Population Structure and Genetic Relationships among Nigerian Ethnic Groups (Ibibio, Igbo, Hausa, Tiv and Yoruba) Based on Nine Short Tandem Repeat Loci

Population Structure and Genetic Relationships among Nigerian Ethnic Groups (Ibibio, Igbo, Hausa, Tiv and Yoruba) Based on Nine Short Tandem Repeat Loci | 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 Article Population Structure and Genetic Relationships among Nigerian Ethnic Groups (Ibibio, Igbo, Hausa, Tiv and Yoruba) Based on Nine Short Tandem Repeat Loci Utom-Obong U. Akpan, Oluwafemi D. Amusa, Olumide A. Adebesin, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4670501/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The genetic relationships between populations can be detected with the use of genetic markers. This study investigated the genetic relationships between five Nigerian populations of Igbo, Ibibio, Yoruba, Tiv and Hausa origin using nine short tandem repeat markers. The nine loci and the sex-typing marker amelogenin were combined into multiplex assays and tested by PCR followed by polyacrylamide gel electrophoresis on 50 individuals per population. The study revealed that four (4) of the nine (9) loci had F ST values between 0.001 and 0.500 in the five populations, indicating that population substructure had almost disappeared in the pooled population. The molecular variance (AMOVA) for the pooled population revealed a variance of 3.850 for individuals and a variance of 0.0004 for among populations. Principal component analysis (PCA) revealed four heterogeneous clusters. The total variation explained by the first three axes of the PCA was 32.86%. All the populations had a pairwise population matrix of Nei genetic identity greater than 0.895 based on these loci. Both the pairwise population matrix and a dendrogram constructed based on the allele frequencies of these loci indicated that the Igbo and Yoruba ethnic groups had the highest genetic similarity (0.993) among the evaluated populations. The pairwise population matrix of Nei genetic distance showed that Igbo and Tiv and Igbo and Ibibio had genetic distances of 0.14 and 0.15, respectively, which were the greatest for all pairs of the five populations. Population Biology Evolutionary Biology Evolutionary Genetics Molecular Genetics Population Genetics Relationship Alleles Ethnic Population Nigeria Figures Figure 1 Figure 2 Figure 3 Figure 4 INTRODUCTION Research into the genetic diversity of African populations has intensified in the last few decades. During this time, African populations have been observed to have the highest genetic diversity among other human populations (Yu et al., 2002 ; Tishkoff and Williams, 2002 ; Campbell and Tishkoff, 2008 ; Chodhury et al. , 2018). Nigeria is located in Western Africa, bordering the Gulf of Guinea, between the Benin Republic, Niger Republic, Chad and Cameroon, with a landmass of 923,768 sq. km and a population of approximately 220 million people (Eberhard et al., 2024 ). Estimates of the number of distinct ethnic groupings vary from 250 to as many as 580, with the most prominent being Hausa, Edo, Fulani, Ibibio, Kanuri, Nupe, Tiv, Ijaw, Itsekiri, Urhobo, Aguleri, Umuleri, Jukun, Ogoni, Mambila, Banso, Kamba, Yoruba, and Igbo (Ibo). There are 515 languages spoken for Nigeria, including English (official), Hausa, Yoruba, Igbo (Ibo), Fulani, Edo, Ibibio, Kanuri, Efik, Ijaw, and Nupe Tiv (Eberhard et al., 2024 ). One must be aware that these discrepancies in numbers result from the fact that these groups are delineated by linguistic differences. Few studies have investigated the population genetic structure of the Nigerian human population(s). Veeramah et al. ( 2010 ) examined genetic differentiation using uniparental markers against substantial language variation in peoples of the Cross River region of Nigeria, revealing the overall genetic homogeneity in the Cross River region in the face of such language variation. The results were obtained by examining mtDNA (mitochondrial DNA) and microsatellites from the nonrecombining region of the Y chromosome (NRY) in males from the region. Adeyemo et al. ( 2005 ) investigated the stratification of genetic structures in four West African population groups. Two Nigerian groups, Igbo and Yoruba, were studied together with two Ghanaian groups, examining 372 autosomal microsatellite loci in 497 unrelated individuals. Using RAPD markers, Titilayo et al. ( 2018 ) reported on the genetic variation among Igbo, Yoruba and Hausa samples. Recently, Joshi et al. ( 2023 ) provided insights into the genetic diversity of 47 Nigerian populations using whole-genome sequences of 449 individuals. These populations included the Hausa, Yoruba, Igbo and Ibibio populations. The diversity and structure of most of the 520 ethnolinguistic groups in Nigeria, including the Tiv, are still largely undefined. There is a need to study more groups to further elucidate the genetic diversity of Africans in general and Nigeria in particular (Veermah et al. ,2010; Tucci and Akey, 2019 ). Genetic studies have shown the Igbo to cluster most closely with other Niger-Congo-speaking peoples (Campbell and Tishkoff, 2008 ). They also predominantly have the E1b1a1-M2 Y-chromosome haplogroup (Veeramah et al., 2010 ). Yorubas have been the subject of many genetic studies since the collection of samples from Ibadan, called Yoruba in Ibadan (YRI), for some genomic studies. One such study showed that ~ 31% of Yoruba people have prehistoric "basal human" admixture (Schlebusch et al., 2017 ). Campbell and Tishkoff ( 2008 ) reported that the Yoruba cluster most closely with other West African peoples. According to a Y-DNA study by Hassan et al. ( 2008 ), approximately 47% of Hausa in Niger, Cameroon, Nigeria and Sudan carry the West Eurasian haplogroup R1b. The remainder belong to various African paternal lineages: 15.6% B, 12.5% A and 12.5% E1b1a. A small minority (approximately 4%) were E1b1b clade bearers, a haplogroup that is most common in North Africa and the Horn of Africa. In terms of overall ancestry, Tishkoff et al . (2009) found Hausa to be most closely related to Nilotic populations from Nigeria, Cameroon, central Chad and South Sudan. The Hausa population has also been reported to exhibit high genetic variability in a global analysis of dinucleotide repeats, presenting the highest heterozygosity of all the populations studied (Deka, et al. 1995 ). A study has shown that the Ibibio cluster contains the Yoruba, Ibibio, Bini, Igbo, and Izon ethnolinguistic groups (Joshi et al., 2023 ). There is still no reported genetic relationship for the Tiv ethnolinguistic group. The advent of genetic markers has made it possible to study population genetics at the molecular level, providing better diversity estimates. One such type is short tandem repeats (STRs). These are microsatellites with short sequences of DNA (1–10 base pairs) lying within genetic markers and short tandem repeats (STRs) end to end in a particular region of the genome (the loci) (Chatumal et al., 2010 ). Generally, they fall within noncoding regions and flanking sequences in the genome but occasionally within coding regions (Edwards et al., 1991 ). Microsatellites are typically characterized by a high mutation rate and therefore a high level of polymorphism, resulting in different alleles in the population (Zhu et al., 2000 ; Hardy et al., 2003 ). There are several thousand STR loci in the human genome. STRs on non-sex chromosomes are widely used as genetic markers in human identification, forensics, paternity investigations and other cases of kinship analysis. The loci are usually typed using polymerase chain reaction (PCR) and electrophoresis. When a sufficient number of loci are tested, a genetic profile is generated that statistically provides the discriminating power needed for human identification (Butler and Hill, 2012 ). Population structure appears as extensive allelic diversity and heterozygosity at the genomic level. Contemporary approaches use molecular markers, including SNPs and STR data, to reveal genetic diversity in populations (Hannelius et al., 2008 ). Several assumptions and relationships exist between the properties of molecular markers, and these could be used to estimate genetic diversity in populations. These methods include principal component analysis (PCA), the fixation index ( F ST ), analysis of molecular variance (AMOVA), and Nei's genetic distance, with varying degrees of precision. Presently, these measures of population structure and population genetics are usually estimated using software programs. The list of programs can be obtained from different websites, including DuckDNA ( https://www.duckdna.org/softwares/ ) and the University of Washington (WU) popgen software page ( https://courses.washington.edu/popgen/Software.htm ). Genomic PCA is based on the eigenvectors of the covariance matrix derived from the genotypes of individuals in the population. These eigenvectors provide an efficient linear combination of marker data with the greatest discriminating ability between the samples without requiring prior sample classification information. The power of PCA to resolve highly structured populations depends on nonrandom patterns of genetic variation. Models of natural population structure indicate that most of the eigenvalues of covariance are small, nearly equal, and arise from sampling noise. Larger eigenvalues reflect past events on the population (Patterson et al., 2006 ). Sampling noise can be reduced by filtering the data to remove one member of a marker pair that is in tight linkage disequilibrium (Pattterson et al. , 2006; Canas-Alvarez et al ., 2015; Malomane et al., 2018 ) or by using approaches such as shrinkage PCA or iterative pruning PCA (Zou et al., 2010 ; Intrapranich et al ., 2009; Limpiti et al ., 2011). Wright introduced the fixation index to measure genetic differences between subdivided populations (Nagylaki, 1998 ). He proposed three parameters that focused on the total population ( F IT ), subdivisions ( F ST ), and individuals ( F IS ). The F IT is the ratio of gametes that produce individuals to gametes in the total population. It gives the ratio of the variance of gene frequencies of random breeding subdivisions (if these occur) to its maximum possible value, which is expected if the subdivisions are completely isolated and each is completely fixed, thus forming an array. The F IT is an assessment of the total (T) generations. F IS is the average over all subdivisions of the correlation between uniting gametes relative to those of their own subdivision. It is also referred to as the inbreeding coefficient. F ST is the correlation between random gametes within subdivisions relative to gametes of the total population. The three F-statistics are related by the formula F ST = ( F IT – F IS )/(1- F IS ) (Wright, 1965). These parameters are also related to probabilities of identity by origin and the levels of heterozygosity in and between the populations. Fixation index ( F ST ) estimation helps to determine how different a group of populations is from each other. Most importantly, however, the F ST is the ratio of the actual variance in the gene frequencies of subdivisions to its limiting value, irrespective of their own structures. F ST is thus necessarily positive. F IS , while usually positive, is negative if there is systematic avoidance of consanguine mating within the subdivisions. F IT is positive if there is systematic subdivision, whether into demes ( F IS = 0, F IT = F ST ) or into inbred groups, but can be negative if there is no systematic subdivision and there is prevailing avoidance of consanguine mating. In addition to Wright's assumptions and the establishment of these relationships, Weir & Cockerham (Weir & Cockerham, 1984 ), Nei ( 1986 ) and Hudson et al . (Hudson 1992) described and proposed other approaches for deriving these F-statistics. However, weir and Cockerham's method is sensitive to sample size, and Nei's method consistently overestimates the F ST, whereas Hudson’s estimator is more precise (Samaragdov & Kudinov, 2020). It is not sensitive to the sample size ratio, it does not systematically overestimate the F ST , and it is accurate and stable under various ascertainment schemes. F ST values can range from 0 to 1, where 0 indicates complete sharing of genetic material (two populations interbred freely) or a panmictic population, 1 indicates that all genetic variation is explained by population structure and that the two populations do not share any genetic identity and are fixed (Barbosa et al. 2019 ; Khan et al., 2021 ). An estimated fixation index less than 0.05 indicates that little genetic difference between 0.05–0.15 indicates moderate genetic difference, 0.15–0.25 indicates great genetic difference, and 0.25 indicates very great genetic difference (Hartl & Clark,1997). If considered in two broad categories, an F ST greater than 0.15 represents significant differentiation, and an F ST less than 0.05 reflects insignificant differentiation (Frankham et al., 2002 ). F ST values can be skewed by the frequency of the most frequent allele. The analysis of molecular variance (AMOVA) is an alternative methodology that makes use of the available molecular information gathered in population surveys to accommodate different assumptions about the evolution of the genetic system (Excoffier et al. 1992 ). It translates information from molecular markers into estimates of the magnitude of intraspecific subdivision, provides estimates of the variance in nucleotide diversity for different sampling processes and computes the fraction of nucleotide diversity due to interpopulation genetic differences