Genetic Diversity and Population Structure of Plasmodium Falciparum in Nigeria: Insights From Microsatellites Loci Analysis

Genetic Diversity and Population Structure of Plasmodium Falciparum in Nigeria: Insights From Microsatellites Loci Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Genetic Diversity and Population Structure of Plasmodium Falciparum in Nigeria: Insights From Microsatellites Loci Analysis Fehintola Victoria Ajogbasile, Adeyemi T. Kayode, Kazeem O. Akano, and 18 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-90709/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version 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, we characterized parasite diversity and structure of Plasmodium falciparum isolates from 633 dried blood spot samples in Nigeria, using 12 microsatellite loci of P. falciparum . These microsatellites were amplified via semi-nested polymerase chain reaction (PCR) and fragments were analyzed using GeneMapper and GENALEX 6.5. Results Estimates of parasite diversity such as Mean complexity of infection (range: 1.71-2.66) and Expected heterozygosity (range: 0.76-0.82) were high, while parasite population sub-structuring was low (Analysis of molecular variance= 0.039, Fixation index= 0.038 and Linkage disequilibrium= 0.0219). Conclusion We conclude that the high level of genetic diversity and low population structuring in this study suggests that parasite populations circulating in Nigeria are homogenous. This implies that a uniform control strategy will be effective across the six geographical zones of Nigeria. The results obtained can be used as a baseline for parasite diversity and structure, aiding in the formulation of appropriate therapeutic and control strategies in Nigeria. Infectious Diseases Malaria Plasmodium falciparum Genetic diversity Microsatellite Nigeria Figures Figure 1 Figure 2 Background Although the incidence of malaria infections and malaria-associated mortality has reduced in many African countries [1, 2, 3], transmission continues in endemic regions despite intensified efforts towards prevention, control and eradication [4, 5]. This is due, in part, to the high genetic diversity of Plasmodium falciparum that contributes to increased transmission rate and spread of resistant parasites [6]. Therefore, understanding the extent of genetic diversity, transmission intensity, and parasite population structure in Nigeria - the most malaria burdened country, is essential if the goal of malaria control or elimination is to be achieved. Molecular techniques play important roles in the analyses of genetic diversity, transmission dynamics, and population structure of P. falciparum field isolates. Early molecular studies focused mostly on the use of polymorphic markers such as merozoite surface protein 1 ( msp -1) and merozoite surface protein 2 ( msp -2) and glutamate-rich protein (Glurp) to characterise falciparum genetic diversity and structure in Nigeria [7, 8, 9]. These markers were also useful in monitoring drug efficacy with regards to classification of recurrent falciparum parasitaemia as re-infection or recrudescent infection [6, 10, 11]. However, there have been contrasting reports of polymorphisms in msp-1 and msp-2 in earlier studies in Nigeria [6, 12, 13, 14] which is associated with the fact that these antigenic markers are often under intense immune pressure [15, 16, 17]. The genotyping results provided by these markers can therefore potentially lead to a masked and distorted view of the population structure and transmission patterns which may account for observed variations across parasite populations circulating in a given environment [6]. Microsatellites have been suggested to be better alternatives to msp-1, msp-2 and GLURP due to their abundance, putative neutrality and higher levels of polymorphisms [18]. This molecular technique remains one of the most efficient and reliable methods for analyzing the genetic diversity data of falciparum populations for epidemiological and drug efficacy purposes within countries and across continents [19]. In past studies of using microsatellite analyses, it was observed that parasites from areas of low malaria transmission [19] (<1% infection) have less genetic diversity but more population structure and greater linkage disequilibrium (i.e. more non-random association among alleles across multiple loci) [4, 19, 20, 21]. Contrary, in regions of high malaria transmission, individuals are more likely to be infected by more than one P . falciparum parasite thereby resulting in an increase in the rate of recombination and subsequently, high diverse population with low linkage disequilibrium [18, 19, 22]. Although, some studies report a deviation from the norm whereby high levels of heterozygosity (a measure of genetic diversity) is observed in several low transmission countries [18, 23, 24]. This suggests that a high level of heterozygosity may reflect past human demographic processes as opposed to recent epidemiological factors [25]. The objective of this study was to investigate the genetic diversity of circulating Plasmodium falciparum parasites and their population structures in Nigerian children 6-96months old with uncomplicated infections, treated with artemisinin-based combination therapies (ACTs). Methods Study site Filter papers containing dried blood spot (DBS) obtained from 633 children from nine Nigerian States covering all six geographical zones i.e., North-east : Adamawa State (n = 48), North-west : Sokoto State (n = 50), North-central : Kano (n = 100), Plateau (n = 100) and Kwara States (n = 58), South-west : Oyo State (n = 50), South-south : Bayelsa State (n = 45), and South-east : Enugu State (n = 100), Imo State (n = 82) with P. falciparum malaria infections on Day 0 were randomly selected for this study. These States are parts of sentinel sites for the National Malaria Elimination Program of the Federal Ministry of Health in Nigeria for the year 2014-2018. Study site Filter papers containing dried blood spot (DBS) obtained from 633 children from nine Nigerian States covering all six geographical zones i.e., North-east : Adamawa State (n = 48), North-west : Sokoto State (n = 50), North-central : Kano (n = 100), Plateau (n = 100) and Kwara States (n = 58), South-west : Oyo State (n = 50), South-south : Bayelsa State (n = 45), and South-east : Enugu State (n = 100), Imo State (n = 82) with P. falciparum malaria infections on Day 0 were randomly selected for this study. These States are parts of sentinel sites for the National Malaria Elimination Program of the Federal Ministry of Health in Nigeria for the year 2014-2018. Sample collection Two to three drops of finger-pricked blood samples were blotted on 3mm Whatman filter paper (Whatman International Limited, Maidstone, United Kingdom) before treatment initiation (Day 0). The blood samples impregnated on to filter papers were allowed to air-dry properly at room temperature, and dry blood spots (DBS) were kept in airtight envelopes with silica gel until analysed. DNA extraction DNA was extracted from DBS for parasite genetic diversity and population structure studies as previously described [26]. DNeasy Blood and Tissue extraction kit (Qiagen, Germany) was used to extract parasite DNA from DBS following the manufacturer's protocol. Plasmodium falciparum genotyping by microsatellite loci analysis Semi-nested PCR amplification of 12 P. falciparum microsatellite loci was done using a previously described protocol [17]. The 12 microsatellites loci were Poly A, PfG377, TA81, ARA2, TA87, TA40, TA42, 2490, TA1, TA60, TA109 and PfPk2 [27]. FAM, YAK YELLOW, and ATTO550N-labeled PCR products for the different loci amplified were pooled together (GeneScan™ 500, Applied Biosystems, Foster City, CA) for electrophoresis on the ABI 3500XL Genetic Analyzer at the African Centre of Excellence for the Genomics of Infectious Diseases (ACEGID), Redeemer’s University Ede, Osun State, Nigeria. Peakscanner (Applied Biosystems) and GeneMarker (Softgenetics) software were used for normalization across runs and automatic determination of allele length and peak heights in samples containing multiple alleles per locus. Minor alleles were scored when the minor peaks were ≥ 20% the height of the predominant allele in the isolate and with a relative fluorescent unit of at least 100. Data analysis Measures of parasite genetic diversity Complexity of infection (COI) The COI was computed as the number of alleles per microsatellite loci divided by the number of amplified samples per microsatellite loci. The mean COI per State was calculated as the average of all COI values per microsatellite loci. Parasite allelic frequency The allele frequencies, per locus were calculated using GENALEX 6.5 [28]. This frequency was calculated for each State involved in the study. Parasite allelic diversity The expected heterozygosity (He), which represents the probability of being infected by two parasites with different alleles at a given locus, was calculated using the formula: He = [(n/n−1) (1−Σp 2 )] - Equation 1 Where n is the number of isolates analysed, and p represents the frequency of each different allele at a locus [29]. He values range from 0 to 1. Values closer to 0 indicate little or no allelic diversity while values closer to 1 indicate high allelic diversity. Measures of parasite population differentiation Analysis of molecular variance (AMOVA) Inter- and intra-population variance was determined with analysis of molecular variance (AMOVA, i.e., ΦPT). ΦPT value of zero (0) is considered indicative of no genetic differentiation among populations. Fixation index (Fst) The population divergence was measured by calculating the fixation index (Fst) for all pairs of parasite population in each State. The software, GENALEX 6.5 was used to compute the Fst value. Principal component analysis (PCA) Principal component analysis (PCA) was performed with the online program, ClustVis [30] across all nine States and separately for each State. Linkage disequilibrium (LD) Linkage disequilibrium (LD) was calculated for all nine States and separately for each State using the standardized index of association, ( I S A ), (LIAN version 3.5 web interface) [31] and the majority allele at each locus in each infection. This index was calculated as ( I S A ) = (1/n – 1 ((VD / (VE) – 1) - Equation 2 Where VE is the expected variance of the n th number of loci for which two individuals differ. VD is the observed variance. Randomization test, previously described [32], was done to determine whether the ratio of VD/VE was significantly higher than 1. Results Demographics and baseline characteristics Overall, 329 (51.97%) were male and the mean age of all children included in the study was 48.4±15.8 months. Also, mean enrollment body temperature was 37.5±2.5 o C. Overall geometric asexual parasitemia was 16,219ᶙL -1 (range: 2003-198200). Parasite genetic diversity Complexity of infection (COI) and Mean complexity of Infection (mCOI) The mCOI recorded from the nine Nigerian States ranged from 1.71 in Sokoto (lowest) to 2.66 in Oyo (highest) (Table 1). The COI obtained using the TA42 locus across all States was low ( 2.16) were recorded (Table 1). Although mCOI observed in most (4 of 5) States in the Northern region were 2.0, there was no significant difference in mCOI values obtained in these regions (p>0.05). Table 1 : The COI and mCOI values of parasites in nine Nigerian States using 12 Microsatellites loci Loci Adamawa (n=48) Bayelsa (n=45) Enugu (n=100) Ibadan (n=50) Imo (n=82) Kano (n=100) Kwara (n=56) Sokoto (n=46) Plateau (n=100) Poly A 2.63 3.02 3.14 2.36 2.28 2.25 2.34 2.16 3.19 PfPK2 1.92 3.2 2.4 1.8 1.68 1.83 1.75 1.58 2.53 Ta81 1.88 1.78 4.17 2.9 1.69 1.64 2.1 1.81 2.52 ARA2 5.05 4.57 6.81 4.14 4.89 2.41 4.43 3.7 6.45 TA40 1.5 1.25 2.37 2.38 1.24 1.17 1.2 1.13 1.99 TA87 1.78 1.38 2.25 8.9 1.48 1.49 1.55 1.68 2.46 2490 1.21 1.27 1.78 1.17 1.2 2.02 1.36 1.48 1.64 TA1 1.7 1.84 3.01 2.04 1.74 2.35 1.86 1.56 2.29 TA42 1.1 1.2 1.28 1.28 1.11 1.17 1.12 1.03 1.13 PFG377 1.44 1.52 1.7 1.63 1.3 1.47 1.33 1.37 1.36 TA109 1.95 1.93 1.96 2 1.45 1.93 1.41 1.52 2.11 TA60 1.45 1.48 1.92 1.33 1.39 1.62 1.62 1.44 2.02 mCOI 1.97 2.04 2.73 2.66 1.79 1.78 1.84 1.71 2.47 Number of alleles, Allelic frequency and diversity The mean number of alleles (Na) observed ranged from 9.75 (Adamawa State) to 15.67 (Enugu State) and the mean number of effective alleles (Ne) observed ranged from 5.4 (Oyo State) to 8.2 (Enugu State) (Table 2). The allelic frequencies at each of the 12 loci in parasite populations obtained in each of the nine States are presented in additional file 1. The highest allelic frequencies in all nine States were observed in microsatellites loci TA40 (ranged from 200-220), TA42 (ranged from 182-183), Pf PK2 (ranged from 161-170), TA81 (ranged from 160-169), TA109 (ranged from 153-174), TA1 (ranged from 153-161), Poly A (ranged from 103-159), Pf G377 (103), TA87 (ranged from 90-106), 2490 (ranged from 80-83), ARA2 (ranged from 52-55), and TA60 ( Table 2: Number of different and effective alleles parasite populations according to study location State Adamawa (n=48) Bayelsa (n=45) Enugu (n=100) Ibadan (n=50) Imo (n=82) Kano (n=100) Kwara (n=56) Sokoto (n=46) Plateau (n=100) Locus Na Ne Na Ne Na Ne Na Ne Na Ne Na Ne Na Ne Na Ne Na Ne PolyA 24 17.6 20 12.4 31 19.2 21 14.5 25 9.7 33 17.2 23 13.1 30 14.7 21 12.7 PfPK2 12 7.4 14 7.1 13 6.6 11 6.6 11 5.9 13 7.3 10 6.7 12 6.1 12 7.4 TA81 11 6.9 15 6.6 19 10.2 15 6 13 5.9 16 5.9 10 6.2 14 6.9 11 6.2 ARA2 9 7.8 11 7 19 12.3 8 3.2 14 8.5 16 7.8 16 9 17 9.2 17 10.8 TA87 11 8.3 14 10.3 22 14.5 14 10.1 24 14.9 13 8.5 18 11.1 22 15.1 15 9.4 TA40 5 3.1 8 6.8 10 2.6 6 3 9 6.7 9 5.1 10 4 10 2.8 8 5.2 TA42 6 1.7 4 1.3 11 2.6 9 2.1 5 1.3 11 2.8 4 1.3 8 1.4 3 1.3 2490 5 2.6 6 2.7 7 3.9 7 3 8 3.2 10 4.2 8 3.6 10 4.3 5 2.6 TA1 10 5.8 13 6.6 24 12.4 7 2 13 4.2 19 11.8 12 5.4 15 5.9 13 4.9 PFG377 5 3 5 1.9 8 2.9 9 3.6 6 3.8 7 2.8 6 3.6 8 3.1 5 3.2 TA109 10 4.8 11 5.3 14 5.3 10 6.4 14 8.3 14 7.1 10 7.1 16 6.5 10 6.3 TA60 9 5.1 6 3.6 10 5.6 11 4.2 8 2.5 9 4.3 9 2.3 14 7.1 10 3.2 Mean 9.8 6.2 10.5 6 15.7 8.2 10.7 5.4 12.5 6.2 14.2 7.1 11.3 6.1 14.7 6.9 10.8 6.1 SE 1.5 1.2 1.4 1 2.1 1.6 1.2 1.1 1.8 1.1 2 1.2 1.5 1 1.8 1.2 1.5 1 All States had a mean allelic diversity (He) value of 0.79. Independently, each State had mean He values > 0.76 with the highest value of 0.82 observed