Galaxy Training: A powerful framework for teaching!

There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis, and stewardship are still rarely taught in life science educational programs, resulting in a skills gap in many of the researchers tasked with analysing these big datasets. In order to address this skills gap and empower researchers to perform their own data analyses, the Galaxy Training Network (GTN) has previously developed the Galaxy Training Platform (https://training.galaxyproject.org), an open access, community-driven framework for the collection of FAIR (Findable, Accessible, Interoperable, Reusable) training materials for data analysis utilizing the user-friendly Galaxy framework as its primary data analysis platform. Since its inception, this training platform has thrived, with the number of tutorials and contributors growing rapidly, and the range of topics extending beyond life sciences to include topics such as climatology, cheminformatics, and machine learning. While initially aimed at supporting researchers directly, the GTN framework has proven to be an invaluable resource for educators as well. We have focused our efforts in recent years on adding increased support for this growing community of instructors. New features have been added to facilitate the use of the materials in a classroom setting, simplifying the contribution flow for new materials, and have added a set of train-the-trainer lessons. Here, we present the latest developments in the GTN project, aimed at facilitating the use of the Galaxy Training materials by educators, and its usage in different learning environments.

Interfacing Seurat with the R tidy universe.

MOTIVATION: Seurat is one of the most popular software suites for the analysis of single-cell RNA sequencing data. Considering the popularity of the tidyverse ecosystem, which offers a large set of data display, query, manipulation, integration and visualization utilities, a great opportunity exists to interface the Seurat object with the tidyverse. This interface gives the large data science community of tidyverse users the possibility to operate with familiar grammar. RESULTS: To provide Seurat with a tidyverse-oriented interface without compromising efficiency, we developed tidyseurat, a lightweight adapter to the tidyverse. Tidyseurat displays cell information as a tibble abstraction, allowing intuitively interfacing Seurat with dplyr, tidyr, ggplot2 and plotly packages powering efficient data manipulation, integration and visualization. Iterative analyses on data subsets are enabled by interfacing with the popular nest-map framework. AVAILABILITY AND IMPLEMENTATION: The software is freely available at cran.r-project.org/web/packages/tidyseurat and github.com/stemangiola/tidyseurat. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The RNA workbench 2.0: next generation RNA data analysis.

RNA has become one of the major research topics in molecular biology. As a central player in key processes regulating gene expression, RNA is in the focus of many efforts to decipher the pathways that govern the transition of genetic information to a fully functional cell. As more and more researchers join this endeavour, there is a rapidly growing demand for comprehensive collections of tools that cover the diverse layers of RNA-related research. However, increasing amounts of data, from diverse types of experiments, addressing different aspects of biological questions need to be consolidated and integrated into a single framework. Only then is it possible to connect findings from e.g. RNA-Seq experiments and methods for e.g. target predictions. To address these needs, we present the RNA Workbench 2.0 , an updated online resource for RNA related analysis. With the RNA Workbench we created a comprehensive set of analysis tools and workflows that enables researchers to analyze their data without the need for sophisticated command-line skills. This update takes the established framework to the next level, providing not only a containerized infrastructure for analysis, but also a ready-to-use platform for hands-on training, analysis, data exploration, and visualization. The new framework is available at https://rna.usegalaxy.eu , and login is free and open to all users. The containerized version can be found at https://github.com/bgruening/galaxy-rna-workbench.

Germline whole exome sequencing of a family with appendiceal mucinous tumours presenting with pseudomyxoma peritonei.

