Intra and interspecies variation and population dynamics of Fasciola gigantica among ruminants in Sudan

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Mohamed, Ayman Ahmed, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3849640/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 May, 2024 Read the published version in Parasitology Research → Version 1 posted 7 You are reading this latest preprint version Abstract Fasciola gigantica is a widespread parasite that causes neglected diseases in livestock worldwide. Its high transmissibility and dispersion are attributed to its ability to infect intermediate snail hosts and adapt to various mammalian definitive hosts. This study investigated the variation and population dynamics of F. gigantica in cattle, sheep, and goats from three states in Sudan. Mitochondrial cytochrome c oxidase subunit I (COI) and NADH dehydrogenase subunit 1 (ND1) genes were sequenced successfully to examine intra and inter-specific differences. ND1 exhibited higher diversity than COI, with 15 haplotypes and 10 haplotypes, respectively. Both genes had high haplotype diversity but low nucleotide diversity, with 21 and 11 polymorphic sites for ND1 and COI, respectively. Mismatch distribution analysis and neutrality tests revealed that F. gigantica from different host species was in a state of population expansion. Maximum likelihood phylogenetic trees and median networks revealed that F. gigantica in Sudan and other African countries had host-specific and country-specific lineages for both genes. The study also indicated that F. gigantica -infected small ruminants were evolutionarily distant, suggesting deep and historical interspecies adaptation. Fasciola gigantica genetic diversity cattle sheep goats Sudan Figures Figure 1 Figure 2 Figure 3 1. Introduction The Platyhelminthes Fasciola hepatica and Fasciola gigantica , commonly known as liver flukes, are important parasites of both animals and humans as they cause fasciolosis [ 1 , 2 ]. Fasciola hepatica was first described by Linnaeus in 1758, while Fasciola gigantica was described by Cobbold in 1856. The former is widely distributed in temperate regions, while the latter is prevalent in tropical regions. However, in subtropical countries, the occurrence of both species overlaps [ 3 , 4 ]. An intermediate species of Fasciola between F. hepatica and F. gigantica has also been identified [ 5 ]. Mitochondrial genes cytochrome oxidase subunit I (COI) and NADH dehydrogenase subunit 1 (ND1) genes, as well as the nuclear ribosomal internal transcribed spacer 1 (ITS1), have been widely investigated to understand the genetic diversity of Fasciola spp. [ 6 – 9 ]. These genes have also been used to characterize the populations of F. hepatica and F. gigantica in relation to drug resistance [ 9 ]. The emergence of drug-resistant populations to triclabendazole, which is the drug of choice in the control of fasciolosis as it kills early immature and adult liver fluke, threatens the development of the livestock industry as well as human livelihoods [ 6 , 7 , 9 , 10 ]. Several studies have been conducted in various African countries to investigate the molecular characterization and genetic diversity of F. gigantica and F. hepatica , including Egypt [ 5 , 8 , 11 ], Ethiopia [ 12 ], Niger [ 13 ], Algeria [ 14 ], Tunisia [ 15 , 16 ], Morocco [ 17 ], Burkina Faso [ 18 ], Nigeria [ 19 ](Ichikawa-Seki et al. 2017), Kenya [ 19 ], Zambia [ 20 ], Mali [ 21 ], Tanzania [ 22 ], South Africa, and Zimbabwe [ 23 ]. However, there is currently no epidemiological data available on the genetic diversity of F. gigantica circulating in cattle, sheep, and goats in Sudan. Therefore, this study aims to examine the intra and interspecific variation and population dynamics of F. gigantica collected from ruminants in three states in Sudan by analyzing mitochondrial genes COI and ND1. This study also aims to compare the results with F. gigantica collected from other African countries to gain a better understanding of the genetic diversity of F. gigantica in the region. 2. Materials and methods 2.1 Samples collection and DNA extraction The study protocol was approved by the Faculty of Veterinary Medicine, University of Khartoum, in accordance with their guidelines for sampling domestic animals in Sudan. Forty-five adult F. gigantica specimens were collected during post-mortem examination of cattle, sheep, and goats slaughtered in six different locations across three states in Sudan. Specifically, we obtained 15 specimens from each animal species and from two slaughterhouses in two different localities within each state of Blue Nile (11.5860° N, 34.1532° E), White Nile (13.2404° N, 32.5373° E), and Sennar (13.0317° N, 33.9750° E). DNA was extracted from adult flukes identified morphologically, the flukes were transferred individually from fixation solution to sterile filter paper and left until complete evaporation of ethanol, then washed 3 times in distilled water and squashed before the genomic DNA was extracted. Approximately 10 mg tissue was removed from the portion of the lateral zone of the adult fluke and cut into small parts. DNA extraction was carried out using the commercial QIAamp DNA extraction Kit (Qiagen, INC) following manufacturer’s instructions. All the DNA samples were stored at -20°C until further use. 2.2 PCR and sequencing Molecular detection of F. gigantica mitochondrial COI and ND1 genes was done using primers described by [ 24 ] to amplify fragments of 438 bp and 535 bp for COI and ND1 genes, respectively. Polymerase chain reactions (PCRs) for both genes were conducted in a 10 µl reaction mixture containing 5.0 µl of 2× Gflex PCR Buffer (Mg 2+ , dNTP plus), 0.2 µl of Tks Gflex DNA Polymerase 1.25 units/ µl (TaKaRa Bio Inc., Shiga, Japan), 200 nM of each primer, 0.5 µl of template DNA and molecular grade water. The cycling conditions for both PCRs were set with initial denaturation at 94°C for 1 min, followed by 35 cycles of denaturation at 98°C for 10 sec, annealing at 55°C for 15 sec, extension at 68°C for 15 sec and final extension at 68°C for 5 min. The amplicons were electrophoresed in 1.5% agarose gel stained with Gel-Red (Biotium, Hayward, CA, USA) and visualized under UV light. The amplicons were purified using USB ExoSAP-IT Enzymatic PCR Clean-Up (Affymetrix Japan K.K., Tokyo Japan). Both forward and reverse primers were used to directly sequence all the purified amplicons using the Big Dye Terminator version 3.1 Cycle Sequencing Kit (Applied Biosystems, Foster City, CA, USA) utilizing an ABI Prism 3130x genetic analyser (Applied Biosystems) according to the manufacturers' instructions. 2.3 Sequence processing analysis Sanger sequences of COI and ND1 were analyzed using GENETYX version 9.1 (GENETYX Corporation, Tokyo, Japan) as described previously (Nakao et al., 2013). These were subsequently joined to reconstruct a fragment of 435 bp and 592 bp of COI and ND1 of 45 and 44 consensus sequences, respectively. Following the alignment of these consensus sequences against the F. gigantica reference sequence (NC_024025), the number of haplotypes were determined using DNASP v5 [ 25 ]. 2.5. Haplotype network and phylogenetic analysis A median joining haplotype network was constructed using PopArt software 1.7 ( https://popart.maths.otago.ac.nz ). Tijama’s D test, Fu’s F S statistics were calculated using DnaSP to explain haplotypes distances in the haplotype network. Unrooted neighbor joining phylogenetic tree was constructed using MEGA7 software and best substitution model for the sequences (Tamura-Nei model) was determined using the model test algorithm [ 26 ]. All haplotypes obtained in this study were submitted to the DNA Data Bank of Japan (DDBJ) ( http://www.ddbj.nig.ac.jp ) under accession numbers (COI gene: LC552612 - LC552621; ND1 gene: LC552622; - LC552636). To construct the median-joining network of Sudan F. gigantica haplotypes with the African F. gigantica sequences, COI and ND1 sequences from African countries were retrieved from the NCBI GenBank Database ( https://www.ncbi.nlm.nih.gov/nuccore/ ). Sequence accession numbers and related information on the country of isolation and host of collection are available in Supplementary File 1 (Tables S1 and S2). 2.4 Genetic variability, mismatch distribution and tests of neutrality Measures of genetic diversity (nucleotide and haplotype diversity and the mean number of nucleotide differences) and their standard deviations were calculated for the two genes datasets using ARLEQUIN v3.5 [ 27 ]. Furthermore, historical dynamics and demographic profiles were inferred from mismatch distribution patterns [ 28 ]. The chi-square test of goodness of fit and Harpending's raggedness index " r " [ 29 ] statistics were used to evaluate the significance of the deviations of the observed sum of squares differences ( SSD ) from the simulated model of expansion (demographic or spatial) following 1,000 coalescent simulations. Fu's Fs [ 30 ](Fu, 1997) and Tajima's D [ 31 ] statistics were also calculated using the infinite sites model in Arlequin v3.5 3. Results 3.1 Sequence variability and haplotype distribution pattern Alignment of the consensus sequences against the F. gigantica reference sequence (NC_024025) by [32], generated 21 and 11 polymorphic sites (18 and 8 transitions; 4 and 3; transversions, were observed, which defined 10 and 15 haplotypes based on COI and ND1 genes respectively (Tables 1 and 2). Similar level of haplotype and nucleotide diversity were observed in the two genes 1.000±0.045 and 1.000±0.024 and higher mean number of nucleotide differences in ND1 gene 4.429±2.314 than in COI gene 2.733±1.581. The two coalescent-based estimators of neutrality Tajima’ s D (D = -1.330 ( P = - 0.117); - 1.292 ( P =0.085) and Fu’s Fs = -8.799 ( P = 0.000); -12.974 ( P = 0.000) for COI and ND1 genes respectively, are both negative values and Fu’s Fs statistically significant, suggested a recent population. The mismatch distribution patterns for the overall dataset and for the two breeds were unimodal (Supplementary File 2, Figure S1). The observed distribution of mismatches did not deviate significantly from the one expected under a null hypothesis model of either spatial or demographic expansion (SSD = 0.027, P = 0.100; r = 0.132, P = 0.100 for COI; SSD = 0.005, P = 0.380; r = 0.027, P = 0.400 for NDI)). These results provide evidence of spatial and demographic expansions for the two breeds combined and for each breed, respectively. The AMOVA statistic for the COI gene in Sudan indicated that the majority of the genetic variation (90.0% of the total variation) was present within populations, with only 10.0% of the genetic variation distributed among populations. These results suggest a low level of genetic differentiation among the populations, and there was no significant genetic variation among groups. On the other hand, the AMOVA statistic for the ND1 gene in Sudan revealed a significant proportion of the genetic variation within populations (91.0% of the total variation), with the remaining 9.0% of the genetic variation distributed among populations. These findings suggest a considerable level of genetic differentiation among the populations. 