in Enugu State and lowest He value of 0.76 observed in Oyo State (Table 3). Kruskal-Wallis test further showed no significant difference between the mean He observed across the nine States (p>0.05). Table 3 : Allelic diversity (He) of microsatellite loci from parasite populations in the nine states Locus Adamawa (n=48) Bayelsa (n=45) Enugu (n=100) Ibadan (n=50) Imo (n=82) Kano (n=100) Kwara (n=56) Sokoto (n=46) Adamawa (n=48) Mean (L*) SE (L*) PolyA 0.964 0.940 0.958 0.950 0.910 0.951 0.941 0.942 0.942 0.944 0.005 PfPK2 0.884 0.879 0.858 0.866 0.843 0.871 0.867 0.845 0.885 0.867 0.005 Ta81 0.873 0.869 0.912 0.851 0.843 0.838 0.855 0.864 0.858 0.863 0.007 ARA2 0.926 0.900 0.928 0.701 0.897 0.885 0.904 0.900 0.927 0.885 0.024 TA87 0.934 0.948 0.941 0.919 0.948 0.895 0.926 0.944 0.914 0.930 0.006 TA40 0.756 0.923 0.624 0.718 0.904 0.821 0.780 0.647 0.846 0.780 0.035 TA42 0.420 0.253 0.627 0.542 0.248 0.651 0.209 0.288 0.221 0.384 0.060 2490 0.626 0.642 0.754 0.681 0.696 0.771 0.735 0.775 0.635 0.702 0.020 TA1 0.846 0.868 0.929 0.512 0.771 0.925 0.831 0.840 0.814 0.815 0.041 PFG377 0.687 0.479 0.666 0.734 0.737 0.645 0.739 0.685 0.703 0.675 0.027 TA109 0.811 0.840 0.821 0.861 0.892 0.868 0.875 0.854 0.861 0.854 0.009 TA60 0.825 0.746 0.828 0.780 0.608 0.778 0.574 0.867 0.704 0.746 0.033 Mean (P**) 0.796 0.774 0.820 0.760 0.775 0.825 0.770 0.788 0.776 0.787 NA SE (P**) 0.045 0.062 0.036 0.040 0.056 0.028 0.059 0.052 0.058 0.044 NA L*: Locus, P**: Population, SE: Standard error Parasite population differentiation Analysis of molecular variance (AMOVA) Comparisons of parasite populations using AMOVA showed that genetic differentiation amongst the nine States was low with ΦPT = 0.039 with a p-value<0.05 which suggests that only 3.9% of genetic variance exists among all States, and to a large extent (96.1%), parasite populations are similar across all nine States. Fixation index (Fst) The fixation index between parasite populations (Fst) is 0.038; that is, the genetic diversity between the nine States constituted 3.8% of the total genetic variance (p<0.05) which essentially suggests that all nine States are not significantly genetically diverse from each other. Principal component analysis (PCA) Based on the PCA plots, low diversity existed among the States. However, plots showing each State independently revealed within-population diversity especially in Bayelsa, Imo and Kano States (Figure 2 - Panels B, E and F, respectively). Results obtained from analyses showed no significant index of association in all parasite populations considered as the obtained LD value was 0.0179 (Table 4). Although the highest LD value of 0.0715 was obtained in Adamawa State, and the lowest LD value of 0.0037 was obtained in Kwara State, there was no significant difference (p>0.05). This is indicative of similar parasite structuring in all nine States. Table 4: Linkage disequilibrium analysis for P. falciparum populations obtained in each state Population V D V E I S A Adamawa 3.5435 1.9832 0.0715 Bayelsa 3.1642 2.0411 0.05 Enugu 1.8239 1.5728 0.0145 Ibadan 2.2501 1.9772 0.0125 Imo 2.3986 1.855 0.0266 Kano 2.2776 1.7312 0.0287 Kwara 1.6931 1.7651 0.0037 Sokoto 2.0717 1.6981 0.02 Plateau 1.8405 1.6313 0.0117 ALL 1.8031 1.507 0.0179 V D : the observed variance. V E : the expected variance of n - the number of loci for which two individuals differ I S A : Linkage disequilibrium Discussion Nigeria remains the country with the highest global malaria burden. Hence, molecular studies on P. falciparum diversity and population structure become essential in monitoring the impact of different intervention strategies in the control of malaria transmission. This study employed the use of 12 microsatellites to evaluate P. falciparum genetic diversity and population structure in nine Nigerian States. Although microsatellites are better alternatives to polymorphic markers such as msp -1, msp -2, and Glurp , there are only a few reports of its use in studies conducted in Nigeria. Our analysis of the microsatellite data generated in this study revealed high parasite diversity across all states. For instance, the mCOI (measure of parasite diversity) in all nine States was high (ranging from 1.71-2.66). Although, higher mCOI values (4.38-5.4) have been reported in earlier studies conducted prior to the introduction of artemisinin combination therapies (ACTs) [10, 11, 33], mCOI values obtained in this study suggest a steady decline in parasite diversity 13 years post-adoption of ACTs in Nigerian children. This may largely be attributed to the adoption and deployment of ACTs in Nigeria. In addition, other concurrent interventions such as broader distribution of long-lasting insecticide treated net (LLIN), may be a contributing factor [26]. Another measure of parasite diversity is the number of effective alleles (Ne) detected per microsatellite locus. It is expected that the number of Ne detected per locus is likely to be high in areas with high malaria endemicity and vice versa [5, 19]. The observed mean Ne in parasites obtained from all States (5.4 - 8.2) were comparable to those reported in other high-endemic regions of Sub-Saharan Africa [4, 5, 34]. The distribution of observed mean Ne in the Northern and Southern States were similar (p>0.05). This is equally expected as malaria endemicity continues to be high throughout Nigeria. Estimated allelic diversity (computed as expected heterozygosity-He), was high in all States with values ranging from 0.774 to 0.825. This suggests that parasites from these States exhibited high heterozygosity, which depicts high parasite transmission [35]. Similar high He values have been reported in other parts of Nigeria (Ekiti State: 0.79 and Lagos State: 0.65) and other countries with high levels of malaria transmission [5, 6, 18, 36, 37]. Although parasite diversity was high, further analysis of microsatellite data generated revealed low parasite population differentiation. Analysis of molecular variance (AMOVA) and genetic differentiation index (F ST ) values obtained were 0.039 and 0.038 respectively, which is low [36, 38]. This implies that about 96% of genetic variations observed among parasites were within populations. The principal component analysis (PCA) of all nine States further confirmed genetic similarities amongst parasite populations as similar clustering patterns consistent with low levels of genetic differentiation were observed. Linkage disequilibrium (LD) values for each parasite population ranged from 0.0037 in Kwara to 0.0715 in Adamawa. The overall association index was 0.0219, which is weaker than those typically reported in regions with low transmission [21, 23]. Studies have associated low LD values such as those reported in this study, to high levels of malaria transmission; which leads to increased cross-breeding and meiotic recombination that results in LD breakdown [5, 6, 19, 39]. Although the LD values obtained in this study remain low, there is a need to continually monitor parasite populations within Nigeria to detect new variants that may inform adaptation against interventions currently employed. The perceived lack of genetic differentiation or sub-structuring between States as evidenced by results obtained from AMOVA, Fst, PCA and LD analysis, is probably as a result of immense human migration between these populations as part of the usual socioeconomic activities and indiscriminate vector migration within the country [6, 40, 41, 42]. Conclusion This study represents the first use of 12 polymorphic microsatellite loci to characterize parasite diversity and structure in Nigeria across regions representing all the six geographical zones of the country. The high level of genetic diversity and low population structuring in this study suggests that parasite populations circulating in Nigeria are homogenous. This implies that a uniform control strategy will be effective across the six geographical zones. The results obtained can be used as a baseline for parasite diversity and structure, aiding in the formulation of appropriate therapeutic and control strategies in Nigeria. Abbreviations PCR: Polymerase chain reaction MSP1: Merozoite surface protein 1 MSP2: Merozoite surface protein 2 GLURP: Glutamate-rich protein DBS: Dried blood spot COI: Complexity of infection mCOI: Mean complexity of infection Na: Number of alleles Ne: Number of effective alleles He: Expected heterozygosity AMOVA: Analysis of molecular variance FST: Fixation index PCA: Principal component analysis LD: Linkage disequilibrium ACTs: Artemisinin combination therapies LLIN: Long lasting insecticide net Declarations Acknowledgement The authors thank all the patients, their parents or guardians for volunteering to participate in the study. We also acknowledge the principal investigators (PI) in each of the nine sentinel locations considered in this study. The National Malaria Elimination Program of the Federal Ministry of Health in Nigeria for the year 2014-2018. Funding This work was supported by grants from African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), World Bank (ACE019) and The National Institute of Health (grants U01HG007480, U54HG007480). The U.S President’s Malaria Initiative (USPMI) funded the primary drug efficacy study from which samples were obtained for the current study. Author information Fehintola V. Ajogbasile and Adeyemi T. Kayode contributed equally to this work. Affiliations African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer’s University, Ede, Nigeria. Fehintola V. Ajogbasile, Adeyemi T. Kayode, Kazeem O. Akano, Paul E. Oluniyi, Jessica N. Uwanibe, Benjamin B. Adegboyega, Courage Philip, Philomena J. Eromon, Onikepe A. Folarin Christian T. Happi Department of Biological Sciences, Faculty of Natural Sciences, Redeemer's University, Ede, Nigeria Fehintola V. Ajogbasile, Adeyemi T. Kayode, Kazeem O. Akano, Paul E. Oluniyi, Jessica N. Uwanibe, Onikepe A. Folarin, Christian T. Happi Department of Biological Sciences, Covenant University, Ota, Nigeria Oluwagboadurami G. John Department of Paediatrics, Imo State University Teaching Hospital, Orlu, Nigeria George Emechebe Department of Paediatrics, Federal Medical Centre, Yenagoa, Nigeria Finimo Finimo Case Management Unit, National Malaria Elimination Programme, Federal Ministry of Health, Abuja, Nigeria Nnenna Ogbulafor Department of Paediatrics, Uthman Dan Fodio University, Sokoto, Nigeria Nma Jiya Department of Paediatrics, University of Nigeria Teaching Hospital, University of Nigeria, Nsukka, Nigeria Uche Okafor Department of Paediatrics, University of Maiduguri, Nigeria Jose Ambe Department of Paediatrics, Ahmadu Bello University, Zaria, Nigeria Robinson D. Wammanda Department of Paediatrics, University of Jos Teaching Hospital, University of Jos, Nigeria Stephen Oguche Department of Paediatrics and Child Health, University of Ilorin, Nigeria Olugbenga Mokuolu Institute of Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria Akintunde Sowunmi Department of Pharmacology and Therapeutics, University of Ibadan, Ibadan, Nigeria Akintunde Sowunmi Corresponding Author Christian T. Happi Author contributions F.V.A., A.T.K., B.B.A., C.P., J.N.U., O.G.J., N.O., U.O., S.O., J.A., R.D.W., N.J., F.F., G.E., and O.M carried out the experiments and acquired data; C.T.H. conceived the study; F.V.A., A.T.K., K.O.A. and P.E.O performed data analysis and interpretation; F.V.A and A.T.K wrote the paper; K.A.O., P.E.O., J.N.U., P.J.E., A.S., O.A.F and C.T.H reviewed and revised the manuscript; P.J.E., A.S., O.A.F and C.T.H. supervised the study. Ethical Declaration The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the National Health Research Ethics Committee, Federal Ministry of Health (FMOH), Abuja, Nigeria. Informed consent was obtained from parents and legal guardians of participants prior to enrollment in study. Consent for publication Not applicable Competing interests The authors declare that they have no competing interests Availability of data and materials The data analyzed for this manuscript is available upon request from the corresponding author. References Ceesay SJ, Casals-Pascual C, Erskine J, Anya SE, Duah NO, Fulford AJC, et al. Changes in malaria indices between 1999 and 2007 in The Gambia: a retrospective analysis. Lancet. 2008;372: 1545–1554. O’Meara WP, Bejon P, Mwangi TW, Okiro EA, Peshu N, Snow RW, et al. Effect of a fall in malaria transmission on morbidity and mortality in Kilifi, Kenya. Lancet. 2008;372: 1555–1562. Jaenisch T, Sullivan DJ, Dutta A, Deb S, Ramsan M, Othman MK, et al. Malaria incidence and prevalence on Pemba island before the onset of the successful control intervention on the Zanzibar archipelago. Malar J. 2010;9: 32. Bogreau H, Renaud F, Bouchiba H, Durand P, Assi S-B, Henry M-C, et al. Genetic diversity and structure of African Plasmodium falciparum populations in urban and rural areas. Am J Trop Med Hyg. 2006;74: 953–959. Mulenge FM, Hunja CW, Magiri E, Culleton R, Kaneko A, Aman RA. Genetic Diversity and Population Structure of Plasmodium falciparum in Lake Victoria Islands, A Region of Intense Transmission. Am J Trop Med Hyg. 2016;95: 1077–1085. Oyebola MK, Idowu ET, Olukosi YA, Iwalokun BA, Agomo CO, Ajibaye OO, et al. Genetic diversity and complexity of Plasmodium falciparum infections in Lagos, Nigeria. Asian Pac J Trop Biomed. 2014;4: S87–91. Ariey F, Chalvet W, Hommel D, Peneau C, Hulin A, Mercereau-Puijalon O, et al. Plasmodium falciparum parasites in French Guiana: limited genetic diversity and high selfing rate. Am J Trop Med Hyg. 1999;61: 978–985. Haddad D, Snounou G, Mattei D, Enamorado IG, Figueroa J, Ståhl S, et al. Limited genetic diversity of Plasmodium falciparum in field isolates from Honduras. Am J Trop Med Hyg. 1999;60: 30–34. Atroosh WM, Al-Mekhlafi HM, Mahdy MA, Saif-Ali R, Al-Mekhlafi AM, Surin J. Genetic diversity of Plasmodium falciparum isolates from Pahang, Malaysia based on MSP-1 and MSP-2 genes. Parasit Vectors. 