High-density SNP-based genetic map development and linkage disequilibrium assessment in Brassica napus L.
High-density SNP-based genetic map development and linkage disequilibrium assessment in Brassica napus L.
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DOI:
10.1186/1471-2164-14-120
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发表时间:
2013-02-22
期刊:
影响因子:
4.4
通讯作者:
Pauquet J
中科院分区:
文献类型:
--
作者:
Delourme R;Falentin C;Fomeju BF;Boillot M;Lassalle G;André I;Duarte J;Gauthier V;Lucante N;Marty A;Pauchon M;Pichon JP;Ribière N;Trotoux G;Blanchard P;Rivière N;Martinant JP;Pauquet J
High density genetic maps built with SNP markers that are polymorphic in various genetic backgrounds are very useful for studying the genetics of agronomical traits as well as genome organization and evolution. Simultaneous dense SNP genotyping of segregating populations and variety collections was applied to oilseed rape (Brassica napus L.) to obtain a high density genetic map for this species and to study the linkage disequilibrium pattern. We developed an integrated genetic map for oilseed rape by high throughput SNP genotyping of four segregating doubled haploid populations. A very high level of collinearity was observed between the four individual maps and a large number of markers (>59%) was common to more than two maps. The precise integrated map comprises 5764 SNP and 1603 PCR markers. With a total genetic length of 2250 cM, the integrated map contains a density of 3.27 markers (2.56 SNP) per cM. Genotyping of these mapped SNP markers in oilseed rape collections allowed polymorphism level and linkage disequilibrium (LD) to be studied across the different collections (winter vs spring, different seed quality types) and along the linkage groups. Overall, polymorphism level was higher and LD decayed faster in spring than in “00” winter oilseed rape types but this was shown to vary greatly along the linkage groups. Our study provides a valuable resource for further genetic studies using linkage or association mapping, for marker assisted breeding and for Brassica napus sequence assembly and genome organization analyses.
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影响因子:
2.9
作者:
Ching A;Caldwell KS;Jung M;Dolan M;Smith OS;Tingey S;Morgante M;Rafalski AJ
通讯作者:
Rafalski AJ
影响因子:
5.4
作者:
Bus, Anja;Koerber, Niklas;Stich, Benjamin
通讯作者:
Stich, Benjamin
影响因子:
4.5
作者:
Famoso AN;Zhao K;Clark RT;Tung CW;Wright MH;Bustamante C;Kochian LV;McCouch SR
通讯作者:
McCouch SR
影响因子:
3.1
作者:
Durstewitz, G.;Polley, A.;Ganal, M. W.
通讯作者:
Ganal, M. W.
影响因子:
2.6
作者:
Excoffier, Laurent;Laval, Guillaume;Schneider, Stefan
通讯作者:
Schneider, Stefan