Livestock phenomics and genetic evaluation approaches in Africa: current state and future perspectives.

The African livestock sector plays a key role in improving the livelihoods of people through the supply of food, improved nutrition and consequently health. However, its impact on the economy of the people and contribution to national GDP is highly variable and generally below its potential. This study was conducted to assess the current state of livestock phenomics and genetic evaluation methods being used across the continent, the main challenges, and to demonstrate the effects of various genetic models on the accuracy and rate of genetic gain that could be achieved. An online survey of livestock experts, academics, scientists, national focal points for animal genetic resources, policymakers, extension agents and animal breeding industry was conducted in 38 African countries. The results revealed 1) limited national livestock identification and data recording systems, 2) limited data on livestock production and health traits and genomic information, 3) mass selection was the common method used for genetic improvement with very limited application of genetic and genomic-based selection and evaluation, 4) limited human capacity, infrastructure, and funding for livestock genetic improvement programmes, as well as enabling animal breeding policies. A joint genetic evaluation of Holstein-Friesian using pooled data from Kenya and South Africa was piloted. The pilot analysis yielded higher accuracy of prediction of breeding values, pointing to possibility of higher genetic gains that could be achieved and demonstrating the potential power of multi-country evaluations: Kenya benefited on the 305-days milk yield and the age at first calving and South Africa on the age at first calving and the first calving interval. The findings from this study will help in developing harmonized protocols for animal identification, livestock data recording, and genetic evaluations (both national and across-countries) as well as in designing subsequent capacity building and training programmes for animal breeders and livestock farmers in Africa. National governments need to put in place enabling policies, the necessary infrastructure and funding for national and across country collaborations for a joint genetic evaluation which will revolutionize the livestock genetic improvement in Africa.

Selection Signature Analyses Revealed Genes Associated With Adaptation, Production, and Reproduction in Selected Goat Breeds in Kenya.

Artificial and natural selection in livestock is expected to leave unique footprints on their genomes. Goat breeds in Kenya have evolved for survival, breeding, and production in various harsh ecological areas, and their genomes are likely to have acquired unique alleles for adaptation to such diverse production environments and other traits of economic importance. To investigate signals of selection for some selected goat breeds in Kenya, Alpine (n = 29), Galla (n = 12), Saanen (n = 24), and Toggenburg (n = 31) were considered. A total of 53,347 single-nucleotide polymorphisms (SNPs) generated using the Illumina GoatSNP50 BeadChip were analyzed. After quality control, 47,663 autosomal single-nucleotide polymorphisms remained for downstream analyses. Several complementary approaches were applied for the following analyses: integrated Haplotype Score (iHS), cross-population-extended haplotype homozygosity (XP-EHH), hapFLK, and FLK. A total of 404 top genomic regions were identified across all the four breeds, based on the four complementary analyses. Out of the 16 identified putative selection signature regions by the intersection of multiple-selective signal analyses, most of the putative regions were found to overlap significantly with the iHS and XP-EHH analyses on chromosomes 3, 4, 10, 15, 22, and 26. These regions were enriched with some genes involved in pathways associated directly or indirectly with environmental adaptation regulating immune responses (e.g., HYAL1 and HYAL3), milk production (e.g., LEPR and PDE4B), and adaptability (e.g., MST1 and PCK). The results revealed few intersect between breeds in genomic selection signature regions. In general, this did not present the typical classic selection signatures as predicted due to the complex nature of the traits. The results support that some various selection pressures (e.g., environmental challenges, artificial selection, and genome admixture challenges) have molded the genome of goat breeds in Kenya. Therefore, the research provides new knowledge on the conservation and utilization of these goat genetic resources in Kenya. In-depth research is needed to detect precise genes connected with adaptation and production in goat breeds in Kenya.

Breeding objectives for indigenous chicken: model development and application to different production systems.

A bio-economic model was developed to evaluate the utilisation of indigenous chickens (IC) under different production systems accounting for the risk attitude of the farmers. The model classified the production systems into three categories based on the level of management: free-range system (FRS), where chickens were left to scavenge for feed resources with no supplementation and healthcare; intensive system (IS), where the chickens were permanently confined and supplied with rationed feed and healthcare; and semi-intensive system (SIS), a hybrid of FRS and IS, where the chickens were partially confined, supplemented with rationed feeds, provided with healthcare and allowed to scavenge within the homestead or in runs. The model allows prediction of the live weights and feed intake at different stages in the life cycle of the IC and can compute the profitability of each production system using both traditional and risk-rated profit models. The input parameters used in the model represent a typical IC production system in developing countries but are flexible and therefore can be modified to suit specific situations and simulate profitability and costs of other poultry species production systems. The model has the capability to derive the economic values as changes in the genetic merit of the biological parameter results in marginal changes in profitability and costs of the production systems. The results suggested that utilisation of IC in their current genetic merit and production environment is more profitable under FRS and SIS but not economically viable under IS.

Application of risk-rated profit model functions in estimation of economic values for indigenous chicken breeding.

