prefrontal cortex), and hormone secretion (pituitary). Disease specificity of this dual AutRef84 profile was demonstrated by comparative analysis with control, diabetes, and non-specific gene sets. We then screened the human genome with the dual AutRef84 profile to derive a set of 460 potential ASD candidate genes. Importantly, the power of our predictive gene map was demonstrated by capturing 18 existing ASD-associated genes which were not part of the AutRef84 input dataset. The remaining 442 genes are entirely novel putative ASD risk genes. Together, we used a composite ASD reference profile to generate a predictive map of novel ASD candidate genes which should be prioritized for future research.

The cyclopic and laterality phenotypes in model organisms linked to disturbances in the generation or propagation of Nodal-like signals are potential examples of similar impairments resulting in birth defects in humans. However, the types of gene mutation(s) and their pathogenetic combinations in humans are poorly understood. Here we describe a mutational analysis of the human NODAL gene in a large panel of patients with phenotypes compatible with diminished NODAL ligand function. Significant reductions in the biological activity of NODAL alleles are detected among patients with congenital heart defects (CHD), laterality anomalies (e.g. left-right mis-specification phenotypes), and only rarely holoprosencephaly (HPE). While many of these NODAL variants are typical for family-specific mutations, we also report the presence of alleles with significantly reduced activity among common population variants. We propose that some of these common variants act as modifiers and contribute to the ultimate phenotypic outcome in these patients; furthermore, we draw parallels with strain-specific modifiers in model organisms to bolster this interpretation.

Recent advances in studies of Autism Spectrum Disorders (ASD) has uncovered many new candidate genes and continues to do so at an accelerated pace. To address the genetic complexity of ASD, we have developed AutDB (http://www.mindspec.org/autdb.html), a publicly available web-portal for on-going collection, manual annotation and visualization of genes linked to the disorder. We present a disease-driven database model in AutDB where all genes connected to ASD are collected and classified according to their genetic variation: candidates identified from genetic association studies, rare single gene mutations and genes linked to syndromic autism. Gene entries are richly annotated for their relevance to autism, along with an in-depth view of their molecular functions. The content of AutDB originates entirely from the published scientific literature and is organized to optimize its use by the research community. The main focus of this resource is to provide an up-to-date, annotated list of ASD candidate genes in the form of reference dataset for interrogating molecular mechanisms underlying the disorder. Our model for consolidated knowledge representation in genetically complex disorders could be replicated to study other such disorders.

We have identified a mutation in the zebrafish gene claudinj generated by retroviral integration. Mutant embryos display otoliths severely reduced in size, no response to tapping stimulus, and an inability to balance properly suggesting vestibular and hearing dysfunction. Antisense in situ hybridization to the cldnj gene showed expression first in the otic placode and later asymmetric expression in the otic vesicle. Morpholino inhibition of claudinj expression showed similar defects in otolith formation. Phylogenetic analysis of claudin sequences from multiple species demonstrates that claudinj was part of a gene expansion that began in the common ancestor of fish and humans, but additional fish specific gene duplications must have also occurred.

Mutations in a number of forkhead transcription factors are associated with the development of inherited diseases in humans. Two closely related genes, FOXP2 and FOXP3, are implicated in two completely different human disorders. A point mutation in the forkhead domain of FOXP2 (R553H) is responsible for a severe speech and language disorder, while a series of missense mutations distributed over the forkhead domain of FOXP3 cause a fatal disorder called IPEX, characterized by immune dysregulation, polyendocrinopathy, and enteropathy. Homology model building techniques were used to generate atomic structures of FOXP2 and FOXP3, using the solution structures of the forkhead domain of the adipocyte-transcription factor FREAC-11 and AFX as templates. The impact of these disease-causing missense mutations on the three-dimensional structure, stability, and surface electrostatic charge distribution of the forkhead domains is examined here. The missense mutations R553H in FOXP2 and R397W in FOXP3 dramatically alter the electrostatic potentials of the molecular surface of their respective forkhead domains., (Copyright 2004 Wiley-Liss, Inc.)

Five missense mutations (P79L, P79T, I91S, I91T and R127H) within the forkhead DNA-binding domain of the FOXC1 transcription factor, identified in patients with Axenfeld-Rieger (AR) malformations, were studied to identify the effects of these mutations on FOXC1 structure and function. Molecular modeling and threading analyses predict that the I91S and T mutations may generate local disruptions to the structure of the forkhead domain while the R127H mutation alters the electrostatic charge of the DNA binding surface of the forkhead domain. The P79L and T mutations are not predicted to grossly perturb the structure of the forkhead domain. Biological analyses indicate that all of these missense mutations cause a range of FOXC1 perturbations, including nuclear localization defects, reduced or abolished DNA binding capacity, and a reduction in the transactivation capacity of FOXC1. These experiments extend our previous hypothesis that reduced transactivation of appropriate target genes by FOXC1, underlie AR malformations mapping to human chromosome 6p25. Importantly, these results can also be applied to predict the consequences of the molecular effects of mutations of other FOX genes that have analogous missense mutations, including FOXP2, FOXE3 and FOXC2.

