dehydrogenase subunit 5 (ND5) gene genetic differentiation of Anopheles arabiensis Patton (Diptera: Culicidae) the malaria vector in the Republic of Sudan

doi:10.21203/rs.3.rs-5301230/v1

Background

Anopheles arabiensis is the main malaria vector in Sudan. The abundance of Anopheles populations is subject to the environmental factors in which they inhabit. These factors play a major role in controlling their population genetic structure and their effectiveness as vectors.

Objective

The main objectives of this study were to investigate the genetic structure of Anopheles arabiensis, and to determine the relationships of An. arabiensis within the An. gambiae complex species based on mtDNA NADH dehydrogenase subunit 5 (ND5) gene.

Method

The samples were collected from six locations in different regions of Sudan during June 2010 to May 2011. The collection sites were; Mygoma, Alhaj Yousif and Algerif West (Khartoum State), Alkrmota and Alhalanga Shemal (Kassala State) and Abu Algoni (Sennar State). Partial mtDNA NADH dehydrogenase subunit 5 (ND5) gene was utilized to examine the interpopulation sequence variation in Sudan.

Results

Haplotype diversity was high (0.61- 0.90) with low nucleotide diversity (0.003-0.004). High gene flow and no isolation by distance were observed among populations using the ND5 gene

Conclusion

This study revealed high gene flow and no isolation by distance among the six populations investigated.

Anopheles arabiensis

ND5 partial gene

gene flow

isolation by distance

Sudan.

Population genetics studies are essential in the control and management of malarial incidence (Tabachnick and Black, 1995). Through the population structure data, the topographic spreading and possible reproductive segregation could be elucidated (Lanzaro and Tripet, 2003). Furthermore, such studies permit gene flow estimations within and between populations and identification of the biological and environmental factors that influence their movement (Lanzaro and Tripet, 2003). Several markers are widely utilised for this purpose particularly the haploid and maternally inherited mtDNA (Avise, 2004). Investigations of population genetics in the mosquitoes of medical importance within the last few decades have relied mainly on mtDNA and microsatellite markers (Besansky et al., 1997; Birungi and Munstermann 2002; Nyanjom et al., 2003; Temu and Yan, 2005; Kent et al., 2007; Venkatesan et al., 2007; Muturi et al., 2010; Vicente et al., 2011; Nghabi et al., 2011; Carter et al., 2019, Mustafa et al., 2021) but there has not been a comprehensive study of the maternally inherited mitochondrial marker in the populations of Sudan.

Population Genetics of Anopheles gambiae Complex Based on Mitochondria DNA

Mitochondrial DNA (mtDNA) is relatively simple to amplify for the reason that it is present in multiple replicates in the cell. Its gene contents are highly conserved across animals, with very little duplication, no intron, and very short intergenic regions (Gissi et al., 2008). Fast mutation rates in mtDNA, particularly in specific genes result in significant variation in sequences within and between species providing ample within-species variance which is useful for phylogenetic investigations (Tamura and Nei, 1993; Mohanty et al., 2009).

In anophelines, mtDNA sequences have been applied to determine associations at different taxonomic levels of divergence, for example at population, species, genus and also at higher taxonomic levels (Krzywinski et al., 2001; Krzywinski and Besansky, 2003; Loaiza et al., 2010). This is due to the differing rates of mutation among genes. For instance, the D-loop, cytochrome b, NDI and ND5 genes (Besansky et al., 1997; Donnelly et al., 2004; Marshall et al., 2008) are frequently utilised for population genetic studies due to their higher mutational rates while 16S rRNA (Shouche and Patole, 2000) is utilised for higher level rankings. It is also very effective in estimating time of separation of lineages (Krzywinski et al., 2006; Moreno et al., 2010) and for resolution of sibling species (Goswami et al., 2006; Dusfour et al., 2007).

Besansky et al. (1997) showed that within An. arabiensis populations across Africa, no population subdivision was detected even at distances of 600 km based on partial gene sequences of the cytochrome b, NDI and ND5 genes. Evidence that populations of An. gambiae and An. arabiensis show low levels of population differentiation across their range as detected using microsatellite loci and mitochondrial ND5 gene has been attributed to the recent population range expansion of these species (Donnelly and Townson, 2000; Donnelly et al., 2001). Also Mustafa et al., 2021 revealed low levels of population differentiation with high gene flow among the An. arabiensis populations investigated in Sudan, using microsatellite loci.

The lack of mitochondrial difference between populations and species within An. gambiae complex has led to conclusions of gene flow across great geographic expanses and contemporary genetic introgression among species within the complex (Beard et al., 1993; Besansky et al., 1994; 1997; Caccone et al., 1996; Lehmann et al., 1997; 2000 and Donnelly et al., 2001; 2004). In the present study, the ND5 gene was chosen because past studies involving Kenyan populations of both An. gambiae and An. arabiensis established that this region was polymorphic {Besansky et al., 1997; Kamau et al., 1999). In addition, a common gene would facilitate easier comparisons.

