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基于牛津纳米孔测序reads 比对的插入缺失检测在作物基因组中的基准测试。

Benchmarking Oxford Nanopore read alignment-based insertion and deletion detection in crop plant genomes.

机构信息

Department of Plant Breeding, Justus Liebig University Giessen, Giessen, Germany.

出版信息

Plant Genome. 2023 Jun;16(2):e20314. doi: 10.1002/tpg2.20314. Epub 2023 Mar 29.

Abstract

Structural variations (SVs) are larger polymorphisms (> 50 bp in length), which consist of insertions, deletions, inversions, duplications, and translocations. They can have a strong impact on agronomical traits and play an important role in environmental adaptation. The development of long-read sequencing technologies, including Oxford Nanopore, allows for comprehensive SV discovery and characterization even in complex polyploid crop genomes. However, many of the SV discovery pipeline benchmarks do not include complex plant genome datasets. In this study, we benchmarked insertion and deletion detection by popular long-read alignment-based SV detection tools for crop plant genomes. We used real and simulated Oxford Nanopore reads for two crops, allotetraploid Brassica napus (oilseed rape) and diploid Solanum lycopersicum (tomato), and evaluated several read aligners and SV callers across 5×, 10×, and 20× coverages typically used in re-sequencing studies. We further validated our findings using maize and soybean datasets. Our benchmarks provide a useful guide for designing Oxford Nanopore re-sequencing projects and SV discovery pipelines for crop plants.

摘要

结构变异(SVs)是较大的多态性(长度> 50bp),包括插入、缺失、倒位、重复和易位。它们对农艺性状有很大的影响,并在环境适应中发挥重要作用。长读测序技术(包括 Oxford Nanopore)的发展使得即使在复杂的多倍体作物基因组中也能全面发现和描述 SV。然而,许多 SV 发现管道的基准测试不包括复杂的植物基因组数据集。在这项研究中,我们针对作物植物基因组,对流行的基于长读序列比对的 SV 检测工具的插入和缺失检测进行了基准测试。我们使用真实和模拟的 Oxford Nanopore 读取数据,对两种作物(异源四倍体 Brassica napus(油菜)和二倍体 Solanum lycopersicum(番茄))进行了评估,并在通常用于重测序研究的 5×、10×和 20×覆盖范围内评估了几种读序列比对器和 SV 调用器。我们进一步使用玉米和大豆数据集验证了我们的发现。我们的基准测试为设计作物植物的 Oxford Nanopore 重测序项目和 SV 发现管道提供了有用的指导。

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