3.2 Haplotype diversity in cytochrome c oxidase subunit I (COI) gene of Fasciola gigantica from Sudan The 10 haplotypes generated from 45 sequences, showed haplotype 1; 17(37.8%) was shared haplotype between cattle and goats followed by haplotype 2; 11(24.4%) and haplotype 3; 6(13.3%) shared among cattle sheep and goats and then haplotype 6 (4.4%) between sheep and goats. The rest five haplotypes were species-specific haplotypes (Table 1). On the other hand, the maximum likelihood phylogenetic tree showed four clusters of haplotypes. The primary cluster contained seven haplotypes, while two haplotypes were specific to sheep and goats (COI-Hap10 and COI-Hap5), and one shared haplotype (COI-Hap2) was found among cattle (N = 1 sequence), sheep (N = 8 sequences), and goats (N = 2 sequences). 3.3 Haplotype diversity in NADH dehydrogenase subunit 1 (ND1) gene of Fasciola gigantica from Sudan The 15 haplotypes generated from 44 sequences showed haplotype 1; 9(20.5%) and haplotype 2; 8(18.2%) shared among cattle, sheep, and goats followed by haplotype 3; 5(11.4%) and haplotype 5; 4(9.1%) shared between cattle and goats. One haplotype (ND1-Hap6) 3(6.82) is shared between sheep and goats. The rest 10 haplotypes were species-specific haplotypes (Table 1). The maximum likelihood phylogenetic tree identified three clusters of haplotypes. The primary cluster contained 12 haplotypes, and the second cluster contained three haplotypes (ND1-Hap 1; N = 9 sequences) found in cattle (N = 1 sequence), sheep (N = 6 sequences), and goats (N = 1 sequence). ND1-Hap12 goats (N = 1 sequence) were evolutionarily distant plus the reference sequence. The third cluster was specific to sheep (ND1-Hap7 sheep; N = 2 sequences) and was evolutionarily distant. 3.4 Relationship of F. gigantica haplotypes from Sudan with African countries based on the COI gene The analysis of the COI gene sequences of the African sequences of the COI gene based on country showed that the highest haplotype diversity in sequences from Mauritania (1.000±0.00391), while Algeria and Niger reported the lowest haplotype diversity with only two sequences that shared the same haplotypes according to the region of COI selected for the analysis. Sudan sequences showed high genetic diversity compared to Egypt and Burkina Faso but lower than Zambia, Nigeria, and Uganda. However, the neutrality tests showed only negative statistically significant values of Tajima’s D and Fu ’s Fs among sequences from Nigeria and Uganda (p-values 0.05). Based on the host of isolation, the highest haplotype diversity was observed among sequences isolated from Buffalo and goat (1.000±0.03125 and 1.000±0.01600, respectively). The lowest haplotype diversity was observed among sequences from deer (0.900±0.02592). The neutrality tests showed only significant negative values among sequences related to cattle host, Tajima’s D at -1.8336 and Fu’s Fs was -33.559 ( p-values < 0.05). Sequences from sheep hosts showed only a negatively significant Tajima’s D value (-1.8954, p-value < 0.05 (Table 3). The phylogenetic tree constructed using COI gene sequences revealed a main cluster with an 86% bootstrap value that included most of the African COI sequences. However, two other main clusters were identified, which consisted mostly of sequences from Zambia. This suggests a higher diversity of the Zambian sequences compared to the other African sequences, including those from Sudan. Additionally, two sequences related to the snail host from Egypt created a separate cluster with 100% bootstrap value (Supplementary File 2, Figure S2). The application of the AMOVA statistic to the COI gene of African F. gigantica isolates revealed that there was no significant variation among groups. However, considerable genetic variation was observed among populations, with a sum of squares of 2973.79 and a sigma^2 of 53.450. Within populations, the sum of squares was 5560.141, and the sigma^2 was 38.882. The fixation indices showed a Phi_SC of 0.57889, indicating genetic differentiation among the populations. Significance tests for all three fixation indices demonstrated that the observed values were statistically significant, with p-values less than 0.001 for all three tests. These findings suggest that although genetic variation exists among populations, there is no significant variation among groups in the COI gene of F. gigantica isolates in Africa. 3.5. Relationship of F. gigantica haplotypes from Sudan with African countries based on the ND1 gene Analysis of F. gigantica haplotypes in Africa based on the ND1 gene showed the presence of 72 haplotypes with a high haplotype diversity (0.9107±0.00019). However, when analyzed according to country of origin, Uganda had the highest number of 25 haplotypes with a haplotype diversity (0.837±0.00243) followed by Nigeria where 21 haplotypes (0.795±0.00289), while in Sudan, 8 haplotypes were detected (0.733±0.01548) according to a shorter 243 bp trimmed sequences and align correctly with the available African sequences. Tajima’s D and Fu’s Fs statistics were insignificant, p-values > 0.05, except Uganda which showed negative and statistically significant Tajima’s D and Fu’s Fs statistics -2.3818 and -31.219, respectively, p-values < 0.05. Nigeria showed only negatively significant Fu’s Fs statistics -16.102 with p-value < 0.05. The positively insignificant neutrality tests and the declined genetic diversity, with nucleotide diversity 0.03736 and 0.00576, respectively, in Sudan and Ghana suggest that both populations are old. Meanwhile, the neutrality tests were negatively insignificant for all host types except for the cattle, in which, Tajima’s D and Fu’s Fs were negatively significant at -1.8008 and -62.686, respectively, with p-values < 0.05. The negatively significant of the neutrality tests indicate that these populations are undergoing expansion following a bottleneck event (Table 4). When constructing the haplotype networks for the ND1 sequences based on the country and the host of isolation, the results were consistent with neutrality statistics. A main haplotype was detected in most countries including Zambia, Nigeria, Uganda, Burkina Faso, Ghana, Niger, and Zimbabwe. Most of sequences of Zambia diverged into several unique haplotypes similar to the haplotypes from Egypt, which clustered separately from most of the Africa countries but showed similarity to haplotypes from Nigeria and one haplotype from Sudan. For the isolates from Sudan, five sequences created five unique haplotypes, one of which was shared with haplotypes from Nigeria, and another one was shared with haplotypes from Burkina Faso, Nigeria, Algeria, Senegal, and Ghana (Figure 3A). However, based on the host, the haplotype network showed the dominance of haplotypes related to isolates from cattle, supporting the negatively significant neutrality tests. Meanwhile, the haplotypes of F. gigantica from Sudan isolated from sheep showed close relation to haplotypes from cattle and goats, with two unique haplotypes related to sheep and goat that diverged from the cattle isolates (Figure 3B). The phylogenetic tree constructed using ND1 gene sequences revealed a main cluster that included most of the African ND1 sequences. Similar to the COI phylogenetic tree, two main clusters were identified that were related to the Zambian sequences. This finding supports the level of diversity shown in the COI phylogenetic tree and highlights the divergence of the Zambian sequences from those of other African countries based on both the cox1 and nd1 genes (Supplementary File 2, Figure S3). AMOVA analysis of the ND1 gene of African F. gigantica isolates revealed no significant variation among groups, with a sum of squares of 0.000. However, a significant amount of genetic variation was observed among populations, with a sum of squares of 1005.208 and sigma^2 of 11.442. Within populations, the sum of squares was 3460.332, and the sigma^2 was 16.717. The fixation indices for the ND1 gene showed a Phi_SC of 0.40635, indicating genetic differentiation among the populations. The significance tests for all three fixation indices were statistically significant, with p-values less than 0.001 for all three tests. These findings suggest that the ND1 gene of F. gigantica isolates in Africa also exhibits genetic variation among populations, but not among groups, similar to the COI gene analysis. 4. Discussion Sudan is known for having one of the largest livestock production industries in Africa, with cattle, sheep, and goats being important sources of economic activity for both local and export markets. Animal fasciolosis, a parasitic disease caused by liver flukes, has been reported throughout the country [ 33 – 36 ], with cattle and sheep being the most commonly affected hosts. Despite the scattered reports and anecdotal nature of various reports of liver fluke infestations in Sudan, none of them have used molecular methods to analyze this neglected parasite. In this study, we successfully examined intra- and interspecies variations in the COI and ND1 genes of F. gigantica collected from various hosts and locations. The number of polymorphic sites was higher in ND1 than COI, with 10 and 15 haplotypes for COI and ND1 respectively. While some haplotypes were shown to be shared between cattle and small ruminants, interspecies variation showed a difference between F. gigantica infections in sheep and goats and those in cattle. A similar finding from Pakistan by [ 37 ] that used the same genetic markers ND1 and COI to demonstrate a significant genetic difference between F. gigantica from buffaloes and goats. More specifically, out of 15 F. gigantica samples from sheep that were examined, 11 were found to be distinct (COI-Hap2 and ND1-Hap1- with exception of one cattle sample shared in each), while one shared with goats (Hap 6) in both genes. However, the goats' haplotypes revealed that four of them were unique and one was shared with sheep as stated earlier. We also provide evidence that, as shown by the phylogenetic analysis, the haplotypes that infect small ruminants are evolutionarily distinct from those that infect cattle. The divergence is quite old since the two markers utilized known to reveal the ancient and deep evolutionary forces of the parasites. In another aspect of the analysis, we found that this parasite is experiencing population expansion, as revealed by the mismatch distribution analysis and tests of neutrality. An indication that the present and previous treatment methods are ineffective, which should warn veterinary authorities and animal owners. The analysis of F. gigantica haplotypes in Sudan and other African countries based on country of isolation revealed a diverse distribution of haplotypes and several unique haplogroups. This suggests that there is significant intra and interspecies variation in F. gigantica across different geographic regions. The distinct haplogroups observed in Zambian and Egyptian haplotypes compared to those from Nigeria may indicate evolutionary adaptation to environmental changes or an increase in host range. The high haplotype diversity and negative values of Tajima's D and Fu's Fs statistics observed in the Nigerian population support the hypothesis of population expansion [ 38 ]. These findings have important implications for the epidemiology and control of fascioliasis, as the genetic diversity observed in F. gigantica populations across different regions may affect their virulence, infectivity, and response to anthelmintic treatment. Additionally, the observed population expansion in Nigeria may result in increased transmission and spread of the disease. Therefore, further studies are needed to investigate the genetic diversity and population structure of F. gigantica populations in other endemic regions and to assess the potential impact of this diversity on the transmission and control of fascioliasis. The analysis of F. gigantica