The aim of the study was to estimate genetic variability and population structure, for any evidence of subdivision and restricted gene flow within An. arabiensis populations from Sudan. This mitochondrial analysis would complement an earlier study (Mustafa et al., 2021) based on microsatellite markers to provide insights on maternal genetic structuring. This is particularly important as the biting females are the source of malaria infection. Furthermore, the relationships of An. arabiensis within the An. gambiae complex species based on mitochondrial ND5 gene would be determined focusing on species from the Sudan.

Study Sites

The mosquitoes were collected from six localities in Sudan representing different geographical regions separated by the River Nile and its tributaries from June 2010 to May 2011. These are subsamples previously described in Mustafa et al., 2021. Three localities were located in Khartoum State, namely 1. Mygoma (My) 2. Al Haj Yousif (Hj) 3. El Gerif West (Gw). My and Hj are nearest to each other and east of the Blue Nile. In addition Hj is northeast of Helt Koko, where animals are bred for milk production in a rich green area on the West bank of the Blue Nile. The fourth and fifth sites are in Kassala State namely 4. Alhalang Shemal (H.sh), located on the east bank of the AlGash River, a non-agricultural land area and 5. Alkrmota (Kr) located on the west bank of the Al Gash River in the centre of an agricultural area which is surrounded by groves of fruit and vegetables in all directions. The sixth population (6) Abu Algoni (Se) is in the Sennar state (Se), specifically at a farming area which is located on the west bank of the Blue Nile River.

Molecular Laboratory Analysis

Genomic DNA was extracted from individual mosquito following QIAGEN protocol (QIAGEN Sciences, Maryland 20874, USA). The mitochondrial ND5 DNA was amplified using the specific PCR primers 19CL F: 5’- CTT CCA CCA ATT ACT GCT ATA ACA G-3’; and DM3A R: 5’-AGG ATG AGA TGG CTT AGG TT-3’ of An. gambiae mtDNA (Besansky et al., 1997). PCR was carried out in a 25 µL reaction containing 18µL sterile H₂O, 2.5 µL 10X PCR Buffer with MgCl2, 1.0 Μl dNTPs (2 mM), 0.3uL MgCl2 (25 mM), 1.5uL forward and reverse primers, 0.2 µL TaqDNA polymerase (5 U/µL) (iNtRON, Gyeonggi-do, Korea) and 0.2 µL template DNA. The cycling conditions conducted in the Mastercyler Thermal Cycler (Eppendorf) were 4 min denaturation at 94ºC, followed by 35 cycles of 30 sec denaturation at 94ºC, 40 sec annealing at 53ºC and 30 sec extension at 72ºC with a final cycle extension at 72ºC for 10 min. The amplified PCR products from each reaction were mixed with 2µL loading dye, electrophoresed through a 2% agarose and stained with ethidium bromide to assess for purity and quantity. Amplified fragments were visualized by illumination with ultraviolet light. The PCR products were purified using the Promega kit (Promega Corporation, Madison, WI, USA). Purified products were sent for DNA sequencing to a service provider, (First BASE Laboratories Sdn Bhd, Selangor, Malaysia).

Data Analysis

Nucleotide Alignment

Each pair of forward-reverse ND5 sequences were separately aligned. Editing and alignment of the sequences were implemented in Clustal W in MEGA 5.0.5 (Tamura et al., 2011). The sequences were then translated into protein in the same programme to detect any occurrence of stop codons which would indicate presence of numts. Collapse 1.2 (Posada, 2004) was used to build a haplotype datasheet and the allocation of haplotypes among all populations was manually summarized in the DnaSP program (Rozas et al., 2003). Within and between population variations were analysed based on these haplotypes.

Genetic Diversity

The programme MEGA 5.05 was also utilised to calculate nucleotide variable and parsimony informative sites, number of haplotypes, number of transitions and transversions, synonymous and non-synonymous amino acid substitutions and nucleotide frequencies. Intra and interpopulation genetic divergence of haplotypes based on Kimura 2-parameter genetic distance were also estimated in the same programme. Using Arlequin 3.5 (Excoffier et al., 2010), three estimations of diversity measurement were calculated to describe DNA polymorphism at each sampling site; haplotype gene diversity, nucleotide diversity and theta S. Haplotype gene diversity (Hd) estimates the probability of uniqueness of a haplotype in a given population. Nucleotide diversity (π) measures the mean number of pairwise nucleotide differences among individuals in a population. Theta S (θs) (Watterson, 1975) calculates the number of segregating sites among haplotypes in a population.

