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人口遗传结构在社会景观中:传统埃塞俄比亚农业系统中的大麦。

Population genetic structure in a social landscape: barley in a traditional Ethiopian agricultural system.

机构信息

University of California Santa Cruz, CA, USA.

University of Montana Missoula, MT, USA.

出版信息

Evol Appl. 2013 Dec;6(8):1133-45. doi: 10.1111/eva.12091. Epub 2013 Aug 12.

Abstract

Conservation strategies are increasingly driven by our understanding of the processes and patterns of gene flow across complex landscapes. The expansion of population genetic approaches into traditional agricultural systems requires understanding how social factors contribute to that landscape, and thus to gene flow. This study incorporates extensive farmer interviews and population genetic analysis of barley landraces (Hordeum vulgare) to build a holistic picture of farmer-mediated geneflow in an ancient, traditional agricultural system in the highlands of Ethiopia. We analyze barley samples at 14 microsatellite loci across sites at varying elevations and locations across a contiguous mountain range, and across farmer-identified barley types and management strategies. Genetic structure is analyzed using population-based and individual-based methods, including measures of population differentiation and genetic distance, multivariate Principal Coordinate Analysis, and Bayesian assignment tests. Phenotypic analysis links genetic patterns to traits identified by farmers. We find that differential farmer management strategies lead to markedly different patterns of population structure across elevation classes and barley types. The extent to which farmer seed management appears as a stronger determinant of spatial structure than the physical landscape highlights the need for incorporation of social, landscape, and genetic data for the design of conservation strategies in human-influenced landscapes.

摘要

保护策略越来越受到我们对跨越复杂景观的基因流动过程和模式的理解的驱动。将群体遗传学方法扩展到传统农业系统需要了解社会因素如何促成该景观,从而促成基因流动。本研究通过对大麦地方品种(Hordeum vulgare)进行广泛的农民访谈和群体遗传学分析,构建了埃塞俄比亚高地一个古老的传统农业系统中农民介导的基因流动的整体图景。我们在 14 个微卫星基因座上分析了大麦样本,这些样本分布在连续山脉的不同海拔和位置的地点,以及农民确定的大麦品种和管理策略。使用基于群体和基于个体的方法分析遗传结构,包括种群分化和遗传距离的度量、多元主坐标分析和贝叶斯分配测试。表型分析将遗传模式与农民确定的特征联系起来。我们发现,不同的农民管理策略导致不同的种群结构模式,跨越海拔等级和大麦类型。农民种子管理似乎比物理景观更能决定空间结构的程度,这突出了需要将社会、景观和遗传数据纳入受人类影响的景观中的保护策略设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d88d/3901544/978698f00644/eva0006-1133-f1.jpg

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