Detection of selection signatures in indigenous African cattle reveals genomic footprints of adaptation, production and temperament traits

Abstract

Indigenous cattle account for approximately 80% of Uganda’s cattle population. These animals are well adapted to the country’s ten agroecological zones and are mainly kept under pastoral and agropastoral systems. Unlike commercial breeds, they thrive on low-quality feeds, while tolerating major tropical diseases and parasites including tsetse flies, ticks, and vector-borne infections. Whole-genome sequence (WGS) analysis offers opportunities to uncover genomic regions underlying these adaptations and to trace the genetic footprints of long-term breeding decisions taken by cattle keepers. In this study, WGS data from 95 animals representing six indigenous cattle populations (Ankole, Karamojong, Nganda10, Nganda17, Nkedi, and Ntuku) were analyzed to identify genomic regions under putative selection. Two complementary approaches were applied: enumeration of the µ-statistic in RAiSD and runs of homozygosity (ROH) analysis. RAiSD identified population-level signals, while conserved ROH regions were defined using breed-specific SNP-incidence thresholds. The two methods identified 803 and 49 candidate genes respectively. The top genes identified included SLC37A1 (BTA1), CHCHD3 (BTA4), and RAB3GAP1 (BTA2) detected by RAiSD, and IL26 (BTA5), FBXL7 (BTA20), and HSPA9 (BTA7) contained in ROH. Furthermore, the regions harbored 107 novel genes (92 detected by RAiSD and 15 by ROH), corresponding to 255 quantitative trait loci. The identified genes under putative selection are associated with economically important traits including adaptation to tropical environments, resistance to parasites and diseases, and other farmer-preferred characteristics. These findings provide insights into the genetic basis of adaptation, selection and production in Ugandan indigenous cattle, supporting conservation and breeding strategies to enhance resilience and productivity.