Why Breeding Values Estimated Using Familial Data Should Not Be Used for Genome-Wide Association Studies

In animal breeding, the genetic potential of an animal is summarized as its estimated breeding value, which is derived from its own performance as well as the performance of related individuals. Here, we illustrate why estimated breeding values are not suitable as a phenotype for genome-wide association studies. We simulated human-type and pig-type pedigrees with a range of quantitative trait loci (QTL) effects (0.5–3% of phenotypic variance) and heritabilities (0.3−0.8). We analyzed 1000 replicates of each scenario with four models: (a) a full mixed model including a polygenic effect, (b) a regression analysis using the residual of a mixed model as a trait score (so called GRAMMAR approach), (c) a regression analysis using the estimated breeding value as a trait score, and (d) a regression analysis that uses the raw phenotype as a trait score. We show that using breeding values as a trait score gives very high false-positive rates (up 14% in human pedigrees and >60% in pig pedigrees). Simulations based on a real pedigree show that additional generations of pedigree increase the type I error. Including the family relationship as a random effect provides the greatest power to detect QTL while controlling for type I error at the desired level and providing the most accurate estimates of the QTL effect. Both the use of residuals and the use of breeding values result in deflated estimates of the QTL effect. We derive the contributions of QTL effects to the breeding value and residual and show how this affects the estimates

Testing phenotypes for degree of resilience using fluctuations in milk yield of dairy cows in sub-Saharan Africa

Despite the relevance of dairy production in the fight against food insecurity and unemployment in sub-Saharan Africa (SSA), negative effects of climate change and general changes in the production environment pose huge challenges to its profitability. Thus, there is a need to improve resilience capacity of dairy animals to adapt to this changing environment. In the current study, we tested two indicators of resilience, logtransformed variance (LnVar) and Skewness (Skew) of deviation, based on fluctuations in animals’ milk yield. Further, we assessed the effects of genotype, agroecological zone, and genotype by agroecological zone (G×E) interaction for these phenotypes. Cows with less than 50% of exotic genetics had higher degree of resilience (P<0.05). Cows performing in semi-arid zones had higher resilience capacity compared to those in semi-humid environment (P<0.05). G×E did not significantly influence both indicators. The results provide valuable information that would inform dairy cattle improvement initiatives in SSA

Enhancing individual animal resilience to environmental disturbances to address low productivity in dairy cattle performing in sub-Saharan Africa

The current review examines potential solutions to enhance the sustainability and productivity of the dairy sector in sub-Saharan Africa (SSA) with an emphasis on breeding for resilience. Additionally, the paper explores various indicators for measuring resilience and provides insights into the data that can be utilized to quantify resilience in SSA’s dairy production systems. Dairy production contributes significantly to food and nutritional security and employment in SSA. However, besides the general lack of enabling policy and institutional environments, production is negatively affected by environmental challenges such as high temperatures and heat stress, diseases and parasites, unreliable rainfall patterns, shortages of feeds and forages and undue preference for taurine cattle breeds regardless of their poor adaptability to prevailing local conditions. Fostering the resilience capacity of dairy animals is imperative to combat climate-related adversities and maintain productivity. This can only be achieved if reliable and practical methods for quantifying and analyzing resilience in SSA are described and undertaken. This study has reviewed variance of deviations, root mean square of deviations, autocorrelation of deviations, skewness of deviations, slope of the reaction norm and its absolute value as possible indicators of resilience in SSA. While previous research has reported genetic variation and favorable correlations of these indicators with health, fitness, and fertility traits, their potential in SSA environments requires further investigation. Besides, labor- and cost-effective phenotypic data collection is essential for characterization of resilience using these indicators. Through this study, we propose frequently collected data on milk production traits, body fat-related traits, and activity patterns as suitable in the sub-Saharan Africa context. The African Asian Dairy Genetic Gains Project by the International Livestock Research Institute (ILRI) offers a valuable opportunity to collate data from diverse dairy systems in SSA for testing the potential of these indicators. Insights from this study are helpful in improving resilience of dairy animals in SSA, which would contribute to poverty alleviation, animal welfare improvement, and better preparedness in lieu of climate change in SSA.</p