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利用缺失-bin 来锚定和排序小麦 7B 染色体上的序列。

Utilization of deletion bins to anchor and order sequences along the wheat 7B chromosome.

机构信息

Department of Plant Sciences, Norwegian University of Life Sciences, Ås, Norway,

出版信息

Theor Appl Genet. 2014 Sep;127(9):2029-40. doi: 10.1007/s00122-014-2358-z. Epub 2014 Aug 19.

Abstract

A total of 3,671 sequence contigs and scaffolds were mapped to deletion bins on wheat chromosome 7B providing a foundation for developing high-resolution integrated physical map for this chromosome. Bread wheat (Triticum aestivum L.) has a large, complex and highly repetitive genome which is challenging to assemble into high quality pseudo-chromosomes. As part of the international effort to sequence the hexaploid bread wheat genome by the international wheat genome sequencing consortium (IWGSC) we are focused on assembling a reference sequence for chromosome 7B. The successful completion of the reference chromosome sequence is highly dependent on the integration of genetic and physical maps. To aid the integration of these two types of maps, we have constructed a high-density deletion bin map of chromosome 7B. Using the 270 K Nimblegen comparative genomic hybridization (CGH) array on a set of cv. Chinese spring deletion lines, a total of 3,671 sequence contigs and scaffolds (~7.8 % of chromosome 7B physical length) were mapped into nine deletion bins. Our method of genotyping deletions on chromosome 7B relied on a model-based clustering algorithm (Mclust) to accurately predict the presence or absence of a given genomic sequence in a deletion line. The bin mapping results were validated using three different approaches, viz. (a) PCR-based amplification of randomly selected bin mapped sequences (b) comparison with previously mapped ESTs and (c) comparison with a 7B genetic map developed in the present study. Validation of the bin mapping results suggested a high accuracy of the assignment of 7B sequence contigs and scaffolds to the 7B deletion bins.

摘要

总共将 3671 个序列连段和支架映射到小麦 7B 号染色体的缺失-bin 上,为该染色体开发高分辨率的整合物理图谱奠定了基础。栽培小麦(Triticum aestivum L.)基因组庞大、复杂且高度重复,难以组装成高质量的拟染色体。作为国际小麦基因组测序联盟(IWGSC)测序六倍体栽培小麦基因组的国际努力的一部分,我们专注于组装 7B 号染色体的参考序列。参考染色体序列的成功完成高度依赖于遗传和物理图谱的整合。为了帮助整合这两种类型的图谱,我们构建了 7B 号染色体的高密度缺失-bin 图谱。使用 270K Nimblegen 比较基因组杂交(CGH)阵列对一组 cv.中国春缺失系进行分析,总共将 3671 个序列连段和支架(约 7.8%的 7B 号染色体物理长度)映射到九个缺失-bin 中。我们在 7B 号染色体上进行缺失基因型分析的方法依赖于基于模型的聚类算法(Mclust),以准确预测缺失系中给定基因组序列的存在或缺失。通过三种不同的方法验证 bin 映射结果,即:(a)随机选择的映射 bin 序列的基于 PCR 的扩增;(b)与先前映射的 EST 进行比较;(c)与本研究中开发的 7B 遗传图谱进行比较。bin 映射结果的验证表明,7B 序列连段和支架分配给 7B 缺失-bin 的准确性很高。

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