Leveraging European infrastructures to access 1 million human genomes by 2022.

Human genomics is undergoing a step change from being a predominantly research-driven activity to one driven through health care as many countries in Europe now have nascent precision medicine programmes. To maximize the value of the genomic data generated, these data will need to be shared between institutions and across countries. In recognition of this challenge, 21 European countries recently signed a declaration to transnationally share data on at least 1 million human genomes by 2022. In this Roadmap, we identify the challenges of data sharing across borders and demonstrate that European research infrastructures are well-positioned to support the rapid implementation of widespread genomic data access.

Author Correction: Leveraging European infrastructures to access 1 million human genomes by 2022.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Transportation as a Disease Vector in COVID-19: Border Mobility and Disease Spread.

More than a year after COVID-19 was declared a pandemic by the World Health Organization, the U.S.A. and Mexico rank first and fourth, respectively, with regard to the number of deaths. From March 2020, nonessential travelers were not allowed to cross the border into the U.S.A. from Mexico via international land ports of entry, which resulted in a more than 50% decrease in the number of people crossing the border. However, border communities still face a higher number of cases and faster community spread compared with those without international land ports of entry. This paper established an econometric model to understand the effects of cross-border mobility and other socioeconomic parameters on the speed of spread. The model was developed at the U.S. county level using data from all 3,141 counties in the U.S.A. Additionally, a follow-up U.S. county comparative analysis was developed to examine the significance of having a border crossing between the U.S.A. and Mexico for U.S. counties. The findings of the analysis revealed that the variables having a significant effect are as follows: population density; number of people per household; population in the 15-65 age group; median household income; mask use; number of visits to transit stations; number of visits to workplace; overall mobility; and having a border crossing to Mexico within county limits. The comparative analysis found that U.S. counties with border crossings have an average of 123 cases per 1,000 population whereas their counterparts without border crossings only have 90 cases per 1,000 population.

The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases.

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.

Maintenance Strategies for Industrial Multi-Stage Machines: The Study of a Thermoforming Machine.

The study of reliability, availability and control of industrial manufacturing machines is a constant challenge in the industrial environment. This paper compares the results offered by several maintenance strategies for multi-stage industrial manufacturing machines by analysing a real case of a multi-stage thermoforming machine. Specifically, two strategies based on preventive maintenance, Preventive Programming Maintenance (PPM) and Improve Preventive Programming Maintenance (IPPM) are compared with two new strategies based on predictive maintenance, namely Algorithm Life Optimisation Programming (ALOP) and Digital Behaviour Twin (DBT). The condition of machine components can be assessed with the latter two proposals (ALOP and DBT) using sensors and algorithms, thus providing a warning value for early decision-making before unexpected faults occur. The study shows that the ALOP and DBT models detect unexpected failures early enough, while the PPM and IPPM strategies warn of scheduled component replacement at the end of their life cycle. The ALOP and DBT strategies algorithms can also be valid for managing the maintenance of other multi-stage industrial manufacturing machines. The authors consider that the combination of preventive and predictive maintenance strategies may be an ideal approach because operating conditions affect the mechanical, electrical, electronic and pneumatic components of multi-stage industrial manufacturing machines differently.

Piezo1 is required for outflow tract and aortic valve development.

AIMS: During embryogenesis, the onset of circulatory blood flow generates a variety of hemodynamic forces which reciprocally induce changes in cardiovascular development and performance. It has been known for some time that these forces can be detected by as yet unknown mechanosensory systems which in turn promote cardiogenic events such as outflow tract and aortic valve development. PIEZO1 is a mechanosensitive ion channel present in endothelial cells where it serves to detect hemodynamic forces making it an ideal candidate to play a role during cardiac development. We sought to determine whether PIEZO1 is required for outflow tract and aortic valve development. METHODS AND RESULTS: By analysing heart development in zebrafish we have determined that piezo1 is expressed in the developing outflow tract where it serves to detect hemodynamic forces. Consequently, disrupting Piezo1 signalling leads to defective outflow tract and aortic valve development and indicates this gene may be involved in the etiology of congenital heart diseases. Based on these findings, we analysed genomic data generated from patients who suffer from left ventricular outflow tract obstructions (LVOTO) and identified 3 probands who each harboured potentially pathogenic variants in PIEZO1. Subsequent in vitro and in vivo assays indicates that these variants behave as dominant negatives leading to an inhibition of normal PIEZO1 mechanosensory activity. Expressing these dominant negative PIEZO1 variants in zebrafish endothelium leads to defective aortic valve development. CONCLUSION: These data indicate that the mechanosensitive ion channel piezo1 is required for outflow tract and aortic valve development.

