The patterns of population differentiation in a Brassica rapa core collection.
The patterns of population differentiation in a Brassica rapa core collection.
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DOI：
10.1007/s00122-010-1516-1
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发表时间：
2011-04
影响因子：
5.4
通讯作者：
Bonnema, Guusje
中科院分区：
文献类型：
--
作者：
Del Carpio, Dunia Pino;Basnet, Ram Kumar;De Vos, Ric C. H.;Maliepaard, Chris;Visser, Richard;Bonnema, Guusje
随着高通量图谱技术的最新进展，可用的遗传和表型数据量急剧增加。虽然许多遗传多样性研究结合了形态和遗传数据，但代谢物图谱尚未整合到这些研究中。在本研究中，我们选取了168份甘蓝型油菜不同形态类型和地理来源的材料。在移栽后5周，对该收集的所有植株最年轻的展开叶进行代谢物图谱分析，并使用相同的材料进行分子标记图谱分析。在一年后的同一季节，对苗期春化的植株进行了26个形态特征的测量。分子标记系统聚类后的类群数量和组成与基于形态性状的类群高度相关(r=0.420)，与代谢谱的类群高度相关(r=0.476)。为了揭示白菜型油菜的混合水平，需要与方案结构的结果进行比较，以获得种群亚结构的信息。为了分析5546个代谢物(LC-MS)信号，用结构识别的基团用于随机森林分类。当比较随机森林和结构成员概率时，86%的材料被分配到同一亚群。我们的发现表明，如果有大量的表型数据(代谢物)，基于这类数据的分类与遗传分类非常相似。这些多变量类型的数据和方法对于研究所选性状的遗传学和遗传改良计划的材料选择是有价值的，并另外提供了关于白菜不同形态类型进化的信息。本文的在线版本(doi：10.1007/s00122-0101516-1)包含补充材料，授权用户可以使用。
With the recent advances in high throughput profiling techniques the amount of genetic and phenotypic data available has increased dramatically. Although many genetic diversity studies combine morphological and genetic data, metabolite profiling has yet to be integrated into these studies. For our study we selected 168 accessions representing the different morphotypes and geographic origins of Brassica rapa. Metabolite profiling was performed on all plants of this collection in the youngest expanded leaves, 5 weeks after transplanting and the same material was used for molecular marker profiling. During the same season a year later, 26 morphological characteristics were measured on plants that had been vernalized in the seedling stage. The number of groups and composition following a hierarchical clustering with molecular markers was highly correlated to the groups based on morphological traits (r = 0.420) and metabolic profiles (r = 0.476). To reveal the admixture levels in B. rapa, comparison with the results of the programme STRUCTURE was needed to obtain information on population substructure. To analyze 5546 metabolite (LC–MS) signals the groups identified with STRUCTURE were used for random forests classification. When comparing the random forests and STRUCTURE membership probabilities 86% of the accessions were allocated into the same subgroup. Our findings indicate that if extensive phenotypic data (metabolites) are available, classification based on this type of data is very comparable to genetic classification. These multivariate types of data and methodological approaches are valuable for the selection of accessions to study the genetics of selected traits and for genetic improvement programs, and additionally provide information on the evolution of the different morphotypes in B. rapa. The online version of this article (doi:10.1007/s00122-010-1516-1) contains supplementary material, which is available to authorized users.
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