Expanding the Galaxy's reference data.

Summary: Properly and effectively managing reference datasets is an important task for many bioinformatics analyses. Refgenie is a reference asset management system that allows users to easily organize, retrieve and share such datasets. Here, we describe the integration of refgenie into the Galaxy platform. Server administrators are able to configure Galaxy to make use of reference datasets made available on a refgenie instance. In addition, a Galaxy Data Manager tool has been developed to provide a graphical interface to refgenie's remote reference retrieval functionality. A large collection of reference datasets has also been made available using the CVMFS (CernVM File System) repository from GalaxyProject.org, with mirrors across the USA, Canada, Europe and Australia, enabling easy use outside of Galaxy. Availability and implementation: The ability of Galaxy to use refgenie assets was added to the core Galaxy framework in version 22.01, which is available from https://github.com/galaxyproject/galaxy under the Academic Free License version 3.0. The refgenie Data Manager tool can be installed via the Galaxy ToolShed, with source code managed at https://github.com/BlankenbergLab/galaxy-tools-blankenberg/tree/main/data_managers/data_manager_refgenie_pull and released using an MIT license. Access to existing data is also available through CVMFS, with instructions at https://galaxyproject.org/admin/reference-data-repo/. No new data were generated or analyzed in support of this research.

Training Infrastructure as a Service.

BACKGROUND: Hands-on training, whether in bioinformatics or other domains, often requires significant technical resources and knowledge to set up and run. Instructors must have access to powerful compute infrastructure that can support resource-intensive jobs running efficiently. Often this is achieved using a private server where there is no contention for the queue. However, this places a significant prerequisite knowledge or labor barrier for instructors, who must spend time coordinating deployment and management of compute resources. Furthermore, with the increase of virtual and hybrid teaching, where learners are located in separate physical locations, it is difficult to track student progress as efficiently as during in-person courses. FINDINGS: Originally developed by Galaxy Europe and the Gallantries project, together with the Galaxy community, we have created Training Infrastructure-as-a-Service (TIaaS), aimed at providing user-friendly training infrastructure to the global training community. TIaaS provides dedicated training resources for Galaxy-based courses and events. Event organizers register their course, after which trainees are transparently placed in a private queue on the compute infrastructure, which ensures jobs complete quickly, even when the main queue is experiencing high wait times. A built-in dashboard allows instructors to monitor student progress. CONCLUSIONS: TIaaS provides a significant improvement for instructors and learners, as well as infrastructure administrators. The instructor dashboard makes remote events not only possible but also easy. Students experience continuity of learning, as all training happens on Galaxy, which they can continue to use after the event. In the past 60 months, 504 training events with over 24,000 learners have used this infrastructure for Galaxy training.

An accessible infrastructure for artificial intelligence using a Docker-based JupyterLab in Galaxy.

BACKGROUND: Artificial intelligence (AI) programs that train on large datasets require powerful compute infrastructure consisting of several CPU cores and GPUs. JupyterLab provides an excellent framework for developing AI programs, but it needs to be hosted on such an infrastructure to enable faster training of AI programs using parallel computing. FINDINGS: An open-source, docker-based, and GPU-enabled JupyterLab infrastructure is developed that runs on the public compute infrastructure of Galaxy Europe consisting of thousands of CPU cores, many GPUs, and several petabytes of storage to rapidly prototype and develop end-to-end AI projects. Using a JupyterLab notebook, long-running AI model training programs can also be executed remotely to create trained models, represented in open neural network exchange (ONNX) format, and other output datasets in Galaxy. Other features include Git integration for version control, the option of creating and executing pipelines of notebooks, and multiple dashboards and packages for monitoring compute resources and visualization, respectively. CONCLUSIONS: These features make JupyterLab in Galaxy Europe highly suitable for creating and managing AI projects. A recent scientific publication that predicts infected regions in COVID-19 computed tomography scan images is reproduced using various features of JupyterLab on Galaxy Europe. In addition, ColabFold, a faster implementation of AlphaFold2, is accessed in JupyterLab to predict the 3-dimensional structure of protein sequences. JupyterLab is accessible in 2 ways-one as an interactive Galaxy tool and the other by running the underlying Docker container. In both ways, long-running training can be executed on Galaxy's compute infrastructure. Scripts to create the Docker container are available under MIT license at https://github.com/usegalaxy-eu/gpu-jupyterlab-docker.

