5 research outputs found
Data from: Landscape genomics and pathway analysis to understand genetic adaptation of South African indigenous goat populations
Extensively raised livestock populations in most smallholder farming communities are exposed to harsh and heterogeneous climates and disease pathogen that they adapt to in order to survive. Majority of these livestock species including goats are of non-descript breeds and their response to natural selection presented by heterogeneous environments is still unresolved. This study investigated genetic diversity and its association with environmental and geographic conditions in 194 South African indigenous goats from different geographic using Illumina goat SNP50K genotypes. The Tankwa goats formed a homogeneous genetic cluster restricted to the Northern Cape province. Overall, the Boer, Kalahari Red, and Savanna showed a wide geographic spread of shared genetic components whereas the village ecotypes revealed a longitudinal distribution. The relative importance of environmental factors on genetic variation of goat populations was assessed using Redundancy Analysis (RDA).
Variance partitioning using Model I with both climatic and geographic variables explained 22% of the total variation while model II with climatic variables accounted for 17%. Model III, which accounted for geographic variables, explained 1% of the total variation. The first axis (Model I) of the RDA analysis, revealed 329 outlier SNPs. Landscape genomic approaches of Spatial Analysis Method identified a total of 843 (1.75%) SNPs, while Latent Factor Mixed Models identified 714 (1.48%) SNPs significantly associated with environmental variables. Significant markers were within genes involved in biological functions potentially important for environmental adaptation. Overall, the study suggested environmental factors to have some effect in shaping the genetic variation of South African indigenous goat populations