Population Differentiation and Structuring

F statistics i.e F_ST population pairwise comparisons that determine genetic differentiation between sites were calculated in Arlequin 3.5 (Excoffier et al., 2010) to estimate the level of differences among populations and spatial population structuring. The analysis used Kimura 2-Parameter distance method and statistically significant pairwise comparisons were tested with 1000 permutations. Analysis of molecular variance (AMOVA) was conducted to infer the relative attribution of variance among groups/regions (F_CT) (Khartoum, Kassala and Sennar), among populations within groups (F_SC) (My, Hj, and Gw –Khartoum; H.sh and Kr –Kassala; and Se –Sennar) and within populations using Arlequin 3.5 (Excoffier et al., 2010). Using the DnaSP programme, gene flow estimates (Nm) based on both haplotype-based and sequence-based statistics were derived as in Nei (1973) and Hudson et al. (1992).

Phylogeography and Phylogenetic analyses within the Anopheles gambiae complex and among the An. arabiensis Populations

The ND5 variation of the six member species of the An. gambiae complex were analysed based on data from the current study and GenBank voucher sequences (www.ncbi.nim.nih.gov); 1. An. gambiae (DQ440687.1, DQ440689.1, DQ440773.1) 2. An. melas (JX117756.1, U10123.1, U10129.1, JX117667.1) 3. An. bwambae (AF116828.1) 4. An. quadriannulatus (U10133.1, U10132.1), 5. An. merus (U10130.1, U10131.1) and 6. An. arabiensis (hj12-, Hj 15, Hj16, from this study ). Anopheles stephensi (AY842526.1) was included in the analysis as the outgroup. Sequence alignment was performed by using MEGA 5.05 software through exclusion of all positional gaps and missing data. The sequences were then trimmed to obtain equal lengths for all the species. Subsequently, a total of 823 bp of the ND5 sequence was used in the final dataset. Evolutionary divergence between all sequence pairs of the An. gambiae complex were calculated using the Maximum Composite Likelihood model based on the Kimura 2-parameter model (Kimura, 1980). Neighbor-Joining (NJ) (Saitou and Nei, 1987) and Maximum Parsimony (MP) (Eck and Dayhoff, 1966) methods were implemented. The Neighbour Joining (NJ), a distance-based and Maximum Parsimony (MP), a character-based method were applied to build the phylogenetic trees with the least evolutionary steps or with the least total branch length. The NJ method was based on the Kimura 2-Parameter (Kimura, 1980) evolutionary distance with confidence level at each node measured by 1000 bootstrap replications (Felsenstein, 1985). The most parsimonious MP tree was generated through the close-neighbour-interchange (CNI) with an initial tree by random addition of sequences in 20 replicates, set at search level of three. To view the most frequent topology, an MP consensus tree with 50% cut-off was generated. On the other hand, the NJ tree was constructed based on F_ST values, to depict the phylogenetic relationships among the populations.

Demographic History

Estimations of departure from neutral expectation were examined through Tajima’s D (Tajima, 1989a) and Fu’s Fs (Fu, 1997) statistics for each population from the Sudan using Arlequin 3.5 (Excoffier et al., 2010). These departures could arise as a consequence of historical population range expansion or mutation-drift disequilibrium. Deviation from neutrality due to population bottleneck or expansion, directional selection or introgression is detected by Tajima’s D, based on mutation (segregating sites) frequency. The null hypothesis for Tajima’s D test is neutral evolution in an equilibrium population, which means no selection bias and the population has not experienced growth or size reduction (Tajima, 1989b). A recent directional selection (selection sweep) or recent population growth with excess of rare alleles would result in a negative value while balancing selection or population sub-structuring or recent bottleneck (Tajima, 1989b) would generate positive value of Tajima’s D. Fu’s Fs statistics is based on Ewens sampling distribution (Ewens, 1972) and haplotype distribution. It is very efficient in detecting past population size fluctuations (Ramos-Onsins and Rozas, 2002).

Isolation-by-Distance (Mantel Test)

Mantel test (Sokal, 1979) was used to investigate the correlation between geographical and genetic distances among populations using Arlequin 3.11 (Excoffier et al., 2005).

All 103 individuals of An. arabiensis from the six sampling areas were successfully sequenced for the ND5 gene producing a 981bp fragment. A final segment of 823 bp was obtained after alignment and editing of ambiguous sequences. These 103 sequences revealed 16 segregating sites with the generation of 19 haplotypes. Sample sizes ranged from 16 to 20 with an average of 17 individuals per population. As observed in the table, there appears to be two sets of major haplotypic groups; 1. Hap1- Hap12 and 2. Hap13-Hap19 with some slight deviation. Hap9 of Kr links the two groups.