Identification of a peripheral blood gene signature predicting aortic valve calcification.

Calcific aortic valve disease (CAVD) is a significant cause of illness and death worldwide. Identification of early predictive markers could help optimize patient management. RNA-sequencing was carried out on human fetal aortic valves at gestational weeks 9, 13, and 22 and on a case-control study with adult noncalcified and calcified bicuspid and tricuspid aortic valves. In dimension reduction and clustering analyses, diseased valves tended to cluster with fetal valves at week 9 rather than normal adult valves, suggesting that part of the disease program might be due to reiterated developmental processes. The analysis of groups of coregulated genes revealed predominant immune-metabolic signatures, including innate and adaptive immune responses involving lymphocyte T-cell metabolic adaptation. Cytokine and chemokine signaling, cell migration, and proliferation were all increased in CAVD, whereas oxidative phosphorylation and protein translation were decreased. Discrete immune-metabolic gene signatures were present at fetal stages and increased in adult controls, suggesting that these processes intensify throughout life and heighten in disease. Cellular stress response and neurodegeneration gene signatures were aberrantly expressed in CAVD, pointing to a mechanistic link between chronic inflammation and biological aging. Comparison of the valve RNA-sequencing data set with a case-control study of whole blood transcriptomes from asymptomatic individuals with early aortic valve calcification identified a highly predictive gene signature of CAVD and of moderate aortic valve calcification in overtly healthy individuals. These data deepen and broaden our understanding of the molecular basis of CAVD and identify a peripheral blood gene signature for the early detection of aortic valve calcification.

VarAFT: a variant annotation and filtration system for human next generation sequencing data.

With the rapidly developing high-throughput sequencing technologies known as next generation sequencing or NGS, our approach to gene hunting and diagnosis has drastically changed. In <10 years, these technologies have moved from gene panel to whole genome sequencing and from an exclusively research context to clinical practice. Today, the limit is not the sequencing of one, many or all genes but rather the data analysis. Consequently, the challenge is to rapidly and efficiently identify disease-causing mutations within millions of variants. To do so, we developed the VarAFT software to annotate and pinpoint human disease-causing mutations through access to multiple layers of information. VarAFT was designed both for research and clinical contexts and is accessible to all scientists, regardless of bioinformatics training. Data from multiple samples may be combined to address all Mendelian inheritance modes, cancers or population genetics. Optimized filtration parameters can be stored and re-applied to large datasets. In addition to classical annotations from dbNSFP, VarAFT contains unique features at the disease (OMIM), phenotypic (HPO), gene (Gene Ontology, pathways) and variation levels (predictions from UMD-Predictor and Human Splicing Finder) that can be combined to optimally select candidate pathogenic mutations. VarAFT is freely available at: http://varaft.eu.

Shared genetic predisposition in rheumatoid arthritis-interstitial lung disease and familial pulmonary fibrosis.

Despite its high prevalence and mortality, little is known about the pathogenesis of rheumatoid arthritis-associated interstitial lung disease (RA-ILD). Given that familial pulmonary fibrosis (FPF) and RA-ILD frequently share the usual pattern of interstitial pneumonia and common environmental risk factors, we hypothesised that the two diseases might share additional risk factors, including FPF-linked genes. Our aim was to identify coding mutations of FPF-risk genes associated with RA-ILD.We used whole exome sequencing (WES), followed by restricted analysis of a discrete number of FPF-linked genes and performed a burden test to assess the excess number of mutations in RA-ILD patients compared to controls.Among the 101 RA-ILD patients included, 12 (11.9%) had 13 WES-identified heterozygous mutations in the TERT, RTEL1, PARN or SFTPC coding regions. The burden test, based on 81 RA-ILD patients and 1010 controls of European ancestry, revealed an excess of TERT, RTEL1, PARN or SFTPC mutations in RA-ILD patients (OR 3.17, 95% CI 1.53-6.12; p=9.45×10-4). Telomeres were shorter in RA-ILD patients with a TERT, RTEL1 or PARN mutation than in controls (p=2.87×10-2).Our results support the contribution of FPF-linked genes to RA-ILD susceptibility.

A mutation in the Gardos channel is associated with hereditary xerocytosis.

