Critical assessment of missense variant effect predictors on disease-relevant variant data.

Regular, systematic, and independent assessment of computational tools used to predict the pathogenicity of missense variants is necessary to evaluate their clinical and research utility and suggest directions for future improvement. Here, as part of the sixth edition of the Critical Assessment of Genome Interpretation (CAGI) challenge, we assess missense variant effect predictors (or variant impact predictors) on an evaluation dataset of rare missense variants from disease-relevant databases. Our assessment evaluates predictors submitted to the CAGI6 Annotate-All-Missense challenge, predictors commonly used by the clinical genetics community, and recently developed deep learning methods for variant effect prediction. To explore a variety of settings that are relevant for different clinical and research applications, we assess performance within different subsets of the evaluation data and within high-specificity and high-sensitivity regimes. We find strong performance of many predictors across multiple settings. Meta-predictors tend to outperform their constituent individual predictors; however, several individual predictors have performance similar to that of commonly used meta-predictors. The relative performance of predictors differs in high-specificity and high-sensitivity regimes, suggesting that different methods may be best suited to different use cases. We also characterize two potential sources of bias. Predictors that incorporate allele frequency as a predictive feature tend to have reduced performance when distinguishing pathogenic variants from very rare benign variants, and predictors supervised on pathogenicity labels from curated variant databases often learn label imbalances within genes. Overall, we find notable advances over the oldest and most cited missense variant effect predictors and continued improvements among the most recently developed tools, and the CAGI Annotate-All-Missense challenge (also termed the Missense Marathon) will continue to assess state-of-the-art methods as the field progresses. Together, our results help illuminate the current clinical and research utility of missense variant effect predictors and identify potential areas for future development.

IMPatienT: An Integrated Web Application to Digitize, Process and Explore Multimodal PATIENt daTa.

Medical acts, such as imaging, lead to the production of various medical text reports that describe the relevant findings. This induces multimodality in patient data by combining image data with free-text and consequently, multimodal data have become central to drive research and improve diagnoses. However, the exploitation of patient data is problematic as the ecosystem of analysis tools is fragmented according to the type of data (images, text, genetics), the task (processing, exploration) and domain of interest (clinical phenotype, histology). To address the challenges, we developed IMPatienT (Integrated digital Multimodal PATIENt daTa), a simple, flexible and open-source web application to digitize, process and explore multimodal patient data. IMPatienT has a modular architecture allowing to: (i) create a standard vocabulary for a domain, (ii) digitize and process free-text data, (iii) annotate images and perform image segmentation, (iv) generate a visualization dashboard and provide diagnosis decision support. To demonstrate the advantages of IMPatienT, we present a use case on a corpus of 40 simulated muscle biopsy reports of congenital myopathy patients. As IMPatienT provides users with the ability to design their own vocabulary, it can be adapted to any research domain and can be used as a patient registry for exploratory data analysis. A demo instance of the application is available at https://impatient.lbgi.fr/.

CeGAL: Redefining a Widespread Fungal-Specific Transcription Factor Family Using an In Silico Error-Tracking Approach.

In fungi, the most abundant transcription factor (TF) class contains a fungal-specific 'GAL4-like' Zn2C6 DNA binding domain (DBD), while the second class contains another fungal-specific domain, known as 'fungal_trans' or middle homology domain (MHD), whose function remains largely uncharacterized. Remarkably, almost a third of MHD-containing TFs in public sequence databases apparently lack DNA binding activity, since they are not predicted to contain a DBD. Here, we reassess the domain organization of these 'MHD-only' proteins using an in silico error-tracking approach. In a large-scale analysis of ~17,000 MHD-only TF sequences present in all fungal phyla except Microsporidia and Cryptomycota, we show that the vast majority (>90%) result from genome annotation errors and we are able to predict a new DBD sequence for 14,261 of them. Most of these sequences correspond to a Zn2C6 domain (82%), with a small proportion of C2H2 domains (4%) found only in Dikarya. Our results contradict previous findings that the MHD-only TF are widespread in fungi. In contrast, we show that they are exceptional cases, and that the fungal-specific Zn2C6-MHD domain pair represents the canonical domain signature defining the most predominant fungal TF family. We call this family CeGAL, after the highly characterized members: Cep3, whose 3D structure is determined, and GAL4, a eukaryotic TF archetype. We believe that this will not only improve the annotation and classification of the Zn2C6 TF but will also provide critical guidance for future fungal gene regulatory network analyses.