BACKGROUND: Familial cases of appendiceal mucinous tumours (AMTs) are extremely rare and the underlying genetic aetiology uncertain. We identified potential predisposing germline genetic variants in a father and daughter with AMTs presenting with pseudomyxoma peritonei (PMP) and correlated these with regions of loss of heterozygosity (LOH) in the tumours. METHODS: Through germline whole exome sequencing, we identified novel heterozygous loss-of-function (LoF) (i.e. nonsense, frameshift and essential splice site mutations) and missense variants shared between father and daughter, and validated all LoF variants, and missense variants with a Combined Annotation Dependent Depletion (CADD) scaled score of ≥10. Genome-wide copy number analysis was performed on tumour tissue from both individuals to identify regions of LOH. RESULTS: Fifteen novel variants in 15 genes were shared by the father and daughter, including a nonsense mutation in REEP5. None of these germline variants were located in tumour regions of LOH shared by the father and daughter. Four genes (EXOG, RANBP2, RANBP6 and TNFRSF1B) harboured missense variants that fell in a region of LOH in the tumour from the father only, but none showed somatic loss of the wild type allele in the tumour. The REEP5 gene was sequenced in 23 individuals with presumed sporadic AMTs or PMP; no LoF or rare missense germline variants were identified. CONCLUSION: Germline exome sequencing of a father and daughter with AMTs identified novel candidate predisposing genes. Further studies are required to clarify the role of these genes in familial AMTs.

Prevalence of PALB2 mutations in Australian familial breast cancer cases and controls.

INTRODUCTION: PALB2 is emerging as a high-penetrance breast cancer predisposition gene in the order of BRCA1 and BRCA2. However, large studies that have evaluated the full gene rather than just the most common variants in both cases and controls are required before all truncating variants can be included in familial breast cancer variant testing. METHODS: In this study we analyse almost 2000 breast cancer cases sourced from individuals referred to familial cancer clinics, thus representing typical cases presenting in clinical practice. These cases were compared to a similar number of population-based cancer-free controls. RESULTS: We identified a significant excess of truncating variants in cases (1.3 %) versus controls (0.2 %), including six novel variants (p = 0.0001; odds ratio (OR) 6.58, 95 % confidence interval (CI) 2.3-18.9). Three of the four control individuals carrying truncating variants had at least one relative with breast cancer. There was no excess of missense variants in cases overall, but the common c.1676A > G variant (rs152451) was significantly enriched in cases and may represent a low-penetrance polymorphism (p = 0.002; OR 1.24 (95 % CI 1.09-1.47). CONCLUSIONS: Our findings support truncating variants in PALB2 as high-penetrance breast cancer susceptibility alleles, and suggest that a common missense variant may also lead to a low level of increased breast cancer risk.

Exome sequencing identifies rare deleterious mutations in DNA repair genes FANCC and BLM as potential breast cancer susceptibility alleles.

Despite intensive efforts using linkage and candidate gene approaches, the genetic etiology for the majority of families with a multi-generational breast cancer predisposition is unknown. In this study, we used whole-exome sequencing of thirty-three individuals from 15 breast cancer families to identify potential predisposing genes. Our analysis identified families with heterozygous, deleterious mutations in the DNA repair genes FANCC and BLM, which are responsible for the autosomal recessive disorders Fanconi Anemia and Bloom syndrome. In total, screening of all exons in these genes in 438 breast cancer families identified three with truncating mutations in FANCC and two with truncating mutations in BLM. Additional screening of FANCC mutation hotspot exons identified one pathogenic mutation among an additional 957 breast cancer families. Importantly, none of the deleterious mutations were identified among 464 healthy controls and are not reported in the 1,000 Genomes data. Given the rarity of Fanconi Anemia and Bloom syndrome disorders among Caucasian populations, the finding of multiple deleterious mutations in these critical DNA repair genes among high-risk breast cancer families is intriguing and suggestive of a predisposing role. Our data demonstrate the utility of intra-family exome-sequencing approaches to uncover cancer predisposition genes, but highlight the major challenge of definitively validating candidates where the incidence of sporadic disease is high, germline mutations are not fully penetrant, and individual predisposition genes may only account for a tiny proportion of breast cancer families.

RNF43 is a tumour suppressor gene mutated in mucinous tumours of the ovary.