haplotypes from Sudan and other African countries based on the COI gene sequences revealed high genetic diversity in Sudan compared to some countries but lower than Zambia, Nigeria, and Uganda. The highest haplotype diversity was observed among sequences isolated from buffalo and goat hosts, while the lowest was observed among deer sequences. Neutrality tests showed significant negative values only among sequences related to cattle hosts. The phylogenetic tree constructed revealed a main cluster including most African COI sequences, two other main clusters mostly from Zambia, and a separate cluster of two sequences related to the snail host from Egypt. On the other hand, the analysis of F. gigantica haplotypes from Sudan and other African countries based on the ND1 gene showed high haplotype diversity in Africa with Uganda having the highest number of haplotypes, followed by Nigeria. Sudan had eight haplotypes with declined genetic diversity suggesting an older population. Neutrality tests indicate that the populations are undergoing expansion following a bottleneck event, and haplotype networks show dominance of haplotypes related to isolates from cattle. The phylogenetic tree shows a main cluster that includes most of the African ND1 sequences, with the Zambian sequences diverging from those of other African countries based on both the COI and ND1 genes. AMOVA results suggest that there is higher genetic variation within populations (intraspecies) compared to between populations (interspecies). This could be due to various factors such as genetic drift, gene flow, or local adaptation. Additionally, the results suggest that there is genetic differentiation among populations, which could indicate the presence of population substructure or local adaptation to different environmental conditions. The results also suggest that for the studied parasite populations, there is low genetic differentiation among populations within the same country or region (intra-country variation) and no significant genetic variation among groups from different countries or regions (inter-country variation). However, there is a significant level of genetic differentiation among populations within each country or region, indicating that the parasite populations have distinct genetic structures that are unique to each country or region. This suggests that factors such as host movements, environmental conditions, and host-parasite interactions may play a role in shaping the genetic diversity of the parasite populations within each country or region. In conclusion, this study advances our understanding of the intra and inter-species variation and phylogenetic relationships of F. gigantica , which circulates in naturally infected hosts across different geographic regions. The parasite was found to be quite diverse within and among animal hosts. Although metacercariae of Fasciola can infect different host species, regardless of the animal host isolate of origin, our phylogeny and network analyses revealed cross-infections among host species. However, the haplotype that infects small ruminants is genetically distinct from their cattle counterparts, which may have implications for treatment and control strategies. These findings have significant implications for the epidemiology and control of fascioliasis. Further research is required to investigate the genetic diversity and population structure of F. gigantica populations in other endemic areas. Declarations Acknowledgement We acknowledge the partial financial support from Japan Society for the Promotion of Science (JSPS) KAKENHI [22H02505] to the last author. Ethics approval and consent to participate The study protocol was reviewed and approved by Central Veterinary Research Laboratory, Khartoum, Sudan. We confirm that the study is conducted in accordance with ARRIVE guidelines (https://arriveguidelines.org) and with the guidelines for sampling domestic animals in Sudan, ensuring ethical compliance in the collection and use of the samples. Conflict of interests The authors declare no competing or financial interests. Author Contributions Conceptualization: [Kamal Ibrahim], [Bashir Salim]; Methodology: [Kamal Ibrahim], [ Bashir Salim], [Elisha Chatanga], [Nouh S. Mohamed], [Ryo Nakao]; Formal analysis and investigation: [Nouh S. Mohamed], [Bashir Salim]; Writing - original draft preparation: [Nouh S. Mohamed], [Bashir Salim], [Ayman Ahmed], [Saeed Alasmari], [Faisal Almathen]; Writing - review and editing: [Ayman Ahmed], [Saeed Alasmari], [Faisal Almathen]; Funding acquisition: [Kamal Ibrahim], [Ryo Nakao]; Resources: [Ryo Nakao]; Supervision: [Bashir Salim]. Funding The authors did not receive support from any organization for the submitted work. Availability of data and materials The sequences obtained were deposited to the DNA Data Bank of Japan (http://www.ddbj.nig.ac.jp) under accession number under accession numbers (COI gene: LC552612 - LC552621; ND1 gene: LC552622; - LC552636). References M.W. Robinson, J.P. 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Tables Table 1: Summary of Fasciola gigantica haplotypes from Sudan and their hosts range-on based analysis COI gene No. Haplotype Accession number Animal species (No. samples) Sample ID No. sequences 1 Hap1_LC552612 Cattle (10); Goat (7) Cattle [1,2,3,5,6,9,11,13,14,15] Goats [43,45,64,66,68,69,70] 17 2 Hap2_LC552613 Cattle (1); Goat (2); Sheep (8) Cattle [7] Goats [41,42,44] Sheep [83,85,86,88,89,90,93,95] 11 3 Hap3_LC552614 Cattle (1); Sheep (2); Goat (3) Cattle [7] Goats [41,42,44] Sheep [84,92] 6 4 Hap4_LC552615 Sheep Sheep [82,87,94] 3 5 Hap5_LC552616 Goat Goats [61,62] 2 6 Hap6_LC552617 Sheep (1); Goat (1) Goats [63] Sheep [91] 2 7 Hap7_LC552618 Cattle Cattle [8] 1 8 Hap8_LC552619 Cattle Cattle [10] 1 9 Hap9_LC552620 Cattle Cattle [12] 1 10 Hap10_LC552620 Sheep Sheep [81] 1 Total 45 Table 2: Summary of Fasciola gigantica haplotypes from Sudan and their hosts range-on based analysis ND1 gene No. Haplotype Accession number Animal species (No. samples) Sample ID No. sequences 1 LC552622 Cattle (1); Goat (2); Sheep (6) Cattle [4] Goats [65,67] Sheep [83,85,88,89,90,93] 9 2 LC552623 Cattle (3); Goat (3); Sheep (2) Cattle [7,11,12] Goats [41,42,44] Sheep [86,92] 8 3 LC552624 Cattle (2); Goat (3) Cattle [8,14] Goats [64,68,70] 5 4 LC552625 Cattle (4) Cattle [2,3,5,13] 4 5 LC552626 Cattle (3); Goat (1) Cattle [6,9,15] Goats [43] 4 6 LC552627 Goat (2); Sheep (1) Goats [63,66] Sheep [91] 3 7 LC552628 Sheep (2) Sheep [87,94] 2 8 LC552629 Goat (2) Goats [61,62] 2 9 LC552630 Cattle (1) Cattle [1] 1 10 LC552631 Cattle (1) Cattle [10] 1 11 LC552632 Goat (1) Goats [45] 1 12 LC552633 Goat (1) Goats [69] 1 13 LC552634 Sheep (1) Sheep [84] 1 14 LC552635 Sheep (1) Sheep [95] 1 15 LC552636 Sheep (1) Sheep [82] 1 Total 44 Table 3: Population genetics indices for the F. gigantica African countries based on COI gene sequences. n S Hap Hapd±STD Pi Tajima D Fu Fs Population Sudan 10 8 8 0.933±0.00597 0.00547 -1.0596 -4.819 Zambia 25 42 23 0.990±0.00026 0.03437 0.5749 -9.333 Egypt 13 38 9 0.872±0.00833 0.02755 -0.6443 0.340 Mauritania 8 27 8 1.000±0.00391 0.01941 -1.4407 -2.803 Nigeria 40 26 28 0.937±0.00099 0.00586 -2.282* -34.386* Uganda 38 27 31 0.982±0.00019 0.00672 -2.0362* -34.339* Algeria 2 0 1 0.000±0.00000 0.00000 n.d. n.d. Burkina Faso 4 2 2 0.500±0.07031 0.00256 -0.7099 1.099 Niger 2 0 1 0.000±0.00000 0.00000 n.d. n.d. Host Cattle 119 73 79 0.978±0.00004 0.01641 -1.8336* -33.559* Sheep 14 24 11 0.956±0.00200 0.01116 -1.8954* -4.477 Goat 5 6 5 1.000±0.01600 0.00718 -0.1909 -2.371 Deer 5 4 4 0.900±0.02592 0.00462 -0.4102 -1.195 Buffalo 4 37 4 1.000±0.03125 0.04744 -0.8642 1.029 Table 4: Population genetic indices for the F. gigantica from African countries based on ND1 gene sequences. n S Hap Hapd±STD Pi Tajima’s D Fu Fs Population Sudan 15 9 8 0.733±0.01548 0.00792 -1.1435 -3.225 Zambia 31 26 13 0.89±0.00119 0.03736 1.2234 0.871 Egypt 42 10 11 0.757±0.00328 0.00476 -1.4852 -6.400 Nigeria 51 19 21 0.795±0.00289 0.00851 -1.6112 -16.102* Uganda 53 23 25 0.837±0.00243 0.00570 -2.3818* -31.219* Ghana 6 3 3 0.733±0.02407 0.00576 0.3384 0.381 Burkina Faso 8 6 5 0.786±0.02274 0.00617 -1.6398 -1.802 Niger 3 1 2 0.667±0.09877 0.00274 n.d. 0.201 Host Cattle 165 55 64 0.884±0.00047 0.01791 -1.8008* -62.686* Sheep 29 10 8 0.793±0.00273 0.00906 -0.4316 -1.026 Goat 8 5 4 0.643±0.0339 0.00735 -0.3355 -0.073 Deer 4 2 3 0.833±0.04948 0.00412 -0.7099 -0.887 Buffalo 11 6 7 0.873±0.00794 0.00584 -1.2181 -4.054 Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.zip Cite Share Download PDF Status: Published Journal Publication published 01 May, 2024 Read the published version in Parasitology Research → Version 1 posted Editorial decision: Revision requested 22 Feb, 2024 Reviews received at journal 26 Jan, 2024 Reviewers agreed at journal 24 Jan, 2024 Reviewers invited by journal 23 Jan, 2024 Editor assigned by journal 15 Jan, 2024 Submission checks completed at journal 15 Jan, 2024 First submitted to journal 10 Jan, 2024 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. 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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-3849640","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":267303162,"identity":"8245844e-2296-413f-b6b8-7c9e382d5234","order_by":0,"name":"Kamal Ibrahim","email":"","orcid":"","institution":"Central Veterinary Research Laboratory, Khartoum, Sudan","correspondingAuthor":false,"prefix":"","firstName":"Kamal","middleName":"","lastName":"Ibrahim","suffix":""},{"id":267303163,"identity":"bc2119c5-c286-4838-97ad-6aaa38bb276f","order_by":1,"name":"Elisha Chatanga","email":"","orcid":"","institution":"Lilongwe University of Agriculture and Natural Resources","correspondingAuthor":false,"prefix":"","firstName":"Elisha","middleName":"","lastName":"Chatanga","suffix":""},{"id":267303164,"identity":"b74cade9-dee6-4b14-892a-3a4ed213fef2","order_by":2,"name":"Nouh S. Mohamed","email":"","orcid":"","institution":"Sirius Training and Research Center","correspondingAuthor":false,"prefix":"","firstName":"Nouh","middleName":"S.","lastName":"Mohamed","suffix":""},{"id":267303165,"identity":"ad3a996a-8d11-43e0-87fb-365e220dafcf","order_by":3,"name":"Ayman Ahmed","email":"","orcid":"","institution":"Institute of Endemic Diseases, University of Khartoum, Khartoum, Sudan","correspondingAuthor":false,"prefix":"","firstName":"Ayman","middleName":"","lastName":"Ahmed","suffix":""},{"id":267303166,"identity":"ed0ab694-1228-4273-b012-9551a3417adf","order_by":4,"name":"Saeed Alasmari","email":"","orcid":"","institution":"Najran University","correspondingAuthor":false,"prefix":"","firstName":"Saeed","middleName":"","lastName":"Alasmari","suffix":""},{"id":267303167,"identity":"db685e06-52cf-4aff-8d84-35427d950300","order_by":5,"name":"Faisal Almathen","email":"","orcid":"","institution":"King Faisal University","correspondingAuthor":false,"prefix":"","firstName":"Faisal","middleName":"","lastName":"Almathen","suffix":""},{"id":267303168,"identity":"5e26791d-8c38-4afc-b46a-9f2bc71bc567","order_by":6,"name":"Ryo Nakao","email":"","orcid":"","institution":"Laboratory of Parasitology, Graduate School of Infectious Diseases, Faculty of Veterinary Medicine, Hokkaido University, Kita-18, Nishi-9, Sapporo, Hokkaido 060-0818, Japan","correspondingAuthor":false,"prefix":"","firstName":"Ryo","middleName":"","lastName":"Nakao","suffix":""},{"id":267303169,"identity":"a4c9084d-b409-49dc-952e-aa77c76e9862","order_by":7,"name":"Bashir Salim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYBACAwYGNoYEIIOPmYHxAZDm4SNaCxszA7MBSAsbUVpAAEiySUAZ+IE5+/FnDx7uqZNnY+dOq/yaYyfDxsD88NENPFose3LMDRKeHTZsY+bddlt2WzLQYWzGxjn4HHYgh00i4cABRrAWyW3MQC08bNJ4tZx//gyopc4epKVYcls9EVpuJJgBtTAngrQwftx2mLAWyxlvQFoOJwO1bJZm3Hach42ZgF/M+dOfSf44UGfbz39248ef26rt+dmbHz7GpwUFMPOASWKVgwDjD1JUj4JRMApGwYgBACOuQfhfHVTSAAAAAElFTkSuQmCC","orcid":"","institution":"University of Khartoum","correspondingAuthor":true,"prefix":"","firstName":"Bashir","middleName":"","lastName":"Salim","suffix":""}],"badges":[],"createdAt":"2024-01-10 07:59:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3849640/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3849640/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00436-024-08201-5","type":"published","date":"2024-05-01T07:17:33+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":49883407,"identity":"2d31050b-752d-49ca-849a-ae0a379e69fe","added_by":"auto","created_at":"2024-01-19 16:48:42","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1009643,"visible":true,"origin":"","legend":"\u003cp\u003eMaximum likelihood phylogenetic trees of F. gigantica haplotypes from Sudan and their African counterparts based on COI and ND1 genes using the HKY model with 1000 bootstrap values. Reference \u003cem\u003eF. gigantica\u003c/em\u003e (NC 024025) and outgroup \u003cem\u003eSchistosoma mansoni\u003c/em\u003e (NC 002545) were used for the analysis. A) Evolutionary distance and relationships of 10 haplotypes derived from 45 COI gene sequences. Haplotypes 5 and 10 from goat and sheep (respectively) are evolutionarily distant. B) Evolutionary distance and relationships of 15 haplotypes generated from 45 ND1 gene sequences. Haplotypes 7 and 12 from goat and sheep (respectively) are also evolutionarily distant.