A heuristic method for fast and accurate phasing and imputation of single nucleotide polymorphism data in bi-parental plant populations
A heuristic method for fast and accurate phasing and imputation of single nucleotide polymorphism data in bi-parental plant populations
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双亲植物群体中单核苷酸多态性数据快速准确定相和插补的启发式方法
DOI：
10.1101/330027
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Gonen S
中科院分区：
文献类型：
--
作者：
Gonen S
【摘要】建立了一种新的快速准确的双亲本植物二倍体群体SNP芯片基因型的分期和植入方法。摘要本文提出了一种新的启发式方法，用于二倍体植物物种基因组数据的相位和输入。我们的方法，称为AlphaPlantImpute，明确利用植物育种计划的特点，以最大限度地提高输入的准确性。其特点是亲本数量少，可以近交，通常具有高密度的基因组数据，并且很少有将亲本和焦点个体分离的低密度重组（即后代是代入目标）。AlphaPlantImpute大致分为三个步骤。首先，它在父母身上识别出信息丰富的低密度基因型标记。其次，它跟踪亲本等位基因和单倍型的遗传，并在信息标记上聚焦个体。最后，利用这些低密度信息作为锚点，将焦点个体归因到高密度。我们测试了AlphaPlantImpute在不同情景下模拟双亲本种群中的imputation准确性。我们还将其准确性与现有的PlantImpute软件进行了比较。一般情况下，AlphaPlantImpute与PlantImpute具有更好或相同的imputation精度。与PlantImpute相比，AlphaPlantImpute的计算时间和内存需求很小。例如，如果父母双方都是近亲繁殖，每条染色体上有25000个标记进行基因分型，而一个f2个体每条染色体上有50个标记进行基因分型，则代入的准确性为0.96。此场景的最大内存需求为0.08 GB，需要37秒才能完成。
AbstractKey messageNew fast and accurate method for phasing and imputation of SNP chip genotypes within diploid bi-parental plant populations.AbstractThis paper presents a new heuristic method for phasing and imputation of genomic data in diploid plant species. Our method, called AlphaPlantImpute, explicitly leverages features of plant breeding programmes to maximise the accuracy of imputation. The features are a small number of parents, which can be inbred and usually have high-density genomic data, and few recombinations separating parents and focal individuals genotyped at low density (i.e. descendants that are the imputation targets). AlphaPlantImpute works roughly in three steps. First, it identifies informative low-density genotype markers in parents. Second, it tracks the inheritance of parental alleles and haplotypes to focal individuals at informative markers. Finally, it uses this low-density information as anchor points to impute focal individuals to high density. We tested the imputation accuracy of AlphaPlantImpute in simulated bi-parental populations across different scenarios. We also compared its accuracy to existing software called PlantImpute. In general, AlphaPlantImpute had better or equal imputation accuracy as PlantImpute. The computational time and memory requirements of AlphaPlantImpute were tiny compared to PlantImpute. For example, accuracy of imputation was 0.96 for a scenario where both parents were inbred and genotyped at 25,000 markers per chromosome and a focalF2individual was genotyped with 50 markers per chromosome. The maximum memory requirement for this scenario was 0.08 GB and took 37 s to complete.