2011;4: 233. Engelbrecht F, Tögel E, Beck HP, Enwezor F, Oettli A, Felger I. Analysis of Plasmodium falciparum infections in a village community in Northern Nigeria: determination of msp2 genotypes and parasite-specific IgG responses. Acta Trop. 2000;74: 63–71. Happi CT, Gbotosho GO, Sowunmi A, Falade CO, Akinboye DO, Gerena L, et al. Molecular analysis of Plasmodium falciparum recrudescent malaria infections in children treated with chloroquine in Nigeria. Am J Trop Med Hyg. 2004;70: 20–26. Amodu OK, Adeyemo AA, Ayoola OO, Gbadegesin RA, Orimadegun AE, Akinsola AK, et al. Genetic diversity of the msp-1 locus and symptomatic malaria in south-west Nigeria. Acta Trop. 2005;95: 226–232. Olasehinde GI, Yah CS, Singh R, Ojuronbge OO, Ajayi AA, Valecha N, et al. Genetic diversity of Plasmodium falciparum field isolates from south western Nigeria. Afr Health Sci. 2012;12: 355–361. Oyedeji SI, Awobode HO, Kun J. Limited Genetic Diversity and Low Multiplicity of Plasmodium falciparum Infections in Children with Severe Malaria in Lafia, North-central Nigeria. Journal of Experimental & Clinical Medicine. 2013;5: 143–147. Hughes AL. Positive selection and interallelic recombination at the merozoite surface antigen-1 (MSA-1) locus of Plasmodium falciparum. Mol Biol Evol. 1992;9: 381–393. Hughes MK, Hughes AL. Natural selection on Plasmodium surface proteins. Mol Biochem Parasitol. 1995;71: 99–113. Escalante AA, Lal AA, Ayala FJ. Genetic polymorphism and natural selection in the malaria parasite Plasmodium falciparum. Genetics. 1998;149: 189–202. Mobegi VA, Loua KM, Ahouidi AD, Satoguina J, Nwakanma DC, Amambua-Ngwa A, et al. Population genetic structure of Plasmodium falciparum across a region of diverse endemicity in West Africa. Malar J. 2012;11: 223. Anderson TJ, Haubold B, Williams JT, Estrada-Franco JG, Richardson L, Mollinedo R, et al. Microsatellite markers reveal a spectrum of population structures in the malaria parasite Plasmodium falciparum. Mol Biol Evol. 2000;17: 1467–1482. Bonizzoni M, Afrane Y, Baliraine FN, Amenya DA, Githeko AK, Yan G. Genetic structure of Plasmodium falciparum populations between lowland and highland sites and antimalarial drug resistance in Western Kenya. Infect Genet Evol. 2009;9: 806–812. Larrañaga N, Mejía RE, Hormaza JI, Montoya A, Soto A, Fontecha GA. Genetic structure of Plasmodium falciparum populations across the Honduras-Nicaragua border. Malar J. 2013;12: 354. Volkman SK, Neafsey DE, Schaffner SF, Park DJ, Wirth DF. Harnessing genomics and genome biology to understand malaria biology. Nat Rev Genet. 2012;13: 315–328. Pumpaibool T, Arnathau C, Durand P, Kanchanakhan N, Siripoon N, Suegorn A, et al. Genetic diversity and population structure of Plasmodium falciparum in Thailand, a low transmission country. Malar J. 2009;8: 155. Branch OH, Sutton PL, Barnes C, Castro JC, Hussin J, Awadalla P, et al. Plasmodium falciparum genetic diversity maintained and amplified over 5 years of a low transmission endemic in the Peruvian Amazon. Mol Biol Evol. 2011;28: 1973–1986. Nkhoma SC, Nair S, Al-Saai S, Ashley E, McGready R, Phyo AP, et al. Population genetic correlates of declining transmission in a human pathogen. Mol Ecol. 2013;22: 273–285. Bankole BE, Kayode AT, Nosamiefan IO, Eromon P, Baniecki ML, Daniels RF, et al. Characterization of Plasmodium falciparum structure in Nigeria with malaria SNPs barcode. Malar J. 2018;17: 472. Anderson TJ, Su XZ, Bockarie M, Lagog M, Day KP. Twelve microsatellite markers for characterization of Plasmodium falciparum from finger-prick blood samples. Parasitology. 1999;119 ( Pt 2): 113–125. Peakall R, Smouse PE. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update. Bioinformatics. 2012;28: 2537–2539. Mohammed H, Kassa M, Mekete K, Assefa A, Taye G, Commons RJ. Genetic diversity of the msp-1, msp-2, and glurp genes of Plasmodium falciparum isolates in Northwest Ethiopia. Malar J. 2018;17: 386. Metsalu T, Vilo J. ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap. Nucleic Acids Res. 2015;43: W566–70. Haubold B, Hudson RR. LIAN 3.0: detecting linkage disequilibrium in multilocus data. Linkage Analysis. Bioinformatics. 2000;16: 847–848. Souza V, Nguyen TT, Hudson RR, Piñero D, Lenski RE. Hierarchical analysis of linkage disequilibrium in Rhizobium populations: evidence for sex? Proc Natl Acad Sci U S A. 1992;89: 8389–8393. Happi CT, Gbotosho GO, Folarin OA, Bolaji OM, Sowunmi A, Kyle DE, et al. Association between mutations in plasmodium falciparum chloroquine resistance transporter and p. falciparum multidrug resistance 1 genes and in vivo amodiaquine resistance in p. falciparum malaria–infected children in nigeria. Am J Trop Med Hyg. 2006;75: 155–161. Zhong D, Afrane Y, Githeko A, Yang Z, Cui L, Menge DM, et al. Plasmodium falciparum genetic diversity in western Kenya highlands. Am J Trop Med Hyg. 2007;77: 1043–1050. Mwingira F, Nkwengulila G, Schoepflin S, Sumari D, Beck H-P, Snounou G, et al. Plasmodium falciparum msp1, msp2 and glurp allele frequency and diversity in sub-Saharan Africa. Malar J. 2011;10: 79. Conway DJ, Machado RL, Singh B, Dessert P, Mikes ZS, Povoa MM, et al. Extreme geographical fixation of variation in the Plasmodium falciparum gamete surface protein gene Pfs48/45 compared with microsatellite loci. Mol Biochem Parasitol. 2001;115: 145–156. Durand P, Michalakis Y, Cestier S, Oury B, Leclerc MC, Tibayrenc M, et al. Significant linkage disequilibrium and high genetic diversity in a population of Plasmodium falciparum from an area (Republic of the Congo) highly endemic for malaria. Am J Trop Med Hyg. 2003;68: 345–349. Balloux F, Lugon-Moulin N. The estimation of population differentiation with microsatellite markers. Mol Ecol. 2002;11: 155–165. Anthony TG, Conway DJ, Cox-Singh J, Matusop A, Ratnam S, Shamsul S, et al. Fragmented population structure of plasmodium falciparum in a region of declining endemicity. J Infect Dis. 2005;191: 1558–1564. Schultz L, Wapling J, Mueller I, Ntsuke PO, Senn N, Nale J, et al. Multilocus haplotypes reveal variable levels of diversity and population structure of Plasmodium falciparum in Papua New Guinea, a region of intense perennial transmission. Malar J. 2010;9: 336. Lum JK, Kaneko A, Tanabe K, Takahashi N, Björkman A, Kobayakawa T. Malaria dispersal among islands: human mediated Plasmodium falciparum gene flow in Vanuatu, Melanesia. Acta Trop. 2004;90: 181–185. Lum JK, Kaneko A, Taleo G, Amos M, Reiff DM. Genetic diversity and gene flow of humans, Plasmodium falciparum, and Anopheles farauti s.s. of Vanuatu: inferred malaria dispersal and implications for malaria control. Acta Trop. 2007;103: 102–107. Supplementary Files TA60.pdf TA42.pdf Ta81.pdf TA87.pdf TA109.pdf ARA2.pdf PFG377.pdf TA40.pdf TA1.pdf PfPK2.pdf 2490.pdf PolyA.pdf AdditionalFiles.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major Revision 23 Dec, 2020 Review # 3 received at journal 22 Dec, 2020 Review # 2 received at journal 01 Dec, 2020 Reviewer # 3 agreed at journal 01 Dec, 2020 Review # 1 received at journal 01 Dec, 2020 Reviewer # 2 agreed at journal 11 Nov, 2020 Reviewer # 1 agreed at journal 09 Nov, 2020 Reviewers invited by journal 23 Oct, 2020 Editor assigned by journal 07 Oct, 2020 First submitted to journal 06 Oct, 2020 Submission checks completed at journal 06 Oct, 2020 Editor invited by journal 06 Oct, 2020 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-90709","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":3336552,"identity":"f15540c2-4405-4319-802a-cf02307ddf41","order_by":0,"name":"Fehintola Victoria Ajogbasile","email":"","orcid":"https://orcid.org/0000-0002-3149-3085","institution":"Redeemer's University College of Natural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Fehintola","middleName":"Victoria","lastName":"Ajogbasile","suffix":""},{"id":3336553,"identity":"907bf093-9f4f-4e9d-9a2d-9bc22d320990","order_by":1,"name":"Adeyemi T. Kayode","email":"","orcid":"","institution":"Redeemer's University College of Natural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Adeyemi","middleName":"T.","lastName":"Kayode","suffix":""},{"id":3336554,"identity":"0890eaf0-772d-4164-bc87-686ef0e3e9b4","order_by":2,"name":"Kazeem O. Akano","email":"","orcid":"","institution":"Redeemer's University College of Natural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Kazeem","middleName":"O.","lastName":"Akano","suffix":""},{"id":3336555,"identity":"419f2e42-9902-4c9b-9e8e-0f93d571ee8f","order_by":3,"name":"Paul E. Oluniyi","email":"","orcid":"","institution":"Redeemer's University College of Natural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"E.","lastName":"Oluniyi","suffix":""},{"id":3336556,"identity":"773cf51e-3709-4149-8421-ce5ab2bc4e30","order_by":4,"name":"Jessica N. Uwanibe","email":"","orcid":"","institution":"Redeemer's University College of Natural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jessica","middleName":"N.","lastName":"Uwanibe","suffix":""},{"id":3336557,"identity":"bc3b80cf-949c-4d3b-a602-df6fbc04285e","order_by":5,"name":"Benjamin B. Adegboyega","email":"","orcid":"","institution":"African Centre for Excellence for the Genomics of Infectious Diseases (ACEGID)","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"B.","lastName":"Adegboyega","suffix":""},{"id":3336558,"identity":"7370bd01-6034-4885-838a-12ab0703bded","order_by":6,"name":"Courage Philip","email":"","orcid":"","institution":"African Centre of Excellence for the Genomics of Infectious Diseases (ACEGID)","correspondingAuthor":false,"prefix":"","firstName":"Courage","middleName":"","lastName":"Philip","suffix":""},{"id":3336559,"identity":"188c30c0-5c80-44db-8052-565421487bab","order_by":7,"name":"Oluwagboadurami G. John","email":"","orcid":"","institution":"Covenant University","correspondingAuthor":false,"prefix":"","firstName":"Oluwagboadurami","middleName":"G.","lastName":"John","suffix":""},{"id":3336560,"identity":"45757a6c-8067-483d-b819-23d605ac979f","order_by":8,"name":"Philomena J. Eromon","email":"","orcid":"","institution":"Africa Centre of Excellence for the Genomics of Infectious Diseases (ACEGID)","correspondingAuthor":false,"prefix":"","firstName":"Philomena","middleName":"J.","lastName":"Eromon","suffix":""},{"id":3336561,"identity":"05df8d73-ac71-41e9-86d2-4fee08532ad8","order_by":9,"name":"George Emechebe","email":"","orcid":"","institution":"Imo State University","correspondingAuthor":false,"prefix":"","firstName":"George","middleName":"","lastName":"Emechebe","suffix":""},{"id":3336562,"identity":"b38d2262-5243-479d-b4ec-b073d0df6107","order_by":10,"name":"Finimo Finimo","email":"","orcid":"","institution":"Federal Medical Centre Yenogoa","correspondingAuthor":false,"prefix":"","firstName":"Finimo","middleName":"","lastName":"Finimo","suffix":""},{"id":3336563,"identity":"c7e5d967-faac-4c17-8f61-e6ae20dac01c","order_by":11,"name":"Nnenna Ogbulafor","email":"","orcid":"","institution":"National Malaria Elimination Program: Federal Ministry of Health","correspondingAuthor":false,"prefix":"","firstName":"Nnenna","middleName":"","lastName":"Ogbulafor","suffix":""},{"id":3336564,"identity":"5b8aa112-f726-4ef2-a74d-d654a93b3d4c","order_by":12,"name":"Nma Jiya","email":"","orcid":"","institution":"Uthman Dan Fodio University, Sokoto","correspondingAuthor":false,"prefix":"","firstName":"Nma","middleName":"","lastName":"Jiya","suffix":""},{"id":3336565,"identity":"9b105e0e-0dc7-428c-a8b6-62cd86c9d5e1","order_by":13,"name":"Uche Okafor","email":"","orcid":"","institution":"University of Nigeria, Nsukka","correspondingAuthor":false,"prefix":"","firstName":"Uche","middleName":"","lastName":"Okafor","suffix":""},{"id":3336566,"identity":"a0d7c86e-cd6e-430a-bcae-abc44db941dd","order_by":14,"name":"Jose Ambe","email":"","orcid":"","institution":"University of Maiduguri","correspondingAuthor":false,"prefix":"","firstName":"Jose","middleName":"","lastName":"Ambe","suffix":""},{"id":3336567,"identity":"110a30a9-4c47-4b45-99be-6a6310ad336a","order_by":15,"name":"Robinson D. Wammanda","email":"","orcid":"","institution":"Ahmadu Bello University","correspondingAuthor":false,"prefix":"","firstName":"Robinson","middleName":"D.","lastName":"Wammanda","suffix":""},{"id":3336568,"identity":"d134dc8c-a6cc-410b-aae7-df6fe4a467d8","order_by":16,"name":"Stephen Oguche","email":"","orcid":"","institution":"University of Jos","correspondingAuthor":false,"prefix":"","firstName":"Stephen","middleName":"","lastName":"Oguche","suffix":""},{"id":3336569,"identity":"3104780d-a163-48bb-8bed-dd10a125f48f","order_by":17,"name":"Olugbenga A. Mokuolu","email":"","orcid":"","institution":"University of Ilorin","correspondingAuthor":false,"prefix":"","firstName":"Olugbenga","middleName":"A.","lastName":"Mokuolu","suffix":""},{"id":3336570,"identity":"9a0fc7c4-1e75-4126-a216-c23a3ad6a170","order_by":18,"name":"Akintunde Sowunmi","email":"","orcid":"","institution":"University of Ibadan College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Akintunde","middleName":"","lastName":"Sowunmi","suffix":""},{"id":3336571,"identity":"4a4ae2a5-b6fb-4503-b970-068ca5e8a2af","order_by":19,"name":"Onikepe A. Folarin","email":"","orcid":"","institution":"Redeemer's University College of Natural Sciences","correspondingAuthor":false,"prefix":"","firstName":"Onikepe","middleName":"A.","lastName":"Folarin","suffix":""},{"id":3336572,"identity":"e49e17c5-e480-4791-b290-4aa269d41c56","order_by":20,"name":"Christian T. Happi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYBACAxCRwGAD4fGQoCWNVC0MDIdJ0GLOfvbYgwc15/MNbjcwPnjbxpAn70BAi2VPXrpBwrHblhvuHGA2nNvGUGx4gJDDDuSYSSQ23DYwuJHAJs3bxpC4sYGQlvNvQFrOgbSw/yZOyw2wLQfAtjCDtMwnoAOo5R3IL8kGkjcSmyXnnJNI3EBQy/ncYw9/1NgZ8N1IPvjhTZlN4nxCDgPGBRuUwQhSKwEMEOK1QIE8YVtGwSgYBaNghAEASUdCflAQqQsAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-3056-6705","institution":"African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Nigeria","correspondingAuthor":true,"prefix":"","firstName":"Christian","middleName":"T.","lastName":"Happi","suffix":""}],"badges":[],"createdAt":"2020-10-10 12:56:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-90709/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-90709/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":2950554,"identity":"8c0ae595-35ef-4151-a5c5-349f8bd5f4b6","added_by":"auto","created_at":"2020-10-13 14:49:06","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":55256,"visible":true,"origin":"","legend":"Geographic representation of sites (highlighted) in Nigeria where samples for in this study were collected.