The economic values for productive (egg number, average daily gain, live weight, and mature weight) and functional (fertility, hatchability, broodiness, survival rate, feed intake, and egg weight) traits were derived for three production systems utilizing indigenous chicken in Kenya. The production systems considered were free-range, semi-intensive, and intensive system and were evaluated based on fixed flock size and fixed feed resource production circumstances. A bio-economic model that combined potential performances, feeding strategies, optimum culling strategies, farmer's preferences and accounted for imperfect knowledge concerning risk attitude of farmers and economic dynamics was employed to derive risk-rated economic values. The economic values for all the traits were highest in free-range system under the two production circumstances and decreased with level of intensification. The economic values for egg number, average daily gain, live weight, fertility, hatchability, and survival rate were positive while those for mature weight, broodiness, egg weight, and feed intake were negative. Generally, the economic values estimated under fixed feed resource production circumstances were higher than those derived under fixed flock size. The difference between economic values estimated using simple (traditional) and risk-rated profit model functions ranged from -47.26% to +67.11% indicating that inclusion of risks in estimation of economic values is important. The results of this study suggest that improvement targeting egg number, average daily gain, live weight, fertility, hatchability, and survival rate would have a positive impact on profitability of indigenous chicken production in Kenya.

Characterization of indigenous chicken production systems in Kenya.

Indigenous chicken (IC) and their production systems were characterized to understand how the whole system operates for purposes of identifying threats and opportunities for holistic improvement. A survey involving 594 households was conducted in six counties with the highest population of IC in Kenya using structured questionnaires. Data on IC farmers' management practices were collected and analysed and inbreeding levels calculated based on the effective population size. Indigenous chicken were ranked highest as a source of livestock income by households in medium- to high-potential agricultural areas, but trailed goats in arid and semi-arid areas. The production system practised was mainly low-input and small-scale free range, with mean flock size of 22.40 chickens per household. The mean effective population size was 16.02, translating to high levels of inbreeding (3.12%). Provision for food and cash income were the main reasons for raising IC, whilst high mortality due to diseases, poor nutrition, housing and marketing channels were the major constraints faced by farmers. Management strategies targeting improved healthcare, nutrition and housing require urgent mitigation measures, whilst rural access road network needs to be developed for ease of market accessibility. Sustainable genetic improvement programmes that account for farmers' multiple objectives, market requirements and the production circumstances should be developed for a full realization of IC productivity.

Economic evaluation of breeding strategies for improvement of dairy cattle in Kenya.

Cost-benefit analysis using net present value (NPV) as the economic evaluation criterion was used to investigate the economic merits of four breeding strategies used for genetic improvement of dairy cattle in Kenya. The breeding strategies were evaluated over a 25-year period. The costs involved in setting up and running each strategy were obtained from large-scale dairy cattle farms, and government and private institutions involved in genetic improvement of dairy cattle. Only benefits from genetic improvement were considered. The impact on NPV due to changes in genetic and economic parameters was investigated. The ranking of the breeding strategies greatly differed with genetic ranking. Among the local selection programs, a strategy utilizing young bulls, sons of local bulls, was more profitable than one utilizing old progeny tested bulls. Continuous semen importation was not an economically viable alternative. The strategy utilizing young bulls progeny of imported bulls (PIB) was only viable if imports were from countries which are >2.00 SD in genetic merit above the local dairy cattle population. The ranking of strategies was not sensitive to changes in genetic parameters but to economic parameters. The use of local semen from young bulls progeny of local proven bulls is recommended. Alternatively, PIB can be utilized but the semen will have to be imported from countries which are >2.00 SD above the local dairy cattle population or the cost of imported semen should be < or = US$40 per straw.

Genetic evaluation of breeding strategies for improvement of dairy cattle in Kenya.

A deterministic approach was used to compare breeding strategies utilizing local and imported semen for improvement of dairy cattle in Kenya. The local selection programs considered were a closed progeny testing scheme (CPT) and a young bull system progeny of local bulls (PLB). The continuous semen importation (CSI) and young bull system progeny of imported bulls (PIB) were the strategies based on imports. The breeding strategies were compared on the basis of selection response. The effect of genetic correlation (r(g)) and initial differences in genetic merit between the two populations was also examined. The CSI and PIB strategies ranked above CPT by, correspondingly, 35.1% and 25.0% when the r(g) between Kenya and the USA was assumed to be one. At a r(g) of 0.58, imports from countries which are 1.50 standard deviation (SD) above the local population were superior to CPT but equal to PLB. This means that if CSI is to be used at a r(g) of 0.58, then only semen from countries which are >1.50 SD should be imported. At a r(g) of 0.70 and with an initial genetic difference of 1.25 SD, the economic responses in CSI and PLB were equal. This indicates that semen importation is only justified when genotype-environment interaction is >0.70. It is concluded that wholesale importation of semen as a means of achieving sustainable genetic progress in Kenya is a less optimal solution and there is the need for an effective local selection program.