The article, authored by a large consortium of researchers and laboratory practitioners working across the Global South, draws directly on lessons learned from regional capacity-building initiatives. Its central claim is deceptively simple: sustainable genomics capacity requires more than technology transfer. Shipping sequencers and reagents to a laboratory, the authors argue, does nothing to guarantee that the laboratory can sustain sequencing operations, interpret the results, or integrate them into clinical and public health decision-making. What matters instead is a human-centered approach built around the workflows and existing expertise of the people already running the laboratory.

This reframing matters because the traditional model of capacity building has often followed a predictable pattern. A funding agency or a high-income country partner donates equipment, runs a short training course, and departs. The sequencer may work for a few months, but without supply chains for reagents, without local bioinformaticians to analyze the data, without institutional commitment to maintain the infrastructure, and without a mandate from the health ministry to use genomic data in practice, the program quietly collapses. The new rules are designed to break that cycle by treating genomics capacity as a long-term institutional transformation rather than a one-time infusion of hardware.

The first cluster of rules emphasizes local context and strategic planning. Before any equipment is purchased, the authors argue, a laboratory should assess what genomic information its health system actually needs. A reference laboratory monitoring tuberculosis drug resistance has very different requirements from a hospital trying to identify pathogens causing neonatal sepsis, and both differ from a public health institute tracking viral outbreaks. Strategic planning means mapping the existing diagnostic landscape, identifying where genomics adds genuine value, and defining realistic goals that align with national health priorities rather than with the research agendas of external funders.

A second cluster of rules focuses on people. The authors stress that continuous learning must be woven into the fabric of the laboratory rather than delivered as occasional workshops. Bioinformatics skills, in particular, are a bottleneck: sequencing data are only useful if someone can assemble, quality-check, and interpret them. The rules call for building local teams that combine molecular biologists, bioinformaticians, clinicians, and data managers, and for creating career paths that retain trained staff rather than losing them to institutions abroad or to the private sector. Mentorship networks that connect laboratories across the region, allowing scientists to learn from peers facing the same constraints, are highlighted as a practical mechanism for keeping expertise circulating within the Global South.

Equitable collaboration forms the third pillar of the framework. The authors are explicit that partnerships between institutions in the Global South and high-income countries must move beyond extractive models in which samples or data flow outward and little capacity flows back. Instead, they advocate for collaborations in which local laboratories lead the science, co-author publications, control their own data, and negotiate terms that build durable infrastructure. The rules also emphasize South-South cooperation, meaning partnerships among laboratories within the Global South itself, which can be more contextually appropriate and less dependent on distant funders than traditional North-South arrangements.

The remaining rules address the practical mechanics of sustaining a genomics program once it exists. Supply chains for reagents and consumables are notoriously fragile in many low- and middle-income settings, and the authors recommend diversifying suppliers, maintaining buffer stocks, and standardizing protocols so that a laboratory is not hostage to a single vendor. Quality management systems, including participation in external quality assessment schemes, are presented as essential for ensuring that genomic results are reliable enough to inform clinical decisions. Data governance receives its own rule: laboratories need clear policies on how genomic data are stored, shared, and protected, particularly given the sensitivity of human genetic information and the importance of equitable data sharing during outbreaks.

Integration into health systems is the final and perhaps most consequential theme. The authors argue that genomics will only become routine if the results actually change decisions, whether a clinician choosing a treatment regimen, an epidemiologist deciding whether an outbreak cluster warrants investigation, or a ministry of health revising vaccination strategy. That requires more than producing sequences; it requires communication channels between the laboratory and the end users of the data, turnaround times fast enough to be actionable, and institutional recognition that genomic surveillance is a core public health function deserving sustained budget lines rather than short-term project funding.

The perspective is grounded in the experience of the REVIGET Consortium, a network of laboratories and researchers whose names on the author list span institutions across Brazil and partner countries in the Global South. Many of the co-authors work in public health laboratories that have themselves navigated the transition from research sequencing to routine diagnostic and surveillance genomics, and the rules reflect hard-won practical knowledge about what fails and what endures. The authors frame the ten rules not as a rigid checklist but as a roadmap that each laboratory must adapt to its own epidemiological context, funding environment, and institutional culture.

The timing of the publication is significant. The COVID-19 pandemic demonstrated both the power and the fragility of genomic surveillance in the Global South: some countries, notably South Africa and Brazil, built world-class sequencing capabilities that shaped global understanding of viral variants, while many others remained almost entirely dependent on sequencing performed abroad. As funding that surged during the pandemic recedes, the risk is that newly acquired capacity will atrophy. The ten rules offer a deliberate countermeasure, arguing that the moment to institutionalize genomics, to write it into national laboratory strategies, to train the next generation of local bioinformaticians, and to secure recurring financing, is now, before the momentum dissipates. If the framework succeeds, genomic technologies that today function mainly as research tools in low- and middle-income countries could become as unremarkable and as indispensable as a complete blood count, quietly informing diagnosis, surveillance, and decision-making in every public health laboratory that needs them.

Subject of Research: Building sustainable genomics capacity for routine laboratory practice in the Global South

Article Title: Ten simple rules to build genomics capacity for routine laboratory practice in the Global South

Article References: Conceição, E. C., Sharma, A., Marcon, D. J., Ribeiro, L. R., dos Santos, D. K. C., Freitas, L. E. D. O., Souza, A. B., de Jesus, H. N. R., Lourenço, M. C. D. S., Andrade, V. D. G. D., de Oliveira, M. A. A., Ramos, T. C. A., Mesquita Cavalcante, Í. J., de Melo, A. L. E. S., Ismail, N., de Oliveira, T., Warren, R. M., Ferreira, A. A., Bessa, T. C. B., … REVIGET Consortium (2026). Ten simple rules to build genomics capacity for routine laboratory practice in the Global South. PLOS Computational Biology, 22(10), e1014863. https://doi.org/10.1371/journal.pcbi.1014863

Image Credits: AI Generated

DOI: 10.1371/journal.pcbi.1014863

Keywords: genomics, Global South, capacity building, public health laboratories, low- and middle-income countries, bioinformatics, diagnostics, surveillance, equitable collaboration, health systems, PLOS Computational Biology, REVIGET Consortium