Nucleotide Composition

The 19 haplotypes generated revealed: mean haplotype diversity, Hd- 0.80, mean number of variable sites- 7 and nucleotide diversity- 0.034. The average nucleotide composition was C:10.26%, T: 44.18%, A: 30.98% and G: 14.58%. All unique sequences have been deposited in GenBank with accession number KC610567-KC610669. There were 8 nonsynonymous substitutions out of the 19 haplotypes. The nonsynonymous substitutions were: G A at positions 162, 225, 288, 613 and T C at positions 21, 24, 36, 45. Three substitutions result in amino acid changes namely at positions 117 and 7 (Ala replaced by Pro) in Hap02 and Hap 05 respectively and at position 205 (Serine replaced by Glycine). Different rates of transitional and transversional substitutions were observed.

Haplotype Distribution

Haplotype distribution varied among the populations and regions studied and showed that 13 were population specific, 1 regional specific while 5 of the totals were shared in more than one region respectively. The 13 population-specific (private alleles) were Hap02, Hap03, Hap04, Hap05, Hap07, Hap09, Hap10, Hap12, Hap14, Hap16, Hap17, Hap18 and Hap19 (Table 3). For example, My had private alleles Hap02 and Hap14. The six shared haplotypes were Hap01, Hap06, Hap08, Hap11, Hap13 and Hap15. Hap01 was the most common (25.42%), observed populations and regions except in the Kassala population. Hap06, Hap08, Hap13 and Hap15 were found in all regions although not represented in every population. However, Hap11 was only restricted to the two populations of Kr and H.sh.

Table 1

Haplotype distribution across six populations of *An. arabiensis* and ratio of observed transition versus transversion substitution in each population inferred from partial mtDNA ND5 gene.
Region	Khartoum			Kassala		Sennar
Pop Hap	My	Hj	Gw	Kr	H.sh	Se	Total	Hap freq
hap01	7	10	2			7	26	0.252
hap02	2						2	0.019
hap03					2		2	0.019
hap04					2		2	0.019
hap05				2			2	0.019
hap06			2	2		2	6	0.058
hap07			2				2	0.019
hap08			2		2	2	6	0.058
hap09				4			4	0.039
hap10			4				4	0.039
hap11				3	2		5	0.049
hap12		2					2	0.019
hap13	4			1	2	4	11	0.107
hap14	2						2	0.019
hap15	2	8		3	5	1	19	0.184
hap16					2		2	0.019
hap17				2			2	0.019
hap18			2				2	0.019
hap19			2				2	0.019
Total	17	20	16	17	17	16	103
TS:TV	7:1	5:0	8:1	6:4	4:1	5:1	5.8:1.3
Populations: My = Mygoma, hj = Alhaj Yousif, Gw = Algerif West, Kr = Krmota, H.sh = AlHalang Shemal, Se = Abu Algonia (Sennar).

Table 2 Genetic diversity for ND5 sequences in An. arabiensis showing sample size (N), number of variable sites (#V), number of haplotypes (H), haplotype diversity (Hd), nucleotide diversity (π), theta (S) and neutrality tests of Tajima^’s D and Fu^’s Fs for each population and each group.

Genetic diversity							Neutrality test
Pop	N	#V	H	Hd	π	Theta (S)	Tajima′s D	Fu^’s Fs
My	17	8	5	0.78	0.004	2.37	0.947 P > 0.10	1.563 P >0.10
Gw	16	9	7	0.90	0.004	2.71	0.344 P> 0.10	-0.559 P>0.01
Hj	20	5	3	0.61	0.003	1.41	2.516 P < 0.01	4.186 P <0.02
Se	16	6	5	0.76	0.03	1.81	0.978 P > 0.10	0.709 P>0.01
H.sh	17	5	7	0.88	0.003	1.48	1.586 P > 0.10	-1.271 P >0.05
Kr	17	9	7	0.89	0.004	2.67	1.035 P > 0.10	0.08 P >0.10
average	17.2	7	5.7	0.80	0.003

Populations: My = Mygoma, Hj = Alhaj Yousif, Gw = Algerif West, Kr = Krmota, H.sh = AlHalang Shemal, Se = Abu Algonia

Table 3

Population differentiation of *An. arabiensis* using distance method F_ST pairwise difference
	Kr	My	Se	Hj	Gw	H.sh
Kr	*	431.75	334.01	427.72	443.21	12.88
My	0.14	*	292.07	3.93	15.55	416.55
Se	0.14	− 0.02	*	311.55	323.10	429.31
Hj	0.20	0.07	0.10	*	5.38	448.59
Gw	0.09	0.12	0.09	0.20	*	426.5
H.sh	0.04	0.11	0.13	0.16	0.10	*
F_ST estimate using pairwise genetic distance shown below diagonal
Geographical distance shown above diagonal.

Genetic Diversity

The number of variable sites ranged from 5–9, and number of haplotypes ranged from 3–7 per population. Overall, high levels of intrapopulation haplotype diversity but low nucleotide diversity was observed. Haplotype diversity (H_d) ranged from 0.611 in Hj to 0.9 in Gw, while nucleotide diversity (π) from 0.003 in H.sh to 0.004 in Kr (Table 2).

