Background Malaria remains a significant global health concern, with Plasmodium falciparum being the most dangerous of the malaria-causing parasites. Sierra Leone, with year-round transmission of malaria, continues to experience high infection rates, largely due to P. falciparum. Although genomic databases have provided valuable insights into malaria transmission patterns, drug resistance, and population structure, data from Sierra Leone has been limited. This study aims to build on our previous report by incorporating new samples and providing a more comprehensive genomic analysis of P. falciparum in Sierra Leone, with a particular focus on genetic diversity, population structure, and drug resistance. Methods We collected P. falciparum samples from Freetown, Sierra Leone, between December 2022 and March 2023. A total of 35 samples underwent sequencing using the MGISEQ and Illumina platforms, resulting in high-coverage genomic data. Population structure was assessed using PCA, NJ trees, and STRUCTURE analysis, alongside comparisons with a global dataset from the pf3k project. Genetic diversity was evaluated using metrics such as <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\:\widehat\pi\)</EquationSource> </InlineEquation>, <InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\:\widehat{\theta}\)</EquationSource> </InlineEquation>ω, Tajima’s D, and iHS. XPEHH was used to examine selection pressures across different regions. Results Sequencing yielded over 376,450 high-quality SNPs across 35 Sierra Leone isolates, indicating substantial genetic variability. PCA, NJ trees, and STRUCTURE analysis revealed that the Sierra Leone isolates formed distinct clusters from both West African and Southeast Asian samples, with evidence of region-specific genetic adaptation. The low IBD we found suggested that infections were largely independent. Meanwhile the Tajima’s D and iHS analysis showed strong directional selection in genes associated with immune evasion and drug resistance genes, exhibiting ongoing evolutionary pressure due to therapeutic behavior. Conclusion This study provides us not only a genomic database but also a profile of P. falciparum in Sierra Leone, revealing high genetic diversity, strong selection pressure on drug resistance genes, and unique population structures. Our data emphasize the need for continued genomic surveillance to better manage malaria.

Comprehensive genomic study of Plasmodium falciparum in Sierra Leone: genetic variation and resistance patterns

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2025年7月1日

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Xin-jie Zhan,
Shen-Bo Chen,
Tian-yu Wang,
Yi-wen Duan,
Hai-Mo Shen,
Jun-Hu Chen,
Jing-jing Xie

摘要

Background

Malaria remains a significant global health concern, with Plasmodium falciparum being the most dangerous of the malaria-causing parasites. Sierra Leone, with year-round transmission of malaria, continues to experience high infection rates, largely due to P. falciparum. Although genomic databases have provided valuable insights into malaria transmission patterns, drug resistance, and population structure, data from Sierra Leone has been limited. This study aims to build on our previous report by incorporating new samples and providing a more comprehensive genomic analysis of P. falciparum in Sierra Leone, with a particular focus on genetic diversity, population structure, and drug resistance.

Methods

We collected P. falciparum samples from Freetown, Sierra Leone, between December 2022 and March 2023. A total of 35 samples underwent sequencing using the MGISEQ and Illumina platforms, resulting in high-coverage genomic data. Population structure was assessed using PCA, NJ trees, and STRUCTURE analysis, alongside comparisons with a global dataset from the pf3k project. Genetic diversity was evaluated using metrics such as \(\:\widehat\pi\) , \(\:\widehat{\theta}\) _ω, Tajima’s D, and iHS. XPEHH was used to examine selection pressures across different regions.

Results

Sequencing yielded over 376,450 high-quality SNPs across 35 Sierra Leone isolates, indicating substantial genetic variability. PCA, NJ trees, and STRUCTURE analysis revealed that the Sierra Leone isolates formed distinct clusters from both West African and Southeast Asian samples, with evidence of region-specific genetic adaptation. The low IBD we found suggested that infections were largely independent. Meanwhile the Tajima’s D and iHS analysis showed strong directional selection in genes associated with immune evasion and drug resistance genes, exhibiting ongoing evolutionary pressure due to therapeutic behavior.

Conclusion

This study provides us not only a genomic database but also a profile of P. falciparum in Sierra Leone, revealing high genetic diversity, strong selection pressure on drug resistance genes, and unique population structures. Our data emphasize the need for continued genomic surveillance to better manage malaria.