| Summary: | The population genetic structure of Biomphalaria snails was investigated. The degree of genetic variation and genetic population differentiation of Biomphalaria populations was inferred from the CO1 gene and the ITS-2 region. Phylogenetic relationships among the populations were deduced by PhyML version 2.4.4 using the Maximum Likelihood method, the GTR+G model, and with bootstrap values based on 1000 replicates. Measures of population differentiation were then calculated from CO1 sequence data and ITS-2 sequence data by use of the AMOVA model in Arlequin software version 3.5. The taxa identified were the ‘B. pfeifferi group’ and the ‘Nilotic Species Complex.’ AMOVA revealed low genetic variation within B. pfeifferi populations (between 4.83% and 5.86%) and high genetic differentiation among the populations (between 94.14% and 95.17%). As for the ‘Nilotic Species Complex’ individuals, the genetic diversity within populations was moderate (between 28.78% and 72.17%) so was the genetic differentiation among populations (between 27.83% and 49.74%). There was a clear geographical clustering of haplotypes with the identification of 18 B. pfeifferi CO1 haplotypes and 20 CO1 haplotypes for the ‘Nilotic Species Complex’ individuals. As for ITS-2 sequence data, there was identification of 27 B. pfeifferi ITS-2 haplotypes and 23 haplotypes for the ‘Nilotic Species Complex’ individuals.
An extensive study on the distribution of Biomphalaria snails in East Africa’s River systems was conducted. Malacological surveys were conducted at a total of 172 sites with ecological and physicochemical parameters associated with snail abundance recorded and the CO1 gene marker used to differentiate the Biomphalaria snails to their respective species groups. Biomphalaria snails were found in a total of 31 out of the 172 visited sites with B. pfeifferi populations being found at 23 sites and members of the ‘Nilotic Species Complex’ being found at 9 sites. Streams proved to be the habitats most preferred by the Biomphalaria snails (61.3% of all the sites where the snails were found were streams). Regarding ecological and physicochemical parameters, temperature and water depth proved to be the only factors that had a statistically significant positive relationship with the abundance of the snails. There was also molecular detection of S. mansoni infections in Biomphalaria snails using ND5 and SMF/R molecular makers. Schistosome infection was detected at 11 out of the 31 sites where Biomphalaria snails were found. We observed low to moderate incidences of S. mansoni infection with an overall infection rate in infected sites of 21.27%. Out of the 11 populations that were found infected with S. mansoni, all of them were B. pfeifferi populations; none were ‘Nilotic Species Complex’ populations.
Furthermore, the population genetic structure of pre-patent and sub-patent S. mansoni populations was examined with the use of the ND5 mitochondrial gene. Moderate levels of genetic diversity were found within (53.34%) and between (46.66%) the S. mansoni populations. Based on the findings presented in this thesis, future work on Biomphalaria snails in East Africa’s River systems can include conducting cercarial shedding studies on the snails from sites where the snails were found and use of molluscicides as part of an integrated approach for schistosomiasis control in locations where Biomphalaria snails were found.
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