ArticleHeredity2018
Landscape genomics and pathway analysis to understand genetic adaptation of South African indigenous goat populations.
Article in Heredity, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Mapping genomic adaptation to environmental heterogeneity in Indian native goat populations through landscape genomics.Mammalian genome : official journal of the International Mammalian Genome Society · 2026Article
- A high-quality chromosome level genome assembly of the South African indigenous Nguni goat (Capra hircus).Scientific data · 2026Article
- Genome-environment association analysis reveals climate-driven adaptation of chickens.Genetics, selection, evolution : GSE · 2025Article
- Integrating SNP data to reveal the adaptive selection features of goat populations in extreme environments.BMC genomics · 2025Article
- Article
- Genomic Analysis of Sarda Sheep Raised at Diverse Temperatures Highlights Several Genes Involved in Adaptations to the Environment and Heat Stress Response.Animals : an open access journal from MDPI · 2024Article
- Landscape genomics reveals genetic signals of environmental adaptation of African wild eggplants.Ecology and evolution · 2024Article
- Selection signatures and landscape genomics analysis to reveal climate adaptation of goat breeds.BMC genomics · 2024Article
- Landscape genomics reveals regions associated with adaptive phenotypic and genetic variation in Ethiopian indigenous chickens.BMC genomics · 2024Article
- Deciphering local adaptation of native Indian cattle (3 Biotech · 2023Article
- Assessment of Genetic Diversity and Conservation in South African Indigenous Goat Ecotypes: A Review.Animals : an open access journal from MDPI · 2022Review
- Carcass Quality Profiles and Associated Genomic Regions of South African Goat Populations Investigated Using Goat SNP50K Genotypes.Animals : an open access journal from MDPI · 2022Article
- Selection signature analysis and genome-wide divergence of South African Merino breeds from their founders.Frontiers in genetics · 2022Article
- Conservation status and historical relatedness of South African communal indigenous goat populations using a genome-wide single-nucleotide polymorphism marker.Frontiers in genetics · 2022Article
- The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock.Animals : an open access journal from MDPI · 2021Review
- The climatic and genetic heritage of Italian goat breeds with genomic SNP data.Scientific reports · 2021Article
- Runs of homozygosity analysis of South African sheep breeds from various production systems investigated using OvineSNP50k data.BMC genomics · 2021Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In Africa, extensively raised livestock populations in most smallholder farming communities are exposed to harsh and heterogeneous climatic conditions and disease pathogens that they adapt to in order to survive. Majority of these livestock species, including goats, are of non-descript and uncharacterized 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 locations genotyped on the Illumina goat SNP50K panel. Population structure analysis revealed a homogeneous genetic cluster of the Tankwa goats, 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). Climatic and geographic variables explained 22% of the total variation while climatic variables alone accounted for 17% of the diversity. Geographic variables solitarily 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 (SAM) identified a total of 843 (1.75%) SNPs, while latent factor mixed models (LFMM) 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. Loci observed to be significant and under selection may be responsible for the adaption of the goat populations to local production systems.
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