首页> 美国卫生研究院文献>DNA Research: An International Journal for Rapid Publication of Reports on Genes and Genomes >A High-Density Genetic Map with Array-Based Markers Facilitates Structural and Quantitative Trait Locus Analyses of the Common Wheat Genome
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A High-Density Genetic Map with Array-Based Markers Facilitates Structural and Quantitative Trait Locus Analyses of the Common Wheat Genome

机译:具有基于阵列的标记的高密度遗传图谱有助于普通小麦基因组的结构和定量性状基因座分析

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摘要

The large genome and allohexaploidy of common wheat have complicated construction of a high-density genetic map. Although improvements in the throughput of next-generation sequencing (NGS) technologies have made it possible to obtain a large amount of genotyping data for an entire mapping population by direct sequencing, including hexaploid wheat, a significant number of missing data points are often apparent due to the low coverage of sequencing. In the present study, a microarray-based polymorphism detection system was developed using NGS data obtained from complexity-reduced genomic DNA of two common wheat cultivars, Chinese Spring (CS) and Mironovskaya 808. After design and selection of polymorphic probes, 13,056 new markers were added to the linkage map of a recombinant inbred mapping population between CS and Mironovskaya 808. On average, 2.49 missing data points per marker were observed in the 201 recombinant inbred lines, with a maximum of 42. Around 40% of the new markers were derived from genic regions and 11% from repetitive regions. The low number of retroelements indicated that the new polymorphic markers were mainly derived from the less repetitive region of the wheat genome. Around 25% of the mapped sequences were useful for alignment with the physical map of barley. Quantitative trait locus (QTL) analyses of 14 agronomically important traits related to flowering, spikes, and seeds demonstrated that the new high-density map showed improved QTL detection, resolution, and accuracy over the original simple sequence repeat map.
机译:普通小麦的大基因组和异源六倍体具有复杂的高密度遗传图谱。尽管下一代测序(NGS)技术吞吐量的提高使得通过直接测序(包括六倍体小麦)获得了整个制图群体的大量基因分型数据成为可能,但由于明显的缺失,很多数据点经常很明显测序覆盖率低。在本研究中,使用NGS数据开发了基于微阵列的多态性检测系统,该数据是从两个普通小麦品种(中国春(CS)和Mironovskaya 808)的降低复杂性的基因组DNA获得的。设计和选择了多态性探针后,共13,056个新标记将其添加到CS和Mironovskaya 808之间的重组近交作图种群的连锁图中。在201个重组自交系中,平均每个标记缺失2.49个数据点,最多42个。大约40%的新标记为来自基因区,11%来自重复区。逆转录元素数量少表明新的多态性标记主要来自小麦基因组的重复性较低的区域。大约25%的映射序列可用于与大麦的物理图谱进行比对。定量性状基因座(QTL)对14个与开花,穗状花序和种子相关的重要农艺性状的分析表明,新的高密度图谱显示QTL的检测,分辨率和准确性均优于原始的简单序列重复图谱。

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