\n\nNote: The designations employed and the presentation of the material on this map do not imply the expression of any opinion whatsoever on the part of Research Square concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. This map has been provided by the authors.","description":"","filename":"Fig1.JPG","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/e953a19cea2a174d8e541024.JPG"},{"id":2950555,"identity":"f2adf693-e80f-49fa-902b-c4cda0b20ca1","added_by":"auto","created_at":"2020-10-13 14:49:07","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":701256,"visible":true,"origin":"","legend":"Principal Component Analysis (PCA) plot of parasite populations in (A) Adamawa State, (B) Bayelsa State, (C) Enugu State, (D) Oyo State, (E) Imo State, (F) Kano State, (G) Kwara State, (H) Plateau State, (I) Sokoto State (J) Southern region States combined (Bayelsa, Enugu, Ibadan and Imo States), (K) Northern region States combined (Kano, Kwara, Plateau and Sokoto States), and (L) Northern region States and Southern Region States combined\nLinkage disequilibrium (LD)","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/39737291c1192b7d399e946a.jpg"},{"id":13601959,"identity":"cf4a5461-543d-4c46-8775-144db49adca1","added_by":"auto","created_at":"2021-09-17 05:49:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":827496,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/18eff942-555d-46d0-9ef7-19ae8d3018aa.pdf"},{"id":2950556,"identity":"32c23760-9b36-4fa3-8161-354d0bd6053a","added_by":"auto","created_at":"2020-10-13 14:49:07","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":236816,"visible":true,"origin":"","legend":"","description":"","filename":"TA60.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/ff1790d787f23955a73d1834.pdf"},{"id":2950557,"identity":"2a7608d5-0703-434d-879b-eaa432d62ebc","added_by":"auto","created_at":"2020-10-13 14:49:07","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":6500,"visible":true,"origin":"","legend":"","description":"","filename":"TA42.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/1cd9db803ca5aced59906ec2.pdf"},{"id":2950558,"identity":"4113312f-9d44-4d30-bb17-3792b7e648d9","added_by":"auto","created_at":"2020-10-13 14:49:07","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":38166,"visible":true,"origin":"","legend":"","description":"","filename":"Ta81.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/4619ba54518da34bb477c2a6.pdf"},{"id":2950559,"identity":"2a20a673-2e10-4e39-a5b5-91fdd6998ab4","added_by":"auto","created_at":"2020-10-13 14:49:07","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":38644,"visible":true,"origin":"","legend":"","description":"","filename":"TA87.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/53e6d642fe4632790ca06c52.pdf"},{"id":2950560,"identity":"89acb15d-4f14-43bb-9a0f-ad102dd21597","added_by":"auto","created_at":"2020-10-13 14:49:08","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":7225,"visible":true,"origin":"","legend":"","description":"","filename":"TA109.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/6297106d81430a53c78af747.pdf"},{"id":2950561,"identity":"1673a8de-5590-4fb2-b101-acce9fe0b97b","added_by":"auto","created_at":"2020-10-13 14:49:08","extension":"pdf","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":7230,"visible":true,"origin":"","legend":"","description":"","filename":"ARA2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/e2b1ffa230eaa8f2f594c816.pdf"},{"id":2950562,"identity":"e0a0e8b4-f037-4a9d-acb5-0739ed7bf8da","added_by":"auto","created_at":"2020-10-13 14:49:08","extension":"pdf","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":6084,"visible":true,"origin":"","legend":"","description":"","filename":"PFG377.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/512d66520146b73cf2ed7922.pdf"},{"id":2950563,"identity":"b71317bf-35f5-485b-b086-32c2aa962ed0","added_by":"auto","created_at":"2020-10-13 14:49:08","extension":"pdf","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":6566,"visible":true,"origin":"","legend":"","description":"","filename":"TA40.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/4290fa106020ee34a99f90ae.pdf"},{"id":2950564,"identity":"aefbec5c-564d-4fc7-904d-999c237488f6","added_by":"auto","created_at":"2020-10-13 14:49:08","extension":"pdf","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":38851,"visible":true,"origin":"","legend":"","description":"","filename":"TA1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/9f8f1dc09f5ae79a2602ae7f.pdf"},{"id":2950565,"identity":"4940183b-26fd-4bcc-b584-ce89a7d2489e","added_by":"auto","created_at":"2020-10-13 14:49:08","extension":"pdf","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":7209,"visible":true,"origin":"","legend":"","description":"","filename":"PfPK2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/93c83a487a5bb75030486bb9.pdf"},{"id":2950566,"identity":"055a3030-0952-4b64-8b71-ff46bc77dcd2","added_by":"auto","created_at":"2020-10-13 14:49:09","extension":"pdf","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":6262,"visible":true,"origin":"","legend":"","description":"","filename":"2490.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/4d3279d485763e207af45a23.pdf"},{"id":2950567,"identity":"7ec8feee-80bb-4ec7-bc94-773ffa845f7f","added_by":"auto","created_at":"2020-10-13 14:49:09","extension":"pdf","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":9660,"visible":true,"origin":"","legend":"","description":"","filename":"PolyA.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/601cef790a71855019eda181.pdf"},{"id":2950568,"identity":"202389f1-691e-4b9b-ab9e-a074ba3b9ee8","added_by":"auto","created_at":"2020-10-13 14:49:09","extension":"pdf","order_by":13,"title":"","display":"","copyAsset":false,"role":"supplement","size":212265,"visible":true,"origin":"","legend":"","description":"","filename":"AdditionalFiles.pdf","url":"https://assets-eu.researchsquare.com/files/rs-90709/v1/976e6f3d742262657eb6ddf0.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eGenetic Diversity and Population Structure of Plasmodium Falciparum in Nigeria: Insights From Microsatellites Loci Analysis\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eAlthough the incidence of malaria infections and malaria-associated mortality has reduced in many African countries [1, 2, 3], transmission continues in endemic regions despite intensified efforts towards prevention, control and eradication [4, 5]. This is due, in part, to the high genetic diversity of \u003cem\u003ePlasmodium falciparum\u003c/em\u003e that contributes to increased transmission rate and spread of resistant parasites [6]. Therefore, understanding the extent of genetic diversity, transmission intensity, and parasite population structure in Nigeria - the most malaria burdened country, is essential if the goal of malaria control or elimination is to be achieved.\u003c/p\u003e\n\u003cp\u003eMolecular techniques play important roles in the analyses of genetic diversity, transmission dynamics, and population structure of \u003cem\u003eP. falciparum\u003c/em\u003e field isolates. Early molecular studies focused mostly on the use of polymorphic markers such as merozoite surface protein 1 (\u003cem\u003emsp\u003c/em\u003e-1) and merozoite surface protein 2 (\u003cem\u003emsp\u003c/em\u003e-2) and glutamate-rich protein (Glurp) to characterise falciparum genetic diversity and structure in Nigeria [7, 8, 9]. These markers were also useful in monitoring drug efficacy with regards to classification of recurrent falciparum parasitaemia as re-infection or recrudescent infection [6, 10, 11]. However, there have been contrasting reports of polymorphisms in \u003cem\u003emsp-1\u003c/em\u003e and \u003cem\u003emsp-2\u003c/em\u003e in earlier studies in Nigeria [6, 12, 13, 14] which is associated with the fact that these antigenic markers are often under intense immune pressure [15, 16, 17]. The genotyping results provided by these markers can therefore potentially lead to a masked and distorted view of the population structure and transmission patterns which may account for observed variations across parasite populations circulating in a given environment [6].\u003c/p\u003e\n\u003cp\u003eMicrosatellites have been suggested to be better alternatives to \u003cem\u003emsp-1, msp-2\u003c/em\u003e and GLURP due to their abundance, putative neutrality and higher levels of polymorphisms [18]. This molecular technique remains one of the most efficient and reliable methods for analyzing the genetic diversity data of falciparum populations for epidemiological and drug efficacy purposes within countries and across continents [19]. In past studies of using microsatellite analyses, it was observed that parasites from areas of low malaria transmission [19] (\u0026lt;1% infection) have less genetic diversity but more population structure and greater linkage disequilibrium (i.e. more non-random association among alleles across multiple loci) [4, 19, 20, 21]. Contrary, in regions of high malaria transmission, individuals are more likely to be infected by more than one \u003cem\u003eP\u003c/em\u003e. \u003cem\u003efalciparum\u003c/em\u003e parasite thereby resulting in an increase in the rate of recombination and subsequently, high diverse population with low linkage disequilibrium [18, 19, 22]. Although, some studies report a deviation from the norm whereby high levels of heterozygosity (a measure of genetic diversity) is observed in several low transmission countries [18, 23, 24]. This suggests that a high level of heterozygosity may reflect past human demographic processes as opposed to recent epidemiological factors [25].\u003c/p\u003e\n\u003cp\u003eThe objective of this study was to investigate the genetic diversity of circulating \u003cem\u003ePlasmodium falciparum\u003c/em\u003e parasites and their population structures in Nigerian children 6-96months old with uncomplicated infections, treated with artemisinin-based combination therapies (ACTs).\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy site\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFilter papers containing dried blood spot (DBS) obtained from 633 children from nine Nigerian States covering all six geographical zones i.e., \u003cstrong\u003eNorth-east\u003c/strong\u003e: Adamawa State (n = 48), \u003cstrong\u003eNorth-west\u003c/strong\u003e: Sokoto State (n = 50), \u003cstrong\u003eNorth-central\u003c/strong\u003e: Kano (n = 100), Plateau (n = 100) and Kwara States (n = 58), \u003cstrong\u003eSouth-west\u003c/strong\u003e: Oyo State (n = 50), \u003cstrong\u003eSouth-south\u003c/strong\u003e: Bayelsa State (n = 45), and \u003cstrong\u003eSouth-east\u003c/strong\u003e: Enugu State (n = 100), Imo State (n = 82) with \u003cem\u003eP. falciparum\u003c/em\u003e malaria infections on Day 0 were randomly selected for this study. These States are parts of sentinel sites for the National Malaria Elimination Program of the Federal Ministry of Health in Nigeria for the year 2014-2018.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy site\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFilter papers containing dried blood spot (DBS) obtained from 633 children from nine Nigerian States covering all six geographical zones i.e., \u003cstrong\u003eNorth-east\u003c/strong\u003e: Adamawa State (n = 48), \u003cstrong\u003eNorth-west\u003c/strong\u003e: Sokoto State (n = 50), \u003cstrong\u003eNorth-central\u003c/strong\u003e: Kano (n = 100), Plateau (n = 100) and Kwara States (n = 58), \u003cstrong\u003eSouth-west\u003c/strong\u003e: Oyo State (n = 50), \u003cstrong\u003eSouth-south\u003c/strong\u003e: Bayelsa State (n = 45), and \u003cstrong\u003eSouth-east\u003c/strong\u003e: Enugu State (n = 100), Imo State (n = 82) with \u003cem\u003eP. falciparum\u003c/em\u003e malaria infections on Day 0 were randomly selected for this study. These States are parts of sentinel sites for the National Malaria Elimination Program of the Federal Ministry of Health in Nigeria for the year 2014-2018.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo to three drops of finger-pricked blood samples were blotted on 3mm Whatman filter paper (Whatman International Limited, Maidstone, United Kingdom) before treatment initiation (Day 0). The blood samples impregnated on to filter papers were allowed to air-dry properly at room temperature, and dry blood spots (DBS) were kept in airtight envelopes with silica gel until analysed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDNA was extracted from DBS for parasite genetic diversity and population structure studies as previously described [26]. DNeasy Blood and Tissue extraction kit (Qiagen, Germany) was used to extract parasite DNA from DBS following the manufacturer's protocol.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePlasmodium falciparum \u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003egenotyping by microsatellite loci analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSemi-nested PCR amplification of 12 \u003cem\u003eP. falciparum\u003c/em\u003e microsatellite loci was done using a previously described protocol [17]. The 12 microsatellites loci were Poly A, PfG377, TA81, ARA2, TA87, TA40, TA42, 2490, TA1, TA60, TA109 and PfPk2 [27]. FAM, YAK YELLOW, and ATTO550N-labeled PCR products for the different loci amplified were pooled together (GeneScan\u0026trade; 500, Applied Biosystems, Foster City, CA) for electrophoresis on the ABI 3500XL Genetic Analyzer at the African Centre of Excellence for the Genomics of Infectious Diseases (ACEGID), Redeemer\u0026rsquo;s University Ede, Osun State, Nigeria. Peakscanner (Applied Biosystems) and GeneMarker (Softgenetics) software were used for normalization across runs and automatic determination of allele length and peak heights in samples containing multiple alleles per locus. Minor alleles were scored when the minor peaks were \u0026ge; 20% the height of the predominant allele in the isolate and with a relative fluorescent unit of at least 100.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures of parasite genetic diversity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComplexity of infection (COI)\u003c/p\u003e\n\u003cp\u003eThe COI was computed as the number of alleles per microsatellite loci divided by the number of amplified samples per microsatellite loci. The mean COI per State was calculated as the average of all COI values per microsatellite loci.\u003c/p\u003e\n\u003cp\u003eParasite allelic frequency\u003c/p\u003e\n\u003cp\u003eThe allele frequencies, per locus were calculated using GENALEX 6.5 [28]. This frequency was calculated for each State involved in the study.