首页> 美国卫生研究院文献>other >Construction of High Density Sweet Cherry (Prunus avium L.) Linkage Maps Using Microsatellite Markers and SNPs Detected by Genotyping-by-Sequencing (GBS)
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Construction of High Density Sweet Cherry (Prunus avium L.) Linkage Maps Using Microsatellite Markers and SNPs Detected by Genotyping-by-Sequencing (GBS)

机译:利用微卫星标记和SNPs通过基因分型测序(GBS)检测高密度甜樱桃(李属)连锁图的构建。

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摘要

Linkage maps are valuable tools in genetic and genomic studies. For sweet cherry, linkage maps have been constructed using mainly microsatellite markers (SSRs) and, recently, using single nucleotide polymorphism markers (SNPs) from a cherry 6K SNP array. Genotyping-by-sequencing (GBS), a new methodology based on high-throughput sequencing, holds great promise for identification of high number of SNPs and construction of high density linkage maps. In this study, GBS was used to identify SNPs from an intra-specific sweet cherry cross. A total of 8,476 high quality SNPs were selected for mapping. The physical position for each SNP was determined using the peach genome, Peach v1.0, as reference, and a homogeneous distribution of markers along the eight peach scaffolds was obtained. On average, 65.6% of the SNPs were present in genic regions and 49.8% were located in exonic regions. In addition to the SNPs, a group of SSRs was also used for construction of linkage maps. Parental and consensus high density maps were constructed by genotyping 166 siblings from a ‘Rainier’ x ‘Rivedel’ (Ra x Ri) cross. Using Ra x Ri population, 462, 489 and 985 markers were mapped into eight linkage groups in ‘Rainier’, ‘Rivedel’ and the Ra x Ri map, respectively, with 80% of mapped SNPs located in genic regions. Obtained maps spanned 549.5, 582.6 and 731.3 cM for ‘Rainier’, ‘Rivedel’ and consensus maps, respectively, with an average distance of 1.2 cM between adjacent markers for both ‘Rainier’ and ‘Rivedel’ maps and of 0.7 cM for Ra x Ri map. High synteny and co-linearity was observed between obtained maps and with Peach v1.0. These new high density linkage maps provide valuable information on the sweet cherry genome, and serve as the basis for identification of QTLs and genes relevant for the breeding of the species.
机译:连锁图谱是遗传和基因组研究中的宝贵工具。对于甜樱桃,已经使用主要的微卫星标记(SSR)以及最近使用来自樱桃6K SNP阵列的单核苷酸多态性标记(SNP)构建了连锁图。测序基因分型法(GBS)是一种基于高通量测序的新方法,对于鉴定大量SNP和构建高密度连锁图谱具有广阔的前景。在这项研究中,GBS被用于从种内甜樱桃杂交中鉴定SNP。总共选择了8,476个高质量SNP用于作图。使用桃子基因组Peach v1.0作为参考来确定每个SNP的物理位置,并获得沿八个桃子支架的标记物均匀分布。平均而言,有65.6%的SNP存在于基因区,有49.8%位于外显子区。除了SNP之外,还使用一组SSR来构建链接图。通过对“ Rainier” x“ Rivedel”(Ra x Ri)十字架的166个同胞进行基因分型,构建了父母和共识高密度地图。使用Ra x Ri种群,将462、489和985标记分别映射到“ Rainier”,“ Rivedel”和Ra x Ri图的八个连锁组中,其中80%的SNP位于基因区。对于“ Rainier”,“ Rivedel”和“共有”图,获得的图分别跨越549.5、582.6和731.3 cM,“ Rainier”和“ Rivedel”图的相邻标记之间的平均距离为1.2 cM,对于Ra x为0.7 cM。里图。在获得的地图之间以及使用Peach v1.0时,观察到了很高的连续性和共线性。这些新的高密度连锁图谱提供了有关甜樱桃基因组的有价值的信息,并为鉴定与该物种育种相关的QTL和基因奠定了基础。

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