Evidence map›Paper›PMID 42289653›Full record

ArticleBMC genomics2026

Evolutionary dynamics and molecular adaptation of Rift Valley fever virus across human and non-human outbreaks in Africa.

Isaac Emmanuel Omara, John Juma, Derek Tshiabuila, Graeme Dor, Eduan Wilkinson, Cheryl Baxter, Houriiyah Tegally, Monika Moir, Samuel O Oyola, Tulio de Oliveira

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Article in BMC genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Isaac Emmanuel OmaraCentre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa. 29860113@sun.ac.za.
John JumaInternational Livestock Research Institute (ILRI), Old Naivasha Road, Nairobi, Kenya.
Derek TshiabuilaCentre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.
Graeme DorCentre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.
Eduan WilkinsonCentre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.
Cheryl BaxterCentre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.
Houriiyah TegallyCentre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.
Monika MoirCentre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.
Samuel O OyolaInternational Livestock Research Institute (ILRI), Old Naivasha Road, Nairobi, Kenya.
Tulio de OliveiraCentre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRift Valley fever virus (RVFV) is an emerging zoonotic virus of major public health and veterinary concern across Africa. Although past genomic studies have focused on outbreak response and lineage classification, the molecular mechanisms driving viral persistence and adaptation remain poorly understood. This study aimed to identify RVFV protein-coding mutations and adaptive signatures across multiple epidemics and epizootics in Africa.

methodsThis retrospective genomic analysis examined 596 RVFV segment sequences retrieved from the NCBI Virus database, including L (n = 173), M (n = 196) and S (n = 227) sequences from 13 African countries across human and non-human hosts between 1944 and 2022. Following the identification of protein-coding mutations via Genome Detective and custom scripts, we performed phylogenetic reconstruction using IQ-TREE and host-state reconstruction to map cross-species transmission patterns and selection pressure analyses were conducted using codon-based models implemented in the Datamonkey platform. All data analyses and visualizations were performed using R software.

resultsA total of 7,339 protein-coding mutations were identified, ranging from 2-20 per isolate. RVFV isolates collected in South Africa, Kenya and Madagascar exhibited the highest genomic diversity. Comparative analysis revealed higher mutation burdens in the L and S segments than in the M segment, with broader diversity among non-human hosts. Phylogenetic reconstruction showed that human-derived sequences clustered within livestock and vector lineages, a pattern consistent with significant genetic bottlenecks during spillovers. Notably, host-state reconstruction identified livestock lineages as the primary source of human outbreaks. We identified seven recurrent amino acid mutations across the genome: N277S, N277D and S278N in the polymerase (L); I442S, I442V, V659A in the glycoproteins (M); and N133S in the NSs protein (S). FUBAR-supported signals consistent with diversifying selection were identified at corresponding codon sites, particularly within the polymerase and glycoprotein regions, highlighting candidate residues potentially associated with adaptive processes affecting replication efficiency and immune evasion.

conclusionOur findings demonstrate that RVFV evolution across Africa is geographically and temporally heterogeneous, with livestock infections identified as the primary driver of human outbreaks. While RVFV evolution is largely shaped by purifying selection, FUBAR analysis revealed a limited number of candidate codon sites under diversifying selection that may facilitate host-specific adaptation. These host-specific pressures likely contribute to adaptive substitutions that fine-tune polymerase function, alter glycoprotein antigenicity and enhance immune escape. Collectively, these results reveal the molecular mechanisms underpinning viral persistence and provide information to support the design of cross-protective vaccines.

Indexed as

Evolution, MolecularRift Valley FeverRift Valley fever virusAfricaAnimalsDisease OutbreaksGenome, ViralHumansMutationPhylogenyViral ProteinsViral ProteinsAdaptive evolutionAfrica OutbreaksDiversifying selectionEvolutionary dynamicsGenomic surveillancePhylogeneticsRift Valley fever virus

Identifiers

PMID42289653
PMCPMC13495268

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.