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Background Free-range local chickens (FRLC) farming is an important activity in Tanzania, however, they have not been well-characterized. This study aimed to phenotypically characterize three Tanzanian FRLCs and to determine their population structure. A total of 389 mature breeder chickens (324 females and 65 males) from three popular Tanzanian FRLC ecotypes (Kuchi, Morogoro-medium and Ching’wekwe) were used for the phenotypic characterization. Progenies of these chickens were utilized to assess population structure. The ecotypes were collected from four geographical zones across Tanzania: Lake, Central, Northern and Coastal zones. Body weights and linear measurements were obtained from the mature breeders, including body, neck, shanks, wingspan, chest girth, and shank girth. Descriptive statistics were utilized to characterize the chickens. Correlations between the linear measurements and differences among the means of measured linear traits between ecotypes and between sexes were assessed. A total of 1399 progeny chicks were genotyped using a chicken 600 K high density single nucleotide polymorphism (SNP) panel for determination of population structure. Results The means for most traits were significantly higher in Kuchi relative to Ching’wekwe and Morogoro-medium. However, shank length and shank girth were similar between Kuchi and Morogoro-medium females. All traits were correlated with the exception of shank girth in Morogoro-medium. Admixture analyses revealed that Morogoro-medium and Ching’wekwe clustered together as one population, separate from Kuchi. Conclusions Phenotypic traits could be used to characterize FRLCs, however, there were variations in traits among individuals within ecotypes; therefore, complementary genomic methods should be considered to improve the characterization for selective breeding.

Three guinea fowl populations from Northern Ghana were compared in terms of their body weight, growth rates, and survivability during the first 11 weeks of life. Keets (n = 865) were hatched from eggs collected from 32 sampling areas divided into eleven subpopulations within three populations in Northern Ghana. Together with an experimental flock maintained at Animal Research Institute (ARI flock), these birds were raised and appraised for weekly body weights, weekly growth rates, and survivability. Weekly body weights did not differ significantly (p > 0.05) among the three populations, although ARI flock were significantly heavier (p ˂ 0.05) compared to the main populations until the fourth week. In contrast, among the subpopulations, significant differences emerged in body weights from the second week and were more pronounced from the sixth week. Growth rates measured as weekly weight gains also differed significantly among subpopulations beyond the second week, although differences in growth rates were not significantly different among whole populations. The mean values for total feed intake, daily feed intake, and feed conversion ratio (FCR) did not vary significantly (p > 0.05) between the populations. Therefore, although the variations in body weight and growth rates were limited among the populations, there existed significant variations among subpopulations, creating opportunities to establish genetically divergent populations for growth rate and to improve early growth rates and body weights in local guinea fowls by selection. High survivability observed in the ARI flock compared to keets from the three populations of Northern Ghana was likely due to good breeder stock management practices despite their common ancestry.

