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通过光学图谱验证水稻基因组序列。

Validation of rice genome sequence by optical mapping.

作者信息

Zhou Shiguo, Bechner Michael C, Place Michael, Churas Chris P, Pape Louise, Leong Sally A, Runnheim Rod, Forrest Dan K, Goldstein Steve, Livny Miron, Schwartz David C

机构信息

Laboratory for Molecular and Computational Genomics, University of Wisconsin-Madison, UW Biotechnology Centre, 425 Henry Mall, Madison, Wisconsin 53706, USA.

出版信息

BMC Genomics. 2007 Aug 15;8:278. doi: 10.1186/1471-2164-8-278.

Abstract

BACKGROUND

Rice feeds much of the world, and possesses the simplest genome analyzed to date within the grass family, making it an economically relevant model system for other cereal crops. Although the rice genome is sequenced, validation and gap closing efforts require purely independent means for accurate finishing of sequence build data.

RESULTS

To facilitate ongoing sequencing finishing and validation efforts, we have constructed a whole-genome SwaI optical restriction map of the rice genome. The physical map consists of 14 contigs, covering 12 chromosomes, with a total genome size of 382.17 Mb; this value is about 11% smaller than original estimates. 9 of the 14 optical map contigs are without gaps, covering chromosomes 1, 2, 3, 4, 5, 7, 8 10, and 12 in their entirety - including centromeres and telomeres. Alignments between optical and in silico restriction maps constructed from IRGSP (International Rice Genome Sequencing Project) and TIGR (The Institute for Genomic Research) genome sequence sources are comprehensive and informative, evidenced by map coverage across virtually all published gaps, discovery of new ones, and characterization of sequence misassemblies; all totalling ~14 Mb. Furthermore, since optical maps are ordered restriction maps, identified discordances are pinpointed on a reliable physical scaffold providing an independent resource for closure of gaps and rectification of misassemblies.

CONCLUSION

Analysis of sequence and optical mapping data effectively validates genome sequence assemblies constructed from large, repeat-rich genomes. Given this conclusion we envision new applications of such single molecule analysis that will merge advantages offered by high-resolution optical maps with inexpensive, but short sequence reads generated by emerging sequencing platforms. Lastly, map construction techniques presented here points the way to new types of comparative genome analysis that would focus on discernment of structural differences revealed by optical maps constructed from a broad range of rice subspecies and varieties.

摘要

背景

水稻养活了世界上许多人口,并且拥有禾本科植物中迄今为止分析过的最简单的基因组,这使其成为其他谷类作物具有经济意义的模式系统。尽管水稻基因组已被测序,但验证和填补缺口的工作需要完全独立的方法来精确完成序列构建数据。

结果

为了促进正在进行的测序完成和验证工作,我们构建了水稻基因组的全基因组SwaI光学限制酶切图谱。该物理图谱由14个重叠群组成,覆盖12条染色体,基因组总大小为382.17 Mb;这个值比原来的估计值小约11%。14个光学图谱重叠群中的9个没有缺口,完整覆盖了第1、2、3、4、5、7、8、10和12号染色体——包括着丝粒和端粒。从国际水稻基因组测序计划(IRGSP)和美国基因组研究所(TIGR)的基因组序列来源构建的光学图谱与电子限制酶切图谱之间的比对是全面且信息丰富的,几乎覆盖了所有已公布的缺口、发现了新的缺口以及对序列错误组装进行了表征,这些都证明了这一点;所有这些加起来约为14 Mb。此外,由于光学图谱是有序的限制酶切图谱,所识别的不一致性在可靠的物理支架上被精确指出,为填补缺口和纠正错误组装提供了独立的资源。

结论

对序列和光学图谱数据的分析有效地验证了由大型、富含重复序列的基因组构建而成 的基因组序列组装。基于这一结论我们设想了这种单分子分析的新应用,它将把高分辨率光学图谱的优势与新兴测序平台产生的廉价但短的序列读取相结合。最后,这里介绍的图谱构建技术为新型比较基因组分析指明了方向,这种分析将专注于识别由广泛的水稻亚种和品种构建的光学图谱所揭示的结构差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f217/2048515/f4db816c0d39/1471-2164-8-278-1.jpg

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