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.

多数小农经营社区中的粗放养殖畜禽种群，长期暴露于严苛且异质的气候环境与病原微生物之中，为生存需逐步适应此类胁迫。包括山羊在内的多数畜禽类群均为未经系统选育的地方混杂品种，它们对异质环境所施加的自然选择的响应规律仍有待阐明。本研究借助Illumina山羊50K单核苷酸多态性（Single Nucleotide Polymorphism, SNP）基因分型芯片技术，对来自不同地理区域的194只南非本土山羊展开遗传多样性分析，并探究其与环境及地理条件的关联。坦夸山羊（Tankwa goats）形成了单一的遗传聚类群，其分布仅局限于北开普省（Northern Cape province）。总体而言，波尔山羊（Boer）、卡拉哈里红山羊（Kalahari Red）与萨凡纳山羊（Savanna）呈现出广泛的地理分布，且共享大量遗传组分；而乡村生态型山羊则呈现出沿经度梯度的分布模式。本研究采用冗余分析（Redundancy Analysis, RDA），评估了环境因子对山羊种群遗传变异的相对重要性。采用同时纳入气候与地理变量的模型I进行方差分解，可解释总变异的22%；仅纳入气候变量的模型II可解释17%的总变异；而仅纳入地理变量的模型III仅解释了1%的总变异。RDA分析的第一轴（模型I）共鉴定出329个异常单核苷酸多态性位点。空间分析方法（Spatial Analysis Method）这一景观基因组学手段共鉴定出843个（占总位点的1.75%）与环境变量显著关联的单核苷酸多态性位点；而潜因子混合模型（Latent Factor Mixed Models）则鉴定出714个（占总位点的1.48%）此类位点。这些显著关联的分子标记均位于参与环境适应性相关生物学功能的基因内部。综上，本研究表明环境因子在塑造南非本土山羊种群的遗传变异过程中发挥了一定作用。