Genetic diversity and population structure of <i>Plasmodium falciparum</i> in Nigeria: insights from microsatellite loci analysis

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Abstract

Background

Malaria remains a public health burden especially in Nigeria. To develop new malaria control and elimination strategies or refine existing ones, understanding parasite population diversity and transmission patterns is crucial.

Methods

In this study, characterization of the parasite diversity and structure of Plasmodium falciparum isolates from 633 dried blood spot samples in Nigeria was carried out using 12 microsatellite loci of P. falciparum. These microsatellite loci were amplified via semi-nested polymerase chain reaction (PCR) and fragments were analysed using population genetic tools.

Results

Estimates of parasite genetic diversity, such as mean number of different alleles (13.52), effective alleles (7.13), allelic richness (11.15) and expected heterozygosity (0.804), were high. Overall linkage disequilibrium was weak (0.006, P < 0.001). Parasite population structure was low (Fst: 0.008–0.105, AMOVA: 0.039).

Conclusion

The high level of parasite genetic diversity and low population structuring in this study suggests that parasite populations circulating in Nigeria are homogenous. However, higher resolution methods, such as the 24 SNP barcode and whole genome sequencing, may capture more specific parasite genetic signatures circulating in the country. The results obtained can be used as a baseline for parasite genetic diversity and structure, aiding in the formulation of appropriate therapeutic and control strategies in Nigeria.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03734-x.

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Most cited references 45

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Inference of Population Structure Using Multilocus Genotype Data

Jonathan Pritchard, Matthew Stephens, Peter Donnelly … (2001)

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.

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STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method

Dent Earl, Bridgett vonHoldt (2012)

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Is Open Access

GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update

Rod Peakall, Peter E. Smouse (2012)

Summary: GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G′ST, G′′ST, Jost’s D est and F′ST through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised. Availability and implementation: GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx. Contact: rod.peakall@anu.edu.au

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Author and article information

Contributors

Christian T. Happi:

ORCID: http://orcid.org/0000-0002-3056-6705

happic@run.edu.ng

Journal

Journal ID (nlm-ta): Malar J

Journal ID (iso-abbrev): Malar J

Title: Malaria Journal

Publisher: BioMed Central (London )

ISSN (Electronic): 1475-2875

Publication date (Electronic): 26 May 2021

Publication date PMC-release: 26 May 2021

Publication date Collection: 2021

Volume: 20

Electronic Location Identifier: 236

Affiliations

[1 ]GRID grid.442553.1, ISNI 0000 0004 0622 6369, African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), , Redeemer’s University, ; Ede, Nigeria

[2 ]GRID grid.442553.1, ISNI 0000 0004 0622 6369, Department of Biological Sciences, Faculty of Natural Sciences, , Redeemer’s University, ; Ede, Nigeria

[3 ]GRID grid.411932.c, ISNI 0000 0004 1794 8359, Department of Biological Sciences, , Covenant University, ; Ota, Nigeria

[4 ]GRID grid.411541.4, Department of Paediatrics, , Imo State University Teaching Hospital, ; Orlu, Nigeria

[5 ]Department of Paediatrics, Federal Medical Centre, Yenagoa, Nigeria

[6 ]GRID grid.434433.7, ISNI 0000 0004 1764 1074, Case Management Unit, , National Malaria Elimination Programme, Federal Ministry of Health, ; Abuja, Nigeria

[7 ]Department of Paediatrics, Uthman Dan Fodio University, Sokoto, Nigeria

[8 ]GRID grid.10757.34, ISNI 0000 0001 2108 8257, Department of Paediatrics, , University of Nigeria Teaching Hospital, University of Nigeria, ; Nsukka, Nigeria

[9 ]GRID grid.413017.0, ISNI 0000 0000 9001 9645, Department of Paediatrics, , University of Maiduguri, ; Maiduguri, Nigeria

[10 ]GRID grid.411225.1, ISNI 0000 0004 1937 1493, Department of Paediatrics, , Ahmadu Bello University, ; Zaria, Nigeria

[11 ]GRID grid.411946.f, ISNI 0000 0004 1783 4052, Department of Paediatrics, , University of Jos Teaching Hospital, University of Jos, ; Jos, Nigeria

[12 ]GRID grid.412974.d, ISNI 0000 0001 0625 9425, Department of Paediatrics and Child Health, , University of Ilorin, ; Ilorin, Nigeria

[13 ]GRID grid.9582.6, ISNI 0000 0004 1794 5983, Institute of Medical Research and Training, College of Medicine, , University of Ibadan, ; Ibadan, Nigeria

[14 ]GRID grid.9582.6, ISNI 0000 0004 1794 5983, Department of Pharmacology and Therapeutics, College of Medicine, , University of Ibadan, ; Ibadan, Nigeria

Author information

Christian T. Happi http://orcid.org/0000-0002-3056-6705

Article

Publisher ID: 3734

DOI: 10.1186/s12936-021-03734-x

PMC ID: 8152046

PubMed ID: 34039364

SO-VID: a87dc296-16e9-43ff-bb0e-fb01af50ce21

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 6 October 2020

Date accepted : 13 April 2021

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100004421, World Bank Group;

Award ID: ACE019

Award Recipient : Onikepe A. Folarin

Funded by: FundRef http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;

Award ID: U01HG007480

Award ID: U54HG007480

Award Recipient : Onikepe A. Folarin

Funded by: U.S President’s Malaria Initiative

Custom metadata

ScienceOpen disciplines: Infectious disease & Microbiology

Keywords: malaria,plasmodium falciparum,genetic diversity,microsatellite,nigeria

Data availability:

ScienceOpen disciplines: Infectious disease & Microbiology

Keywords: malaria, plasmodium falciparum, genetic diversity, microsatellite, nigeria

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Genetic diversity and population structure of Plasmodium falciparum in Nigeria: insights from microsatellite loci analysis

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Supplementary Information

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Malaria vaccine development

Most cited references 45

Inference of Population Structure Using Multilocus Genotype Data

STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method

GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—an update

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Cited by 10

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