\u003c/p\u003e\n\u003cp\u003eParasite allelic diversity\u003c/p\u003e\n\u003cp\u003eThe expected heterozygosity (He), which represents the probability of being infected by two parasites with different alleles at a given locus, was calculated using the formula:\u003c/p\u003e\n\u003cp\u003eHe = [(n/n\u0026minus;1) (1\u0026minus;\u0026Sigma;p\u003csup\u003e2\u003c/sup\u003e)] - Equation 1\u003c/p\u003e\n\u003cp\u003eWhere n is the number of isolates analysed, and p represents the frequency of each different allele at a locus [29]. He values range from 0 to 1. Values closer to 0 indicate little or no allelic diversity while values closer to 1 indicate high allelic diversity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures of parasite population differentiation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of molecular variance (AMOVA)\u003cbr /\u003e Inter- and intra-population variance was determined with analysis of molecular variance (AMOVA, i.e., \u0026Phi;PT). \u0026Phi;PT value of zero (0) is considered indicative of no genetic differentiation among populations.\u003c/p\u003e\n\u003ch2\u003eFixation index (Fst)\u003c/h2\u003e\n\u003cp\u003eThe population divergence was measured by calculating the fixation index (Fst) for all pairs of parasite population in each State. The software, GENALEX 6.5 was used to compute the Fst value.\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis (PCA)\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis (PCA) was performed with the online program, ClustVis [30] across all nine States and separately for each State. \u003cbr /\u003e Linkage disequilibrium (LD)\u003c/p\u003e\n\u003cp\u003eLinkage disequilibrium (LD) was calculated for all nine States and separately for each State using the standardized index of association, (\u003cem\u003eI\u003csup\u003eS\u003c/sup\u003e\u003csub\u003eA\u003c/sub\u003e\u003c/em\u003e), (LIAN version 3.5 web interface) [31] and the majority allele at each locus in each infection. This index was calculated as\u003c/p\u003e\n\u003cp\u003e(\u003cem\u003eI\u003csup\u003eS\u003c/sup\u003e\u003csub\u003eA\u003c/sub\u003e\u003c/em\u003e) = (1/n \u0026ndash; 1 ((VD / (VE) \u0026ndash; 1) - Equation 2\u003c/p\u003e\n\u003cp\u003eWhere VE is the expected variance of the n\u003csup\u003eth\u003c/sup\u003e number of loci for which two individuals differ. VD is the observed variance. Randomization test, previously described [32], was done to determine whether the ratio of VD/VE was significantly higher than 1.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDemographics and baseline characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOverall, 329 (51.97%) were male and the mean age of all children included in the study was 48.4\u0026plusmn;15.8 months. Also, mean enrollment body temperature was 37.5\u0026plusmn;2.5\u003csup\u003eo\u003c/sup\u003eC. Overall geometric asexual parasitemia was 16,219ᶙL\u003csup\u003e-1\u003c/sup\u003e (range: 2003-198200).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParasite genetic diversity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eComplexity of infection (COI) and Mean complexity of Infection (mCOI)\u003c/p\u003e\n\u003cp\u003eThe mCOI recorded from the nine Nigerian States ranged from 1.71 in Sokoto (lowest) to 2.66 in Oyo (highest) (Table 1). The COI obtained using the TA42 locus across all States was low (\u003cu\u003e\u0026lt;\u003c/u\u003e 1.28) while at loci such as Poly A and ARA 2, high COI values (\u003cu\u003e\u0026gt;\u003c/u\u003e 2.16) were recorded (Table 1). Although mCOI observed in most (4 of 5) States in the Northern region were \u0026lt; 2.0 and in most (3 of 4) States in the Southern region were \u0026gt;2.0, there was no significant difference in mCOI values obtained in these regions (p\u0026gt;0.05).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e: The COI and mCOI values of parasites in nine Nigerian States using 12 Microsatellites loci\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003eLoci\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003eAdamawa\u003c/p\u003e\n\u003cp\u003e(n=48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003eBayelsa\u003c/p\u003e\n\u003cp\u003e(n=45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eEnugu\u003c/p\u003e\n\u003cp\u003e(n=100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eIbadan\u003c/p\u003e\n\u003cp\u003e(n=50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003eImo\u003c/p\u003e\n\u003cp\u003e(n=82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eKano\u003c/p\u003e\n\u003cp\u003e(n=100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003eKwara\u003c/p\u003e\n\u003cp\u003e(n=56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003eSokoto\u003c/p\u003e\n\u003cp\u003e(n=46)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003ePlateau\u003c/p\u003e\n\u003cp\u003e(n=100)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003ePoly A\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e2.63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e3.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e3.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e2.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e2.34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e3.19\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003ePfPK2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e3.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.83\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.58\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e2.53\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003eTa81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1.88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e4.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e2.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e2.52\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003eARA2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e5.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e4.57\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e6.81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e4.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e4.89\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e4.43\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e3.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e6.45\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003eTA40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e1.99\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003eTA87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e8.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.49\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.55\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.68\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e2.46\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e2490\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.02\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e1.64\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003eTA1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e3.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.86\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.56\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e2.29\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003eTA42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.28\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.03\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e1.13\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003ePFG377\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1.44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.63\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.37\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e1.36\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003eTA109\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1.95\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.93\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e2.11\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u003cstrong\u003eTA60\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1.45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e1.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.39\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.62\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.44\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e2.02\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"68\"\u003e\n\u003cp\u003e\u003cstrong\u003emCOI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"81\"\u003e\n\u003cp\u003e1.97\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"76\"\u003e\n\u003cp\u003e2.04\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.73\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e2.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"58\"\u003e\n\u003cp\u003e1.79\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.78\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"65\"\u003e\n\u003cp\u003e1.84\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"66\"\u003e\n\u003cp\u003e1.71\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"77\"\u003e\n\u003cp\u003e2.47\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNumber of alleles, Allelic frequency and diversity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean number of alleles (Na) observed ranged from 9.75 (Adamawa State) to 15.67 (Enugu State) and the mean number of effective alleles (Ne) observed ranged from 5.4 (Oyo State) to 8.2 (Enugu State) (Table 2). The allelic frequencies at each of the 12 loci in parasite populations obtained in each of the nine States are presented in additional file 1. The highest allelic frequencies in all nine States were observed in microsatellites loci TA40 (ranged from 200-220), TA42 (ranged from 182-183), \u003cem\u003ePf\u003c/em\u003ePK2 (ranged from 161-170), TA81 (ranged from 160-169), TA109 (ranged from 153-174), TA1 (ranged from 153-161), Poly A (ranged from 103-159), \u003cem\u003ePf\u003c/em\u003eG377 (103), TA87 (ranged from 90-106), 2490 (ranged from 80-83), ARA2 (ranged from 52-55), and TA60 (\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e Number of different and effective alleles parasite populations according to study location\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003eState\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"79\"\u003e\n\u003cp\u003eAdamawa\u003c/p\u003e\n\u003cp\u003e(n=48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"80\"\u003e\n\u003cp\u003eBayelsa\u003c/p\u003e\n\u003cp\u003e(n=45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"80\"\u003e\n\u003cp\u003eEnugu\u003c/p\u003e\n\u003cp\u003e(n=100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"80\"\u003e\n\u003cp\u003eIbadan\u003c/p\u003e\n\u003cp\u003e(n=50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"80\"\u003e\n\u003cp\u003eImo\u003c/p\u003e\n\u003cp\u003e(n=82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"80\"\u003e\n\u003cp\u003eKano\u003c/p\u003e\n\u003cp\u003e(n=100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"80\"\u003e\n\u003cp\u003eKwara\u003c/p\u003e\n\u003cp\u003e(n=56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"80\"\u003e\n\u003cp\u003eSokoto\u003c/p\u003e\n\u003cp\u003e(n=46)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd colspan=\"2\" width=\"80\"\u003e\n\u003cp\u003ePlateau\u003c/p\u003e\n\u003cp\u003e(n=100)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003eLocus\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003eNa\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003eNe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNa\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNa\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNa\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNa\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNa\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNa\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNa\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003eNe\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u003cstrong\u003eNa\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e\u003cstrong\u003eNe\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003ePolyA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e17.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e12.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e31\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e19.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e9.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e33\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e17.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e13.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e12.7\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003ePfPK2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e7.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003eTA81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e6.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003eARA2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e7.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e12.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e9.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10.8\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003eTA87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e8.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e18\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e11.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e22\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e15.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e9.4\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003eTA40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e3.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5.2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003eTA42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e1.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e2490\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e2.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e4.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e4.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.6\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003eTA1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e5.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e12.