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首页> 外文期刊>BMC Genomics >Whole Genome Profiling provides a robust framework for physical mapping and sequencing in the highly complex and repetitive wheat genome
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Whole Genome Profiling provides a robust framework for physical mapping and sequencing in the highly complex and repetitive wheat genome

机译:全基因组分析为高度复杂和重复的小麦基因组中的物理作图和测序提供了一个强大的框架

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Background Sequencing projects using a clone-by-clone approach require the availability of a robust physical map. The SNaPshot technology, based on pair-wise comparisons of restriction fragments sizes, has been used recently to build the first physical map of a wheat chromosome and to complete the maize physical map. However, restriction fragments sizes shared randomly between two non-overlapping BACs often lead to chimerical contigs and mis-assembled BACs in such large and repetitive genomes. Whole Genome Profiling (WGP?) was developed recently as a new sequence-based physical mapping technology and has the potential to limit this problem. Results A subset of the wheat 3B chromosome BAC library covering 230 Mb was used to establish a WGP physical map and to compare it to a map obtained with the SNaPshot technology. We first adapted the WGP-based assembly methodology to cope with the complexity of the wheat genome. Then, the results showed that the WGP map covers the same length than the SNaPshot map but with 30% less contigs and, more importantly with 3.5 times less mis-assembled BACs. Finally, we evaluated the benefit of integrating WGP tags in different sequence assemblies obtained after Roche/454 sequencing of BAC pools. We showed that while WGP tag integration improves assemblies performed with unpaired reads and with paired-end reads at low coverage, it does not significantly improve sequence assemblies performed at high coverage (25x) with paired-end reads. Conclusions Our results demonstrate that, with a suitable assembly methodology, WGP builds more robust physical maps than the SNaPshot technology in wheat and that WGP can be adapted to any genome. Moreover, WGP tag integration in sequence assemblies improves low quality assembly. However, to achieve a high quality draft sequence assembly, a sequencing depth of 25x paired-end reads is required, at which point WGP tag integration does not provide additional scaffolding value. Finally, we suggest that WGP tags can support the efficient sequencing of BAC pools by enabling reliable assignment of sequence scaffolds to their BAC of origin, a feature that is of great interest when using BAC pooling strategies to reduce the cost of sequencing large genomes.
机译:使用逐个克隆方法进行的后台测序项目需要强大的物理映射。 SNaPshot技术基于限制性片段大小的成对比较,最近已用于构建小麦染色体的第一个物理图谱并完成玉米的物理图谱。但是,在两个不重叠的BAC之间随机共享的限制性片段大小通常会导致嵌合体重叠群和此类大而重复的基因组中BAC组装错误。全基因组分析(WGP?)最近作为一种新的基于序列的物理作图技术而开发,并有可能限制这一问题。结果使用覆盖230 Mb的小麦3B染色体BAC库的子集来建立WGP物理图谱,并将其与SNaPshot技术获得的图谱进行比较。我们首先调整了基于WGP的装配方法,以应对小麦基因组的复杂性。然后,结果表明WGP映射的覆盖范围与SNaPshot映射的覆盖范围相同,但重叠群减少了30%,更重要的是错误组装的BAC减少了3.5倍。最后,我们评估了将WGP标签整合到BAC库的Roche / 454测序后获得的不同序列组件中的好处。我们显示,虽然WGP标签集成可以改善未配对读取和低覆盖范围内的成对末端读段的装配,但它并不能显着改善高覆盖范围(25x)下具有配对末端读段的序列装配。结论我们的结果表明,与小麦中的SNaPshot技术相比,使用合适的组装方法,WGP可以构建比SNaPshot技术更强大的物理图谱,并且WGP可以适应任何基因组。此外,WGP标签在序列装配中的集成改善了低质量的装配。但是,要实现高质量的草稿序列装配,需要25倍配对末端读取的测序深度,此时WGP标签集成不能提供额外的支架价值。最后,我们建议WGP标签可以通过将序列支架可靠地分配给其起源的BAC来支持BAC池的有效测序,当使用BAC合并策略降低大型基因组测序的成本时,这一功能将引起人们的极大兴趣。

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