Demographic History

As shown in Table 2 all populations showed positive but nonsignificant values for Tajima^’s D neutrality tests, except for Hj which indicated balancing selection or population sub-structuring or recent bottleneck (Tajima, 1989). Gw and H.sh population showed negative but nonsignificant values for Fu^’s Fs.

Population Differentiation and Structuring

F_ST pairwise values ranged from − 0.02 to 0.20. All F_ST values were significant except between Kr and H.sh, My and Hj and My and Se. According to Wright’s values F_ST = 0 indicates no genetic divergence, F_ST = 0–0.05 indicates low genetic differentiation, F_ST = 0.05–0.15 indicates moderate difference and F_ST = 0.15–0.25 indicates high genetic differentiation. No genetic divergence was found between My and Se (different regions). Low genetic differentiation was observed between Kr and H.sh (same region). Moderate values were observed between My and Hj (same region); Gw and Se; and Gw and Kr (both pairs involve populations of different regions). High genetic differentiation were observed between pairwise Kr and Hj, H.sh and Hj and unexpectedly also between Gw and Hj which are geographically closely related populations. Overall, the F_ST analysis generated two groups; 1. Kr, H.sh, Gw and 2. Se, My and Hj. These genetic groups do not appear to correlate with geographical partitioning. Gw and H.sh; and Se and H.sh. In agreement, Neighbor-Joining tree based on F_ST values also consisted of two clades; Clade I includes Kr, H.sh and Gw, while Clade II includes Se, My and Hj (Fig. 1).

To determine the hierarchical genetic apportion of An. arabiensis in Sudan, an AMOVA approach was applied. The AMOVA results showed a high proportion of total variation within population (88.06%), but moderate proportion of variation was attributed to difference among populations within groups (9.75%) and low among groups within total (2.19%) – Table 4. However, all analyses are significant.

Table 4

Results of AMOVA *An. arabiensis* populations ND5 gene.
Source of Variation	d.f.	Variance Components	Percentage of Variation	Fixation Indices	P value
Among groups	2	0.010	2.19	F_CT: 0.10	0.00
Among populations within groups	3	0.044	9.75	F_SC: 0.119	0.00
Within populations	97	0.398	88.06	0.022	0.018

Genetic differentiation, genetic distance and gene flow were estimated among all An. arabiensis populations from Sudan (Table 5). Gene flow ranged from 1.63 to infinity. High gene flow was found between My and Hj; My and Gw which are geographically close, and surprisingly between My and Se; and Gw and Se which are distantly positioned. As expected the lowest gene flow was found between Gw and H.sh; and Se and H.sh, which are distant populations. However, unexpected low gene flow was also observed between the geographically close Kr and H.sh populations (Table 5). The genetic distance between populations ranged from 0 to 0.307, the genetic distance between Gw and Se; and My and Se = zero while it is high between Gw and H.sh.

Table 5

Gene flow (Nm) and genetic distance between populations
	Kr	H.sh	My	Hj	Gw	Se
Kr	0	0.096	0.074	0.109	0.106	0.084
H.sh	5.21	0	0.171	0.132	0.307	0.307
My	6.79	2.92	0	0.019	0.018	0.00
Hj	4.57	3.79	26.07	0	0.058	0.036
Gw	4.72	1.63	27.96	8.57	0	0.00
Se	5.94	1.63	inf	13.79	inf	0
Nm (bold) shown below diagonal
Genetic distance shown above diagonal.

Isolation-by-Distance (Mantel Test)

The Mantel test calculated based on the mean pairwise genetic distance versus geographical distance showed low and nonsignificant correlation (R² = 0.229, P > 0.05) between the two parameters (Fig. 2).

Phylogenetic Relationships Among Anopheles gambiae complex (GenBank) and Sudanese Samples.

Neighbour Joining and Maximum Likelihood methods generated similar trees for phylogenetic relationships among selected anopheline mosquitoes (Fig. 3). The estimates of evolutionary divergence between sequences of the An. arabiensis and other members of the Anopheles gambiae complex are presented in Table 6. The evolutionary divergence is lowest between An. arabiensis - An. gambiae (0.005), followed by An. bwambae- An. quadriannulatus (0.012), An. merus- An. quadriannulatus (0.017) and An. merus -An. bwambae(0.019) pairs. The divergences between other pairwise species comparisons were much greater (0.376–0.744).