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-3849640/v1/171baa20eba20f28191b70b0.png"},{"id":49883405,"identity":"1716b629-6b50-4c0b-bd68-acfee27d2e83","added_by":"auto","created_at":"2024-01-19 16:48:42","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1388888,"visible":true,"origin":"","legend":"\u003cp\u003eMedian joining network (MJN) showing the relationship of \u003cem\u003eF. gigantica\u003c/em\u003e haplotypes from Sudan with other African countries based on the COI gene. \u003cstrong\u003eA\u003c/strong\u003e) MJN based on animal hosts showing host-specific \u003cem\u003eF. gigantica\u003c/em\u003e lineages with cattle being the predominant host. Deer showing quite distant haplotype. \u003cstrong\u003eB\u003c/strong\u003e) MJN based on countries showing country-specific \u003cem\u003eF. gigantica\u003c/em\u003e lineages distribution. Unique haplotype is represented by circles, which are sized according to the frequency at which the haplotype was seen. Haplotype colors match the animal species in 2A and country of origin in 2B.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3849640/v1/f347378d5f61c9fe2a6f6097.png"},{"id":49883406,"identity":"503b6d21-5f09-4c5d-9f6b-32a0e5f49d47","added_by":"auto","created_at":"2024-01-19 16:48:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1281541,"visible":true,"origin":"","legend":"\u003cp\u003eMedian joining network (MJN) showing the relationship of \u003cem\u003eF. gigantica\u003c/em\u003e haplotypes from Sudan with other African countries based on the ND1 gene. \u003cstrong\u003eA\u003c/strong\u003e) MJN based on animal hosts showing host-specific \u003cem\u003eF. gigantica\u003c/em\u003e lineages with cattle being the predominant host. Deer from Zambia showing quite distant haplotype. \u003cstrong\u003eB\u003c/strong\u003e) MJN based on countries showing country-specific \u003cem\u003eF. gigantica\u003c/em\u003e lineages distribution. Unique haplotype is represented by circles, which are sized according to the frequency at which the haplotype was seen. Haplotype colors match the animal species in 2A and country of origin in 2B.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3849640/v1/138ad2e00d37dea3ea551acd.png"},{"id":57597672,"identity":"f704bdf7-70dc-4e8f-b276-49a2d4cdca22","added_by":"auto","created_at":"2024-06-03 07:17:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4827672,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3849640/v1/b2842df9-cb62-4a16-a3d7-132dd7a0315e.pdf"},{"id":49883408,"identity":"956e8f2d-f11a-4fd8-a384-3d3bacd34742","added_by":"auto","created_at":"2024-01-19 16:48:42","extension":"zip","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1678254,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.zip","url":"https://assets-eu.researchsquare.com/files/rs-3849640/v1/da3437528ccc5dfe381b00f0.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Intra and interspecies variation and population dynamics of Fasciola gigantica among ruminants in Sudan","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe Platyhelminthes \u003cem\u003eFasciola hepatica\u003c/em\u003e and \u003cem\u003eFasciola gigantica\u003c/em\u003e, commonly known as liver flukes, are important parasites of both animals and humans as they cause fasciolosis [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. \u003cem\u003eFasciola hepatica\u003c/em\u003e was first described by Linnaeus in 1758, while \u003cem\u003eFasciola gigantica\u003c/em\u003e was described by Cobbold in 1856. The former is widely distributed in temperate regions, while the latter is prevalent in tropical regions. However, in subtropical countries, the occurrence of both species overlaps [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. An intermediate species of \u003cem\u003eFasciola\u003c/em\u003e between \u003cem\u003eF. hepatica\u003c/em\u003e and \u003cem\u003eF. gigantica\u003c/em\u003e has also been identified [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMitochondrial genes cytochrome oxidase subunit I (COI) and NADH dehydrogenase subunit 1 (ND1) genes, as well as the nuclear ribosomal internal transcribed spacer 1 (ITS1), have been widely investigated to understand the genetic diversity of \u003cem\u003eFasciola\u003c/em\u003e spp. [\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These genes have also been used to characterize the populations of \u003cem\u003eF. hepatica and F. gigantica\u003c/em\u003e in relation to drug resistance [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The emergence of drug-resistant populations to triclabendazole, which is the drug of choice in the control of fasciolosis as it kills early immature and adult liver fluke, threatens the development of the livestock industry as well as human livelihoods [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral studies have been conducted in various African countries to investigate the molecular characterization and genetic diversity of \u003cem\u003eF. gigantica\u003c/em\u003e and \u003cem\u003eF. hepatica\u003c/em\u003e, including Egypt [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], Ethiopia [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], Niger [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], Algeria [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], Tunisia [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], Morocco [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], Burkina Faso [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], Nigeria [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e](Ichikawa-Seki et al. 2017), Kenya [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], Zambia [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], Mali [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], Tanzania [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], South Africa, and Zimbabwe [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, there is currently no epidemiological data available on the genetic diversity of \u003cem\u003eF. gigantica\u003c/em\u003e circulating in cattle, sheep, and goats in Sudan. Therefore, this study aims to examine the intra and interspecific variation and population dynamics of \u003cem\u003eF. gigantica\u003c/em\u003e collected from ruminants in three states in Sudan by analyzing mitochondrial genes COI and ND1. This study also aims to compare the results with \u003cem\u003eF. gigantica\u003c/em\u003e collected from other African countries to gain a better understanding of the genetic diversity of \u003cem\u003eF. gigantica\u003c/em\u003e in the region.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Samples collection and DNA extraction\u003c/h2\u003e \u003cp\u003e The study protocol was approved by the Faculty of Veterinary Medicine, University of Khartoum, in accordance with their guidelines for sampling domestic animals in Sudan. Forty-five adult \u003cem\u003eF. gigantica\u003c/em\u003e specimens were collected during post-mortem examination of cattle, sheep, and goats slaughtered in six different locations across three states in Sudan. Specifically, we obtained 15 specimens from each animal species and from two slaughterhouses in two different localities within each state of Blue Nile (11.5860\u0026deg; N, 34.1532\u0026deg; E), White Nile (13.2404\u0026deg; N, 32.5373\u0026deg; E), and Sennar (13.0317\u0026deg; N, 33.9750\u0026deg; E). DNA was extracted from adult flukes identified morphologically, the flukes were transferred individually from fixation solution to sterile filter paper and left until complete evaporation of ethanol, then washed 3 times in distilled water and squashed before the genomic DNA was extracted. Approximately 10 mg tissue was removed from the portion of the lateral zone of the adult fluke and cut into small parts. DNA extraction was carried out using the commercial QIAamp DNA extraction Kit (Qiagen, INC) following manufacturer\u0026rsquo;s instructions. All the DNA samples were stored at -20\u0026deg;C until further use.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 PCR and sequencing\u003c/h2\u003e \u003cp\u003eMolecular detection of \u003cem\u003eF. gigantica\u003c/em\u003e mitochondrial COI and ND1 genes was done using primers described by [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] to amplify fragments of 438 bp and 535 bp for COI and ND1 genes, respectively. Polymerase chain reactions (PCRs) for both genes were conducted in a 10 \u0026micro;l reaction mixture containing 5.0 \u0026micro;l of 2\u0026times; Gflex PCR Buffer (Mg\u003csup\u003e2+\u003c/sup\u003e, dNTP plus), 0.2 \u0026micro;l of Tks Gflex DNA Polymerase 1.25 units/ \u0026micro;l (TaKaRa Bio Inc., Shiga, Japan), 200 nM of each primer, 0.5 \u0026micro;l of template DNA and molecular grade water. The cycling conditions for both PCRs were set with initial denaturation at 94\u0026deg;C for 1 min, followed by 35 cycles of denaturation at 98\u0026deg;C for 10 sec, annealing at 55\u0026deg;C for 15 sec, extension at 68\u0026deg;C for 15 sec and final extension at 68\u0026deg;C for 5 min. The amplicons were electrophoresed in 1.5% agarose gel stained with Gel-Red (Biotium, Hayward, CA, USA) and visualized under UV light.