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Pathogenic variants in RAC3 cause a neurodevelopmental disorder with brain malformations and craniofacial dysmorphism, called NEDBAF. This gene encodes a small GTPase, which plays a critical role in neurogenesis and neuronal migration. We report a 31 weeks of gestation fetus with triventricular dilatation, and temporal and perisylvian polymicrogyria, without cerebellar, brainstem, or callosal anomalies. Trio whole exome sequencing identified a RAC3 (NM_005052.3, GRCh38) probably pathogenic de novo variant c.276 T>A p.(Asn92Lys). Eighteen patients harboring 13 different and essentially de novo missense RAC3 variants were previously reported. All the patients presented with corpus callosum malformations. Gyration disorders, ventriculomegaly (VM), and brainstem and cerebellar malformations have frequently been described. The only previous prenatal case associated with RAC3 variant presented with complex brain malformations, mainly consisting of midline and posterior fossa anomalies. We report the second prenatal case of NEDBAF presenting an undescribed pattern of cerebral anomalies, including VM and polymicrogyria, without callosal, cerebellar, or brainstem malformations. All neuroimaging data were reviewed to clarify the spectrum of cerebral malformations.

Current yeast interactome network maps contain several hundred molecular complexes with limited and somewhat controversial representation of direct binary interactions. We carried out a comparative quality assessment of current yeast interactome data sets, demonstrating that high-throughput yeast two-hybrid (Y2H) screening provides high-quality binary interaction information. Because a large fraction of the yeast binary interactome remains to be mapped, we developed an empirically controlled mapping framework to produce a \"second-generation\" high-quality, high-throughput Y2H data set covering ~20% of all yeast binary interactions. Both Y2H and affinity purification followed by mass spectrometry (AP/MS) data are of equally high quality but of a fundamentally different and complementary nature, resulting in networks with different topological and biological properties. Compared to co-complex interactome models, this binary map is enriched for transient signaling interactions and intercomplex connections with a highly significant clustering between essential proteins. Rather than correlating with essentiality, protein connectivity correlates with genetic pleiotropy.

High-throughput yeast two-hybrid screening is used to generate the largest C. elegans interactome resource available thus far. Using an empirical quality control framework presented in Venkatesan et al ., also online, the data set is evaluated for quality and is used to estimate the total size of the worm interactome. To provide accurate biological hypotheses and elucidate global properties of cellular networks, systematic identification of protein-protein interactions must meet high quality standards. We present an expanded C. elegans protein-protein interaction network, or 'interactome' map, derived from testing a matrix of ∼10,000 × ∼10,000 proteins using a highly specific, high-throughput yeast two-hybrid system. Through a new empirical quality control framework, we show that the resulting data set (Worm Interactome 2007, or WI-2007) was similar in quality to low-throughput data curated from the literature. We filtered previous interaction data sets and integrated them with WI-2007 to generate a high-confidence consolidated map (Worm Interactome version 8, or WI8). This work allowed us to estimate the size of the worm interactome at ∼116,000 interactions. Comparison with other types of functional genomic data shows the complementarity of distinct experimental approaches in predicting different functional relationships between genes or proteins.

We describe a new syndrome of young onset diabetes, short stature and microcephaly with intellectual disability in a large consanguineous family with three affected children. Linkage analysis and whole exome sequencing were used to identify the causal nonsense mutation, which changed an arginine codon into a stop at position 127 of the tRNA methyltransferase homolog gene TRMT10A (also called RG9MTD2). TRMT10A mRNA and protein were absent in lymphoblasts from the affected siblings. TRMT10A is ubiquitously expressed but enriched in brain and pancreatic islets, consistent with the tissues affected in this syndrome. In situ hybridization studies showed that TRMT10A is expressed in human embryonic and fetal brain. TRMT10A is the mammalian ortholog of S. cerevisiae TRM10, previously shown to catalyze the methylation of guanine 9 (m(1)G9) in several tRNAs. Consistent with this putative function, in silico topology prediction indicated that TRMT10A has predominant nuclear localization, which we experimentally confirmed by immunofluorescence and confocal microscopy. TRMT10A localizes to the nucleolus of β- and non-β-cells, where tRNA modifications occur. TRMT10A silencing induces rat and human β-cell apoptosis. Taken together, we propose that TRMT10A deficiency negatively affects β-cell mass and the pool of neurons in the developing brain. This is the first study describing the impact of TRMT10A deficiency in mammals, highlighting a role in the pathogenesis of microcephaly and early onset diabetes. In light of the recent report that the type 2 diabetes candidate gene CDKAL1 is a tRNA methylthiotransferase, the findings in this family suggest broader relevance of tRNA methyltransferases in the pathogenesis of type 2 diabetes.

