Johns Hopkins University, Baltimore, MD, USA.
University of Lausanne, Lausanne, CH, Switzerland.
Nat Commun. 2020 Mar 18;11(1):1432. doi: 10.1038/s41467-020-14998-3.
An important assessment prior to genome assembly and related analyses is genome profiling, where the k-mer frequencies within raw sequencing reads are analyzed to estimate major genome characteristics such as size, heterozygosity, and repetitiveness. Here we introduce GenomeScope 2.0 (https://github.com/tbenavi1/genomescope2.0), which applies combinatorial theory to establish a detailed mathematical model of how k-mer frequencies are distributed in heterozygous and polyploid genomes. We describe and evaluate a practical implementation of the polyploid-aware mixture model that quickly and accurately infers genome properties across thousands of simulated and several real datasets spanning a broad range of complexity. We also present a method called Smudgeplot (https://github.com/KamilSJaron/smudgeplot) to visualize and estimate the ploidy and genome structure of a genome by analyzing heterozygous k-mer pairs. We successfully apply the approach to systems of known variable ploidy levels in the Meloidogyne genus and the extreme case of octoploid Fragaria × ananassa.
在进行基因组组装和相关分析之前,一个重要的评估是基因组分析,其中对原始测序reads 中的 k-mer 频率进行分析,以估计主要的基因组特征,如大小、杂合性和重复性。在这里,我们介绍 GenomeScope 2.0(https://github.com/tbenavi1/genomescope2.0),它应用组合理论建立了一个详细的数学模型,说明 k-mer 频率在杂合和多倍体基因组中的分布情况。我们描述并评估了一种实用的多倍体混合模型实现,该模型可以快速准确地推断数千个模拟数据集和几个真实数据集的基因组特性,这些数据集涵盖了广泛的复杂性范围。我们还提出了一种名为 Smudgeplot(https://github.com/KamilSJaron/smudgeplot)的方法,通过分析杂合 k-mer 对来可视化和估计基因组的倍性和基因组结构。我们成功地将该方法应用于已知具有可变倍性水平的 Meloidogyne 属系统和极端的八倍体 Fragaria ×ananassa 中。