Choosing the right breed is a crucial step in your poultry journey, especially here in East Africa. Let’s explore the diversity of feathered companions suited to our unique climate and farming conditions.
Key Chicken Breeds for East African Farms
Each breed brings its own unique advantages, and understanding their characteristics is key.
Kuroiler: The Resilient Egg Layer
Known for their hardiness and excellent egg-laying abilities, these birds could be the perfect addition to your farm.
Rainbow Rooster: Vibrant and Robust
Ideal for both meat and egg production, these birds thrive in East Africa’s varied environments.
Rainbow Rooster
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Dixie Rainbow Chicken Breed Profile History Health Issues - Dixie Rainbow Chicken Egg Ratio Lifespan
Sasso: Slow-Growing Excellence
Sasso chickens are known for their slow-growing nature and high meat quality.
Indigenous Breeds: Preserving Heritage
Celebrate the importance of preserving indigenous chicken breeds. These birds are well-adapted to local conditions and play a vital role in maintaining genetic diversity.
A breed from Tanzania
Considerations for Your Farm
Understand the factors to consider when selecting a breed for your farm. From space requirements to desired outputs, tailor your choice to fit your specific goals.
Genetic Insights into African Chicken Breeds
Chicken domestication began in Asia as a combination of several local domestication events between 6,000 and 8,000 years ago. Meanwhile, intensive human-directed selection for economic traits and the development of breeds is much more recent.
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A study based on mitochondrial D-loop sequences suggested that African chickens can be separated into two clades: the first includes North-African (e.g., Egypt), Central African, European, and West and Central Asian chickens, while the second clade includes East-African (e.g., Uganda and Rwanda) and the Pacific chickens.
The authors suggested that the first clade group likely originated from South-Asia and migrated to West-Asia, then arrived in Africa through Egypt, while the second clade migrated from the Pacific to East-Africa through the Indian Ocean.
Present Egyptian chicken populations, as an example of the North-Africa chickens, include pure native breeds, such as Fayoumi and Dandarawi, and admixed fowl ecotypes which originated from unplanned crossings among native populations and are identified by their geographic distribution (ecotypes), such as the Baladi (synonym of local) and its naked neck type.
The Fayoumi is a medium-sized breed (average 2 kg for male and 1.6 kg for female) characterized by early maturation (150 days), aggressive behavior, flying ability and resistance to several pathogens, including resistance to Rous Sarcoma, Marek’s disease virus and E. tenella infection (coccidiosis).
The Dandarawi is an auto-sexing bird and the smallest Egyptian breed (average 1.4 kg for male and 1.2 kg for female). This breed originated in Southern Egypt (Qena Governorate) which is characterized by hot (>40°C) dry climate, with intensive solar radiation.
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According to the Koppen climate classification, Egypt is located in the Warm desert climate zone, while Uganda and Rwanda are in the Tropical savanna zone. The main environmental differences between Egypt and both Eastern Africa countries are altitude, precipitation, and temperature.
According to the World Meteorological Organization (WMO), World Weather Information Service1, the 30-year averages for the major meteorological parameters for the capital of each country are as follows: Egypt has the hottest and driest weather with larger diurnal variation. In Rwanda, average temperatures ranged from 25.9 to 28.2°C with an average annual precipitation rate of 79.24 ml, while Ugandan average temperatures ranged between 26.9 and 29.3°C with a precipitation rate of 105.24 ml. Altitude averages are, respectively, 75, 1,497 and 1,155 m in Egypt, Rwanda, and Uganda.
For climatic variation among sampling locations of indigenous Egyptian chicken populations, Khalil et al. (2011) classified Egypt into six Agro-climatic zones according to the evapotranspiration (ETo) which considers major weather parameters, i.e., solar radiation, air temperature and humidity, and wind speed.
According to the ETo mapping, Qalyubia (source of Baladi), Fayoum (source of Fayoumi) and Qena (source of Dandarawi) governorates belong to different ETo zones.
The solar Atlas of Egypt indicated that average annual solar radiation ranges from 2,000 (North) to 3,200 (South) kWh/m2/year, and accordingly, Egypt was classified into 12 belts (zones).