\u003c/p\u003e \u003cp\u003eThe amplicons were purified using USB ExoSAP-IT Enzymatic PCR Clean-Up (Affymetrix Japan K.K., Tokyo Japan). Both forward and reverse primers were used to directly sequence all the purified amplicons using the Big Dye Terminator version 3.1 Cycle Sequencing Kit (Applied Biosystems, Foster City, CA, USA) utilizing an ABI Prism 3130x genetic analyser (Applied Biosystems) according to the manufacturers' instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Sequence processing analysis\u003c/h2\u003e \u003cp\u003eSanger sequences of COI and ND1 were analyzed using GENETYX version 9.1 (GENETYX Corporation, Tokyo, Japan) as described previously (Nakao et al., 2013). These were subsequently joined to reconstruct a fragment of 435 bp and 592 bp of COI and ND1 of 45 and 44 consensus sequences, respectively. Following the alignment of these consensus sequences against the \u003cem\u003eF. gigantica\u003c/em\u003e reference sequence (NC_024025), the number of haplotypes were determined using DNASP v5 [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Haplotype network and phylogenetic analysis\u003c/h2\u003e \u003cp\u003eA median joining haplotype network was constructed using PopArt software 1.7 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://popart.maths.otago.ac.nz\u003c/span\u003e\u003cspan address=\"https://popart.maths.otago.ac.nz\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Tijama\u0026rsquo;s \u003cem\u003eD\u003c/em\u003e test, Fu\u0026rsquo;s \u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003eS\u003c/em\u003e\u003c/sub\u003e statistics were calculated using DnaSP to explain haplotypes distances in the haplotype network. Unrooted neighbor joining phylogenetic tree was constructed using MEGA7 software and best substitution model for the sequences (Tamura-Nei model) was determined using the model test algorithm [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. All haplotypes obtained in this study were submitted to the DNA Data Bank of Japan (DDBJ) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ddbj.nig.ac.jp\u003c/span\u003e\u003cspan address=\"http://www.ddbj.nig.ac.jp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) under accession numbers (COI gene: LC552612 - LC552621; ND1 gene: LC552622; - LC552636).\u003c/p\u003e \u003cp\u003eTo construct the median-joining network of Sudan \u003cem\u003eF. gigantica\u003c/em\u003e haplotypes with the African \u003cem\u003eF. gigantica\u003c/em\u003e sequences, COI and ND1 sequences from African countries were retrieved from the NCBI GenBank Database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/nuccore/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/nuccore/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Sequence accession numbers and related information on the country of isolation and host of collection are available in Supplementary File 1 (Tables S1 and S2).\u003cb\u003e2.4 Genetic variability, mismatch distribution and tests of neutrality\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMeasures of genetic diversity (nucleotide and haplotype diversity and the mean number of nucleotide differences) and their standard deviations were calculated for the two genes datasets using ARLEQUIN v3.5 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Furthermore, historical dynamics and demographic profiles were inferred from mismatch distribution patterns [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The chi-square test of goodness of fit and Harpending's raggedness index \"\u003cem\u003er\u003c/em\u003e\" [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] statistics were used to evaluate the significance of the deviations of the observed sum of squares differences (\u003cem\u003eSSD\u003c/em\u003e) from the simulated model of expansion (demographic or spatial) following 1,000 coalescent simulations. Fu's \u003cem\u003eFs\u003c/em\u003e [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e](Fu, 1997) and Tajima's \u003cem\u003eD\u003c/em\u003e [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] statistics were also calculated using the infinite sites model in Arlequin v3.5\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Sequence variability and haplotype distribution pattern\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAlignment of the consensus sequences against the \u003cem\u003eF. gigantica\u0026nbsp;\u003c/em\u003ereference sequence (NC_024025) by [32], generated 21 and 11 polymorphic sites (18 and 8 transitions; 4 and 3; transversions, were observed, which defined 10 and 15 haplotypes based on COI and ND1 genes respectively (Tables 1 and 2). \u0026nbsp;Similar level of haplotype and nucleotide diversity were observed in the two genes 1.000\u0026plusmn;0.045 and 1.000\u0026plusmn;0.024 and higher mean number of nucleotide differences in ND1 gene 4.429\u0026plusmn;2.314 than in COI gene 2.733\u0026plusmn;1.581. The two coalescent-based estimators of neutrality Tajima\u0026rsquo;\u003cem\u003es D\u0026nbsp;\u003c/em\u003e(D = -1.330 (\u003cem\u003eP\u003c/em\u003e = - 0.117); - 1.292 (\u003cem\u003eP\u0026nbsp;\u003c/em\u003e=0.085) and Fu\u0026rsquo;s \u003cem\u003eFs\u003c/em\u003e = -8.799 (\u003cem\u003eP\u003c/em\u003e = 0.000); -12.974 (\u003cem\u003eP\u003c/em\u003e = 0.000) for COI and ND1 genes respectively, are both negative values and Fu\u0026rsquo;s \u003cem\u003eFs\u003c/em\u003e statistically significant, suggested a recent population. The mismatch distribution patterns for the overall dataset and for the two breeds were unimodal (Supplementary File 2, Figure S1). The observed distribution of mismatches did not deviate significantly from the one expected under a null hypothesis model of either spatial or demographic expansion (SSD = 0.027, P = 0.100; r = 0.132, P = 0.100 for COI; SSD = 0.005, P = 0.380; r = 0.027, P = 0.400 for NDI)). These results provide evidence of spatial and demographic expansions for the two breeds combined and for each breed, respectively.\u003c/p\u003e\n\u003cp\u003eThe AMOVA statistic for the COI gene in Sudan indicated that the majority of the genetic variation (90.0% of the total variation) was present within populations, with only 10.0% of the genetic variation distributed among populations. These results suggest a low level of genetic differentiation among the populations, and there was no significant genetic variation among groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOn the other hand, the AMOVA statistic for the ND1 gene in Sudan revealed a significant proportion of the genetic variation within populations (91.0% of the total variation), with the remaining 9.0% of the genetic variation distributed among populations. These findings suggest a considerable level of genetic differentiation among the populations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Haplotype diversity in cytochrome c oxidase subunit I (COI) gene of \u003cem\u003eFasciola gigantica\u0026nbsp;\u003c/em\u003efrom Sudan\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 10 haplotypes generated from 45 sequences, showed haplotype 1; 17(37.8%) was shared haplotype between cattle and goats followed by haplotype 2; 11(24.4%) and haplotype 3; 6(13.3%) shared among cattle sheep and goats and then haplotype 6 (4.4%) between sheep and goats. The rest five haplotypes were species-specific haplotypes (Table 1). On the other hand, the maximum likelihood phylogenetic tree showed four clusters of haplotypes. The primary cluster contained seven haplotypes, while two haplotypes were specific to sheep and goats (COI-Hap10 and COI-Hap5), and one shared haplotype (COI-Hap2) was found among cattle (N = 1 sequence), sheep (N = 8 sequences), and goats (N = 2 sequences).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Haplotype diversity in NADH dehydrogenase subunit 1 (ND1)\u003c/strong\u003e \u003cstrong\u003egene of \u003cem\u003eFasciola gigantica\u0026nbsp;\u003c/em\u003efrom Sudan\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe 15 haplotypes generated from 44 sequences showed haplotype 1; 9(20.5%) and haplotype 2; 8(18.2%) shared among cattle, sheep, and goats followed by haplotype 3; 5(11.4%) and haplotype 5; 4(9.1%) shared between cattle and goats. One haplotype (ND1-Hap6) 3(6.82) is shared between sheep and goats. The rest 10 haplotypes were species-specific haplotypes (Table 1). The maximum likelihood phylogenetic tree identified three clusters of haplotypes. The primary cluster contained 12 haplotypes, and the second cluster contained three haplotypes (ND1-Hap 1; N = 9 sequences) found in cattle (N = 1 sequence), sheep (N = 6 sequences), and goats (N = 1 sequence). ND1-Hap12 goats (N = 1 sequence) were evolutionarily distant plus the reference sequence. The third cluster was specific to sheep (ND1-Hap7 sheep; N = 2 sequences) and was evolutionarily distant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Relationship of \u003cem\u003eF. gigantica\u003c/em\u003e haplotypes from Sudan with African countries based on the COI gene\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis of the COI gene sequences of the African sequences of the COI gene based on country showed that the highest haplotype diversity in sequences from Mauritania (1.000\u0026plusmn;0.00391), while Algeria and Niger reported the lowest haplotype diversity with only two sequences that shared the same haplotypes according to the region of COI selected for the analysis. Sudan sequences showed high genetic diversity compared to Egypt and Burkina Faso but lower than Zambia, Nigeria, and Uganda. However, the neutrality tests showed only negative statistically significant values of Tajima\u0026rsquo;s\u003cem\u003e\u0026nbsp;D\u0026nbsp;\u003c/em\u003eand Fu\u003cem\u003e\u0026rsquo;s Fs\u0026nbsp;\u003c/em\u003eamong sequences from Nigeria and Uganda (p-values \u0026lt; 0.05), whereas both neutrality tests were negative in Sudan but did not show statistically significant (p-value \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Based on the host of isolation, the highest haplotype diversity was observed among sequences isolated from Buffalo and goat (1.000\u0026plusmn;0.03125 and 1.000\u0026plusmn;0.01600, respectively). The lowest haplotype diversity was observed among sequences from deer (0.900\u0026plusmn;0.02592). The neutrality tests showed only significant negative values among sequences related to cattle host, Tajima\u0026rsquo;s\u003cem\u003e\u0026nbsp;D\u0026nbsp;\u003c/em\u003eat -1.8336 and Fu\u0026rsquo;s\u003cem\u003e\u0026nbsp;Fs\u0026nbsp;\u003c/em\u003ewas -33.559 (\u003cem\u003ep-values\u003c/em\u003e \u0026lt; 0.05). Sequences from sheep hosts showed only a negatively significant Tajima\u0026rsquo;s\u003cem\u003e\u0026nbsp;D\u0026nbsp;\u003c/em\u003evalue (-1.8954, \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.05 (Table 3).\u003c/p\u003e\n\u003cp\u003eThe phylogenetic tree constructed using COI gene sequences revealed a main cluster with an 86% bootstrap value that included most of the African COI sequences. However, two other main clusters were identified, which consisted mostly of sequences from Zambia. This suggests a higher diversity of the Zambian sequences compared to the other African sequences, including those from Sudan. Additionally, two sequences related to the snail host from Egypt created a separate cluster with 100% bootstrap value (Supplementary File 2, Figure S2).\u003c/p\u003e\n\u003cp\u003eThe application of the AMOVA statistic to the COI gene of African \u003cem\u003eF. gigantica\u003c/em\u003e isolates revealed that there was no significant variation among groups. However, considerable genetic variation was observed among populations, with a sum of squares of 2973.79 and a sigma^2 of 53.450. Within populations, the sum of squares was 5560.141, and the sigma^2 was 38.882. The fixation indices showed a Phi_SC of 0.57889, indicating genetic differentiation among the populations. Significance tests for all three fixation indices demonstrated that the observed values were statistically significant, with p-values less than 0.001 for all three tests. These findings suggest that although genetic variation exists among populations, there is no significant variation among groups in the COI gene of \u003cem\u003eF. gigantica\u003c/em\u003e isolates in Africa.