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利用表型差异和SSR标记评估芥菜型油菜(十字花科)基因型的遗传多样性

Assessment of genetic diversity in Brassica juncea (Brassicaceae) genotypes using phenotypic differences and SSR markers.

作者信息

Vinu V, Singh Naveen, Vasudev Sujata, Yadava Devendra Kumar, Kumar Sushil, Naresh Sugandh, Bhat Sripad Ramachandra, Prabhu Kumble Vinod

机构信息

Division of Genetics, Indian Agricultural Research Institute, New Delhi.

NRC on Plant Biotechnology, IARI Campus, New Delhi.

出版信息

Rev Biol Trop. 2013 Dec;61(4):1919-34.

Abstract

Brassica mustard species represent one of the most important oilseed crops in India, nevertheless, their genetic diversity is barely known. A better understanding on this topic is essential for the proper utilization of genotypes in breeding programmes. We evaluated the genetic diversity among 44 Indian mustard (Brassica juncea) genotypes including varieties/purelines from different agro-climatic zones of India and few exotic genotypes (Australia, Poland and China). For this, we used A and B genome specific SSR markers and phenotypic data on 12 yield and yield contributing traits. Out of the 143 primers tested, 134 reported polymorphism and a total of 355 alleles were amplified. Dendrograms based on Jaccard's similarity coefficients and Manhattan dissimilarity coefficients were generated based on an average linkage algorithm (UPGMA) using marker data and phenotypic data. Genotypes were grouped into four clusters based on genetic distances. Both the clustering patterns based on Jaccard's similarity and Manhattan dissimilarity coefficients, independently, discriminated the genotypes effectively as per their pedigree and origin. PCoA revealed that, the grouping of genotypes based on SSR marker data is more convincing than phenotypic data, however, the correlation between phenotypic and genetic distance matrices was observed to be very low (r = 0.11). Hence, for diversity studies reliability on molecular markers is worth proving and SSR markers are the stronger tools than quantitative traits in discriminating B. juncea genotypes.

摘要

芥菜型油菜是印度最重要的油料作物之一,然而,其遗传多样性却鲜为人知。更好地了解这一主题对于在育种计划中合理利用基因型至关重要。我们评估了44个印度芥菜(Brassica juncea)基因型的遗传多样性,这些基因型包括来自印度不同农业气候区的品种/纯系以及少数外来基因型(澳大利亚、波兰和中国)。为此,我们使用了A和B基因组特异性SSR标记以及关于12个产量和产量构成性状的表型数据。在测试的143对引物中,134对表现出多态性,共扩增出355个等位基因。基于标记数据和表型数据,使用平均连锁算法(UPGMA),基于杰卡德相似系数和曼哈顿相异系数生成了聚类图。根据遗传距离,基因型被分为四个聚类。基于杰卡德相似系数和曼哈顿相异系数的聚类模式分别根据基因型的系谱和起源有效地对其进行了区分。主坐标分析显示,基于SSR标记数据对基因型进行分组比基于表型数据更有说服力,然而,观察到表型和遗传距离矩阵之间的相关性非常低(r = 0.11)。因此,对于多样性研究,分子标记的可靠性值得验证,并且在区分芥菜型油菜基因型方面,SSR标记比数量性状是更强有力的工具。

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