Exome sequencing in Crisponi/cold-induced sweating syndrome-like individuals reveals unpredicted alternative diagnoses.

Crisponi/cold-induced sweating syndrome (CS/CISS) is a rare autosomal recessive disorder characterized by a complex phenotype (hyperthermia and feeding difficulties in the neonatal period, followed by scoliosis and paradoxical sweating induced by cold since early childhood) and a high neonatal lethality. CS/CISS is a genetically heterogeneous disorder caused by mutations in CRLF1 (CS/CISS1), CLCF1 (CS/CISS2) and KLHL7 (CS/CISS-like). Here, a whole exome sequencing approach in individuals with CS/CISS-like phenotype with unknown molecular defect revealed unpredicted alternative diagnoses. This approach identified putative pathogenic variations in NALCN, MAGEL2 and SCN2A. They were already found implicated in the pathogenesis of other syndromes, respectively the congenital contractures of the limbs and face, hypotonia, and developmental delay syndrome, the Schaaf-Yang syndrome, and the early infantile epileptic encephalopathy-11 syndrome. These results suggest a high neonatal phenotypic overlap among these disorders and will be very helpful for clinicians. Genetic analysis of these genes should be considered for those cases with a suspected CS/CISS during neonatal period who were tested as mutation negative in the known CS/CISS genes, because an expedited and corrected diagnosis can improve patient management and can provide a specific clinical follow-up.

Confirmation of a new phenotype in an individual with a variant in the last part of exon 30 of CREBBP.

We report here a novel de novo missense variant affecting the last amino acid of exon 30 of CREBBP [NM_004380, c.5170G>A; p.(Glu1724Lys)] in a 17-year-old boy presenting mild intellectual disability and dysmorphisms but not resembling the phenotype of classical Rubinstein-Taybi syndrome. The patient showed a marked overweight from early infancy on and had cortical heterotopias. Recently, 22 individuals have been reported with missense mutations in the last part of exon 30 and the beginning of exon 31 of CREBBP, showing this new phenotype. This additional case further delineates the genotype-phenotype correlations within the molecular and phenotypic spectrum of variants in CREBBP and EP300.

Novel ANKRD11 gene mutation in an individual with a mild phenotype of KBG syndrome associated to a GEFS+ phenotypic spectrum: a case report.

BACKGROUND: KBG syndrome is a very rare autosomal dominant disorder, characterized by macrodontia, distinctive craniofacial findings, skeletal findings, post-natal short stature, and developmental delays, sometimes associated with seizures and EEG abnormalities. So far, there have been over 100 cases of KBG syndrome reported. CASE PRESENTATION: Here, we describe two sisters of a non-consanguineous family, both presenting generalized epilepsy with febrile seizures (GEFS+), and one with a more complex phenotype associated with mild intellectual disability, skeletal and dental anomalies. Whole exome sequencing (WES) analysis in all the family members revealed a heterozygous SCN9A mutation, p.(Lys655Arg), shared among the father and the two probands, and a novel de novo loss of function mutation in the ANKRD11 gene, p.(Tyr1715*), in the proband with the more complex phenotype. The reassessment of the phenotypic features confirmed that the patient fulfilled the proposed diagnostic criteria for KBG syndrome, although complicated by early-onset isolated febrile seizures. EEG abnormalities with or without seizures have been reported previously in some KBG cases. The shared variant, occurring in SCN9A, has been previously found in several individuals with GEFS+ and Dravet syndrome. CONCLUSIONS: This report describe a novel de novo variant in ANKRD11 causing a mild phenotype of KGB syndrome and further supports the association of monogenic pattern of SCN9A mutations with GEFS+. Our data expand the allelic spectrum of ANKRD11 mutations, providing the first Brazilian case of KBG syndrome. Furthermore, this study offers an example of how WES has been instrumental allowing us to better dissect the clinical phenotype under study, which is a multilocus variation aggregating in one proband, rather than a phenotypic expansion associated with a single genomic locus, underscoring the role of multiple rare variants at different loci in the etiology of clinical phenotypes making problematic the diagnostic path. The successful identification of the causal variant in a gene may not be sufficient, making it necessary to identify other variants that fully explain the clinical picture. The prevalence of blended phenotypes from multiple monogenic disorders is currently unknown and will require a systematic re-analysis of large WES datasets for proper diagnosis in daily practice.

