ArticleBMC genomics2025
Integrating SNP data to reveal the adaptive selection features of goat populations in extreme environments.
Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Single- and Multi-Trait GWASs Combined with Genetic Parameter Estimation Reveal Candidate Genes for Body Conformation Traits in Sika Deer (Animals : an open access journal from MDPI · 2026Article
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Authors and funding
10 authors.
Funding
Abstract
The frequent occurrence of extreme climate events globally has elevated the requirements for environmental adaptability in livestock and poultry. Some goat populations have shown strong adaptability in specific extreme environments, and their genomes often leave genetic traces of adaptive evolution. This study integrated global goat single nucleotide polymorphism (SNP) chip data and raster data of 11 environmental variables. We retained 162 native goat populations and analyzed the environmental data of their regions. We detected 23 candidate genes related to environmental adaptation using selection signal analysis and genome-environment association analysis. After that, we screened out goat populations in extreme environments based on environmental data. Then, we used three selection signal analysis methods (F
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Registered trials
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