while remaining irrespective of evolutionary history. Excoffier et al. ( 1992 ) constructed a hierarchical analysis of molecular variance directly from the matrix of squared distances between all pairs of haplotypes based on interpreting the conventional sum of squares (SS) as the sum of squared differences between all pairs of observations. Beyond its clear relation to an analysis of variance, the method has the additional advantage that several different assumptions can be imposed on the haplotype differentiation process, each of which translates into a different distance matrix, with no change in the structure of the subsequent analysis. When all distances between haplotypes are presumed to be equal, the analysis is equivalent to a multiallelic (multivariate) analysis of variance. Taken together, these measures of population genetic parameters can reveal valuable information on population structure and history. Therefore, the aim of this study was to investigate the genetic relationships between the five Nigerian populations of Igbo, Ibibio, Yoruba, Tiv and Hausa using nine short tandem repeat markers. MATERIALS AND METHODS Ethical Approval Approval for the research, consent forms and biosample collection methods was obtained from the Ethics Review Board of the Lagos University Teaching Hospital with reference ADM/DCST/HREC/1921. Collection of Samples Sample size determination The sampling method was an initial cluster sampling of five selected ethnic groups from Nigeria, followed by a random sampling of individuals from the chosen ethnic groups. The ethnic populations in the study were chosen to represent the three largest groups (Igbo, Yoruba and Hausa) and two smaller groups (one Northern and one Southern - Tiv and Ibibio, respectively) in Nigeria. The population sizes of these ethnic groups are as follows: Yoruba, 18,900,000; Hausa, 18,500,000; Igbo, 18,000,000; Ibibio, 4,700,000; and Tiv, 2,210,000 (Lewis et al., 2014). The estimated effective population size of each of the chosen ethnic groups was less than 50 individuals based on the method of Hale et al. (2012). However, 50 individuals were sampled from each population, and data from 50 individuals were presented to allow for comparisons between the groups (Bashalkhanov et al ., 2009). Participant Recruitment and Consent Potential participants who self-identified as being from any of the Hausa, Yoruba, Igbo, Ibibio or Tiv ethnic/linguistic groups were recruited at the blood donor clinic of the participating hospitals. These hospitals are in regions with a high density of members of the ethnic groups included in the study. It includes the Lagos University Teaching Hospital (LUTH) and locations in Ilesha, Osun State and Ogbomoso, Oyo (for Yoruba), the University of Uyo Teaching Hospital (UUTH) (for Ibibio) and Aminu Kano Teaching Hospital (AKTH) (for Hausa), Anambra State University Teaching Hospital (ANSUTH), Amaku, and Awka communities in Anambra State (for Igbo) and Benue State University Teaching Hospital, Makurdi (for Tiv) (see Figure 1). Sociological data were also collected from each individual, including date of birth (or age), current residence, birthplace, self-declared cultural identity, first language, second language (when available) and ethnic affiliation. The ethnic origins of both paternal and maternal grandparents were also obtained. No names or addresses were obtained or recorded. Biosample collection and storage Two types of samples were collected from participants depending on their preference: peripheral blood. Whole blood (3-5 ml) was drawn from participating individuals by venipuncture. Blood was collected from each sample into an anticoagulant storage bottle labelled with a unique anonymous identifier, temporarily stored in mobile ice coolers, transported to the Department of Cell Biology & Genetics, University of Lagos, and stored at -80 °C. Molecular Analysis of STRs Extraction and quantification of DNA Genomic DNA was extracted from white blood cells present in the blood samples using Omega Biotek E.Z.N.A. Forensic DNA Mini Kit. Briefly, whole blood was lysed using a cocktail of lysis buffer. The supernatant was centrifuged, and proteins were removed using a protease (proteinase-K). The DNA was washed in spin columns and eluted using TE buffer. The recovered DNA was stored for use in quantification and PCR analysis. The quality of the DNA was assessed on a 1% agarose gel run at 70 mV for 45 minutes. The DNA was quantified using a NanoDrop spectrophotometer. Locus Selection The autosomal STR markers used in the study were selected from the lists of STRs with a high number of genotypes observed, high heterozygosity, high polymorphism information content value and good probability of identity values in African American, African and other black populations. A total of 10 STR loci (including the sex-typing marker amelogenin) were chosen. The loci are D21S11, FGA, D18S51, D2S1338, D10S1248, D22S1045, D9S2157, D6S1017, D8S1179, and Amelogenin. The sequences of primers used were obtained from the literature (Hill et al .,2008, and STRBase,2015) (Table 1). Based on these sequences, PCR primer oligonucleotides were purchased from Inqaba Biotec, South Africa. The nine (9) loci were tested as four miniplexes of two 2-primer pairs and two 3-primer pairs based on product size. Primer-primer comparison to avoid excessive regions of complementarity between primers was performed using the software AutoDimer (Vallone & Butler, 2004). A visual schematic of the multiplex loci was prepared to provide a visual representation of the loci and highlight areas of possible size overlap. The miniplexes were then named M01, M02, M03 and M04 (Figure 2). Table 1: List of primers S/NO LOCUS NAME GENBANK ACCESSION PRIMER SEQUENCE (5′ - 3′) REFERENCES 1 D2S1338 AC010136 ACTGCAGTCCAATCTGGGT Krenke et al ., 2002 ATGAAATCAACAGAGGCTTGC 2 FGA M64982 GGCTGCAGGGCATAACATTA Krenke et al ., 2002 alpha fibrinogen 3rd intron ATTCTATGACTTTGCGCTTCAGGA 3 D6S1017 AL035588 CCACCCGTCCATTTAGGC Hill et al ., 2008 GTGAAAAAGTAGATATAATGGTTGGTG 4 D8S1179 AF216671 ATTGCAACTTATATGTATTTTTGTATTTCATG Krenke et al ., 2002 ACCAAATTGTGTTCATGAGTATAGTTTC 5 D9S2157 AL162417 CAAAGCGAGACTCTGTCTCAA Hill et al ., 2008 GAAAATGCTATCCTCTTTGGTATAAAT 6 D10S1248 AL391869 TTAATGAATTGAACAAATGAGTGAG GCAACTCTGGTTGTATTGTCTTCAT Hill et al ., 2008 7 D18S51 AP001534 TTCTTGAGCCCAGAAGGTTA Krenke et al ., 2002 ATTCTACCAGCAACAACACAAATAAAC 8 D21S11 AP001752 ATATGTGAGTCAATTCCCCAAG TGTATTAGTCAATGTTCTCCAGAGAC Krenke et al ., 2002 9 D22S1045 AL033314 ATTTTCCCCGATGATAGTAGTCT GCGAATGTATGATTGGCAATATTTTT Hill et al ., 2008 10 Amelogenin M55418 ACCTCATCCTGGGCACCCTGG Sullivan et al., 1993 M55419 AGGCTTGAGGCCAACCATCAG The PCR parameters for all the miniplexes included an initial denaturation temperature of 95 °C for 15 min, a denaturation temperature of 95 °C for 30 s, an extension temperature of 72 °C for 1 min 40 s and a final extension temperature of 72 °C for 10 min. The annealing temperature and duration were different for each of the miniplexes. The annealing temperatures of M01, M02, M03 and M04 were 62 °C, 59 °C, 57.4 °C and 59.5 °C, respectively, after 60 s. The PCR cycles were 30 cycles for M01 and 35 cycles for the other miniplexes (Table 2). Table 2: PCR conditions for the four multiplexes Loci Initial Denaturation Denaturation Annealing Extension Final Extension Cycles Miniplex Loci Temp Time (min) Temp Time Temp Time (Min) Temp Time Temp Time (min) M01 Amelogenin; D10S1248 95 15 95 30 s 62 1 72 1.40 min 72 10 30 M02 D6S1017; D18S51 95 15 95 30 s 59 1 72 1.40 min 72 10 35 M03 D22S1045; D21S11; D2S1338 95 15 95 30 s 57.4 1 72 1.40 min 72 10 35 M04 D9S2157; FGA; D8S1179 95 15 95 30 s 59.5 1 72 1.40 min 72 10 35 Polyacrylamide Gel Electrophoresis (PAGE): The PCR products were mixed with a loading dye solution containing 10 mM NaOH, 95% formamide, 0.05% bromophenol blue and 0.05% xylene cyanol. The mixture was then heated (to denature) at 95 °C for 2-3 minutes and then subjected to 4-8% (depending on the size of the band) PAGE (37 mm long, 0.4 mm thick) containing 7 M urea and 0.5X Tris Borate EDTA buffer. Using a sequencing gel apparatus, the samples were then allowed to resolve at a constant temperature between 40-50 W for at least 75 minutes (and a maximum of 5-6 hours). The PAGE was then followed by silver staining using the method of Refaat et al. (2008). The gels were then viewed with a UV transilluminator, and images were captured with a camera for gel documentation. Gel Scoring The gels were scored using GelAnalyzer (v. 23.1). Briefly, each gel image was opened on the software. The lanes were selected and added using the ‘select lanes’ mode. The ‘Detect bands on every lane’ command was used for the initial identification of bands on all lanes. The selections were then modified manually if necessary. The marker sizes for the ladder were then added for bands on the ladder lane using the molecular weight calibration mode. The software then generates a molecular weight value (in base pairs) as well as intensity, raw volume, calibrated volume and rf values for all selected bands on the gel. Data Collection and Computation of Statistics The allele types and sizes were read and recorded for each locus for every individual. Allelic frequencies were calculated using GenAlEx v6.502. Gene diversity, P values for exact tests for linkage disequilibrium, population pairwise genetic distances ( F ST and R ST ) and analysis of molecular variance (AMOVA) among the studied populations were determined using Powerstat software. To summarize the relationships among the five Nigerian populations, a principal component analysis (PCA) of the STRs was carried out. The unweighted pair group method with arithmetic mean tree was built from the distance matrix ( F ST ) using the option ‘neighbour and draw tree’ in the Phylip software package and visualized with Tree View software. RESULTS Population Structure Fixation index (F ST ) and measures of population structure The fixation index and other population genetic parameters were calculated for all the loci in all the populations and for the Nigerian summarized population (Table 3). The allele number (An), average number of different alleles (N a ), number of effective alleles (N e ), observed heterozygosity (H o ), expected heterozygosity (H e ), and fixation indices ( F , F IS and F ST ) are all presented. In the whole Nigerian population, the D21S11, FGA, and D10S1248 loci had F ST values of 0.001; D8S1179, D2S1338 and D18S51 had values of 0.003; and D22S1045 had a value of 0.002. When examined in each subpopulation, the F ST values for many of the loci were negative. In Ibibio, only the D22S1045 and D6S1017 loci had positive F ST values of 0.023 and 0.013, respectively. D2S1338 had the lowest F ST (-0.003) in that population. D22S1045 also had a positive value (0.010) in the Igbo population and was the only locus with a positive F ST in that population. The tendency of D2S1338 to have the lowest F ST continued in the Igbo population. The Yoruba population had four loci with positive F ST values: 0.005 (D8S1179), 0.035 (D22S1045), 0.50 (D18S51) and 0.053 (D6S1017). The FGA value of -0.001 was the lowest for the Yoruba population. In the Hausa population, D8S1179 had a positive value of 0.008, and D6S1017 had a value of 0.010. A D18S51 value of 0.014 was the only positive value of F ST in the Tiv population. When examined for each population, the F statistics for all the populations had negative values ranging from -0.01 to 0.04 (Table 4). The inbreeding coefficient in the Nigerian population F IS was very low for all loci (-0.11-0.01). A tendency of the F -statistics to be low or negative was also observed for the F IT. The observed number of alleles among the sampled populations ranged between 10.33 and 10.67. The observed heterozygosity was greater than expected for all the populations examined. However, the highest observed heterozygosity was found in the Igbo (H o = 0.88±0.01) population, while the lowest was observed in the Yoruba (0.85±0.02) population (Table 4). Table 3: Summary of measures of population structure in the Nigerian population Locus H o H e F IT F IS F ST D21S11 0.86±0.00 0.83±0.00 -0.04±0.01 -0.04±0.01 0.001±0.01 D22S1045 0.83±0.01 0.84±0.00 0.01±0.01 0.01±0.01 0.002±0.00 D2S1338 0.88±0.01 0.87±0.01 -0.01±0.00 -0.01±0.01 0.003±0.01 D8S1179 0.83±0.02 0.79±0.01 -0.05±0.03 -0.05±0.00 0.003±0.01 FGA 0.88±0.00 0.87±0.00 -0.01±0.01 -0.01±0.00 0.001±0.02 D9S2157 0.90±0.00 0.85±0.00 -0.06±0.00 -0.06±0.00 0.001±0.00 D18S51 0.87±0.01 0.87±0.00 0.00±0.01 0.00±0.01 0.003±0.01 D6S1017 0.80±0.01 0.81±0.00 0.01±0.01 0.01±0.00 0.000±0.00 D10S1248 0.90±0.01 0.81±0.00 -0.11±0.01 -0.11±0.00 0.001±0.00 Mean ±SE 0.86±0.01 0.84±0.01 -0.03±0.01 0.03±0.01 0.002±0.00 SE: standard error, H o : observed heterozygosity, H e : expected heterozygosity, F ST : fixation index, F IS : inbreeding coefficient, Table 4: Comparative measures of population structure in the 5 populations Pop N a N e H o H e F Ibibio 10.56±0.69 6.35±0.42 0.87±0.01 0.84±0.01 -0.04±0.02 Igbo 10.67±0.67 6.52±0.42 0.88±0.01 0.84±0.01 -0.04±0.02 Yoruba 10.67±0.87 6.64±0.49 0.85±0.02 0.84±0.01 -0.01±0.02 Hausa 10.33±0.76 6.19±0.38 0.86±0.01 0.83±0.01 -0.03±0.02 Tiv 10.67±0.60 6.24±0.38 0.86±0.01 0.83±0.01 -0.04±0.01 N a : Observed number of alleles, N e : Number of effective alleles, H o : Observed heterozygosity, H e : Expected heterozygosity F: Fixation Pairwise Population Matrix The results of the pairwise population matrix of genetic similarity between populations are presented in Table 5 . The pairwise population matrix value between Yoruba and Igbo was 0.993, which was the highest of the pairwise genetic