Alba Marino (1), Capucine Mayoud (1), Anna-Sophie Fiston-Lavier (1,2)

(1) ISEM, Univ Montpellier, CNRS, IRD, Montpellier, France

(2) Institut Universitaire de France

Biodiversity is the bedrock of many ecosystem services fundamental to human society. Acquiring genome-level information appears increasingly important for a deeper understanding of biodiversity and to plan conservation actions for endangered species (Lewin et al. 2022). Consortia such as the Vertebrate Genomes Project (VGP; Rhie et al. 2021) and the European Reference Genome Atlas (ERGA; Formenti et al. 2022) have been undertaken to coordinate global efforts toward sequencing of all the existing vertebrate and European eukaryotic species, respectively. Indeed, generating genome-scale data across such a wide taxonomic range presents significant challenges—not least the development and long-term maintenance of computational tools and workflows that ensure both reproducibility and transparency.

Galaxy offers a user-friendly, web-based environment for executing complex pipelines in a reproducible way, as well as servers for data storage (Bray & Maier 2023). In this context, Larivière et al. (2024) present a major enhancement to reference genome assembly with the development of a scalable, accessible, and reproducible pipeline embedded within the Galaxy platform. The framework has been designed to democratize the production of high-quality genomes, in line with initiatives such as the Earth BioGenome Project (Lewin et al. 2022). It integrates six main stages, namely (1) k-mer genome profiling, (2) phased assembly construction, (3) artefactual duplication purging, (4) scaffolding, (5) decontamination, and (6) mitogenome assembly. The pipeline builds on the expertise of VGP (Rhie et al. 2021) and ERGA (Formenti et al. 2022), while incorporating recent advances in high-fidelity long-read sequencing technologies.

A key strength of the pipeline lies in the open availability and its modularity, which enables end-to-end processing from raw reads to curated assemblies while emphasizing reproducibility, transparency, and ease of use (Afgan et al. 2018). Another major advantage is the integration of quality control steps throughout the pipeline. Moreover, the system is designed to accommodate a wide range of input data types and is applicable to a broad spectrum of species (Larivière et al. 2024).

Several public Galaxy instances are available worldwide (e.g. in the USA: https://usegalaxy.org; in Europe: https://usegalaxy.eu; in Australia: https://usegalaxy.org.au). These platforms provide free access to computing resources for running complex workflows and analysing large datasets. Nonetheless, certain steps in genome assembly may require more memory (RAM) or processing power (CPU) than the instances can offer, thus demanding access to high-performance computing (HPC) environments. Although cloud execution is mentioned as a means of processing large amounts of data, the manuscript offers little detail on deployment costs or potential technical barriers. 

Beyond technical and financial considerations, the environmental impact of scaling up genome sequencing and assembly also deserves attention. As more projects are launched and reliance on cloud infrastructure increases, the demand for computing, data storage, and long-term archival will increase substantially. Such operations are energy-intensive and contribute significantly to the environmental footprint of computational biology (Lannelongue & Inouye 2023). While Larivière et al. (2024) rightly emphasize accessibility and scalability, the community must also consider sustainability strategies to limit the ecological impact of large-scale genome initiatives. 

The authors suggest that the pipeline can be adapted for non-vertebrate species, such as plants or fungi, by adjusting a few parameters (e.g. BUSCO clade selection). However, the pipeline has so far only been validated on vertebrate genomes. Its robustness across taxa with complex genomic features, such as extreme GC content, polyploidy, or high repeat density, will require further benchmarking. Finally, another challenge is keeping the pipeline up to date. The rapid evolution of genome assembly tools (Nurk et al. 2022) contrasts with the often slower update cycles of Galaxy workflows, raising concerns about maintaining best practice standards without active long-term governance. The pipeline would benefit from an additional step to compare the established Galaxy pipeline with new assembly tools better suited to data generating using the latest technologies.

In conclusion, Larivière et al. (2024) offer a vital step forward in making reference-quality genome assembly broadly accessible. It is now in the hands of the community to address the remaining open challenges, such as computational accessibility, broader taxonomic validation, environmental sustainability, and further proofing of the pipeline.

                         
References

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