Mucinous carcinomas represent a distinct morphological subtype which can arise from several organ sites, including the ovary, and their genetic characteristics are largely under-described. Exome sequencing of 12 primary mucinous ovarian tumours identified RNF43 as the most frequently somatically mutated novel gene, secondary to KRAS and mutated at a frequency equal to that of TP53 and BRAF. Further screening of RNF43 in a larger cohort of ovarian tumours identified additional mutations, with a total frequency of 2/22 (9%) in mucinous ovarian borderline tumours and 6/29 (21%) in mucinous ovarian carcinomas. Seven mutations were predicted to truncate the protein and one missense mutation was predicted to be deleterious by in silico analysis. Six tumours had allelic imbalance at the RNF43 locus, with loss of the wild-type allele. The mutation spectrum strongly suggests that RNF43 is an important tumour suppressor gene in mucinous ovarian tumours, similar to its reported role in mucinous pancreatic precancerous cysts.

CONTRA: copy number analysis for targeted resequencing.

MOTIVATION: In light of the increasing adoption of targeted resequencing (TR) as a cost-effective strategy to identify disease-causing variants, a robust method for copy number variation (CNV) analysis is needed to maximize the value of this promising technology. RESULTS: We present a method for CNV detection for TR data, including whole-exome capture data. Our method calls copy number gains and losses for each target region based on normalized depth of coverage. Our key strategies include the use of base-level log-ratios to remove GC-content bias, correction for an imbalanced library size effect on log-ratios, and the estimation of log-ratio variations via binning and interpolation. Our methods are made available via CONTRA (COpy Number Targeted Resequencing Analysis), a software package that takes standard alignment formats (BAM/SAM) and outputs in variant call format (VCF4.0), for easy integration with other next-generation sequencing analysis packages. We assessed our methods using samples from seven different target enrichment assays, and evaluated our results using simulated data and real germline data with known CNV genotypes.

An international consensus on effective, inclusive, and career-spanning short-format training in the life sciences and beyond.

Science, technology, engineering, mathematics, and medicine (STEMM) fields change rapidly and are increasingly interdisciplinary. Commonly, STEMM practitioners use short-format training (SFT) such as workshops and short courses for upskilling and reskilling, but unaddressed challenges limit SFT's effectiveness and inclusiveness. Education researchers, students in SFT courses, and organizations have called for research and strategies that can strengthen SFT in terms of effectiveness, inclusiveness, and accessibility across multiple dimensions. This paper describes the project that resulted in a consensus set of 14 actionable recommendations to systematically strengthen SFT. A diverse international group of 30 experts in education, accessibility, and life sciences came together from 10 countries to develop recommendations that can help strengthen SFT globally. Participants, including representation from some of the largest life science training programs globally, assembled findings in the educational sciences and encompassed the experiences of several of the largest life science SFT programs. The 14 recommendations were derived through a Delphi method, where consensus was achieved in real time as the group completed a series of meetings and tasks designed to elicit specific recommendations. Recommendations cover the breadth of SFT contexts and stakeholder groups and include actions for instructors (e.g., make equity and inclusion an ethical obligation), programs (e.g., centralize infrastructure for assessment and evaluation), as well as organizations and funders (e.g., professionalize training SFT instructors; deploy SFT to counter inequity). Recommendations are aligned with a purpose-built framework-"The Bicycle Principles"-that prioritizes evidenced-based teaching, inclusiveness, and equity, as well as the ability to scale, share, and sustain SFT. We also describe how the Bicycle Principles and recommendations are consistent with educational change theories and can overcome systemic barriers to delivering consistently effective, inclusive, and career-spanning SFT.

RNA-Seq Data Analysis in Galaxy.

A complete RNA-Seq analysis involves the use of several different tools, with substantial software and computational requirements. The Galaxy platform simplifies the execution of such bioinformatics analyses by embedding the needed tools in its web interface, while also providing reproducibility. Here, we describe how to perform a reference-based RNA-Seq analysis using Galaxy, from data upload to visualization and functional enrichment analysis of differentially expressed genes.

tidybulk: an R tidy framework for modular transcriptomic data analysis.

