From local records to global impact: Integrating farmer-led data and genomics in livestock systems for LMICs

Sustainable improvement of livestock in low and middle-income countries (LMICs) depends on breeding strategies that effectively balance increased productivity with resilience, and the preservation of genetic diversity over time. In the absence of centralised recording systems, information gathered through veterinary visits and directly from farmers is often the only source of usable data. Therefore, the development and maintenance of farmer-led databases are essential for capturing and retaining this information, also empowering farmers to participate directly in breeding decisions.<br/>We recently showed the usefulness of such databases by integrating them with genomic data from both crossbred and purebred dairy cattle in Kampala, Uganda. Using high-density SNP genotypes from crossbred, exotic and indigenous animals, we characterised population structure, admixture patterns, genetic diversity, and inbreeding, and linked these genomic insights to disease records collected through a farmer-led digital platform. Ugandan crossbred cattle exhibited high levels of exotic introgression, primarily from Holstein and Jersey breeds, alongside lower levels of homozygosity and inbreeding compared with indigenous or intensively selected exotic populations. While this genetic diversity reflects recent crossbreeding practices aimed at improving productivity, it also implies substantial heterogeneity among animals and potential maladaptation, underscoring the need for informed, locally adapted breeding strategies.<br/>We also explored associations between breed composition and disease occurrence in crossbred animals. Although our statistical power was constrained by limited sample size and unbalanced disease records, we observed clear evidence of survivor bias for East Coast fever, a lethal disease to exotic cattle. Animals with higher levels of exotic ancestry were strongly under-represented among recorded cases, likely because the most susceptible individuals had already been infected and died before sampling. This highlights the need for farmer-led data collection that is both systematic and longitudinal; without it, inferences about disease risk and breed suitability may be misleading, especially in high pressure environments.<br/>In summary, farmer-led databases combined with genomics provide cost-effective tools to improve understanding of genetic susceptibility to disease in imported or admixed livestock populations, strengthening global biosecurity and resilience.<br/>