Overexpression of the Cytokine BAFF and Autoimmunity Risk.

BACKGROUND: Genomewide association studies of autoimmune diseases have mapped hundreds of susceptibility regions in the genome. However, only for a few association signals has the causal gene been identified, and for even fewer have the causal variant and underlying mechanism been defined. Coincident associations of DNA variants affecting both the risk of autoimmune disease and quantitative immune variables provide an informative route to explore disease mechanisms and drug-targetable pathways. METHODS: Using case-control samples from Sardinia, Italy, we performed a genomewide association study in multiple sclerosis followed by TNFSF13B locus-specific association testing in systemic lupus erythematosus (SLE). Extensive phenotyping of quantitative immune variables, sequence-based fine mapping, cross-population and cross-phenotype analyses, and gene-expression studies were used to identify the causal variant and elucidate its mechanism of action. Signatures of positive selection were also investigated. RESULTS: A variant in TNFSF13B, encoding the cytokine and drug target B-cell activating factor (BAFF), was associated with multiple sclerosis as well as SLE. The disease-risk allele was also associated with up-regulated humoral immunity through increased levels of soluble BAFF, B lymphocytes, and immunoglobulins. The causal variant was identified: an insertion-deletion variant, GCTGT→A (in which A is the risk allele), yielded a shorter transcript that escaped microRNA inhibition and increased production of soluble BAFF, which in turn up-regulated humoral immunity. Population genetic signatures indicated that this autoimmunity variant has been evolutionarily advantageous, most likely by augmenting resistance to malaria. CONCLUSIONS: A TNFSF13B variant was associated with multiple sclerosis and SLE, and its effects were clarified at the population, cellular, and molecular levels. (Funded by the Italian Foundation for Multiple Sclerosis and others.).

Bi-allelic Mutations in KLHL7 Cause a Crisponi/CISS1-like Phenotype Associated with Early-Onset Retinitis Pigmentosa.

Crisponi syndrome (CS)/cold-induced sweating syndrome type 1 (CISS1) is a very rare autosomal-recessive disorder characterized by a complex phenotype with high neonatal lethality, associated with the following main clinical features: hyperthermia and feeding difficulties in the neonatal period, scoliosis, and paradoxical sweating induced by cold since early childhood. CS/CISS1 can be caused by mutations in cytokine receptor-like factor 1 (CRLF1). However, the physiopathological role of CRLF1 is still poorly understood. A subset of CS/CISS1 cases remain yet genetically unexplained after CRLF1 sequencing. In five of them, exome sequencing and targeted Sanger sequencing identified four homozygous disease-causing mutations in kelch-like family member 7 (KLHL7), affecting the Kelch domains of the protein. KLHL7 encodes a BTB-Kelch-related protein involved in the ubiquitination of target proteins for proteasome-mediated degradation. Mono-allelic substitutions in other domains of KLHL7 have been reported in three families affected by a late-onset form of autosomal-dominant retinitis pigmentosa. Retinitis pigmentosa was also present in two surviving children reported here carrying bi-allelic KLHL7 mutations. KLHL7 mutations are thus associated with a more severe phenotype in recessive than in dominant cases. Although these data further support the pathogenic role of KLHL7 mutations in a CS/CISS1-like phenotype, they do not explain all their clinical manifestations and highlight the high phenotypic heterogeneity associated with mutations in KLHL7.

Bacterial Genomic Data Analysis in the Next-Generation Sequencing Era.