The retroviral oncogene qin, homologue of mammalian brain factor 1 (FOXG1 B), belongs to the family of winged helix transcription factors. Oncogenic transformation by Qin requires sequence-specific DNA binding. Missense mutations in the forkhead domain of Qin modulate its oncogenic transforming ability in chicken embryonic fibroblasts. We used homology model building (threading) techniques to generate atomic structures of wild-type c-Qin and c-Qin mutants, using the solution structure of the forkhead domain of the adipocyte transcription factor as a template (M. J. van Dongen et al., J. Mol. Biol., 296: 351-359, 2000). Energy calculations indicate that the Qin forkhead structure is stabilized primarily by hydrophobic interactions between residues at the helical interface. None of the missense mutations analyzed here were responsible for maintaining the most critical pairwise interactions holding the forkhead domain together. The mutated proteins form the overall structure of the forkhead domain, but the mutations do interfere with DNA binding.

Functional annotation is used to catalog information that would be of value in experimental design and analysis but annotations in public databases are often incorrect. Here, one such case is discussed.

Five missense mutations of the winged-helix FOXC1 transcription factor, found in patients with Axenfeld-Rieger (AR) malformations, were investigated for their effects on FOXC1 structure and function. Molecular modeling of the FOXC1 forkhead domain predicted that the missense mutations did not alter FOXC1 structure. Biochemical analyses indicated that, whereas all mutant proteins correctly localize to the cell nucleus, the I87M mutation reduced FOXC1-protein levels. DNA-binding experiments revealed that, although the S82T and S131L mutations decreased DNA binding, the F112S and I126M mutations did not. However, the F112S and I126M mutations decrease the transactivation ability of FOXC1. All the FOXC1 mutations had the net effect of reducing FOXC1 transactivation ability. These results indicate that the FOXC1 forkhead domain contains separable DNA-binding and transactivation functions. In addition, these findings demonstrate that reduced stability, DNA binding, or transactivation, all causing a decrease in the ability of FOXC1 to transactivate genes, can underlie AR malformations.

McKusick-Kaufman syndrome (MKKS, MIM 236700) is a human developmental anomaly syndrome comprising hydrometrocolpos (HMC), postaxial polydactyly (PAP) and congenital heart disease (CHD). MKKS has been mapped in the Old Order Amish population to 20p12, between D20S162 and D20S894 (ref. 3). Here we describe the identification of a gene mutated in MKKS. We analysed the approximately 450-kb candidate region by sample sequencing, which revealed the presence of several known genes and EST clusters. We evaluated candidate transcripts by northern-blot analysis of adult and fetal tissues. We selected one transcript with widespread expression, MKKS, for analysis in a patient from the Amish pedigree and a sporadic, non-Amish case. The Old Order Amish patient was found to be homozygous for an allele that had two missense substitutions and the non-Amish patient was a compound heterozygote for a frameshift mutation predicting premature protein truncation and a distinct missense mutation. The MKKS predicted protein shows amino acid similarity to the chaperonin family of proteins, suggesting a role for protein processing in limb, cardiac and reproductive system development. We believe that this is the first description of a human disorder caused by mutations affecting a putative chaperonin molecule.

DNA mismatch repair is important because of its role in maintaining genomic integrity and its association with hereditary non-polyposis colon cancer (HNPCC). To identify new human mismatch repair proteins, we probed nuclear extracts with the conserved carboxy-terminal MLH1 interaction domain. Here we describe the cloning and complete genomic sequence of MLH3, which encodes a new DNA mismatch repair protein that interacts with MLH1. MLH3 is more similar to mismatch repair proteins from yeast, plants, worms and bacteria than to any known mammalian protein, suggesting that its conserved sequence may confer unique functions in mice and humans. Cells in culture stably expressing a dominant-negative MLH3 protein exhibit microsatellite instability. Mlh3 is highly expressed in gastrointestinal epithelium and physically maps to the mouse complex trait locus colon cancer susceptibility I (Ccs1). Although we were unable to identify a mutation in the protein-coding region of Mlh3 in the susceptible mouse strain, colon tumours from congenic Ccs1 mice exhibit microsatellite instability. Functional redundancy among Mlh3, Pms1 and Pms2 may explain why neither Pms1 nor Pms2 mutant mice develop colon cancer, and why PMS1 and PMS2 mutations are only rarely found in HNPCC families.

The homeodomain is a common structural motif found in many transcription factors involved in cell fate determination during development. We have used threading analysis techniques to predict whether the atypical homeodomain of prospero (pros) family members could form the three-helical homeodomain structural motif, even though these proteins are not statistically similar to canonical homeodomains as assessed by BLAST searches. Amino acid sequences of these divergent homeodomain proteins were threaded through the X-ray coordinates of the Drosophila engrailed homeodomain protein [23]. The analysis confirms that the prospero class of homeodomain proteins is indeed capable of forming the homeodomain structure despite its low degree of sequence identity to the canonical homeodomain. Energy calculations indicate that the homeodomain structure is stabilized primarily by hydrophobic interactions between residues at the helical interfaces. Although the atypical prospero-type homeodomain shows very little sequence similarity when compared to other homeodomain proteins, the critical amino acids responsible for maintaining the three-dimensional structure are highly conserved. A number of other homeodomain proteins, such as PHO2p from Saccharomyces and Pax6 from human, were also included in the threading analysis and were shown to be able to form the engrailed structure, indicating that there are no rigid overall sequence requirements for the formation of the homeodomain structural motif. Based on the threading experiments and the subsequent structural alignment, a new amino acid signature that unambiguously identifies the prospero-type proteins was deduced.

