Geographical variation drives adaptive equilibrium of the P. falciparum sickle-associated mutations

Python, A.; Forster, A. J.; Todd, P.; Niare, K.; Conrad, M.; Ishengoma, D. S.; Amenga-Etego, L. N.; Lian, J.; Liu, B.; Yan, Y.; Liang, J.; Khan, M. M.; Zheng, J.; Bailey, J.; Conway, D. J.; Mentzer, A. J.; Amambua-Ngwa, A.; Leffler, E. M.; Williams, T. N.; Band, G.

doi:10.1101/2025.08.31.672853

Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.08.31.672853

Geographical variation drives adaptive equilibrium of the P. falciparum sickle-associated mutations

View original source ↗Export metadata ↓

Abstract

The recent discovery of genetic mutations in Plasmodium falciparum--the most lethal malaria parasite--that enable it to overcome the protective effects of sickle cell trait, raises fundamental questions about the underlying biological and evolutionary interactions. Here we develop a geostatistical model to compare sickle haemoglobin genotype frequencies to the Plasmodium falciparum sickle-associated alleles across global populations, and find a robust association at multiple geographical scales, implying that sickle drives positive selection for these parasite mutations. A model of parasite evolution and an analysis of local haplotype patterns suggest that key features of these mutations - that they are polymorphic in all African populations and are mutually correlated despite lying in different genome regions - are caused by geographical variation in selection pressure, and that the alleles may have been maintained by balancing selection over timescales comparable to the age of the sickle mutation itself. The predicted impact of this host-parasite interaction on disease outcomes varies widely across populations, and functional data are needed to discover the biological mechanisms involved.

Explore related subjects

genetics Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Python, A., Forster, A. J., Todd, P., Niare, K., Conrad, M., Ishengoma, D. S., Amenga-Etego, L. N., Lian, J., Liu, B., Yan, Y., Liang, J., Khan, M. M., Zheng, J., Bailey, J., Conway, D. J., Mentzer, A. J., Amambua-Ngwa, A., Leffler, E. M., Williams, T. N., Band, G.. 2025-09-04. Geographical variation drives adaptive equilibrium of the P. falciparum sickle-associated mutations. https://doi.org/10.1101/2025.08.31.672853

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Generation of a transgenic cephalopod

Coleoid cephalopods (cuttlefish, octopus, and squid) are marine mollusks with elaborate nervous systems that support a diverse repertoire of complex behaviors. These include the neural control of the color, pattern, and texture of the skin, facilitating both adaptive camouflage and innate patterning that may reflect internal state. The development of transgenic cephalopods expressing fluorescent proteins, optogenetic actuators, and reporters of neural activity would contribute a new and important technology to cephalopod biology. The generation of transgenic cephalopods, however, has remained a major challenge. Here, we report the development of stable transgenic dwarf cuttlefish (Ascarosepion bandense) expressing ubiquitous nuclear-localized mScarlet, a red fluorescent protein. We evaluated multiple strategies for transgenesis, and established cuttlefish lines using both CRISPR and the transposons Sleeping Beauty and Minos. The stable expression of transgenes enabled live imaging of cell dynamics during embryonic development. The Minos transposon emerged as the most efficient transgenesis strategy and is adaptable to promoters and transgenes of choice. These strategies now enable the generation of diverse genetic tools for mechanistic studies of cephalopod biology.

genetics↗

bioRxiv2026

Large language model-based bibliometric evaluation of population descriptors in human genetics

As the use of population descriptors such as race, ethnicity, and ancestry have become increasingly common in modern genetics research, there have been growing calls to critically examine their use. Most notably, in 2023, the National Academies of Science, Engineering, and Medicine (NASEM) published a report titled Using Population Descriptors in Genetics and Genomics Research: A New Framework for an Evolving Field, which included eight specific and actionable recommendations for researchers to implement the ethical and accurate use of population descriptors in genetic research. Here, we use the 2023 NASEM report as a benchmark to analyze the use of population descriptors in genome-wide association studies (GWAS). We develop a general toolkit for large language model-based bibliometrics, operationalize the report's recommendations into an evaluation framework, and apply this framework to evaluate all 4,007 papers from the GWAS Catalog published between 2007 and 2025 with full text available on PubMedCentral. We find significant improvements in adherence to NASEM report recommendations over time. However, most improvements predate the publication of the NASEM report itself, suggesting the report functioned primarily as a synthesis of existing best practices rather than a catalyst for change. We conclude by highlighting opportunities for growth in the field of human genetics.

genetics↗

bioRxiv2026

Mitigating biases of rescaling in forward-in-time population genetic simulations

Forward-in-time population genetic simulations are widely used in evolutionary analyses, but simulating large populations and long genomic regions remains computationally demanding. To reduce this cost, parameter rescaling is widely employed, in which the original evolutionary process is approximated by one with a smaller population size and fewer generations. Recently, several studies using the SLiM simulator have raised concerns about the accuracy of this rescaling approach. In this study, we show that many of the biases reported in these studies can be mitigated by using a different simulation algorithm. These results reveal that the accuracy of parameter rescaling depends on how well the simulation algorithm preserves diffusion-limit properties under rescaling.

genetics↗