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The aim of this research was to assess genetic diversity of Korean-Holstein, Korean Hanwoo, and Ugandan-Holstein dairy cattle. DNA was extracted from either blood or hair of Korean-Holstein (n=74), Korean-Hanwoo (n=75) and Ugandan-Holstein (N=77) using AccuPrep® PCR purification kit. The DNA samples were amplified by multiplex polymerase chain reaction, using GeneTrack™ Hanwoo genotyping kit and assayed using ABI genetic analyser 3130XL. Number of alleles, expected heterozygosity (He), observed heterozygosity (Ho), and the polymorphism information content (PIC) were estimated from 10 microsatellite loci in the three breeds. In addition, F-statistics for each of the 10 microsatellites in the three cattle breeds were estimated using fstat version 2.9.3.2 computer program. GENETIX (v.4.02) was used to perform factorial correspondence analysis (FCA) from the allele frequencies and multi-locus clustering was done using STRUCTURE analyses. A total of 124 alleles were detected. The number of alleles per locus varied from eight (TGLA126) to 22 (TGLA122), with an overall mean of 12.2. Expected heterozygosity ranged from 0.617 (SPS115) to 0.854 (TGLA53) and averaged 0.761. Observed heterozygosity ranged from 0.6 (SPS115) to 0.859 (TGLA53); and averaged 0.761. The mean PIC was 0.723; and means of the F-statistics FIT, FST and FIS were 0.077, 0.076 and 0.001 respectively. Although FCA revealed clear differentiation of Uganda-Holstein, Korean-Holstein, and Hanwoo, clustering assignments showed genetic admixture between Ugandan dairy cattle (Uganda-Holstein) and Hanwoo. In conclusion, the allelic variation present at the 10 loci was sufficient to categorize these cattle into distinct breed groups. [ABSTRACT FROM AUTHOR]

Background: Nagana (African Animal Trypanosomiasis-AAT) and tick-borne diseases (TBDs) constrain livestock production in most parts of sub-Saharan Africa. To this realisation, Uganda government set up an African trypanosomiasis (AT) control unit, which among other activities generates national tsetse control priority maps using apparent tsetse density data. Such maps underestimate mechanically transmitted AAT and thus ought to be refined using actual AT prevalence data. We therefore set out to generate up-to-date cattle and donkey trypanosomiasis prevalence data as well as find out the constraints to livestock production in Karamoja region in a bid to re-define AT control priority in this region., Results: Livestock keepers and animal health workers indicated that TBDs and AAT were the most important livestock diseases in Karamoja region. The prevalence of Trypanosoma spp. in cattle and donkeys was 16.3% (95% CI: 12.4-21.1%) and 32.4% (95% CI; 20.2-47.6%) respectively. Trypanosoma vivax (12.1%) and Trypanosoma congolense savannah (29.6%) were the most prevalent Trypanosoma spp. in cattle and donkeys respectively. Majority of the cattle (85.7%) and more than half of the donkey (57.1%) herds were positive for Trypanosoma spp., Conclusions: African animal trypanosomiasis and TBDs are the most important constraints to livestock production in Karamoja region. In order to improve livestock production and hence Karamajong livelihoods, government of Uganda and her development partners will need to invest in livestock health programs particularly targeting tsetse and TBD control.

Maize production in sub-Saharan Africa incurs serious losses to epiphytotics of foliar diseases. Quantitative trait loci conditioning partial resistance (rQTL) to infection by causal agents of gray leaf spot (GLS), northern corn leaf blight (NCLB), and maize streak have been reported. Our objectives were to identify simple-sequence repeat (SSR) molecular markers linked to consensus rQTL and one recently identified rQTL associated with GLS, and to determine their suitability as tools for selection of improved host resistance. We conducted evaluations of disease severity phenotypes in separate field nurseries, each containing 410 F2:3 families derived from a cross between maize inbred CML202 (NCLB and maize streak resistant) and VP31 (a GLS-resistant breeding line) that possess complimentary rQTL. F2:3 families were selected for resistance based on genotypic (SSR marker), phenotypic, or combined data and the selected F3:4 families were reevaluated. Phenotypic values associated with SSR markers for consensus rQTL in bins 4.08 for GLS, 5.04 for NCLB, and 1.04 for maize streak significantly reduced disease severity in both generations based on single-factor analysis of variance and marker-interval analysis. These results were consistent with the presence of homozygous resistant parent alleles, except in bin 8.06, where markers were contributed by the NCLB-susceptible parent. Only one marker associated with resistance could be confirmed in bins 2.09 (GLS) and 3.06 (NCLB), illustrating the need for more robust rQTL discovery, fine-mapping, and validation prior to undertaking marker-based selection.