London School of Hygiene and Tropical Medicine, WC1E 7HT, London, UK, Wellcome Trust Sanger Institute, CB10 1SA, Hinxton, UK and Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Box 30096 BT3, Blantyre, Malawia.
Bioinformatics. 2014 May 1;30(9):1292-4. doi: 10.1093/bioinformatics/btu005. Epub 2014 Jan 17.
Individuals living in endemic areas generally harbour multiple parasite strains. Multiplicity of infection (MOI) can be an indicator of immune status and transmission intensity. It has a potentially confounding effect on a number of population genetic analyses, which often assume isolates are clonal. Polymerase chain reaction-based approaches to estimate MOI can lack sensitivity. For example, in the human malaria parasite Plasmodium falciparum, genotyping of the merozoite surface protein (MSP1/2) genes is a standard method for assessing MOI, despite the apparent problem of underestimation. The availability of deep coverage data from massively parallizable sequencing technologies means that MOI can be detected genome wide by considering the abundance of heterozygous genotypes. Here, we present a method to estimate MOI, which considers unique combinations of polymorphisms from sequence reads. The method is implemented within the estMOI software. When applied to clinical P.falciparum isolates from three continents, we find that multiple infections are common, especially in regions with high transmission.
生活在流行地区的个体通常携带多种寄生虫株。感染的多重性（MOI）可以作为免疫状态和传播强度的指标。它对许多群体遗传分析有潜在的混杂影响，这些分析通常假设分离物是克隆的。基于聚合酶链反应的方法来估计 MOI 可能缺乏敏感性。例如，在人类疟疾寄生虫恶性疟原虫中，对裂殖子表面蛋白（MSP1/2）基因进行基因分型是评估 MOI 的标准方法，尽管存在低估的明显问题。大规模并行测序技术提供了深度覆盖数据，这意味着通过考虑杂合基因型的丰度，可以在全基因组范围内检测 MOI。在这里，我们提出了一种估计 MOI 的方法，该方法考虑了来自序列读数的多态性的独特组合。该方法在 estMOI 软件中实现。当应用于来自三大洲的临床恶性疟原虫分离物时，我们发现多重感染很常见，尤其是在传播率高的地区。