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5. Relationship of \u003cem\u003eF. gigantica\u003c/em\u003e haplotypes from Sudan with African countries based on the ND1 gene\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of \u003cem\u003eF. gigantica\u0026nbsp;\u003c/em\u003ehaplotypes in Africa based on the ND1 gene showed the presence of 72 haplotypes with a high haplotype diversity (0.9107\u0026plusmn;0.00019). \u0026nbsp;However, when analyzed according to country of origin, Uganda had the highest number of 25\u0026nbsp;haplotypes with a haplotype diversity (0.837\u0026plusmn;0.00243) followed by Nigeria where 21 haplotypes (0.795\u0026plusmn;0.00289), while in Sudan, 8 haplotypes were detected (0.733\u0026plusmn;0.01548) according to a shorter 243 bp trimmed sequences and align correctly with the available African sequences.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTajima\u0026rsquo;s\u003cem\u003e\u0026nbsp;D\u0026nbsp;\u003c/em\u003eand Fu\u0026rsquo;s\u003cem\u003e\u0026nbsp;Fs\u0026nbsp;\u003c/em\u003estatistics were insignificant, \u003cem\u003ep-values\u003c/em\u003e \u0026gt; 0.05, except Uganda which showed negative and statistically significant Tajima\u0026rsquo;s\u003cem\u003e\u0026nbsp;D\u0026nbsp;\u003c/em\u003eand Fu\u0026rsquo;s\u003cem\u003e\u0026nbsp;Fs\u0026nbsp;\u003c/em\u003estatistics -2.3818 and -31.219, respectively, \u003cem\u003ep-values\u003c/em\u003e \u0026lt; 0.05. Nigeria showed only negatively significant Fu\u0026rsquo;s\u003cem\u003e\u0026nbsp;Fs\u0026nbsp;\u003c/em\u003estatistics -16.102 with \u003cem\u003ep-value\u003c/em\u003e \u0026lt; 0.05. The positively insignificant neutrality tests and the declined genetic diversity, with nucleotide diversity 0.03736 and 0.00576, respectively, in Sudan and Ghana suggest that both populations are old. Meanwhile, the neutrality tests were negatively insignificant for all host types except for the cattle, in which, Tajima\u0026rsquo;s\u003cem\u003e\u0026nbsp;D\u0026nbsp;\u003c/em\u003eand Fu\u0026rsquo;s\u003cem\u003e\u0026nbsp;Fs\u0026nbsp;\u003c/em\u003ewere negatively significant at -1.8008 and -62.686, respectively, with \u003cem\u003ep-values\u003c/em\u003e \u0026lt; 0.05. The negatively significant of the neutrality tests indicate that these populations are undergoing expansion following a bottleneck event (Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen constructing the haplotype networks for the ND1 sequences based on the country and the host of isolation, the results were consistent with neutrality statistics. A main haplotype was detected in most countries including Zambia, Nigeria, Uganda, Burkina Faso, Ghana, Niger, and Zimbabwe. Most of sequences of Zambia diverged into several unique haplotypes similar to the haplotypes from Egypt, which clustered separately from most of the Africa countries but showed similarity to haplotypes from Nigeria and one haplotype from Sudan. For the isolates from Sudan, five sequences created five unique haplotypes, one of which was shared with haplotypes from Nigeria, and another one was shared with haplotypes from Burkina Faso, Nigeria, Algeria, Senegal, and Ghana (Figure 3A). However, based on the host, the haplotype network showed the dominance of haplotypes related to isolates from cattle, supporting the negatively significant neutrality tests. Meanwhile, the haplotypes of \u003cem\u003eF. gigantica\u0026nbsp;\u003c/em\u003efrom Sudan isolated from sheep showed close relation to haplotypes from cattle and goats, with two unique haplotypes related to sheep and goat that diverged from the cattle isolates (Figure 3B). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe phylogenetic tree constructed using ND1 gene sequences revealed a main cluster that included most of the African ND1 sequences. Similar to the COI phylogenetic tree, two main clusters were identified that were related to the Zambian sequences. This finding supports the level of diversity shown in the COI phylogenetic tree and highlights the divergence of the Zambian sequences from those of other African countries based on both the cox1 and nd1 genes (Supplementary File 2, Figure S3). AMOVA analysis of the ND1 gene of African \u003cem\u003eF. gigantica\u003c/em\u003e isolates revealed no significant variation among groups, with a sum of squares of 0.000. However, a significant amount of genetic variation was observed among populations, with a sum of squares of 1005.208 and sigma^2 of 11.442. Within populations, the sum of squares was 3460.332, and the sigma^2 was 16.717. The fixation indices for the ND1 gene showed a Phi_SC of 0.40635, indicating genetic differentiation among the populations. The significance tests for all three fixation indices were statistically significant, with p-values less than 0.001 for all three tests. These findings suggest that the ND1 gene of \u003cem\u003eF. gigantica\u003c/em\u003e isolates in Africa also exhibits genetic variation among populations, but not among groups, similar to the COI gene analysis.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eSudan is known for having one of the largest livestock production industries in Africa, with cattle, sheep, and goats being important sources of economic activity for both local and export markets. Animal fasciolosis, a parasitic disease caused by liver flukes, has been reported throughout the country [\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], with cattle and sheep being the most commonly affected hosts. Despite the scattered reports and anecdotal nature of various reports of liver fluke infestations in Sudan, none of them have used molecular methods to analyze this neglected parasite.\u003c/p\u003e \u003cp\u003eIn this study, we successfully examined intra- and interspecies variations in the COI and ND1 genes of \u003cem\u003eF. gigantica\u003c/em\u003e collected from various hosts and locations. The number of polymorphic sites was higher in ND1 than COI, with 10 and 15 haplotypes for COI and ND1 respectively. While some haplotypes were shown to be shared between cattle and small ruminants, interspecies variation showed a difference between \u003cem\u003eF. gigantica\u003c/em\u003e infections in sheep and goats and those in cattle. A similar finding from Pakistan by [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] that used the same genetic markers ND1 and COI to demonstrate a significant genetic difference between \u003cem\u003eF. gigantica\u003c/em\u003e from buffaloes and goats. More specifically, out of 15 \u003cem\u003eF. gigantica\u003c/em\u003e samples from sheep that were examined, 11 were found to be distinct (COI-Hap2 and ND1-Hap1- with exception of one cattle sample shared in each), while one shared with goats (Hap 6) in both genes. However, the goats' haplotypes revealed that four of them were unique and one was shared with sheep as stated earlier. We also provide evidence that, as shown by the phylogenetic analysis, the haplotypes that infect small ruminants are evolutionarily distinct from those that infect cattle. The divergence is quite old since the two markers utilized known to reveal the ancient and deep evolutionary forces of the parasites. In another aspect of the analysis, we found that this parasite is experiencing population expansion, as revealed by the mismatch distribution analysis and tests of neutrality. An indication that the present and previous treatment methods are ineffective, which should warn veterinary authorities and animal owners.\u003c/p\u003e \u003cp\u003eThe analysis of \u003cem\u003eF. gigantica\u003c/em\u003e haplotypes in Sudan and other African countries based on country of isolation revealed a diverse distribution of haplotypes and several unique haplogroups. This suggests that there is significant intra and interspecies variation in \u003cem\u003eF. gigantica\u003c/em\u003e across different geographic regions. The distinct haplogroups observed in Zambian and Egyptian haplotypes compared to those from Nigeria may indicate evolutionary adaptation to environmental changes or an increase in host range. The high haplotype diversity and negative values of Tajima's \u003cem\u003eD\u003c/em\u003e and Fu's \u003cem\u003eFs\u003c/em\u003e statistics observed in the Nigerian population support the hypothesis of population expansion [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. These findings have important implications for the epidemiology and control of fascioliasis, as the genetic diversity observed in \u003cem\u003eF. gigantica\u003c/em\u003e populations across different regions may affect their virulence, infectivity, and response to anthelmintic treatment. Additionally, the observed population expansion in Nigeria may result in increased transmission and spread of the disease. Therefore, further studies are needed to investigate the genetic diversity and population structure of \u003cem\u003eF. gigantica\u003c/em\u003e populations in other endemic regions and to assess the potential impact of this diversity on the transmission and control of fascioliasis.\u003c/p\u003e \u003cp\u003eThe analysis of F. gigantica haplotypes from Sudan and other African countries based on the COI gene sequences revealed high genetic diversity in Sudan compared to some countries but lower than Zambia, Nigeria, and Uganda. The highest haplotype diversity was observed among sequences isolated from buffalo and goat hosts, while the lowest was observed among deer sequences. Neutrality tests showed significant negative values only among sequences related to cattle hosts. The phylogenetic tree constructed revealed a main cluster including most African COI sequences, two other main clusters mostly from Zambia, and a separate cluster of two sequences related to the snail host from Egypt. On the other hand, the analysis of F. gigantica haplotypes from Sudan and other African countries based on the ND1 gene showed high haplotype diversity in Africa with Uganda having the highest number of haplotypes, followed by Nigeria. Sudan had eight haplotypes with declined genetic diversity suggesting an older population. Neutrality tests indicate that the populations are undergoing expansion following a bottleneck event, and haplotype networks show dominance of haplotypes related to isolates from cattle. The phylogenetic tree shows a main cluster that includes most of the African ND1 sequences, with the Zambian sequences diverging from those of other African countries based on both the COI and ND1 genes.\u003c/p\u003e \u003cp\u003eAMOVA results suggest that there is higher genetic variation within populations (intraspecies) compared to between populations (interspecies). This could be due to various factors such as genetic drift, gene flow, or local adaptation. Additionally, the results suggest that there is genetic differentiation among populations, which could indicate the presence of population substructure or local adaptation to different environmental conditions. The results also suggest that for the studied parasite populations, there is low genetic differentiation among populations within the same country or region (intra-country variation) and no significant genetic variation among groups from different countries or regions (inter-country variation). However, there is a significant level of genetic differentiation among populations within each country or region, indicating that the parasite populations have distinct genetic structures that are unique to each country or region. This suggests that factors such as host movements, environmental conditions, and host-parasite interactions may play a role in shaping the genetic diversity of the parasite populations within each country or region.