Genetic diversity and population structure analysis of bambara groundnuts (Vigna subterranea (L.) Verdc.) landraces using morpho-agronomic characters and SSR markers
Genetic diversity and population structure analysis of bambara groundnuts (Vigna subterranea (L.) Verdc.) landraces using morpho-agronomic characters and SSR markers
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利用形态农艺性状和 SSR 标记对班巴拉花生 (Vigna subterranea (L.) Verdc.) 地方品种进行遗传多样性和群体结构分析
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发表时间：
2012
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通讯作者：
O. Molosiwa
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作者：
O. Molosiwa
班巴拉花生是一种主要生长在撒哈拉以南非洲的非洲本土豆类;它是大多数农村人口的重要蛋白质来源。没有成熟的品种，自给农民种植适应当地情况的地方品种，这些品种一般产量低。班巴拉花生是一种主要的自花授粉作物，预计将存在不同的自交系，虽然以前缺乏共显性标记，阻止了正式评估的杂合性内班巴拉花生基因型。
一组共75个微卫星，其特征在于在这项研究中被用来调查一组24个班巴拉花生地方品种的遗传多样性，提供多态性标记的评价，并提供与DArT标记数据，以前分析的链接。
筛选出68个具有一致性和重复性的微卫星标记，并将其应用于班巴拉花生的遗传变异研究，比较分子标记和形态标记的应用，以及SSR标记在纯系选择中的应用。
在英国诺丁汉大学萨顿博宁顿校区的温室实验和在博茨瓦纳农业学院（Notwane农场）的田间实验中，采用随机区组设计，重复三次，对两个季节的班巴拉花生的遗传多样性进行了评估。地方品种的特点是24个数量和13个质量性状。结果表明，数量性状的变异较大，而大多数性状的形态差异也很大。采用主成分分析、聚类分析和遗传力估计等方法进行多变量分析。形态学特征的低成本、简单性和农业相关性使其成为种质遗传变异研究的重要工具。
利用20个微卫星标记对来自田间试验的34个株系进行了遗传多样性分析。期望杂合度（He）平均为1，这与班巴拉花生主要是自花授粉的事实相一致。聚类分析和主成分分析（PCoA）主要根据它们的原产地对地方品种进行分组。
通过对班巴拉花生遗传变异和形态变异的分子生物学分析，探讨了两种评价技术之间的关系。这种比较将有助于育种者做出明智的决定，即哪种方法最适合用于种质鉴定和植物育种，以及如何最好地将这些知识应用于实际情况。然后，DNA标记可以帮助选择用于育种的种质，育种计划中的质量控制，并可能通过标记辅助选择（MAS）进行直接选择。形态学数据的欧氏距离估计值和SSR数据的遗传距离估计值（Nei's 1972）在农艺学室和控制生长室中强相关（r = 0.7; P < 0.001）（r = 0.6; P< 0.001）。这些结果表明，这两种方法产生了相同的遗传多样性模式，因此可以作为彼此的替代品。
Bambara groundnut is an indigenous African legume grown mainly in sub-Saharan Africa; it is an important source of protein to the rural majority. There are no established varieties and subsistence farmers grow locally adapted landraces which are generally low yielding. Bambara groundnut is a predominantly self-pollinating crop and is expected to exist as non-identical inbred lines, although the previous lack of co-dominant markers has prevented a formal assessment of heterozygosity within bambara groundnut genotypes.
A total set of 75 microsatellites that were characterised in this study were used to investigate the genetic diversity of a set of 24 bambara groundnut landraces, to provide an evaluation of the markers for polymorphism and provide a link with DArT marker data that were previously analysed.
Sixty eight microsatellites were identified that were found to be consistent and reproducible, from which a set of markers were selected and used for genetic variability studies of bambara groundnut, to compare the use of molecular markers with morphological markers, and to investigate using SSR markers in pure line selection.
The genetic diversity of bambara groundnut was assessed based on morphological characters for two seasons; in a glasshouse experiment at the University of Nottingham, Sutton Bonington Campus, UK and in a field experiment that was conducted at the Botswana College of Agriculture (Notwane farm), Gaborone in a randomised block design with three replicates. The landraces were characterised for 24 quantitative and 13 qualitative characters. The results indicated considerable variation for quantitative characters, while significant morphological differences were also recorded for most characters. Multivariate data analysis was conducted using principal component analysis, cluster analysis and heritability estimates were developed. The low cost, simplicity and agricultural relevance of morphological characterisation makes it an important tool in germplasm genetic variation studies.
Thirty four lines from field experiments were investigated for genetic diversity based on 20 microsatellites. The expected heterozygosity (He) had an average of 1 in agreement with the fact that bambara groundnut is predominantly self-pollinating. Both cluster analysis and principle component analysis (PCoA) grouped landraces based mainly on their areas of origin.
A thorough molecular analysis of genetic and morphological variation in bambara groundnut was conducted to investigate the relationship between the two assessment techniques. This comparison will assist in breeders making informed decisions as to which approach is best to use in germplasm characterisation and plant breeding and how best to apply such knowledge in practical situations. DNA markers could then aid with the selection of germplasm for breeding, quality control within breeding programmes and, potentially, direct selection via Marker Assisted Selection (MAS). Euclidean distance estimates for morphological data and (Nei’s 1972) genetic distance estimates for SSR data were strongly correlated (r = 0.7; P < 0.001) in the agronomy bay and (r = 0.6; P< 0.001) in the controlled growth room. These results suggest the two approaches are generating the same pattern of genetic diversity, and as such can be used as a surrogate for each other.