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GENETIC DIVERSITY OF COMMON BEANS AS IMPACTED ON BY FARMER VARIETY SELECTION FOR THE MANAGEMENT OF BEAN ROOT ROTS IN SOUTH WESTERN UGANDA   S. Buah 1 , P. Okori 2  and R. Buruchara 1 1 International Center for Tropical Agriculture (CIAT), Kawanda, P.O. Box 6247, Kampala, Uganda;  2  Makerere University, Faculty of Agriculture, P.O. Box 7062, Kampala, Uganda. Introduction  Common bean is the world's most important food legume with an average consumption of 66 kg per person per year in Eastern Africa.  Uganda is the second largest consumer after Rwanda. However, production of the crop  is curtailed by several biotic and abiotic constraints. Among the biotic constraints,  Pythium  root rot caused by a complex of  Pythium  species, is one of the most devastating  diseases, causing yield losses of  up to 100% in certain seasons. Mixtures of beans have been cultivated and managed by farmers from season to season for various reasons including  protection against total crop losses. This practice has resulted in a broad array of phenotypically different seed and plant types. However, the impact of root rots on the genetic diversity of these mixtures is not well understood. The objectives of this study were therefore  to 1) understand farmer practices of using bean mixtures in bean root rot management; 2) analyze genetic diversity associated with bean mixtures in South-western Uganda.  Materials and Methods Diagnostic Survey :  This was conducted to collect bean samples and information on mixtures representing various landraces from Kabale and Kisoro districts (Figure 1). Fifty two farmers and 28 traders/stockists were randomly selected, interviewed and a 1kg of their bean seeds collected.  Morphological characterisation:   Collected samples were sorted out according to seed phenotypes and were morphologically characterised in the field using  the IBPGR’s (1982) descriptor list for common bean. All the cultigens were then screened against  P. ultimum   var. ultimum   in the screen house. Molecular characterisation:   Due to a large number  of cultigens involved, 100 samples representing all the morpho-agronomic clusters were randomly selected and assessed for genetic variability using Simple Sequence Repeats. A total of 6 SSR primers were used to amplify specific PCR products. Phaseolin, the major storage protein of common bean, was analysed using primers that differentiate “S” phaseolin gene family from the “T” phaseolin types. Figure 3: Genetic relationships among common beans based on 6 SSR loci  ,[object Object],[object Object],[object Object],[object Object],Figure 1: The location and number of mixtures (in red) collected from Kabale and Kisoro districts. Figure 2: Morphological relationships among bean cultigens based on 8 traits ,[object Object],[object Object],[object Object],[object Object],Results Farmer indigenous knowledge Over 60% of bean varieties were discovered to be locally conserved within the area either through savings from previous harvests or buying known seed types from local markets.  The most important reason for using bean mixtures was insurance against unforeseen weather changes or pest and diseases.   More than 78% of the respondents recognised and described symptoms of root rots on their farms. Morphological characterisation Cluster analysis based on morphological traits revealed two distinct groups corresponding to Andean (41%) and Mesoamerican (59%) gene pools (Figure 2).  Overall average disease score for the Andean group was 5.7 compared to 4.7 for the Mesoamerican group.  Only 16% of cultigens were resistant to  Pythium,  58% were moderately resistant. About70% of resistance found in Kisoro district.  Molecular Characterisation SSR analysis showed a higher diversity in the susceptible Andean genotypes than in  the resistant Mesoamerican genotypes.  Bootstrap analysis divided the cultigens into 2 clusters corresponding to Mesoamerican and Andean gene pools (Figure 3). The Andean cluster had T-Type phaseolin, whereas the Mesoamerican group had predominantly S-Type phaseolin which is characteristic of that gene pool.  A hierarchical AMOVA revealed significant differentiation within populations at the sub-counties ( P  < 0.001, but  no significant genetic variability between the districts of Kabale and Kisoro ( P  > 0.05).

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