Table 6

Estimates of Evolutionary Divergence among members of *An. gambiae* complex.
Species	1	2	3	4	5
An. arabiensis hj16
An. gambiae DQ440687	0.005
An. melas JX117756.1	0.521	0.534
An. bwambae AF116828.1	0.376	0.388	0.709
An.quadriannulatus U10133.1	0.393	0.405	0.717	0.012
An. merus U10130.1	0.393	0.405	0.744	0.017	0.019

Spanning Network of ND5 Gene

The minimum spanning network (MSN) depicts haplotype geneology (Fig. 4). The size of the circle parallels the frequencies of haplotypes. The area of coloured region represents the contribution of each population for a particular haplotype. Median vectors (mv) are shown in red diamond dots which represent samples that should be present but could not be detected during sampling. Numbers between two haplotypes represent the mutation sites. The minimum spanning network of An. arabiensis revealed two highly divergent clades, each with one common central haplotype, regarded as the ancestral haplotype. The central haplotypes Hap01 and Hap13 represent the inferred ancestral haplotypes for clade 1 and clade 2, respectively. Hap01, Hap 13 and Hap 15 are the dominant haplotypes in populations Se, My, Kr, and H.sh with high frequency in Hj population from which lower frequency haplotypes radiated. All populations are represented in both major clades with varying frequencies.

Phylogenetic Relationships Among An. arabiensis populations from Sudanese and Selected African GenBank sequences

The analysis showed well resolved clades, of which two branches on the MP tree are well supported at 100%. The NJ tree is similar but not presented here. However, there was a great deal of admixture among the populations from Ethiopia, Malawi and Sudanese populations in the present study. Thus, no population structuring was observed even on a large scale. For instance, several haplotypes from Ethiopia and Malawi clustered with haplotypes from Kr namely Hap5 and Hap9 (the most genetically distant Sudanese population) while others from the same region (countries) cluster with haplotypes from other Sudanese regions (Fig. 5).

A good knowledge of the molecular evolution and phylogenetics of the An. gambiae complex will assist in the understanding of its origin, evolution, classification and epidemiology (Foley et al., 1998; Thelwell et al., 2000). This is essential in strategising the control of malaria infection (Besansky et al., 2003). Knowledge of species identification, distribution, ability to act as vectors, their roles in the malaria transmission and insecticide resistance gene spreading through populations are important in vector control.

Genetic variability

The nucleotide diversity in the An. arabiensis of the current study for the ND5 gene was low ranging from 0.003 to 0.004 with a mean of 0.0034, similar to Besansky et al. (1997) which observed nucleotide diversity of 0.0038 and 0.0046 in An. gambiae and An. arabiensis, respectively in their study conducted in Kenya, Senegal and South Africa. The haplotype diversity in the Sudanese populations of the current study ranged from 0.61 to 0.9 in agreement with Solorzano et al. (2010) which documented values of 0.887 to 0.975 in Ae. vexans of New Orleans population also based on ND5 gene. This high haplotype diversity was suggested due to the species being native or has been established for a long period of time in a particular habitat (Hartl and Clark, 1997). However, Maia et al. (2009) observed much lower levels of genetic variation in Ae. albopictus from Manaus, Brazil, based on analysis of the ND5 with mean values of haplotype and nucleotide diversities of 0.187 ± 0.059 and 0.0004 ± 0.00014, respectively. Their observation was attributed to genetic drift effect from a small founder population of only a few individuals (Davies et al., 1999; Martocq and Villablanca, 2001), coupled by the increase of populations in the suburbs of the city (Fé et al., 2003). This expansion in Manaus resulted in homogenisation of the gene pool through high gene flow (Nm values). Therefore, the low genetic structuring was attributed to an inadequate period for accumulation of genetic differences between populations of Ae. albopictus in Manaus, and not due to the widespread contemporary gene flow.

Temu and Yan, (2005) observed genetic structuring of An. gambiae and An. arabiensis collected from four study sites in Western Kenya, the Great Rift Valley and coastal Kenya into clusters. Our study also showed subdivision of An. arabiensis in Sudan where the six populations were divided into two clusters 1. Kr, H.sh (Kassala) with Gw (Khartoum), cluster 2. Hj, My (Khartoum), Se (Sennar). We hypothesise that the structuring is due to human anthropogenic influence. Group 1 comprises of Gw from Khartoum region, and the Kassala populations of Kr, H.sh. The genetic affinity among these populations may be due to the movement of Ethiopian refugees through Kassala to Gw in Khartoum. The Anopheles vector is transported with their belongings across these towns. The genetic similarity of Hj and My could be attributed to their close geographical proximity. However, they are also genetically close to Se although it is distant from either geographically. This genetic similarity may also be attributed to human movement between city populations for trading needs- selling and buying goods, animals and crops.

Haplotype distribution

In the current study, several haplotypes were shown be shared between two or more populations and even between regions in Sudan similar to Besansky et al. (1997) which observed several shared haplotypes within the Kenyan populations of An. gambiae and An. Arabiensis, respectively. Temu and Yan (2005) also reported similar sharing between haplotypes of An. arabiensis populations from Western Kenya, the Great Rift Valley and coastal Kenya. Furthermore, Marshall et al. (2008) also reported shared haplotypes between several molecular forms of An. gambiae from the islands of Sao Tome and Principe.