Background Human congenital non-syndromic hydrocephalus is a vastly heterogeneous condition. A subgroup of cases are not secondary to a specific cause (eg, a neural tube defect), and within this subgroup, autosomal recessive inheritance has been described. One homozygous mutation in the DAPLE (Dvl-associating protein with a high frequency of leucine residues) protein-encoding gene CCDC88C (coiled-coil domain containing 88C) has recently been reported in a single family. The role of this gene has not been validated in another family, and no other autosomal recessive gene has been reported. Methods We used homozygosity mapping and whole exome sequencing in two families with primary, non-syndromic congenital hydrocephalus from two different ethnic backgrounds. Results In each family, we identified a novel homozygous mutation of CCDC88C. One mutation produced a premature stop codon at position 312 of the protein, while the second mutation induced a frameshift in the last exon, producing a stop codon that truncated the extreme C-terminus of DAPLE, including the 2026-2028 Gly-Cys-Val motif known to bind the post synaptic density protein (PSD95), Drosophila disc large tumor suppressor (Dlg1), and zonula occludens-1 protein (zo-1) (PDZ) domain of Dishevelled. Conclusions Our data validate CCDC88C as causing autosomal recessive, primary non-syndromic congenital hydrocephalus, suggesting this gene may be an important cause of congenital hydrocephalus, and underscore the important role of the C-terminal PDZ domain-binding motif in the DAPLE protein.

High-quality datasets are needed to understand how global and local properties of protein-protein interaction, or 'interactome', networks relate to biological mechanisms, and to guide research on individual proteins. In an evaluation of existing curation of protein interaction experiments reported in the literature, we found that curation can be error-prone and possibly of lower quality than commonly assumed.

Background Harstfield syndrome is the rare and unique association of holoprosencephaly (HPE) and ectrodactyly, with or without cleft lip and palate, and variable additional features. All the reported cases occurred sporadically. Although several causal genes of HPE and ectrodactyly have been identified, the genetic cause of Hartsfield syndrome remains unknown. We hypothesised that a single key developmental gene may underlie the co-occurrence of HPE and ectrodactyly. Methods We used whole exome sequencing in four isolated cases including one case-parents trio, and direct Sanger sequencing of three additional cases, to investigate the causative variants in Hartsfield syndrome. Results We identified a novel FGFR1 mutation in six out of seven patients. Affected residues are highly conserved and are located in the extracellular binding domain of the receptor (two homozygous mutations) or the intracellular tyrosine kinase domain (four heterozygous de novo variants). Strikingly, among the six novel mutations, three are located in close proximity to the ATP's phosphates or the coordinating magnesium, with one position required for kinase activity, and three are adjacent to known mutations involved in Kallmann syndrome plus other developmental anomalies. Conclusions Dominant or recessive FGFR1 mutations are responsible for Hartsfield syndrome, consistent with the known roles of FGFR1 in vertebrate ontogeny and conditional Fgfr1-deficient mice. Our study shows that, in humans, lack of accurate FGFR1 activation can disrupt both brain and hand/foot midline development, and that FGFR1 loss-of-function mutations are responsible for a wider spectrum of clinical anomalies than previously thought, ranging in severity from seemingly isolated hypogonadotropic hypogonadism, through Kallmann syndrome with or without additional features, to Hartsfield syndrome at its most severe end.