Mutations in the homeobox gene PITX2 are responsible for a range of clinical phenotypes involving ocular and craniofacial development. Several mutations within the Pitx2 homeodomain region are specifically responsible for the development of the related autosomal-dominant disorders Rieger syndrome and iridogoniodysgenesis. To address the question of the structural effect of disease-causing mutations on the Pitx2 homeodomain, we used threading techniques to examine the tertiary structure of the Pitx2 wild-type and mutant homeodomain, using the crystal structure of Drosophila engrailed homeodomain bound with DNA as a template [Kissinger et al., 1990]. The threading analysis reveals that the wild-type Pitx2 homeodomain is indeed capable of forming the typical three-helical bundle-fold characteristic of homeodomain proteins. Energy calculations indicate that the homeodomain structure is stabilized primarily by hydrophobic interactions between residues at the helical interface. Point mutations responsible for the development of these genetic disorders were also examined; the results suggest that these mutations lead to the inability of Pitx2 to adopt its proper structure and bind to the regulatory sequences of its target gene(s), which in turn affects its metabolic role in the cell. Published 1999 Wiley-Liss, Inc.

Prox 1 is the vertebrate homolog of Drosophila prospero, a gene known to be expressed in the lens-secreting cone cells of fly ommatidia. Chicken Prox 1 cDNAs were isolated from 14 day embryonic chicken lenses, and a complete open reading frame encoding an 83 kDa protein was elucidated. The homeodomains of chicken and mouse Prox 1 are identical at the amino acid level and are 65-67% similar to the homeodomains of Drosophila and C. elegans prospero. The homology between these proteins extends beyond the homeodomain. There is 56% identity between chicken Prox 1 and Drosophila prospero in the C-terminal region downstream of the homeodomain, whereas there is little similarity upstream of the homeodomain. Prox 1 is expressed most actively in the developing lens and midgut and at lower levels in the developing brain, heart, muscle, and retina. cDNA sequencing has established that there are alternatively spliced forms of the single Prox 1 gene, which probably account for the two abundant RNAs of about 2 and 8 kb and two less abundant RNAs close to 3.5 kb in length in the lens. In the lens fibers, only the shortest mRNA was present, whereas, in the epithelial cells, both short and long mRNAs were detected. By using in situ hybridization, expression of the Prox 1 gene was first detected at stage 14 in the early lens placode and slightly preceded the expression of delta 1-crystallin, the first crystallin gene expressed in the developing chicken lens. At later stages of development, Prox 1 mRNA was observed throughout the lens, but it appeared more abundant around the bow region of the equator than in the anterior epithelium or the fibers. In the retina, expression of the Prox 1 gene was detected mainly in the inner nuclear layer during later stages of histogenesis. The conserved pattern of Prox 1/prospero gene expression in vertebrates and Drosophila suggests that Prox 1, like Pax-6, may be essential for eye development in different systematic groups.

Crystallins are a diverse group of proteins that contribute to the transparency and refractive properties of the eye lens. Previously, the chicken orthologs of four out of the six known bovine beta-crystallin genes have been cloned and sequenced. In the present study, cDNAs corresponding to the chicken orthologs of beta A2- and beta B3-crystallin, the two previously unidentified chicken beta-crystallins, have been isolated. In addition, sequence analysis of three independent chicken beta B2-crystallin cDNAs yielded a deduced connecting peptide sequence which is considerably shorter than that reported previously. Thus, direct homologs of all of the known bovine beta-crystallins are expressed in the chicken lens. This demonstrates that the duplications giving rise to the known vertebrate beta-crystallins occurred over 300 million years ago. beta B2- and beta B3/A1-crystallin are the most highly conserved of the beta-crystallins suggesting that these genes may be important for other functions besides their refractive role in the lens. By Northern blot hybridization analysis, both beta A2- and beta B3-crystallin were shown to be lens-specific in the chicken embryo. The relative levels of beta A2-crystallin remained stable from five days of embryogenesis until adulthood, while the relative amounts of beta B3-crystallin increased until hatching and were appreciably lower in the adult lens. Approximately equal relative amounts of beta A2-crystallin mRNA were found in the lens epithelia and fibers of 5 day embryonic chicken embryos; by contrast, beta B3-crystallin mRNA was detected preferentially in the lens fibers. These data in combination with previous studies suggest that beta-crystallin genes are regulated independently from each other in the developing chicken lens. The elucidation of the primary structures for all seven chicken beta-crystallin polypeptides will facilitate future studies on the structure/function relationships responsible for lens transparency and on the molecular basis for beta-crystallin gene expression during development.