Donnelly et al. (2004) stated that shared haplotypes between species in the An. gambiae complex may reflect non-contemporary processes such as incomplete lineage sorting between species or historical introgression events.

In the current study five out of 19 haplotypes were shared between populations which were geographically distant for example, Hap 01 was shared between My, Hj, Gw (Khartoum) and Se (Sennar) populations. Hap15 was shared between My, Hj (Khartoum), Kr, H.sh (Kassala) and Se (Sennar) populations. This common haplotypes showed that they were of the same ancestral origin which have shared a widespread demographic history. High genetic differentiation were observed between Kr and all other population using microsatellite markers (Mustafa et al., 2021), while with ND5 gene these were observed between pairwise Kr and Hj, H.sh and Hj and unexpectedly also between Gw and Hj which are geographically closely related populations.

Genetic diversity

Maia et al. (2009) found low genetic diversity (π = 0.00044) in Ae. albopictus populations from Manaus, Brazil (present study, π = 0.00335). They suggested that this may be due to an inadequate time for accumulating genetic differences among populations of Ae. albopictus in Manaus, and not due to the widespread gene flow occurring among them. Similarly, Birungi and Munstermann (2002) reported lower genetic diversity (π = 0.0002) compared to the present study in Ae. albopictus populations from the south and southeast coast of Brazil, utilising ND5 gene. Kambhampati and Rai (1991) and Kambhampati et al. (1991) also observed low nucleotide diversity in 17 populations of Ae. albopictus from Asia. They suggested a recent expansion from a bottleneck event of Ae. albopictus in this region to account for the observation.

However, when there are no barriers to gene flow, populations would randomly mate and become panmictic. Solorzano et al. (2010) revealed high levels of gene flow with Nm value ranging from 29 to 32 between populations of Orleans and Chalmette in the United States. Similar high gene flow, among several populations from Sudan was observed which we attribute to human transportation through daily or frequent movement between the villages and cities for medical needs, trading of animals and vegetables that have resulted in passive long-distance migration of the An. arabiensis populations. Microsatellite loci revealed significant levels of gene flow among the An. arabiensis populations and between An. gambiae populations from Asembo Bay in Western Kenya and Ghana in West Africa suggesting a high capacity for the dispersal of genes such as those accountable for insecticide resistance or refractoriness to malaria among these populations (Kamau et al., 1999). In Sudan insecticide resistance had been reported in most parts of the country as a result of spreading of this gene due to interaction and the movement from one place to another in the country. While most populations seem to be genetically well connected, the unexpected low gene flow between Kr and H.sh which are geographically near to each other, may be because of the presence of the Al Gash River which acts as a physical barrier between them.

Demographic history

Tajima^’s D analysis did not detect any significant deviation from neutrality in five of the six populations investigated in this study suggesting that the ND5 genetic variability are consistent with the neutral evolution theory and gene flow is extensive in the An. arabiensis populations. The sixth population, Hj significantly deviated from neutral expectation indicating balancing selection or population sub-structuring or a recent bottleneck event (Tajima, 1989b). Maia et al. (2009) also reported that Tajima’s D neutrality test was nonsignificant for all populations analyzed from Manaus, Brazil, concluding that these populations were in genetic equilibrium (Kimura, 1983). Similarly, Birungi and Munstermann (2002) also reported that Tajima’s D tests were also non-significant in their study on ND5 gene in Brazil and United States. Fu’s Fs neutrality test, which assesses population growth, also did not show significance, and therefore Ae. albopictus populations in Manaus were believed to be expanding. However, the populations structuring detected in their study may be due to ecological and climatic factors in the different populations. The sixth population of the present study, Hj, significantly deviated from neutral expectation indicating balancing selection or population bottleneck event. This could be due to effective control programmes applied at this locality, while other populations showed insecticide resistance or high development than Hj.

Isolation by distance

In the present study no isolation by distance (Mantel test), specifically no correlation of genetic distance with geographic distance, was found among the six populations from Sudan similar to early of populations from Sudan based on microsatellite markers (Mustafa et al., 2021). Similarly, Solorzano et al., 2010 found ‘no isolation by distance’ across the three parishes of New Orleans that they investigated and suggested that there was no geographic barrier to movement of mosquitoes within the geographical range. Similarly, Kamgang et al. (2011) who studied genetic structure of the tiger mosquito, Ae. albopictus, in Cameroon found no observable relationship between genetic and geographic distances suggesting that the genetic structure observed among several population pairs had been shaped by other biotic or abiotic factors. However, Carnahan et al. (2002) observed a strong correlation between geographic and genetic distance across consistently favourable habitats in Mali. This revealed that geographic barriers are not the only the reason for a decrease in gene flow in An. gambiae s.s. The circumstances in Mali, West Africa were evidently different than those in East Africa in terms of habitats and climatic factors between the two groups. Ayala & Coluzzi, (2005) and Costantini et al. (2009) established that the species within An. gambiae complex are not isolated by geographic barriers. In this study it appears that the River Nile and its tributaries act as geographic barriers among these populations.