Bacterial genome sequencing is now an affordable choice for many laboratories for applications in research, diagnostic, and clinical microbiology. Nowadays, an overabundance of tools is available for genomic data analysis. However, tools differ for algorithms, languages, hardware requirements, and user interface, and combining them as it is necessary for sequence data interpretation often requires (bio)informatics skills which can be difficult to find in many laboratories. In addition, multiple data sources, as well as exceedingly large dataset sizes, and increasingly computational complexity further challenge the accessibility, reproducibility, and transparency of the entire process. In this chapter we will cover the main bioinformatics steps required for a complete bacterial genome analysis using next-generation sequencing data, from the raw sequence data to assembled and annotated genomes. All the tools described are available in the Orione framework ( http://orione.crs4.it ), which uniquely combines in a transparent way the most used open source bioinformatics tools for microbiology, allowing microbiologist without any specific hardware or informatics skill to conduct data-intensive computational analyses from quality control to microbial gene annotation.

Tools and data services registry: a community effort to document bioinformatics resources.

Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand.Here we present a community-driven curation effort, supported by ELIXIR-the European infrastructure for biological information-that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners.As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools.

Simulating Cardiac Electrophysiology Using Unstructured All-Hexahedra Spectral Elements.

We discuss the application of the spectral element method to the monodomain and bidomain equations describing propagation of cardiac action potential. Models of cardiac electrophysiology consist of a system of partial differential equations coupled with a system of ordinary differential equations representing cell membrane dynamics. The solution of these equations requires solving multiple length scales due to the ratio of advection to diffusion that varies among the different equations. High order approximation of spectral elements provides greater flexibility in resolving multiple length scales. Furthermore, spectral elements are extremely efficient to model propagation phenomena on complex shapes using fewer degrees of freedom than its finite element equivalent (for the same level of accuracy). We illustrate a fully unstructured all-hexahedra approach implementation of the method and we apply it to the solution of full 3D monodomain and bidomain test cases. We discuss some key elements of the proposed approach on some selected benchmarks and on an anatomically based whole heart human computational model.

Genome-wide association study of susceptibility loci for breast cancer in Sardinian population.

BACKGROUND: Despite progress in identifying genes associated with breast cancer, many more risk loci exist. Genome-wide association analyses in genetically-homogeneous populations, such as that of Sardinia (Italy), could represent an additional approach to detect low penetrance alleles. METHODS: We performed a genome-wide association study comparing 1431 Sardinian patients with non-familial, BRCA1/2-mutation-negative breast cancer to 2171 healthy Sardinian blood donors. DNA was genotyped using GeneChip Human Mapping 500 K Arrays or Genome-Wide Human SNP Arrays 6.0. To increase genomic coverage, genotypes of additional SNPs were imputed using data from HapMap Phase II. After quality control filtering of genotype data, 1367 cases (9 men) and 1658 controls (1156 men) were analyzed on a total of 2,067,645 SNPs. RESULTS: Overall, 33 genomic regions (67 candidate SNPs) were associated with breast cancer risk at the p < 0(-6) level. Twenty of these regions contained defined genes, including one already associated with breast cancer risk: TOX3. With a lower threshold for preliminary significance to p < 10(-5), we identified 11 additional SNPs in FGFR2, a well-established breast cancer-associated gene. Ten candidate SNPs were selected, excluding those already associated with breast cancer, for technical validation as well as replication in 1668 samples from the same population. Only SNP rs345299, located in intron 1 of VAV3, remained suggestively associated (p-value, 1.16 x 10(-5)), but it did not associate with breast cancer risk in pooled data from two large, mixed-population cohorts. CONCLUSIONS: This study indicated the role of TOX3 and FGFR2 as breast cancer susceptibility genes in BRCA1/2-wild-type breast cancer patients from Sardinian population.

Buried in the Middle but Guilty: Intronic Mutations in the TCIRG1 Gene Cause Human Autosomal Recessive Osteopetrosis.