similarity indices between the five populations. Yoruba-Ibibio was 0.990, Yoruba-Hausa was 0.992, and Yoruba-Tiv was 0.987. The Igbo-Ibibio similarity at these loci was the lowest at 0.895. When a dendrogram was constructed for the five populations based on data from these 9 loci, Ibibio and Tiv clustered together. Igbo and Yoruba formed a more recent cluster and were joined by Hausa (Figure 3). Table 5: Pairwise population matrix of genetic similarity between populations Population Ibibio Igbo Yoruba Hausa Tiv Ibibio 1.000 Igbo 0.985 1.000 Yoruba 0.990 0.993 1.000 Hausa 0.988 0.991 0.992 1.000 Tiv 0.991 0.986 0.987 0.991 1.000 Analysis of Molecular Variance (AMOVA) The analysis of molecular variance at the 9 loci in the 5 populations revealed an estimated variation of 3.850 within individuals. The variation among populations was 0.0004. Among individuals, the variation was 0.00001 (Table 6). The estimated variation partitioned within individuals was 99.98%, with the remaining 0.10% attributed to variation among populations. Table 6: Summary of AMOVAs Source Df SS MS Est. Var. % Among Pops 4 3.5460 0.8865 0.0004 0.10% Among Indiv 245 927.3900 3.7853 0.0000 0% Within Indiv 250 962.5000 3.8500 3.8500 99.98% Total 499 1893.4360 3.8504 100% df: degree of freedom, SS: sum of squares, MS: mean sum of squares, Est. Var.: Estimated variation Principal component analysis Principal component analysis (PCA) revealed four clusters (Figure 4). The clusters are labelled A-D. The coloured small shapes represent individuals, with each colour representing an ethnic group. The numbers, in addition to the shapes, represent the sample identities of the individuals. The clusters are heterogeneous, with each cluster containing samples from all five (5) ethnic groups. The total variation explained by the PCA was 25.52%. DISCUSSION The ethnic populations of Nigeria have occupied their present-day homes for several centuries, and as such, expected relationships between individuals from these ethnic groups are bound to exist. The dynamics of population substructure and the underlying genetics are the subject of several recent studies. In the last century, there has apparently been gene flow between ethnic populations, as evidenced by interethnic mating between individuals from these groups, although the extent and nature of genetic activity are unknown. This study established that there is an excess of heterozygotes in all the examined loci for all the populations, as indicated by high values of observed heterozygotes compared to the expected heterozygotes. High observed heterozygosity is a frequent observation when human population samples are obtained at the ethnic home of each population where genetic diversity is usually very high. Natural populations also usually violate the Hardy‒Weinberg equilibrium (HWE) to some degree, which is the cause of allele frequency changes over time. Some of the loci in this study were not in HWE because the observed genotypes deviated from the expected genotypes. The main suspect for the deviation of some of the loci in any population is the population substructure. This excess heterozygosis points to the absence of consanguineous mating in these populations and that mate selection is mostly random. In fact, the inbreeding coefficient ( F IS ) observed in this study in the five Nigerian subpopulations was very low for all loci. The US National Research Council report recommends that a conservative F IS estimate of 0.01 is expected in populations examined for forensic data and suggests that a value of 0.03 indicates that cousin mating occurs in such populations (Balding, 2013). Heterozygosity also shows that there is stabilizing or balanced selection where natural selection favours the heterozygote over homozygotes, leading to lower-than-average F ST values for the selected loci. Five of the loci (D21S11, FGA, D9S2157, D6S1017, and D10S1248) had FSTs, indicating that there was stratification in the subpopulations. The extent of the variation in F ST from one locus to another helps to establish the source of the variation being observed. In populations where natural selection is selectively neutral, the only expected force at play is drift, and the observed F ST will be almost equal for all loci since drift depends only on demographic properties of the populations and not on any of the specific loci being studied (Khan et al., 2021). This is because the populations are assumed to have evolved independently from each other, and each will produce constraints that affect the F ST distribution. F ST will still vary from locus to locus in each of the subpopulations, but the extent of variation will be similar in each population. These stratifications seem to disappear when the Nigerian population is examined as a whole. The analysis of molecular variance in this study revealed an estimated 99.98% variation within individuals. The variation among populations was 0.10%. Although Igbo shares a common geographic boundary with Ibibio, the pairwise population matrix of genetic similarity for these loci shows that Igbo has greater similarity to Yoruba (0.993) than to every other population than to Ibibio. In fact, the Igbo-Ibibio similarity at these loci was the lowest (0.895) for all of the tested population pairs. These populations are actually the only populations that share a common geographic boundary, implying that this heightened dissimilarity for this population may be due to the alleles of these loci in individuals in this region diverging from each other. In fact, it has been previously established in other studies that the region of ethnic origin of any organism usually has the highest genetic diversity. The results of the pairwise population matrix of genetic similarity between populations also indicated that Ibibio and Tiv were more similar at these loci. The Hausa population had a similarity index that was similar for all populations: Yoruba (0.992), Igbo and Tiv each (0.991) and Ibibio (0.988). These populations all share a common lingual ancestor, as they have all been classified into the Niger-Congo group of languages (Eberhard et al ., 2024). However, Igbo and Yoruba share linguistic similarity and are further classified together as YEAIs (non-Bantoid), whereas Ibibio and Tiv together belong to the Benue-Congo (Bantoid) subgroup of languages. The Hausa language is often classified as a member of the Afro-Asiatic group of languages. A similar relationship was observed in this study when a dendrogram was constructed for the five populations based on data from these 9 loci. Ibibio and Tiv clustered together. Igbo and Yoruba formed a more recent cluster and were joined by the Hausa. Declarations Approval of the research design, with the consent forms and biosample collection methods, was obtained from the Ethics Review Board of the Lagos University Teaching Hospital with reference ADM/DCST/HREC/1921 Consent for publication All the authors provided consent for publication. Availability of data and material The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This research was partly funded by the University of Lagos Central Research Committee grant. no. 2016/1 to KOA and JO The research and thesis writing were also supported by the Association of African Universities (AUU) Small grant for Thesis writing with reference number PC/6 to AUU Authors' contributions UUA, KOA and JO designed the experiments. KOA and JO applied for and obtained funding from the University of Lagos. UUA, EO, KU and NG collected the samples and performed the sampling trips. UUA and OAA performed the experiments. UUA and ODA analysed the results. KOA and JO reviewed the laboratory results. UUA obtained funding from the Association of African Universities for thesis writing. UUA wrote the manuscript. All the authors have read and approved the final manuscript. Acknowledgements The authors acknowledge the assistance of the technical staff of the Faculty of Science University of Lagos, Nigeria. 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Biotechniques 37(2):226–231 Veeramah KR, Connell BA, Pour NA, Powell A, Plaster CA, Zeitlyn D, Mendell NR, Weale ME, Bradman N, Thomas MG (2010) Little genetic differentiation as assessed by uniparental markers in the presence of substantial language variation in peoples of the Cross River region of Nigeria. Biomed Cent (BMC) Evolutionary Biology 10:9 Weir BS, Cockerham CC (1984) Estimating F-Statistics for the Analysis of Population Structure. Evolution 38(6):1358–1370. https://doi.org/10.1111/j.1558-5646.1984.tb05657.x Wikimedia Commons (2024) Maps of ethnic groups in Nigeria. Accessed from https://commons.wikimedia.org/wiki/Category:Maps_of_ethnic_groups_in_Nigeria Yu N, Chen FC, Ota S, Jorde LB, Pamilo P, Patthy L, Ramsay M, Jenkins T, Shyue SK, Li WH (2002) Larger genetic differences within Africans than between Africans & Eurasians. Genetics 161(1):269–274. https://doi.org/10.1093/genetics/161.1.269 Zhu Y, Strassmann JE, Queller DC (2000) Insertion, Substitution & the origin of microsatellite. Genet Res 76:22–236 Zou F, Lee S, Knowles MR, Wright FA (2010) Quantification of population structure using correlated SNPs by shrinkage principal components. Human Hered 70:9–22. https://doi.org/10.1159/000288706 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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-4670501","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":321435275,"identity":"353c1618-da6b-4b95-87be-e7e4af5a1a0c","order_by":0,"name":"Utom-Obong U. 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The loci are combined into groups,and each group is identified here by boxes of the same colour.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4670501/v1/36f00a605b9636a7f34aa75b.jpeg"},{"id":59595019,"identity":"a9c2ab41-be17-4e6d-b627-e6e382dc00ac","added_by":"auto","created_at":"2024-07-03 15:39:58","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":49778,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic tree of the relationship between the 5 populations based on the Nei Pairwise population matrix of genetic similarity between populations in Table 5\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4670501/v1/d8a2409d2dd216b65bd90cef.jpeg"},{"id":59595021,"identity":"4e36e07e-029f-4787-8e8b-90a6b860a024","added_by":"auto","created_at":"2024-07-03 15:39:58","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":631753,"visible":true,"origin":"","legend":"\u003cp\u003ePrincipal component analysis for the variation in the five ethnic groups\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-4670501/v1/758e8833f1eeab1d0f8ef0c7.jpeg"},{"id":59595760,"identity":"651020f4-7210-4717-ba8e-6e2f21d6aaae","added_by":"auto","created_at":"2024-07-03 15:47:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1835636,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4670501/v1/422b491f-bf1c-45c9-a80e-d3cec51e2ddb.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePopulation Structure and Genetic Relationships among Nigerian Ethnic Groups (Ibibio, Igbo, Hausa, Tiv and Yoruba) Based on Nine Short Tandem Repeat Loci\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eResearch into the genetic diversity of African populations has intensified in the last few decades. During this time, African populations have been observed to have the highest genetic diversity among other human populations (Yu et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Tishkoff and Williams, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Campbell and Tishkoff, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Chodhury \u003cem\u003eet al.\u003c/em\u003e, 2018). Nigeria is located in Western Africa, bordering the Gulf of Guinea, between the Benin Republic, Niger Republic, Chad and Cameroon, with a landmass of 923,768 sq. km and a population of approximately 220\u0026nbsp;million people (Eberhard et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Estimates of the number of distinct ethnic groupings vary from 250 to as many as 580, with the most prominent being Hausa, Edo, Fulani, Ibibio, Kanuri, Nupe, Tiv, Ijaw, Itsekiri, Urhobo, Aguleri, Umuleri, Jukun, Ogoni, Mambila, Banso, Kamba, Yoruba, and Igbo (Ibo). There are 515 languages spoken for Nigeria, including English (official), Hausa, Yoruba, Igbo (Ibo), Fulani, Edo, Ibibio, Kanuri, Efik, Ijaw, and Nupe Tiv (Eberhard et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). One must be aware that these discrepancies in numbers result from the fact that these groups are delineated by linguistic differences.\u003c/p\u003e \u003cp\u003eFew studies have investigated the population genetic structure of the Nigerian human population(s). Veeramah et al. (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) examined genetic differentiation using uniparental markers against substantial language variation in peoples of the Cross River region of Nigeria, revealing the overall genetic homogeneity in the Cross River region in the face of such language variation. The results were obtained by examining mtDNA (mitochondrial DNA) and microsatellites from the nonrecombining region of the Y chromosome (NRY) in males from the region. Adeyemo et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) investigated the stratification of genetic structures in four West African population groups. Two Nigerian groups, Igbo and Yoruba, were studied together with two Ghanaian groups, examining 372 autosomal microsatellite loci in 497 unrelated individuals. Using RAPD markers, Titilayo et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) reported on the genetic variation among Igbo, Yoruba and Hausa samples. Recently, Joshi et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) provided insights into the genetic diversity of 47 Nigerian populations using whole-genome sequences of 449 individuals. These populations included the Hausa, Yoruba, Igbo and Ibibio populations. The diversity and structure of most of the 520 ethnolinguistic groups in Nigeria, including the Tiv, are still largely undefined.