Crossbreeding is practiced extensively in commercial breeding programs of many plant and animal species, in order to exploit heterosis, breed complementarity, and to protect pure line genetic material. The success of commercial crossbreeding schemes depends on identifying and using the right combination of breeds, lines or varieties that produce the desired crossbred offspring. Currently, the selection of pure lines is based on the results of “field tests”, during which the performance of their crossbreds is assessed under typical commercial settings. Field tests are time-consuming, and also constitute a large percent of the costs of commercial crossbreeding programs. The research in this thesis therefore set out mainly to develop models for the accurate prediction of heterosis in White Leghorn crossbreds, using genomic information from their parental pure lines. Predicted heterosis could be used as pre-selection criteria, thus substantially reducing the number of crosses that need to be field-tested. In Chapter 1, I give an overview of the history of selective breeding in laying hens, and introduce heterosis and its genetic basis. In Chapter 2, based on a dominance model, we showed that a genome-wide squared difference in allele frequency between parental pure lines (SDAF) predicts heterosis in egg number (EN) and egg weight (EW) at the line level with an accuracy of ~0.5. With this accuracy, one can reduce the number of field tests by 50%, with only ~4 loss in realised heterosis. In laying hens, selection pressure is highest on the sires. We therefore went further to develop a model to predict heterosis at the individual sire level, in order to exploit the variation between sires from the same line. We found that the within-line variation between sires in our data was very small (0.7% of the variation in predicted heterosis), and most of the variation was explained by across-line differences (90%) (Chapter 3). Quantitative genetic theory shows that heterosis is proportional to SDAF and the dominance effect at a locus. In Chapter 4, we estimated variance components and dominance effects of single nucleotide polymorphisms (SNPs) on EN and EW in White Leghorn pure lines. We found that dominance variance accounted for up to 37% of the genetic variance in EN, and up to 4% of that in EW. We then used the estimated dominance effects to calculate dominance-weighted SDAFs for EN and EW between parental pure lines, and showed that prediction of heterosis based on a weighted SDAF would yield considerably different ranking of crosses for each trait, compared with a prediction based on the raw SDAF. This implies that different crosses would be selected depending on the criterion used to predict heterosis. To gain an insight into the genetic architecture of EN and EW, in Chapter 5 we performed genome-wide association studies using data on 16 commercial crossbred populations. We did not identify any significant SNPs for EN, indicating that EN is a highly polygenic trait with no large quantitative trait loci segregating in the populations studied. For EW, however, we identified several significant SNPs. One explanation for these results is that EN has been under intense directional selection for several decades, whereas EW has been under less-intense, stabilising selection. Finally, in the general discussion of this thesis (Chapter 6), I discuss the genomic prediction of heterosis, focusing on possible reasons for the lack of a consensus on the approach to predict heterosis, even after decades of research. I also discuss new opportunities for the genomic prediction of heterosis, considering the advancements in genotyping and computation methods. Lastly, I give an example of the application of results from this thesis in crossbreeding programs.

Newcastle Disease (ND) is a continuing global threat to domestic poultry, especially in developing countries, where severe outbreaks of velogenic ND virus (NDV) often cause major economic losses to households. Local chickens are of great importance to rural family livelihoods through provision of high-quality protein. To investigate the genetic basis of host response to NDV, three popular Tanzanian chicken ecotypes (regional populations) were challenged with a lentogenic (vaccine) strain of NDV at 28 days of age. Various host response phenotypes, including anti-NDV antibody levels (pre-infection and 10 days post-infection, dpi), and viral load (2 and 6 dpi) were measured, in addition to growth rate. We estimated genetic parameters and conducted genome-wide association study analyses by genotyping 1399 chickens using the Affymetrix 600K chicken SNP chip. Estimates of heritability of the evaluated traits were moderate (0.18&ndash, 0.35). Five quantitative trait loci (QTL) associated with growth and/or response to NDV were identified by single-SNP analyses, with some regions explaining &ge, 1% of genetic variance based on the Bayes-B method. Immune related genes, such as ETS1, TIRAP, and KIRREL3, were located in regions associated with viral load at 6 dpi. The moderate estimates of heritability and identified QTL indicate that NDV response traits may be improved through selective breeding of chickens to enhance increased NDV resistance and vaccine efficacy in Tanzanian local ecotypes.

Prediction of heterosis has a long history with mixed success, partly due to low numbers of genetic markers and/or small data sets. We investigated the prediction of heterosis for egg number, egg weight and survival days in domestic white Leghorns, using ∼400 000 individuals from 47 crosses and allele frequencies on ∼53 000 genome-wide single nucleotide polymorphisms (SNPs). When heterosis is due to dominance, and dominance effects are independent of allele frequencies, heterosis is proportional to the squared difference in allele frequency (SDAF) between parental pure lines (not necessarily homozygous). Under these assumptions, a linear model including regression on SDAF partitions crossbred phenotypes into pure-line values and heterosis, even without pure-line phenotypes. We therefore used models where phenotypes of crossbreds were regressed on the SDAF between parental lines. Accuracy of prediction was determined using leave-one-out cross-validation. SDAF predicted heterosis for egg number and weight with an accuracy of ∼0.5, but did not predict heterosis for survival days. Heterosis predictions allowed preselection of pure lines before field-testing, saving ∼50% of field-testing cost with only 4% loss in heterosis. Accuracies from cross-validation were lower than from the model-fit, suggesting that accuracies previously reported in literature are overestimated. Cross-validation also indicated that dominance cannot fully explain heterosis. Nevertheless, the dominance model had considerable accuracy, clearly greater than that of a general/specific combining ability model. This work also showed that heterosis can be modelled even when pure-line phenotypes are unavailable. We concluded that SDAF is a useful predictor of heterosis in commercial layer breeding.