Autosomal recessive osteopetrosis (ARO) is a rare genetic bone disease with genotypic and phenotypic heterogeneity, sometimes translating into delayed diagnosis and treatment. In particular, cases of intermediate severity often constitute a diagnostic challenge and represent good candidates for exome sequencing. Here, we describe the tortuous path to identification of the molecular defect in two siblings, in which osteopetrosis diagnosed in early childhood followed a milder course, allowing them to reach the adult age in relatively good conditions with no specific therapy. No clearly pathogenic mutation was identified either with standard amplification and resequencing protocols or with exome sequencing analysis. While evaluating the possible impact of a 3'UTR variant on the TCIRG1 expression, we found a novel single nucleotide change buried in the middle of intron 15 of the TCIRG1 gene, about 150 nucleotides away from the closest canonical splice site. By sequencing a number of independent cDNA clones covering exons 14 to 17, we demonstrated that this mutation reduced splicing efficiency but did not completely abrogate the production of the normal transcript. Prompted by this finding, we sequenced the same genomic region in 33 patients from our unresolved ARO cohort and found three additional novel single nucleotide changes in a similar location and with a predicted disruptive effect on splicing, further confirmed in one of them at the transcript level. Overall, we identified an intronic region in TCIRG1 that seems to be particularly prone to splicing mutations, allowing the production of a small amount of protein sufficient to reduce the severity of the phenotype usually associated with TCIRG1 defects. On this basis, we would recommend including TCIRG1 not only in the molecular work-up of severe infantile osteopetrosis but also in intermediate cases and carefully evaluating the possible effects of intronic changes.

BioBlend.objects: metacomputing with Galaxy.

SUMMARY: BioBlend.objects is a new component of the BioBlend package, adding an object-oriented interface for the Galaxy REST-based application programming interface. It improves support for metacomputing on Galaxy entities by providing higher-level functionality and allowing users to more easily create programs to explore, query and create Galaxy datasets and workflows. AVAILABILITY AND IMPLEMENTATION: BioBlend.objects is available online at https://github.com/afgane/bioblend. The new object-oriented API is implemented by the galaxy/objects subpackage.

Orione, a web-based framework for NGS analysis in microbiology.

UNLABELLED: End-to-end next-generation sequencing microbiology data analysis requires a diversity of tools covering bacterial resequencing, de novo assembly, scaffolding, bacterial RNA-Seq, gene annotation and metagenomics. However, the construction of computational pipelines that use different software packages is difficult owing to a lack of interoperability, reproducibility and transparency. To overcome these limitations we present Orione, a Galaxy-based framework consisting of publicly available research software and specifically designed pipelines to build complex, reproducible workflows for next-generation sequencing microbiology data analysis. Enabling microbiology researchers to conduct their own custom analysis and data manipulation without software installation or programming, Orione provides new opportunities for data-intensive computational analyses in microbiology and metagenomics. AVAILABILITY AND IMPLEMENTATION: Orione is available online at http://orione.crs4.it.

The PARIGA server for real time filtering and analysis of reciprocal BLAST results.

BLAST-based similarity searches are commonly used in several applications involving both nucleotide and protein sequences. These applications span from simple tasks such as mapping sequences over a database to more complex procedures as clustering or annotation processes. When the amount of analysed data increases, manual inspection of BLAST results become a tedious procedure. Tools for parsing or filtering BLAST results for different purposes are then required. We describe here PARIGA (http://resources.bioinformatica.crs4.it/pariga/), a server that enables users to perform all-against-all BLAST searches on two sets of sequences selected by the user. Moreover, since it stores the two BLAST output in a python-serialized-objects database, results can be filtered according to several parameters in real-time fashion, without re-running the process and avoiding additional programming efforts. Results can be interrogated by the user using logical operations, for example to retrieve cases where two queries match same targets, or when sequences from the two datasets are reciprocal best hits, or when a query matches a target in multiple regions. The Pariga web server is designed to be a helpful tool for managing the results of sequence similarity searches. The design and implementation of the server renders all operations very fast and easy to use.

Variants within the immunoregulatory CBLB gene are associated with multiple sclerosis.

A genome-wide association scan of approximately 6.6 million genotyped or imputed variants in 882 Sardinian individuals with multiple sclerosis (cases) and 872 controls suggested association of CBLB gene variants with disease, which was confirmed in 1,775 cases and 2,005 controls (rs9657904, overall P = 1.60 x 10(-10), OR = 1.40). CBLB encodes a negative regulator of adaptive immune responses, and mice lacking the ortholog are prone to experimental autoimmune encephalomyelitis, the animal model of multiple sclerosis.