The landscape of human genomic diversity

The human genome encodes the history of our species, including migrations across continents, adaptations to climate and pathogen pressure, and the structures of diverse populations that have emerged over hundreds of thousands of years. The human genome is not any single population’s genome. It belongs in the deepest sense to a species that initially evolved in Africa, spread across every habitable environment on earth, and through that process generated a diversity of biological adaptations that we are only beginning to comprehend. Understanding this diversity is not merely an intellectual exercise, it is the foundation upon which equitable and globally relevant genomic medicine must be built.

Fortunately, the field of human genomics has increasingly recognised and embraced diversity as a key resource that can be leveraged to this end, rather than an obstacle to manage. The past decade has witnessed transformative advances in our capacity to characterise human genomic variation. Large-scale sequencing initiatives from the 1000 Genomes Project [1] to the NIH All of Us and TOPMed Programmes have expanded the catalogue of human variants into the billions, revealing the breadth of common and rare variation across the global population [1–4]. Improvements in long-read sequencing, pangenome graph representations, and imputation reference panels have further democratised access to high-resolution genomic data. These technological advancements, combined with the falling cost of whole-genome sequencing, have made it relatively feasible to conduct population-scale genomic studies in settings that were until recently beyond reach. This Collection in BMC Biology seeks to build on that momentum by highlighting research that values genetic diversity and promotes inclusive approaches in genomics.

Gaps in the genomic map

Despite the recent technological progress, the field retains a profound genomic imbalance. For instance, the GWAS Diversity Monitor [5] aims to track representation across all published GWAS studies: individuals of European descent comprised more than 87% of participants in genome-wide association studies (GWAS), while Africans who harbour the greatest genetic diversity of any continental group accounted for 0.16% only [5]. The consequences are far-reaching. The polygenic risk scores derived primarily from European cohorts perform poorly in non-European populations, drug targets identified in biased discovery datasets may be less effective across different genetic backgrounds, while individuals who stand to benefit most from precision medicine are those least represented in the research that underpins it [6, 7].

African and other underrepresented populations are not merely ‘missing data’. They constitute an invaluable scientific resource. The shorter linkage disequilibrium in African genomes offers finer-resolution mapping of causal variants. Environments characterised by intense pathogen exposure, nutritional transitions, and altitude have driven adaptive selection events that explain fundamental biology. The genetic architectures of metabolic, cardiovascular, and infectious diseases differ across ancestries in ways that, once understood, challenge and enrich universal disease models.

Challenges and opportunities

Efforts to increase diversity in genomic research face persistent structural and regulatory obstacles. Sequencing infrastructure is largely concentrated in wealthier nations, limiting access for underrepresented populations. Regulatory differences in biobanking and data sharing create hurdles for global collaboration, while intellectual property rules sometimes disadvantage communities whose genetic material forms the basis of significant discoveries. Academic incentives, which often prioritise novel findings over replication or expansion, have historically discouraged the development of inclusive reference datasets. Beyond these structural barriers, equity and inclusion in genomic research practice remain a critical and often under-acknowledged challenge. Communities that have historically contributed biological samples and data to research have frequently been excluded from the benefits of those discoveries, including access to resulting therapeutics, diagnostic tools, and clinical guidelines. Achieving genuine inclusion therefore requires moving beyond sample collection to ensure meaningful community engagement, local scientific leadership, and equitable benefit-sharing across the full research lifecycle. However, practical solutions are emerging. For example, the H3Africa consortium has established continent-wide networks for ethical sample collection and local governance, fostering capacity for large-scale genomic studies.

Actionable strategies have proven effective in overcoming these barriers. Partnerships, such as the Global Alliance for Genomics and Health [2], are harmonising international data-sharing standards, enabling researchers to collaborate securely and efficiently across borders. Successful interventions include the creation of imputation panels tailored for diverse populations, improving the accuracy of genetic studies. Advances in long-read have made it feasible to construct reference pangenomes [8], which serve as more inclusive benchmarks for research.

Real-world initiatives demonstrate tangible impact. Studies in African cohorts have uncovered genetic variants linked to diseases such as type 2 diabetes, hypertension, and HIV susceptibility, previously undetectable in European datasets. Whole genome studies conducted in Southeast Asia found positive selection genes associated to multiple phenotypes and the immune system that are distinct from African populations, [9, 10], suggesting parallel adaptive evolution occurred independently in different geographical regions in response to similar environmental pressures.

An invitation to the community

This Collection is open to researchers across all biological sciences working on diverse global populations: from the evolutionary biologist mapping selective sweeps across the African savanna, to the clinical geneticist building equitable polygenic risk scores for populations in South Asia. We want to hear from the computational biologist developing targeted ancestry-specific algorithms, the anthropologist integrating genomic and archaeological evidence, and the bioethicist designing community engagement frameworks that shift power as well as practice. Human genomic diversity is, by its nature, an interdisciplinary subject, and we welcome contributions that reflect that breadth.

We also encourage manuscripts that challenge prevailing assumptions about what ‘diversity’ means, about how ancestry is operationalised in genomic analyses, about the epistemic status of race in biomedical research, and about whose questions get to define the field’s agenda. Submissions that bring new frameworks to bear on established problems, or that propose methodological standards the field has yet to adopt, are especially welcome.

We seek original research and methods papers that advance understanding across several interconnected themes:

Population history, migration, and adaptation

Ancient DNA analyses using improved computational frameworks and expanded sampling, particularly from historically underrepresented regions of Africa, Southeast Asia, Oceania, and the Americas are revealing migration waves, population admixtures, and selective sweeps with unprecedented resolution.

Genomic technology and data infrastructure

The capacity to generate data has outpaced our ability to analyse and contextualise it, particularly in low- and middle-income countries. We welcome papers on sequencing methodology, imputation panels optimised for underrepresented populations, pangenome construction, and bioinformatic pipelines suited to diverse ancestries.

Diversity in genomic medicine and disease susceptibility

Translating genomic discovery into clinical benefit demands that we understand how allele frequencies, linkage disequilibrium structure, and gene-environment interactions vary across populations. We welcome work that interrogates the transferability of polygenic scores, elucidates ancestry-specific variant effects, or identifies novel disease loci through trans-ancestry analyses.

Equity and inclusion in genomic research practice

Diversity is not only a scientific imperative, but also an ethical one. We encourage contributions that present structured approaches and actionable strategies to promote more equitable research practices [3]

Computational genomics and new analytical frameworks

Many standard analytical tools were benchmarked on European-ancestry cohorts and may underperform when applied to other populations. Papers that develop, validate, or critically evaluate computational methods in the context of diverse ancestries from ancestry inference and admixture modelling to structural variant calling and multi-ancestry fine-mapping are encouraged.

Authors' contributions

S.F. wrote the draft. S.F., W.K. and J.I.K. revised the manuscript. All authors have read and agreed to the final content.

Funding

Not applicable.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

Not applicable.

Competing interests

Segun Fatumo, Wibhu Kutanan and I. King Jordan are Guest Editors for the Human Genomic Diversity Collection, but were not involved in the editorial process of this manuscript, including peer review. The manuscript was handled by a member of the journal’s editorial team.