The Gardos channel is a Ca(2+)-sensitive, intermediate conductance, potassium selective channel expressed in several tissues including erythrocytes and pancreas. In normal erythrocytes, it is involved in cell volume modification. Here, we report the identification of a dominantly inherited mutation in the Gardos channel in 2 unrelated families and its association with chronic hemolysis and dehydrated cells, also referred to as hereditary xerocytosis (HX). The affected individuals present chronic anemia that varies in severity. Their red cells exhibit a panel of various shape abnormalities such as elliptocytes, hemighosts, schizocytes, and very rare stomatocytic cells. The missense mutation concerns a highly conserved residue among species, located in the region interacting with Calmodulin and responsible for the channel opening and the K(+) efflux. Using 2-microelectrode experiments on Xenopus oocytes and patch-clamp electrophysiology on HEK293 cells, we demonstrated that the mutated channel exhibits a higher activity and a higher Ca(2+) sensitivity compared with the wild-type (WT) channel. The mutated channel remains sensitive to inhibition suggesting that treatment of this type of HX by a specific inhibitor of the Gardos channel could be considered. The identification of a KCNN4 mutation associated with chronic hemolysis constitutes the first report of a human disease caused by a defect of the Gardos channel.

Exome sequencing identifies recurrent BCOR alterations and the absence of KLF2, TNFAIP3 and MYD88 mutations in splenic diffuse red pulp small B-cell lymphoma.

Splenic diffuse red pulp lymphoma is an indolent small B-cell lymphoma recognized as a provisional entity in the World Health Organization 2008 classification. Its precise relationship to other related splenic B-cell lymphomas with frequent leukemic involvement or other lymphoproliferative disorders remains undetermined. We performed whole-exome sequencing to explore the genetic landscape of ten cases of splenic diffuse red pulp lymphoma using paired tumor and normal samples. A selection of 109 somatic mutations was then evaluated in a cohort including 42 samples of splenic diffuse red pulp lymphoma and compared to those identified in 46 samples of splenic marginal zone lymphoma and eight samples of hairy-cell leukemia. Recurrent mutations or losses in BCOR (the gene encoding the BCL6 corepressor) - frameshift (n=3), nonsense (n=2), splicing site (n=1), and copy number loss (n=4) - were identified in 10/42 samples of splenic diffuse red pulp lymphoma (24%), whereas only one frameshift mutation was identified in 46 cases of splenic marginal zone lymphoma (2%). Inversely, KLF2, TNFAIP3 and MYD88, common mutations in splenic marginal zone lymphoma, were rare (one KLF2 mutant in 42 samples; 2%) or absent (TNFAIP3 and MYD88) in splenic diffuse red pulp lymphoma. These findings define an original genetic profile of splenic diffuse red pulp lymphoma and suggest that the mechanisms of pathogenesis of this lymphoma are distinct from those of splenic marginal zone lymphoma and hairy-cell leukemia.

Neural crest regulates myogenesis through the transient activation of NOTCH.

How dynamic signalling and extensive tissue rearrangements interact to generate complex patterns and shapes during embryogenesis is poorly understood. Here we characterize the signalling events taking place during early morphogenesis of chick skeletal muscles. We show that muscle progenitors present in somites require the transient activation of NOTCH signalling to undergo terminal differentiation. The NOTCH ligand Delta1 is expressed in a mosaic pattern in neural crest cells that migrate past the somites. Gain and loss of Delta1 function in neural crest modifies NOTCH signalling in somites, which results in delayed or premature myogenesis. Our results indicate that the neural crest regulates early muscle formation by a unique mechanism that relies on the migration of Delta1-expressing neural crest cells to trigger the transient activation of NOTCH signalling in selected muscle progenitors. This dynamic signalling guarantees a balanced and progressive differentiation of the muscle progenitor pool.

How to Identify Pathogenic Mutations among All Those Variations: Variant Annotation and Filtration in the Genome Sequencing Era.

High-throughput sequencing technologies have become fundamental for the identification of disease-causing mutations in human genetic diseases both in research and clinical testing contexts. The cumulative number of genes linked to rare diseases is now close to 3,500 with more than 1,000 genes identified between 2010 and 2014 because of the early adoption of Exome Sequencing technologies. However, despite these encouraging figures, the success rate of clinical exome diagnosis remains low due to several factors including wrong variant annotation and nonoptimal filtration practices, which may lead to misinterpretation of disease-causing mutations. In this review, we describe the critical steps of variant annotation and filtration processes to highlight a handful of potential disease-causing mutations for downstream analysis. We report the key annotation elements to gather at multiple levels for each mutation, and which systems are designed to help in collecting this mandatory information. We describe the filtration options, their efficiency, and limits and provide a generic filtration workflow and highlight potential pitfalls through a use case.