MISTIC: A prediction tool to reveal disease-relevant deleterious missense variants.

The diffusion of next-generation sequencing technologies has revolutionized research and diagnosis in the field of rare Mendelian disorders, notably via whole-exome sequencing (WES). However, one of the main issues hampering achievement of a diagnosis via WES analyses is the extended list of variants of unknown significance (VUS), mostly composed of missense variants. Hence, improved solutions are needed to address the challenges of identifying potentially deleterious variants and ranking them in a prioritized short list. We present MISTIC (MISsense deleTeriousness predICtor), a new prediction tool based on an original combination of two complementary machine learning algorithms using a soft voting system that integrates 113 missense features, ranging from multi-ethnic minor allele frequencies and evolutionary conservation, to physiochemical and biochemical properties of amino acids. Our approach also uses training sets with a wide spectrum of variant profiles, including both high-confidence positive (deleterious) and negative (benign) variants. Compared to recent state-of-the-art prediction tools in various benchmark tests and independent evaluation scenarios, MISTIC exhibits the best and most consistent performance, notably with the highest AUC value (> 0.95). Importantly, MISTIC maintains its high performance in the specific case of discriminating deleterious variants from benign variants that are rare or population-specific. In a clinical context, MISTIC drastically reduces the list of VUS (<30%) and significantly improves the ranking of "causative" deleterious variants. Pre-computed MISTIC scores for all possible human missense variants are available at http://lbgi.fr/mistic.

Novel IQCE variations confirm its role in postaxial polydactyly and cause ciliary defect phenotype in zebrafish.

Polydactyly is one of the most frequent inherited defects of the limbs characterized by supernumerary digits and high-genetic heterogeneity. Among the many genes involved, either in isolated or syndromic forms, eight have been implicated in postaxial polydactyly (PAP). Among those, IQCE has been recently identified in a single consanguineous family. Using whole-exome sequencing in patients with uncharacterized ciliopathies, including PAP, we identified three families with biallelic pathogenic variations in IQCE. Interestingly, the c.895_904del (p.Val301Serfs*8) was found in all families without sharing a common haplotype, suggesting a recurrent mechanism. Moreover, in two families, the systemic phenotype could be explained by additional pathogenic variants in known genes (TULP1, ATP6V1B1). RNA expression analysis on patients' fibroblasts confirms that the dysfunction of IQCE leads to the dysregulation of genes associated with the hedgehog-signaling pathway, and zebrafish experiments demonstrate a full spectrum of phenotypes linked to defective cilia: Body curvature, kidney cysts, left-right asymmetry, misdirected cilia in the pronephric duct, and retinal defects. In conclusion, we identified three additional families confirming IQCE as a nonsyndromic PAP gene. Our data emphasize the importance of taking into account the complete set of variations of each individual, as each clinical presentation could finally be explained by multiple genes.

Bardet-Biedl syndrome: Antenatal presentation of forty-five fetuses with biallelic pathogenic variants in known Bardet-Biedl syndrome genes.