\u003c/p\u003e \u003cp\u003eThere is a need to study more groups to further elucidate the genetic diversity of Africans in general and Nigeria in particular (Veermah \u003cem\u003eet al.\u003c/em\u003e,2010; Tucci and Akey, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Genetic studies have shown the Igbo to cluster most closely with other Niger-Congo-speaking peoples (Campbell and Tishkoff, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). They also predominantly have the E1b1a1-M2 Y-chromosome haplogroup (Veeramah et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Yorubas have been the subject of many genetic studies since the collection of samples from Ibadan, called Yoruba in Ibadan (YRI), for some genomic studies. One such study showed that ~\u0026thinsp;31% of Yoruba people have prehistoric \"basal human\" admixture (Schlebusch et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Campbell and Tishkoff (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) reported that the Yoruba cluster most closely with other West African peoples. According to a Y-DNA study by Hassan et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), approximately 47% of Hausa in Niger, Cameroon, Nigeria and Sudan carry the West Eurasian haplogroup R1b. The remainder belong to various African paternal lineages: 15.6% B, 12.5% A and 12.5% E1b1a. A small minority (approximately 4%) were E1b1b clade bearers, a haplogroup that is most common in North Africa and the Horn of Africa. In terms of overall ancestry, Tishkoff \u003cem\u003eet al\u003c/em\u003e. (2009) found Hausa to be most closely related to Nilotic populations from Nigeria, Cameroon, central Chad and South Sudan. The Hausa population has also been reported to exhibit high genetic variability in a global analysis of dinucleotide repeats, presenting the highest heterozygosity of all the populations studied (Deka, et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). A study has shown that the Ibibio cluster contains the Yoruba, Ibibio, Bini, Igbo, and Izon ethnolinguistic groups (Joshi et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). There is still no reported genetic relationship for the Tiv ethnolinguistic group.\u003c/p\u003e \u003cp\u003eThe advent of genetic markers has made it possible to study population genetics at the molecular level, providing better diversity estimates. One such type is short tandem repeats (STRs). These are microsatellites with short sequences of DNA (1\u0026ndash;10 base pairs) lying within genetic markers and short tandem repeats (STRs) end to end in a particular region of the genome (the loci) (Chatumal et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Generally, they fall within noncoding regions and flanking sequences in the genome but occasionally within coding regions (Edwards et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Microsatellites are typically characterized by a high mutation rate and therefore a high level of polymorphism, resulting in different alleles in the population (Zhu et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Hardy et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). There are several thousand STR loci in the human genome. STRs on non-sex chromosomes are widely used as genetic markers in human identification, forensics, paternity investigations and other cases of kinship analysis. The loci are usually typed using polymerase chain reaction (PCR) and electrophoresis. When a sufficient number of loci are tested, a genetic profile is generated that statistically provides the discriminating power needed for human identification (Butler and Hill, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePopulation structure appears as extensive allelic diversity and heterozygosity at the genomic level. Contemporary approaches use molecular markers, including SNPs and STR data, to reveal genetic diversity in populations (Hannelius et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Several assumptions and relationships exist between the properties of molecular markers, and these could be used to estimate genetic diversity in populations. These methods include principal component analysis (PCA), the fixation index (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e), analysis of molecular variance (AMOVA), and Nei's genetic distance, with varying degrees of precision. Presently, these measures of population structure and population genetics are usually estimated using software programs. The list of programs can be obtained from different websites, including DuckDNA (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.duckdna.org/softwares/\u003c/span\u003e\u003cspan address=\"https://www.duckdna.org/softwares/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and the University of Washington (WU) popgen software page (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://courses.washington.edu/popgen/Software.htm\u003c/span\u003e\u003cspan address=\"https://courses.washington.edu/popgen/Software.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGenomic PCA is based on the eigenvectors of the covariance matrix derived from the genotypes of individuals in the population. These eigenvectors provide an efficient linear combination of marker data with the greatest discriminating ability between the samples without requiring prior sample classification information. The power of PCA to resolve highly structured populations depends on nonrandom patterns of genetic variation. Models of natural population structure indicate that most of the eigenvalues of covariance are small, nearly equal, and arise from sampling noise. Larger eigenvalues reflect past events on the population (Patterson et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Sampling noise can be reduced by filtering the data to remove one member of a marker pair that is in tight linkage disequilibrium (Pattterson \u003cem\u003eet al.\u003c/em\u003e, 2006; Canas-Alvarez \u003cem\u003eet al\u003c/em\u003e., 2015; Malomane et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) or by using approaches such as shrinkage PCA or iterative pruning PCA (Zou et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Intrapranich \u003cem\u003eet al\u003c/em\u003e., 2009; Limpiti \u003cem\u003eet al\u003c/em\u003e., 2011).\u003c/p\u003e \u003cp\u003eWright introduced the fixation index to measure genetic differences between subdivided populations (Nagylaki, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). He proposed three parameters that focused on the total population (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eIT\u003c/sub\u003e), subdivisions (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e), and individuals (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eIS\u003c/sub\u003e). The \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIT\u003c/sub\u003e is the ratio of gametes that produce individuals to gametes in the total population. It gives the ratio of the variance of gene frequencies of random breeding subdivisions (if these occur) to its maximum possible value, which is expected if the subdivisions are completely isolated and each is completely fixed, thus forming an array. The \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIT\u003c/sub\u003e is an assessment of the total (T) generations. \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIS\u003c/sub\u003e is the average over all subdivisions of the correlation between uniting gametes relative to those of their own subdivision. It is also referred to as the inbreeding coefficient. \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e is the correlation between random gametes within subdivisions relative to gametes of the total population. The three F-statistics are related by the formula \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e = (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eIT\u003c/sub\u003e \u0026ndash; \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIS\u003c/sub\u003e)/(1- \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIS\u003c/sub\u003e) (Wright, 1965). These parameters are also related to probabilities of identity by origin and the levels of heterozygosity in and between the populations. Fixation index (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e) estimation helps to determine how different a group of populations is from each other. Most importantly, however, the \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e is the ratio of the actual variance in the gene frequencies of subdivisions to its limiting value, irrespective of their own structures. \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e is thus necessarily positive. \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIS\u003c/sub\u003e, while usually positive, is negative if there is systematic avoidance of consanguine mating within the subdivisions. \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIT\u003c/sub\u003e is positive if there is systematic subdivision, whether into demes (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eIS\u003c/sub\u003e = 0, \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIT\u003c/sub\u003e= \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e) or into inbred groups, but can be negative if there is no systematic subdivision and there is prevailing avoidance of consanguine mating.\u003c/p\u003e \u003cp\u003eIn addition to Wright's assumptions and the establishment of these relationships, Weir \u0026amp; Cockerham (Weir \u0026amp; Cockerham, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1984\u003c/span\u003e), Nei (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1986\u003c/span\u003e) and Hudson \u003cem\u003eet al\u003c/em\u003e. (Hudson 1992) described and proposed other approaches for deriving these F-statistics. However, weir and Cockerham's method is sensitive to sample size, and Nei's method consistently overestimates the \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST,\u003c/sub\u003e whereas Hudson\u0026rsquo;s estimator is more precise (Samaragdov \u0026amp; Kudinov, 2020). It is not sensitive to the sample size ratio, it does not systematically overestimate the \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e, and it is accurate and stable under various ascertainment schemes. \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e values can range from 0 to 1, where 0 indicates complete sharing of genetic material (two populations interbred freely) or a panmictic population, 1 indicates that all genetic variation is explained by population structure and that the two populations do not share any genetic identity and are fixed (Barbosa et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Khan et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). An estimated fixation index less than 0.05 indicates that little genetic difference between 0.05\u0026ndash;0.15 indicates moderate genetic difference, 0.15\u0026ndash;0.25 indicates great genetic difference, and 0.25 indicates very great genetic difference (Hartl \u0026amp; Clark,1997). If considered in two broad categories, an \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e greater than 0.15 represents significant differentiation, and an \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e less than 0.05 reflects insignificant differentiation (Frankham et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e values can be skewed by the frequency of the most frequent allele.\u003c/p\u003e \u003cp\u003eThe analysis of molecular variance (AMOVA) is an alternative methodology that makes use of the available molecular information gathered in population surveys to accommodate different assumptions about the evolution of the genetic system (Excoffier et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). It translates information from molecular markers into estimates of the magnitude of intraspecific subdivision, provides estimates of the variance in nucleotide diversity for different sampling processes and computes the fraction of nucleotide diversity due to interpopulation genetic differences while remaining irrespective of evolutionary history. Excoffier et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e1992\u003c/span\u003e) constructed a hierarchical analysis of molecular variance directly from the matrix of squared distances between all pairs of haplotypes based on interpreting the conventional sum of squares (SS) as the sum of squared differences between all pairs of observations. Beyond its clear relation to an analysis of variance, the method has the additional advantage that several different assumptions can be imposed on the haplotype differentiation process, each of which translates into a different distance matrix, with no change in the structure of the subsequent analysis. When all distances between haplotypes are presumed to be equal, the analysis is equivalent to a multiallelic (multivariate) analysis of variance.\u003c/p\u003e \u003cp\u003eTaken together, these measures of population genetic parameters can reveal valuable information on population structure and history. Therefore, the aim of this study was to investigate the genetic relationships between the five Nigerian populations of Igbo, Ibibio, Yoruba, Tiv and Hausa using nine short tandem repeat markers.