For solar radiation estimates in Rwanda, Batalla and Parellada (2015) reported a much lower variation than Egypt that ranged between 4.98 kWh/m2/day in Kayonza district and 5.28 kWh/m2/day in Bugesera district. In Uganda, average solar radiation ranged between 17.2 MJ/m2 (4.78 kW/m2/day) in Kabale and 21.5 NJ/m2 (5.97 kWh/m2/day) in Soroti.
The current study aims to identify genomic footprints of natural selection of some North- vs. East-African chicken breeds and ecotypes raised and adapted to different local environments. The analytical approach combined high-density genotype-based, intra-population runs of homozygosity (ROH) and the allele-frequency-based inter-population genetic differentiation (FST).
ROH exist when identical haplotypes are inherited from each parent. ROH analysis indicated the population history and trait architecture. The length of ROH reflects individual demographic history and level of inbreeding.
Meanwhile, the homozygosity burden can be used to detect genetic architecture of complex traits. It was also reported that ROH are universally common in genomes, even among outbred individuals of human.
In cattle, a large proportion of ROH are likely the result of the accumulation of elite alleles from long-term selective breeding programs. Therefore ROH was selected for studying population architecture and investigating selection signature resulted from natural selective forces in the indigenous African chicken breeds that are usually outbred and have been exposed to local natural selection forces for uncountable generations.
FST is one of the most widely used measures for assessing genetic differentiation. It plays a major role in ecological and evolutionary genetic studies. Since the emergence of next generation sequencing data, it was proved that the large number of genetic markers can compensate for small sample sizes when estimating FST.
A total of 268 blood samples were collected on FTA cards from birds of East Africa (EA; Rwanda and Uganda), and North Africa (NA; Egypt). Samples were collected by local veterinarians following the approved country standards of animal care practices.
A total of 172 samples were collected in EA: 100 Rwandan and 72 Ugandan ecotypes. Rwandan samples were collected from the Huye (n = 25), Kicukiro, Kirehe, Musanze, Nyagatare, and Rubavu (n = 15 for each) districts. Ugandan samples were collected from three districts; Kamuli, Masaka, and Luweero (n = 24, for each). For more details on Ugandan and Rwandan samples see Fleming et al. (2016).
A total of 96 samples were collected from Egypt: 31 Egyptian Native Naked Neck Baladi (will be referenced to as Baladi) from three villages in Qalyubia Governorate (30° 24′ 36″ N, 31° 12′ 36″ E, 19m) in the Delta; 31 Fayoumi from four villages in Mid-Egypt (Fayoum Governorate, 29° 21′ 48″ N, 30° 44′ 45″ E, 14m); and 34 Dandarawi from four villages in Southern Egypt (Qena Governorate, 26° 8′ 34.8″ N, 32° 43′ 40.8″ E, 76m).
Chicken blood samples from Egypt, Rwanda, and Uganda were collected in accordance with the local veterinary guidelines in each country. Genotyping of all samples was conducted at GeneSeek (Lincoln, NE, United States) using the Affymetrix Axiom® 600k Array.
A total number of 494,332 SNPs and 266 birds were utilized in the downstream analysis after QC measures of MAF >0.05 and call rate of >0.97 applied to all samples using PLINK 1.9.
PLINK 1.9 was used for constructing a multi-dimension scaling (MDS) plot based on a 266 × 266 matrix of genome-wide Identity-By-State (IBS) scores calculated based on pairwise comparisons of the genetic distances for all individuals, and the first two components.
Runs of homozygosity analyses were carried out for both individual populations and combined EA and NA breeds/ecotypes using PLINK 1.9 to examine overlapping genomic regions that harbored alleles driven to fixation within each population or group of populations using a SNP based sliding window approach.
ROH requirements were defined as ≥300 SNPs, a minimum SNP density per ROH was set to one SNP per 50 kb, a maximum gap permitted between consecutive homozygous SNPs was set to 10 kb, three heterozygous calls were allowed within a run to account for genotyping errors and/or hitch-hiking events, and allelic match threshold of 0.95 identity and >20 SNPs.
The overlapping ROH was considered as those overlapped across all populations, regardless their length, and consensus ROHs are those reached a consensus in either >50% of the individuals of an ecotype or in >75% of a breed, except for the Rwanda and Uganda ecotypes where a 40% consensus threshold was accepted.
