A farmer-friendly tool for estimation of weights of pigs kept by smallholder farmers in Uganda.

Pig keeping is important to the livelihoods of many rural Ugandans. Pigs are typically sold based on live weight or a carcass weight derived from this; however this weight is commonly estimated due to the lack of access to scales. Here, we explore the development of a weigh band for more accurate weight determination and potentially increased farmer bargaining power on sale price. Pig weights and varied body measurements (heart girth, height, and length) were collected on 764 pigs of different ages, sex, and breed types, from 157 smallholder pig keeping households in Central and Western Uganda. Mixed-effects linear regression analyses, with household as a random effect and the varied body measurements as a fixed effect, were performed to determine the best single predictor for cube root of weight (transformation of weight for normality), for 749 pigs ranging between 0 and 125 kg. The most predictive single body measurement was heart girth, where weight in kg = (0.4011 + heart girth in cm × 0.0381)3. This model was found to be most suitable for pigs between 5 and 110 kg, notably more accurate than farmers' estimates, but still with somewhat broad confidence intervals (for example, ±11.5 kg for pigs with a predicted weight of 51.3 kg). We intend to pilot test a weigh band based on this model before deciding on whether it is suitable for wider scaling.

Integrative QTL mapping and selection signatures in Groningen White Headed cattle inferred from whole-genome sequences.

Here, we aimed to identify and characterize genomic regions that differ between Groningen White Headed (GWH) breed and other cattle, and in particular to identify candidate genes associated with coat color and/or eye-protective phenotypes. Firstly, whole genome sequences of 170 animals from eight breeds were used to evaluate the genetic structure of the GWH in relation to other cattle breeds by carrying out principal components and model-based clustering analyses. Secondly, the candidate genomic regions were identified by integrating the findings from: a) a genome-wide association study using GWH, other white headed breeds (Hereford and Simmental), and breeds with a non-white headed phenotype (Dutch Friesian, Deep Red, Meuse-Rhine-Yssel, Dutch Belted, and Holstein Friesian); b) scans for specific signatures of selection in GWH cattle by comparison with four other Dutch traditional breeds (Dutch Friesian, Deep Red, Meuse-Rhine-Yssel and Dutch Belted) and the commercial Holstein Friesian; and c) detection of candidate genes identified via these approaches. The alignment of the filtered reads to the reference genome (ARS-UCD1.2) resulted in a mean depth of coverage of 8.7X. After variant calling, the lowest number of breed-specific variants was detected in Holstein Friesian (148,213), and the largest in Deep Red (558,909). By integrating the results, we identified five genomic regions under selection on BTA4 (70.2-71.3 Mb), BTA5 (10.0-19.7 Mb), BTA20 (10.0-19.9 and 20.0-22.7 Mb), and BTA25 (0.5-9.2 Mb). These regions contain positional and functional candidate genes associated with retinal degeneration (e.g., CWC27 and CLUAP1), ultraviolet protection (e.g., ERCC8), and pigmentation (e.g. PDE4D) which are probably associated with the GWH specific pigmentation and/or eye-protective phenotypes, e.g. Ambilateral Circumocular Pigmentation (ACOP). Our results will assist in characterizing the molecular basis of GWH phenotypes and the biological implications of its adaptation.

Natural Selection Footprints Among African Chicken Breeds and Village Ecotypes.

Natural selection is likely a major factor in shaping genomic variation of the African indigenous rural chicken, driving the development of genetic footprints. Selection footprints are expected to be associated with adaptation to locally prevailing environmental stressors, which may include diverse factors as high altitude, disease resistance, poor nutrition, oxidative and heat stresses. To determine the existence of a selection footprint, 268 birds were randomly sampled from three indigenous ecotypes from East Africa (Rwanda and Uganda) and North Africa (Baladi), and two registered Egyptian breeds (Dandarawi and Fayoumi). Samples were genotyped using the chicken Affymetrix 600K Axiom® Array. A total of 494,332 SNPs were utilized in the downstream analysis after implementing quality control measures. The intra-population runs of homozygosity (ROH) that occurred in >50% of individuals of an ecotype or in >75% of a breed were studied. To identify inter-population differentiation due to genetic structure, FST was calculated for North- vs. East-African populations and Baladi and Fayoumi vs. Dandarawi for overlapping windows (500 kb with a step-size of 250 kb). The ROH and FST mapping detected several selective sweeps on different autosomes. Results reflected selection footprints of the environmental stresses, breed behavior, and management. Intra-population ROH of the Egyptian chickens showed selection footprints bearing genes for adaptation to heat, solar radiation, ion transport and immunity. The high-altitude-adapted East-African populations' ROH showed a selection signature with genes for angiogenesis, oxygen-heme binding and transport. The neuroglobin gene (GO:0019825 and GO:0015671) was detected on a Chromosome 5 ROH of Rwanda-Uganda ecotypes. The sodium-dependent noradrenaline transporter, SLC6A2 on a Chromosome 11 ROH in Fayoumi breed may reflect its active behavior. Inter-population FST among Egyptian populations reflected genetic mechanisms for the Fayoumi resistance to Newcastle Disease Virus (NDV), while FST between Egyptian and Rwanda-Uganda populations indicated the Secreted frizzled related protein 2, SFRP2, (GO:0009314) on Chromosome 4, that contributes to melanogenic activity and most likely enhances the Dandarawi chicken adaptation to high-intensity of solar radiation in Southern Egypt. These results enhance our understanding of the natural selection forces role in shaping genomic structure for adaptation to the stressful African conditions.

Lowland grazing and Marburg virus disease (MVD) outbreak in Kween district, Eastern Uganda.

BACKGROUND: Uganda is one of the few countries in Africa that has been experiencing outbreaks of viral hemorrhagic fevers such as Ebola, Marburg and Crimean-Congo Hemorrhagic fevers. In 2017 Uganda experienced a Marburg Virus Disease (MVD) outbreak with case fatality rate of 100% in Kween district. Although hunting for wild meat was linked to the MVD outbreak in Kween district, less was reported on the land use changes, especially the changing animal grazing practices in Kween district. METHODS: Through Makerere University One Health graduate fellowship program with attachment to Uganda Red Cross Society, a study was conducted among the agricultural communities to elucidate the risk behaviors in Kween district that can be linked to the 2017 Marburg disease outbreak. RESULTS: Results show that although a few elderly participants ascribed fatal causes (disobedience to gods, ancestors, and evil spirits) to the MVD outbreak during FGDs, majority of participants linked MVD to settling in caves (inhabited by Fruit Bats) during wet season as upper belts are extensively used for crop production leaving little space for animal grazing. Members also noted side activities like hunting for wild meat during this grazing period that could have predisposed them to Marburg Virus. CONCLUSIONS: There is need to integrate One Health concepts within agricultural extension service provision in Uganda so as to enhance the management of such infectious diseases.