An integrated SSR map of grapevine based on five mapping populations
An integrated SSR map of grapevine based on five mapping populations
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DOI：
10.1007/s00122-006-0295-1
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发表时间：
2006-08-01
影响因子：
5.4
通讯作者：
Di Gaspero, G.
中科院分区：
文献类型：
--
作者：
Doligez, A.;Adam-Blondon, A. F.;Di Gaspero, G.
葡萄藤（主要是葡萄属葡萄属L.，2n = 38）使用CarthaGene利用46、95、114、139和153个个体的5个全同胞群体的分离数据构建复合遗传图谱，以确定大量分子标记的相对位置。该图谱共包含515个位点（502个SSR和13个其他类型的PCR标记），使用439对引物（426个SSR和13个其他类型的PCR标记）扩增，其中50.1%的标记至少为两个杂交组合所共有。其中257个、85个、74个、69个和30个位点分别定位在1、2、3、4和5个作图群体中。标记顺序一般是很好的保守的个别群体之间的地图，只有少数显着差异，在两个或两个以上的人口之间的标记对的重组率。整合图谱的总长度为1，647 cM Kosambi，覆盖19个连锁群，相邻位点之间的平均距离为3.3 cM。还建立了一个框架集成的地图，标记顺序支持LOD为2.0。它包括257个位点，跨越1，485 cM Kosambi，平均位点间距离为6.2 cM，超过19个连锁群。这些整合的图谱是迄今为止在葡萄藤中可用的最全面的基于SSR的图谱，并且将用于选择均匀分散在整个基因组上的标记或用于选择覆盖特定感兴趣区域的标记。框架图也是整合葡萄物理和遗传图谱的有用起点。
A grapevine (mainly Vitis vinifera L., 2n = 38) composite genetic map was constructed with CarthaGene using segregation data from five full-sib populations of 46, 95, 114, 139 and 153 individuals, to determine the relative position of a large set of molecular markers. This consensus map comprised 515 loci (502 SSRs and 13 other type PCR-based markers), amplified using 439 primer pairs (426 SSRs and 13 others) with 50.1% common markers shared by at least two crosses. Out of all loci, 257, 85, 74, 69 and 30 were mapped in 1, 2, 3, 4 and 5 individual mapping populations, respectively. Marker order was generally well conserved between maps of individual populations, with only a few significant differences in the recombination rate of marker pairs between two or more populations. The total length of the integrated map was 1,647 cM Kosambi covering 19 linkage groups, with a mean distance between neighbour loci of 3.3 cM. A framework-integrated map was also built, with marker order supported by a LOD of 2.0. It included 257 loci spanning 1,485 cM Kosambi with a mean inter-locus distance of 6.2 cM over 19 linkage groups. These integrated maps are the most comprehensive SSR-based maps available so far in grapevine and will serve either for choosing markers evenly scattered over the whole genome or for selecting markers that cover particular regions of interest. The framework map is also a useful starting point for the integration of the V. vinifera physical and genetic maps.