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e4.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e11.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e15\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e13\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e4.9\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003ePFG377\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3.2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003eTA109\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e4.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.3\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003eTA60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e5.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e4.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e4.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e3.2\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003eMean\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e9.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e6.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e15.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e8.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e5.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e12.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e7.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e11.3\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e14.7\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.9\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e10.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e6.1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"63\"\u003e\n\u003cp\u003e\u003cstrong\u003eSE\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"36\"\u003e\n\u003cp\u003e1.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"44\"\u003e\n\u003cp\u003e1.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.4\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.6\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.8\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1.5\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"40\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll States had a mean allelic diversity (He) value of 0.79. Independently, each State had mean He values \u003cu\u003e\u0026gt;\u003c/u\u003e 0.76 with the highest value of 0.82 observed in Enugu State and lowest He value of 0.76 observed in Oyo State (Table 3). Kruskal-Wallis test further showed no significant difference between the mean He observed across the nine States (p\u0026gt;0.05).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e: Allelic diversity (He) of microsatellite loci from parasite populations in the nine states\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e\u003cstrong\u003eLocus\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003eAdamawa\u003c/p\u003e\n\u003cp\u003e(n=48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003eBayelsa\u003c/p\u003e\n\u003cp\u003e(n=45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003eEnugu\u003c/p\u003e\n\u003cp\u003e(n=100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003eIbadan\u003c/p\u003e\n\u003cp\u003e(n=50)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003eImo\u003c/p\u003e\n\u003cp\u003e(n=82)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003eKano\u003c/p\u003e\n\u003cp\u003e(n=100)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003eKwara\u003c/p\u003e\n\u003cp\u003e(n=56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003eSokoto\u003c/p\u003e\n\u003cp\u003e(n=46)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003eAdamawa\u003c/p\u003e\n\u003cp\u003e(n=48)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003eMean (L*)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eSE (L*)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003ePolyA\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.964\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.940\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.958\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.950\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.910\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.951\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.941\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.942\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.942\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.944\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003ePfPK2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.884\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.879\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.858\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.866\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.843\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.871\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.867\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.845\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.885\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.867\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eTa81\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.873\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.869\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.912\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.851\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.843\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.838\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.855\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.864\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.858\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.863\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.007\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eARA2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.926\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.900\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.928\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.701\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.897\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.885\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.904\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.900\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.927\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.885\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.024\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eTA87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.934\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.948\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.941\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.919\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.948\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.895\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.926\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.944\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.914\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.930\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.006\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eTA40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.756\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.923\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.624\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.718\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.904\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.821\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.780\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.647\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.846\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.780\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.035\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eTA42\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.420\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.253\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.627\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.542\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.248\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.651\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.209\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.288\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.221\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.384\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.060\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003e2490\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.626\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.642\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.754\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.681\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.696\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.771\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.735\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.775\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.635\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.702\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.020\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eTA1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.846\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.868\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.929\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.512\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.771\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.925\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.831\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.840\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.814\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.815\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.041\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003ePFG377\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.687\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.479\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.666\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.734\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.737\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.645\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.739\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.685\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.703\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.675\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.027\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eTA109\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.811\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.840\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.821\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.861\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.892\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.868\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.875\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.854\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.861\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.854\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.009\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eTA60\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.825\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.746\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.828\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.780\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.608\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.778\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.574\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.867\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.704\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.746\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003e0.033\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eMean (P**)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.796\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.774\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.820\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.760\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.775\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.825\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.770\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.788\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.776\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.787\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"67\"\u003e\n\u003cp\u003eSE (P**)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.045\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"61\"\u003e\n\u003cp\u003e0.062\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.036\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.040\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.056\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"62\"\u003e\n\u003cp\u003e0.028\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"55\"\u003e\n\u003cp\u003e0.059\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.052\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"74\"\u003e\n\u003cp\u003e0.058\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"59\"\u003e\n\u003cp\u003e0.044\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"69\"\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eL*: Locus, P**: Population, SE: Standard error\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParasite population differentiation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of molecular variance (AMOVA)\u003c/p\u003e\n\u003cp\u003eComparisons of parasite populations using AMOVA showed that genetic differentiation amongst the nine States was low with \u0026Phi;PT = 0.039 with a p-value\u0026lt;0.05 which suggests that only 3.9% of genetic variance exists among all States, and to a large extent (96.1%), parasite populations are similar across all nine States.\u003c/p\u003e\n\u003cp\u003eFixation index (Fst)\u003c/p\u003e\n\u003cp\u003eThe fixation index between parasite populations (Fst) is 0.038; that is, the genetic diversity between the nine States constituted 3.8% of the total genetic variance (p\u0026lt;0.05) which essentially suggests that all nine States are not significantly genetically diverse from each other.