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproval for the research, consent forms and biosample collection methods was obtained from the Ethics Review Board of the Lagos University Teaching Hospital with reference\u0026nbsp;ADM/DCST/HREC/1921.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCollection of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSamples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size determination\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sampling method was an initial cluster sampling of five selected ethnic groups from Nigeria, followed by a random sampling of individuals from the chosen ethnic groups. The ethnic populations in the study were chosen to represent the three largest groups (Igbo, Yoruba and Hausa) and two smaller groups (one Northern and one Southern - Tiv and Ibibio, respectively) in Nigeria. The population sizes of these ethnic groups are as follows: Yoruba, 18,900,000; Hausa, 18,500,000; Igbo, 18,000,000; Ibibio, 4,700,000; and Tiv, 2,210,000 (Lewis \u003cem\u003eet al.,\u003c/em\u003e 2014). The estimated effective population size of each of the chosen ethnic groups was less than 50 individuals based on the method of Hale \u003cem\u003eet al.\u003c/em\u003e (2012). However, 50 individuals were sampled from each population, and data from 50 individuals were presented to allow for comparisons between the groups (Bashalkhanov \u003cem\u003eet al\u003c/em\u003e., 2009).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipant Recruitment and Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePotential participants who self-identified\u0026nbsp;as being from any of\u0026nbsp;the\u0026nbsp;Hausa, Yoruba, Igbo, Ibibio or Tiv ethnic/linguistic groups were recruited at the blood donor clinic of the participating hospitals. These hospitals are in regions with a high density of members of the ethnic groups\u0026nbsp;included\u0026nbsp;in the study. It includes the Lagos University Teaching Hospital (LUTH) and locations in\u0026nbsp;Ilesha, Osun State and Ogbomoso, Oyo\u0026nbsp;(for Yoruba), the University of Uyo Teaching Hospital (UUTH) (for Ibibio) and Aminu Kano Teaching Hospital (AKTH) (for\u0026nbsp;Hausa),\u0026nbsp;Anambra State University Teaching Hospital (ANSUTH), Amaku, and Awka communities in Anambra State (for Igbo) and Benue State University Teaching Hospital, Makurdi (for Tiv) (see Figure 1).\u003c/p\u003e\n\u003cp\u003eSociological data\u0026nbsp;were\u0026nbsp;also collected from each individual,\u0026nbsp;including date of birth (or age), current residence, birthplace, self-declared cultural identity, first language, second language (when available) and ethnic affiliation. The ethnic origins of both paternal and maternal grandparents were also obtained. No names or addresses were obtained or recorded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBiosample collection and storage\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo types of samples were collected from participants depending on their preference: peripheral blood. Whole blood (3-5 ml)\u0026nbsp;was drawn from participating individuals\u0026nbsp;by venipuncture. Blood\u0026nbsp;was collected\u0026nbsp;from each sample\u0026nbsp;into an\u0026nbsp;anticoagulant\u0026nbsp;storage bottle\u0026nbsp;labelled\u0026nbsp;with a unique anonymous identifier,\u0026nbsp;temporarily stored in mobile ice\u0026nbsp;coolers, transported to the Department of Cell Biology \u0026amp; Genetics, University of Lagos,\u0026nbsp;and stored\u0026nbsp;at\u0026nbsp;-80 \u0026deg;C.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMolecular Analysis of STRs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExtraction and quantification of DNA \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenomic DNA was extracted from white blood cells present in the blood samples using Omega Biotek E.Z.N.A. Forensic DNA Mini Kit. Briefly, whole blood was lysed using a cocktail of lysis buffer. The supernatant was centrifuged,\u0026nbsp;and proteins were removed using a protease (proteinase-K). The DNA was washed in spin columns and eluted using TE buffer. The recovered DNA was stored for use in quantification and PCR analysis. The quality of the DNA was assessed on\u0026nbsp;a\u0026nbsp;1% agarose gel run\u0026nbsp;at\u0026nbsp;70 mV for 45 minutes. The DNA was quantified using a\u0026nbsp;NanoDrop\u0026nbsp;spectrophotometer.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLocus\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe autosomal STR markers used in the study were selected from the lists of STRs with a high number of genotypes observed, high heterozygosity, high polymorphism information content value and good probability of identity values in African American, African and other black populations. A total of 10 STR loci (including the sex-typing marker amelogenin) were chosen. The loci are D21S11, FGA, D18S51, D2S1338, D10S1248, D22S1045, D9S2157, D6S1017, D8S1179, and Amelogenin. The sequences of primers used were obtained from the literature (Hill \u003cem\u003eet al\u003c/em\u003e.,2008, and STRBase,2015) (Table 1). Based on these sequences, PCR primer oligonucleotides were purchased from Inqaba Biotec, South Africa.\u0026nbsp;The\u0026nbsp;nine\u0026nbsp;(9) loci were tested as four miniplexes of two 2-primer pairs and two 3-primer\u0026nbsp;pairs\u0026nbsp;based on product size. Primer-primer comparison to avoid excessive regions of complementarity between primers was performed using the software AutoDimer (Vallone \u0026amp; Butler, 2004). A visual schematic of the multiplex loci was prepared to provide\u0026nbsp;a\u0026nbsp;visual representation of the loci and highlight areas of possible size overlap. The miniplexes were then named M01, M02, M03 and M04\u0026nbsp;(Figure 2).\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: List of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eprimers\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.851549755301795%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS/NO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29200652528548%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOCUS NAME\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.760195758564436%\"\u003e\n \u003cp\u003e\u003cstrong\u003eGENBANK ACCESSION\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.98858075040783%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePRIMER SEQUENCE (5\u0026prime; - 3\u0026prime;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.107667210440457%\"\u003e\n \u003cp\u003e\u003cstrong\u003eREFERENCES\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.851549755301795%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29200652528548%\"\u003e\n \u003cp\u003eD2S1338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.760195758564436%\"\u003e\n \u003cp\u003eAC010136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.98858075040783%\"\u003e\n \u003cp\u003eACTGCAGTCCAATCTGGGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.107667210440457%\" rowspan=\"2\"\u003e\n \u003cp\u003eKrenke \u003cem\u003eet al\u003c/em\u003e., 2002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.366533864541832%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.115537848605577%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.90836653386454%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.60956175298805%\"\u003e\n \u003cp\u003eATGAAATCAACAGAGGCTTGC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.851549755301795%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29200652528548%\"\u003e\n \u003cp\u003eFGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.760195758564436%\"\u003e\n \u003cp\u003eM64982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.98858075040783%\"\u003e\n \u003cp\u003eGGCTGCAGGGCATAACATTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.107667210440457%\" rowspan=\"2\"\u003e\n \u003cp\u003eKrenke \u003cem\u003eet al\u003c/em\u003e., 2002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.366533864541832%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.115537848605577%\"\u003e\n \u003cp\u003ealpha fibrinogen 3rd intron\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.90836653386454%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.60956175298805%\"\u003e\n \u003cp\u003eATTCTATGACTTTGCGCTTCAGGA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.851549755301795%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29200652528548%\"\u003e\n \u003cp\u003eD6S1017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.760195758564436%\"\u003e\n \u003cp\u003eAL035588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.98858075040783%\"\u003e\n \u003cp\u003eCCACCCGTCCATTTAGGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.107667210440457%\" rowspan=\"2\"\u003e\n \u003cp\u003eHill \u003cem\u003eet al\u003c/em\u003e., 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.366533864541832%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.115537848605577%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.90836653386454%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.60956175298805%\"\u003e\n \u003cp\u003eGTGAAAAAGTAGATATAATGGTTGGTG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.851549755301795%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29200652528548%\"\u003e\n \u003cp\u003eD8S1179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.760195758564436%\"\u003e\n \u003cp\u003eAF216671\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.98858075040783%\"\u003e\n \u003cp\u003eATTGCAACTTATATGTATTTTTGTATTTCATG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.107667210440457%\" rowspan=\"2\"\u003e\n \u003cp\u003eKrenke \u003cem\u003eet al\u003c/em\u003e., 2002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.366533864541832%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.115537848605577%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.90836653386454%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.60956175298805%\"\u003e\n \u003cp\u003eACCAAATTGTGTTCATGAGTATAGTTTC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.851549755301795%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29200652528548%\"\u003e\n \u003cp\u003eD9S2157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.760195758564436%\"\u003e\n \u003cp\u003eAL162417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.98858075040783%\"\u003e\n \u003cp\u003eCAAAGCGAGACTCTGTCTCAA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.107667210440457%\" rowspan=\"2\"\u003e\n \u003cp\u003eHill \u003cem\u003eet al\u003c/em\u003e., 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.366533864541832%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.115537848605577%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.90836653386454%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.60956175298805%\"\u003e\n \u003cp\u003eGAAAATGCTATCCTCTTTGGTATAAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.851549755301795%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29200652528548%\"\u003e\n \u003cp\u003eD10S1248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.760195758564436%\"\u003e\n \u003cp\u003eAL391869\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.98858075040783%\" rowspan=\"2\"\u003e\n \u003cp\u003eTTAATGAATTGAACAAATGAGTGAG GCAACTCTGGTTGTATTGTCTTCAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.107667210440457%\" rowspan=\"2\"\u003e\n \u003cp\u003eHill \u003cem\u003eet al\u003c/em\u003e., 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.96958174904943%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.3041825095057%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.72623574144487%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.851549755301795%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29200652528548%\"\u003e\n \u003cp\u003eD18S51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.760195758564436%\" rowspan=\"2\"\u003e\n \u003cp\u003eAP001534\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.98858075040783%\"\u003e\n \u003cp\u003eTTCTTGAGCCCAGAAGGTTA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.107667210440457%\" rowspan=\"2\"\u003e\n \u003cp\u003eKrenke \u003cem\u003eet al\u003c/em\u003e., 2002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.852713178294573%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.39018087855297%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"61.75710594315245%\"\u003e\n \u003cp\u003eATTCTACCAGCAACAACACAAATAAAC\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.851549755301795%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29200652528548%\"\u003e\n \u003cp\u003eD21S11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.760195758564436%\"\u003e\n \u003cp\u003eAP001752\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.98858075040783%\" rowspan=\"2\"\u003e\n \u003cp\u003eATATGTGAGTCAATTCCCCAAG TGTATTAGTCAATGTTCTCCAGAGAC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.107667210440457%\" rowspan=\"2\"\u003e\n \u003cp\u003eKrenke \u003cem\u003eet al\u003c/em\u003e., 2002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.96958174904943%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.3041825095057%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.72623574144487%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.851549755301795%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29200652528548%\"\u003e\n \u003cp\u003eD22S1045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.760195758564436%\"\u003e\n \u003cp\u003eAL033314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.98858075040783%\" rowspan=\"2\"\u003e\n \u003cp\u003eATTTTCCCCGATGATAGTAGTCT GCGAATGTATGATTGGCAATATTTTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.107667210440457%\" rowspan=\"2\"\u003e\n \u003cp\u003eHill \u003cem\u003eet al\u003c/em\u003e., 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"15.96958174904943%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.3041825095057%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"43.72623574144487%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"6.851549755301795%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29200652528548%\"\u003e\n \u003cp\u003eAmelogenin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.760195758564436%\"\u003e\n \u003cp\u003eM55418\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"38.98858075040783%\"\u003e\n \u003cp\u003eACCTCATCCTGGGCACCCTGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.107667210440457%\" rowspan=\"2\"\u003e\n \u003cp\u003eSullivan \u003cem\u003eet al.,\u003c/em\u003e 1993\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.366533864541832%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.115537848605577%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.90836653386454%\"\u003e\n \u003cp\u003eM55419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.60956175298805%\"\u003e\n \u003cp\u003eAGGCTTGAGGCCAACCATCAG\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe PCR parameters for all the miniplexes\u0026nbsp;included an\u0026nbsp;initial denaturation\u0026nbsp;temperature\u0026nbsp;of 95\u0026nbsp;\u0026deg;C\u0026nbsp;for\u0026nbsp;15 min,\u0026nbsp;a\u0026nbsp;denaturation\u0026nbsp;temperature\u0026nbsp;of 95\u0026nbsp;\u0026deg;C\u0026nbsp;for\u0026nbsp;30 s, an\u0026nbsp;extension\u0026nbsp;temperature\u0026nbsp;of 72\u0026nbsp;\u0026deg;C\u0026nbsp;for\u0026nbsp;1 min 40 s\u0026nbsp;and\u0026nbsp;a\u0026nbsp;final extension\u0026nbsp;temperature\u0026nbsp;of 72\u0026nbsp;\u0026deg;C\u0026nbsp;for\u0026nbsp;10 min. The annealing\u0026nbsp;temperature\u0026nbsp;and duration were different for each of the miniplexes. The annealing\u0026nbsp;temperatures\u0026nbsp;of M01, M02, M03 and M04 were 62 \u0026deg;C, 59 \u0026deg;C, 57.4 \u0026deg;C and 59.5 \u0026deg;C, respectively, after 60 s. The PCR cycles were 30 cycles for M01 and 35 cycles for the other miniplexes (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003ePCR conditions for the four multiplexes\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"595\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.067226890756302%\" colspan=\"2\"\u003e\n \u003cp\u003eLoci\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.605042016806722%\" colspan=\"2\"\u003e\n \u003cp\u003eInitial Denaturation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.260504201680673%\" colspan=\"2\"\u003e\n \u003cp\u003eDenaturation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.605042016806722%\" colspan=\"2\"\u003e\n \u003cp\u003eAnnealing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.605042016806722%\" colspan=\"2\"\u003e\n \u003cp\u003eExtension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.277310924369749%\" colspan=\"2\"\u003e\n \u003cp\u003eFinal Extension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.579831932773109%\"\u003e\n \u003cp\u003eCycles\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.942760942760943%\"\u003e\n \u003cp\u003eMiniplex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.171717171717173%\"\u003e\n \u003cp\u003eLoci\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"top\"\u003e\n \u003cp\u003eTemp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\" valign=\"top\"\u003e\n \u003cp\u003eTime (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"top\"\u003e\n \u003cp\u003eTemp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"top\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\" valign=\"top\"\u003e\n \u003cp\u003eTemp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.723905723905724%\" valign=\"top\"\u003e\n \u003cp\u003eTime (Min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"top\"\u003e\n \u003cp\u003eTemp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\" valign=\"top\"\u003e\n \u003cp\u003eTime\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\" valign=\"top\"\u003e\n \u003cp\u003eTemp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.575757575757576%\" valign=\"top\"\u003e\n \u003cp\u003eTime (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.595959595959595%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.942760942760943%\"\u003e\n \u003cp\u003eM01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.171717171717173%\"\u003e\n \u003cp\u003eAmelogenin; D10S1248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e30 s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.723905723905724%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e1.40 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.575757575757576%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.595959595959595%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.942760942760943%\"\u003e\n \u003cp\u003eM02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.171717171717173%\"\u003e\n \u003cp\u003eD6S1017; D18S51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e30 s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.723905723905724%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e1.40 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.575757575757576%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.595959595959595%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.942760942760943%\"\u003e\n \u003cp\u003eM03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.171717171717173%\"\u003e\n \u003cp\u003eD22S1045; D21S11; D2S1338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e30 s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e57.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.723905723905724%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e1.40 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.575757575757576%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.595959595959595%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"10.942760942760943%\"\u003e\n \u003cp\u003eM04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.171717171717173%\"\u003e\n \u003cp\u003eD9S2157; FGA; D8S1179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e30 s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e59.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.723905723905724%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.070707070707071%\"\u003e\n \u003cp\u003e1.40 min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.555555555555555%\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.575757575757576%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.595959595959595%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePolyacrylamide Gel Electrophoresis (PAGE):\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe PCR products were mixed with a loading dye solution containing 10 mM NaOH, 95% formamide, 0.05%\u0026nbsp;bromophenol blue and 0.05% xylene cyanol. The mixture was then heated (to denature) at 95\u0026nbsp;\u0026deg;C\u0026nbsp;for 2-3 minutes and then\u0026nbsp;subjected to\u0026nbsp;4-8% (depending on the\u0026nbsp;size\u0026nbsp;of the band) PAGE (37 mm long, 0.4\u0026nbsp;mm\u0026nbsp;thick) containing 7\u0026nbsp;M\u0026nbsp;urea and 0.5X Tris Borate EDTA buffer. Using a sequencing gel apparatus,\u0026nbsp;the\u0026nbsp;samples were then allowed to resolve at a constant temperature between 40-50\u0026nbsp;W\u0026nbsp;for at least 75 minutes (and a maximum of 5-6 hours). The PAGE was then followed by silver staining using the method of Refaat\u003cem\u003e\u0026nbsp;et al.\u0026nbsp;\u003c/em\u003e(2008). The gels were then viewed with a UV transilluminator,\u0026nbsp;and images were captured with a camera for gel documentation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGel Scoring\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe gels were scored using GelAnalyzer\u0026nbsp;(v. 23.1). Briefly, each gel image was opened on the software. The lanes were selected and added using the \u0026lsquo;select\u0026nbsp;lanes\u0026rsquo; mode. The \u0026lsquo;Detect bands on every lane\u0026rsquo; command was used for the initial identification of bands on all lanes. The selections were then modified manually if necessary. The marker sizes for the ladder were then added for bands on the ladder lane using the molecular weight calibration mode. The software then generates a molecular weight value (in base pairs) as well as intensity, raw volume, calibrated volume and rf values for all selected bands on the gel.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection and Computation of Statistics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe allele types and sizes were read and recorded for each locus for every individual. Allelic frequencies were calculated using GenAlEx v6.502. Gene diversity, P values for exact tests for linkage disequilibrium, population pairwise genetic distances (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e and \u003cem\u003eR\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e) and analysis of molecular variance (AMOVA) among the studied populations were determined using Powerstat software. To summarize the relationships among the five Nigerian populations, a principal component analysis (PCA) of the STRs was carried out. The unweighted pair group method with arithmetic mean tree was built from the distance matrix (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e) using the option \u0026lsquo;neighbour and draw tree\u0026rsquo; in the Phylip software package and visualized with Tree View software.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003ePopulation Structure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFixation index (F\u003csub\u003eST\u003c/sub\u003e\u003c/strong\u003e\u003cstrong\u003e) and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003emeasures of population structure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe fixation index and other population genetic parameters were calculated for all the loci in all the populations and for the Nigerian summarized population (Table 3). The allele number (An), average number of different alleles (N\u003csub\u003ea\u003c/sub\u003e), number of effective alleles (N\u003csub\u003ee\u003c/sub\u003e), observed heterozygosity (H\u003csub\u003eo\u003c/sub\u003e), expected heterozygosity (H\u003csub\u003ee\u003c/sub\u003e), and fixation indices (\u003cem\u003eF\u003c/em\u003e, \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIS\u003c/sub\u003e and \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e) are all presented.\u003c/p\u003e\n\u003cp\u003eIn the whole Nigerian population, the D21S11, FGA, and D10S1248 loci had \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e values of 0.001; D8S1179, D2S1338 and D18S51 had values of 0.003; and D22S1045 had a value of 0.002. When examined in each subpopulation, the \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e values for many of the loci were negative. In Ibibio, only the D22S1045 and D6S1017 loci had positive \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e values of 0.023 and 0.013, respectively. D2S1338 had the lowest \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e (-0.003) in that population. D22S1045 also had a positive value (0.010) in the Igbo population and was the only locus with a positive \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e in that population. The tendency of D2S1338 to have the lowest \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e continued in the Igbo population. The Yoruba population had four loci with positive \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e values: 0.005 (D8S1179), 0.035 (D22S1045), 0.50 (D18S51) and 0.053 (D6S1017). The FGA value of -0.001 was the lowest for the Yoruba population. In the Hausa population, D8S1179 had a positive value of 0.008, and D6S1017 had a value of 0.010. A D18S51 value of 0.014 was the only positive value of \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e in the Tiv population. When examined for each population, the \u003cem\u003eF\u003c/em\u003e statistics for all the populations had negative values ranging from -0.01 to 0.04 (Table 4). The inbreeding coefficient in the Nigerian population \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIS\u0026nbsp;\u003c/sub\u003ewas very low for all loci (-0.11-0.01). A tendency of the \u003cem\u003eF\u003c/em\u003e-statistics to be low or negative was also observed for the \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIT.\u003c/sub\u003e\u003c/p\u003e\n\u003cp\u003eThe observed number of alleles among\u0026nbsp;the\u0026nbsp;sampled populations ranged between 10.33 and 10.67.