Mcknight presentation3

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  1. 1. DETERMINATION OF PHYTOPLASMA HOST RANGEAMONG WILD GRASSES IN WESTERN KENYAPRESENTED BY; Adam O. Juma I56/10103/08 (Kenyatta University)SUPERVISORS; Dr. Runo S. Maina Kenyatta University Dr. Charles A. O. Midega International Center of Insect Physiology and Ecology.
  2. 2. Hypothesis Background information a Phytoplasma affects many unrelated plantsworldwide In East Africa, Napier stunt phytoplasmaposes a serious threat to Napier grassfarming The disease symptoms include severebstunted growth and loss of biomass The disease is mainly transmitted by aleafhopper Maeistas (=Recilia) banda inKenya (Obura et al., 2009)Photographs illustrating thecomparison between Health (a) &Diseased (b) Napier grass.
  3. 3. Statement of the problem Napier stunt disease has reduced Napier productivity by 30-90% inthe region Phytoplasma attacks other wild grasses, it is likely that several wildgrasses could be infected by specific phytoplasma strains These wild grasses might also act as reservoirs for fresh inoculums The determination of phytoplasma host range among wild grasses isnecessary for precise and sustainable phytoplasma diseasemanagement HWLDNSD BGWL
  4. 4. HypothesisThere is no diversity of wild grasses hostingphytoplasmas in Western Kenya.
  5. 5. Objectives General Objective To identify phytoplasmas wild host range among wildgrasses in Western Kenya.Specific Objectives To detect and identify phytoplasma strains infectingwild grasses in western Kenya To identify wild grass species hosting phytoplasmas inWestern Kenya.
  6. 6. Study Area
  7. 7. Sampling strategy1-3m1-3 m1m 1m Transects Quadrat Grass field boundary
  8. 8. Collection of leaf samples (300mg)DNA extraction PCR amplificationCTAB Method (Doyle & P1/P6 Primer pairDoyle, 1990) (Saitou & Nei, 1987)nPCR neighbour joining method Phylogenetic analysis byNapF/NapR Primer pairusing BLAST search at NCBIComparison of sequences aracterization bynotypicPurification of PCRquencing of PCRproductsoductsCharacterizationPhytoplasma detection &
  9. 9. Diversity of grasses in Busia and Bungoma districtsPennisetum polystachion1.6%Echinochloa pyramidalis0.7%Eragrostis curvula 0.7%Hyparrhenia pilgerama0.7%Sorghum versicolor 0.7%Rottboelia cochinchinensis 0.3%Setaria incrassata 0.3%Sporobolus pyramidalis 0.3%Themeda triada 0.3%Panicum maximum0.4%Hyparrhenia pilgerama1.2%Sporobolus pyramidalis 0.9%Cymbopogon nardus0.6%Eragrostis curvula 0.6%Setaria incrassata 0.6%Cenchrus ciliaris0.3%Eleusine indica0.3%Pennisetum purpureum 0.3%Poverty grass0.3%
  10. 10. Diversity of grasses in Busia and Bungoma districts D. scalarum, C. dactylon and Brachiaria arethe most dominant in both districts Account for 69% and 76% of the grassessampled in Busia and Bungoma respectively
  11. 11. Incidence of Phytoplasma in Busia and Bungoma Phytoplasma infection in common grasses of both districts.13% of sampled grasses infected. 11% infected in Busia Low, widespread infection in Busia (between 7 22% infection) 14% infected in Bungoma. Highest infection in Cynodon dactylon and Bracharia (35% and 18.5% respectively!)
  12. 12. Latent infections in Busia and Bungoma63% of all phytoplasmainfections Latent!42.9%79% of infected plants in27.3% Busia asymptomatic.25.0%Bracharia, Cynodon andother identified grasses.44.0%48% of infected plants inBungoma asymptomatic.Cynodon and Digitaria16.0%
  13. 13. Modeled proportions of potential host grassesrelative to other grasses (GLM)Model: Takes into consideration abundance and infection statusesBungomaBracharia and C. dactylon the main host of phytoplasma in BungomaBracharia 22% (95% CI 10 51%; P