\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis (PCA)\u003c/p\u003e\n\u003cp\u003eBased on the PCA plots, low diversity existed among the States. However, plots showing each State independently revealed within-population diversity especially in Bayelsa, Imo and Kano States (Figure 2 - Panels B, E and F, respectively).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults obtained from analyses showed no significant index of association in all parasite populations considered as the obtained LD value was 0.0179 (Table 4). Although the highest LD value of 0.0715 was obtained in Adamawa State, and the lowest LD value of 0.0037 was obtained in Kwara State, there was no significant difference (p\u0026gt;0.05). This is indicative of similar parasite structuring in all nine States.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: \u003c/strong\u003eLinkage disequilibrium analysis for \u003cem\u003eP. falciparum\u003c/em\u003e populations obtained in each state\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u003cstrong\u003ePopulation\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e\u003cstrong\u003eV\u003csub\u003eD\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e\u003cstrong\u003eV\u003csub\u003eE\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eI\u003csup\u003eS\u003c/sup\u003e\u003csub\u003eA\u003c/sub\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eAdamawa\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e3.5435\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.9832\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e0.0715\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eBayelsa\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e3.1642\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e2.0411\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eEnugu\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.8239\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.5728\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e0.0145\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eIbadan\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e2.2501\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.9772\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e0.0125\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eImo\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e2.3986\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.855\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e0.0266\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eKano\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e2.2776\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.7312\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e0.0287\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eKwara\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.6931\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.7651\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e0.0037\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003eSokoto\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e2.0717\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.6981\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e0.02\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003ePlateau\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.8405\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.6313\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e0.0117\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"183\"\u003e\n\u003cp\u003e\u003cstrong\u003eALL\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.8031\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e1.507\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"119\"\u003e\n\u003cp\u003e0.0179\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eV\u003csub\u003eD\u003c/sub\u003e: the observed variance.\u003c/p\u003e\n\u003cp\u003eV\u003csub\u003eE\u003c/sub\u003e: the expected variance of n - the number of loci for which two individuals differ\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eI\u003csup\u003eS\u003c/sup\u003e\u003csub\u003eA\u003c/sub\u003e\u003c/em\u003e: Linkage disequilibrium\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eNigeria remains the country with the highest global malaria burden. Hence, molecular studies on \u003cem\u003eP. falciparum\u003c/em\u003e diversity and population structure become essential in monitoring the impact of different intervention strategies in the control of malaria transmission. This study employed the use of 12 microsatellites to evaluate \u003cem\u003eP. falciparum\u003c/em\u003e genetic diversity and population structure in nine Nigerian States. Although microsatellites are better alternatives to polymorphic markers such as \u003cem\u003emsp\u003c/em\u003e-1, \u003cem\u003emsp\u003c/em\u003e-2, and \u003cem\u003eGlurp\u003c/em\u003e, there are only a few reports of its use in studies conducted in Nigeria.\u003c/p\u003e\n\u003cp\u003eOur analysis of the microsatellite data generated in this study revealed high parasite diversity across all states. For instance, the mCOI (measure of parasite diversity) in all nine States was high (ranging from 1.71-2.66). Although, higher mCOI values (4.38-5.4) have been reported in earlier studies conducted prior to the introduction of artemisinin combination therapies (ACTs) [10, 11, 33], mCOI values obtained in this study suggest a steady decline in parasite diversity 13 years post-adoption of ACTs in Nigerian children. This may largely be attributed to the adoption and deployment of ACTs in Nigeria. In addition, other concurrent interventions such as broader distribution of long-lasting insecticide treated net (LLIN), may be a contributing factor [26]. Another measure of parasite diversity is the number of effective alleles (Ne) detected per microsatellite locus. It is expected that the number of Ne detected per locus is likely to be high in areas with high malaria endemicity and vice versa [5, 19]. The observed mean Ne in parasites obtained from all States (5.4 - 8.2) were comparable to those reported in other high-endemic regions of Sub-Saharan Africa [4, 5, 34]. The distribution of observed mean Ne in the Northern and Southern States were similar (p\u0026gt;0.05). This is equally expected as malaria endemicity continues to be high throughout Nigeria. Estimated allelic diversity (computed as expected heterozygosity-He), was high in all States with values ranging from 0.774 to 0.825. This suggests that parasites from these States exhibited high heterozygosity, which depicts high parasite transmission [35]. Similar high He values have been reported in other parts of Nigeria (Ekiti State: 0.79 and Lagos State: 0.65) and other countries with high levels of malaria transmission [5, 6, 18, 36, 37].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAlthough parasite diversity was high, further analysis of microsatellite data generated revealed low parasite population differentiation. Analysis of molecular variance (AMOVA) and genetic differentiation index (F\u003csub\u003eST\u003c/sub\u003e) values obtained were 0.039 and 0.038 respectively, which is low [36, 38]. This implies that about 96% of genetic variations observed among parasites were within populations. The principal component analysis (PCA) of all nine States further confirmed genetic similarities amongst parasite populations as similar clustering patterns consistent with low levels of genetic differentiation were observed. Linkage disequilibrium (LD) values for each parasite population ranged from 0.0037 in Kwara to 0.0715 in Adamawa. The overall association index was 0.0219, which is weaker than those typically reported in regions with low transmission [21, 23]. Studies have associated low LD values such as those reported in this study, to high levels of malaria transmission; which leads to increased cross-breeding and meiotic recombination that results in LD breakdown [5, 6, 19, 39]. Although the LD values obtained in this study remain low, there is a need to continually monitor parasite populations within Nigeria to detect new variants that may inform adaptation against interventions currently employed. The perceived lack of genetic differentiation or sub-structuring between States as evidenced by results obtained from AMOVA, Fst, PCA and LD analysis, is probably as a result of immense human migration between these populations as part of the usual socioeconomic activities and indiscriminate vector migration within the country [6, 40, 41, 42].\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study represents the first use of 12 polymorphic microsatellite loci to characterize parasite diversity and structure in Nigeria across regions representing all the six geographical zones of the country. The high level of genetic diversity and low population structuring in this study suggests that parasite populations circulating in Nigeria are homogenous. This implies that a uniform control strategy will be effective across the six geographical zones. The results obtained can be used as a baseline for parasite diversity and structure, aiding in the formulation of appropriate therapeutic and control strategies in Nigeria.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePCR: Polymerase chain reaction\u003c/p\u003e\n\u003cp\u003eMSP1: Merozoite surface protein 1\u003c/p\u003e\n\u003cp\u003eMSP2: Merozoite surface protein 2\u003c/p\u003e\n\u003cp\u003eGLURP: Glutamate-rich protein\u003c/p\u003e\n\u003cp\u003eDBS: Dried blood spot\u003c/p\u003e\n\u003cp\u003eCOI: Complexity of infection\u003c/p\u003e\n\u003cp\u003emCOI: Mean complexity of infection\u003c/p\u003e\n\u003cp\u003eNa: Number of alleles\u003c/p\u003e\n\u003cp\u003eNe: Number of effective alleles\u003c/p\u003e\n\u003cp\u003eHe: Expected heterozygosity\u003c/p\u003e\n\u003cp\u003eAMOVA: Analysis of molecular variance\u003c/p\u003e\n\u003cp\u003eFST: Fixation index\u003c/p\u003e\n\u003cp\u003ePCA: Principal component analysis\u003c/p\u003e\n\u003cp\u003eLD: Linkage disequilibrium\u003c/p\u003e\n\u003cp\u003eACTs: Artemisinin combination therapies\u003c/p\u003e\n\u003cp\u003eLLIN: Long lasting insecticide net\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all the patients, their parents or guardians for volunteering to participate in the study. We also acknowledge the principal investigators (PI) in each of the nine sentinel locations considered in this study. The National Malaria Elimination Program of the Federal Ministry of Health in Nigeria for the year 2014-2018.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), World Bank (ACE019) and The National Institute of Health (grants U01HG007480, U54HG007480). The U.S President\u0026rsquo;s Malaria Initiative (USPMI) funded the primary drug efficacy study from which samples were obtained for the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFehintola V. Ajogbasile and Adeyemi T. Kayode contributed equally to this work.\u003c/p\u003e\n\u003cp\u003eAffiliations\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAfrican Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer\u0026rsquo;s University, Ede, Nigeria.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFehintola V. Ajogbasile, Adeyemi T. Kayode, Kazeem O. Akano, Paul E. Oluniyi, Jessica N. Uwanibe, Benjamin B. Adegboyega, Courage Philip, Philomena J. Eromon, Onikepe A. Folarin Christian T. Happi\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Biological Sciences, Faculty of Natural Sciences, Redeemer's University, Ede, Nigeria \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFehintola V. Ajogbasile, Adeyemi T. Kayode, Kazeem O. Akano, Paul E. Oluniyi, Jessica N. Uwanibe, Onikepe A. Folarin, Christian T. Happi\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Biological Sciences, Covenant University, Ota, Nigeria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOluwagboadurami G. John\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Paediatrics, Imo State University Teaching Hospital, Orlu, Nigeria \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGeorge Emechebe\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Paediatrics, Federal Medical Centre, Yenagoa, Nigeria \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFinimo Finimo\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCase Management Unit, National Malaria Elimination Programme, Federal Ministry of Health, Abuja, Nigeria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNnenna Ogbulafor\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Paediatrics, Uthman Dan Fodio University, Sokoto, Nigeria \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNma Jiya\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Paediatrics, University of Nigeria Teaching Hospital, University of Nigeria, Nsukka, Nigeria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUche Okafor\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Paediatrics, University of Maiduguri, Nigeria \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJose Ambe\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Paediatrics, Ahmadu Bello University, Zaria, Nigeria \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRobinson D. Wammanda\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Paediatrics, University of Jos Teaching Hospital, University of Jos, Nigeria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStephen Oguche\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Paediatrics and Child Health, University of Ilorin, Nigeria \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOlugbenga Mokuolu\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitute of Medical Research and Training, College of Medicine, University of Ibadan, Ibadan, Nigeria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAkintunde Sowunmi\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Pharmacology and Therapeutics, University of Ibadan, Ibadan, Nigeria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAkintunde Sowunmi\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding Author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChristian T. Happi\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eF.V.A., A.T.K., B.B.A., C.P., J.N.U., O.G.J., N.O., U.O., S.O., J.A., R.D.W., N.J., F.F., G.E., and O.M carried out the experiments and acquired data; C.T.H. conceived the study; F.V.A., A.T.K., K.O.A. and P.E.O performed data analysis and interpretation; F.V.A and A.T.K wrote the paper; K.A.O., P.E.O., J.N.U., P.J.E., A.S., O.A.F and C.T.H reviewed and revised the manuscript; P.J.E., A.S., O.A.F and C.T.H. supervised the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the National Health Research Ethics Committee, Federal Ministry of Health (FMOH), Abuja, Nigeria. Informed consent was obtained from parents and legal guardians of participants prior to enrollment in study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data analyzed for this manuscript is available upon request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCeesay SJ, Casals-Pascual C, Erskine J, Anya SE, Duah NO, Fulford AJC, et al. Changes in malaria indices between 1999 and 2007 in The Gambia: a retrospective analysis. Lancet. 