Recently, efforts have been made toward the harmonization of transcriptomic data structures and workflows using the concept of data tidiness, to facilitate modularisation. We present tidybulk, a modular framework for bulk transcriptional analyses that introduces a tidy transcriptomic data structure paradigm and analysis grammar. Tidybulk covers a wide variety of analysis procedures and integrates a large ecosystem of publicly available analysis algorithms under a common framework. Tidybulk decreases coding burden, facilitates reproducibility, increases efficiency for expert users, lowers the learning curve for inexperienced users, and bridges transcriptional data analysis with the tidyverse. Tidybulk is available at R/Bioconductor bioconductor.org/packages/tidybulk .

Drug target prediction and prioritization: using orthology to predict essentiality in parasite genomes.

BACKGROUND: New drug targets are urgently needed for parasites of socio-economic importance. Genes that are essential for parasite survival are highly desirable targets, but information on these genes is lacking, as gene knockouts or knockdowns are difficult to perform in many species of parasites. We examined the applicability of large-scale essentiality information from four model eukaryotes, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus and Saccharomyces cerevisiae, to discover essential genes in each of their genomes. Parasite genes that lack orthologues in their host are desirable as selective targets, so we also examined prediction of essential genes within this subset. RESULTS: Cross-species analyses showed that the evolutionary conservation of genes and the presence of essential orthologues are each strong predictors of essentiality in eukaryotes. Absence of paralogues was also found to be a general predictor of increased relative essentiality. By combining several orthology and essentiality criteria one can select gene sets with up to a five-fold enrichment in essential genes compared with a random selection. We show how quantitative application of such criteria can be used to predict a ranked list of potential drug targets from Ancylostoma caninum and Haemonchus contortus--two blood-feeding strongylid nematodes, for which there are presently limited sequence data but no functional genomic tools. CONCLUSIONS: The present study demonstrates the utility of using orthology information from multiple, diverse eukaryotes to predict essential genes. The data also emphasize the challenge of identifying essential genes among those in a parasite that are absent from its host.

Central carbon metabolism of Leishmania parasites.

Leishmania spp. are sandfly-transmitted protozoa parasites that cause a spectrum of diseases in humans. Many enzymes involved in Leishmania central carbon metabolism differ from their equivalents in the mammalian host and are potential drug targets. In this review we summarize recent advances in our understanding of Leishmania central carbon metabolism, focusing on pathways of carbon utilization that are required for growth and pathogenesis in the mammalian host. While Leishmania central carbon metabolism shares many features in common with other pathogenic trypanosomatids, significant differences are also apparent. Leishmania parasites are also unusual in constitutively expressing most core metabolic pathways throughout their life cycle, a feature that may allow these parasites to exploit a range of different carbon sources (primarily sugars and amino acids) rapidly in both the insect vector and vertebrate host. Indeed, recent gene deletion studies suggest that mammal-infective stages are dependent on multiple carbon sources in vivo. The application of metabolomic approaches, outlined here, are likely to be important in defining aspects of central carbon metabolism that are essential at different stages of mammalian host infection.

Molecular comparison of pure ovarian fibroma with serous benign ovarian tumours.

OBJECTIVE: Ovarian fibromas and adenofibromas are rare ovarian tumours. They are benign tumours composed of spindle-like stromal cells (pure fibroma) or a mixture of fibroblast and epithelial components (adenofibroma). We have previously shown that 40% of benign serous ovarian tumours are likely primary fibromas due to the neoplastic alterations being restricted to the stromal compartment of these tumours. We further explore this finding by comparing benign serous tumours to pure fibromas. RESULTS: Performing copy number aberration (CNA) analysis on the stromal component of 45 benign serous tumours and 8 pure fibromas, we have again shown that trisomy of chromosome 12 is the most common aberration in ovarian fibromas. CNAs were more frequent in the pure fibromas than the benign serous tumours (88% vs 33%), however pure fibromas more frequently harboured more than one CNA event compared with benign serous tumours. As these extra CNA events observed in the pure fibromas were unique to this subset our data indicates a unique tumour evolution. Gene expression analysis on the two cohorts was unable to show gene expression changes that differed based on tumour subtype. Exome analysis did not reveal any recurrently mutated genes.

