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首页> 外文期刊>Genome research >The prion protein gene in humans revisited: lessons from a worldwide resequencing study.
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The prion protein gene in humans revisited: lessons from a worldwide resequencing study.

机译:in病毒蛋白基因在人类中的应用:一项全球测序研究的经验教训。

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Ample evidence has accumulated showing that different coding variants of the PRNP gene confer differential susceptibility for prion diseases. Here we evaluate the patterns of nucleotide variation in PRNP exon 2, which includes all the protein-coding sequence, by resequencing a worldwide sample of 174 humans for 2378 bp. In line with previous studies, we found two main haplotypes differentiated by nonsynonymous substitution in codon 129. Our analyses reveal the worldwide pattern of variation at the PRNP gene to be inconsistent with neutral expectations, indicating instead an excess of low-frequency variants, a footprint of the action of either positive or purifying selection. A comparison of neutrality test statistics for PRNP with other human genes indicates that the signal of positive selection on PRNP is stronger than expected from a possible confounding genome-wide background signal of population expansion. Two main conclusions arise from our analysis. First, the existence of an ancient, stable, balanced polymorphism that has been claimed in a previous study and related to cannibalism can be rejected and is shown to be due to ascertainment bias. Second, our results are consistent with a complex history of selection including mainly positive selection, even if short local periods of balancing selection (Kuru-like episodes), or even a weak purifying selection model, are consistent with our data.
机译:大量证据表明,PRNP基因的不同编码变体赋予了con病毒疾病不同的敏感性。在这里,我们通过对174个人的全球样本重新测序2378 bp,来评估PRNP外显子2中核苷酸变异的模式,其中包括所有蛋白质编码序列。与先前的研究一致,我们发现了两个主要的单倍型,它们通过129密码子的非同义替换来区分。我们的分析显示,PRNP基因的全球变异模式与中性预期不一致,表明存在过多的低频变异,一个足迹积极选择或净化选择的作用。 PRNP与其他人类基因的中立性测试统计数据的比较表明,PRNP上的阳性选择信号比可能由混杂的全基因组人口扩张背景信号所预期的强。我们的分析得出两个主要结论。首先,在先前的研究中声称存在的与食人症有关的古老,稳定,平衡的多态性可以被拒绝,并被证明是由于确定性偏见所致。其次,我们的结果与复杂的选择历史相吻合,即使主要是积极选择,即使本地平衡选择的短期时间(库鲁样事件),甚至是较弱的净化选择模型都与我们的数据一致。

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