UMD-Predictor: A High-Throughput Sequencing Compliant System for Pathogenicity Prediction of any Human cDNA Substitution.

Whole-exome sequencing (WES) is increasingly applied to research and clinical diagnosis of human diseases. It typically results in large amounts of genetic variations. Depending on the mode of inheritance, only one or two correspond to pathogenic mutations responsible for the disease and present in affected individuals. Therefore, it is crucial to filter out nonpathogenic variants and limit downstream analysis to a handful of candidate mutations. We have developed a new computational combinatorial system UMD-Predictor (http://umd-predictor.eu) to efficiently annotate cDNA substitutions of all human transcripts for their potential pathogenicity. It combines biochemical properties, impact on splicing signals, localization in protein domains, variation frequency in the global population, and conservation through the BLOSUM62 global substitution matrix and a protein-specific conservation among 100 species. We compared its accuracy with the seven most used and reliable prediction tools, using the largest reference variation datasets including more than 140,000 annotated variations. This system consistently demonstrated a better accuracy, specificity, Matthews correlation coefficient, diagnostic odds ratio, speed, and provided the shortest list of candidate mutations for WES. Webservices allow its implementation in any bioinformatics pipeline for next-generation sequencing analysis. It could benefit to a wide range of users and applications varying from gene discovery to clinical diagnosis.

Actionable Genes, Core Databases, and Locus-Specific Databases.

Adoption of next-generation sequencing (NGS) in a diagnostic context raises numerous questions with regard to identification and reports of secondary variants (SVs) in actionable genes. To better understand the whys and wherefores of these questioning, it is necessary to understand how they are selected during the filtering process and how their proportion can be estimated. It is likely that SVs are underestimated and that our capacity to label all true SVs can be improved. In this context, Locus-specific databases (LSDBs) can be key by providing a wealth of information and enabling classifying variants. We illustrate this issue by analyzing 318 SVs in 23 actionable genes involved in cancer susceptibility syndromes identified through sequencing of 572 participants selected for a range of atherosclerosis phenotypes. Among these 318 SVs, only 43.4% are reported in Human Gene Mutation Database (HGMD) Professional versus 71.4% in LSDB. In addition, 23.9% of HGMD Professional variants are reported as pathogenic versus 4.8% for LSDB. These data underline the benefits of LSDBs to annotate SVs and minimize overinterpretation of mutations thanks to their efficient curation process and collection of unpublished data.

WES/WGS Reporting of Mutations from Cardiovascular "Actionable" Genes in Clinical Practice: A Key Role for UMD Knowledgebases in the Era of Big Databases.

High-throughput next-generation sequencing such as whole-exome and whole-genome sequencing are being rapidly integrated into clinical practice. The use of these techniques leads to the identification of secondary variants for which decisions about the reporting or not to the patient need to be made. The American College of Medical Genetics and Genomics recently published recommendations for the reporting of these variants in clinical practice for 56 "actionable" genes. Among these, seven are involved in Marfan Syndrome And Related Disorders (MSARD) resulting from mutations of the FBN1, TGFBR1 and 2, ACTA2, SMAD3, MYH11 and MYLK genes. Here, we show that mutations collected in UMD databases for MSARD genes (UMD-MSARD) are rarely reported, including the most frequent ones, in global scale initiatives for variant annotation such as the NHLBI GO Exome Sequencing Project (ESP), the Exome Aggregation Consortium (ExAC), and ClinVar. The predicted pathogenic mutations reported in global scale initiatives but absent in locus-specific databases (LSDBs) mainly correspond to rare events. UMD-MSARD databases are therefore the only resources providing access to the full spectrum of known pathogenic mutations. They are the most comprehensive resources for clinicians and geneticists to interpret MSARD-related variations not only primary variants but also secondary variants.

BRCA Share: A Collection of Clinical BRCA Gene Variants.