CDK13 cooperates with CDK12 to control global RNA polymerase II processivity.

The RNA polymerase II (POLII)-driven transcription cycle is tightly regulated at distinct checkpoints by cyclin-dependent kinases (CDKs) and their cognate cyclins. The molecular events underpinning transcriptional elongation, processivity, and the CDK-cyclin pair(s) involved remain poorly understood. Using CRISPR-Cas9 homology-directed repair, we generated analog-sensitive kinase variants of CDK12 and CDK13 to probe their individual and shared biological and molecular roles. Single inhibition of CDK12 or CDK13 induced transcriptional responses associated with cellular growth signaling pathways and/or DNA damage, with minimal effects on cell viability. In contrast, dual kinase inhibition potently induced cell death, which was associated with extensive genome-wide transcriptional changes including widespread use of alternative 3' polyadenylation sites. At the molecular level, dual kinase inhibition resulted in the loss of POLII CTD phosphorylation and greatly reduced POLII elongation rates and processivity. These data define substantial redundancy between CDK12 and CDK13 and identify both as fundamental regulators of global POLII processivity and transcription elongation.

A single-cell RNA-sequencing training and analysis suite using the Galaxy framework.

BACKGROUND: The vast ecosystem of single-cell RNA-sequencing tools has until recently been plagued by an excess of diverging analysis strategies, inconsistent file formats, and compatibility issues between different software suites. The uptake of 10x Genomics datasets has begun to calm this diversity, and the bioinformatics community leans once more towards the large computing requirements and the statistically driven methods needed to process and understand these ever-growing datasets. RESULTS: Here we outline several Galaxy workflows and learning resources for single-cell RNA-sequencing, with the aim of providing a comprehensive analysis environment paired with a thorough user learning experience that bridges the knowledge gap between the computational methods and the underlying cell biology. The Galaxy reproducible bioinformatics framework provides tools, workflows, and trainings that not only enable users to perform 1-click 10x preprocessing but also empower them to demultiplex raw sequencing from custom tagged and full-length sequencing protocols. The downstream analysis supports a range of high-quality interoperable suites separated into common stages of analysis: inspection, filtering, normalization, confounder removal, and clustering. The teaching resources cover concepts from computer science to cell biology. Access to all resources is provided at the singlecell.usegalaxy.eu portal. CONCLUSIONS: The reproducible and training-oriented Galaxy framework provides a sustainable high-performance computing environment for users to run flexible analyses on both 10x and alternative platforms. The tutorials from the Galaxy Training Network along with the frequent training workshops hosted by the Galaxy community provide a means for users to learn, publish, and teach single-cell RNA-sequencing analysis.

Circulating insulin-like growth factors and related binding proteins are selectively altered in amyotrophic lateral sclerosis and multiple sclerosis.