2008;372: 1545\u0026ndash;1554.\u003c/li\u003e\n\u003cli\u003eO\u0026rsquo;Meara WP, Bejon P, Mwangi TW, Okiro EA, Peshu N, Snow RW, et al. Effect of a fall in malaria transmission on morbidity and mortality in Kilifi, Kenya. Lancet. 2008;372: 1555\u0026ndash;1562.\u003c/li\u003e\n\u003cli\u003eJaenisch T, Sullivan DJ, Dutta A, Deb S, Ramsan M, Othman MK, et al. Malaria incidence and prevalence on Pemba island before the onset of the successful control intervention on the Zanzibar archipelago. Malar J. 2010;9: 32.\u003c/li\u003e\n\u003cli\u003eBogreau H, Renaud F, Bouchiba H, Durand P, Assi S-B, Henry M-C, et al. Genetic diversity and structure of African Plasmodium falciparum populations in urban and rural areas. Am J Trop Med Hyg. 2006;74: 953\u0026ndash;959.\u003c/li\u003e\n\u003cli\u003eMulenge FM, Hunja CW, Magiri E, Culleton R, Kaneko A, Aman RA. Genetic Diversity and Population Structure of Plasmodium falciparum in Lake Victoria Islands, A Region of Intense Transmission. Am J Trop Med Hyg. 2016;95: 1077\u0026ndash;1085.\u003c/li\u003e\n\u003cli\u003eOyebola MK, Idowu ET, Olukosi YA, Iwalokun BA, Agomo CO, Ajibaye OO, et al. Genetic diversity and complexity of Plasmodium falciparum infections in Lagos, Nigeria. Asian Pac J Trop Biomed. 2014;4: S87\u0026ndash;91.\u003c/li\u003e\n\u003cli\u003eAriey F, Chalvet W, Hommel D, Peneau C, Hulin A, Mercereau-Puijalon O, et al. Plasmodium falciparum parasites in French Guiana: limited genetic diversity and high selfing rate. Am J Trop Med Hyg. 1999;61: 978\u0026ndash;985.\u003c/li\u003e\n\u003cli\u003eHaddad D, Snounou G, Mattei D, Enamorado IG, Figueroa J, St\u0026aring;hl S, et al. Limited genetic diversity of Plasmodium falciparum in field isolates from Honduras. Am J Trop Med Hyg. 1999;60: 30\u0026ndash;34.\u003c/li\u003e\n\u003cli\u003eAtroosh WM, Al-Mekhlafi HM, Mahdy MA, Saif-Ali R, Al-Mekhlafi AM, Surin J. Genetic diversity of Plasmodium falciparum isolates from Pahang, Malaysia based on MSP-1 and MSP-2 genes. Parasit Vectors. 2011;4: 233.\u003c/li\u003e\n\u003cli\u003eEngelbrecht F, T\u0026ouml;gel E, Beck HP, Enwezor F, Oettli A, Felger I. Analysis of Plasmodium falciparum infections in a village community in Northern Nigeria: determination of msp2 genotypes and parasite-specific IgG responses. Acta Trop. 2000;74: 63\u0026ndash;71.\u003c/li\u003e\n\u003cli\u003eHappi CT, Gbotosho GO, Sowunmi A, Falade CO, Akinboye DO, Gerena L, et al. Molecular analysis of Plasmodium falciparum recrudescent malaria infections in children treated with chloroquine in Nigeria. Am J Trop Med Hyg. 2004;70: 20\u0026ndash;26.\u003c/li\u003e\n\u003cli\u003eAmodu OK, Adeyemo AA, Ayoola OO, Gbadegesin RA, Orimadegun AE, Akinsola AK, et al. Genetic diversity of the msp-1 locus and symptomatic malaria in south-west Nigeria. Acta Trop. 2005;95: 226\u0026ndash;232.\u003c/li\u003e\n\u003cli\u003eOlasehinde GI, Yah CS, Singh R, Ojuronbge OO, Ajayi AA, Valecha N, et al. Genetic diversity of Plasmodium falciparum field isolates from south western Nigeria. Afr Health Sci. 2012;12: 355\u0026ndash;361.\u003c/li\u003e\n\u003cli\u003eOyedeji SI, Awobode HO, Kun J. Limited Genetic Diversity and Low Multiplicity of Plasmodium falciparum Infections in Children with Severe Malaria in Lafia, North-central Nigeria. Journal of Experimental \u0026amp; Clinical Medicine. 2013;5: 143\u0026ndash;147.\u003c/li\u003e\n\u003cli\u003eHughes AL. Positive selection and interallelic recombination at the merozoite surface antigen-1 (MSA-1) locus of Plasmodium falciparum. Mol Biol Evol. 1992;9: 381\u0026ndash;393.\u003c/li\u003e\n\u003cli\u003eHughes MK, Hughes AL. Natural selection on Plasmodium surface proteins. Mol Biochem Parasitol. 1995;71: 99\u0026ndash;113.\u003c/li\u003e\n\u003cli\u003eEscalante AA, Lal AA, Ayala FJ. Genetic polymorphism and natural selection in the malaria parasite Plasmodium falciparum. Genetics. 1998;149: 189\u0026ndash;202.\u003c/li\u003e\n\u003cli\u003eMobegi VA, Loua KM, Ahouidi AD, Satoguina J, Nwakanma DC, Amambua-Ngwa A, et al. Population genetic structure of Plasmodium falciparum across a region of diverse endemicity in West Africa. Malar J. 2012;11: 223.\u003c/li\u003e\n\u003cli\u003eAnderson TJ, Haubold B, Williams JT, Estrada-Franco JG, Richardson L, Mollinedo R, et al. Microsatellite markers reveal a spectrum of population structures in the malaria parasite Plasmodium falciparum. Mol Biol Evol. 2000;17: 1467\u0026ndash;1482.\u003c/li\u003e\n\u003cli\u003eBonizzoni M, Afrane Y, Baliraine FN, Amenya DA, Githeko AK, Yan G. Genetic structure of Plasmodium falciparum populations between lowland and highland sites and antimalarial drug resistance in Western Kenya. Infect Genet Evol. 2009;9: 806\u0026ndash;812.\u003c/li\u003e\n\u003cli\u003eLarra\u0026ntilde;aga N, Mej\u0026iacute;a RE, Hormaza JI, Montoya A, Soto A, Fontecha GA. Genetic structure of Plasmodium falciparum populations across the Honduras-Nicaragua border. Malar J. 2013;12: 354.\u003c/li\u003e\n\u003cli\u003eVolkman SK, Neafsey DE, Schaffner SF, Park DJ, Wirth DF. Harnessing genomics and genome biology to understand malaria biology. Nat Rev Genet. 2012;13: 315\u0026ndash;328.\u003c/li\u003e\n\u003cli\u003ePumpaibool T, Arnathau C, Durand P, Kanchanakhan N, Siripoon N, Suegorn A, et al. Genetic diversity and population structure of Plasmodium falciparum in Thailand, a low transmission country. Malar J. 2009;8: 155.\u003c/li\u003e\n\u003cli\u003eBranch OH, Sutton PL, Barnes C, Castro JC, Hussin J, Awadalla P, et al. Plasmodium falciparum genetic diversity maintained and amplified over 5 years of a low transmission endemic in the Peruvian Amazon. Mol Biol Evol. 2011;28: 1973\u0026ndash;1986.\u003c/li\u003e\n\u003cli\u003eNkhoma SC, Nair S, Al-Saai S, Ashley E, McGready R, Phyo AP, et al. Population genetic correlates of declining transmission in a human pathogen. Mol Ecol. 2013;22: 273\u0026ndash;285.\u003c/li\u003e\n\u003cli\u003eBankole BE, Kayode AT, Nosamiefan IO, Eromon P, Baniecki ML, Daniels RF, et al. Characterization of Plasmodium falciparum structure in Nigeria with malaria SNPs barcode. Malar J. 2018;17: 472.\u003c/li\u003e\n\u003cli\u003eAnderson TJ, Su XZ, Bockarie M, Lagog M, Day KP. Twelve microsatellite markers for characterization of Plasmodium falciparum from finger-prick blood samples. Parasitology. 1999;119 ( Pt 2): 113\u0026ndash;125.\u003c/li\u003e\n\u003cli\u003ePeakall R, Smouse PE. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update. Bioinformatics. 2012;28: 2537\u0026ndash;2539.\u003c/li\u003e\n\u003cli\u003eMohammed H, Kassa M, Mekete K, Assefa A, Taye G, Commons RJ. Genetic diversity of the msp-1, msp-2, and glurp genes of Plasmodium falciparum isolates in Northwest Ethiopia. Malar J. 2018;17: 386.\u003c/li\u003e\n\u003cli\u003eMetsalu T, Vilo J. ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap. Nucleic Acids Res. 2015;43: W566\u0026ndash;70.\u003c/li\u003e\n\u003cli\u003eHaubold B, Hudson RR. LIAN 3.0: detecting linkage disequilibrium in multilocus data. Linkage Analysis. Bioinformatics. 2000;16: 847\u0026ndash;848.\u003c/li\u003e\n\u003cli\u003eSouza V, Nguyen TT, Hudson RR, Pi\u0026ntilde;ero D, Lenski RE. Hierarchical analysis of linkage disequilibrium in Rhizobium populations: evidence for sex? Proc Natl Acad Sci U S A. 1992;89: 8389\u0026ndash;8393.\u003c/li\u003e\n\u003cli\u003eHappi CT, Gbotosho GO, Folarin OA, Bolaji OM, Sowunmi A, Kyle DE, et al. Association between mutations in plasmodium falciparum chloroquine resistance transporter and p. falciparum multidrug resistance 1 genes and in vivo amodiaquine resistance in p. falciparum malaria\u0026ndash;infected children in nigeria. Am J Trop Med Hyg. 2006;75: 155\u0026ndash;161.\u003c/li\u003e\n\u003cli\u003eZhong D, Afrane Y, Githeko A, Yang Z, Cui L, Menge DM, et al. Plasmodium falciparum genetic diversity in western Kenya highlands. Am J Trop Med Hyg. 2007;77: 1043\u0026ndash;1050.\u003c/li\u003e\n\u003cli\u003eMwingira F, Nkwengulila G, Schoepflin S, Sumari D, Beck H-P, Snounou G, et al. Plasmodium falciparum msp1, msp2 and glurp allele frequency and diversity in sub-Saharan Africa. Malar J. 2011;10: 79.\u003c/li\u003e\n\u003cli\u003eConway DJ, Machado RL, Singh B, Dessert P, Mikes ZS, Povoa MM, et al. Extreme geographical fixation of variation in the Plasmodium falciparum gamete surface protein gene Pfs48/45 compared with microsatellite loci. Mol Biochem Parasitol. 2001;115: 145\u0026ndash;156.\u003c/li\u003e\n\u003cli\u003eDurand P, Michalakis Y, Cestier S, Oury B, Leclerc MC, Tibayrenc M, et al. Significant linkage disequilibrium and high genetic diversity in a population of Plasmodium falciparum from an area (Republic of the Congo) highly endemic for malaria. Am J Trop Med Hyg. 2003;68: 345\u0026ndash;349.\u003c/li\u003e\n\u003cli\u003eBalloux F, Lugon-Moulin N. The estimation of population differentiation with microsatellite markers. Mol Ecol. 2002;11: 155\u0026ndash;165.\u003c/li\u003e\n\u003cli\u003eAnthony TG, Conway DJ, Cox-Singh J, Matusop A, Ratnam S, Shamsul S, et al. Fragmented population structure of plasmodium falciparum in a region of declining endemicity. J Infect Dis. 2005;191: 1558\u0026ndash;1564.\u003c/li\u003e\n\u003cli\u003eSchultz L, Wapling J, Mueller I, Ntsuke PO, Senn N, Nale J, et al. Multilocus haplotypes reveal variable levels of diversity and population structure of Plasmodium falciparum in Papua New Guinea, a region of intense perennial transmission. Malar J. 2010;9: 336.\u003c/li\u003e\n\u003cli\u003eLum JK, Kaneko A, Tanabe K, Takahashi N, Bj\u0026ouml;rkman A, Kobayakawa T. Malaria dispersal among islands: human mediated Plasmodium falciparum gene flow in Vanuatu, Melanesia. Acta Trop. 2004;90: 181\u0026ndash;185.\u003c/li\u003e\n\u003cli\u003eLum JK, Kaneko A, Taleo G, Amos M, Reiff DM. Genetic diversity and gene flow of humans, Plasmodium falciparum, and Anopheles farauti s.s. of Vanuatu: inferred malaria dispersal and implications for malaria control. Acta Trop. 2007;103: 102\u0026ndash;107.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Malaria, Plasmodium falciparum, Genetic diversity, Microsatellite, Nigeria","lastPublishedDoi":"10.21203/rs.3.rs-90709/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-90709/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eMalaria 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. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eIn this study, we characterized parasite diversity and structure of \u003cem\u003ePlasmodium falciparum\u003c/em\u003e isolates from 633 dried blood spot samples in Nigeria, using 12 microsatellite loci of \u003cem\u003eP. falciparum\u003c/em\u003e. These microsatellites were amplified via semi-nested polymerase chain reaction (PCR) and fragments were analyzed using GeneMapper and GENALEX 6.5.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eEstimates of parasite diversity such as Mean complexity of infection (range: 1.71-2.66) and Expected heterozygosity (range: 0.76-0.82) were high, while parasite population sub-structuring was low (Analysis of molecular variance= 0.039, Fixation index= 0.038 and Linkage disequilibrium= 0.0219). \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eWe conclude that the high level of genetic diversity and low population structuring in this study suggests that parasite populations circulating in Nigeria are homogenous. This implies that a uniform control strategy will be effective across the six geographical zones of Nigeria. The results obtained can be used as a baseline for parasite diversity and structure, aiding in the formulation of appropriate therapeutic and control strategies in Nigeria.\u003c/p\u003e","manuscriptTitle":"Genetic Diversity and Population Structure of Plasmodium Falciparum in Nigeria: Insights From Microsatellites Loci Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-10-13 14:46:51","doi":"10.21203/rs.3.rs-90709/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major Revision","date":"2020-12-24T00:00:00+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-12-23T00:00:00+00:00","index":3,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"editorInvitedReview","content":"","date":"2020-12-02T00:00:00+00:00","index":2,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"reviewerAgreed","content":"","date":"2020-12-02T00:00:00+00:00","index":3,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-12-02T00:00:00+00:00","index":1,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"reviewerAgreed","content":"","date":"2020-11-12T00:00:00+00:00","index":2,"fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-11-10T00:00:00+00:00","index":1,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-10-23T12:00:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2020-10-07T12:00:00+00:00","index":"","fulltext":""},{"type":"submitted","content":"","date":"2020-10-06T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-10-06T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-10-06T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"358c09f9-2b22-475c-b73f-317b1048e687","owner":[],"postedDate":"October 13th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":762462,"name":"Infectious Diseases"}],"tags":[],"updatedAt":"2021-05-27T12:41:12+00:00","versionOfRecord":[],"versionCreatedAt":"2020-10-13 14:46:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-90709","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-90709","identity":"rs-90709","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}