Background: There is no information on human and animal Cryptosporidium spp. in Njoro sub- county. The risk posed to humans and animals within the sub-county is therefore unknown. Materials and Methods: A total of 1476 animal and 378 human fecal samples were evaluated. Multivariate logistic regression was used to evaluate association between infection status and the predisposing factors. Results were expressed as odds ratio (OR) with a 95% confidence interval. Chi-square and Maentel–Haenszel tests were used to quantify relationships among variables. Results: Prevalence of Cryptosporidium spp. was 9.8% in humans, 10.8% in cows, 19.6% in sheep and 4.5% in goats. Prevalence in humans was significantly higher in females 12/37. Infection was highest in the elderly (27.27%), and significantly lower in adolescents and adults at 8.66% and 9.59%, respectively. Goats had lowest overall parasitization at all levels, while sheep had the highest parasitization at levels (+1 and +2). Relatively, humans had the highest parasite counts +3 cases (1.5%). Conclusion: Cryptosporidium spp. is prevalent in Njoro sub-county and domestic animals are important reservoirs and a potential source of zoonosis in humans. Children, elderly and females are at increased risk of infection, especially during rainy season. The study recommends maintenance of proper sanitation when handling domestic animals, treatment of drinking water and use of alternative safer sources of water in order to reduce infection.

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Coconut is the most important cash crop along the Coast of Kenya, yet its genetic diversity has not been fully established. Genetic diversity study of 48 coconut genotypes, collected at the Coastal Kenya was conducted with 13 polymorphic short sequence repeats (SSRs) markers. SSR analysis was performed using GeneMapper while data analysis was done with PowerMarker and DARwin softwares. Analysis revealed a total of 68 alleles ranging from 2 to 11 per locus with a mean of 5.23 per marker. Gene diversity and polymorphic information content (PIC) ranged between 0.41 to 0.83 and 0.33 to 0.79, respectively. Neighbour -joining dendrogram grouped the genotypes into three major clusters with distinct sub-clusters. This study underscored that capillary electrophoresis is a more accurate and informative technique for SSRs allele scoring as opposed to agarose gels. The clusters observed forms the basis to isolate conservation blocks, which is key to establishing a genebank, since there is no documented coconut genebank for ex-situ conservation in Kenya.

Cape gooseberry (Physalis peruviana L.) is a neglected high potential crop, knowledge of the genetic diversity of the genotypes domesticated in Kenya is limited. To understand the genetic diversity and structure within and between Cape gooseberry germplasm, 70 accessions from six selected counties were analyzed using 15 pairs of highly polymorphic SSR primers. In this study, a total of 61 polymorphic SSR alleles were identified with mean polymorphic information content (PIC) of 0.43. Analysis of Molecular Variance (AMOVA) revealed that 92.8% of the total genetic variation was within accessions whereas variation among accessions accounted for 7.2% of the total genetic variation. Genetic diversity parameters among the 70 accessions revealed that Cape gooseberry was more diverse than previously recorded. Based on the SSR data, the 70 accessions were classified into five main phylogenetic groups, which corresponded to the county of origin through factorial analysis, principal component analysis (PCA), and phylogenetic analysis. Seven core SSR primer pairs, namely SSR1, SSR2, SSR10, SSR11, SSR123, SSR138, and SSR146 were found to have a wide applicability in genotype identification of cape gooseberry, and thus they are recommended for use in genetic characterization of germplasm collected from other counties not covered by the present study. This study demonstrated the existence of considerable genetic diversity in Cape gooseberry accessions growing in selected counties in Kenya and can therefore be used as a basis for future breeding programs in the development of hybrids with desirable traits. This wider genetic diversity is vital for posterity as it will help cope with unpredictable climatic changes and human needs.

Cryptosporidium spp. cause Cryptosporidiosis in humans through zoonotic and anthroponotic transmission. Previous studies have illustrated the significance of domestic animals as reservoirs of this parasite. However, there is no information on the Cryptosporidium spp. and genotypes circulating in Njoro Sub County. A total of 2174 samples from humans, cattle, chicken, sheep and goats were assessed for presence of Cryptosporidium spp. Thirty-three positive samples were successfully sequenced. The sequences obtained were compared to Cryptosporidium sequences in the GenBank using NCBI’s (National Center for Biotechnology Information) online BLAST (Basic Local Alignment Search Tool) algorithmic program. Sequence alignment was done using the Clustal W program and phylogenetic analysis was executed in MEGA 6 (Molecular Evolutionary Genetics Analysis version 6.0). The Cryptosporidium spp. present in the watershed showed great genetic diversity with nine (9) Cryptosporidium spp. namely: C. parvum, C. hominis, C. ubiquitum, C. meleagridis, C. andersoni, C. baileyi, C. muris, C. xiaoi and C. viatorum. Cattle were the biggest reservoirs of zoonotic Cryptosporidium spp. hence a potential source of zoonosis in humans while goats had the least species. This is the first study that reported presence of C. viatorum in Kenya.