OBJECTIVE: To provide a detailed profile of the peripheral IGF system in the neurological conditions; amyotrophic lateral sclerosis (ALS), post polio syndrome (PPS) and multiple sclerosis (MS). To determine whether subsets of patients within the disease groups could be identified in whom one or more components of the IGF regulatory system are altered compared to healthy control subjects matched for age, sex and BMI. DESIGN: Three cohorts of patients were recruited, 28 with ALS, 18 with PPS and 23 with MS. Patients were individually matched to a healthy control based on sex, age (+/-3 yr), and BMI (+/-2.5 kg m(-2)). The concentration (ng/ml) of serum IGF-I, IGF-II, IGFBP-1, IGFBP-2 and IGFBP-3 and acid-labile subunit (microg/ml) was determined by IRMA. RESULTS: In ALS patients, there was an increase of 11% in [IGF(TOTAL)] (p=0.042) ([IGF(TOTAL)]=[IGF-I]+[IGF-II]) and [IGFBP-1] was decreased by 34% (p=0.050) compared to matched controls. In "surviving" ALS patients, defined as those ALS patients with long disease duration (+2 SD from the mean survival time for Irish patients post diagnosis), there was an increase in [IGF-I] 36% (p=0.032) and a large decrease in [IGFBP-1] -58% (p=0.020) compared to controls. These differences were not evident in pre-agonal ALS patients. The concentration of serum IGF-I was 38% (p=0.018), acid-labile subunit 17% (p=0.044) and IGFBP-2 43% (p=0.035) higher in MS patients compared to controls. When stratified for interferon-beta (IFN-beta) use, we observed an increase in serum [IGF-I] 52% (p=0.013) and [IGF(TOTAL)] 19% (p=0.043) in MS patients undergoing IFN-beta treatment, but MS patients not undergoing IFN-beta treatment had similar IGF and IGFBP concentration to controls. Serum [IGFBP-3] 18% (p=0.033), [IGFBP-2] 86% (p=0.015) and (acid-labile subunit) 33% (p=0.012) was also higher in IFN-beta patients compared to controls. Stratified by stage of disease the most significant increase in components of the peripheral IGF system was attributed to relapsing-remitting MS patients treated with IFN-beta. All components of the peripheral IGF system in PPS patients were similar to controls. CONCLUSIONS: The increase in circulating IGF-I and a reduction in regulatory binding protein IGFBP-1 in ALS patients with a "stable" disease profile suggest a potential change in peripheral IGF bioavailability in these subjects. In MS, we report a change in a number of components of the peripheral IGF system, the observed increase in IGF-I in patients treated with IFN-beta being of most significance as a potential therapeutic biomarker.

PathOS: a decision support system for reporting high throughput sequencing of cancers in clinical diagnostic laboratories.

BACKGROUND: The increasing affordability of DNA sequencing has allowed it to be widely deployed in pathology laboratories. However, this has exposed many issues with the analysis and reporting of variants for clinical diagnostic use. Implementing a high-throughput sequencing (NGS) clinical reporting system requires a diverse combination of capabilities, statistical methods to identify variants, global variant databases, a validated bioinformatics pipeline, an auditable laboratory workflow, reproducible clinical assays and quality control monitoring throughout. These capabilities must be packaged in software that integrates the disparate components into a useable system. RESULTS: To meet these needs, we developed a web-based application, PathOS, which takes variant data from a patient sample through to a clinical report. PathOS has been used operationally in the Peter MacCallum Cancer Centre for two years for the analysis, curation and reporting of genetic tests for cancer patients, as well as the curation of large-scale research studies. PathOS has also been deployed in cloud environments allowing multiple institutions to use separate, secure and customisable instances of the system. Increasingly, the bottleneck of variant curation is limiting the adoption of clinical sequencing for molecular diagnostics. PathOS is focused on providing clinical variant curators and pathology laboratories with a decision support system needed for personalised medicine. While the genesis of PathOS has been within cancer molecular diagnostics, the system is applicable to NGS clinical reporting generally. CONCLUSIONS: The widespread availability of genomic sequencers has highlighted the limited availability of software to support clinical decision-making in molecular pathology. PathOS is a system that has been developed and refined in a hospital laboratory context to meet the needs of clinical diagnostics. The software is available as a set of Docker images and source code at https://github.com/PapenfussLab/PathOS .

Genomic characterisation of Eµ-Myc mouse lymphomas identifies Bcor as a Myc co-operative tumour-suppressor gene.

The Eµ-Myc mouse is an extensively used model of MYC driven malignancy; however to date there has only been partial characterization of MYC co-operative mutations leading to spontaneous lymphomagenesis. Here we sequence spontaneously arising Eµ-Myc lymphomas to define transgene architecture, somatic mutations, and structural alterations. We identify frequent disruptive mutations in the PRC1-like component and BCL6-corepressor gene Bcor. Moreover, we find unexpected concomitant multigenic lesions involving Cdkn2a loss and other cancer genes including Nras, Kras and Bcor. These findings challenge the assumed two-hit model of Eµ-Myc lymphoma and demonstrate a functional in vivo role for Bcor in suppressing tumorigenesis.