To identify the regions under selection that are differentiated among breeds or ecotypes, an overlapping sliding window-based FST analysis was calculated according to Karlsson et al. (2007). The pairwise comparisons were performed for North-African (Baladi, Dandarawi, and Fayoumi) vs. East-African (Rwanda and Uganda) populations, and all population-pairwise combinations, for overlapping windows along each chromosome.
Each FST window consisted of 500 kb with a step size of 250 kb. Only windows with ≥20 SNP were considered. Candidate genomic regions under selection were defined by a cutoff FST value >0.30, that exceeds the value of 0.25 defined as very great genetic differentiation according to Hartl and Clark (1997).
Genes within the regions of high interest for both ROH and FST analyses were identified using the software bedtools v2.26.0 using the (Gallus_gallus-5.0, GCA_000002315.3) annotation genome2. GO for molecular function and biological processes for the identified genes were determined by PANTHER using the Gallus gallus reference genome3 and enriched genes were identified using Enrichr.
GO terms were considered statistically significant at adjusted P < 0.05. The multi-dimensional scaling analysis (Figure 1) showed clear stratification and distinctive separation among the five populations studied.
The first dimension (C1) separated the Egyptian (North-African) from both the Rwanda and Uganda (East-African) populations. The second dimension (C2) separated the Dandarawi (smallest-sized and tolerant to Southern Egypt extreme heat and solar radiation conditions) from both the Baladi (Nile Delta) and Fayoumi (Mid-Egypt).
Baladi and Fayoumi (prevalent in similar environments of the Nile delta and Mid-Egypt) are genetically closer to each other than the Southern-Egypt Dandarawi breed. MDS also shows overlapping between the Rwandan and Ugandan populations, which was also reported by Fleming et al. (2016).
For the admixture analysis, the best K (K = 5) was determined based on the cross-validation error for different numbers of ancestral genetic backgrounds. Admixture analysis (Figure 2) showed that Dandarawi and Fayoumi was the only population with minimal admixture.
Baladi, Rwanda and Uganda are all ecotypes composed of an admixture of genetic backgrounds. Both Rwanda and Uganda chickens showed a composition of a one common main genetic background (ancestral genotypes) and four other minor backgrounds.
Figure 1. Multi-dimensional scaling, MDS, plot showing the distinct sampled five native African (two East- and three North-African) chicken populations. Plot was constructed based on a matrix of genome-wide Identity-By-State scores calculated based on pairwise comparisons of the genetic distances for all individuals.
Figure 2. Admixture analysis plot for the five native African chicken populations, based on ancestral model-clustering, with no prior knowledge on breed origins. The optimum number of clusters (ancestral genetic background) k = 5.
Total individual ROH, regardless of consensus conditions, were classified according to length into three classes (Supplementary Table S1); short (300 kb-<1 Mb), medium (1-<1.5 Mb), and long (>1.5 Mb).
The number and length of individual ROH differed widely among the populations in the study due to the nature of the population; e.g., breed or ecotype, number of samples and genetic structure. Breeds (Fayoumi and Dandarawi) showed higher average number of ROH than ecotypes.
Egyptian Dandarawi showed the highest average number of ROH (180.8) and the highest percentage of medium (7.56%) and long (3.80%) ROH (Supplementary Table S1), indicating recent ancestral relationships and probably the highest inbreeding. For ecotypes, the Egyptian Baladi showed the lowest average number of ROH, and lowest number of long and medium-length ROH.
A total of 153 within-population consensuses ROH were detected with 41, 49, 35, and 28 in Baladi, Dandarawi, Fayoumi, and Rwanda-Uganda populations, respectively. Consensus ROHs were found on Chromosomes 3, 5, and 8 in Rwanda-Uganda; 2, 3, 4, 8, and 11 in Fayoumi; 1, 4, and 8 in Dandarawi; and 2, 3, 8, and 11 in Baladi (Supplementary Figure S1).
The number of genes enriched and annotated within the overlapping consensus ROH was 62, 33, 72, and 29 genes for Baladi, Dandarawi, Fayoumi, and Rwanda-Uganda populations, respectively. The total 196 genes located on the consensus 153 ROH regions were used for detecting over-enriched GO terms.
Genes annotated within ROH and enriched GO terms reflected a common signature of selection for energy generation and transport; and ion binding in both the East-African (Rwanda-Uganda) and North-African (Fayoumi and Dandarawi) chicken populations studied.