Cellular functions are mediated through complex systems of macromolecules and metabolites linked through biochemical and physical interactions, represented in interactome models as ‘nodes’ and ‘edges’, respectively. Better understanding of genotype‐to‐phenotype relationships in human disease will require modeling of how disease‐causing mutations affect systems or interactome properties. Here we investigate how perturbations of interactome networks may differ between complete loss of gene products (‘node removal’) and interaction‐specific or edge‐specific (‘edgetic’) alterations. Global computational analyses of ∼50 000 known causative mutations in human Mendelian disorders revealed clear separations of mutations probably corresponding to those of node removal versus edgetic perturbations. Experimental characterization of mutant alleles in various disorders identified diverse edgetic interaction profiles of mutant proteins, which correlated with distinct structural properties of disease proteins and disease mechanisms. Edgetic perturbations seem to confer distinct functional consequences from node removal because a large fraction of cases in which a single gene is linked to multiple disorders can be modeled by distinguishing edgetic network perturbations. Edgetic network perturbation models might improve both the understanding of dissemination of disease alleles in human populations and the development of molecular therapeutic strategies. Synopsis Genotype‐to‐phenotype relationships in human genetic disease are often modeled as: ‘mutation in gene X leads to loss of gene product X, which leads to disease A’. However, single ‘gene‐loss’ models cannot explain the increasingly appreciated prevalence of complex genotype‐to‐phenotype relationships, particularly with instances of allelic or locus hetrogeneity (Goh et al , 2007 ). Genes and gene products function not in isolation but as components of complex networks of macromolecules (DNA, RNA, or proteins) and metabolites linked through biochemical or physical interactions, often represented in ‘interactome’ network models as ‘nodes’ and ‘edges’, respectively. Here we use network perturbation models to explain molecular dysfunctions underlying human disease in addition to the gene‐loss model. We hypothesize that different mutations leading to different molecular defects to proteins may cause distinct perturbations of cellular networks, giving rise to distinct phenotypic outcomes (Figure 1 ). For example, truncations close to the start of an open‐reading frame, or mutations that grossly destabilize a protein structure, can be modeled as removing a protein node from the network (‘node removal’). Alternatively, single amino‐acid substitutions that affect specific binding sites, or truncations that preserve certain domains of a protein, may give rise to partially functional gene products with specific changes in distinct molecular interaction(s) (edge‐specific or ‘edgetic’ perturbations) (Figure 1B ). Taking advantage of the large number of known disease‐causing allelic variations in human Mendelian disorders, we investigated how disease‐associated mutations may cause complete loss of gene products or, alternatively, may cause specific loss or gain of individual molecular interaction(s). We examined ∼50 000 Mendelian disease‐causing alleles, affecting over 1900 protein‐coding genes, altogether associated with more than 2000 human disorders available in the Human Gene Mutation Database (HGMD) (Stenson et al , 2003 ), that can be subdivided into two subsets: truncating’ alleles (truncations or frameshifts caused by stop codons, out‐of‐frame insertions or deletions, or defective splicing) versus ‘in‐frame’ alleles (missense mutations and in‐frame insertions or deletions). Over 50% (27 919/52 491) of Mendelian alleles in HGMD correspond to ‘in‐frame’ mutations. Our hypothesis is that, ‘in‐frame’ alleles may affect specific interactions of a given gene product while leaving most other interactions unperturbed. Although exceptions may apply, our hypothesis has several predictions. First, ‘truncating’ versus ‘in‐frame’ alleles may distribute differently among autosomal dominant and autosomal recessive disease, given that dominant mutations are more likely to be edgetic than recessive ones. Indeed, autosomal dominant and autosomal recessive traits annotated in the Online Mendelian Inheritance in Man (OMIM) database (Hamosh et al , 2005 ) show a clear separation with respect to the associated ‘in‐frame’ versus ‘truncating’ mutations. Among genes affected solely by ‘in‐frame’ mutations, the proportion of dominant diseases is ∼10‐fold higher than that of recessive ones, supporting ‘in‐frame’ mutations causing distinct molecular defects as opposed to ‘truncating’ mutations. A proof‐of‐principle characterization of binary protein interaction defects of mutant alleles associated with five genetic disorders supports our hypothesis that ‘in‐frame’ alleles indeed produce mostly functional proteins, preserving many specific protein interactions. As grossly disruptive mutations versus mutations leading to loss or gain of specific interaction(s) probably distribute differently on protein structures, we examined available three‐dimensional structures of all disease proteins. Mutated residues in autosomal dominant disease are significantly more exposed to the surface of the structure than those in autosomal recessive disease, consistent with the idea that disease with distinct modes of inheritance probably involves distinct network perturbations. A second testable prediction of our edgetic perturbation model is that edgetic perturbation versus gene loss for a given gene product might in some cases cause different diseases. We examined 142 genes associated with two or more distinct diseases in which at least five distinct alleles have been reported for each disease. We found ∼30% of the cases for which distribution of ‘in‐frame’ versus ‘truncating’ mutations is significantly different between the two diseases linked to the same gene ( P <0.05). Hence, when affecting the same gene, node removal versus edgetic perturbation can confer strikingly different phenotypes. A third testable prediction is that different edgetic perturbations for a given gene product might cause phenotypically distinguishable diseases (Figure 6 ). We used predicted Pfam domains (Finn et al , 2006 ) as surrogates for functional interaction domains, assuming that ‘in‐frame’ mutations located in distinct Pfam domain‐encoding sequences probably alter distinct interactions. Among 169 genes associated with two or more diseases and encoding proteins containing at least two Pfam domains, nine proteins have at least two Pfam domains significantly enriched with ‘in‐frame’ mutations ( P <0.05). For each of the nine proteins, we found a striking pattern of near mutual exclusivity, whereby different Pfam domains seem to be specifically affected in distinct disorders (Figure 6B ). We conclude that edgetic alleles probably underlie many complex genotype‐to‐phenotype relationships in human disease, such as incomplete penetrance or variable expressivity, as well as allele‐specific phenotypic variations among patients. Edgetic perturbation of human inherited disorders might help explain how seemingly devastating alleles have appeared and persevered in human populations. We present alternative models to explain molecular dysfunctions underlying human inherited disorders based on interaction‐specific or “edgetic” perturbations rather than complete loss of gene products. We find that a substantial fraction of known genetic variants in human Mendelian disorders likely cause edgetic perturbations. We find frequent situations where edgetic perturbation models can explain how different mutations in a single gene can cause distinct disorders. Edgetic perturbation models should provide alternative explanations to complex genotype‐to‐phenotype relationships