Bardet-Biedl syndrome (BBS) is an emblematic ciliopathy associated with retinal dystrophy, obesity, postaxial polydactyly, learning disabilities, hypogonadism and renal dysfunction. Before birth, enlarged/cystic kidneys as well as polydactyly are the hallmark signs of BBS to consider in absence of familial history. However, these findings are not specific to BBS, raising the problem of differential diagnoses and prognosis. Molecular diagnosis during pregnancies remains a timely challenge for this heterogeneous disease (22 known genes). We report here the largest cohort of BBS fetuses to better characterize the antenatal presentation. Prenatal ultrasound (US) and/or autopsy data from 74 fetuses with putative BBS diagnosis were collected out of which molecular diagnosis was established in 51 cases, mainly in BBS genes (45 cases) following the classical gene distribution, but also in other ciliopathy genes (6 cases). Based on this, an updated diagnostic decision tree is proposed. No genotype/phenotype correlation could be established but postaxial polydactyly (82%) and renal cysts (78%) were the most prevalent symptoms. However, autopsy revealed polydactyly that was missed by prenatal US in 55% of the cases. Polydactyly must be carefully looked for in pregnancies with apparently isolated renal anomalies in fetuses.

Genetic Evidence Supporting the Role of the Calcium Channel, CACNA1S, in Tooth Cusp and Root Patterning.

In this study, we report a unique dominantly inherited disorganized supernumerary cusp and single root phenotype presented by 11 affected individuals belonging to 5 north-eastern Thai families. Using whole exome sequencing (WES) we identified a common single missense mutation that segregates with the phenotype in exon 6 of CACNA1S (Cav1.1) (NM_000069.2: c.[865A > G];[=] p.[Ile289Val];[=]), the Calcium Channel, Voltage-Dependent, L Type, Alpha-1s Subunit, OMIM ∗ 114208), affecting a highly conserved amino-acid isoleucine residue within the pore forming subdomain of CACNA1S protein. This is a strong genetic evidence that a voltage-dependent calcium ion channel is likely to play a role in influencing tooth morphogenesis and patterning.

MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers.

BACKGROUND: The constant and massive increase of biological data offers unprecedented opportunities to decipher the function and evolution of genes and their roles in human diseases. However, the multiplicity of sources and flow of data mean that efficient access to useful information and knowledge production has become a major challenge. This challenge can be addressed by taking inspiration from Web 2.0 and particularly social networks, which are at the forefront of big data exploration and human-data interaction. OBJECTIVE: MyGeneFriends is a Web platform inspired by social networks, devoted to genetic disease analysis, and organized around three types of proactive agents: genes, humans, and genetic diseases. The aim of this study was to improve exploration and exploitation of biological, postgenomic era big data. METHODS: MyGeneFriends leverages conventions popularized by top social networks (Facebook, LinkedIn, etc), such as networks of friends, profile pages, friendship recommendations, affinity scores, news feeds, content recommendation, and data visualization. RESULTS: MyGeneFriends provides simple and intuitive interactions with data through evaluation and visualization of connections (friendships) between genes, humans, and diseases. The platform suggests new friends and publications and allows agents to follow the activity of their friends. It dynamically personalizes information depending on the user's specific interests and provides an efficient way to share information with collaborators. Furthermore, the user's behavior itself generates new information that constitutes an added value integrated in the network, which can be used to discover new connections between biological agents. CONCLUSIONS: We have developed MyGeneFriends, a Web platform leveraging conventions from popular social networks to redefine the relationship between humans and biological big data and improve human processing of biomedical data. MyGeneFriends is available at lbgi.fr/mygenefriends.

Insights into Ciliary Genes and Evolution from Multi-Level Phylogenetic Profiling.

