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BAC-End Sequence-Based SNP Mining in Allotetraploid Cotton (Gossypium) Utilizing Resequencing Data Phylogenetic Inferences and Perspectives for Genetic Mapping

机译:利用重测序数据系统发育推断和基因定位的观点在异源四倍体棉(棉)中基于BAC末端序列的SNP采矿

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摘要

A bacterial artificial chromosome library and BAC-end sequences for cultivated cotton (Gossypium hirsutum L.) have recently been developed. This report presents genome-wide single nucleotide polymorphism (SNP) mining utilizing resequencing data with BAC-end sequences as a reference by alignment of 12 G. hirsutum L. lines, one G. barbadense L. line, and one G. longicalyx Hutch and Lee line. A total of 132,262 intraspecific SNPs have been developed for G. hirsutum, whereas 223,138 and 470,631 interspecific SNPs have been developed for G. barbadense and G. longicalyx, respectively. Using a set of interspecific SNPs, 11 randomly selected and 77 SNPs that are putatively associated with the homeologous chromosome pair 12 and 26, we mapped 77 SNPs into two linkage groups representing these chromosomes, spanning a total of 236.2 cM in an interspecific F2 population (G. barbadense 3-79 × G. hirsutum TM-1). The mapping results validated the approach for reliably producing large numbers of both intraspecific and interspecific SNPs aligned to BAC-ends. This will allow for future construction of high-density integrated physical and genetic maps for cotton and other complex polyploid genomes. The methods developed will allow for future Gossypium resequencing data to be automatically genotyped for identified SNPs along the BAC-end sequence reference for anchoring sequence assemblies and comparative studies.
机译:最近已经开发了用于栽培棉花(陆地棉)的细菌人工染色体文库和BAC末端序列。本报告介绍了利用BAC末端序列的重测序数据作为参考的全基因组单核苷酸多态性(SNP)挖掘,方法是将12 G.hirsutum L.品系,一条G.barbadense L.品系和一条G.longicalyx Hutch和李行。已为hirsutum开发了总共132,262种种内SNP,而分别为Barbadense和G. longicalyx开发了223,138和470,631种间SNP。使用一组种间SNP,随机选择的11个SNP和与同源染色体对12和26关联的77个SNP,我们将77个SNP映射到代表这些染色体的两个连锁组中,跨种F2群体的总跨度为236.2 cM(巴巴木霉3-79×陆地棉TM-1)。映射结果验证了该方法可可靠地产生大量与BAC末端对齐的种内和种间SNP。这将为将来构建棉花和其他复杂多倍体基因组的高密度综合物理图谱和遗传图谱提供条件。所开发的方法将使未来的棉花重测序数据能够根据BAC末端序列参考自动进行基因分型,以识别SNP,从而锚定序列装配和比较研究。

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