Many human diseases, arising from mutations of disease susceptibility genes (genetic diseases), are also associated with viral infections (virally implicated diseases), either in a directly causal manner or by indirect associations. Here we examine whether viral perturbations of host interactome may underlie such virally implicated disease relationships. Using as models two different human viruses, Epstein-Barr virus (EBV) and human papillomavirus (HPV), we find that host targets of viral proteins reside in network proximity to products of disease susceptibility genes. Expression changes in virally implicated disease tissues and comorbidity patterns cluster significantly in the network vicinity of viral targets. The topological proximity found between cellular targets of viral proteins and disease genes was exploited to uncover a novel pathway linking HPV to Fanconi anemia.

Background Human T-cell leukemia virus type 1 (HTLV-1) and type 2 both target T lymphocytes, yet induce radically different phenotypic outcomes. HTLV-1 is a causative agent of Adult T-cell leukemia (ATL), whereas HTLV-2, highly similar to HTLV-1, causes no known overt disease. HTLV gene products are engaged in a dynamic struggle of activating and antagonistic interactions with host cells. Investigations focused on one or a few genes have identified several human factors interacting with HTLV viral proteins. Most of the available interaction data concern the highly investigated HTLV-1 Tax protein. Identifying shared and distinct host-pathogen protein interaction profiles for these two viruses would enlighten how they exploit distinctive or common strategies to subvert cellular pathways toward disease progression. Results We employ a scalable methodology for the systematic mapping and comparison of pathogen-host protein interactions that includes stringent yeast two-hybrid screening and systematic retest, as well as two independent validations through an additional protein interaction detection method and a functional transactivation assay. The final data set contained 166 interactions between 10 viral proteins and 122 human proteins. Among the 166 interactions identified, 87 and 79 involved HTLV-1 and HTLV-2 -encoded proteins, respectively. Targets for HTLV-1 and HTLV-2 proteins implicate a diverse set of cellular processes including the ubiquitin-proteasome system, the apoptosis, different cancer pathways and the Notch signaling pathway. Conclusions This study constitutes a first pass, with homogeneous data, at comparative analysis of host targets for HTLV-1 and -2 retroviruses, complements currently existing data for formulation of systems biology models of retroviral induced diseases and presents new insights on biological pathways involved in retroviral infection.