\u003c/p\u003e \u003cp\u003eIn conclusion, this study advances our understanding of the intra and inter-species variation and phylogenetic relationships of \u003cem\u003eF. gigantica\u003c/em\u003e, which circulates in naturally infected hosts across different geographic regions. The parasite was found to be quite diverse within and among animal hosts. Although metacercariae of Fasciola can infect different host species, regardless of the animal host isolate of origin, our phylogeny and network analyses revealed cross-infections among host species. However, the haplotype that infects small ruminants is genetically distinct from their cattle counterparts, which may have implications for treatment and control strategies. These findings have significant implications for the epidemiology and control of fascioliasis. Further research is required to investigate the genetic diversity and population structure of \u003cem\u003eF. gigantica\u003c/em\u003e populations in other endemic areas.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eWe acknowledge the partial financial support from Japan Society for the Promotion of Science (JSPS) KAKENHI [22H02505] to the last author. \u0026nbsp;\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eEthics approval and consent to participate \u0026nbsp;\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe study protocol was reviewed and approved by Central Veterinary Research Laboratory, Khartoum, Sudan. We confirm that the study is conducted in accordance with ARRIVE guidelines (https://arriveguidelines.org) and with the guidelines for sampling domestic animals in Sudan, ensuring ethical compliance in the collection and use of the samples.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eConflict of interests\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe authors declare no competing or financial interests.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eConceptualization: [Kamal Ibrahim], [Bashir Salim]; Methodology: [Kamal Ibrahim], [ Bashir Salim], [Elisha Chatanga], [Nouh S. Mohamed], [Ryo Nakao]; Formal analysis and investigation: [Nouh S. Mohamed], [Bashir Salim]; Writing - original draft preparation: [Nouh S. Mohamed], [Bashir Salim], [Ayman Ahmed], \u003csup\u003e\u0026nbsp;\u003c/sup\u003e[Saeed Alasmari], [Faisal Almathen]; Writing - review and editing: [Ayman Ahmed], \u003csup\u003e\u0026nbsp;\u003c/sup\u003e[Saeed Alasmari], [Faisal Almathen]; Funding acquisition: [Kamal Ibrahim], [Ryo Nakao]; Resources: [Ryo Nakao]; Supervision: [Bashir Salim].\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe authors did not receive support from any organization for the submitted work.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThe sequences obtained were deposited to the DNA Data Bank of Japan (http://www.ddbj.nig.ac.jp) under accession number under accession numbers (COI gene: LC552612 - LC552621; ND1 gene: LC552622; - LC552636).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eM.W. 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Gameel, Studies on naturally-occurring ovine fascioliasis in the Sudan, Journal of Helminthology. 60 (1986) 47\u0026ndash;53.\u003c/li\u003e\n\u003cli\u003eW. Koko, H. Abdalla, M. Galal, Caprine fascioliasis in the Gezira State, Central Sudan, J. Anim. Vet. Adv. 2 (2003) 396\u0026ndash;399.\u003c/li\u003e\n\u003cli\u003eA.E. Babiker, A. Osman, A. Azza, Y. Elmansory, A. Majid, Efficacy of Oxyclozanide against Fasciola gigantica Infection in sheep under Sudan condition, Sudan J Vet Res. 27 (2012) 43\u0026ndash;7.\u003c/li\u003e\n\u003cli\u003eZ.U. Rehman, A. Tashibu, M. Tashiro, I. Rashid, Q. Ali, O. Zahid, K. Ashraf, W. Shehzad, U. Chaudhry, M. Ichikawa-Seki, Molecular characterization and phylogenetic analyses of Fasciola gigantica of buffaloes and goats in Punjab, Pakistan, Parasitology International. 82 (2021) 102288.\u003c/li\u003e\n\u003cli\u003eM. Ichikawa-Seki, M. Tokashiki, M.N. Opara, G. Iroh, K. Hayashi, U.M. Kumar, T. Itagaki, Molecular characterization and phylogenetic analysis of Fasciola gigantica from Nigeria, Parasitology International. 66 (2017) 893\u0026ndash;897.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1:\u0026nbsp;\u003c/strong\u003eSummary of \u003cem\u003eFasciola gigantica\u003c/em\u003e haplotypes from Sudan and their hosts range-on based analysis COI gene\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"696\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. Haplotype\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccession number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnimal species (No. samples)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. sequences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003eHap1_LC552612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eCattle (10); Goat (7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [1,2,3,5,6,9,11,13,14,15]\u003c/p\u003e\n \u003cp\u003eGoats [43,45,64,66,68,69,70]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003eHap2_LC552613\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eCattle (1); Goat (2); Sheep (8)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [7]\u003c/p\u003e\n \u003cp\u003eGoats [41,42,44]\u003c/p\u003e\n \u003cp\u003eSheep [83,85,86,88,89,90,93,95]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003eHap3_LC552614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eCattle (1); Sheep (2); Goat (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [7]\u003c/p\u003e\n \u003cp\u003eGoats [41,42,44]\u003c/p\u003e\n \u003cp\u003eSheep [84,92]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003eHap4_LC552615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eSheep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003eSheep [82,87,94]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003eHap5_LC552616\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eGoat\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003eGoats [61,62]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003eHap6_LC552617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eSheep (1); Goat (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003eGoats [63]\u003c/p\u003e\n \u003cp\u003eSheep [91]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003eHap7_LC552618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eCattle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003eHap8_LC552619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eCattle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003eHap9_LC552620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eCattle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003eHap10_LC552620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eSheep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003eSheep [81]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"13.649425287356323%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.25287356321839%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.270114942528735%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.758620689655174%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.068965517241379%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e45\u003c/strong\u003e\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\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eSummary of \u003cem\u003eFasciola gigantica\u003c/em\u003e haplotypes from Sudan and their hosts range-on based analysis ND1 gene\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"696\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. Haplotype\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccession number\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnimal species (No. samples)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. sequences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552622\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eCattle (1); \u0026nbsp; \u0026nbsp; Goat (2); Sheep (6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [4]\u003c/p\u003e\n \u003cp\u003eGoats [65,67]\u003c/p\u003e\n \u003cp\u003eSheep [83,85,88,89,90,93]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552623\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eCattle (3); Goat (3); Sheep (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [7,11,12]\u003c/p\u003e\n \u003cp\u003eGoats [41,42,44]\u003c/p\u003e\n \u003cp\u003eSheep [86,92]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eCattle (2); Goat (3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [8,14]\u003c/p\u003e\n \u003cp\u003eGoats [64,68,70]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552625\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eCattle (4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [2,3,5,13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eCattle (3); Goat (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [6,9,15]\u003c/p\u003e\n \u003cp\u003eGoats [43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552627\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eGoat (2); Sheep (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eGoats [63,66]\u003c/p\u003e\n \u003cp\u003eSheep [91]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552628\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eSheep (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eSheep [87,94]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552629\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eGoat (2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eGoats [61,62]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552630\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eCattle (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eCattle (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eCattle [10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eGoat (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eGoats [45]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eGoat (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eGoats [69]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eSheep (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eSheep [84]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eSheep (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eSheep [95]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003eLC552636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003eSheep (1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003eSheep [82]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.91248206599713%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.49067431850789%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"32.998565279770446%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.83357245337159%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.764705882352942%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e44\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003ePopulation genetics indices for the \u003cem\u003eF. gigantica\u003c/em\u003e African countries based on COI gene sequences.