Cilia (flagella) are important eukaryotic organelles, present in the Last Eukaryotic Common Ancestor, and are involved in cell motility and integration of extracellular signals. Ciliary dysfunction causes a class of genetic diseases, known as ciliopathies, however current knowledge of the underlying mechanisms is still limited and a better characterization of genes is needed. As cilia have been lost independently several times during evolution and they are subject to important functional variation between species, ciliary genes can be investigated through comparative genomics. We performed phylogenetic profiling by predicting orthologs of human protein-coding genes in 100 eukaryotic species. The analysis integrated three independent methods to predict a consensus set of 274 ciliary genes, including 87 new promising candidates. A fine-grained analysis of the phylogenetic profiles allowed a partitioning of ciliary genes into modules with distinct evolutionary histories and ciliary functions (assembly, movement, centriole, etc.) and thus propagation of potential annotations to previously undocumented genes. The cilia/basal body localization was experimentally confirmed for five of these previously unannotated proteins (LRRC23, LRRC34, TEX9, WDR27, and BIVM), validating the relevance of our approach. Furthermore, our multi-level analysis sheds light on the core gene sets retained in gamete-only flagellates or Ecdysozoa for instance. By combining gene-centric and species-oriented analyses, this work reveals new ciliary and ciliopathy gene candidates and provides clues about the evolution of ciliary processes in the eukaryotic domain. Additionally, the positive and negative reference gene sets and the phylogenetic profile of human genes constructed during this study can be exploited in future work.

A mutation in VPS15 (PIK3R4) causes a ciliopathy and affects IFT20 release from the cis-Golgi.

Ciliopathies are a group of diseases that affect kidney and retina among other organs. Here, we identify a missense mutation in PIK3R4 (phosphoinositide 3-kinase regulatory subunit 4, named VPS15) in a family with a ciliopathy phenotype. Besides being required for trafficking and autophagy, we show that VPS15 regulates primary cilium length in human fibroblasts, as well as ciliary processes in zebrafish. Furthermore, we demonstrate its interaction with the golgin GM130 and its localization to the Golgi. The VPS15-R998Q patient mutation impairs Golgi trafficking functions in humanized yeast cells. Moreover, in VPS15-R998Q patient fibroblasts, the intraflagellar transport protein IFT20 is not localized to vesicles trafficking to the cilium but is restricted to the Golgi. Our findings suggest that at the Golgi, VPS15 and GM130 form a protein complex devoid of VPS34 to ensure the IFT20-dependent sorting and transport of membrane proteins from the cis-Golgi to the primary cilium.

[Bardet-Biedl syndrome: cilia and obesity - from genes to integrative approaches]. / Syndrome de Bardet-Biedl: cils et obésité - de la génétique aux approches intégratives.

The primary cilium is a specialized organelle, present at the surface of most eukaryotic cells, whose main function is to detect, integrate and transmit intra- and extra-cellular signals. Its dysfunction usually results in a group of severe clinical manifestations nowadays termed ciliopathies. The latter can be of syndromic nature with multi-organ dysfunctions and can also be associated with a morbid obese phenotype, like it is the case in the iconic ciliopathy, the Bardet Biedl syndrome (BBS). This review will discuss the contribution of the unique context offered by the emblematic BBS for understanding the mechanisms leading to obesity via the involvement of the primary cilium together with identification of novel molecular players and signaling pathways it has helped to highlight. In the current context of translational medicine and system biology, this article will also discuss the potential benefits and challenges posed by these techniques via multi-level approaches to better dissect the underlying mechanisms leading to the complex condition of obesity.

Exome sequencing of Bardet-Biedl syndrome patient identifies a null mutation in the BBSome subunit BBIP1 (BBS18).

BACKGROUND: Bardet-Biedl syndrome (BBS) is a recessive and genetically heterogeneous ciliopathy characterised by retinitis pigmentosa, obesity, kidney dysfunction, postaxial polydactyly, behavioural dysfunction and hypogonadism. 7 of the 17 BBS gene products identified to date assemble together with the protein BBIP1/BBIP10 into the BBSome, a protein complex that ferries signalling receptors to and from cilia. METHODS AND RESULTS: Exome sequencing performed on a sporadic BBS case revealed for the first time a homozygous stop mutation (NM_001195306: c.173T>G, p.Leu58*) in the BBIP1 gene. This mutation is pathogenic since no BBIP1 protein could be detected in fibroblasts from the patient, and BBIP1[Leu58*] is unable to associate with the BBSome subunit BBS4. CONCLUSIONS: These findings identify BBIP1 as the 18th BBS gene (BBS18) and suggest that BBSome assembly may represent a unifying pathomechanism for BBS.