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植物基因组测序项目技术的关键比较

A critical comparison of technologies for a plant genome sequencing project.

作者信息

Paajanen Pirita, Kettleborough George, López-Girona Elena, Giolai Michael, Heavens Darren, Baker David, Lister Ashleigh, Cugliandolo Fiorella, Wilde Gail, Hein Ingo, Macaulay Iain, Bryan Glenn J, Clark Matthew D

机构信息

Technology Development, Earlham Institute, Norwich Research Park, Norwich NR4 7UZ, UK.

Department of Cell and Developmental Biology, John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK.

出版信息

Gigascience. 2019 Mar 1;8(3). doi: 10.1093/gigascience/giy163.

Abstract

BACKGROUND

A high-quality genome sequence of any model organism is an essential starting point for genetic and other studies. Older clone-based methods are slow and expensive, whereas faster, cheaper short-read-only assemblies can be incomplete and highly fragmented, which minimizes their usefulness. The last few years have seen the introduction of many new technologies for genome assembly. These new technologies and associated new algorithms are typically benchmarked on microbial genomes or, if they scale appropriately, on larger (e.g., human) genomes. However, plant genomes can be much more repetitive and larger than the human genome, and plant biochemistry often makes obtaining high-quality DNA that is free from contaminants difficult. Reflecting their challenging nature, we observe that plant genome assembly statistics are typically poorer than for vertebrates.

RESULTS

Here, we compare Illumina short read, Pacific Biosciences long read, 10x Genomics linked reads, Dovetail Hi-C, and BioNano Genomics optical maps, singly and combined, in producing high-quality long-range genome assemblies of the potato species Solanum verrucosum. We benchmark the assemblies for completeness and accuracy, as well as DNA compute requirements and sequencing costs.

CONCLUSIONS

The field of genome sequencing and assembly is reaching maturity, and the differences we observe between assemblies are surprisingly small. We expect that our results will be helpful to other genome projects, and that these datasets will be used in benchmarking by assembly algorithm developers.

摘要

背景

任何模式生物的高质量基因组序列都是遗传研究及其他研究的重要起点。基于克隆的传统方法速度慢且成本高,而更快、更便宜的仅使用短读长的组装方法可能不完整且高度碎片化,这使其实用性大打折扣。在过去几年中,出现了许多用于基因组组装的新技术。这些新技术及相关新算法通常在微生物基因组上进行基准测试,或者如果它们能够适当扩展,则在更大的(例如人类)基因组上进行测试。然而,植物基因组可能比人类基因组更具重复性且更大,并且植物生物化学特性常常使得获取无污染的高质量DNA变得困难。鉴于其具有挑战性的特性,我们观察到植物基因组组装统计数据通常比脊椎动物的要差。

结果

在此,我们比较了Illumina短读长、太平洋生物科学公司的长读长、10x Genomics连接读长、Dovetail Hi-C和BioNano Genomics光学图谱,单独使用以及组合使用时,在生成马铃薯物种疣粒野生种的高质量长程基因组组装方面的效果。我们对组装的完整性、准确性以及DNA计算需求和测序成本进行了基准测试。

结论

基因组测序和组装领域正在走向成熟,我们观察到的不同组装方法之间的差异小得出奇。我们预计我们的结果将对其他基因组项目有所帮助,并且这些数据集将被组装算法开发者用于基准测试。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a97b/6423373/9a5c614a1488/giy163fig1.jpg

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