As next-generation sequencing increases access to human genetic variation, the challenge of determining clinical significance of variants becomes ever more acute. Germline variants in the BRCA1 and BRCA2 genes can confer substantial lifetime risk of breast and ovarian cancer. Assessment of variant pathogenicity is a vital part of clinical genetic testing for these genes. A database of clinical observations of BRCA variants is a critical resource in that process. This article describes BRCA Share™, a database created by a unique international alliance of academic centers and commercial testing laboratories. By integrating the content of the Universal Mutation Database generated by the French Unicancer Genetic Group with the testing results of two large commercial laboratories, Quest Diagnostics and Laboratory Corporation of America (LabCorp), BRCA Share™ has assembled one of the largest publicly accessible collections of BRCA variants currently available. Although access is available to academic researchers without charge, commercial participants in the project are required to pay a support fee and contribute their data. The fees fund the ongoing curation effort, as well as planned experiments to functionally characterize variants of uncertain significance. BRCA Share™ databases can therefore be considered as models of successful data sharing between private companies and the academic world.

The king cobra genome reveals dynamic gene evolution and adaptation in the snake venom system.

Snakes are limbless predators, and many species use venom to help overpower relatively large, agile prey. Snake venoms are complex protein mixtures encoded by several multilocus gene families that function synergistically to cause incapacitation. To examine venom evolution, we sequenced and interrogated the genome of a venomous snake, the king cobra (Ophiophagus hannah), and compared it, together with our unique transcriptome, microRNA, and proteome datasets from this species, with data from other vertebrates. In contrast to the platypus, the only other venomous vertebrate with a sequenced genome, we find that snake toxin genes evolve through several distinct co-option mechanisms and exhibit surprisingly variable levels of gene duplication and directional selection that correlate with their functional importance in prey capture. The enigmatic accessory venom gland shows a very different pattern of toxin gene expression from the main venom gland and seems to have recruited toxin-like lectin genes repeatedly for new nontoxic functions. In addition, tissue-specific microRNA analyses suggested the co-option of core genetic regulatory components of the venom secretory system from a pancreatic origin. Although the king cobra is limbless, we recovered coding sequences for all Hox genes involved in amniote limb development, with the exception of Hoxd12. Our results provide a unique view of the origin and evolution of snake venom and reveal multiple genome-level adaptive responses to natural selection in this complex biological weapon system. More generally, they provide insight into mechanisms of protein evolution under strong selection.

The TREAT-NMD DMD Global Database: analysis of more than 7,000 Duchenne muscular dystrophy mutations.

Analyzing the type and frequency of patient-specific mutations that give rise to Duchenne muscular dystrophy (DMD) is an invaluable tool for diagnostics, basic scientific research, trial planning, and improved clinical care. Locus-specific databases allow for the collection, organization, storage, and analysis of genetic variants of disease. Here, we describe the development and analysis of the TREAT-NMD DMD Global database (http://umd.be/TREAT_DMD/). We analyzed genetic data for 7,149 DMD mutations held within the database. A total of 5,682 large mutations were observed (80% of total mutations), of which 4,894 (86%) were deletions (1 exon or larger) and 784 (14%) were duplications (1 exon or larger). There were 1,445 small mutations (smaller than 1 exon, 20% of all mutations), of which 358 (25%) were small deletions and 132 (9%) small insertions and 199 (14%) affected the splice sites. Point mutations totalled 756 (52% of small mutations) with 726 (50%) nonsense mutations and 30 (2%) missense mutations. Finally, 22 (0.3%) mid-intronic mutations were observed. In addition, mutations were identified within the database that would potentially benefit from novel genetic therapies for DMD including stop codon read-through therapies (10% of total mutations) and exon skipping therapy (80% of deletions and 55% of total mutations).

Identification of splicing defects caused by mutations in the dysferlin gene.

Missense, iso-semantic, and intronic mutations are challenging for interpretation, in particular for their impact in mRNA. Various tools such as the Human Splicing Finder (HSF) system could be used to predict the impact on splicing; however, no diagnosis result could rely on predictions alone, but requires functional testing. Here, we report an in vitro approach to study the impact of DYSF mutations on splicing. It was evaluated on a series of 45 DYSF mutations, both intronic and exonic. We confirmed splicing alterations for all intronic mutations localized in 5' or 3' splice sites. Then, we showed that DYSF missense mutations could also result in splicing defects: mutations c.463G>A and c.2641A>C abolished ESEs and led to exon skipping; mutations c.565C>G and c.1555G>A disrupted Exonic Splicing Enhancer (ESE), while concomitantly creating new 5' or 3' splice site leading to exonic out of frame deletions. We demonstrated that 20% of DYSF missense mutations have a strong impact on splicing. This minigene strategy is an efficient tool for the detection of splicing defects in dysferlinopathies, which could allow for a better comprehension of splicing defects due to mutations and could improve prediction tools evaluating splicing defects.