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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.

Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations. Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.

This is the open peer reviewers comments and recommendations regarding the submitted GigaScience article and/or dataset.

Summary MLL-AF4+ infant B cell acute lymphoblastic leukemia is characterized by an early onset and dismal survival. It initiates before birth, and very little is known about the early stages of the disease’s development. Using a conditional Mll-AF4-expressing mouse model in which fusion expression is targeted to the earliest definitive hematopoietic cells generated in the mouse embryo, we demonstrate that Mll-AF4 imparts enhanced B lymphoid potential and increases repopulation and self-renewal capacity during a putative pre-leukemic state. This occurs between embryonic days 12 and 14 and manifests itself most strongly in the lymphoid-primed multipotent progenitor population, thus pointing to a window of opportunity and a potential cell of origin. However, this state alone is insufficient to generate disease, with the mice succumbing to B cell lymphomas only after a long latency. Future analysis of the molecular details of this pre-leukemic state will shed light on additional events required for progression to acute leukemia., Graphical Abstract, Highlights • Mll-AF4 confers enhanced B cell potential and causes an expansion of pro-B cells • Mll-AF4 increases self-renewal potential • Mll-AF4 exerts its effects in a restricted developmental window • The LMPP is a potential cell of origin for Mll-AF4-associated disease, Barrett et al. describe the changes in pre-natal hematopoiesis induced by the Mll-AF4 oncogene in vivo. These include enhanced B lymphoid potential, an expansion of pro-B cells, and increased self-renewal. The authors identify the midgestation lymphoid-primed multipotent progenitor as a potential cell of origin.

The regulation of hematopoietic stem cell (HSC) emergence during development provides important information about the basic mechanisms of blood stem cell generation, expansion, and migration. We set out to investigate the role that cytokine signaling pathways play in these early processes and show here that the 2 cytokines interleukin 3 and thrombopoietin have the ability to expand hematopoietic stem and progenitor numbers by regulating their survival and proliferation. For this, they differentially use the Janus kinase (Jak2) and phosphatidylinositol 3-kinase (Pi3k) signaling pathways, with Jak2 mainly relaying the proproliferation signaling, whereas Pi3k mediates the survival signal. Furthermore, using Jak2-deficient embryos, we demonstrate that Jak2 is crucially required for the function of the first HSCs, whereas progenitors are less dependent on Jak2. The JAK2V617F mutation, which renders JAK2 constitutively active and has been linked to myeloproliferative neoplasms, was recently shown to compromise adult HSC function, negatively affecting their repopulation and self-renewal ability, partly through the accumulation of JAK2V617F-induced DNA damage. We report here that nascent HSCs are resistant to the JAK2V617F mutation and show no decrease in repopulation or self-renewal and no increase in DNA damage, even in the presence of 2 mutant copies. More importantly, this unique property of embryonic HSCs is stably maintained through ≥1 round of successive transplantations. In summary, our dissection of cytokine signaling in embryonic HSCs has uncovered unique properties of these cells that are of clinical importance.