\u0026nbsp;The observed\u0026nbsp;heterozygosity was\u0026nbsp;greater\u0026nbsp;than expected for all\u0026nbsp;the\u0026nbsp;populations\u0026nbsp;examined. However, the highest observed heterozygosity was found in the Igbo (H\u003csub\u003eo\u003c/sub\u003e = 0.88\u0026plusmn;0.01) population, while the lowest was observed in the Yoruba (0.85\u0026plusmn;0.02) population (Table 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Summary of measures of population structure in the Nigerian population\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"562\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.577540106951872%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\"\u003e\n \u003cp\u003e\u003cstrong\u003eH\u003csub\u003eo\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\"\u003e\n \u003cp\u003e\u003cstrong\u003eH\u003csub\u003ee\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eF\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csub\u003eIT\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.112299465240643%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eF\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csub\u003eIS\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29055258467023%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eF\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csub\u003eST\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.577540106951872%\" valign=\"top\"\u003e\n \u003cp\u003eD21S11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e-0.04\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.112299465240643%\"\u003e\n \u003cp\u003e-0.04\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29055258467023%\"\u003e\n \u003cp\u003e0.001\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.577540106951872%\" valign=\"top\"\u003e\n \u003cp\u003eD22S1045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e0.01\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.112299465240643%\"\u003e\n \u003cp\u003e0.01\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29055258467023%\"\u003e\n \u003cp\u003e0.002\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.577540106951872%\" valign=\"top\"\u003e\n \u003cp\u003eD2S1338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e-0.01\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.112299465240643%\"\u003e\n \u003cp\u003e-0.01\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29055258467023%\"\u003e\n \u003cp\u003e0.003\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.577540106951872%\" valign=\"top\"\u003e\n \u003cp\u003eD8S1179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.79\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e-0.05\u0026plusmn;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.112299465240643%\"\u003e\n \u003cp\u003e-0.05\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29055258467023%\"\u003e\n \u003cp\u003e0.003\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.577540106951872%\" valign=\"top\"\u003e\n \u003cp\u003eFGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e-0.01\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.112299465240643%\"\u003e\n \u003cp\u003e-0.01\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29055258467023%\"\u003e\n \u003cp\u003e0.001\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.577540106951872%\" valign=\"top\"\u003e\n \u003cp\u003eD9S2157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.90\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e-0.06\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.112299465240643%\"\u003e\n \u003cp\u003e-0.06\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29055258467023%\"\u003e\n \u003cp\u003e0.001\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.577540106951872%\" valign=\"top\"\u003e\n \u003cp\u003eD18S51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e0.00\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.112299465240643%\"\u003e\n \u003cp\u003e0.00\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29055258467023%\"\u003e\n \u003cp\u003e0.003\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.577540106951872%\" valign=\"top\"\u003e\n \u003cp\u003eD6S1017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.80\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e0.01\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.112299465240643%\"\u003e\n \u003cp\u003e0.01\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29055258467023%\"\u003e\n \u003cp\u003e0.000\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.577540106951872%\" valign=\"top\"\u003e\n \u003cp\u003eD10S1248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.90\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e-0.11\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.112299465240643%\"\u003e\n \u003cp\u003e-0.11\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29055258467023%\"\u003e\n \u003cp\u003e0.001\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.577540106951872%\" valign=\"top\"\u003e\n \u003cp\u003eMean \u0026plusmn;SE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.686274509803921%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.647058823529413%\"\u003e\n \u003cp\u003e-0.03\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.112299465240643%\"\u003e\n \u003cp\u003e0.03\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.29055258467023%\"\u003e\n \u003cp\u003e0.002\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSE:\u0026nbsp;standard\u0026nbsp;error, H\u003csub\u003eo\u003c/sub\u003e:\u0026nbsp;observed\u0026nbsp;heterozygosity, H\u003csub\u003ee\u003c/sub\u003e: expected heterozygosity, \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e: fixation index, \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIS\u003c/sub\u003e: inbreeding coefficient,\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u0026nbsp;\u003c/strong\u003eComparative measures of population structure in the 5\u0026nbsp;populations\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"593\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.996627318718382%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePop\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.875210792580102%\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003csub\u003ea\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003csub\u003ee\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e\u003cstrong\u003eH\u003csub\u003eo\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e\u003cstrong\u003eH\u003csub\u003ee\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.561551433389546%\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.996627318718382%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIbibio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.875210792580102%\"\u003e\n \u003cp\u003e10.56\u0026plusmn;0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e6.35\u0026plusmn;0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e0.87\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e0.84\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.561551433389546%\"\u003e\n \u003cp\u003e-0.04\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.996627318718382%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIgbo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.875210792580102%\"\u003e\n \u003cp\u003e10.67\u0026plusmn;0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e6.52\u0026plusmn;0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e0.88\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e0.84\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.561551433389546%\"\u003e\n \u003cp\u003e-0.04\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.996627318718382%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYoruba\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.875210792580102%\"\u003e\n \u003cp\u003e10.67\u0026plusmn;0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e6.64\u0026plusmn;0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e0.85\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e0.84\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.561551433389546%\"\u003e\n \u003cp\u003e-0.01\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.996627318718382%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHausa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.875210792580102%\"\u003e\n \u003cp\u003e10.33\u0026plusmn;0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e6.19\u0026plusmn;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e0.86\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e0.83\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.561551433389546%\"\u003e\n \u003cp\u003e-0.03\u0026plusmn;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.996627318718382%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTiv\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.875210792580102%\"\u003e\n \u003cp\u003e10.67\u0026plusmn;0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e6.24\u0026plusmn;0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e0.86\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.188870151770658%\"\u003e\n \u003cp\u003e0.83\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.561551433389546%\"\u003e\n \u003cp\u003e-0.04\u0026plusmn;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003eN\u003csub\u003ea\u003c/sub\u003e: Observed number of alleles, N\u003csub\u003ee\u003c/sub\u003e: Number of effective alleles, H\u003csub\u003eo\u003c/sub\u003e: Observed heterozygosity, H\u003csub\u003ee\u003c/sub\u003e: Expected heterozygosity\u003c/p\u003e\n\u003cp\u003eF: Fixation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePairwise Population Matrix\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the pairwise population matrix of genetic similarity between populations\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eare presented in Table 5\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eThe pairwise population matrix value between Yoruba and Igbo was 0.993, which was the highest of the pairwise genetic similarity indices between the five populations. Yoruba-Ibibio was 0.990, Yoruba-Hausa was 0.992, and Yoruba-Tiv was 0.987. The Igbo-Ibibio similarity at these loci was the lowest at 0.895. When a dendrogram was constructed for the five populations based on data from these 9 loci, Ibibio and Tiv clustered together. Igbo and Yoruba formed a more recent cluster and were joined by Hausa (Figure 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5: Pairwise population matrix of genetic similarity between populations\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"386\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.020725388601036%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePopulation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.689119170984455%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIbibio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIgbo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.357512953367877%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYoruba\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.025906735751295%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHausa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTiv\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.020725388601036%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIbibio\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.689119170984455%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"17.357512953367877%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.025906735751295%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.020725388601036%\"\u003e\n \u003cp\u003e\u003cstrong\u003eIgbo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.689119170984455%\" valign=\"top\"\u003e\n \u003cp\u003e0.985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.357512953367877%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"15.025906735751295%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.020725388601036%\"\u003e\n \u003cp\u003e\u003cstrong\u003eYoruba\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.689119170984455%\" valign=\"top\"\u003e\n \u003cp\u003e0.990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\n \u003cp\u003e0.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.357512953367877%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.025906735751295%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.020725388601036%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHausa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.689119170984455%\" valign=\"top\"\u003e\n \u003cp\u003e0.988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\n \u003cp\u003e0.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.357512953367877%\" valign=\"top\"\u003e\n \u003cp\u003e0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.025906735751295%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.020725388601036%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTiv\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.689119170984455%\" valign=\"top\"\u003e\n \u003cp\u003e0.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\n \u003cp\u003e0.986\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.357512953367877%\" valign=\"top\"\u003e\n \u003cp\u003e0.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.025906735751295%\" valign=\"top\"\u003e\n \u003cp\u003e0.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.953367875647668%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of Molecular Variance (AMOVA)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of molecular variance at the 9 loci in the 5 populations revealed an estimated variation of 3.850 within individuals. The variation among populations was 0.0004. Among individuals, the variation was 0.00001 (Table 6). The estimated variation partitioned within individuals was 99.98%, with the remaining 0.10% attributed to variation among populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6:\u0026nbsp;\u003c/strong\u003eSummary of\u0026nbsp;AMOVAs\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"607\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.382838283828384%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSource\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e\u003cstrong\u003eDf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.17161716171617%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEst. Var.