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHap\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHapd\u0026plusmn;STD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTajima \u003cem\u003eD\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFu \u003cem\u003eFs\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePopulation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eSudan \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e0.933\u0026plusmn;0.00597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.00547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e-1.0596\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e-4.819\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eZambia \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e0.990\u0026plusmn;0.00026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.03437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e0.5749\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e-9.333\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eEgypt \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e0.872\u0026plusmn;0.00833\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.02755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e-0.6443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eMauritania \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u0026plusmn;0.00391\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.01941\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e-1.4407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e-2.803\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eNigeria \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e0.937\u0026plusmn;0.00099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.00586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e-2.282*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e-34.386*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eUganda \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e0.982\u0026plusmn;0.00019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.00672\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e-2.0362*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e-34.339*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eAlgeria \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u0026plusmn;0.00000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.00000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eBurkina Faso \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e0.500\u0026plusmn;0.07031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.00256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e-0.7099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e1.099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eNiger \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e0.000\u0026plusmn;0.00000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.00000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHost\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eCattle \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e0.978\u0026plusmn;0.00004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.01641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e-1.8336*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e-33.559*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eSheep \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e0.956\u0026plusmn;0.00200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.01116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e-1.8954*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e-4.477\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eGoat \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u0026plusmn;0.01600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.00718\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e-0.1909\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e-2.371\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eDeer \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e0.900\u0026plusmn;0.02592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.00462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e-0.4102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e-1.195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.330578512396695%\" valign=\"top\"\u003e\n \u003cp\u003eBuffalo \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.9421487603305785%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.107438016528926%\" valign=\"top\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.768595041322314%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.677685950413224%\" valign=\"top\"\u003e\n \u003cp\u003e1.000\u0026plusmn;0.03125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e0.04744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.049586776859504%\" valign=\"top\"\u003e\n \u003cp\u003e-0.8642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.561983471074381%\" valign=\"top\"\u003e\n \u003cp\u003e1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u0026nbsp;\u003c/strong\u003ePopulation genetic indices for the \u003cem\u003eF. gigantica\u003c/em\u003e from African countries based on ND1 gene sequences.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.851500789889414%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"7.424960505529226%\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.424960505529226%\"\u003e\n \u003cp\u003e\u003cstrong\u003eS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.004739336492891%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHap\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.43127962085308%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHapd\u0026plusmn;STD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.006319115323855%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.428120063191153%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTajima\u0026rsquo;s \u003cem\u003eD\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.428120063191153%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFu \u003cem\u003eFs\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.851500789889414%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePopulation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.424960505529226%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.424960505529226%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.004739336492891%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.43127962085308%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.006319115323855%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.428120063191153%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.428120063191153%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.851500789889414%\" valign=\"top\"\u003e\n \u003cp\u003eSudan \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n 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width=\"13.428120063191153%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.428120063191153%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"17.851500789889414%\"\u003e\n \u003cp\u003eCattle \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.424960505529226%\"\u003e\n \u003cp\u003e165\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.424960505529226%\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.004739336492891%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.43127962085308%\"\u003e\n \u003cp\u003e0.884\u0026plusmn;0.00047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.006319115323855%\"\u003e\n \u003cp\u003e0.01791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.428120063191153%\"\u003e\n \u003cp\u003e-1.8008*\u003c/p\u003e\n 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\u003c/tbody\u003e\n\u003c/table\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"parasitology-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pare","sideBox":"Learn more about [Parasitology Research](http://link.springer.com/journal/436)","snPcode":"436","submissionUrl":"https://submission.nature.com/new-submission/436/3","title":"Parasitology Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Fasciola gigantica, genetic diversity, cattle, sheep, goats, Sudan","lastPublishedDoi":"10.21203/rs.3.rs-3849640/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3849640/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eFasciola gigantica\u003c/em\u003e is a widespread parasite that causes neglected diseases in livestock worldwide. Its high transmissibility and dispersion are attributed to its ability to infect intermediate snail hosts and adapt to various mammalian definitive hosts. This study investigated the variation and population dynamics of \u003cem\u003eF. gigantica\u003c/em\u003e in cattle, sheep, and goats from three states in Sudan. Mitochondrial cytochrome c oxidase subunit I (COI) and NADH dehydrogenase subunit 1 (ND1) genes were sequenced successfully to examine intra and inter-specific differences. ND1 exhibited higher diversity than COI, with 15 haplotypes and 10 haplotypes, respectively. Both genes had high haplotype diversity but low nucleotide diversity, with 21 and 11 polymorphic sites for ND1 and COI, respectively. Mismatch distribution analysis and neutrality tests revealed that \u003cem\u003eF. gigantica\u003c/em\u003e from different host species was in a state of population expansion. Maximum likelihood phylogenetic trees and median networks revealed that \u003cem\u003eF. gigantica\u003c/em\u003e in Sudan and other African countries had host-specific and country-specific lineages for both genes. The study also indicated that \u003cem\u003eF. gigantica\u003c/em\u003e-infected small ruminants were evolutionarily distant, suggesting deep and historical interspecies adaptation.\u003c/p\u003e","manuscriptTitle":"Intra and interspecies variation and population dynamics of Fasciola gigantica among ruminants in Sudan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-19 16:48:37","doi":"10.21203/rs.3.rs-3849640/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-02-22T09:36:17+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-01-26T09:56:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54b2a721-8b2b-4989-9e15-1207bd1aea84","date":"2024-01-24T09:06:51+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-01-23T07:04:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-01-16T02:34:27+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-01-16T02:30:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Parasitology Research","date":"2024-01-10T07:46:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"parasitology-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pare","sideBox":"Learn more about [Parasitology Research](http://link.springer.com/journal/436)","snPcode":"436","submissionUrl":"https://submission.nature.com/new-submission/436/3","title":"Parasitology Research","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"752e6cf5-20fc-4483-8ddd-f27995ed9bbe","owner":[],"postedDate":"January 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-06-03T07:17:33+00:00","versionOfRecord":{"articleIdentity":"rs-3849640","link":"https://doi.org/10.1007/s00436-024-08201-5","journal":{"identity":"parasitology-research","isVorOnly":false,"title":"Parasitology Research"},"publishedOn":"2024-05-01 07:17:33","publishedOnDateReadable":"May 1st, 2024"},"versionCreatedAt":"2024-01-19 16:48:37","video":"","vorDoi":"10.1007/s00436-024-08201-5","vorDoiUrl":"https://doi.org/10.1007/s00436-024-08201-5","workflowStages":[]},"version":"v1","identity":"rs-3849640","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3849640","identity":"rs-3849640","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}