Detection of anaplasma antibodies in wildlife and domestic species in wildlife-livestock interface areas of Kenya by major surface protein 5 competitive inhibition enzyme-linked immunosorbent assay

The seroprevalence of Anaplasma antibodies in wildlife (eland, blue wildebeest, kongoni, impala, Thomson's gazelle, Grant's gazelle, giraffe and plains zebra) and domestic animal (cattle, sheep and goat) populations was studied in wildlife / livestock interface areas of Kenya. Serum samples were analyzed by competitive inhibition enzyme-linked immunosorbent assay (CI-ELISA), using a recombinant antigen (MSP-5) from Anaplasma marginale surface membrane. A monoclonal antibody, FC-16, was used as the primary antibody, while anti-mouse conjugated to horseradish peroxidase was used as the secondary antibody. The results indicate a high seroprevalence in both wildlife and livestock populations, in contrast to earlier reports from Kenya, which indicated a low seroprevalence. The differences are attributed to the accurate analytical method used (CI-ELISA), as compared with agglutination techniques, clinical signs and microscopy employed by the earlier workers.Netherlands Government,through the Wildlife Disease Research Project and the Director, Kenya Agricultural Research Institute (KARl

Genetic diversity of indigenous chickens from selected areas in Kenya using microsatellite markers

In this study, indigenous chickens were collected from eight different regions in Kenya and kept at InCIP-Egerton University. These were studied using eighteen microsatellite markers to determine genetic variation. Statistics related to genetic variation were estimated using GenALEx6. Mean percentage polymorphic loci (PPL) was 96.71% and 4% genetic variance (p ≥ 0.003) was seen between the eight populations. MCW0123 marker had the highest genetic variance of 13% among populations (p ≥ 0.003) at 95% CI. Mean He ranged from 0.351 ± 0.031 (SIB) to 0.434 ± 0.022 (BM) with a grand mean He of 0.399 ± 0.011 across the populations using the microsatellite markers. Nei’s genetic distance ranged from 0.016 (SIB and WP) to 0.126 (NR and SIB). DARwin6.501 analysis software was used to draw the population dendrogram and two major population clusters were observed, also seen with PCoA. This study found a lot of genetic variation and relatedness within and among populations. Based on the phylogenetic tree result, it is concluded that the clustering of the chicken populations in the present study is not based on geographical proximity. The microsatellite markers used in this study were suitable for the measurement of the genetic biodiversity and relationship of Kenyan chicken populations. These results can therefore serve as an initial step to plan the conservation of indigenous chickens in Kenya