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Genomic and genealogical investigation of the French Canadian founder population structure.

机译:法国加拿大裔创始人人口结构的基因组学和族谱研究。

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Characterizing the genetic structure of worldwide populations is important for understanding human history and is essential to the design and analysis of genetic epidemiological studies. In this study, we examined genetic structure and distant relatedness and their effect on the extent of linkage disequilibrium (LD) and homozygosity in the founder population of Quebec (Canada). In the French Canadian founder population, such analysis can be performed using both genomic and genealogical data. We investigated genetic differences, extent of LD, and homozygosity in 140 individuals from seven sub-populations of Quebec characterized by different demographic histories reflecting complex founder events. Genetic findings from genome-wide single nucleotide polymorphism data were correlated with genealogical information on each of these sub-populations. Our genomic data showed significant population structure and relatedness present in the contemporary Quebec population, also reflected in LD and homozygosity levels. Our extended genealogical data corroborated these findings and indicated that this structure is consistent with the settlement patterns involving several founder events. This provides an independent and complementary validation of genomic-based studies of population structure. Combined genomic and genealogical data in the Quebec founder population provide insights into the effects of the interplay of two important sources of bias in genetic epidemiological studies, unrecognized genetic structure and cryptic relatedness.
机译:表征全球人群的遗传结构对于理解人类历史非常重要,并且对遗传流行病学研究的设计和分析至关重要。在这项研究中,我们检查了遗传结构和远距离的亲缘关系及其对魁北克(加拿大)创始人群的连锁不平衡(LD)和纯合性的程度的影响。在加拿大法属开国人口中,可以使用基因组数据和家谱数据进行此类分析。我们调查了魁北克省七个亚群的140个个体的遗传差异,LD程度和纯合性,这些个体特征以反映复杂创始人事件的不同人口统计学特征为特征。来自全基因组单核苷酸多态性数据的遗传发现与这些亚群中每一个的族谱信息相关。我们的基因组数据显示,当代魁北克人口中存在重要的种群结构和相关性,这也反映在LD和纯合水平上。我们扩展的家谱数据证实了这些发现,并表明这种结构与涉及多个创始人事件的定居模式是一致的。这提供了基于基因组的种群结构研究的独立和补充性验证。魁北克创始人群体中的基因组数据和家谱数据相结合,提供了洞悉遗传流行病学研究中两个重要偏见源,无法识别的遗传结构和隐秘关联性之间相互作用的影响的见解。

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