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Landscape genomics reveal signatures of local adaptation in barley ( Hordeum vulgare L.)

机译:景观基因组学揭示了大麦局部适应的签名(<斜视> Hordeum Vulgare L.)

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Land plants are sessile organisms that cannot escape the adverse climatic conditions of a given environment. Hence, adaptation is one of the solutions to surviving in a challenging environment. This study was aimed at detecting adaptive loci in barley landraces that are affected by selection. To that end, a diverse population of barley landraces was analyzed using the genotyping by sequencing approach. Climatic data for altitude, rainfall and temperature were collected from 61 weather sites near the origin of selected landraces across Ethiopia. Population structure analysis revealed three groups whereas spatial analysis accounted significant similarities at shorter geographic distances (< 40 Km) among barley landraces. Partitioning the variance between climate variables and geographic distances indicated that climate variables accounted for most of the explainable genetic variation. Markers by climatic variables association analysis resulted in altogether 18 and 62 putative adaptive loci using Bayenv and latent factor mixed model (LFMM), respectively. Subsequent analysis of the associated SNPs revealed putative candidate genes for plant adaptation. This study highlights the presence of putative adaptive loci among barley landraces representing original gene pool of the farming communities.
机译:土地植物是无柄生物,不能逃避给定环境的不利气候条件。因此,适应是在挑战环境中存活的解决方案之一。本研究旨在检测受选择影响的大麦地体的自适应基因座。为此,通过测序方法使用基因分型分析了各种大麦体重体的群体。从埃塞俄比亚的选定地位的起源附近的61个天气部位收集了海拔高度,降雨和温度的气候数据。人口结构分析显示了三组,而空间分析在大麦实地较短的地理距离(<40公里)上占据了重要相似之处。分区气候变量和地理距离之间的差异表明,气候变量占大多数可解释的遗传变异。通过气候变量的标记分析,分别使用BACENV和潜在因子混合模型(LFMM)共18和62个推定的自适应基因座。相关SNP的后续分析显示了植物适应的推定候选基因。本研究突出了代表农业社区原始基因库的大麦地体积中推定的自适应基因座的存在。

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