Browsing by Author "H. Talwana"

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    Effect of Marker Aided Pyramiding of Anthracnose and Pythium Root Rot Resistance Genes on Plant Agronomic Characters among Advanced Common Bean Genotypes
    (Journal of Agricultural Science, 2015-02-15) M. Kiryowa; S. T. Nkalubo; C. Mukankusi; H. Talwana; P. Gibson; P. Tukamuhabwa
    One of the factors that accounts for the low yields in common bean is the simultaneous occurrence of diseases on the common bean crop. Bean root rots and anthracnose are the most important common bean diseases that simultaneously occur on the bean crop in Uganda. Moreover, Colletotrichum lindemuthianum, the pathogen that causes bean anthracnose, possesses a high genetic variability which makes it easily break down single gene resistance. Pyramiding resistance genes for both diseases in commercial varieties would ensure reduction of yield losses resulting from the two diseases. However, the effect of marker assisted gene pyramiding on plant agronomic characters is not well understood. Three-way crosses were made to pyramid three anthracnose and one Pythium root rot resistance genes in four susceptible market class varieties. Sequence characterized amplified regions (SCAR) markers were used to facilitate the pyramiding scheme. Correlation analysis and Path coefficient analysis were used to assess the association between number of pyramided genes and different plant agronomic characters. Number of pyramided genes was negatively correlated with number of pods per plant (-0.32), number of seeds per plant (-0.25), number of seeds per pod (-0.18), pod length (-0.17), days to 50% flowering (-0.09) and 100-seed weight (-0.02). Path coefficient analysis showed that number of pyramided genes, plant height, days to 50% flowering, number of seeds per pod and number of pods per plant had negative direct effects on seed weight per plant. Number of seeds per plant had the highest positive direct effects (0.98) followed by 100-seed weight (0.28) while days to maturity had the least positive direct effect (0.03) on seed weight per plant. Only number of seeds per plant had its correlation coefficient (0.94) almost equal to the direct path coefficient (0.97). Number of pyramided genes had significant (P < 0.05) negative indirect effect on seed weight per plant only through number of seeds per plant (-0.25). Therefore, pyramiding higher numbers of resistance genes may cause a grain yield reduction via number of seeds per plant. Therefore, it is important for breeders to simultaneously select for number of pyramided genes with number of seeds per plant and other highly associated traits.
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    Nematode 18S rRNA gene is a reliable tool for environmental biosafety assessment of transgenic banana in confined field trials
    (Transgenic Res, 2013-05-10) R. Nakacwa; A. Kiggundu; H. Talwana; J. Namaganda; C. Lilley; W. Tushemereirwe; H. Atkinson
    Information on relatedness in nematodes is commonly obtained by DNA sequencing of the ribosomal internal transcribed spacer region. However, the level of diversity at this locus is often insufficient for reliable species differentiation. Recent findings suggest that the sequences of a fragment of the small subunit nuclear ribosomal DNA (18S rRNA or SSU), identify genera of soil nematodes and can also distinguish between species in some cases. A database of soil nematode genera in a Ugandan soil was developed using 18S rRNA sequences of individual nematodes from a GM banana confined field trial site at the National Agricultural Research Laboratories, Kawanda in Uganda. The trial was planted to evaluate transgenic bananas for resistance to black Sigatoka disease. Search for relatedness of the sequences gained with entries in a public genomic database identified a range of 20 different genera and sometimes distinguished species. Molecular markers were designed from the sequence information to underpin nematode faunal analysis. This approach provides bio-indicators for disturbance of the soil environment and the condition of the soil food web. It is being developed to support environmental biosafety analysis by detecting any perturbance by transgenic banana or other GM crops on the soil environment.