低通全基因组测序和变异填补使用同一性的血统在一个孤立的人类群体
Low-pass Genomewide Sequencing and Variant Imputation Using Identity-by-descent in an Isolated Human Population
摘要：
全基因组测序在一个孤立的人口与少数创始人直接排除变异的人口瓶颈，可能是罕见的其他地方。在这样的人群中，共享的单倍型允许在未测序的样本中估算变异，而不需要像远交群体的研究那样诉诸统计学方法。我们专注于一个孤立的人群队列，从太平洋岛屿的科斯特拉邦，密克罗尼西亚，在那里我们以前收集的SNP阵列和丰富的表型数据的大多数人口。我们报告识别长区域与单倍型共同继承对个人和方法，以利用这种共享的遗传内容进行插补。我们的估计表明，只要对40个个人基因组进行测序，就可以在3,000人的平均基因座队列中进行高达60%的插补。我们确定了来自7个Kosraean个体的全基因组序列的试点数据集，平均覆盖率为5倍。该数据集确定了5，735，306个独特的位点，其中1，212，831个以前未知。此外，这些Kosraen变体与地理邻居相比，在其他人群中罕见的等位基因异常丰富。我们能够利用这七个人之间存在的共享单倍型来估计已知和新型变体的插补准确性，并分别达到99.6%和97.3%的水平。这项研究提出了第一个全基因组分析的一个同质的分离群体，重点是罕见的变异推断。
英文摘要：
Whole-genome sequencing in an isolated population with few founders directly ascertains variants from the population bottleneck that may be rare elsewhere. In such populations, shared haplotypes allow imputation of variants in unsequenced samples without resorting to statistical methods, as in studies of outbred cohorts. We focus on an isolated population cohort from the Pacific Island of Kosrae, Micronesia, where we previously collected SNP array and rich phenotype data for the majority of the population. We report identification of long regions with haplotypes co-inherited between pairs of individuals and methodology to leverage such shared genetic content for imputation. Our estimates show that sequencing as few as 40 personal genomes allows for imputation in up to 60% of the 3,000-person cohort at the average locus. We ascertained a pilot data-set of whole-genome sequences from seven Kosraean individuals, with average 5X coverage. This dataset identified 5,735,306 unique sites of which 1,212,831 were previously unknown. Additionally, these Kosraen variants are unusually enriched for alleles that are rare in other populations when compared to geographic neighbors. We were able to use the presence of shared haplotypes between the seven individuals to estimate imputation accuracy of known and novel variants and achieved levels of 99.6% and 97.3%, respectively. This study presents the first whole-genome analysis of a homogenous isolate population with emphasis on rare variant inference.
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