Phylogenetic divergence among Anopheles gambiae complex

Mitochondrial ND5 gene is a powerful tool in elucidating the level of genetic and phylogenetic divergence among closely related species (Krzywinski et al., 2001). The results of the present study on An. gambiae complex inferred that An. arabiensis and An. gambiae are the most closely related taxa based on the evolutionary sequence divergence of the two species as had been documented in previous studies (Krzywinski et al., 2001). This is in conformity with the morphological, behavioural, and ecological similarity between the two species described by Besansky et al. (2003). Furthermore, Otarigho and Falade (2013) in their study on the molecular evolution and phylogenomics of the Anopheles gambiae complex using COI gene showed that An. arabiensis and An. gambiae, the two major vectors of malaria are genetically similar.

In the case of Hj population based on ND5, Tajima᾽s value indicated recent bottleneck supporting an earliers by microsatellite markers Mustafa et al., 2021, which suggest recent population size reduction in Hj unlike in the other populations. The phylogenetic tree using ND5 positioned Kr with H.sh and Gw, while microsatellite markers isolated Kr from the rest (Mustafa et al., 2021). The population subdivision suggested by the ND5 gene and microsatellite markers Mustafa et al., 2021 explained that An. arabiensis populations in Sudan are not homogeneous. The differences in the observed level of genetic differentiation among ND5 gene and microsatellite markers by Mustafa et al. (2021) suggest that the mutational rates varies significantly among different regions within the genome.

The ND5 genetic analysis revealed a general trend of high levels of haplotype diversity but coupled with low nucleotide diversity. All populations showed positive but nonsignificant values for Tajima᾽s D neutrality tests from neutral expectation, excluding Hj which indicates balancing selection or population substructuring or recent bottleneck for this population. Non-significant Tajima᾽s D values indicated that the patterns of molecular diversity among populations were not likely due to selection and rapid range expansion but rather of pure demographic expansion, attributable to malaria control programmes applied in the country. Overall, the six populations were divided into two genetic group; 1. Kr, H.sh (Kassala State) and Gw (Khartoum State) 2. Se (Sennar State), My and Hj (Khartoum State). High gene flow was found between My and Hj; Gw and My which are geographically close population pairs but unexpectedly also between My and Se; and Gw and Se which are distantly positioned. The latter observation was possibly a result of human mediated transportation. Although the lowest gene flow was found between Gw and H.sh; and Se and H.sh, which are distant populations, low gene flow was also observed between Kr and H.sh which are geographically close and this may be due to the AlGash River acting as a physical barrier between them. Phylogenetic divergence among Anopheles gambiae complex inferred that An. arabiensis and An. gambiae are the most closely related taxa based on the evolutionary sequence divergence of the two species.

More extensive studies on population structure and genetics of Anopheles arabiensis in the other regions in Sudan using mitochondrial and microsatellite loci would enable gathering information on factors that may affect gene flow, subsequently to recommend a comprehensive control programme of malaria in Sudan.

Author Contribution

MSM: did the field and practical laboratory work, data analyses and prepared the manuscript. ZJ and SAMN supervised the study and edited the manuscript. SA supervised the field work

Acknowledgement

This project was mainly supported by the Postgraduate Research Grant Scheme (USM- RU-PRGS) of the Universiti Sains Malaysia. Thanks also go to TWAS for providing the PhD fellowship, and to the Unversity of Albutana for granting me the study leave. Special thanks go to the Zoology Department, Faculty of Science, University of Khartoum and the Malaria Research Center in Sennar for allowing me to use their laboratory and the technical assistance given during the period of the study and all members of Lab 308, School of Biological Sciences, Universiti Sains Malaysia.

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No competing interests reported.

dehydrogenase subunit 5 (ND5) gene genetic differentiation of Anopheles arabiensis Patton (Diptera: Culicidae) the malaria vector in the Republic of Sudan

Status:

Version 1

Abstract

Figures

Introduction

Materials and Methods

Study Sites

Molecular Laboratory Analysis

Data Analysis

Nucleotide Alignment

Genetic Diversity

Population Differentiation and Structuring

Demographic History

Isolation-by-Distance (Mantel Test)

Results

Nucleotide Composition

Haplotype Distribution

Genetic Diversity

Demographic History

Population Differentiation and Structuring

Isolation-by-Distance (Mantel Test)

Spanning Network of ND5 Gene

Discussion

Genetic variability

Haplotype distribution

Genetic diversity

Demographic history

Isolation by distance

Conclusions

Declarations

Author Contribution

Acknowledgement

References

Additional Declarations

Status:

Version 1