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.382838283828384%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmong Pops\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.17161716171617%\"\u003e\n \u003cp\u003e3.5460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e0.8865\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e0.0004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e0.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.382838283828384%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eAmong Indiv\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.17161716171617%\"\u003e\n \u003cp\u003e927.3900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e3.7853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e0.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.382838283828384%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eWithin Indiv\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.17161716171617%\"\u003e\n \u003cp\u003e962.5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e3.8500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e3.8500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e99.98%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"28.382838283828384%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.17161716171617%\"\u003e\n \u003cp\u003e1893.4360\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e3.8504\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.861386138613861%\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003edf: degree of freedom, SS: sum of squares, MS: mean sum of squares, Est. Var.: Estimated variation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrincipal component analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrincipal component analysis (PCA) revealed four clusters (Figure 4). The clusters are labelled A-D. The coloured small shapes represent individuals, with each colour representing an ethnic group. The numbers, in addition to the shapes, represent the sample identities of the individuals. The clusters are heterogeneous, with each cluster containing samples from all five (5) ethnic groups. The total variation explained by the PCA was 25.52%.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe ethnic populations of Nigeria have occupied their present-day homes for several centuries,\u0026nbsp;and as such,\u0026nbsp;expected relationships between individuals from these ethnic groups are bound to exist. The\u0026nbsp;dynamics\u0026nbsp;of population substructure and the underlying genetics\u0026nbsp;are\u0026nbsp;the subject of several recent studies. In the last century, there\u0026nbsp;has\u0026nbsp;apparently\u0026nbsp;been\u0026nbsp;gene flow between ethnic populations,\u0026nbsp;as evidenced by\u0026nbsp;interethnic\u0026nbsp;mating between individuals from these groups,\u0026nbsp;although\u0026nbsp;the extent and nature of genetic activity\u0026nbsp;are\u0026nbsp;unknown.\u003c/p\u003e\n\u003cp\u003eThis study established that there is an excess of heterozygotes in all the examined loci for all the populations, as indicated by high values of observed heterozygotes compared to the expected heterozygotes. High observed heterozygosity is a frequent observation when human population samples are obtained at the ethnic home of each population where genetic diversity is usually very high. Natural populations also usually violate\u0026nbsp;the\u0026nbsp;Hardy‒Weinberg\u0026nbsp;equilibrium\u0026nbsp;(HWE) to some degree,\u0026nbsp;which is the cause of allele\u0026nbsp;frequency\u0026nbsp;changes over time. Some of the loci in this study were not in HWE because the observed genotypes deviated from the expected\u0026nbsp;genotypes. The main suspect for the deviation of some of the loci in any population is the population substructure.\u0026nbsp;This excess heterozygosis points to the absence of consanguineous mating in these populations and that mate selection is mostly random. In fact, the\u0026nbsp;inbreeding coefficient (\u003cem\u003eF\u003c/em\u003e\u003csub\u003eIS\u003c/sub\u003e) observed in this study in the five Nigerian subpopulations was very low for all loci.\u0026nbsp;The US National Research Council report recommends that a conservative \u003cem\u003eF\u003c/em\u003e\u003csub\u003eIS\u003c/sub\u003e estimate of 0.01 is expected in populations examined for forensic data and suggests that a value of 0.03 indicates that cousin mating\u0026nbsp;occurs\u0026nbsp;in such populations\u0026nbsp;(Balding, 2013).\u003c/p\u003e\n\u003cp\u003eHeterozygosity\u0026nbsp;also shows that there is stabilizing or balanced selection where natural selection\u0026nbsp;favours\u0026nbsp;the heterozygote over homozygotes, leading to lower-than-average\u003cem\u003e\u0026nbsp;F\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e values for the selected loci.\u0026nbsp;Five of the loci (D21S11, FGA, D9S2157, D6S1017,\u0026nbsp;and\u0026nbsp;D10S1248)\u0026nbsp;\u003csub\u003ehad FSTs,\u003c/sub\u003e indicating that there\u0026nbsp;was\u0026nbsp;stratification in the subpopulations. The extent of the variation\u0026nbsp;in\u0026nbsp;\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e from one locus to another helps to establish the source of the variation being observed. In populations where natural selection is selectively neutral, the only expected force at play is drift,\u0026nbsp;and the observed\u0026nbsp;\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u0026nbsp;\u003c/sub\u003ewill be\u0026nbsp;almost equal for all loci since drift depends only on demographic properties of the populations and not on any of the specific loci being studied (Khan \u003cem\u003eet al.,\u003c/em\u003e 2021). This is because the populations are assumed to have evolved independently from each other,\u0026nbsp;and each will produce constraints that affect the\u0026nbsp;\u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e distribution.\u003cem\u003e\u0026nbsp;F\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e will still vary from\u0026nbsp;locus\u0026nbsp;to\u0026nbsp;locus\u0026nbsp;in each of the subpopulations, but the extent of variation will be similar in each population.\u003c/p\u003e\n\u003cp\u003eThese stratifications seem to disappear when the Nigerian population is examined as a whole.\u0026nbsp;The analysis of molecular variance in this study\u0026nbsp;revealed\u0026nbsp;an estimated 99.98% variation within individuals. The variation among populations\u0026nbsp;was\u0026nbsp;0.10%.\u0026nbsp;Although\u0026nbsp;Igbo\u0026nbsp;shares\u0026nbsp;a common geographic boundary with Ibibio,\u0026nbsp;the\u0026nbsp;pairwise population matrix of genetic similarity for these loci shows that Igbo\u0026nbsp;has\u0026nbsp;greater similarity to Yoruba (0.993)\u0026nbsp;than\u0026nbsp;to every other population than to Ibibio. In fact, the Igbo-Ibibio similarity at these loci\u0026nbsp;was\u0026nbsp;the lowest (0.895) for all of the tested population pairs. These populations are actually the only populations that share a common geographic boundary, implying that this heightened dissimilarity for this population may be due to the alleles of these loci in\u0026nbsp;individuals\u0026nbsp;in this region diverging from each other. In fact, it has been previously established in other studies that the region of ethnic origin of any organism usually\u0026nbsp;has\u0026nbsp;the highest genetic diversity. The\u0026nbsp;results\u0026nbsp;of\u0026nbsp;the\u0026nbsp;pairwise population matrix of genetic similarity between populations also indicated that Ibibio and Tiv were more similar at these loci.\u0026nbsp;The Hausa population\u0026nbsp;had\u0026nbsp;a similarity index that\u0026nbsp;was\u0026nbsp;similar for all populations: Yoruba (0.992), Igbo and Tiv each (0.991) and Ibibio (0.988).\u003c/p\u003e\n\u003cp\u003eThese\u0026nbsp;populations\u0026nbsp;all share a common lingual ancestor, as they have all been classified into the Niger-Congo group of languages (Eberhard \u003cem\u003eet al\u003c/em\u003e., 2024). However, Igbo and Yoruba share linguistic similarity and are further classified together as YEAIs (non-Bantoid), whereas Ibibio and Tiv together belong to the Benue-Congo (Bantoid) subgroup of languages. The Hausa language is often classified as a member of the Afro-Asiatic group of languages. A similar relationship was observed in this study when a dendrogram was constructed for the five populations based on data from these 9 loci. Ibibio and Tiv clustered together. Igbo and Yoruba formed a more recent cluster and were joined by the Hausa.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eApproval of the research design, with the consent forms and biosample collection methods,\u0026nbsp;was\u003c/p\u003e\n\u003cp\u003eobtained from the Ethics Review Board of the Lagos University Teaching\u0026nbsp;Hospital\u0026nbsp;with\u003c/p\u003e\n\u003cp\u003ereference ADM/DCST/HREC/1921\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors\u0026nbsp;provided\u0026nbsp;consent for publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding\u003c/p\u003e\n\u003cp\u003eauthor on reasonable request.\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\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis\u0026nbsp;research\u0026nbsp;was partly funded by the University of Lagos Central Research\u0026nbsp;Committee\u0026nbsp;grant.\u003c/p\u003e\n\u003cp\u003eno. 2016/1 to KOA and JO\u003c/p\u003e\n\u003cp\u003eThe research and thesis writing were also supported by the Association of African Universities\u003c/p\u003e\n\u003cp\u003e(AUU) Small grant for Thesis writing with reference number PC/6 to AUU\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUUA, KOA and JO designed the experiments. KOA and JO applied for and obtained funding\u003c/p\u003e\n\u003cp\u003efrom the University of Lagos. UUA, EO, KU and NG collected\u0026nbsp;the\u0026nbsp;samples and\u0026nbsp;performed the\u0026nbsp;sampling trips. UUA and OAA performed the experiments. UUA and ODA analysed the results. KOA and JO reviewed the laboratory results. UUA obtained funding from the Association of African Universities for thesis writing. UUA wrote the manuscript. All the authors have read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the assistance of the technical staff of the Faculty of Science\u003c/p\u003e\n\u003cp\u003eUniversity of Lagos, Nigeria.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdeyemo A, Chen Y, Rotimi C (2005) Genetic Structure in four West African Population Groups. 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Human Hered 70:9\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1159/000288706\u003c/span\u003e\u003cspan address=\"10.1159/000288706\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Lagos","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Relationship, Alleles, Ethnic, Population, Nigeria","lastPublishedDoi":"10.21203/rs.3.rs-4670501/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4670501/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe genetic relationships between populations can be detected with the use of genetic markers. This study investigated the genetic relationships between five Nigerian populations of Igbo, Ibibio, Yoruba, Tiv and Hausa origin using nine short tandem repeat markers. The nine loci and the sex-typing marker amelogenin were combined into multiplex assays and tested by PCR followed by polyacrylamide gel electrophoresis on 50 individuals per population. The study revealed that four (4) of the nine (9) loci had \u003cem\u003eF\u003c/em\u003e\u003csub\u003eST\u003c/sub\u003e values between 0.001 and 0.500 in the five populations, indicating that population substructure had almost disappeared in the pooled population. The molecular variance (AMOVA) for the pooled population revealed a variance of 3.850 for individuals and a variance of 0.0004 for among populations. Principal component analysis (PCA) revealed four heterogeneous clusters. The total variation explained by the first three axes of the PCA was 32.86%. All the populations had a pairwise population matrix of Nei genetic identity greater than 0.895 based on these loci. Both the pairwise population matrix and a dendrogram constructed based on the allele frequencies of these loci indicated that the Igbo and Yoruba ethnic groups had the highest genetic similarity (0.993) among the evaluated populations. The pairwise population matrix of Nei genetic distance showed that Igbo and Tiv and Igbo and Ibibio had genetic distances of 0.14 and 0.15, respectively, which were the greatest for all pairs of the five populations.\u003c/p\u003e","manuscriptTitle":"Population Structure and Genetic Relationships among Nigerian Ethnic Groups (Ibibio, Igbo, Hausa, Tiv and Yoruba) Based on Nine Short Tandem Repeat Loci","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-03 15:39:53","doi":"10.21203/rs.3.rs-4670501/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ba68b9c0-354d-4fcd-8467-2510fc40b5d6","owner":[],"postedDate":"July 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":33983039,"name":"Population Biology"},{"id":33983040,"name":"Evolutionary Biology"},{"id":33983041,"name":"Evolutionary Genetics"},{"id":33983042,"name":"Molecular Genetics"},{"id":33983043,"name":"Population Genetics"}],"tags":[],"updatedAt":"2024-07-03T15:39:53+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-03 15:39:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4670501","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4670501","identity":"rs-4670501","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}