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一种新的基因组规模下重组事件重构方法。

A new method to reconstruct recombination events at a genomic scale.

机构信息

IBE, Institute of Evolutionary Biology (UPF-CSIC), CEXS-UPF-PRBB, Barcelona, Catalonia, Spain.

出版信息

PLoS Comput Biol. 2010 Nov 24;6(11):e1001010. doi: 10.1371/journal.pcbi.1001010.

Abstract

Recombination is one of the main forces shaping genome diversity, but the information it generates is often overlooked. A recombination event creates a junction between two parental sequences that may be transmitted to the subsequent generations. Just like mutations, these junctions carry evidence of the shared past of the sequences. We present the IRiS algorithm, which detects past recombination events from extant sequences and specifies the place of each recombination and which are the recombinants sequences. We have validated and calibrated IRiS for the human genome using coalescent simulations replicating standard human demographic history and a variable recombination rate model, and we have fine-tuned IRiS parameters to simultaneously optimize for false discovery rate, sensitivity, and accuracy in placing the recombination events in the sequence. Newer recombinations overwrite traces of past ones and our results indicate more recent recombinations are detected by IRiS with greater sensitivity. IRiS analysis of the MS32 region, previously studied using sperm typing, showed good concordance with estimated recombination rates. We also applied IRiS to haplotypes for 18 X-chromosome regions in HapMap Phase 3 populations. Recombination events detected for each individual were recoded as binary allelic states and combined into recotypes. Principal component analysis and multidimensional scaling based on recotypes reproduced the relationships between the eleven HapMap Phase III populations that can be expected from known human population history, thus further validating IRiS. We believe that our new method will contribute to the study of the distribution of recombination events across the genomes and, for the first time, it will allow the use of recombination as genetic marker to study human genetic variation.

摘要

重组是塑造基因组多样性的主要力量之一,但它所产生的信息经常被忽视。重组事件在两个亲本序列之间创建一个连接,该连接可能会传递给后代。就像突变一样,这些连接携带序列共享过去的证据。我们提出了 IRiS 算法,该算法可以从现存序列中检测过去的重组事件,并指定每个重组事件的位置以及重组序列。我们使用复制标准人类人口历史和可变重组率模型的合并模拟对人类基因组进行了验证和校准,并且我们对 IRiS 参数进行了微调,以同时优化在序列中放置重组事件的假发现率、灵敏度和准确性。较新的重组会覆盖过去重组的痕迹,我们的结果表明,IRiS 对较新的重组具有更高的灵敏度。使用精子分型对 MS32 区域进行的 IRiS 分析与估计的重组率具有良好的一致性。我们还将 IRiS 应用于 HapMap Phase 3 人群中的 18 个 X 染色体区域的单倍型。为每个人检测到的重组事件被重新编码为二元等位基因状态,并组合成 recotypes。基于 recotypes 的主成分分析和多维缩放再现了从已知人类种群历史可以预期的十一个 HapMap Phase III 种群之间的关系,从而进一步验证了 IRiS。我们相信我们的新方法将有助于研究基因组中重组事件的分布,并且首次可以使用重组作为遗传标记来研究人类遗传变异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c61d/2991245/f50ac75118e4/pcbi.1001010.g001.jpg

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