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 \u3e50% of individuals of an ecotype or in \u3e75% 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

Genomic Diversity Using Copy Number Variations in Worldwide Chicken Populations

Recently, many studies in livestock have focused on the identification of Copy Number Variants (CNVs) using high-density Single Nucleotide Polymorphism (SNP) arrays, but few have focused on studying chicken ecotypes coming from many locations. CNVs are polymorphisms, which may influence phenotype and are an important source of genetic variation in populations. The aim of this study was to explore the genetic difference and structure, using a high density SNP chip in 936 individuals from seven different countries (Brazil, Italy, Egypt, Mexico, Rwanda, Sri Lanka and Uganda). The DNA was genotyped with the Affymetrix Axiom®600k Chicken Genotyping Array and processed with stringent quality controls to obtain 559,201 SNPs in 915 individuals. The Log R Ratio (LRR) and the B Allele Frequency of SNPs were used to perform the CNV calling with PennCNV software based on a Hidden Markov Model analysis and the LRR was used to perform CNV detection with SVS Golden Helix software.After filtering, a total of 19,027 CNVs were detected with the SVS software, while 9,065 CNVs were identified with the Penn CNV software. The CNVs were summarized in 7,001 Copy Number Variant Regions (CNVRs) and 4,414 CNVRs, using the software BedTool.The consensus analysis across the CNVRs allowed the identification of 2,820 consensus CNVR, of which 1,721 were gain, 637 loss and 462 complex, for a total length of 53 Mb corresponding to the 5 % of the GalGal5 chicken autosomes. Only the consensus CNV regions obtained from both detections were considered for further analysis.The intersection analysis performed between the chicken gene database (Gallus_gallus-5.0) and the 1,927 consensus CNVRs allowed the identification (within or partial overlap) of a total of 2,354 unique genes with an official gene ID.  The CNVRs identified here represent the first comprehensive mapping in several worldwide populations, using a high-density SNP chip

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

Bee Keeping - Theory and Practice 2nd Edition

   This book is divided into two parts. Part One focuses on understanding  these important insects. It show that bees are not only matriarchal but  also that they are such a well organised community of insects, with  clear roles for every hive occupant, and with a complex communication system that  human armies cannot help but marvel at. The second part presents the  practice of beekeeping. It looks at the equipment and tools, management  aspects, and general care needed for a successful enterprise.  Beekeeping, unlike livestock does not require high investment and  maintenance costs or intensive labour, which keep out many potential  farmers. Beekeeping provides an avenue for production of nutritious  food, and most importantly, enables the majority of rural dwellers to  earn good levels of income without necessarily destroying the  environment, and without investing a lot of capital or requiring daily labour.  </p

Uganda chicken genetic resources: II. genetic diversity and population demographic history inferred from mitochondrial DNA D-loop sequences

The genetic diversity of indigenous chickens, which comprise over 80% of the chicken resources in Uganda, is largely not well-characterized for their genetic contribution. This study assessed the genetic diversity and population structure of the indigenous chicken population in Uganda to serve as an essential component for improvement and conservation strategies. A set of 344 mitochondrial DNA (mtDNA) D-loop sequences among 12 Ugandan chicken populations was evaluated. Twenty-eight polymorphic sites, accounting for 4.26% of the total analyzed loci of 658 bp, defined 32 haplotypes. The haplotype diversity (Hd) was 0.437, with a nucleotide diversity (π) of 0.0169, while the average number of nucleotide differences (k) was 0.576, indicating a population that is moderately genetically diverse. Analysis of molecular variance found 98.39% (ρ &lt; 0.01) of the total sequence variation among the chicken haplotypes within populations, 1.08% (ρ &lt; 0.05) among populations, and 0.75% (ρ &gt; 0.05) among populations within regions. This revealed subtle genetic differentiation among the populations, which appeared to be influenced by population fragmentation, probably due to neutral mutation, random genetic drift, and/or balancing selection. All the haplotypes showed affinity exclusively to the haplogroup-E mtDNA phylogeny, with haplotype UGA01 signaling an ancestral haplotype in Uganda. Neutrality tests Tajima’s D (−2.320) and Fu’s Fs (−51.369), augmented with mismatch distribution to measure signatures of recent historical demographic events, supported a population expansion across the chicken populations. The results show one matrilineal ancestry of Ugandan chickens from a lineage widespread throughout the world that began in the Indian subcontinent. The lack of phylogeographic signals is consistent with recent expansion events with extensive within-country genetic intermixing among haplotypes. Thus, the findings in this study hold the potential to guide conservation strategies and breeding programs in Uganda, given that higher genetic diversity comes from within the chicken population

Commercialisation of Alternative Livestock Feeds Could Save Fish Stocks in Lake Victoria

Increasing livestock production in East Africa requires increased use of fish meal as a source of protein, some of which comes from the Silver Cyprinid (Rastrineobola argentea) in Lake Victoria, which could result in its over-exploitation and affect the survival of other organisms in the lake. The crude protein content of cockroaches (38-76% CP depending on the age) and of other insects is similar to that of fish meal (61.24% CP) and could be a substitute for it, if these insects can be domesticated and used as animal feeds. Non-conventional feeds such as cockroaches, houseflies, termites, earthworms and carabid beetles are used on a small scale by farmers in Uganda who would be willing to use them more if they could be produced on a large scale. There is therefore a need to promote large scale insect breeding so that these alternative protein sources can be integrated into farming systems.Keywords: Alternative protein sources, Fishmeal, Insects, Poultr

Development of a weigh-band for pigs in Uganda (Data on weights and body measurements of Ugandan pigs)

Knowledge of the body weight in pigs is important in informing management decisions and, often, negotiating a sale price. In the smallholder pig system in Uganda the smallholder pig keepers usually do not know the body weights of their animals nor have access to scales. To overcome this, we propose to collect body measurement of pigs with the following objectives: 1. Determine the best predictive equation for weight from body measurement for (a) all animals, and (b) subsets of animals (e.g., grouped by weight, age, sex) 2. Estimate the loss in predictive accuracy in only using one variable for all animals and subsets of animals (testing this as one predictive variable makes a weigh-band a viable option) 3. Should one variable not be viable explore the options for making a farming friendly tool for predicting weight (weigh band, table, app etc.) 4. Synthesis and reporting of results including sharing with local partners 5. Production and dissemination of weight bands (or alternative tool) to participating farmers. Exploration of options for a distributor of these (e.g.private sector partner) The dataset is provided along with the ODK tool used to collect the data (the dictionary for coded variables can be found on the Choices sheet